高速鐵路全要素生產(chǎn)率研究
發(fā)布時間：2018-12-11 19:43
【摘要】：近年來,國家大力發(fā)展高速鐵路,時速為200公里以上的高速鐵路運營里程在2020年將會是當前的三倍。高鐵建設(shè)初期需要大量資金注入,建成后的收入很難在短時期內(nèi)償清債務(wù),高鐵的生產(chǎn)率水平直接影響著企業(yè)的償債能力和營運狀況。高速鐵路是普通鐵路運輸技術(shù)進步的體現(xiàn),建成后的生產(chǎn)率趨勢和影響因素分析有利于高鐵運輸企業(yè)降低高速鐵路的運輸成本,能夠有針對性地控制影響高速鐵路生產(chǎn)率變化的因素,提高其生產(chǎn)率。全要素生產(chǎn)率(Total Factor Productivity)是宏觀經(jīng)濟學(xué)的重要概念,該指標能夠觀察到剔除由勞動和資金投入的其他因素給生產(chǎn)率帶來的變化,通過分析能夠得出高速鐵路技術(shù)對產(chǎn)出的影響。 文章介紹了高速鐵路全要素生產(chǎn)率的相關(guān)基本理論,由技術(shù)進步理論引出全要素生產(chǎn)率的概念及其產(chǎn)生與發(fā)展。在確定了高速鐵路投入和產(chǎn)出要素特點及構(gòu)成的基礎(chǔ)上,分析了全要素生產(chǎn)率計算方法在測度高速鐵路全要素生產(chǎn)率時的適用性,最終選擇了生產(chǎn)函數(shù)法、索洛余值法、狄氏指數(shù)法及精確指數(shù)法測度了廣深城際高速列車全要素生產(chǎn)率水平的具體方法,并分析了計算結(jié)果。 研究結(jié)果表明,在高速鐵路建設(shè)和運營初期,樣本和數(shù)據(jù)量較少,應(yīng)選用適合于時間序列數(shù)據(jù)的全要素生產(chǎn)率計算方法,如生產(chǎn)函數(shù)法、狄氏指數(shù)法和精確指數(shù)法。狄氏指數(shù)法和精確指數(shù)法不能夠具體測算出高速鐵路的TFP值,但其計算模型不用對參數(shù)進行分析,能夠直接比較各年高鐵TFP值的變化情況,也能分析各投入要素對TFP值的影響。在高鐵運營形成規(guī)模后,數(shù)據(jù)樣本量巨大,可以選擇數(shù)據(jù)包絡(luò)分析法或曼奎斯特指數(shù)法對高鐵的全要素生產(chǎn)率作進一步的分析,如考慮到隨機因素對TFP的影響,隨機前沿生產(chǎn)函數(shù)法是最佳選擇。高速鐵路TFP值受到資本產(chǎn)出彈性、勞動產(chǎn)出彈性,投入要素價格以及產(chǎn)出量和產(chǎn)出價格的影響,引起TFP值變化的因素還包括如金融危機、自然災(zāi)害、社會活動、國家政策等外在因素。高速鐵路的全要素生產(chǎn)率變化特征可描述為三個時期：迅速增長期,下降期,平穩(wěn)增長期。迅速增長期為高速鐵路投入運營的初期,下降期為運營后的過渡階段,TFP值較初期有小幅下降,在此之后的平穩(wěn)增長期TFP值比較穩(wěn)定并且有小幅增長。 提高高速鐵路全要素生產(chǎn)率,應(yīng)加強新技術(shù)的創(chuàng)新和應(yīng)用,注重資源投入的質(zhì)量和有效性,降低國際不良經(jīng)濟形勢對企業(yè)運營的影響。從產(chǎn)出的角度來說,客運周轉(zhuǎn)量的增加幅度也決定了高速鐵路運輸企業(yè)TFP值的變化幅度,提高客運周轉(zhuǎn)量也是提高TFP值的因素。
[Abstract]:In recent years, the country has made great efforts to develop high-speed railways. The operating mileage of high-speed railways with speeds of more than 200 kilometers per hour will triple that of the present in 2020. At the beginning of high-speed railway construction, a large amount of capital is needed, and the income after completion is difficult to pay off debts in a short period of time. The productivity level of high-speed rail has a direct impact on the solvency and operation of enterprises. High-speed railway is the embodiment of the technical progress of ordinary railway transportation. The trend of productivity after completion and the analysis of influencing factors are beneficial to the high-speed railway enterprises to reduce the transportation cost of high-speed railway. It can control the factors that affect the productivity of high speed railway and improve its productivity. Total factor productivity (Total Factor Productivity) is an important concept in macroeconomics. This index can observe the change of productivity caused by excluding other factors of labor and capital input, and the influence of high-speed railway technology on output can be obtained by analysis. This paper introduces the basic theory of total factor productivity of high-speed railway, and introduces the concept of total factor productivity and its production and development from the theory of technological progress. On the basis of determining the characteristics and composition of input and output factors of high-speed railway, the applicability of total factor productivity calculation method in measuring total factor productivity of high-speed railway is analyzed. Finally, the production function method and Solow residual value method are selected. The Dee exponent method and the exact index method are used to measure the total factor productivity level of Guangzhou-Shenzhen Intercity High Speed Train and the calculation results are analyzed. The results show that, in the early stage of high-speed railway construction and operation, the sample and data quantity are relatively small, so the calculation methods of total factor productivity suitable for time series data, such as production function method, Dixon index method and accurate index method, should be selected. The TFP value of high-speed railway can not be calculated concretely by Dixon index method and precise exponent method, but its calculation model does not need to analyze the parameters, and can directly compare the change of TFP value of high-speed railway in each year, and can also analyze the influence of each input element on TFP value. After the scale of high-speed rail operation, the sample size is huge, so we can choose data envelopment analysis method or Manquist index method to further analyze the total factor productivity of high-speed rail, such as considering the impact of random factors on TFP. The stochastic frontier production function method is the best choice. The TFP value of high-speed railway is influenced by the elasticity of capital output, labor output, input factor price, output and output price. The factors that cause the change of TFP value include financial crisis, natural disasters, social activities, etc. State policy and other external factors. The characteristics of total factor productivity change of high speed railway can be described as three periods: rapid growth period, decline period and steady growth period. The rapid growth period is the initial period of the high-speed railway operation, the decline period is the transition stage after operation, the TFP value is slightly lower than the initial period, and the TFP value of the stable growth period after this period is relatively stable and has a small increase. To improve the total factor productivity of high speed railway, we should strengthen the innovation and application of new technology, pay attention to the quality and effectiveness of resource input, and reduce the influence of the bad international economic situation on the operation of enterprises. From the point of view of output, the increase of passenger transport turnover also determines the change of TFP value of high-speed railway transportation enterprises, and the increase of passenger transport turnover is also the factor of increasing TFP value.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：U238;F532
