On The Measurement Of Excess Industrial Capacity In China

Since1990s, the economy of china has entered a stage of steady rapid growth, the capacity of social supply has significantly increased, the number and types of products greatly enriched. But with the rapid growth of economy, excess capacity problem has become one of the bottlenecks which hind economic development. China has experienced twice large-scale overcapacity during1998-2001and2003-2006, and has been experiencing another overcapacity which started in2008. The fields of overcapacity have gradually expanded, the influence period has gradually extended, and the harm level has gradually deepened, which severely restrict the stable and healthy development of national economy. In this condition, excess capacity problem has gradually become one of focus that Chinese macroeconomic administration authorities and theoretical circles both concern.The theoretical circle in china has begun to discuss and research the problem of excess capacity in later1990s. The core research content includes the definition of the overcapacity, the qualitative analysis and quantitative measurement of overcapacity level, the manifestations and consequences of excess capacity, the formation mechanism and countermeasures of excess capacity, while the quantitative measure of excess capacity degree is the core and foundation of the overcapacity problem study. Understanding of the meaning of excess capacity in academia circle can be divided into two angles:the perspective of production capacity and the perspective of market demand. With regard to the measurement methods of excess capacity, there has qualitative analysis and quantitative analysis, the method qualitative analysis has a certain degree of subjectivity and inaccuracy, while the quantitative analysis compensates for the qualitative analysis, making the analysis results objective and accurate. Currently the widely used quantitative analysis include:Peak method, the production function method, data envelopment analysis, structural vector autoregression method, but there isn’t a quantitative analysis which has been recognized as the best.Structural vector autoregression method assumes that the level of output is affected by the disturbance of two factors, which are supply disturbances and demand disturbances, and there is no correlation between these two kinds of disturbance factors. Supply disturbances have long-term effects on output levels, determining the potential level of output, while demand disturbances only have short-term impact, determining the level of the output gap. It can be seen from the assumed model that this method has a better theoretical basis of economics, and to measure overcapacity based on this method is persuasive. In this paper, we use the SVAR model applied to long-term constraints which is proposed by Blanchard and Quah (1989),learning from the research findings of Dergiades and Tsoulfidis(2007), establish a SVAR model includes fixed asset investment in industrial enterprises, the main business income and credit flow to estimate the extent of excess industrial capacity, and the model estimated results are verified. Estimates showed that SVAR model can measure the degree and trends of excess capacity in China. Finally, this paper analyses the policy implications of capacity utilization. Capacity utilization is the key indicators to identify overcapacity, which has good policy implications. First, capacity utilization is a important reference index of macroeconomic decision; Second, capacity utilization will guide companies to make rational investment; finally, capacity utilization has a warning function on inflation pressures. However, capacity utilization is not a sufficient condition for the determination of excess capacity. Overcapacity recognition is a systematic project, with multiple indicators should been taken into account.This paper try to build SVAR model contain three variables to measure industrial capacity utilization in China, which has a certain degree of innovation in the measurement methods of capacity utilization, and enriching the measurement methods of capacity utilization in China, but there are still some deficiencies in the model building and variable chosen. Apart from the influence of main business income and credit flow, the fixed assets investment of enterprise is also influenced by tax policy. If these factors have greater influence to enterprise’s fixed assets investment, it will affect the accuracy of the estimation result of capacity utilization. Excluding the impact of other factors, estimating the capacity utilization rate more accurately is the direction of future research.In addition, we use the estimate results of SVAR model as the variation of capacity utilization, it is necessary to determine the initial value to estimate the absolute amount of production capacity utilization.This paper is divided into five chapters, the chapter1is introduction, it mainly introduces the background and significance of this title, reviews the research literature of the definitions and measurement methods of excess capacity, and analyzes the structure arrangement and the innovation of this paper.The chapter2presents the theory connotation of overcapacity, and analyzes the research perspective of excess capacity. Studying the measurement method of capacity utilization in academia systematically, it analyzes the advantages and disadvantages of various kinds of measurement.The chapter3analyzes the three massive excess capacity in China, summarizing the characteristics and causes of previous excess capacity, it obtains the qualitative judgment on the overcapacity, and lays the foundation to the later estimated results of capacity utilization.The chapter4builds SVAR model include industrial enterprise fixed assets investment, prime operating revenue and credit flow to estimate the capacity utilization of China, estimating results can reflect the three times of excess production capacity in China roughly, which show the applicability in estimating macro capacity utilization of SVAR model.The chapter5is the conclusion and policy suggestions. It analyzes the relationship between capacity utilization indicators and overcapacity, and elaborates policy implications of capacity utilization.