evidence-based policy making” is hall mark of good governance
#data driven politics,#databased governance,#good governance
Minutes after Prime Minister Narendra Modi delivered his Independence Day speech, India’s fact checking industry got to work. The Swachh Bharat Mission (SBM) saved three lakh children’s lives, said the PM, citing the World Health Organization. False, said the fact checkers. The World Health Organization cited the three-lakh figure describing potential rather than actual SBM impact. Construction of new rural homes increased by four times, said the PM. True, tweeted the fact checkers.
This cycle of using data to make claims on performance by the Modi government and fact checking is now a regular feature in our public discourse. At one level this is welcome. In my world of policy wonks, “evidence-based policy making” is the gold standard that all governments must aspire to. And what better evidence of evidence based policy than a government that routinely uses data to showcase performance? Arguably, the emergence of fact checkers is a sign of a healthy democracy where government is held accountable for its claims. But behind this virtuous cycle of claims and counter claims is the emergence of a new data politics that is slowly framing political discourse and government action in the country. This merits careful examination.
This cycle of using data to make claims on performance by the Modi government and fact checking is now a regular feature in our public discourse. At one level this is welcome. In my world of policy wonks, “evidence-based policy making” is the gold standard that all governments must aspire to. And what better evidence of evidence based policy than a government that routinely uses data to showcase performance? Arguably, the emergence of fact checkers is a sign of a healthy democracy where government is held accountable for its claims. But behind this virtuous cycle of claims and counter claims is the emergence of a new data politics that is slowly framing political discourse and government action in the country. This merits careful examination.
To examine this new politics, it is worth considering the kinds of data that government collects and showcases versus data that it stays stubbornly silent on. There is today a deluge of administrative data on flagship schemes. Dashboards, mobile apps and indexes that rank states, district, cities and villages on every conceivable indicator from ease of business to ease of living are the hallmark of this government’s governance style. And the BJP, more than any of its predecessors, has been deft at using data to score political points. Consider the recent Saaf Niyat, Sahi Vikas campaign celebrating four years in government — all the publicity material on billboards and websites used data-based infographics to showcase sahi vikas.
Despite this deluge, there is relatively little by way of independent, third party survey data, particularly on politically contentious issues. This is most visible in the ongoing debate on jobs. The PM and his government have repeatedly argued that the real jobs problem is not the lack of jobs, rather the lack of data on jobs. But as economist Himanshu has pointed out, the obvious question to ask then is why the government has refused to collect credible data on jobs. The National Sample Survey Office (NSSO) is widely regarded, including by the Niti Aayog task force on improving employment data, as the most comprehensive source of labour force statistics in India. Between 2004 and 2011-12, six employment-unemployment surveys (EUS) were conducted by NSSO. Rather than revive the practice of conducting annual surveys, on coming to power, a debate was had on methodology and quality of employment data, and the next round of the EUS was delayed to 2018. In the interim, the lack of jobs data became a political convenience. A similar story is now playing out in the fracas over revised GDP figures.
Despite this deluge, there is relatively little by way of independent, third party survey data, particularly on politically contentious issues. This is most visible in the ongoing debate on jobs. The PM and his government have repeatedly argued that the real jobs problem is not the lack of jobs, rather the lack of data on jobs. But as economist Himanshu has pointed out, the obvious question to ask then is why the government has refused to collect credible data on jobs. The National Sample Survey Office (NSSO) is widely regarded, including by the Niti Aayog task force on improving employment data, as the most comprehensive source of labour force statistics in India. Between 2004 and 2011-12, six employment-unemployment surveys (EUS) were conducted by NSSO. Rather than revive the practice of conducting annual surveys, on coming to power, a debate was had on methodology and quality of employment data, and the next round of the EUS was delayed to 2018. In the interim, the lack of jobs data became a political convenience. A similar story is now playing out in the fracas over revised GDP figures.
What about data that is collected? How is it being used? Administrative data is a powerful tool for monitoring and course correction. However, in a low-capacity state like ours, when data becomes politically relevant, it can create perverse incentives that compromise both data quality and the core objectives of government intervention. This is precisely the dynamic unfolding in SBM. High political visibility and tightly monitored targets have resulted in a frantic race to the top. But as studies by the Centre for Policy Research’s Accountability Initiative, RICE and other researchers show, where capacity is low, to meet targets and make a splash on the dashboard, many administrators have taken to penalisation and coercion of citizens rather than awareness-raising and demand creation, thereby undermining the spirit behind SBM. When data becomes political it also becomes vulnerable. And SBM is an important illustration of just this.
Finally, data-driven politics is only credible if administrative data is complemented by rigorous independent studies and evaluations. Civil society too plays a critical role by demystifying and communicating data, thus empowering citizens with relevant information. Governments and politicians have few incentives to create such an environment. But benign neglect helps. Take the example of MGNREGA. In its early years, academics and civil society closely evaluated the programme creating a powerful data ecosystem. The UPA did not actively encourage this but it didn’t dissuade academia and civil society, often relying on them for feedback. This government’s limited appetite for dissent and critique is discouraging the creation of a similar data-ecosystem on flagships. So for all its data-driven speeches and publicity, citizens today are none the wiser about their government’s performance.
Finally, data-driven politics is only credible if administrative data is complemented by rigorous independent studies and evaluations. Civil society too plays a critical role by demystifying and communicating data, thus empowering citizens with relevant information. Governments and politicians have few incentives to create such an environment. But benign neglect helps. Take the example of MGNREGA. In its early years, academics and civil society closely evaluated the programme creating a powerful data ecosystem. The UPA did not actively encourage this but it didn’t dissuade academia and civil society, often relying on them for feedback. This government’s limited appetite for dissent and critique is discouraging the creation of a similar data-ecosystem on flagships. So for all its data-driven speeches and publicity, citizens today are none the wiser about their government’s performance.