4.1 Main empirical framework
The empirical framework used to estimate the main results is the conventional labour supply function; this is extended to accommodate firm characteristics and policies. This framework posits that the natural log of number of hours worked per week is a function of the natural log of the hourly wage rate and socio-demographic variables correlated with hours worked. We distinguish between labour supply characteristics (family income, gender, marital status, communist party membership, hukou status, health and trade union membership) and human capital characteristics (education, age, language proficiency, tenure with the firm, certification, received on-the-job training and feels under pressure to meet deadlines).
One important characteristic that has not received much attention in traditional analysis of working time at the individual worker level is workplace policies or norms (Bryan, 2007). A firm's policies on paid overtime and whether the firm has a trade union will formulate a set of norms around what firms expect. Norms are also related to the types of workers that firms employ. In high-income countries, the ideal worker norm exists among highly educated managers and professionals, with such individuals expecting themselves and others in similar positions to work long hours for years or even decades (Drago et al., 2009). In manufacturing and service sector enterprises in developing countries, though, the ideal worker norm is likely to apply to less educated female and migrant workers who firms will expect to work long hours (Smyth et al., 2012). Hence, the proportion of female staff and proportion of migrant workers that the firm employs is likely to have a significant impact on the organisational culture of the firm and underlying norms governing employer expectations of hours worked.
Bringing this together, we express the natural log of hours worked ln(HW) as a function of the following: the natural log of the hourly wage rate ln(W); labour supply characteristics of workers (LS); human capital characteristics of workers (HC); and firm characteristics (FC). Taking the natural log of hours worked and wages follows MaCurdy (1981). This can be expressed as follows where ε is the error term, reflecting unobserved random factors:
The effect of wages on hours worked is ambiguous and depends on the magnitude of the income and substitution effect. The substitution effect is predicted to exert a positive effect on hours worked in response to a wage increase. The income effect is predicted to exert a negative effect on hours worked in response to a wage increase, assuming leisure is a normal good. If the income effect outweighs the substitution effect, the individual will work less in response to a wage increase; otherwise, the individual will work more.
Human capital characteristics such as education and training relate to differences in the productivity of leisure and work across employees. Age and the square of age may capture variations in preferences for work as well as changes in family responsibilities impacting on hours worked over the course of the life cycle (Li and Zax, 2003).
Of the worker characteristics, we expect that individuals with higher non-wage family income will work fewer hours. Moreover, we expect that females will work fewer hours because of traditional familial responsibilities (see references cited in Maurer-Fazio et al., 2011). Similarly, we expect that workers who are married will be more likely to want to synchronise home time with their partner and, hence, have less flexibility to work longer hours. We expect that those with a non-agricultural hukou will work fewer hours than those with an agricultural hukou. We expect that health status will be positively correlated with hours worked because people in better health will have greater capacity to work longer hours.
The sign on the coefficient for individuals who are members of the Chinese Communist Party is ambiguous. If party membership is a proxy for talent (Bishop and Liu, 2008), individuals who are members of the Chinese Communist Party can be expected to work less because they are more productive and complete tasks faster. Alternatively, party members might work more than non-members if ideology exhorts such individuals to exceptionally high work effort (Li and Zax, 2003). The expected sign on trade union membership is not clear-cut. Studies in Western contexts have found that being a member of a trade union will be negatively correlated with hours worked (see e.g. Bryan, 2007). In China, trade unions have traditionally played a subordinate role in resolving labour disputes and have typically acted as a mediator between employer and employee rather than as a representative of labour.
Among the firm characteristics, we expect that firms that employ a higher proportion of females and/or migrant workers will have norms of longer working hours over and above individual characteristics (Smyth et al., 2012). However, the effect of union presence in the firm on hours worked is unclear. Perloff and Sickles (1987), Earle and Pencavel (1990) and DiNardo (1991) all found that unionisation reduces the number of hours worked in studies with US data. As mentioned earlier, unions in China have played a different role than in the West. Finally, the expected sign on paid overtime is also unclear. If firms pay overtime, this might mean that employers will work longer hours because they are responding to the monetary incentive to do so. Alternatively, if firms pay overtime, this may indicate better labour management practices more generally (Seo, 2011). If so, such firms may be better able to schedule their workload and reduce excessive overtime, hence reducing hours at work.
Because the survey did not contain data on the hourly wage rate, the only way to obtain a measure of this variable was to divide reported monthly earnings by the monthly number of hours worked. Deriving the wage rate in this manner means that any errors in the measurement of monthly hours worked would be repeated in the derivation of the respondent's wage rate. Hence, estimation of Equation (1) using ordinary least squares (OLS) results in a spurious, inverse correlation between measurement errors in the wage rate and the error term (Hall, 1973; Schultz, 1980). The spurious correlation biases the estimate of the wage correlation downward (Killingsworth, 1983). To overcome the problem of biased and inconsistent estimates using OLS, a standard approach is to use instrumental variable estimation (IV) made popular by Hall (1973). The practical difficulty with IV estimation is finding an instrument or set of instruments that are significantly correlated with wages but also orthogonal to the residuals of the main equation (hours worked).
The existing literature relies mainly on worker characteristics for IVs that are normally excluded from the hours worked equation, such as higher order terms of age or education and age interacted with education (Chau et al., 2007; Fortin and LaCroix, 1997; Li and Zax, 2003; Mroz, 1987; Sahn and Alderman, 1996). We used the square of years of schooling and age interacted with education, which are common IVs in hours worked equations.
It should be noted that components of non-wage family income are also potentially endogenous. For instance, transfer payments from the government or from individuals outside the family may depend on hours worked (Li and Zax, 2003). To address this issue, Li and Zax (2003) use lagged values of non-wage family income to instrument for current non-wage family income. However, we do not have this information for our data set or other appropriate IVs for non-wage family income. Thus, while recognising the problem, we follow Sahn and Alderman (1996) and treat non-wage family income as being exogenous.