Publications
Journal of Development Economics, 2023, 103083.
This paper analyzes the impact of externalities on household demand for sanitation and the subsequent welfare effects generated from policy interventions. A critical feature of household sanitation (e.g., toilets) is that the take-up generates externalities where the privately chosen level is less than the socially optimal. To analyze the impact of policy interventions, I explicitly model household choice, taking into account the interdependence of household decision-making within the village. I identify and estimate the model using micro-survey data from India. Using the estimated model, I show how untargeted price subsidies, although cost effective at increasing sanitation coverage, have a regressive effect. I contrast this policy response with a targeted cash transfer to households with children, which ameliorates the regressive impact at the expense of a lower take-up.
Journal of Development Economics, 163, 2023, 103092.
This paper measures the additional value of sanitation within the marriage arrangement. We use data from the Indian human development household survey (IHDS) to model the marital decisions of men and women in rural India and to estimate the marital surplus (the gains from being married). We use the model to demonstrate that the government’s Total Sanitation Campaign (TSC) increased marital surplus and changed marriage market outcomes for men and women. Decomposition reveals (i) that sanitation makes it more attractive to be in a marriage for both gender, and (ii) that TSC exposure led to a decrease in the wife’s surplus share, implying a redistribution of gains within the marriage
Working Papers
Can informal health providers help improve health? Experimental evidence from Nigeria
We evaluate experimentally the impact of a statewide malaria control program implemented in Anambra, one of the most populous states in Nigeria. The intervention promoted the integration of informal health providers (IP) with the Nigerian public health system through training and improved supplies of drugs and rapid diagnostic tests. The program led to a 42 percent and 35 percent reduction in malaria incidence among children under-5 and 5 to 11, respectively. These impacts are accompanied (and partly driven) by an improvement in household knowledge about malaria prevention and treatment. Impacts are larger in areas where the quality of public health facilities is higher, which likely occurs because in these areas: 1) there is better availability of drugs and RDTs to be distributed to IPs in the communities; 2) IPs are able to refer patients to better health facilities.
This paper analyses the problem of under-adoption of sanitation and addresses the current policy debate on the choice between loans and price subsidy policies to increase sanitation coverage in the developing world. While sanitation is a expensive investment for a poor potentially liquidity constrained household, adoption also generates positive health externalities for others within the village. Both factors may result in under-adoption but are driven by different sources of market failure. To investigate impact of these two distinct policies on sanitation coverage I estimate a dynamic model of household sanitation demand with interdependent adoption choice, using a unique dataset from rural India. I use the model to compute equilibrium adoption levels under both loans and subsidy policies to study the optimal design of interventions in an equilibrium setting. Counterfactual analysis reveals existing sanitation level to be below the social planner solution, implying under-adoption. I find price subsidies to be more cost effective at increasing sanitation coverage. But the policy effects are heterogeneous with coverage levels, where loans are found to be equally, if not marginally more, effective in villages with no sanitation coverage. A price subsidy has a high social rate of return where the presence of externalities accounts for a substantial fraction of its impact. While a sanitation loan policy generates smaller social returns it is also cost efficient under targeted delivery.
Work in progress
The Effect of Transfers on Consumption: Cash versus In-Kind Transfers in Rural Mexico
A large literature has examined the impact of cash and in-kind transfers on consumption in developing countries. In evaluating these programs, however, existing work has mostly ignored households’ subsistence or liquidity constraints; the dispersion in the unit prices of even the most common staples; the impact of transfers on this price dispersion; and the non-pecuniary (real) and pecuniary (price) indirect effects of transfers on both eligible and non-eligible households in communities targeted by these programs. In this paper, we complement the existing literature in all of these dimensions. Namely, we first develop an equilibrium model to estimate the impact of transfers on consumption, consumer welfare, and the nonlinearity of prices accounting for households’ heterogeneous preferences and subsistence or liquidity constraints, and to measure the potential spillover effects of transfers on eligible and non-eligible households. We then examine the optimal design of transfers in the presence of the spillover effects we measure.
Two-step Conditional Choice Probability Estimators with Measurement Error
This paper develops a correction method for existing Two-step CCP methods to estimate static and dynamic discrete choice models of incomplete information. Under the assumption that the observed data is generated by one of the possible equilibria, two-step estimators avoid the computational burden associated with repeatedly solving the fixed point for each candidate vector of parameters. However, to obtain consistent choice probability estimates in the first stage, two-step estimators rely on being able to observe the entire vector of states and actions in the data. This data limitation can be treated as a contamination of the variable of interest with measurement error. Using insights from small variance approximation to probability distributions, I extend the error correction method proposed by Chesher (1991) to the estimation of simple static interaction models. The method is applied to estimate Brock & Durlauf's (2001) interaction model which has been the cornerstone in the study of peer effects in recent literature. Monte Carlo simulations are conducted to approximate the magnitude of the impact of error in data and the resulting bias in parameter estimates.