| Automobile industry has always been a leading industry in many industrialized countries. After more than 50 years of development history, China's automobile industry has established a relatively complete industrial chain, and becomes a new leading industry which stimulates the macroeconomic growth. In the process of development, efficiency is an interesting research topic. For most of the last century, China's automobile industry developed in an environment which lacked of adequate market competition. Is it true that China's automobile industry is less efficient in this period? Since 2002, a new round development cycle began, the automotive industry sentiment index rose line, did the efficiency of the automobile industry rise too during the period? Which factors have important impact on the efficiency of China's automobile industry?Because of the interesting in above questions, we reviewed the existing literatures about China's automobile industry and found that the research on the efficiency of China's automobile industry was not enough, although many other topics had been covered. And these studies had some drawbacks in the data, empirical models and study methods, such as only using corporate data to estimate industry production function, simple using of the C-D production function without inspection, just using time-series data rather than panel data and using a single research method and so on.We use industrial statistical panel data and a variety of models and methods to research the technical efficiency of China's automobile industry in-deepth and factors impacting the efficiency. After reviewing of the literature, we analyze the status of China's automobile industry, on this basis, selecting the appropriate input and output indicators, collecting the necessary statistical data. Then, we construct the model to do empirical study on technical efficiency of China's automobile industry, using stochastic frontier production function model and data envelopment analysis model respectively. Next, we promote an assumption of factors impacting the technical efficiency, testing and modifying the assumptions through empirical research by using of structural equation model. Finally we come to the following conclusions:In the section of China's automobile industry status analysis, we believe that there are a number of important features in the developing process of China's automobile industry: (1) Merging gradually increased, reflecting economies of scale. (2) The power of China's brands expanded. (3) Industrial chain increasingly improved and China's automobile service industry developed rapidly. (4) China's commercial automobile industry expanded the international market share, with strong international competitiveness.The empirical research on China's automobile industry technical efficiency shows that it is a reasonable assumption that China's automobile industry production function is a trans-log function form, including the technological progress. Since 1992, there is a non-neutral technological progress which means the marginal technical elements alternative rate has a significant change in the China's automobile industry. And there is significant non-efficiency item that changes with time in automobile production process. After further studying the regional distribution of technical efficiency, we come to some important conclusions. (1) China's automobile industry technical efficiency and yield have the similar regional distribution. The provinces which have higher production, such as Shanghai, have higher efficiency than the lower output province, such as Hebei, by 20 percent. But output is not the sole factor which impacts technical efficiency. Because some regions have high efficiency also, as a leader in some segments market, although their production is not high. (2) Before 1994, China's automobile industry had a fairly high tariffs and price controls. Vehicle production was not high, but under the protection of the policy, the efficiency which output is valued using money was still high. In the late 1990s, as the tariffs reduced and market competition intensified, there was a 30 percent decline in average efficiency till 1998. Then, it started to rise from 1998, the efficiency in 2006 reached 0.946, which means that it is possible to increase output by 5 percent, only through improves efficiency. (3) The regional distribution of technical efficiency experienced substantial changes in the past 15 years. Some regions, such as Guangdong, steadily improved efficiency while other regions, such as Tianjin, continued decline in efficiency.Then, we give an assumption that the technical efficiency of China's automobile industry is impacted by five factors: enterprise, industry, market forces, policy, and international factor. After empirical study using structural equation model, we come to the following conclusions: (1) the cost of profit margins and the proportion of R&D personnel has positive relationship with technical efficiency which shows that it is possible to improve technical efficiency through strengthen the management of enterprises and R&D staff input. (2) Foreign direct investment and the amount of import and export for China's automobile industry have a positive effect on technical efficiency. (3) Production focus degree CR5 shows positive impact on the technical efficiency reflecting the economies of scale of China's automobile industry. (4) Further reducing tariffs and other industrial policies promulgated jointly promote China's automobile industry more efficiency after 2002.The main innovation of this paper is that we conducted in-depth research on the efficiency of China's automobile industry and reached some useful conclusions, using more standardize research method. In this paper, we assume China's automobile industry production function is a trans-log form, and through hypothesis testing to validate if the assumption is correct. When select the input and output indicators, we use factor analysis to research the relevance of input indicators. In the empirical study on technical efficiency, we use stochastic frontier analysis and data envelopment analysis at the same time. Meanwhile, we contrast the two results to avoid the estimated error when use a single method. The use of industry statistical panel data also improves the accuracy of the study. Because of the complex factors that impact technical efficiency, our thinking cover the market structure, foreign direct investment, import and export, industrial policy, and other factors. Besides, we use of structural equation model which can dealt with latent variables to began empirical analysis.This paper is just an exploration work and has many deficiencies in theoretical supporfc and data, with limited time and energy. |
PDF Full Text Request