Estimation And Decomposition Of Total Factor Productivity Growth In Shandong And Henan Province: A Comparison

As a significant indicator for the quality of regional economic growth, total factor productivity (TFP)has gradually become the focus of research in growth theory since World War II. In the tide of reform andopening up, Shandong and Henan, two Northern provinces of P. R. China, has both experienced rapideconomic growth, but the sustainability of their growth model is quite questionable. Besides, economicgrowth has distinct characteristics in different municipal regions. Then, what factors promote regionaleconomic growth and what constraint it, is the major concern of this thesis.After a brief review of growth theory and TFP empirics, an analytical framework is formed byextending Lucas model to capture the human capital spillover effects, as well as the impact ofenvironmental factors on regional economic growth including urbanization, export, governmentexpenditure, etc. Empirical study is applied to the statistical data of Henan and Shandong Province. TheSolow residual approach and the translog stochastic frontier model are applied to economic output andinput factors of provincial and municipal data respectively to estimate the TFP growth in each region,and to recognize the contribution of each environmental factor to economic growth using the regressionresults. For municipal data, TFP growth is further decomposed into technical progress, technicalefficiency change and scale efficiency change.The empirical results show that:Firstly, the two provinces share many identical characteristics in economic growth. In bothprovinces, the average annual growth rate is higher than the national level and their trends of fluctuationare much the same. Growth in both provinces are evidently driven by fixed assets investment with a decrease of labor share in the relative contribution to economic growth, while the contribution of TFPgrowth is not very satisfactory. Specifically, in the era of1978-2011, more than60%of economic growthis pulled by the increase of fixed capital, and the proportion is still in an upward trend, signifying thatboth provinces are in the stage of accelerating capital accumulation. The amount of labor explains nearly10%of economic growth, and the labor quality explains about6%. Although human capital has positivespillover effect, its contribution is in a downward trend. After deducting the direct contribution of humancapital, the average annual growth rate of TFP in both provinces is around3%.Secondly, the quality of economic growth in Shandong Province is higher than in Henan Province.Judging from the economic growth rate, Shandong Province grows faster and more stable, HenanProvince, on the other hand, is more vulnerable to economic fluctuations. Judging from the pace ofcapital accumulation, the annual growth in Shandong Province is more balanced, with a standarddeviation of2.86, which is4.39in Henan. In the three periods, the average annual growth rate of capitalin Shandong Province were11.7%,13.7%and15.8%respectively, while in Henan Province, were9.4%,11.7%and16.8%. Judging from comprehensive productive efficiency, the municipal data of2000-2011indicates that, Shandong Province has higher scale efficiency and technical efficiency. Although there is adecreasing trend in both provinces, it is more obvious in Henan Province. Therefore, the outputefficiency of input factors in Henan Province is far less than in Shandong Province. Taking capital forexample, the annual growth rates in both provinces are around20%, but it only promoted6.27%inoutput growth in Henan, which is9.04%in Shandong.The formation of total factor productivity growth shows that, the proportions of governmentexpenditure and balance of loans from financial institutions in GDP were negatively correlated with TFPgrowth, with the former being more significant. The regression results of the inefficiency equation on prefecture-level data reveals that, urbanization, export and human capital spillovers can promote thegrowth rate of TFP to some degree, while the effects of the share of secondary industry and tertiaryindustry in GDP are not obvious. The road density and public employment are both significant in10%level, but their coefficients are contrary to expectation. The positive coefficient of road density showsthat infrastructure investment has no positive externalities, while the negative coefficient of publicemployment might be caused by its collinearity with the proportion of government expenditure.Last but not least, the decomposition of the municipal TFP shows that, technical progress is thefundamental driving force of TFP growth, while the decline in regional technical efficiency and scaleefficiency is a major constraint on it. The relatively backward regions tend to have faster rates oftechnical progress, in which sense, inter-regional technology spillovers is the main force promotingregional convergence. Technical efficiency and scale efficiency in most regions during2000-2011showsa general downward trend, which decreased less in economically developed areas, while more obvious inrelatively backward regions. The decrease of technical efficiency has strong correlation with thesubstantial increase of the proportion of government expenditure in GDP.