Estimation and Dynamic Evolution of Provincial Factor-Output Elasticity in China-Reference-Cited by-同舟云学术

Estimation and Dynamic Evolution of Provincial Factor-Output Elasticity in China

Published:2022-09-20 Issue:5 Volume:26 Page:792-800
ISSN:1883-8014
Container-title:Journal of Advanced Computational Intelligence and Intelligent Informatics
language:en
Short-container-title:JACIII

Author:

Xu Zhengzhi,Li Xiujie,Zhang Chaojie,Zhu Jiani,Zhang Shangfeng,Lu Ke, , ,

Abstract

China is currently in a new phase of transition from high-speed growth to high-quality growth, and accurate estimation of element outputs is essential for the smooth progress of the transition. Using the back-fitting method, this study constructed a model of a spatiotemporal-varying elasticity production function to estimate the factor-output elasticity from 1993 to 2017 in 31 Chinese provinces. Nonparametric kernel density method was applied to describe the spatiotemporal evolution characteristics of factor-output elasticity. The results show that the factor-output elasticity of different provinces shows a nonlinear change trend over time and between regions. Overall, the elasticity of labor output shows a decreasing trend, the elasticity of capital output shows an increasing tendency, the eastern region has the lowest level of labor-output elasticity, but the highest level of capital-output elasticity. The western region has the highest level of labor-output elasticity but the lowest level of capital-output elasticity. On the whole, regions with higher resilience in labor output gradually shift towards the West, while capital shifts towards the East.

Funder

Zhejiang Natural Science Foundation

National Social Science Foundation

Zhejiang Statistical Research Foundation

Zhejiang Province Universities Basic Scientific Research Foundation

Characteristic & Preponderant Discipline of Key Construction Universities in Zhejiang Province

Collaborative Innovation Center of Statistical Data Engineering Technology & Application

Zhejiang Gongshang University Postgraduate Innovation Foundation

Publisher

Fuji Technology Press Ltd.

Subject

Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction

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