Deprecated (16384): The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 73 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php. [CORE/src/Core/functions.php, line 311]Code Context
trigger_error($message, E_USER_DEPRECATED);
}
$message = 'The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 73 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php.' $stackFrame = (int) 1 $trace = [ (int) 0 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ServerRequest.php', 'line' => (int) 2421, 'function' => 'deprecationWarning', 'args' => [ (int) 0 => 'The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead.' ] ], (int) 1 => [ 'file' => '/home/brlfuser/public_html/src/Controller/ArtileDetailController.php', 'line' => (int) 73, 'function' => 'offsetGet', 'class' => 'Cake\Http\ServerRequest', 'object' => object(Cake\Http\ServerRequest) {}, 'type' => '->', 'args' => [ (int) 0 => 'catslug' ] ], (int) 2 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Controller/Controller.php', 'line' => (int) 610, 'function' => 'printArticle', 'class' => 'App\Controller\ArtileDetailController', 'object' => object(App\Controller\ArtileDetailController) {}, 'type' => '->', 'args' => [] ], (int) 3 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ActionDispatcher.php', 'line' => (int) 120, 'function' => 'invokeAction', 'class' => 'Cake\Controller\Controller', 'object' => object(App\Controller\ArtileDetailController) {}, 'type' => '->', 'args' => [] ], (int) 4 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ActionDispatcher.php', 'line' => (int) 94, 'function' => '_invoke', 'class' => 'Cake\Http\ActionDispatcher', 'object' => object(Cake\Http\ActionDispatcher) {}, 'type' => '->', 'args' => [ (int) 0 => object(App\Controller\ArtileDetailController) {} ] ], (int) 5 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/BaseApplication.php', 'line' => (int) 235, 'function' => 'dispatch', 'class' => 'Cake\Http\ActionDispatcher', 'object' => object(Cake\Http\ActionDispatcher) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 6 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Http\BaseApplication', 'object' => object(App\Application) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 7 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Routing/Middleware/RoutingMiddleware.php', 'line' => (int) 162, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 8 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Routing\Middleware\RoutingMiddleware', 'object' => object(Cake\Routing\Middleware\RoutingMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 9 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Routing/Middleware/AssetMiddleware.php', 'line' => (int) 88, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 10 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Routing\Middleware\AssetMiddleware', 'object' => object(Cake\Routing\Middleware\AssetMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 11 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Middleware/ErrorHandlerMiddleware.php', 'line' => (int) 96, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 12 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Error\Middleware\ErrorHandlerMiddleware', 'object' => object(Cake\Error\Middleware\ErrorHandlerMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 13 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 51, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 14 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Server.php', 'line' => (int) 98, 'function' => 'run', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\MiddlewareQueue) {}, (int) 1 => object(Cake\Http\ServerRequest) {}, (int) 2 => object(Cake\Http\Response) {} ] ], (int) 15 => [ 'file' => '/home/brlfuser/public_html/webroot/index.php', 'line' => (int) 39, 'function' => 'run', 'class' => 'Cake\Http\Server', 'object' => object(Cake\Http\Server) {}, 'type' => '->', 'args' => [] ] ] $frame = [ 'file' => '/home/brlfuser/public_html/src/Controller/ArtileDetailController.php', 'line' => (int) 73, 'function' => 'offsetGet', 'class' => 'Cake\Http\ServerRequest', 'object' => object(Cake\Http\ServerRequest) { trustProxy => false [protected] params => [ [maximum depth reached] ] [protected] data => [[maximum depth reached]] [protected] query => [[maximum depth reached]] [protected] cookies => [ [maximum depth reached] ] [protected] _environment => [ [maximum depth reached] ] [protected] url => 'latest-news-updates/lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714/print' [protected] base => '' [protected] webroot => '/' [protected] here => '/latest-news-updates/lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714/print' [protected] trustedProxies => [[maximum depth reached]] [protected] _input => null [protected] _detectors => [ [maximum depth reached] ] [protected] _detectorCache => [ [maximum depth reached] ] [protected] stream => object(Zend\Diactoros\PhpInputStream) {} [protected] uri => object(Zend\Diactoros\Uri) {} [protected] session => object(Cake\Http\Session) {} [protected] attributes => [[maximum depth reached]] [protected] emulatedAttributes => [ [maximum depth reached] ] [protected] uploadedFiles => [[maximum depth reached]] [protected] protocol => null [protected] requestTarget => null [private] deprecatedProperties => [ [maximum depth reached] ] }, 'type' => '->', 'args' => [ (int) 0 => 'catslug' ] ]deprecationWarning - CORE/src/Core/functions.php, line 311 Cake\Http\ServerRequest::offsetGet() - CORE/src/Http/ServerRequest.php, line 2421 App\Controller\ArtileDetailController::printArticle() - APP/Controller/ArtileDetailController.php, line 73 Cake\Controller\Controller::invokeAction() - CORE/src/Controller/Controller.php, line 610 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 120 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51 Cake\Http\Server::run() - CORE/src/Http/Server.php, line 98
Deprecated (16384): The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 74 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php. [CORE/src/Core/functions.php, line 311]Code Context
trigger_error($message, E_USER_DEPRECATED);
}
$message = 'The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead. - /home/brlfuser/public_html/src/Controller/ArtileDetailController.php, line: 74 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php.' $stackFrame = (int) 1 $trace = [ (int) 0 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ServerRequest.php', 'line' => (int) 2421, 'function' => 'deprecationWarning', 'args' => [ (int) 0 => 'The ArrayAccess methods will be removed in 4.0.0.Use getParam(), getData() and getQuery() instead.' ] ], (int) 1 => [ 'file' => '/home/brlfuser/public_html/src/Controller/ArtileDetailController.php', 'line' => (int) 74, 'function' => 'offsetGet', 'class' => 'Cake\Http\ServerRequest', 'object' => object(Cake\Http\ServerRequest) {}, 'type' => '->', 'args' => [ (int) 0 => 'artileslug' ] ], (int) 2 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Controller/Controller.php', 'line' => (int) 610, 'function' => 'printArticle', 'class' => 'App\Controller\ArtileDetailController', 'object' => object(App\Controller\ArtileDetailController) {}, 'type' => '->', 'args' => [] ], (int) 3 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ActionDispatcher.php', 'line' => (int) 120, 'function' => 'invokeAction', 'class' => 'Cake\Controller\Controller', 'object' => object(App\Controller\ArtileDetailController) {}, 'type' => '->', 