Total Factor Productivity Of China’s Service Industry Based On Supply And Demand Shocks

The18thCPC National Congress points out that China’s economic developmentshould rely more on domestic demand, especially consumer demand, to rely more onthe modern service industry and strategic emerging industries. At present, vigorouslydeveloping the service industry has important meaning for our strategic adjustment ofeconomic structure. Therefore, identifying the factors that influence the developmentof China’s service industry is the most important thing. The past relying on largeinputs to ensure economic growth is not sustainable. Only when the index to measurethe quality of economic development, Total Factor productivity, becomes a pillar ofeconomic development can we achieve the real transformation of economicdevelopment. It’s same for the service industry. Service Industry’s TFP which decidesthe service industry’s long-term development is an important guarantee for thesustained and healthy development of a country’s service industry. Therefore, it is ofsignificance for China’s service industry to achieve long-term development throughdecomposing and calculating our country’s service industry’s TFP.In this article, we refer to the method of three shocks to calculate TFP which isproposed by Konishi and Nishiyama, combined with China’s actual, to improve theresearch. Through the establishment of the Cobb Douglas model based on the actualproduction and production capacity, we decompose the TFP into demand shocks,supply shocks and other shocks in the production capacity data available. Because ofthe difference between production capacity and actual production are the foundationof our study, and the lack of production capacity date, this paper first to calculate theservice industry’s production capacity index. Through the use of semi-parametricinstrumental variable method proposed by Ichimura, Konishi and Nishiyama tomeasure the capacity utilization rate of growth, we can indirectly calculate the serviceindustry’s production capacity. At the same time, in order to verify the new model’s credibility, we will compare the new model’s calculation results and the traditionalDEA model’s.On the basis of the above research, we calculated the service industry’sproduction capacity, TFP and three shocks respectively. First, by calculating theservice industry’s production capacity we conclude that our country service industrycapacity has not reached the peak at the present and the service industry developmentstill has great potential. At the same time, along with the globalization progress andcloser relationship between various countries, every crisis in the world will producelarge or small impact on our service industry’s production capacity. Secondly, thecalculating results on service industry’s TFP show that service industry’s TFP of ourcountry had been volatile in the sample period. At the first ten years of reform andopening-up, it fluctuated in the low position. It fluctuated in the high position at themiddle of reform and opening-up and more stable in recent years. Finally, from theresults of three shocks we can conclude that our country service industry’s economicgrowth little affected by the supply shocks at present but by the demand shocks andother shocks supply shocks greatly. During the sample period, the supply shocks arerelative stable and other shocks performance for both positive and negative peaks andtroughs alternately. There has been existed positive demand shocks for TFP of China’sservice industry over the sample period. A period of volatility is relatively stable andthe main fluctuation appeared in1992. After that high shock, the demand shock hasbeen stable.The demand shock began to increase steadily after a slight decline in2003.At the same time, in order to verify the new model that we use to calculate theresults reliability, we comprised the results that calculated by the traditionalDEA-Malmquist model with Konishi-Nishiyama model. From the comparison wefound that the growth rate of service industry TFP calculated by the two methods andthe growth rate between technological progress decomposed by DEA-Malmquistmodel with supply shocks decomposed by Konishi-Nishiyama model are almostconsistent in positive and negative direction. This also proves that we useKonishi-Nishiyama model to calculate TFP of service industry is credibility. At the same time, the Konishi-Nishiyama model calculates and decomposes the TFP ofservice industry from the perspective of supply and demand, which helps usunderstand the economic meaning of TFP of service industry and clear the directionand regulatory of future policy.