This paper investigates the impact of pension income on living arrangements of the elderly. Taking advantage of a unique opportunity due to the recent establishment and expansion of the New Rural Pension Scheme in China, we explicitly address the endogeneity of pension status and pension income through a fixed-effect model with instrumental variable approach by exploiting exogenous time variation in the program implementation at county level. We find an overall positive effect of pension income on independent living as well as considerable heterogeneity. The positive income effects of the NRPS are concentrated among the elderly with adult children living nearby, of higher socio-economic status, and with better health at baseline; for other groups, the effects are insignificant. We also find that more generous programs exhibit larger effects. Our results highlight that living arrangement is multidimensional in rural China.
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China has 2852 county-level administrative areas in 2012.
Several studies investigate the impact of multigenerational coresidence on labor force participation of household members in China. For example, Maurer-Fazio et al. (2011) find that coresidence with elderly parents has significantly increased married women’s participation in market work in urban China. Connelly et al. (2014) show a significant quantitatively important negative effect of coresidence with adult children on the labor force participation of both male and female elders in rural China, but no significant effect on the labor force participation of urban elders.
1 US dollar is about 6.62 Chinese yuan on December 31, 2010.
In practice, the project counties vary considerably in their enforcement of this family-binding requirement. It has been even dropped gradually in some areas. Unfortunately, it is difficult to obtain the precise information about its enforcement at county level. However, it can help explain the low take-up rate among the rural elderly as well as the positive association between program duration and individual pension status in our data. Future evaluation based on additional data would be necessary to specify the benefits and costs of family-binding provisions.
As the life expectancy in 2009 was 71.5 years in China, the average duration of benefits is 11.5 years, or 139 months, for a 60-year old individual.
The replacement rate from the basic pension benefit of the NRPS is lower than those from the social pensions in most OECD countries, which range from 20 to 40% and have a cross-country average of around 30% (Cai et al. 2012).
The annual per capita consumption expenditure of rural households was 3661 Chinese yuan in 2008, and food spending accounted for nearly half of total consumption.
The data can be found in the government report available online: http:// www.mohrss.gov.cn/ncshbxs/NCSHBXSgongzuodongtai/201305/t20130531_104217.htm.
We do not consider the choice to live in a nursing home, because it is rare in rural China.
It is important to note that grand-parenting is also an aspect of multigenerational coresidence in China. Although it can be incorporated in the framework, we cannot empirically examine the implications of this dimension due to data limitation. For this reason, we do not consider grand-parenting here. Moreover, the literature finds that coresidence is largely dependent on elderly parents’ needs rather than adult children’s needs in China (Lei et al. 2015; Bian et al. 1998).
Note that theoretically informal care from adult children is an important health input in health production of the elderly parents, but the effect of coresidence on health of the elderly is inconclusive both theoretically and empirically (Maruyama 2015).
This distrust stems mostly from the previous experience that local governments have consistently imposed a number of taxes and fees on rural residents but misused those funds in the past (Yip and Hsiao 2009).
In the 2011/12 survey, the non-pensioners in the program counties were asked about the reasons why they had no social pension. The primary reasons were “do not know” (about 52%), “cannot afford the payment” (26%), and “not necessary” (20%).
Cai et al. (2012) show that 82.1% of rural migrants are younger than age 40 in 2006.
As nearly all counties had been exposed to the NRPS by the 2011/12 survey, counties that had been exposed for more than 6 months are termed “program counties,” whereas those counties that had not are considered as non-program counties. Our study sample consists of 169 program counties and 189 non-program counties.
It reflects rural-to-urban migration or population loss from the county.
Urbanization, GDP per capita, and government spending per capita reflect the development and urbanization level of the county.
It helps control for geographic variation in health care delivery.
The latest wave of the CLHLS was collected in 2014 and is not available at present.
The newly added sample focuses on younger elderly aged 65–79; of the 1879 respondents in our main sample, 74 respondents were aged 60–65 in wave 2008/2009 and almost all of them (except one respondent) were over the age of 65 in the 2011/2012 survey.
The sample provinces include seven eastern provinces, three northeastern provinces, eight central provinces, and four western provinces, hosting approximately 85% of China’s total population.
We do not include the oldest-old sample in the main analysis, because the oldest-old population is not the focus of the existing literature (besides, there are few oldest-old observations in the existing studies), and their living arrangement may be dictated by health care need instead of economic concerns.
Among those we classify as independent living, 1 person-year observations (0.03% of the study sample) lived with parents/in-laws, and 19 person-year observations (0.52% of the study sample) lived with children under age 15.
We exclude institutionalized individuals because they account for less than 1% of the study sample. The results are very similar when we include them, no matter whether they are classified as living with others or as living independently.
We believe that this is a reasonable measure, as there was no expansion of other social pension programs in rural China during the study period. But we have to acknowledge the possibility of misclassification which can lead to attenuation bias in the estimated treatment effect (Lewbel 2007); to the extent that the bias exists, our estimates provide a lower bound of the effect of the NRPS.
The CLHLS covers a total of 535 rural counties. Due to sample restriction shown in Table A1, the study sample includes 358 counties: 63 (18%) belong to the first-wave pilot counties, 87 (24%) belong to the second-wave pilot counties, and 208 belong to the third-wave pilot counties. The exposed rates are consistent with national data presented in Section 2. Among the 358 counties, 76 had been exposed for over 6 months, 66 for over 1 year, and 27 for over 2 years at the time of survey 2011/2012. The 189 counties that had not been exposed or had been exposed less than 6 months are considered as non-program counties.