'args' => [] ], (int) 4 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/ActionDispatcher.php', 'line' => (int) 94, 'function' => '_invoke', 'class' => 'Cake\Http\ActionDispatcher', 'object' => object(Cake\Http\ActionDispatcher) {}, 'type' => '->', 'args' => [ (int) 0 => object(App\Controller\ArtileDetailController) {} ] ], (int) 5 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/BaseApplication.php', 'line' => (int) 235, 'function' => 'dispatch', 'class' => 'Cake\Http\ActionDispatcher', 'object' => object(Cake\Http\ActionDispatcher) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 6 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Http\BaseApplication', 'object' => object(App\Application) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 7 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Routing/Middleware/RoutingMiddleware.php', 'line' => (int) 162, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 8 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Routing\Middleware\RoutingMiddleware', 'object' => object(Cake\Routing\Middleware\RoutingMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 9 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Routing/Middleware/AssetMiddleware.php', 'line' => (int) 88, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 10 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Routing\Middleware\AssetMiddleware', 'object' => object(Cake\Routing\Middleware\AssetMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 11 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Middleware/ErrorHandlerMiddleware.php', 'line' => (int) 96, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 12 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 65, 'function' => '__invoke', 'class' => 'Cake\Error\Middleware\ErrorHandlerMiddleware', 'object' => object(Cake\Error\Middleware\ErrorHandlerMiddleware) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {}, (int) 2 => object(Cake\Http\Runner) {} ] ], (int) 13 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Runner.php', 'line' => (int) 51, 'function' => '__invoke', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\ServerRequest) {}, (int) 1 => object(Cake\Http\Response) {} ] ], (int) 14 => [ 'file' => '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Http/Server.php', 'line' => (int) 98, 'function' => 'run', 'class' => 'Cake\Http\Runner', 'object' => object(Cake\Http\Runner) {}, 'type' => '->', 'args' => [ (int) 0 => object(Cake\Http\MiddlewareQueue) {}, (int) 1 => object(Cake\Http\ServerRequest) {}, (int) 2 => object(Cake\Http\Response) {} ] ], (int) 15 => [ 'file' => '/home/brlfuser/public_html/webroot/index.php', 'line' => (int) 39, 'function' => 'run', 'class' => 'Cake\Http\Server', 'object' => object(Cake\Http\Server) {}, 'type' => '->', 'args' => [] ] ] $frame = [ 'file' => '/home/brlfuser/public_html/src/Controller/ArtileDetailController.php', 'line' => (int) 74, 'function' => 'offsetGet', 'class' => 'Cake\Http\ServerRequest', 'object' => object(Cake\Http\ServerRequest) { trustProxy => false [protected] params => [ [maximum depth reached] ] [protected] data => [[maximum depth reached]] [protected] query => [[maximum depth reached]] [protected] cookies => [ [maximum depth reached] ] [protected] _environment => [ [maximum depth reached] ] [protected] url => 'latest-news-updates/lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714/print' [protected] base => '' [protected] webroot => '/' [protected] here => '/latest-news-updates/lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714/print' [protected] trustedProxies => [[maximum depth reached]] [protected] _input => null [protected] _detectors => [ [maximum depth reached] ] [protected] _detectorCache => [ [maximum depth reached] ] [protected] stream => object(Zend\Diactoros\PhpInputStream) {} [protected] uri => object(Zend\Diactoros\Uri) {} [protected] session => object(Cake\Http\Session) {} [protected] attributes => [[maximum depth reached]] [protected] emulatedAttributes => [ [maximum depth reached] ] [protected] uploadedFiles => [[maximum depth reached]] [protected] protocol => null [protected] requestTarget => null [private] deprecatedProperties => [ [maximum depth reached] ] }, 'type' => '->', 'args' => [ (int) 0 => 'artileslug' ] ]deprecationWarning - CORE/src/Core/functions.php, line 311 Cake\Http\ServerRequest::offsetGet() - CORE/src/Http/ServerRequest.php, line 2421 App\Controller\ArtileDetailController::printArticle() - APP/Controller/ArtileDetailController.php, line 74 Cake\Controller\Controller::invokeAction() - CORE/src/Controller/Controller.php, line 610 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 120 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51 Cake\Http\Server::run() - CORE/src/Http/Server.php, line 98
Warning (512): Unable to emit headers. Headers sent in file=/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Debugger.php line=853 [CORE/src/Http/ResponseEmitter.php, line 48]Code Contextif (Configure::read('debug')) {
trigger_error($message, E_USER_WARNING);
} else {
$response = object(Cake\Http\Response) { 'status' => (int) 200, 'contentType' => 'text/html', 'headers' => [ 'Content-Type' => [ [maximum depth reached] ] ], 'file' => null, 'fileRange' => [], 'cookies' => object(Cake\Http\Cookie\CookieCollection) {}, 'cacheDirectives' => [], 'body' => '<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd"> <html xmlns="http://www.w3.org/1999/xhtml"> <head> <link rel="canonical" href="https://im4change.in/<pre class="cake-error"><a href="javascript:void(0);" onclick="document.getElementById('cakeErr67f8002983bef-trace').style.display = (document.getElementById('cakeErr67f8002983bef-trace').style.display == 'none' ? '' : 'none');"><b>Notice</b> (8)</a>: Undefined variable: urlPrefix [<b>APP/Template/Layout/printlayout.ctp</b>, line <b>8</b>]<div id="cakeErr67f8002983bef-trace" class="cake-stack-trace" style="display: none;"><a href="javascript:void(0);" onclick="document.getElementById('cakeErr67f8002983bef-code').style.display = (document.getElementById('cakeErr67f8002983bef-code').style.display == 'none' ? '' : 'none')">Code</a> <a href="javascript:void(0);" onclick="document.getElementById('cakeErr67f8002983bef-context').style.display = (document.getElementById('cakeErr67f8002983bef-context').style.display == 'none' ? '' : 'none')">Context</a><pre id="cakeErr67f8002983bef-code" class="cake-code-dump" style="display: none;"><code><span style="color: #000000"><span style="color: #0000BB"></span><span style="color: #007700"><</span><span style="color: #0000BB">head</span><span style="color: #007700">> </span></span></code> <span class="code-highlight"><code><span style="color: #000000"> <link rel="canonical" href="<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">Configure</span><span style="color: #007700">::</span><span style="color: #0000BB">read</span><span style="color: #007700">(</span><span style="color: #DD0000">'SITE_URL'</span><span style="color: #007700">); </span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$urlPrefix</span><span style="color: #007700">;</span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">category</span><span style="color: #007700">-></span><span style="color: #0000BB">slug</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>/<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">seo_url</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>.html"/> </span></code></span> <code><span style="color: #000000"><span style="color: #0000BB"> </span><span style="color: #007700"><</span><span style="color: #0000BB">meta http</span><span style="color: #007700">-</span><span style="color: #0000BB">equiv</span><span style="color: #007700">=</span><span style="color: #DD0000">"Content-Type" </span><span style="color: #0000BB">content</span><span style="color: #007700">=</span><span style="color: #DD0000">"text/html; charset=utf-8"</span><span style="color: #007700">/> </span></span></code></pre><pre id="cakeErr67f8002983bef-context" class="cake-context" style="display: none;">$viewFile = '/home/brlfuser/public_html/src/Template/Layout/printlayout.ctp' $dataForView = [ 'article_current' => object(App\Model\Entity\Article) { 'id' => (int) 1636, 'title' => 'Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'subheading' => '', 'description' => '<p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> ', 'credit_writer' => 'The Hindu, 21 April, 2010, http://www.hindu.com/2010/04/21/stories/2010042153701000.htm', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 1714, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ [maximum depth reached] ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ [maximum depth reached] ], '[dirty]' => [[maximum depth reached]], '[original]' => [[maximum depth reached]], '[virtual]' => [[maximum depth reached]], '[hasErrors]' => false, '[errors]' => [[maximum depth reached]], '[invalid]' => [[maximum depth reached]], '[repository]' => 'Articles' }, 'articleid' => (int) 1636, 'metaTitle' => 'LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'metaKeywords' => 'Food Security', 'metaDesc' => ' To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; The pilot surveys for the next Census of BPL (below-poverty-line) households...', 'disp' => '<p align="justify"><font ></font></p><p align="justify"><font ><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font></p><p align="justify"><font >The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p>', 'lang' => 'English', 'SITE_URL' => 'https://im4change.in/', 'site_title' => 'im4change', 'adminprix' => 'admin' ] $article_current = object(App\Model\Entity\Article) { 'id' => (int) 1636, 'title' => 'Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'subheading' => '', 'description' => '<p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> ', 'credit_writer' => 'The Hindu, 21 April, 2010, http://www.hindu.com/2010/04/21/stories/2010042153701000.htm', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 1714, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ (int) 0 => object(Cake\ORM\Entity) {} ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ '*' => true, 'id' => false ], '[dirty]' => [], '[original]' => [], '[virtual]' => [], '[hasErrors]' => false, '[errors]' => [], '[invalid]' => [], '[repository]' => 'Articles' } $articleid = (int) 1636 $metaTitle = 'LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar' $metaKeywords = 'Food Security' $metaDesc = ' To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; The pilot surveys for the next Census of BPL (below-poverty-line) households...' $disp = '<p align="justify"><font ></font></p><p align="justify"><font ><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font></p><p align="justify"><font >The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p>' $lang = 'English' $SITE_URL = 'https://im4change.in/' $site_title = 'im4change' $adminprix = 'admin'</pre><pre class="stack-trace">include - APP/Template/Layout/printlayout.ctp, line 8 Cake\View\View::_evaluate() - CORE/src/View/View.php, line 1413 Cake\View\View::_render() - CORE/src/View/View.php, line 1374 Cake\View\View::renderLayout() - CORE/src/View/View.php, line 927 Cake\View\View::render() - CORE/src/View/View.php, line 885 Cake\Controller\Controller::render() - CORE/src/Controller/Controller.php, line 791 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 126 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51</pre></div></pre>latest-news-updates/lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714.html"/> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/> <link href="https://im4change.in/css/control.css" rel="stylesheet" type="text/css" media="all"/> <title>LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar | Im4change.org</title> <meta name="description" content=" To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. 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Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any “rural household whose adult members volunteer to do unskilled marginal work” qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the “best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.”</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a “score-based ranking.” Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the “non-scoring parameters,” which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 “scoring parameters,” was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that “in actual practice no detailed survey was done and survey sheets were filled up within the office itself.”</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the “transient poor” in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, “ensure that the poorest and most vulnerable sections are automatically included,” and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably — in theory and practice — arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria — for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty — whether based on criteria set by the MoRD or the Planning Commission or a combination of the two — be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and — more important — exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights — food, education, health, and sanitation, for example — is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p> </font> </td> </tr> <tr> <td> </td> </tr> <tr> <td height="50" style="border-top:1px solid #000; border-bottom:1px solid #000;padding-top:10px;"> <form><input type="button" value=" Print this page " onclick="window.print();return false;"/></form> </td> </tr> </table></body> </html>' } $maxBufferLength = (int) 8192 $file = '/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Debugger.php' $line = (int) 853 $message = 'Unable to emit headers. Headers sent in file=/home/brlfuser/public_html/vendor/cakephp/cakephp/src/Error/Debugger.php line=853'Cake\Http\ResponseEmitter::emit() - CORE/src/Http/ResponseEmitter.php, line 48 Cake\Http\Server::emit() - CORE/src/Http/Server.php, line 141 [main] - ROOT/webroot/index.php, line 39
