Benefit incidence with incentive effects, measurement errors and latent heterogeneity: A case study for China

•Past studies of tax and benefit incidence routinely ignore behavioral responses and measurement errors.•The estimated benefit withdrawal rate allows for incentive effects, measurement errors and correlated latent heterogeneity.•Analysis for a large cash transfer program in China indicates that past methods are deceptive.

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 likely to be too low in the light of the literature on optimal income taxation. 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.