We do not know the exact dates of program initiation for each county. As the government made announcements about the first two waves of pilots on 31 September 2009 and 30 September 2010, respectively, we assume that it was October 2009 for the first pilot counties, October 2010 for the second pilot counties. The third wave of pilots rolled out in July 2011. Although our measures of program duration may have measurement errors, we first mitigate this measurement error by discretizing the program duration into three dummies; and second, the official announcement may already affect the behavior of rural households in anticipation of a pension in the near future.
Han Chinese is the majority ethnic group in China and accounts for more than 90% of the total population.
In the CLHLS data, we have the information on total annual household income, but unfortunately cannot distinguish between the income of elderly parents and that of co-residing adult children. Following the previous literature (Engelhardt et al. 2005; Jensen 2003), we exclude the continuous measure of household income due to concerns over endogeneity in the empirical analysis. As a robustness check, we add controls for non-pension household income, and obtain similar results.
Note that it is hard to distinguish between the linear age effect and the linear time trend due to the multicollinearity problem. But the quadratic age effect is robust to the exclusion of time trend. We also find similar results when we control for cohort dummies.
This finding is consistent with Lei et al. (2015) based on the CHARLS national baseline sample. Although unreported here, we find that having more adult children is associated with a higher likelihood of living independently but near adult children. It is probably because there is a potential free-rider problem in caregiving decisions among siblings (Maruyama and Johar 2016). Giles and Mu (2007) also provide some evidence that conflict among siblings over care for the elderly was the third most important source of conflict in rural China.
For example, program and non-program counties may be different with respect to return migration after the global financial crisis in 2008, or to formal elderly care systems.
The sample size of the rural retired may be not large enough to produce a precise estimate. To address this concern, we randomly draw a similar sample size as the rural retired sample from our eligible sample ten times and re-estimate Eq. (3). The results based on the smaller samples (available upon request) are similar to our baseline results in Table 4.
The literatures show that poor health of elderly parents and their care needs have constrained labor migration of adult children (Eggleston et al. 2016). Giles and Mu (2007) find that at least one adult child will either return to the village or choose not to migrate when elderly parents become ill.
Terza et al. (2008) show that the 2SRI estimator is generally consistent in nonlinear models with endogenous regressors. In our application, we estimate the first stage using a linear FE specification and the second stage using a multinomial logit model with fixed effects. The standard errors for the second stage should be adjusted for the inclusion of first-stage residuals. However, bootstrap standard errors could not be computed here, as about 70% of the respondents are dropped due to no changes in living arrangement across waves, and the sample is actually not large enough for the bootstrap to be properly applied.
In an earlier version of the paper, we examined the differential effects of pension income with respect to the presence of adult children living nearby in the baseline wave. Consistently, we find that the income effects are stronger for those with adult children in the same village and insignificant for those without nonresident adult children in the same village at baseline.
Lei et al. (2015) find that children living far away provide more financial support to their parents, suggesting that transfers from children to parents tend to be a substitute for co-residence in China. It is beyond the scope of this paper to explore the impact of the NRPS on private transfer due to data limitation of the CLHLS, but it is an important topic for future research. We do not make a distinction between living with adult sons and living with adult daughters in this analysis, because fewer than 4% of our study sample were living with adult daughters, and this small percentage is consistent with the social norm in China.
Over half of the elderly sample had no education (defined as being illiterate in our study), while those with a high school education or less account for about 48% of the sample, classified as the less-educated elderly by Engelhardt et al. (2005).
We should point out that although the results in Table 7 are consistent with the hypothesis of privacy concern, there may be other rationales as well. For example, better educated elderly may be more independent both financially and psychologically so that the shadow price of living alone is lower.
Ideally, we should use the annual per capita disposable income of rural household in each county; but to our knowledge, there are no complete data publically available in China.
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We would like to express appreciation for comments from three anonymous referees, the editor Junsen Zhang, participants of the 2015 Annual Conference of the Chinese Economist Society, the 29th Annual Conference of the European Society for Population Economics, the 1st World Congress of Comparative Economics, and seminars at Central University of Finance and Economics and Renmin University of China. The collection of the data used in this study was supported by NIH R01 grant (R01-AG023627) and the United Nations Fund for Population Activities. This study was supported by the National Natural Science Foundation of China (Grant No. 71110107025, No. 71173227, No. 71673313, and No. 71233001), the National Social Science Fund of China (Grant No. 13CJY028), and Training Program for Major Fundamental Research of Central University of Finance and Economics (Grant No. 14ZZD001).
The collection of the data used in this study was supported by NIH R01 grant (R01-AG023627) and the United Nations Fund for Population Activities. This study was supported by the National Natural Science Foundation of China (Grant No. 71110107025, No. 71173227, No. 71673313, and No. 71233001), the National Social Science Fund of China (Grant No. 13CJY028), and Training Program for Major Fundamental Research of Central University of Finance and Economics (Grant No. 14ZZD001).
Conflict of interest
The authors declare that they have no conflict of interest.
Responsible editor: Junsen Zhang
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Cheng, L., Liu, H., Zhang, Y. et al. The heterogeneous impact of pension income on elderly living arrangements: evidence from China’s new rural pension scheme. J Popul Econ 31, 155–192 (2018). https://doi.org/10.1007/s00148-017-0655-y
- Pension income
- Living arrangements