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A Control Function Approach to Estimating Dynamic Probit Models with Endogenous Regressors, with an Application to the Study of Poverty Persistence in China


John Giles


World Bank; Institute for the Study of Labor (IZA)

Irina Murtazashvili


affiliation not provided to SSRN

August 1, 2010

World Bank Policy Research Working Paper No. 5400

Abstract:     
This paper proposes a parametric approach to estimating a dynamic binary response panel data model that allows for endogenous contemporaneous regressors. This approach is of particular value for settings in which one wants to estimate the effects of an endogenous treatment on a binary outcome. The model is next used to examine the impact of rural-urban migration on the likelihood that households in rural China fall below the poverty line. In this application, it is shown that migration is important for reducing the likelihood that poor households remain in poverty and that non-poor households fall into poverty. Furthermore, it is demonstrated that failure to control for unobserved heterogeneity would lead the researcher to underestimate the impact of migrant labor markets on reducing the probability of falling into poverty.

Number of Pages in PDF File: 41

Keywords: Rural Poverty Reduction, Population Policies, Achieving Shared Growth, Debt Markets, Regional Economic Development

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Date posted: August 16, 2010  

Suggested Citation

Giles, John and Murtazashvili, Irina, A Control Function Approach to Estimating Dynamic Probit Models with Endogenous Regressors, with an Application to the Study of Poverty Persistence in China (August 1, 2010). World Bank Policy Research Working Paper Series, Vol. , pp. -, 2010. Available at SSRN: http://ssrn.com/abstract=1658775

Contact Information

John Giles (Contact Author)
World Bank ( email )
Washington DC
United States
Institute for the Study of Labor (IZA)
Schaumburg-Lippe-Str. 7 / 9
Bonn, D-53072
Germany
Irina Murtazashvili
affiliation not provided to SSRN
No Address Available
Feedback to SSRN (Beta)


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