Household Income Dynamics in Rural China

28 Pages Posted: 20 Apr 2016

See all articles by Martin Ravallion

Martin Ravallion

Georgetown University

Jyotsna Jalan

Indian Statistical Institute

Date Written: November 5, 2001

Abstract

Is effective social protection an investment with long-term benefits? Does inequality impede growth? Household panel data on incomes in rural China offer some answers. Theoretical work has shown that nonlinear dynamics in household incomes can yield poverty traps and distribution-dependent growth. If this is true, the potential implications for policy are dramatic: Effective social protection from transient poverty would be an investment with lasting benefits, and pro-poor redistribution would promote aggregate economic growth.

Jalan and Ravallion test for nonlinearity in the dynamics of household incomes and expenditures using panel data for 6,000 households over six years in rural southwest China. While they find evidence of nonlinearity in the income and expenditure dynamics, there is no sign of a dynamic poverty trap.

The authors argue that existing private and social arrangements in this setting protect vulnerable households from the risk of destitution. However, their findings imply that the speed of recovery from an income shock is appreciably slower for the poor than for others. They also find that current inequality reduces future growth in mean incomes, though the "growth cost" of inequality appears to be small. The maximum contribution of inequality is estimated to be 4-7 percent of mean income and 2 percent of mean consumption.

This paper - a product of the Poverty Team, Development Research Group - is part of a larger effort in the group to better understand the dynamic processes influencing household welfare in risk-prone environments.

Suggested Citation

Ravallion, Martin and Jalan, Jyotsna, Household Income Dynamics in Rural China (November 5, 2001). Available at SSRN: https://ssrn.com/abstract=632775

Martin Ravallion (Contact Author)

Georgetown University ( email )

Washington, DC 20057
United States

Jyotsna Jalan

Indian Statistical Institute ( email )

7 S.J.S. Sansanwal Marg
Planning Unit
New Delhi - 110016
India

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