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'' : 'none');"><b>Notice</b> (8)</a>: Undefined variable: urlPrefix [<b>APP/Template/Layout/printlayout.ctp</b>, line <b>8</b>]<div id="cakeErr67f8002983bef-trace" class="cake-stack-trace" style="display: none;"><a href="javascript:void(0);" onclick="document.getElementById('cakeErr67f8002983bef-code').style.display = (document.getElementById('cakeErr67f8002983bef-code').style.display == 'none' ? '' : 'none')">Code</a> <a href="javascript:void(0);" onclick="document.getElementById('cakeErr67f8002983bef-context').style.display = (document.getElementById('cakeErr67f8002983bef-context').style.display == 'none' ? '' : 'none')">Context</a><pre id="cakeErr67f8002983bef-code" class="cake-code-dump" style="display: none;"><code><span style="color: #000000"><span style="color: #0000BB"></span><span style="color: #007700"><</span><span style="color: #0000BB">head</span><span style="color: #007700">> </span></span></code> <span class="code-highlight"><code><span style="color: #000000"> <link rel="canonical" href="<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">Configure</span><span style="color: #007700">::</span><span style="color: #0000BB">read</span><span style="color: #007700">(</span><span style="color: #DD0000">'SITE_URL'</span><span style="color: #007700">); </span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$urlPrefix</span><span style="color: #007700">;</span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">category</span><span style="color: #007700">-></span><span style="color: #0000BB">slug</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>/<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">seo_url</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>.html"/> </span></code></span> <code><span style="color: #000000"><span style="color: #0000BB"> </span><span style="color: #007700"><</span><span style="color: #0000BB">meta http</span><span style="color: #007700">-</span><span style="color: #0000BB">equiv</span><span style="color: #007700">=</span><span style="color: #DD0000">"Content-Type" </span><span style="color: #0000BB">content</span><span style="color: #007700">=</span><span style="color: #DD0000">"text/html; charset=utf-8"</span><span style="color: #007700">/> </span></span></code></pre><pre id="cakeErr67f8002983bef-context" class="cake-context" style="display: none;">$viewFile = '/home/brlfuser/public_html/src/Template/Layout/printlayout.ctp' $dataForView = [ 'article_current' => object(App\Model\Entity\Article) { 'id' => (int) 1636, 'title' => 'Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'subheading' => '', 'description' => '<p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> ', 'credit_writer' => 'The Hindu, 21 April, 2010, http://www.hindu.com/2010/04/21/stories/2010042153701000.htm', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 1714, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ [maximum depth reached] ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ [maximum depth reached] ], '[dirty]' => [[maximum depth reached]], '[original]' => [[maximum depth reached]], '[virtual]' => [[maximum depth reached]], '[hasErrors]' => false, '[errors]' => [[maximum depth reached]], '[invalid]' => [[maximum depth reached]], '[repository]' => 'Articles' }, 'articleid' => (int) 1636, 'metaTitle' => 'LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'metaKeywords' => 'Food Security', 'metaDesc' => ' To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; The pilot surveys for the next Census of BPL (below-poverty-line) households...', 'disp' => '<p align="justify"><font ></font></p><p align="justify"><font ><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font></p><p align="justify"><font >The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p>', 'lang' => 'English', 'SITE_URL' => 'https://im4change.in/', 'site_title' => 'im4change', 'adminprix' => 'admin' ] $article_current = object(App\Model\Entity\Article) { 'id' => (int) 1636, 'title' => 'Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'subheading' => '', 'description' => '<p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> ', 'credit_writer' => 'The Hindu, 21 April, 2010, http://www.hindu.com/2010/04/21/stories/2010042153701000.htm', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 1714, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ (int) 0 => object(Cake\ORM\Entity) {} ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ '*' => true, 'id' => false ], '[dirty]' => [], '[original]' => [], '[virtual]' => [], '[hasErrors]' => false, '[errors]' => [], '[invalid]' => [], '[repository]' => 'Articles' } $articleid = (int) 1636 $metaTitle = 'LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar' $metaKeywords = 'Food Security' $metaDesc = ' To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; The pilot surveys for the next Census of BPL (below-poverty-line) households...' $disp = '<p align="justify"><font ></font></p><p align="justify"><font ><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font></p><p align="justify"><font >The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p>' $lang = 'English' $SITE_URL = 'https://im4change.in/' $site_title = 'im4change' $adminprix = 'admin'</pre><pre class="stack-trace">include - APP/Template/Layout/printlayout.ctp, line 8 Cake\View\View::_evaluate() - CORE/src/View/View.php, line 1413 Cake\View\View::_render() - CORE/src/View/View.php, line 1374 Cake\View\View::renderLayout() - CORE/src/View/View.php, line 927 Cake\View\View::render() - CORE/src/View/View.php, line 885 Cake\Controller\Controller::render() - CORE/src/Controller/Controller.php, line 791 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 126 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51</pre></div></pre>latest-news-updates/lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714.html"/> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/> <link href="https://im4change.in/css/control.css" rel="stylesheet" type="text/css" media="all"/> <title>LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar | Im4change.org</title> <meta name="description" content=" To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. 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Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any “rural household whose adult members volunteer to do unskilled marginal work” qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the “best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.”</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a “score-based ranking.” Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the “non-scoring parameters,” which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 “scoring parameters,” was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that “in actual practice no detailed survey was done and survey sheets were filled up within the office itself.”</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the “transient poor” in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, “ensure that the poorest and most vulnerable sections are automatically included,” and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably — in theory and practice — arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria — for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty — whether based on criteria set by the MoRD or the Planning Commission or a combination of the two — be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and — more important — exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights — food, education, health, and sanitation, for example — is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p> </font> </td> </tr> <tr> <td> </td> </tr> <tr> <td height="50" style="border-top:1px solid #000; border-bottom:1px solid #000;padding-top:10px;"> <form><input type="button" value=" Print this page " onclick="window.print();return false;"/></form> </td> </tr> </table></body> </html>' } $reasonPhrase = 'OK'header - [internal], line ?? Cake\Http\ResponseEmitter::emitStatusLine() - CORE/src/Http/ResponseEmitter.php, line 148 Cake\Http\ResponseEmitter::emit() - CORE/src/Http/ResponseEmitter.php, line 54 Cake\Http\Server::emit() - CORE/src/Http/Server.php, line 141 [main] - ROOT/webroot/index.php, line 39
