A Study On The Current Situation And Influence Mechanism Of Income Gap In China

It has been 30 years since the reform, and China’s economy and resident living standard have largely improved. But at the same time, income gaps have been growing too. The income inequality in urban and rural areas, industries, and regions has become one of the prominent structure features of our economic development. From 2010 to 2014, income distribution system reform has been mention in the Government Work Report for five consecutive years. In 2013, National Development and Reform Commission, Ministry of Finance, and Ministry of Human Resources and Social Security cosigned “Some Opinions on Pushing Forward Income Distribution System Reform”. Since the issuance of the policy, resident income gaps have shrunk slightly, but are still on a very high level. The high salaries of monopoly industries and the parallel endowment insurance systems are still being criticized, and the policy is not as effective as it should. Basing on the background mentioned above, this paper discusses resident income differences, digs into the reasons and influence mechanism of the differences, and searches for solutions and improve measures on policy level. This research is important for China’s income distribution policies, economic structure reforms, and socialist society harmony.Standing on the shoulders of domestic and foreign researchers, I study the following 3 subjects: 1. Current domestic employee structure and industry income gaps, and their trends in the recent past; 2. The differences in employee structure, work intensity, and industry income gaps between China and USA; 3. The influence of industry, government macro-control, and ideology on industry income gaps.There are 8 chapters in this paper. The first one is introduction, which introduces the background and choosing of the subject, and identifies the research method, structure, innovations, and difficulties. The second chapter includes income distribution theories and systems, as well as domestic and foreign research results. To set up a foundation for the subsequent study, the chapter reviews major income distribution theories since classical economics, China’s income distribution systems since the 1978 reform, and domestic and foreign studies on industry income gaps. Chapter 3 is about China’s employee structure and industry income difference condition and trend. After identifying the industry classification and statistic scope, the chapter analyzes the current situations and trends of China’s employee structure and industry income gaps. Gini coefficient is used as the measurement index of industry income gaps. The chapter discusses the influence on Gini coefficient from weighted employee number, urban private company employees and self-employed people, and industry classification etc. Chapter 4, the employee structure and industry income gaps comparison between China and USA, analyzes the difference between China and USA in employees’ industry structure, labor intensity, and industry income gaps measured by Gini coefficient. Chapter 5, 6 and 7 are about the causes of the industry income gaps. Chapter 5 takes industry for instance and select industry attribute indicators base on their influences on industry income gaps. The result is corroborated through an industry income difference influential model established on panel data of 39 industries from 2005 to 2008. Chapter 6 mainly focuses on the influence of market entry threshold policy and price control to discuss the influence from macro-control. Chapter 7, the influence of enterprise ownership, identifies the relationship between enterprise ownership and industry income gaps, and looks for the reason why state ownership influences industry incomes. Chapter 8 is the result and suggestions, which summarizes the research and suggests on how to decrease industry income gaps.The key conclusions are as follows.In 2013, 55.7% of the urban employees are state-owned entity employees, and 44.3% are from private enterprises or self-employed. Private and self-employed sectors are the main force of job creation. Most of the new employees from 1996 to 2013 were employed by private enterprises self-employed. Manufacture industry had the most employees in all urban employees. The second and third ones were whole-sale and retail industries, which together stand 48.2% of all urban employees. The rest of the employees were mainly from construction industry, education industry, government departments, and social organizations. Urban employee structure changed with economic environment. Real estate related, IT, wholesale and retail, accommodation and restaurant, rental, and business service industries developed in high speed, while resource and transportation industries and government departments were expanding on a relatively slow pace. In health, social security, social welfare, and education, employee increasing speeds were below average, indicating that the government budget on education, health, and social security was still not enough. The 1996-2011 average urban salary compound growth rate was 13.5%, 0.3% higher than that of GDP, 12.1% if inflation excluded. Comparing with GDP, the average salary fluctuated less and resists cycles. The difference between the highest and lowest industry average salaries has been growing since 1996, peaked in 2006, and has been shrinking for 7 consecutive years since 2007. The more segments an industry had, the bigger the difference was. State-owned entity average salary was higher than private enterprises’. 2009-2013, the ratio of urban private enterprise and state-owned entity average salaries were 56%, 57%, 59%, 61% and 64%。respectively. The difference between the two was smaller in construction and accommodation industries, and bigger in manufacture, transportation, storage, wholesale, retail, rental, and business service industries.1996-2009, the average Gini coefficients weighted by urban employee numbers showed that industry income gaps were expanding in general. The only two shrinkages of the gaps happened in 1998 and 2003. The Gini coefficient reached its peak at 0.1379 in 2009, and dropped from 2010 to 2013. The 2013 Gini coefficient was 0.1181, 14.4% lower than 2009’s, but still 30.2% higher than 1996’s. The employee volume difference of different industries lessened industry income gaps. The normal average Gini coefficients, employee volumes not considered, fluctuated in the same way as the weighted averages, but were 30% to 40% higher. Industry income gaps would be underestimated if only state-owned entities and self-employed people were counted or if industry segments were not considered. Calculated in the same model, the Gini Coefficients average would be 20% to 25% higher with private enterprises than without, and the 2005-2008 Gini coefficients average would be 40% to 50% higher with industry segments than without.China’s employee industry structure, labor