Analysis on Regional Characteristics of Economic Growth Based on Total Factor Productivity

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Abstract

In this paper, we adopt stochastic frontier model of translog production function to measure the total factor productivity growth rate of 13 cities in Jiangsu province from the year 2000 to 2020 and study the characteristics of the contribution rates of capital, labor, and total factor productivity in driving economic growth. The study shows that, firstly, the explanatory power of the model could be increased by 35.9% after 6 effect variables, such as urban economic development level, have been taken into consideration when two-step method has been adopted to explore the model parameters of stochastic frontier; secondly, there is an obviously positive correlation between the 4 variables, urban economic development level, urban size, level of opening up to the outside world and infrastructure construction, and production efficiency, while there is a negative correlation between economic structure and production efficiency, and the research input intensity has an uncertain effect on production efficiency; thirdly, the TFP growth trend of urban economy of the province shows a similar "W"trend, technical progress becomes the first element in affecting total factor productivity, and the negative growth in technical efficiency and scale efficiency result in a dramatic decline in growth rate of TFP; fourthly, among all the elements contributing to urban economic growth, capital has the greatest contribution, TFP takes the second place, and labor element takes the last. The double difference between capital and TFP appears to be the major cause in forming regional difference of urban economy. The regional differences of TFP concerning infrastructure advantage, position advantage, factor advantage, and policy advantage are the key factors in urban economic gap. At the end of this study, we propose some policy suggestions.

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Ma, W., Wu, C. C., & Tang, D. (2022). Analysis on Regional Characteristics of Economic Growth Based on Total Factor Productivity. Discrete Dynamics in Nature and Society, 2022. https://doi.org/10.1155/2022/9747559

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