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'' : 'none')">Context</a><pre id="cakeErr67f8002983bef-code" class="cake-code-dump" style="display: none;"><code><span style="color: #000000"><span style="color: #0000BB"></span><span style="color: #007700"><</span><span style="color: #0000BB">head</span><span style="color: #007700">> </span></span></code> <span class="code-highlight"><code><span style="color: #000000"> <link rel="canonical" href="<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">Configure</span><span style="color: #007700">::</span><span style="color: #0000BB">read</span><span style="color: #007700">(</span><span style="color: #DD0000">'SITE_URL'</span><span style="color: #007700">); </span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$urlPrefix</span><span style="color: #007700">;</span><span style="color: #0000BB">?><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">category</span><span style="color: #007700">-></span><span style="color: #0000BB">slug</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>/<span style="color: #0000BB"><?php </span><span style="color: #007700">echo </span><span style="color: #0000BB">$article_current</span><span style="color: #007700">-></span><span style="color: #0000BB">seo_url</span><span style="color: #007700">; </span><span style="color: #0000BB">?></span>.html"/> </span></code></span> <code><span style="color: #000000"><span style="color: #0000BB"> </span><span style="color: #007700"><</span><span style="color: #0000BB">meta http</span><span style="color: #007700">-</span><span style="color: #0000BB">equiv</span><span style="color: #007700">=</span><span style="color: #DD0000">"Content-Type" </span><span style="color: #0000BB">content</span><span style="color: #007700">=</span><span style="color: #DD0000">"text/html; charset=utf-8"</span><span style="color: #007700">/> </span></span></code></pre><pre id="cakeErr67f8002983bef-context" class="cake-context" style="display: none;">$viewFile = '/home/brlfuser/public_html/src/Template/Layout/printlayout.ctp' $dataForView = [ 'article_current' => object(App\Model\Entity\Article) { 'id' => (int) 1636, 'title' => 'Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'subheading' => '', 'description' => '<p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> ', 'credit_writer' => 'The Hindu, 21 April, 2010, http://www.hindu.com/2010/04/21/stories/2010042153701000.htm', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 1714, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ [maximum depth reached] ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ [maximum depth reached] ], '[dirty]' => [[maximum depth reached]], '[original]' => [[maximum depth reached]], '[virtual]' => [[maximum depth reached]], '[hasErrors]' => false, '[errors]' => [[maximum depth reached]], '[invalid]' => [[maximum depth reached]], '[repository]' => 'Articles' }, 'articleid' => (int) 1636, 'metaTitle' => 'LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'metaKeywords' => 'Food Security', 'metaDesc' => ' To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; The pilot surveys for the next Census of BPL (below-poverty-line) households...', 'disp' => '<p align="justify"><font ></font></p><p align="justify"><font ><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font></p><p align="justify"><font >The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p>', 'lang' => 'English', 'SITE_URL' => 'https://im4change.in/', 'site_title' => 'im4change', 'adminprix' => 'admin' ] $article_current = object(App\Model\Entity\Article) { 'id' => (int) 1636, 'title' => 'Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'subheading' => '', 'description' => '<p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> ', 'credit_writer' => 'The Hindu, 21 April, 2010, http://www.hindu.com/2010/04/21/stories/2010042153701000.htm', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 1714, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ (int) 0 => object(Cake\ORM\Entity) {} ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ '*' => true, 'id' => false ], '[dirty]' => [], '[original]' => [], '[virtual]' => [], '[hasErrors]' => false, '[errors]' => [], '[invalid]' => [], '[repository]' => 'Articles' } $articleid = (int) 1636 $metaTitle = 'LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar' $metaKeywords = 'Food Security' $metaDesc = ' To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; The pilot surveys for the next Census of BPL (below-poverty-line) households...' $disp = '<p align="justify"><font ></font></p><p align="justify"><font ><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.&nbsp; </em></font></p><p align="justify"><font >The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any &ldquo;rural household whose adult members volunteer to do unskilled marginal work&rdquo; qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the &ldquo;best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.&rdquo;</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a &ldquo;score-based ranking.&rdquo; Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the &ldquo;non-scoring parameters,&rdquo; which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 &ldquo;scoring parameters,&rdquo; was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that &ldquo;in actual practice no detailed survey was done and survey sheets were filled up within the office itself.&rdquo;</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the &ldquo;transient poor&rdquo; in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, &ldquo;ensure that the poorest and most vulnerable sections are automatically included,&rdquo; and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably &mdash; in theory and practice &mdash; arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria &mdash; for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty &mdash; whether based on criteria set by the MoRD or the Planning Commission or a combination of the two &mdash; be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and &mdash; more important &mdash; exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights &mdash; food, education, health, and sanitation, for example &mdash; is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p>' $lang = 'English' $SITE_URL = 'https://im4change.in/' $site_title = 'im4change' $adminprix = 'admin'</pre><pre class="stack-trace">include - APP/Template/Layout/printlayout.ctp, line 8 Cake\View\View::_evaluate() - CORE/src/View/View.php, line 1413 Cake\View\View::_render() - CORE/src/View/View.php, line 1374 Cake\View\View::renderLayout() - CORE/src/View/View.php, line 927 Cake\View\View::render() - CORE/src/View/View.php, line 885 Cake\Controller\Controller::render() - CORE/src/Controller/Controller.php, line 791 Cake\Http\ActionDispatcher::_invoke() - CORE/src/Http/ActionDispatcher.php, line 126 Cake\Http\ActionDispatcher::dispatch() - CORE/src/Http/ActionDispatcher.php, line 94 Cake\Http\BaseApplication::__invoke() - CORE/src/Http/BaseApplication.php, line 235 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\RoutingMiddleware::__invoke() - CORE/src/Routing/Middleware/RoutingMiddleware.php, line 162 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Routing\Middleware\AssetMiddleware::__invoke() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 88 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Error\Middleware\ErrorHandlerMiddleware::__invoke() - CORE/src/Error/Middleware/ErrorHandlerMiddleware.php, line 96 Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65 Cake\Http\Runner::run() - CORE/src/Http/Runner.php, line 51</pre></div></pre>latest-news-updates/lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714.html"/> <meta http-equiv="Content-Type" content="text/html; charset=utf-8"/> <link href="https://im4change.in/css/control.css" rel="stylesheet" type="text/css" media="all"/> <title>LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar | Im4change.org</title> <meta name="description" content=" To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. 