intensity, and income gaps are different from USA’s. Take industry structure for instance, USA employees are mainly in tertiary industries such as education, health care, finance, and business service etc. China’s are mainly in manufacture and low level service industries.Evidently, China’s employee labor intensity was higher than USA’s. In USA, the average work week was 34-35 hours. But in China, the number peaked at 47 hours in 2010. Even the lowest in 2008 was 44.6 hours. Averagely, the week was 33% longer in China than in USA. Also, the inequality of different industry salary per hour was 61% worse, and the number was 25% if averaged in total. The reason why the number was smaller when averaged is that employees were more evenly distributed in industries in USA, and employee volumes were bigger in medium salary industries in China. I based my calculation on annual average salary, compared it with salary per hour, and took industry labor intensity into consideration. The results indicated that the income inequality among industries was decreasing in both China and USA. The difference between them was only 10%. In USA, labor intensity was higher in industries with better salary per hour, and the labor intensity difference further increased the income gaps. But in China, labor intensity was higher in industries with lower salary per hour, and the labor intensity difference therefore decreased the gaps.Industry category, government macro-control, and enterprise ownership have influences on industry income gaps, but of different importance levels, and in various ways and mechanisms.In for-profit industries, industry differences are the most important and direct factor in income gap causes. First, different industries have different cost structures and yield curve. Second, Different industries are in different phases of the cycle. The different supply and demand patterns and competition environments result in different profit and develop potentials, and further cause income gaps among industries. Specifically speaking, capital intensive industries pay higher salary than labor intensive ones do; fast expanding and mature industries pay higher than starting or decaying ones; stable competition environment industries pay higher than competitive ones.Government macro-control mainly influences industry income gaps by changing industry conditions, thus it is an in-direct factor. On one side, government sets up industry entry thresholds to control new company quantity, total supply volume and competition environment, which keeps the industry profit high, and enterprises able to afford salaries above average. On the other side, it controls interest rates and prices of specific products, such as agriculture products, to influence upstream and downstream industries’ profits, which eventually has effects on different industries’ employee incomes.As one of the influencing factors of industry income gaps, enterprise ownership is China’s unique factor. Same as macro-control, it is also an indirect factor. The fundamental reason why enterprise ownership has effect on industry income gaps is that state-owned enterprises and governments have unspoken relationship. Government sets up biased entry thresholds for state-owned enterprises, so industries with government entry thresholds and stable competition environment mostly are crowded with state-owned enterprises. On the other hand, state-owned banks more or less prefer state-owned enterprises in loans, and offer more favorable amounts and interest rates, which results in the finance cost difference between state-owned and private enterprises. Another important reason why ownership influences income gaps is that state-owned enterprises have the problem so-called “owner displacement”. These enterprise managers tend to increase employee salaries to win their support and obtain promotion opportunities.In the factors causing industry income gaps, reasonable factors include industry structure changes, different phases in the industry life cycle, and different yield curve; unreasonable factors include entry thresholds set up by the government to interfere with competition environments, price limits influencing upstream and downstream industry profit levels, commercial banks’ preference in loan approval that causes finance cost difference, the “owner displacement” phenomenon that deviates the enterprise from pursuing maximum profit, and the parallel pension systems that create income inequality between enterprises and state-owned entities.To decrease industry income gaps means to change the unreasonable factors that influence industry income gaps. To be specific, it includes: 1. removing entry thresholds for private enterprises in most of the industries; 2. pushing forward interest rate market reform; 3. improving market price system and reduce government interference; 4. establishing modern enterprise systems in state-owned enterprises; 5. building a professional skill training system for economic structure reform.This research stands out in three ways. First, data and material are consecutive and complete. Different from earlier researches on urban employees, this research covers private enterprises and self-employed people and provides a more complete database, which more accurately reflects the actual industry income gaps. When the industry income gaps were being analyzed, factors such as industry segments, private enterprises and self-employed people, as well as industry employee numbers were applied to breakdown the result and trace the cause. To eliminate the discontinuity in the data before and after 2003, GBT4754-94 industry classification was reorganized according to GBT4754-2002 classification. Second, China’s industry income gaps are studied in comparison with USA’s. Industry labor intensity and employee industry structure differences between China and USA are presented in 4 dimensions: average salary per hour; average salary per hour weighted by industry employee volumes; average annual salary; average annual salary weighted by industry employee volumes. The conclusion that labor intensities and employee industry structures in China and USA have opposite effects on income gaps is useful in practice. Third, this research establishes a multi-level industry income gap cause system, dividing causes into two categories: direct causes and indirect causes. Factors related to industry attributes are the former; else are the latter. Indirect causes influence income gaps by changing industry attributes. The analysis on how indirect causes such as government macro-control and enterprise ownership influence income gaps by changing industry attribute, a direct cause, is supported by massive industry and enterprise cases. In the multi-level system, reasonable factors and unreasonable factors are identified for policy makers. Policies would be more effective if they focus on the unreasonable factors of the industry income gap causes.