摘要
农村居民的信息消费水平较城镇居民有较大差距,但却较城镇居民有更高的空间相关性,表现出较强的空间集聚特征。本文基于此提出了考虑内、外部消费习惯形成及当期消费空间效应三种影响因素的消费理论模型,在此基础上,遵循"从一般到特殊"的原则提出动态空间面板模型,但是经检验其不满足平稳性条件,采用空间协整模型后的估计结果表明农村居民在信息消费支出方面没有形成显著的消费习惯;采用静态空间面板模型的估计结果表明,农村居民信息消费支出存在显著的空间溢出效应,收入仍是提高农村居民在信息消费支出的主要因素,信息基础设施对农村居民信息消费提升的作用有限,物价上涨、受教育水平、城镇居民信息消费习惯对农村居民信息消费没有产生显著性的影响。上述结论得到政策启示:在我国农村居民收入不断增长的同时,采取措施重点扶持、培养农村居民信息消费习惯,扩大其空间溢出效应,或可成为加速我国农村社会经济文化发展、缩小城乡差别的一条捷径。
Rural residents' information consumption level is lower than urban residents', but the spatial correlation is higher than urban residents', showing higher spatial integration features. So the theory model of considering three factors that include the internal, external consumption habit and the spillover effects of information corisumption is put forward. Based on the principle of from general condition to special condition, the dynamic spatial panel model is established. But the model is non-stable through wald-test. The conclusions of spatially cointegrated model show that the rural residents do not form significant consumption habit; the conclusions of static spatial panel model show that the information con- sumption has marked spillover effects, the income is still the main factor enhancing rural residents' information consump- tion, the information infrastructure has smaller influence, the price, urban residents'education and consumption habit have no significant influence. Based on the above conclusions, the corresponding polices include training the consumption habit and enhancing spillover effects with continuous increasing of rural residents' income, which may be a shortcut to accelerate the development of economy and culture of rural area, and decrease differences between urban and rural resi- dents.
作者
张肃
ZHANG Su(School of Economics and Management, Tongji University, Shanghai 200092, China School of Economics and Management, Zhongyuan University of Technology, Zhengzhou 450007, China)
出处
《商业研究》
CSSCI
北大核心
2017年第7期184-192,共9页
Commercial Research
基金
国家社科基金项目
项目编号:14CTJ002
关键词
农村居民
信息消费
影响因素
空间相关性
空间面板模型
rural residents
information consumption
influence factors
spatial correlation
spatial panel model