Students who get more schooling because of such policies may earn higher wages, but they are not affected in isolation. In the labor market, an expansion in schooling makes skilled workers more abundant and lowers their equilibrium earnings. At the same time, an increase in the size of the skilled workforce may attract capital and technology, benefiting skilled workers. These changes to the structure of the local economy will affect benefits to workers by changing the labor market returns to schooling – a parameter that labor economists have been debating for at least the last half century. In the education sector, on the other hand, additional public schools may simply crowd-out private schools, diminishing the benefits of schooling expansions. In my job market paper, I develop a new methodology to causally estimate these GE effects in order to determine the overall economic consequences and benefits of a nationwide education program in India.
In my paper, I build a new framework to analyze the consequences of a large-scale educational expansion program in India with an explicit focus on issues that are inherent to nationwide government policies: most importantly the GE effects in the markets for both education and labor. I model firms, households, private and public schools, and I decompose wage changes into the individual returns to schooling and the general equilibrium effects. I then estimate the parameters of the model using a Regression Discontinuity (RD) approach.
The policy I study is the District Primary Education Program (DPEP), which expanded public schooling in half the country by targeting low-literacy regions. It was the Indian government's flagship scheme in the 1990s and early 2000s, and at that time was the largest program for primary education in terms of geography, population and funding, suggesting that its effects would be similarly broad. The allocation rule under which districts receive the funding allows me to estimate the parameters of the model using a Regression Discontinuity (RD) approach. The policy rules were such that districts that had a female literacy rate below the national average were more likely to receive the program. I can therefore compare regions on either side of the literacy-rate cutoff to determine the causal impact of the policy. The RD design allows me to tackle biases that may arise when estimating the individual returns to education, and when comparing earnings in two different local economies.
To support each piece of the general equilibrium model, I create a comprehensive dataset and then use the data to estimate the returns to education and the GE effects. I do this by exploiting not just the RD, but also the variation in cohort exposure and skill levels. Younger cohorts can change their educational attainment in response to the policy, whereas older cohorts cannot. Both the young and the old are, however, affected by changes in the labor market skill distribution and the movement of firms. Furthermore, since the young and the old are not perfect substitutes in the labor market, the GE effects on the two cohorts must be estimated separately. The change in the earnings skill-premium for older workers tells me the part of the GE effects that affect all cohorts, whereas the change in skill-premium for younger workers helps me derive the additional impact on younger workers.
I find that the program increased both education and earnings for students in targeted regions. In the figure alongside, I show that at the RD cutoff there were more new schools and young workers had more education. Overall welfare increases are driven by reductions in the costs of education and an increase in the overall output of the region. However, general equilibrium effects substantially mitigate the rise in labor market welfare. Increases in the supply of educated workers dampened earnings for skilled workers and put upward pressure on the earnings of unskilled workers. The returns to skill are 13.4%, but the estimated labor market GE effects are substantial – they depress the returns by 6.5 percentage points – down from 19.9% – and dampen the increase in student welfare by 23%. These GE effects have important distributional consequences, with a transfer of labor-market benefits from skilled to unskilled workers, particularly among the younger cohorts. High-skill workers who did not change their educational levels under the policy are adversely affected in the labor market, whereas low-skill workers benefit.
One crucial concern with an expansion in public schooling is that it may crowd out private supply. On the other hand, a crowd-in could also have occurred if the program increased the overall size and demand for a skilled workforce. Understanding how private schools respond is, therefore, essential to identifying the overall welfare benefits, as a large amount of crowd-out implies that the funds are essentially wasted and could have been spent on other programs. In my context, I model and estimate this change in private supply, and in line with other work, I find an influx of private schools when public schooling is expanded.
Finally, to track long-run outcomes, I assemble a 10 year panel of districts that allows me to follow the local labor and education markets over time. While policies that lower the costs of schooling seem to have positive impacts in the short run, the existing evidence on the persistence of impacts is mixed. I find that only a few of the schooling inputs last in the long run. Once the funding is phased out, the physical infrastructure upgrades remain but the differential effects on more qualified teachers dissipates.
The results in this paper indicate that these wage responses may undermine some of the effectiveness of micro-interventions when they are scaled up. On the other hand, the crowd-in of private schools indicate that large-scale public schooling expansions may have other unintended benefits in the education sector. I also show that once the funding was phased out, certain crucial inputs, like college-educated teachers no longer remain. These empirically important consequences are crucial considerations for both researchers and policy-makers who examine or implement such large-scale interventions.
Gaurav is a job-market candidate in Economics at the University of Michigan with interests in Development Economics, Labor Economics and Applied Econometrics. His research focuses on education policy, high skill immigration, infrastructure, public-works programs and conflict. You can learn more about his research by visiting his website.