Research On Total Factor Productivity In High Speed Railway

This paper introduces the basic theories of Total Factor Productivity and leads to the concept, creation and development of the index through the technology advances theory. On the basis of output and input features of High-speed railway, this paper analyzes the applicability of the calculating method of the Total Factor Productivity, chooses the Productivity Function, Solow Residual Method, Accurate Index Method and Dickinson’s Dismantles Index Method to measure the level of Total Factor Productivity in Guangzhou-Shenzhen intercity railway. The results are also be analyzed.High-speed Railway System in our country is developing rapidly in recent years. It’s estimated that from now till2020, the High-speed railway (above200km/hr) mileage will be tripled. At the starting or constructing period, large amount of funds are needed to be injected into such a gigantic transport system and the income after construction can’t pay off all the debt in short time. The productivity level of High-speed Railway System directly influences the debt paying ability and operation conditions of the enterprise. Representing the technological advances of the common railway transport, the analysis on the productivity trends and influencing factors of the High-speed railway system has benefits on decreasing the transporting cost and pertinently controlling the factor which affect the productivity of High-speed railway. Then the productivity will be increased. The Total Factor Productivity is an important concept in macro economy and also an index through which we can observe the change of productivity without the influence of funds and labor. Analyzing this index, we can get the affect on output by the High-speed railway technology.The research results illustrate that at the staring period of construction and operation, because of the lack of the sample and data, we’d better choose the calculating methods which fit the time-series data, such as the Productivity Function, Dickinson’s Dismantles Index Method and Accurate Index Method. The Dickinson’s Dismantles Index Method and Accurate Index Method can’t calculate the High-speed railway’s TFP value directly, but the models can compare the yearly changes of the TFP value and the influence on the value by all the income without analyzing parameter. When the operation scale has been largely extended, there will be large amount of samples and data, thus, we can use the Data Environment Analysis (DEA), or the Malmquist index method for further analysis on Total Factor Productivity. Considering the influence from the random factor, the Stochastic Frontier Approach may be the best choice. The value of TFP is influenced by the input and output elasticity of labor and capital, the price of input factors, the quantity and price of output. Also, the financial crisis, natural disasters, social activities and the policies of nation can affect the TFP value of high-speed railway system. The variation characteristics can be described as three periods:rapid growth period (2007), the decline period (2008-2009), smooth growth (2010-2011). The rapid growth period is the period of initial stage of the Highs-peed railway operation. The decline period is the transition stage after the on-going operation. Compare to the early stage, the TFP value declines slightly, and stays in a stable situation with small amplification in smooth growth period.In order to increase the Total Factor Productivity of the railway system, it’s necessary to enhance the creation and application of new technology. Paying attention to the quality and effectiveness of resource investment and lessening the impact which hit the enterprise because of the bad international economic situation are also helpful. From the point of output, the increasing range of passenger person-kilometers determines the changing range of the value TFP of high-speed railway cooperation. So increasing the passenger person-kilometer is one of the elements which can increase the value of TFP.