宏观债务负担与消费扩张:基于面板模型和面板分位数回归模型的分析

Qianqian Lu, Kun Xu, Guangjian Xu
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引用次数: 0

摘要

摘要随着社会信用负担水平的提高,缓解居民流动性约束是当前拉动内需的重要途径。本文利用2007-2017年中国省级行政单位的面板数据,采用面板回归模型和面板分位数回归模型实证分析了债务负担水平与平均消费倾向之间的关系。结果表明,宏观债务负担水平的提高可以显著提高居民的APC;宏观债务负担对APC的边际促进作用呈V型结构;这种边际影响在不同地区有明显差异,其中东北地区的边际促进作用最为突出。因此,建议政府不断完善信贷市场,多渠道增加居民收入,引导流动性向实体经济供给,促进基本公共服务均等化,以实现消费的扩张和升级。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Macro Debt Burden and Consumption Expansion: An Analysis Based on Panel Model and Panel Quantile Regression Model
Abstract As the level of social credit burden rises, to ease the liquidity constraint for residents is currently an important way to boost the domestic demand in China. This paper uses the panel data of Chinese provincial-level administrative units in 2007−2017 and adopts the panel regression model and panel quantile regression model to empirically analyze the relationship between debt burden level and average propensity to consume (APC). The result shows that increase in the level of macro debt burden can significantly improve the APC of residents; the marginal promoting effect of macro debt burden for the APC is in a V-shaped structure; such marginal influence differs evidently in different areas, with the marginal promoting effect turning out most prominent in the northeast of China. Accordingly, it’s suggested for government to keep refining the credit market, increase residents’ income in multiple means, guide supply of liquidity towards the real economy and promote equalization of basic public services, so as to realize the expansion and upgrade of consumption.
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