Studying Spatial Correlation and Regional Differences in Local Government Debt Performance Using Spatial Econometric Models-Reference-Cited by-同舟云学术

Studying Spatial Correlation and Regional Differences in Local Government Debt Performance Using Spatial Econometric Models

Published:2023-10-28 Issue:1 Volume:9 Page:
ISSN:2444-8656
Container-title:Applied Mathematics and Nonlinear Sciences
language:en
Short-container-title:

Author:

Dong Haoran¹,Wang Shiyu²,Bai Yumeng³,Liu Jun⁴,Liu Fengrui⁵

Affiliation:

1. 1 Faculty of Economics and Management, Luoyang Institute of Science and Technology , Luoyang 471023 , China .

2. 2 Department of Economics, Faculty of Arts and Social Sciences , National University of Singapore , , Singapore .

3. 3 School of Environmental Engineering and Chemistry, Luoyang Institute of Science and Technology , Luoyang, Henan, 471023 , China .

4. 4 School of Computer and Information Engineering, Luoyang Institute of Science and Technology , Luoyang, Henan, 471023 , China .

5. 5 School of Public Finance and Taxation , Zhongnan University of Economics and Law , Wuhan, Hubei, 430073 , China .

Abstract

Abstract The magnitude and type structure of local government debt are first analyzed in this work. Then, using the “4E” evaluation theory, a local government debt performance assessment index system is built. Second, an entropy-TOPSIS technique is used to calculate the risk index of local government debt performance, and a spatial econometric model is used to examine the geographical spillover impact of local government debt performance across different areas. Finally, the heterogeneity of local government debt management was evaluated using the Malmquist index. The findings demonstrate that the hypothesized national effect is often superior to the sub-regional effects, with a debt ratio regression result of -0.065. Despite the overall local government debt coefficient being -0.032, the direct impact coefficient for the eastern area is -0.025.

Publisher

Walter de Gruyter GmbH

Subject

Applied Mathematics,Engineering (miscellaneous),Modeling and Simulation,General Computer Science

Link

https://www.sciendo.com/pdf/10.2478/amns.2023.2.00834

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