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Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any “rural household whose adult members volunteer to do unskilled marginal work” qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the “best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.”</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a “score-based ranking.” Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the “non-scoring parameters,” which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 “scoring parameters,” was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that “in actual practice no detailed survey was done and survey sheets were filled up within the office itself.”</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the “transient poor” in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, “ensure that the poorest and most vulnerable sections are automatically included,” and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably — in theory and practice — arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria — for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty — whether based on criteria set by the MoRD or the Planning Commission or a combination of the two — be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and — more important — exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights — food, education, health, and sanitation, for example — is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p> </font> </td> </tr> <tr> <td> </td> </tr> <tr> <td height="50" style="border-top:1px solid #000; border-bottom:1px solid #000;padding-top:10px;"> <form><input type="button" value=" Print this page " onclick="window.print();return false;"/></form> </td> </tr> </table></body> </html>' } $cookies = [] $values = [ (int) 0 => 'text/html; charset=UTF-8' ] $name = 'Content-Type' $first = true $value = 'text/html; charset=UTF-8'header - [internal], line ?? Cake\Http\ResponseEmitter::emitHeaders() - CORE/src/Http/ResponseEmitter.php, line 181 Cake\Http\ResponseEmitter::emit() - CORE/src/Http/ResponseEmitter.php, line 55 Cake\Http\Server::emit() - CORE/src/Http/Server.php, line 141 [main] - ROOT/webroot/index.php, line 39
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$viewFile = '/home/brlfuser/public_html/src/Template/Layout/printlayout.ctp' $dataForView = [ 'article_current' => object(App\Model\Entity\Article) { 'id' => (int) 1636, 'title' => 'Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'subheading' => '', 'description' => '<p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. </em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any “rural household whose adult members volunteer to do unskilled marginal work” qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the “best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.”</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Unlike the previous BPL Censuses, the BPL Census 2002 used a “score-based ranking.” Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the “non-scoring parameters,” which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 “scoring parameters,” was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that “in actual practice no detailed survey was done and survey sheets were filled up within the office itself.”</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the “transient poor” in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, “ensure that the poorest and most vulnerable sections are automatically included,” and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably — in theory and practice — arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria — for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty — whether based on criteria set by the MoRD or the Planning Commission or a combination of the two — be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and — more important — exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights — food, education, health, and sanitation, for example — is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> ', 'credit_writer' => 'The Hindu, 21 April, 2010, http://www.hindu.com/2010/04/21/stories/2010042153701000.htm', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 1714, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ [maximum depth reached] ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ [maximum depth reached] ], '[dirty]' => [[maximum depth reached]], '[original]' => [[maximum depth reached]], '[virtual]' => [[maximum depth reached]], '[hasErrors]' => false, '[errors]' => [[maximum depth reached]], '[invalid]' => [[maximum depth reached]], '[repository]' => 'Articles' }, 'articleid' => (int) 1636, 'metaTitle' => 'LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'metaKeywords' => 'Food Security', 'metaDesc' => ' To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. The pilot surveys for the next Census of BPL (below-poverty-line) households...', 'disp' => '<p align="justify"><font ></font></p><p align="justify"><font ><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. </em></font></p><p align="justify"><font >The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any “rural household whose adult members volunteer to do unskilled marginal work” qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the “best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.”</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a “score-based ranking.” Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the “non-scoring parameters,” which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 “scoring parameters,” was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that “in actual practice no detailed survey was done and survey sheets were filled up within the office itself.”</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the “transient poor” in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, “ensure that the poorest and most vulnerable sections are automatically included,” and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably — in theory and practice — arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria — for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty — whether based on criteria set by the MoRD or the Planning Commission or a combination of the two — be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and — more important — exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights — food, education, health, and sanitation, for example — is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p>', 'lang' => 'English', 'SITE_URL' => 'https://im4change.in/', 'site_title' => 'im4change', 'adminprix' => 'admin' ] $article_current = object(App\Model\Entity\Article) { 'id' => (int) 1636, 'title' => 'Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar', 'subheading' => '', 'description' => '<p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. </em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any “rural household whose adult members volunteer to do unskilled marginal work” qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the “best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.”