Panel Paper: Public Assistance and Families' Investment in Children: The Case of Urban China

Thursday, November 7, 2013 : 3:40 PM
Lincoln (Ritz Carlton)

*Names in bold indicate Presenter

Qin Gao1, Sui Yang2 and Shi Li2, (1)Fordham University, (2)Beijing Normal University
Using the China Household Income Project 2002 and 2007 survey data and a propensity score matching method, this study examines the effects of urban China’s primary public assistance program –Minimum Living Standard Assistance (MLSA, or Dibao) – on how families invest in children through expenditures. MLSA is a means-tested safety net program aiming at providing a minimum level of living subsidy to the very poor. Recent empirical studies have highlighted the constant challenge of selection bias in sorting out the effects of program participation in observational studies. Specifically, program participants may be systematically different from non-participants, which may bias the estimation of the “true effects” of the program. To address the issue of selection bias, this study adopts a propensity score matching method to identify comparable non-participants who have similar observed characteristics to those of MLSA participants. The effects of MLSA participation are estimated by comparing the outcomes of MLSA participants with those of their “matched” non-participant peers.

In this study, we focus on whether MLSA participation enables families to invest in children to promote better future life opportunities for these children growing up in poverty. We examine two broad categories of family expenditures: expenditures on household necessities that often are shared among family members (e.g., paying for food, clothing, rent and utilities) and expenditures specifically on children (e.g., paying for tuition, other school fees, books, tutors). In addition, we also examine families’ expenditures on health care, an item measured specific to each household member, which enables us to differentiate those for children and adults. Using the nationally representative CHIP data allows us to address this research question in the national context and track changes over time from 2002 to 2007 based on a relatively large sample size. This analysis will be supplemented by similar analysis using survey data from a smaller sample of low-income families in Shanghai collected in 2009 to see if the result patterns match. Findings from this study will help us gain insight into the effectiveness of the MLSA program on enabling poor families to invest in their children to increase their social mobility and enhance their future life opportunities.