The Inequality of Health-Income Effect in Employed Workers in China: A Longitudinal Study from China Family Panel Studies

Abstract

BackgroundThe relationship between health and income is an essential part of human capital research. The majority of current analyses using classical regression models show that health has a significant impact on income after controlling for the endogeneity of health due to the measurement error and reverse causality. Currently, the Chinese government implements various policies including health related policies to fiercely fight for the domestic poverty issues, and thus only estimating the average effect of health on income could underestimate the impact for low income population and will make policy makers neglect or not pay enough attention to the significant role of health in poverty alleviation. To study the effect of health on income for workers at different income quantiles, we apply the quantile regression method to a panel data from a Chinese household survey. Furthermore, we test the heterogeneity of this health-income effect for different subgroups of workers characterized by sex, registered residence, and residential area. Lastly, we provide an explanation on the possible mechanism of the health-income effect.MethodsThis study uses data from four waves of the China Family Panel Studies (CPFS)- a biennial longitudinal study spanning from 2012 to 2018. The final data used in the regression analysis includes a balanced sample of 19,540 person-year observations aged between 18 to 70 years, with complete information of demographic and social economic status characteristics, job information, and health status of individuals. We use lagged self-reported health to control the potential endogeneity problem caused by reverse causality between health and income. Our identification on heterogenous treatment effects relies on panel quantile regressions, which generate more information than the commonly used mean regression method, and hopefully could reveal the effects of health on income for workers with income distributed at a wide range of quantiles. In addition, we compare the results derived from panel quantile regressions and mean regressions. Finally, we added interaction terms between health and other independent variables to recover the influence channel of health on income.Results The regression estimates show that the effects of health on income are more pronounced for workers distributed on the lower ends of income spectrum, and the health-income effect decreases monotonically with the increase of income. The treatment effect is robust to alternative measures of health and seems to be more pronounced for females than males, for rural workers than their urban counterparts. Finally, we find that health not only directly affects worker’s income but also has different effects on income for different occupation cohorts.ConclusionsThis study provides a different perspective on the impact of individual health status on income, uncovering the heterogeneous effects of health deterioration on income reduction for workers with different incomes by using panel data and rather advanced statistical techniques- panel quantile regressions. At present, the Chinese government is making every effort to solve the problem of poverty and our findings suggest public policies on health and income protections should emphasize different needs of workers with different incomes and special attention should be paid to low-income workers who are much more financially fragile to health deterioration than other income groups.

Peer popularity and self‐discipline as protective factors against depressive symptoms in Chinese adolescents: Do boys and girls benefit equally?

“…The current study used data from the CFPS, a large‐scale, longitudinal panel survey project conducted by the Institute of Social Science Survey at Peking University (extensive information about the survey can be found at www.isss.edu.cn/cfps/ ). CFPS surveys collected representative samples from 25 provinces that represent 95% of the population in mainland China (Xie, 2012 ). Beginning in 2010, the CFPS team conducted a full survey every 2 years, with 14,798 households surveyed in the first wave.…”

“…Self‐discipline (e.g., “I do things carefully,” “I finish homework before playing”) was measured using a 12‐item “self‐discipline scale” (Xie, 2012 ), which was conceptually similar to established psychological scales measuring the construct of “insight, planning, and control” (e.g., Figueredo, 2007 ) and self‐discipline (Duckworth & Seligman, 2005 ). These items were rated on a 4‐point scale ranging from 1 ( strongly disagree ) to 4 ( strongly agree ).…”

“…The current research addressed these issues by using the China Family Panel Studies (CFPS; Xie, 2012 ) dataset, which sampled both adults and children in the majority of Chinese provinces. The CFPS data set used the Center for Epidemiologic Studies Depression Scale (CES‐D; Radloff, 1977 ) to indicate the severity of depressive symptoms among adolescents as a continuous variable.…”

Depressive Symptoms and Negative Experiences in School: A Network Analysis

“…CFPS project has initiated since 2010, which is designed to collect individual-, family- and community-level data every two years to provide information on Chinese development of economic activities, family relationships, educations, and citizen’s health (including physical health and mental health). This project adopted the multi-stage stratified sampling method, which includes 25 provinces in China covering over 95% population 12 . The data in the current study were collected in 2018, which is the latest data of the national survey.…”

“…CFPS-2018 adopted a special 8-item questionnaire based on the standard Center for Epidemiological Studies Depression Scale (CES-D) 12 to screen depressive traits. This original questionnaire asked participants to report their emotional state in last week from 1 to 4, where “1” referred to “little or no (<1 day),” “2” referred to “not too many (1-2 days),” “3” referred to “sometimes half the time (3-4 days)” and “4” referred to “most of the time (5-7 days).” It contained one physiological symptom, two symptoms of anhedonia, and five symptoms of negative affection-cognition, consistent with CES-D’s design 13 .…”