本文編號：2373116
[Abstract]:In recent years, the country has made great efforts to develop high-speed railways. The operating mileage of high-speed railways with speeds of more than 200 kilometers per hour will triple that of the present in 2020. At the beginning of high-speed railway construction, a large amount of capital is needed, and the income after completion is difficult to pay off debts in a short period of time. The productivity level of high-speed rail has a direct impact on the solvency and operation of enterprises. High-speed railway is the embodiment of the technical progress of ordinary railway transportation. The trend of productivity after completion and the analysis of influencing factors are beneficial to the high-speed railway enterprises to reduce the transportation cost of high-speed railway. It can control the factors that affect the productivity of high speed railway and improve its productivity. Total factor productivity (Total Factor Productivity) is an important concept in macroeconomics. This index can observe the change of productivity caused by excluding other factors of labor and capital input, and the influence of high-speed railway technology on output can be obtained by analysis. This paper introduces the basic theory of total factor productivity of high-speed railway, and introduces the concept of total factor productivity and its production and development from the theory of technological progress. On the basis of determining the characteristics and composition of input and output factors of high-speed railway, the applicability of total factor productivity calculation method in measuring total factor productivity of high-speed railway is analyzed. Finally, the production function method and Solow residual value method are selected. The Dee exponent method and the exact index method are used to measure the total factor productivity level of Guangzhou-Shenzhen Intercity High Speed Train and the calculation results are analyzed. The results show that, in the early stage of high-speed railway construction and operation, the sample and data quantity are relatively small, so the calculation methods of total factor productivity suitable for time series data, such as production function method, Dixon index method and accurate index method, should be selected. The TFP value of high-speed railway can not be calculated concretely by Dixon index method and precise exponent method, but its calculation model does not need to analyze the parameters, and can directly compare the change of TFP value of high-speed railway in each year, and can also analyze the influence of each input element on TFP value. After the scale of high-speed rail operation, the sample size is huge, so we can choose data envelopment analysis method or Manquist index method to further analyze the total factor productivity of high-speed rail, such as considering the impact of random factors on TFP. The stochastic frontier production function method is the best choice. The TFP value of high-speed railway is influenced by the elasticity of capital output, labor output, input factor price, output and output price. The factors that cause the change of TFP value include financial crisis, natural disasters, social activities, etc. State policy and other external factors. The characteristics of total factor productivity change of high speed railway can be described as three periods: rapid growth period, decline period and steady growth period. The rapid growth period is the initial period of the high-speed railway operation, the decline period is the transition stage after operation, the TFP value is slightly lower than the initial period, and the TFP value of the stable growth period after this period is relatively stable and has a small increase. To improve the total factor productivity of high speed railway, we should strengthen the innovation and application of new technology, pay attention to the quality and effectiveness of resource input, and reduce the influence of the bad international economic situation on the operation of enterprises. From the point of view of output, the increase of passenger transport turnover also determines the change of TFP value of high-speed railway transportation enterprises, and the increase of passenger transport turnover is also the factor of increasing TFP value.
【學(xué)位授予單位】：西南交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：U238;F532
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