Reforming India’s public works scheme raised incomes


Published 30.10.23

Improving the payment infrastructure for India’s National Rural Employment Guarantee Scheme raised incomes — mostly through increases in non-programme earnings

India’s National Rural Employment Guarantee Scheme (NREGS) is among the largest and most influential social programmes in the world, guaranteeing 100 days of paid work to 8% of the world’s population. The programme was designed as a vital lifeline to India’s poor, tasked with smoothing income in agricultural off seasons and providing “employment of last resort” in the face of unforeseen economic hardship.

At the same time, the NREGS has faced both practical challenges and more fundamental critiques. Administration has not been easy: few workers report being able to access the promised 100 days per year of employment on demand, and wages are frequently delayed (The Hindu 2023). And critics have long contended that if it were well-implemented such a scheme would be problematic, as it could crowd out private-sector employment. This critique gets to the heart of the programme’s design, as the work requirement is the core mechanism in place to ensure that benefits reach only those who really need them. Other than this, and the restriction to rural areas, eligibility is not restricted in any way.

Recent work of ours, in collaboration with the government of the (erstwhile) state of Andhra Pradesh, created a unique opportunity to examine these issues. The core of the project involved randomising the geographic rollout of a significant upgrade to the programme’s operational capacities–specifically, the infrastructure used to deliver payments. In earlier work we documented that this reform meaningfully improved NREGS performance on a number of dimensions–decreasing “leakage” or corruption, speeding up payments, and increasing beneficiary access to and satisfaction with the programme (Muralidharan et al. 2016).

Having seen these improvements in programme implementation, we turned next to the question of how they affected programme participants, and the economy overall. We were particularly interested in assessing the critique that a better-implemented programme might actually hurt broader economic performance.

Intervention & research design

Prior to 2010, NREGS payments in Andhra Pradesh were authenticated using pen and paper, with beneficiaries collecting wages at local post offices. Diversion of funds by bureaucratic intermediates was common, contributing to an unsavory picture of the NREGS as a “leaky bucket” (Mookherjee 2014) in desperate need of reform.

To address this issue the government introduced a new system of biometrically authenticated payments (“Smartcards” for short). In this new regime all payments were initially issued into bank accounts, and cash withdrawals from these accounts were allowed only after biometric authentication using fingerprint scans.

To examine the impacts of this reform, we worked with the state government to randomise the order in which it was rolled out in different parts of the state. The consequence was that mid-way through the rollout there were regions using Smartcards, and others not, that were different only by chance. Comparing outcomes in these regions thus gives us a good, unbiased estimate of the impacts the reform was having.

An important feature of the design was that the geographic units in which the rollout was sequenced were large. We randomised the rollout across mandals, administrative units with an average of over 60,000 inhabitants. Experimenting at this scale made it possible to see not only how the reform impacted individual programme participants, but also how it affected the broader economies in which they live. In total the experiment encompassed mandals home to 19 million people, and our results are representative of that population.


Overall we found that the reform had profound effects, raising beneficiary incomes by 14% and reducing overall poverty by 26%. And as you might imagine, effects this large were not solely attributable to the direct effects of the NREGS itself. Take the earnings gains, for example–just 14% of the increase we see came directly from NREGS earnings. Most of the rest (80\% of the total) came from increases in private labour-market earnings.

Why would a better NREGS raise earnings from the private sector? One obvious possibility is that it puts competitive pressure on local labour markets, driving up wages. This is exactly what we see. Wages during the peak period of NREGS activity, for example, rose by 10%. Of course this is exactly the scenario that critics of the programme have feared, anticipating that higher wages would mean lower private-sector employment.

Yet we find the opposite. Market employment among NREGS-registered households during the same period did not fall but actually rose by 20%. And data sources entirely independent from our own surveys tell a similar story–the government’s census of non-agricultural establishments shows a 49% increase in employment, for example, along with an increase in the number of small owner-operated enterprises. Overall, it seems that this reform was not a curse but a boon for the private sector.

What explains this surprising result? In the paper we explore a number of possible explanations, but ultimately emphasise one that seems to matter most, which is employer market power. The effects discussed above were especially strong in regions where landholdings were concentrated, for example. This suggests that the reform made it harder for large landowners to keep wages low by limiting employment.

Policy implications

We draw a few broader implications from these results.

First, they highlight the importance of good implementation. There were no changes to the “policy” of the NREGS in our experiment; simply improving the implementation of the existing policy had large effects. In fact the effects of reform were almost as large as our best estimates of the effects of the initial rollout of the policy itself (Imbert & Papp 2015). Getting implementation right can be critical.

Second, they shift our views on rural workfare programmes. Many villages in India (and elsewhere) look like the ones we study, with a few large landholders who exert substantial influence over local labour markets. This influence may depress both wages and employment. In such settings, a workfare programme that serves–even imperfectly–as an employer of last resort can have beneficial effects on efficiency as well as on equity. The idea is analogous to the idea that a minimum wage can act as a “thumb on the scale” for workers (Card and Krueger 1994). This narrative is consistent with the vehement opposition of landholders to the initial rollout of the NREGS (Anderson et al. 2015); and also consistent with the increasing evidence on employer monopsony power around the world (Manning 2021).

Finally, they highlight a lesson for the evaluation of other policies: we risk greatly under-estimating the full consequences if we do not find ways to measure the indirect effect these have on the economy, as well as the direct effects on participants. Running more experiments at large scale is one strategy for learning more about these “general equilibrium” effects, though not the only one (Muralidharan and Niehaus 2017). 


Anderson, S, P Francois, and A Kotwal (2015), “Clientelism in Indian Villages”, American Economic Review 105(6): 1780-1816.

Card, D and A Krueger (1994), “Minimum Wages and Employment: A Case Study of the Fast-Food Industry in New Jersey and Pennsylvania, American Economic Review 84(4): 772-793.

Economic Times (10 October 2013), “World Bank calls NREGS a stellar example of rural development”,

Imbert, C and J Papp (2015), “Labor Market Effects of Social Programs: Evidence from India’s Employment Guarantee”, American Economic Journal: Applied Economics 7(2): 233-263.

Manning, A. (2021). Monopsony in Labor Markets: A Review. ILR Review, 74(1): 3-26. 

Mookherjee, D (28 May 2014), “MGNREGA: Populist leaky bucket or anti-poverty success?”, Ideas for India,

Muralidharan, K, P Niehaus, and S Sukhtankar (2023), “General Equilibrium Effects of Improving Public Employment Programmes: Experimental Evidence from India.”, Econometrica 91(4): 1261-1295.

Muralidharan, K, P Niehaus, and S Sukhtankar (2016), “Building State Capacity: Evidence from Biometric Smartcards in India”, American Economic Review 106(10): 2895-2929.

Muralidharan, K and P Niehaus (2017), “Experimentation at Scale”, Journal of Economic Perspectives 31(4): 103-124.

The Hindu (09 September 2023), “Workers in Muzaffarpur endure penury as wages are delayed under the MGNREGA scheme”,