Differences In Employment Quality In China's Urban Labor Market: Empirical Analysis And Theoretical Improvemen

According to the seventh census,63.89% of the total population lives in urban areas.Compared with 2010,the proportion of urban population increased by 14.21 percent.In the past decade,China’s urbanization rate has increased rapidly,and the migrant population has increased substantially.China’s urban labor market shows some new characteristics.First of all,the urbanization rate is increasing,while the migrant population is increasing.As a result,the proportion of migrants flowing to cities and towns is increasing.At present,citizenization of migrant population has become an important task in urbanization.Statistics show that the income gap between urban local workers and migrant workers is gradually narrowing.However,there are still great differences between migrant workers and local workers in labor intensity,employment stability and social security status.The employment quality gap between the migrant population and the local population not only affects the living conditions and quality of life of the migrant population,but also relates to their sense of acquisition and belonging.And then it has an impact on the process of urbanization.Secondly,informal employment is an important channel for rural migrant workers to enter urban areas.Informal employment plays an important role in alleviating urban unemployment and absorbing rural surplus labor.However,the wage level of informal workers is significantly lower than that of formal workers,and informal employment is less stable and lacks social protection.Such inequality will act as a brake on urbanization.Considering China’s national conditions,this paper carries out empirical analysis on the employment quality difference between local population and migrant population,as well as the income gap between formal employment and informal employment.In labor economics,the difference decomposition method is a classical empirical analysis method to study the differences between different types of labor groups.Including Oaxaca-Blinder decomposition(Oaxaca,1973;Blinder,1973),and FFL decomposition(Firpo et al.2018).However,these two decomposition methods have some limitations when applied to practical research.Taking the income of laborers as an example,there may be outliers in the sample data at both ends of the income distribution,and there may also be abnormal features in some quantiles of the income distribution.In this case,when the Oaxaca-Blinder method is used for mean decomposition of the full sample,it is affected by abnormal samples.When the FFL method is used to decompose the quantile,the abnormal features of the quantile will lead to a large deviation.This paper presents a RIF decomposition method on quantile interval of dependent variable.This method improves the limitations of previous decomposition methods in overcoming data defects.On the basis of sorting out the relevant methods of difference decomposition and reviewing the literature on difference in China’s urban labor market,this paper makes the following theoretical improvement and empirical research.In chapter 3,this paper proposes a new method of distribution decomposition,which is used to decompose the wages differences or changes in different positions of distribution.This paper extends the decomposition method of FFL(Firpo et al.,2018)to the decomposition of the interval of the distribution.I derive the outcomeconditioned recentered influence function(OC-RIF)and complete the decomposition by the OC-RIF regressions.Traditional Oaxaca-Blinder decomposition cannot investigate heterogeneity and is susceptible to the outlier data.And the decomposition of FFL on quantile is very sensitive to quantile position.The OC-OB decomposition proposed by us are more robust and can reveal the heterogeneity characteristics.The results of numerical simulation and empirical data analysis show that the standard deviation of decomposition terms is significantly lower than that of FFL quantile decomposition,which effectively improves the efficiency of inference.In chapter 4,based on CFPS data,this paper constructs an employment quality index system from four dimensions: employment income,employment environment,employment security and employment feeling.The employment quality of migrant population and local workers is analyzed and decomposed.The results show that the employment quality of migrant population is significantly lower than that of local population,and the gap between rural-urban migrant population and local workers is large and increasing year by year.The employment quality gap between urban migrant population and local workers is small.The inter-group gap in employment quality is mainly reflected in employment environment,employment security and employment feeling,while the difference in employment income is not significant.The difference between local population and migrant population is mainly caused by the difference of middle employment quality.The human capital factor is the main reason for the difference between groups,but there is also obvious separation between regional household registration,which is most obvious in the ownership choice of workers.This study provides empirical experience for migrant population policy system.In chapter 5,I analyze the labor income gap between formal and informal workers,paying special attention to the impact of the development of digital inclusive finance on workers’ income and the inter-group income gap.Using the traditional method and the improved difference decomposition method,I examine the impact of the development of digital inclusive finance on the income gap between formal and informal employment.The results show that there is a significant income gap between formal employment and informal employment,and the income gap among lower income workers is the main source of the income gap between formal employment and informal employment.The development of digital inclusive finance has a significant promotion effect on the employment income of workers,and its increasing effect on the income of informal workers is greater than that of formal workers.This is mainly reflected in the impact of coverage breadth and depth of use.The development of digital inclusive finance plays a positive role in narrowing the income gap between formal employment and informal employment,which is increasing year by year.Using the distribution decomposition method,it is found that digital financial inclusion has a greater convergence effect on the low-income range.This will help to narrow the income gap between formal and informal employment and achieve inclusive growth.Mechanism analysis shows that digital inclusive finance reduces the income gap by promoting employment,entrepreneurs’ income and workers’ financial literacy.The above research results reveal the new characteristics of employment structure and the new trend of income distribution in the context of the development of digital inclusive finance.To sum up,in terms of theoretical improvement,this paper optimized and improved the difference decomposition method commonly used in labor economics.Combined with the actual application scenarios,the methods are demonstrated to expand the theoretical tools of decomposition.In the empirical aspect,firstly,this paper focuses on the difference of employment quality between migrant workers and local workers in urban labor market.This article has carried on the reasonable measure to the employment quality,and has carried on the characterization to the employment quality present situation.Through the use of a variety of traditional decomposition methods to analyze the causes of employment quality gap.This clarifies the net impact of different household register on employment quality gap.It also provides a new perspective for evaluating the effect of China’s migration policy.Then,this paper analyzes the impact of digital inclusive finance on the income gap between formal and informal employment.These studies have enriched the research scope of the economic effects of digital inclusive finance development and expanded the related research on the income difference between formal employment and informal employment.