</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Unlike the previous BPL Censuses, the BPL Census 2002 used a “score-based ranking.” Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the “non-scoring parameters,” which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 “scoring parameters,” was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that “in actual practice no detailed survey was done and survey sheets were filled up within the office itself.”</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the “transient poor” in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, “ensure that the poorest and most vulnerable sections are automatically included,” and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably — in theory and practice — arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria — for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty — whether based on criteria set by the MoRD or the Planning Commission or a combination of the two — be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3">In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and — more important — exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights — food, education, health, and sanitation, for example — is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font> </p> <p align="justify"> <font face="arial,helvetica,sans-serif" size="3"></font> </p> ', 'credit_writer' => 'The Hindu, 21 April, 2010, http://www.hindu.com/2010/04/21/stories/2010042153701000.htm', 'article_img' => '', 'article_img_thumb' => '', 'status' => (int) 1, 'show_on_home' => (int) 1, 'lang' => 'EN', 'category_id' => (int) 16, 'tag_keyword' => '', 'seo_url' => 'lessons-from-bpl-censuses-by-vk-ramachandran-y-usami-and-biplab-sarkar-1714', 'meta_title' => null, 'meta_keywords' => null, 'meta_description' => null, 'noindex' => (int) 0, 'publish_date' => object(Cake\I18n\FrozenDate) {}, 'most_visit_section_id' => null, 'article_big_img' => null, 'liveid' => (int) 1714, 'created' => object(Cake\I18n\FrozenTime) {}, 'modified' => object(Cake\I18n\FrozenTime) {}, 'edate' => '', 'tags' => [ (int) 0 => object(Cake\ORM\Entity) {} ], 'category' => object(App\Model\Entity\Category) {}, '[new]' => false, '[accessible]' => [ '*' => true, 'id' => false ], '[dirty]' => [], '[original]' => [], '[virtual]' => [], '[hasErrors]' => false, '[errors]' => [], '[invalid]' => [], '[repository]' => 'Articles' } $articleid = (int) 1636 $metaTitle = 'LATEST NEWS UPDATES | Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar' $metaKeywords = 'Food Security' $metaDesc = ' To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. The pilot surveys for the next Census of BPL (below-poverty-line) households...' $disp = '<p align="justify"><font ></font></p><p align="justify"><font ><em>To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. </em></font></p><p align="justify"><font >The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses.</font></p><p align="justify"><font >Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any “rural household whose adult members volunteer to do unskilled marginal work” qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes.</font></p><p align="justify"><font >The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the “best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.”</font></p><p align="justify"><font >Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas.</font></p><p align="justify"><font >The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission.</font></p><p align="justify"><font >Unlike the previous BPL Censuses, the BPL Census 2002 used a “score-based ranking.” Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the “non-scoring parameters,” which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 “scoring parameters,” was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set.</font></p><p align="justify"><font >The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor.</font></p><p align="justify"><font >We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages.</font></p><p align="justify"><font >There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks.</font></p><p align="justify"><font >Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that “in actual practice no detailed survey was done and survey sheets were filled up within the office itself.”</font></p><p align="justify"><font >Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village.</font></p><p align="justify"><font >Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the “transient poor” in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block.</font></p><p align="justify"><font >Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, “ensure that the poorest and most vulnerable sections are automatically included,” and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion.</font></p><p align="justify"><font >Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably — in theory and practice — arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria — for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty — whether based on criteria set by the MoRD or the Planning Commission or a combination of the two — be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure?</font></p><p align="justify"><font >In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and — more important — exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights — food, education, health, and sanitation, for example — is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well.</font></p><p align="justify"><font ><em>(V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.)</em></font></p><p align="justify"><font ></font></p>' $lang = 'English' $SITE_URL = 'https://im4change.in/' $site_title = 'im4change' $adminprix = 'admin'
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Lessons from BPL Censuses by VK Ramachandran, Y Usami and Biplab Sarkar |
To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. The pilot surveys for the next Census of BPL (below-poverty-line) households are due to begin. Discussions are now on to finalise the methodology for the survey, and as the BPL Census is a matter of the subsistence and survival of hundreds of millions of India's households, it is important that we draw lessons from the experience of past BPL Censuses. Poverty alleviation programmes in India can be categorised into universal programmes (or programmes whose beneficiaries are self-selected), and targeted programmes (or programmes that are exclusively for predetermined target groups). An example of the former is the National Rural Employment Guarantee Scheme, for participation in which any “rural household whose adult members volunteer to do unskilled marginal work” qualifies. Most anti-poverty programmes, however, are targeted programmes. The Public Distribution System (PDS) for the provision of fair-priced food, and the Indira Awas Yojana (IAY), India's major rural housing scheme, are examples of targeted programmes. The criterion for targeting is, most often, whether or not a household is below the