分析墨西哥各州的公共债务:空间趋同、区域驱动因素和政策建议

IF 2.4 3区 经济学 Q2 ECONOMICS
Mihaela Simionescu , Javier Cifuentes‐Faura
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引用次数: 0

摘要

考虑到公共债务是墨西哥政策制定者的优先事项,本文的目的是研究2006-2021年期间墨西哥32个州的人均债务和债务的主要驱动因素的趋同或差异。结果支持各州债务/上限的显著空间相关性。横截面和空间动态回归用于分析人均债务的绝对和条件贝塔收敛,并记录了发散假设。基于矩分位数方法模型和汇总平均组估计的面板数据模型表明,贫困是债务的主要决定因素,而外国直接投资不足以支持长期债务的减少。这些结果为一系列政策建议提供了证据,以确保墨西哥走上可持续的债务道路。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Analysing public debt in the Mexican states: Spatial convergence, regional drivers and policy recommendations
Considering that public debt is a priority for policymakers in Mexico, the aim of this paper is to examine the convergence or divergence in debt per capita and main drivers of debt in the 32 Mexican states in the period 2006–2021. The results support significant spatial correlation of debt/cap across states. Cross‐section and spatial dynamic regressions are used to analyse absolute and conditional beta‐convergence in debt per capita, and the divergence assumption is documented. The panel data models based on the method‐of‐moments quantile models and pooled mean group estimators indicate that poverty is the main determinant of debt, whereas foreign direct investment is insufficient to support the reduction in debt in the long run. These results provide evidence for a set of policy recommendations to ensure a sustainable debt path in Mexico.
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来源期刊
CiteScore
4.40
自引率
4.80%
发文量
58
期刊介绍: Regional Science is the official journal of the Regional Science Association International. It encourages high quality scholarship on a broad range of topics in the field of regional science. These topics include, but are not limited to, behavioral modeling of location, transportation, and migration decisions, land use and urban development, interindustry analysis, environmental and ecological analysis, resource management, urban and regional policy analysis, geographical information systems, and spatial statistics. The journal publishes papers that make a new contribution to the theory, methods and models related to urban and regional (or spatial) matters.
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