Research On The Effects Of Network Infrastructures On The Growth Of TFP

With the fast development of economy of China, Infrastructures especially network infrastructures improve continuously. Until the end of 2012, China had a traffic mileage of road of 4237.5 thousand kilometers, and the traffic mileage of expressway was 96.2 thousand kilometers. Both of traffic mileage of road and traffic mileage of expressway rank the first in the world. The traffic mileage of railway was 97.6 thousands kilometers, ranking second in the world; and the traffic mileage of high-speed rail was 11 thousand kilometers, ranking first in the world. Communicaitons infrastructures have improved constantly, and the business volume of post and telecommunications has increased continuely. China’s post business volumes were 568.1 billion yuan. There were 7.074 billon letters,68755 thousand packages,154017 thousand newspapers and 5.685 billion expressages in post business. China’s telecommunication business volumes were 3621.179 billion yuan. The number of mobile and fixed phone users were 1.112 billion and 0.278 billion, and the internet access number was 0.567 billion. Advanced construction of network infrastructures was regarded as one of the important reasons of China’s economic miracle.In theory, the economy of China can keep high-speed development in such a long time, the total factor productivity (TFP) which is the source of long-term sustained economic growth must increase rapidly. And if the development of network infrastructures prior to the economic development is one of a reason for China’s economic miracle, there must be exist close relationship between TFP’s growth and network infrastructures. However, the research conclusions of existing literature which study the relationship between network infrastructures and TFP’s growth were different. Some research conclusions showed that network infrastructures had significant positive effects on TFP’s growth, while other research conclusions showed that network infrastructures had no effects or negative effects on TFP’s growth. Except there were differences in the theoretical basis, study sample and method of measurement, in my opinion, there are three important reasons for this phenomenon. Firstly, existing literature ignored the spatial spillover effects of network infrastructures on TFP’s growth, or studied the spatial spillover effects of network infrastructures, but most of these studies had inaccurate use of spatial econometric model panel. Secondly, existing literature ignored the effects of quality improvement of network infrastructures on TFP’s growth. Thirdly, existing literature which studied the effects of network infrastructures on independent R&D and international R&D technology spillover which are the important content of TFP’s growth ignored the threshold effects of network infrastructures. For these reasons, it is hard to avoid there were difference between the study results of existing literature which studied the relationship between TFP’s growth and network infrastructures and the reality of the situation. Using various econometric models, this paper studied the local external effects, spatial spillover effects, quality improvement and threshold effects of network infrastructures on TFP’s growth in economic growth theory, new economic geography theory and international trade theory. Then we can understand the mechanism of action of network infrastructures on TFP’s growth fully and deeply. So the reasonably effective theory basis can be provided to the investment policies of government of network infrastructures.This paper had seven chapters, specific arrangements as follow:Chapter one is introduction. This part introduced this paper’s research background and significance, research idea and contents, research methods, main innovations and definition of concept of study objects.Chapter two includes theory review and literature review. This part clarified relevant economic theory, and sorted out existing literature. So the pointcut of this paper can be sure, and the theoretical basis of empirical analysis can be provided.Chapter three analyzed the development of network infrastructures and its effects on TFP’s growth. This part described the development of network infrastructures from reform and opening up. We can see the cumulative investment, stock and quality of network infrastructures present rising trend all the time. Then this part comprehensive analyzed the mechanism of action of network infrastructures on TFP’s growth, in order to provide theoretical basis for empirical analysis.Chapter four analyzed the spatial spillover effects of network infrastructures on TFP’s growth. Firstly, this part calculated the TFP’s growth of each province in China from 1985 to 2012 by using method of DEA-Malmquist index of productivity. We can see the average rate of TFP’s growth was 4.2% in our country, which contributed 42.08% for economic growth. Specifically, the average rate of technology efficiency’s growth was 0.3%, which contributed 3.01% for economic growth. The average rate of technology progress was 3.9%, which contributed 39.07 for economic growth. Technology progress was the main motivation for TFP’s growth. The TFP’s growth, technology efficiency’s growth and technology progress of east region were greater than these of central region and west region. Then this part built spatial durbin model (SDM) based on model of Hulten in 2006, and tested the local and spatial spillover effects of network infrastructures on the TFP’s growth