poverty line. Identifying BPL households as on the ground is thus crucial to the implementation of targeted anti-poverty schemes. Indeed, the XI Plan Working Group on Poverty Elimination Programmes has written that the “best course in future would be to rely increasingly on the aggregation of BPL Survey data for the policy decisions at the state and central level and for monitoring the progress of poverty elimination.” Since 1992, the Ministry of Rural Development (MoRD) has conducted three BPL Censuses in rural areas. The BPL Survey of 1992 used an income criterion to determine poverty, and the annual income cut-off was fixed at Rs. 11,000 per household. The BPL Census of 1997 was conducted in two stages. First, some families were excluded on the basis of certain criteria. In the second stage, each remaining household was interviewed to determine its total consumer expenditure, and was identified as a BPL household if its per capita consumer expenditure was below the poverty line set by the Planning Commission. Unlike the previous BPL Censuses, the BPL Census 2002 used a “score-based ranking.” Each household questionnaire had two parts. Section A recorded some introductory characteristics of households. These were the “non-scoring parameters,” which did not figure in the final assessment of the household's poverty status. Section B, which recorded 13 “scoring parameters,” was intended to evaluate the quality of life of the households. A score (0, 1, 2, 3 or 4) was assigned for each parameter. The aggregate score of the thirteen parameters for each household was calculated and the absolute and relative position of each household in a village in respect of its poverty status was set. The BPL Census 2002 has been widely criticised by the rural poor and their organisations, and by scholars. Even the expert group set up by the MoRD to advise it on the methodology for the next BPL Census said that, although the number of parameters needed to measure poverty had gone up from one in the 1992 survey to thirteen in 2002, the errors of exclusion and inclusion remained above acceptable limits. Targeting errors involved exclusion errors, which exclude poor households from the category of the poor, and inclusion errors, which include non-poor households in the category of the poor. We recently conducted a study of the reliability of the BPL Census of 2002, comparing household-level data from the MoRD website for four villages (one each in Maharashtra, Uttar Pradesh, Rajasthan and Andhra Pradesh) with village-level socio-economic data collected by the Foundation for Agrarian Studies in the same villages. There were four types of causes for exclusion and inclusion errors in BPL household identification. First, there are errors involved in the survey, i.e., in the questionnaire and in the investigation process. The selection of indicators and the scoring scheme for each parameter have rightly been criticised for their inconsistency. There were two major types of problems with respect to the stipulation of scoring parameters. The first set of problems relates to specification. With regard to many variables there are problems of mis-specification, under-specification, or vagueness, allowing for no certainty in how a household is to be classified. The second set of problems relates to gradation. It is not always true that a higher score in the questionnaire represents lower poverty in practice. For instance, with respect to the indebtedness parameter. although a household that has a few paltry household assets and no debts could be one that is in fact too poor to be considered creditworthy by even an informal-sector lender, such a household receives a score of 4, which is higher than the score assigned to, say, a rich landlord who borrows only from commercial banks. Secondly, there was data-cooking or manipulation after the survey. Even the expert group wrote that “in actual practice no detailed survey was done and survey sheets were filled up within the office itself.” Thirdly, one of the most serious flaws in the methodology of BPL household identification was in the aggregation of scores of 13 parameters to establish the absolute and relative position of each household with respect to poverty status in a village. Lastly, another serious cause for exclusion errors is the way cut-off scores were set for each State, district and village. According to the MoRD guidelines, the State-level cut-off was set at the level of the official Planning Commission poverty line plus 10 per cent as an allowance for including the “transient poor” in the BPL category. The determination of the cut-off for administrative divisions within the State (district, block, and village, for example) was left to State governments. As a consequence, the aggregate cut-off score for the determination of BPL households could vary across those administrative entities. In our study, in one State the cut-off varied even from village to village in the same block. Two main methods of conducting the fourth BPL Census are now under discussion. The first, suggested by the Expert Committee chaired by N. C. Saxena, proposes a method that will identify those who will automatically be excluded, “ensure that the poorest and most vulnerable sections are automatically included,” and grade the rest to identify the poorest among them. The second proposes that identification be broadly on the basis of exclusion and inclusion. Past experience teaches us important lessons. First, any system of score-based ranking to identify the rural poor is inevitably — in theory and practice — arbitrary, unfair, and inequitable. Secondly, poverty is multi-dimensional, that is, people can be poor with respect to some or all of a range of criteria — for instance, with respect to income, hunger, health, schooling and education, housing, access to the means of sanitary living, and so on. Why then should a single classification of poverty — whether based on criteria set by the MoRD or the Planning Commission or a combination of the two — be considered adequate to measure whether a person is income-poor, nutrition-poor, education-poor, housing-poor, and so on? The natural beneficiaries of a scheme that provides housing should be the population without adequate, safe and clean housing, just as the natural target group for a scheme to provide sanitary toilets is those who have no access to such facilities. Why should access to such schemes be determined by arbitrary reference to fictitious BPL categories? And why should State governments be forced to fit welfare policies to the Procrustean bed of the MoRD's current BPL measure? In India today, BPL and APL (above poverty line) are not used merely as analytical categories, but as categories that determine inclusion in and — more important — exclusion from anti-poverty programmes. The basic welfare of households and their access to facilities that should be basic rights — food, education, health, and sanitation, for example — is made or broken by the system of BPL-APL segregation in our administrative system. To perpetuate a system that assigns a household to a single BPL/APL category in circumstances in which poverty is multi-dimensional is not only bad economics, but unconscionable as well. (V. K. Ramachandran is a Professor at the Indian Statistical Institute, Yoshifumi Usami is a researcher at the University of Tokyo, and B. Sarkar is a Research Assistant at the Foundation for Agrarian Studies.) |