The causes of inter-industrial wage differentials have been studied in many countries since the late 1970s. In China, research indicates that inter-industrial wage inequality has increasingly contributed to overall income inequality since 1995 (Chen et al., Social Science in China, 2010). To obtain a comprehensive picture of the causes of inter-industrial income inequality in China, the following question needs to be answered: Who gets to enter high-wage industries? Empirically estimating the factors that can influence a person’s ability to enter high-wage industries is the key to reducing inter-industrial wage differentials. This paper used data from the Chinese Household Income Project (CHIP) database (http://www.ciidbnu.org/chip/index.asp). The urban household surveys used in this research contain 12 provinces, 77 cities, around 7000 households and over 20,000 individuals in both 2002 and 2013.

To identify the high-wage industries, this paper used a logarithmic income regression function to determine which industry pays a higher wage after controlling for productivity and other personal characteristics. The manufacturing industry was chosen to be the base group as this sector hires more people than any other industry in urban areas. If an industry had significantly higher wages than the manufacturing industry, the value for that industry was set to 1. Industries with significantly lower income were set to -1. If the difference was insignificant, then the value was set to 0.

Because the dependent variable was dichotomous, this paper used the ordered probit model to investigate factors influencing entry into high-wage industries. For the explanatory variables, socioeconomic factors that could potentially influence labour market entry were controlled for, like gender, marital status, age, education, working experience, health status, and party membership. To address the unobserved factor of a personal desire for a higher wage, the paper used the ratio of the family’s number of working to non-working people, as one might have a higher incentive to enter high-wage industries in order to put more food on the table. Explanatory variables also included non-productivity-related variables like network, hukou (also known as household registration) and family background. As it is possible for the low-income population to use more networks to find jobs, the education level of the respondents’ father-in-law was used as the instrumental variable to deal with this endogeneity.

It is necessary to provide more explanations for the non-productivity-related variables as they are the focus of this analysis. The effect of having a better personal network was estimated by the dummy variable ‘the way of finding your current job’. The paper classified answers ‘Referred by a family member/relative/friend’ and ‘Inherited it’ as finding the job using a network. These answers imply both the existence of a personal network and the utilisation of this network. Other channels of finding a job, like ‘Recruited from formal process/examination’, were deemed as finding the job in a fair and competitive way, generally. To reduce potential bias caused by omitted variables, the analysis controlled for the respondent’s parents’ education level. The effect of hukou (household registration) was another key variable this research investigated. It is a factor with strong Chinese characteristics as the hukou system has been widely used in China since 350 BC. China is one of the few countries that still use this system extensively. Hukou is a registration system that records the individuals’ information, like date of birth, marital status, and home address, and registers this information in the unit of household. Even though job allocation and the rationing of resources, like food and fabrics, disappeared long ago and people can move freely in China nowadays, the policy’s momentum lingered. Also, there are some implicit benefits to having a local hukou, like lower administrative costs for the firm.

Unbalanced growth in different regions is a typical characteristic of the development of the Chinese economy. Most of the growth happened in the coastal regions, where more resources were concentrated and international transportation costs were lower. The trans-regional comparison shows that the network was twice as important in the middle and west regions as it was in the coastal region in 2002. (Online Supplemental Appendix Table 1) However, in 2013, the coefficient of the network variable increased to 0.0490 in the coastal region and 0.0423 for the middle and west regions. However, the network variable in the IV estimations shows that the coefficient of the network in the more prosperous coastal regions is more than two times higher than that in the middle and western regions. (Online Supplemental Appendix Table 2) The endogeneity of the network was much higher in the coastal regions, where the market mechanism was more mature, implying that marketisation and economic development did not reduce the effect of the network.

Having a local hukou had a coefficient as high as 0.5180 in 2002 in the more developed coastal region, but was insignificant in the middle and western regions. However, in 2013, the coefficient on hukou was only 0.1033 for the coastal regions and 0.0762 for the middle and western regions. Although the difference between richer and poorer still exists, the decrease in the significance level of hukou in the coastal region was pronounced. This trend suggests that the advantage of having a local hukou diminished as marketisation and economic development proceeded.

The policy implication of this research is that breaking down the entry barriers of different industries is a crucial step if China wants to form a fair and competitive labour market and equalise industrial wages. If the non-market factors consolidating the entry barriers can be reduced or even eliminated, then the high income from monopoly industries can be controlled, making inter-industrial income inequality no longer an important source of overall income inequality. Targeted and specified policies need to be implemented to overcome these non-market influences.