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连片特困地区消费市场规模对金融减贫的门槛效应研究——基于2009-2015年武陵山片区31个贫困县数据的分析 被引量:7

Threshold Effects of Consumption Market Size on Financial Poverty Reduction in Contiguous Poverty Area:An Analysis of 31 Poverty Counties in Wu Ling Mountain Area from 2009 to 2015
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摘要 本文运用Hansen面板门槛模型,检验了连片特困地区消费市场规模对金融减贫的门槛效应。研究发现:连片特困地区农村金融支持与农民收入提高之间呈现非线性关系,县域消费市场规模对农村金融减贫具有明显的门槛效应。当县域消费市场规模低于第一门槛值2069.6元时,除扶持性贷款外,其他农村信贷支持并不利于农户脱贫增收;当跨越第二门槛值3927.3元时,农户贷款、农村企业贷款和扶持性贷款增加均能显著提高农民收入,且三者减贫成效依次增加,农户小额信贷并未发挥明显减贫成效。建议着力构建连片特困地区农村电商平台,加大扶持性贷款力度,发展新型农村经营主体,提高农村助农取款服务点铺设率以及扩大农业保险覆盖面等。 This paper uses the Hansen panel threshold regression model to examine the threshold effects of consumption market size on financial poverty reduction. We find that there is a nonlinear relationship between the financial support and farmers' income growth in poverty areas. The consumption market size in counties has obvious threshold effects on the rural poverty reduction. When the counties' consumption market size are lower than the first threshold of 2069.6 yuan, rural credits including the farmer loan, the rural enterprise loan and the farmer microfinance are not conducive to pull farmers out of poverty, except for the supporting loan; when the counties' consumption market size are larger than the second threshold of 3927.3 yuan, the farmer loan, the rural enterprise loan and the supporting loan can significantly increase farmers' income, except for the farmer's micro credit loans, and their effectiveness on poverty reduction are increase in sequence. We propose to build a platform for rural electric business in the poverty areas, to increase the scale of supporting loan, to develop new rural business entities, to improve the distribution rate of rural cash dispensers in rural area and to increase the coverage rate of agricultural insurance.
作者 罗栋 LUO Dong(The People's Bank of China Wangcheng Branch, Changsha 410200, Hunan, China)
出处 《消费经济》 北大核心 2017年第3期39-46,共8页 Consumer Economics
关键词 消费市场规模 金融减贫 面板门槛回归模型 Consumption Market Size Financial Poverty Reduction Panel Threshold Regression Model
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