and its decomposing indexes using provincial panel data from 1985 to 2012. The results find that:Local transportation infrastructures had positive impact on improving local technology efficiency, while local information infrastructures had positive effects on both local technology efficiency’s growth and technology progress. The marked negative spatial spillover effects of other provinces’transportation infrastructures had been found on local technology efficiency’s growth and technology progress. On the contrary, other provinces’ information infrastructures had significant positive spatial spillovers on local TFP’s growth. The existing of spatial spillover effect reminded local government to pay attention to other regional governments’behaviors before making policies. Under the condition of keeping optimal size of network infrastructures, local government also need to make some initiative adjustments to ensure continued growth of TFP.Chapter five analyzed the effects of quality improvement of network infrastructures on TFP’s growth. Railway speed-up is deemed as quality improvement of transportation infrastructure. Using data of city-level from 1994-2006 and propensity score matching model (PSM), this part tested the effects of railway speed-up on the growth of total factor productivity (TFP) of cities along the three railway which took the lead in speeding up. The results find that railway speed-up had positive effects on the TFP of cities along the railway. Specifically, railway speed-up mainly improved technology progress and then promoted the growth of TFP. The effect of railway speed-up on technology efficiency’s growth was not remarkable statistically, but the average treatment effect (ATT) form negative become positive as time goes on. This illustrates that railway speed-up had a certain spillover effect on technology efficiency’s growth.Chapter six analyzed the mechanism of action of network infrastructures on independent R&D and international R&D technology spillover. The purpose of this part was analyzing how the network infrastructures indirectly affect the TFP’s growth through affect independent R&D and international R&D technology spillover. Firstly, this part analyzed the effects of network infrastructures on independent R&D and international R&D technology spillover in theory, and pointed out that the difference in scale of network infrastructures of different regions may cause the difference in independent R&D capacity and international R&D technology spillover effects because of threshold effect. Then based on the model of Coe and Helpman in 1995, this part tested the spillover effect of independent R&D capital and international R&D capital on the total factor of productivity (TFP) using panel data model of province-level from 1994-2012. The result showed that the independent R&D capacity and the technology spillover effect of international R&D had significant difference among every province. Using panel smooth threshold regression (PSTR) model with network infrastructures as the threshold variables, this part measured the threshold characteristics of network infrastructures which caused the change of the innovation capacity of independent R&D and the technology spillover effect of international R&D. The existing of threshold effect was verified. It was also can be learned that every province should strive to develop and improve information infrastructures, at the same time developing transportation infrastructures according to actual condition of themselves.Chapter seven includes the study conclusions of this paper, policy advices and study prospect. This part summarized the results of theoretical and empirical analysis. Based on these results, this part gave some significant policy advices. Finally, this part pointed out the shortcomings of this paper and the orientation of further study.There were several innovations in this paper:Firstly, this paper expanded the theoretical model of Hulten through introducing other provinces’ network infrastructures. Using this expanded model, this paper comprehensively analyzed the local and spatial spillover effects of network infrastructures on the TFP’s growth through building SDM. Decomposing TFP’s growth into technology efficiency’s growth and technology progress can understand the mechanism of action of network infrastructures on TFP’s growth deeply compared with existing literature.Secondly, on account of the shortcomings that existing literature ignored the effects of quality improvement of network infrastructures on TFP’s growth, this paper analyzed the effects of quality improvement of network infrastructures on TFP’s growth through taking the three railways which took the lead in speed-up as study objects. Meanwhile, this paper used PSM can effectively reduce the selection bias because railway speed-up can’t be regarded as random experiment.Thirdly, this paper analyzed the mechanism of action of network infrastructures on independent R&D and international R&D technology spillover for the first time, and pointed out network infrastructures can improve independent R&D capacity and international R&D technology spillover effects. Because the character of net of network infrastructures appears only when the scale of network infrastructures reach a certain size, this paper pointed out there were threshold effects of network infrastructures on the TFP’s growth, and verified by using PSTR. This supplemented the theoretical system of study independent R&D capacity and international R&D technology spillover effects.