Does rural subsistence allowance participation induce work disincentives: an empirical test based on CFPS data

HAN Huawei1

(1.School of Social Development and Public Policy, Beijing Normal University, Beijing, China 100875)

【Abstract】Using national longitudinal survey data from the China Family Panel Studies (CFPS) in 2012 and 2014 and a combination of propensity score matching and difference-in-differences methods, this article empirically tests the effect of rural subsistence allowance participation on able-bodied recipients’ work incentive and further investigates the heterogenous work incentive effects among different groups. The article finds that rural subsistence allowance participation had a significant negative effect on able-bodied recipients’ work incentive. This result still held after the work outcome variable considered additional information on working willingness.Receiving different subsistence allowance benefit amounts had heterogenous work incentive effects. Specifically, receiving a high-level benefit amount had a significant negative effect on work incentive, while the work incentive effect of receiving a low-level benefit amount was not statistically significant.The work disincentive effects were more significant among samples who were female, older, low-educated and unhealthy, and lived in the eastern region. All of these results were robust across different matching methods. Three types of policy initiative can be tried to control the work disincentive and welfare dependence arising from rural subsistence allowance participation. First, the marginal tax rate benefits need to be reduced by adopting an earned income disregard and establishing a mechanism of gradual reduction of subsistence allowance benefits after recipients find a job. Second, the reforms should consider to gradually give up the tied eligibility for rural subsistence allowance and other supplemental assistance programs. Third, positive and targeted employment assistance should be provided to promote the able-bodied subsistence allowance recipients to work.

【Keywords】 rural subsistence allowance; work disincentives; panel data; PSM-DID;

【DOI】

【Funds】 National Natural Science Foundation of China (71703008)

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(Translated by XU Ziyue)

    Footnote

    [1]. ① For example, there are community targeting, classified targeting, and agent household targeting methods. [^Back]

    [2]. ① In order to differentiate between the two, samples receiving no subsistence allowance before matching are referred to as the reference group, and those receiving no subsistence allowance after matching are called the control group. [^Back]

    [3]. ① The common trend hypothesis is an important prerequisite for identifying policy effects using the DID method. This hypothesis claims that without policy intervention, there is no significant difference in the outcome variables of the intervention and reference groups during the two periods. The PSM method can eliminate the systemic differences between the control group and the intervention group except for policy intervention to a certain extent, so as to better meet the common trend hypothesis. [^Back]

    [4]. ② The PSM method matches samples by controlling the observable features, but there may be differences in the unobservable features between the intervention group and the control group. The difference-in-differences (DID) between the two periods helps to eliminate the disturbance of unobservable heterogeneity that does not alter over time. [^Back]

    [5]. ③ For example, many surveys only used the question, do you have a job now, to determine the employment status of the sample. [^Back]

    [6]. ① The household net assets per capita come from the calculation results of Jin et al.[30] [^Back]

    [7]. ② Housing difficulties refer to situations when houses are too small that children over 12 years old share the same room with their parents, three generations live in the same room, heterosexual children over the age of 12 share the same room, beds are set up during the night and dismantled during the day, and people sleep in the living room. [^Back]

    [8]. ① We define M = family out-of-pocket medical expenditure/family non-food expenditure. If M < 40%, the family will be defined as not having catastrophic medical expenditures. If 40% ≤ M < 80%, the family will be defined as having a mild catastrophic medical expenditure. If M ≥ 80%, the family will be defined as having a severe catastrophic medical expenditure. [^Back]

    [9]. ② Considering that community characteristics were unlikely to change within two years, CFPS2012 did not investigate community characteristics as they were surveyed in the CFPS2010. Therefore, this study used the community characteristics in CFPS2010 to measure the initial community characteristics. [^Back]

    [10]. ① The independent variables of the ordered Probit model are completely consistent with those in Table 2. Due to space limitations, this result is not presented in the article. [^Back]

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This Article

ISSN:1004-129X

CN: 22-1017/C

Vol 41, No. 06, Pages 89-102

November 2019

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Article Outline

Abstract

  • 1 Introduction and literature review
  • 2 Empirical strategy and econometric model
  • 3 Data source and variable description
  • 4 Empirical results
  • 5 Conclusions and policy implications
  • Footnote

    References