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);

    }
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 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php.'
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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
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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
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Cake\Http\Runner::__invoke() - CORE/src/Http/Runner.php, line 65
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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);

    }
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 You can disable deprecation warnings by setting `Error.errorLevel` to `E_ALL & ~E_USER_DEPRECATED` in your config/app.php.'
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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 Context
            if (Configure::read('debug')) {

                trigger_error($message, E_USER_WARNING);

            } else {
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-The Indian Express&lt;br /&gt;
&lt;br /&gt;
&lt;em&gt;The state has failed to create capacities for a timely, reliable, decentralised data regime. &lt;br /&gt;
&lt;/em&gt;&lt;br /&gt;
The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &amp;mdash; health, education, nutrition &amp;mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.&lt;br /&gt;
&lt;br /&gt;
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&lt;br /&gt;
Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.&lt;br /&gt;
&lt;br /&gt;
Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.&lt;br /&gt;
&lt;br /&gt;
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&lt;br /&gt;
Please &lt;a href=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot;&gt;click here&lt;/a&gt; to read more. &lt;br /&gt;
&lt;/div&gt;&#039;,
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The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While...&#039;,
	&#039;disp&#039; =&gt; &#039;&lt;div align=&quot;justify&quot;&gt;-The Indian Express&lt;br /&gt;&lt;br /&gt;&lt;em&gt;The state has failed to create capacities for a timely, reliable, decentralised data regime. &lt;br /&gt;&lt;/em&gt;&lt;br /&gt;The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &amp;mdash; health, education, nutrition &amp;mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.&lt;br /&gt;&lt;br /&gt;One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&amp;rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &amp;mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.&lt;br /&gt;&lt;br /&gt;Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.&lt;br /&gt;&lt;br /&gt;Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.&lt;br /&gt;&lt;br /&gt;In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.&lt;br /&gt;&lt;br /&gt;Please &lt;a href=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot; title=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot;&gt;click here&lt;/a&gt; to read more. &lt;br /&gt;&lt;/div&gt;&#039;,
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&lt;br /&gt;
&lt;em&gt;The state has failed to create capacities for a timely, reliable, decentralised data regime. &lt;br /&gt;
&lt;/em&gt;&lt;br /&gt;
The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &amp;mdash; health, education, nutrition &amp;mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.&lt;br /&gt;
&lt;br /&gt;
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&lt;br /&gt;
Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.&lt;br /&gt;
&lt;br /&gt;
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&lt;br /&gt;
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&lt;br /&gt;
Please &lt;a href=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot;&gt;click here&lt;/a&gt; to read more. &lt;br /&gt;
&lt;/div&gt;&#039;,
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The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While...&#039;
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The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While..."/>
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                <strong>There&#039;s a hole in the data -Kiran Bhatty &amp; Dipa Sinha</strong></h1>
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                <div align="justify">-The Indian Express<br /><br /><em>The state has failed to create capacities for a timely, reliable, decentralised data regime. <br /></em><br />The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &mdash; health, education, nutrition &mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.<br /><br />One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.<br /><br />Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.<br /><br />Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.<br /><br />In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.<br /><br />Please <a href="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/" title="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/">click here</a> to read more. <br /></div>               </font>
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-The Indian Express&lt;br /&gt;
&lt;br /&gt;
&lt;em&gt;The state has failed to create capacities for a timely, reliable, decentralised data regime. &lt;br /&gt;
&lt;/em&gt;&lt;br /&gt;
The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &amp;mdash; health, education, nutrition &amp;mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.&lt;br /&gt;
&lt;br /&gt;
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&lt;br /&gt;
Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.&lt;br /&gt;
&lt;br /&gt;
Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.&lt;br /&gt;
&lt;br /&gt;
In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.&lt;br /&gt;
&lt;br /&gt;
Please &lt;a href=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot;&gt;click here&lt;/a&gt; to read more. &lt;br /&gt;
&lt;/div&gt;&#039;,
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The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While...&#039;,
	&#039;disp&#039; =&gt; &#039;&lt;div align=&quot;justify&quot;&gt;-The Indian Express&lt;br /&gt;&lt;br /&gt;&lt;em&gt;The state has failed to create capacities for a timely, reliable, decentralised data regime. &lt;br /&gt;&lt;/em&gt;&lt;br /&gt;The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &amp;mdash; health, education, nutrition &amp;mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.&lt;br /&gt;&lt;br /&gt;One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&amp;rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &amp;mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.&lt;br /&gt;&lt;br /&gt;Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.&lt;br /&gt;&lt;br /&gt;Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.&lt;br /&gt;&lt;br /&gt;In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.&lt;br /&gt;&lt;br /&gt;Please &lt;a href=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot; title=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot;&gt;click here&lt;/a&gt; to read more. &lt;br /&gt;&lt;/div&gt;&#039;,
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-The Indian Express&lt;br /&gt;
&lt;br /&gt;
&lt;em&gt;The state has failed to create capacities for a timely, reliable, decentralised data regime. &lt;br /&gt;
&lt;/em&gt;&lt;br /&gt;
The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &amp;mdash; health, education, nutrition &amp;mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.&lt;br /&gt;
&lt;br /&gt;
One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&amp;rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &amp;mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.&lt;br /&gt;
&lt;br /&gt;
Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.&lt;br /&gt;
&lt;br /&gt;
Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.&lt;br /&gt;
&lt;br /&gt;
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&lt;br /&gt;
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The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While...&#039;
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-The Indian Express

