This study uses the China Household Nutrition Survey (CHNS). CHNS is an ongoing project designed to examine the effects of the health, nutrition, and family planning poli- cies and programs. It currently contains nine panels from 1989 to 2011 and covers around 4,400 households with a total of 26,000 individuals in nine provinces of China. In addition to general household and individual characteristics, the household surveys contain infor- mation on individuals’ labor market outcomes, including labor supply and compositions of earnings. They also keep a record of women’s birth history so that I can monitor the order and sex composition of children. On the community level, the data contain community characteristics such as geographic and demographic information, as well as various sorts of
1White (1992) did not specify how this claim was supported by actual data. I do not find evidence on
infrastructure and social services. The key community-level indicator of OCP is whether there was a relaxation of a second child, and the timing of the relaxation.
Since the relaxation was only released in rural areas, I restrict my sample to married rural women. A woman included in the sample must have already had at least one child, i.e., observations in the years when she did not have children were dropped. And she should not have had a second birth by 1980, hence would be restrained by the OCP. The final sample contains 3840 women with 16351 observations in 181 communities, among which 81 were already relaxed when entering the survey, 38 were relaxed during the survey period and 62 were still not relaxed in 2011.
The main outcomes I examine are women’s time of working and income. Time of working involves both working as wage earners and on farm. The former type involves only non-agricultural activities and being employed on others’ farms is included in the latter type. These two types of working can overlap, i.e. one can both work as a wage earner and a farmer. Women’s income is the aggregate annual income from all kinds of jobs, including income from one’s own farm, and involves all sorts of benefits, either cash or in-kind. However, not all outcomes are observed for all women, and the empirical analysis involves only observations without missing values. The sample size shrinks to 7352 with time of working as wage earners being the outcome, 8302 with farming time and 12023 with income. I check whether the likelihood of missing outcomes is correlated with fertility by regressing an indicator for having missing outcomes on the explanatory variables conditional on a woman working. The likelihood of having missing values in working time (which means both working time as wage earners and farming time are missing) is not correlated with the total number of children or the number of small children. The likelihood of income missing is not correlated with the number of small children either, but negatively correlated with the total number of children. However, since neither income nor the total number of children is of our main concern, this is not a big problem. Appendix 2.A presents these testing results.
missing values in the outcomes. I compare individual characteristics by the number of children ever born and the number of children under six years old for the purpose of the empirical studies. On average, women with two or more children were five years older and obtained one year fewer of education than women with only one child. Labor force participation is defined as a binary variable of currently working or not. There is little difference in this variable between the two groups, suggesting small chances of finding a fertility effect on overall labor force participation. Women with two or more children worked less as wage earners and more as farmers, and earned less than women with only one child. They were also more likely to work in agricultural sectors and less likely in state-owned enterprises. When dividing the sample by whether having children under six, women with small children were younger and more educated, worked less on farms and earned less. However these are unconditional disparities and do not necessarily indicate the causal effect of fertility on differences between the two groups.
To determine a fertility-stopping age for women, I plot rural women’s age distributions at the first, second and last births in Figure 2.1. Since women who had not given birth to a second child by 1980 are considered as being treated by OCP and can present systematic differences from the non-treated ones, I look at the age distributions of two subgroups by whether having a second birth before 1980 as well as the age distribution of the whole population. These figures generally show that age 45 is a critical cutoff for fertility in the sense that women over 45 are highly unlikely to give more births. To be more specific, the 99 percentiles of the distributions of ages at the first, second and last births are 40, 40 and 42. Hence at age 45 more than 99% of women had stopped childbearing.