Benefit Incidence with Incentive Effects, Measurement Errors and Latent Heterogeneity: A Case Study for China

31 Pages Posted: 20 Apr 2015

See all articles by Martin Ravallion

Martin Ravallion

Georgetown University

Shaohua Chen

World Bank; World Bank - Development Research Group (DECRG)

Date Written: April 2015

Abstract

In what is probably the largest cash transfer program in the world today China’s Dibao program aims to fill all poverty gaps. In theory, the program creates a poverty trap, with 100% benefit withdrawal rate (BWR). But is that what we see in practice? The paper proposes an econometric method of estimating the mean BWR allowing for incentive effects, measurement errors and correlated latent heterogeneity. Under the method’s identifying assumptions, a feasible instrumental variables estimator corrects for incentive effects and measurement errors, and provides a bound for the true value when there is correlated incidence heterogeneity. The results suggest that past methods of assessing benefit incidence using either nominal official rates or raw tabulations from survey data are deceptive. The actual BWR appears to be much lower than the formal rate, and is also lower than the rate implied by optimal income tax models for poverty reduction. The paper discusses likely reasons based on qualitative observations from field work. The program’s local implementation appears to matter far more than incentives implied by its formal rules.

Suggested Citation

Ravallion, Martin and Chen, Shaohua, Benefit Incidence with Incentive Effects, Measurement Errors and Latent Heterogeneity: A Case Study for China (April 2015). NBER Working Paper No. w21111, Available at SSRN: https://ssrn.com/abstract=2596440

Martin Ravallion (Contact Author)

Georgetown University ( email )

Washington, DC 20057
United States

Shaohua Chen

World Bank ( email )

1818 H Street, N.W.
Washington, DC 20433
United States

World Bank - Development Research Group (DECRG)

1818 H. Street, N.W.
MSN3-311
Washington, DC 20433
United States

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