The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While..."/>
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                <strong>There&#039;s a hole in the data -Kiran Bhatty &amp; Dipa Sinha</strong></h1>
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                <div align="justify">-The Indian Express<br /><br /><em>The state has failed to create capacities for a timely, reliable, decentralised data regime. <br /></em><br />The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &mdash; health, education, nutrition &mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.<br /><br />One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.<br /><br />Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.<br /><br />Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.<br /><br />In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.<br /><br />Please <a href="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/" title="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/">click here</a> to read more. <br /></div>               </font>
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-The Indian Express&lt;br /&gt;
&lt;br /&gt;
&lt;em&gt;The state has failed to create capacities for a timely, reliable, decentralised data regime. &lt;br /&gt;
&lt;/em&gt;&lt;br /&gt;
The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &amp;mdash; health, education, nutrition &amp;mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.&lt;br /&gt;
&lt;br /&gt;
One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&amp;rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &amp;mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.&lt;br /&gt;
&lt;br /&gt;
Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.&lt;br /&gt;
&lt;br /&gt;
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&lt;br /&gt;
In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.&lt;br /&gt;
&lt;br /&gt;
Please &lt;a href=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot;&gt;click here&lt;/a&gt; to read more. &lt;br /&gt;
&lt;/div&gt;&#039;,
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The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While...&#039;,
	&#039;disp&#039; =&gt; &#039;&lt;div align=&quot;justify&quot;&gt;-The Indian Express&lt;br /&gt;&lt;br /&gt;&lt;em&gt;The state has failed to create capacities for a timely, reliable, decentralised data regime. &lt;br /&gt;&lt;/em&gt;&lt;br /&gt;The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &amp;mdash; health, education, nutrition &amp;mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.&lt;br /&gt;&lt;br /&gt;One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&amp;rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &amp;mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.&lt;br /&gt;&lt;br /&gt;Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.&lt;br /&gt;&lt;br /&gt;Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.&lt;br /&gt;&lt;br /&gt;In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.&lt;br /&gt;&lt;br /&gt;Please &lt;a href=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot; title=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot;&gt;click here&lt;/a&gt; to read more. &lt;br /&gt;&lt;/div&gt;&#039;,
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-The Indian Express&lt;br /&gt;
&lt;br /&gt;
&lt;em&gt;The state has failed to create capacities for a timely, reliable, decentralised data regime. &lt;br /&gt;
&lt;/em&gt;&lt;br /&gt;
The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &amp;mdash; health, education, nutrition &amp;mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.&lt;br /&gt;
&lt;br /&gt;
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&lt;br /&gt;
Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.&lt;br /&gt;
&lt;br /&gt;
Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.&lt;br /&gt;
&lt;br /&gt;
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&lt;br /&gt;
Please &lt;a href=&quot;https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/&quot;&gt;click here&lt;/a&gt; to read more. &lt;br /&gt;
&lt;/div&gt;&#039;,
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The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&amp;rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While...&#039;
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-The Indian Express

The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While..."/>
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                <strong>There&#039;s a hole in the data -Kiran Bhatty &amp; Dipa Sinha</strong></h1>
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                <div align="justify">-The Indian Express<br /><br /><em>The state has failed to create capacities for a timely, reliable, decentralised data regime. <br /></em><br />The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &mdash; health, education, nutrition &mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.<br /><br />One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.<br /><br />Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.<br /><br />Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.<br /><br />In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.<br /><br />Please <a href="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/" title="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/">click here</a> to read more. <br /></div>               </font>
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-The Indian Express<br />
<br />
<em>The state has failed to create capacities for a timely, reliable, decentralised data regime. <br />
</em><br />
The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &mdash; health, education, nutrition &mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.<br />
<br />
One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.<br />
<br />
Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.<br />
<br />
Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.<br />
<br />
In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.<br />
<br />
Please <a href="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/">click here</a> to read more. <br />
</div>',
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	'metaTitle' => 'LATEST NEWS UPDATES | There&#039;s a hole in the data -Kiran Bhatty &amp; Dipa Sinha',
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-The Indian Express

The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While...',
	'disp' => '<div align="justify">-The Indian Express<br /><br /><em>The state has failed to create capacities for a timely, reliable, decentralised data regime. <br /></em><br />The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &mdash; health, education, nutrition &mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.<br /><br />One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.<br /><br />Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.<br /><br />Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.<br /><br />In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.<br /><br />Please <a href="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/" title="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/">click here</a> to read more. <br /></div>',
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	'title' => 'There&#039;s a hole in the data -Kiran Bhatty &amp; Dipa Sinha',
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-The Indian Express<br />
<br />
<em>The state has failed to create capacities for a timely, reliable, decentralised data regime. <br />
</em><br />
The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector &mdash; health, education, nutrition &mdash; the situation, even with these sources (along with other large data sets), has been deficient on numerous counts.<br />
<br />
One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don&rsquo;t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time &mdash; the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available.<br />
<br />
Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark.<br />
<br />
Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education.<br />
<br />
In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it.<br />
<br />
Please <a href="https://indianexpress.com/article/opinion/columns/india-employment-data-national-sample-survey-nsso-data-health-expenditure-narendra-modi-govt-5577718/">click here</a> to read more. <br />
</div>',
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-The Indian Express

The state has failed to create capacities for a timely, reliable, decentralised data regime. 

The credibility of India&rsquo;s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While...'
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There's a hole in the data -Kiran Bhatty & Dipa Sinha

-The Indian Express The state has failed to create capacities for a timely, reliable, decentralised data regime. The credibility of India’s data systems is under serious threat with the recent controversy over the employment data of the National Sample Survey. While the Census of India and the National Sample Survey Organisation (NSSO) have a good reputation, when it comes to data related to the social sector — health, education, nutrition — the situation, even with these sources (along with other large data sets), has been deficient on numerous counts. One, the information collected is not available in real time or even annually. The NSSO collects data through specific rounds (health expenditure, debt etc.) which don’t have a fixed cycle unlike the consumption expenditure surveys, and the Census collects data once in 10 years. Budget allocations follow an annual cycle and policy pronouncements are not dovetailed to the years for which data is available. This raises important questions about the basis on which policies and plans are made. In the case of malnutrition, which is a problem needing urgent solutions, there was no independent data telling us what the trends are for a long time — the National Family Health Survey (NFHS-4) report came out in 2017 after a gap of over 10 years (NFHS-3 was in 2006). In the interim, major initiatives were planned for the eradication of malnutrition without any inkling of the situation on the ground or how it was changing. Similarly, data on learning levels was not collected consistently by the government, till 2017, and it is not known when the next round will be held or how long it will take for the data to be made available. Two, there are inconsistencies in definitions and sampling frames across data sources and across time in the same data source. For instance, questions posed by the NSS for obtaining information on out-of-school children vary dramatically from those posed by the Census. As a result, the two arrive at vastly different numbers. Similarly, in the case of malnutrition data, there have been changes in the definitions used by NFHS across different rounds that make comparisons over time difficult. Periodicity of data collection also varies across sources, furthering difficulty in validation. Data validation plays an important part in improving the quality of data collected and ensuring authenticity, without which departments are basically shooting in the dark. Three, the data collected in these surveys, is not geared towards policy or planning. The education rounds of NSS are part of the survey on social consumption, which in turn is for the purpose of making an assessment of the benefits derived by various sections of society from public expenditure incurred by the government. It provides no information on how the education system is functioning. As a result, several important indicators that would be of interest for planning or to the people, do not even figure in them. For instance, the different categories of teachers or their salaries is a not a data point in any data-set on education. In the absence of regular large-scale survey data, what is available is the registry data collected by departments and ministries for monitoring of programmes. Unfortunately, these too suffer from gaps in information and are rarely used for programmatic purposes. At most, they are part of an accounting exercise. For instance, school surveys by the MHRD collect information on broad indicators of infrastructure and teacher availability (only two categories, whereas multiple exist) and student enrolment (but not attendance) and distribution of incentives. These take stock of the provisioning in schools, showcasing administrative efforts, but not functioning of the education system or real changes within it. Please click here to read more.