中国信贷配置的时空分异及时空收敛性研究——来自制造业上市公司的数据分析

文章基于2008-2017年制造业上市公司信贷数据，采用Dagum基尼系数、Kernel密度估计等方法实证考察了中国三大地区及四大行业群信贷配置的差距及其动态演进，并利用空间面板数据对信贷配置的时空收敛性进行检验。研究结果表明：（1）总体来看，中国信贷配置水平呈上升趋势，但信贷资金的地区配置和行业配置存在明显差距。（2）从地区角度，中国信贷配置总体差距、地区内差距和地区间差距均呈下降趋势，东部地区信贷配置较为均衡，未出现分化现象，中、西部地区的信贷配置在部分年份具有极化现象，且极化程度有所差异。具体来看，超变密度是总体差距的主要来源，各地区内省份之间信贷配置水平的非均衡性不断加强，地区内差距的贡献率逐渐上升，而地区间差距对总体差距的贡献率呈现下降的态势。（3）从行业角度，各行业群信贷配置差距的波动更加明显，呈现行业内差距和行业间差距演变趋势不一致的走向，其中资本投入拉动型行业群的内部差距呈扩大趋势，技术创新驱动型行业群的内部差距波动最大，劳动密集优势型行业群与技术创新驱动型行业群间差距最大。（4）此外，考虑时间和空间因素的收敛模型表明，在2008-2013年和2014-2017年两个样本时间段中，尽管中国信贷配置的时空收敛速度存在差距，但其时空收敛性是明显的，从经济进入新常态以来，外围区域向中心区域的追赶速度降低了。

Research on Time and Space Differentiation and Spatio-temporal Convergence of China's Credit Allocation

Based on the credit data of listed manufacturing companies from 2008 to 2017, this paper empirically investigated the gap and dynamic evolution of credit allocation in three regions and four major industry groups in China by using Dagum gini coefficient, Kernel density estimation and other methods, and tested the spatial-temporal convergence of credit allocation by using spatial panel data. The results show that:(1) overall, the credit allocation level in China is on the rise, but there is an obvious gap between the regional and industrial allocation of credit funds. (2) from the regional perspective, the overall gap, intra-regional gap and inter-regional gap of credit allocation in China all show a downward trend. The credit allocation in the eastern region is relatively balanced without differentiation. The credit allocation in the central and western regions shows polarization in some years, and the degree of polarization is different. To be specific, hyper-variable density is the main source of the overall gap. The non-equilibrium of credit allocation level among the provinces in each region is continuously strengthened, and the contribution rate of intra-regional gap is gradually increasing, while the contribution rate of inter-regional gap to the overall gap shows a downward trend. (3) From an industry perspective, the fluctuations in credit allocation gaps between various industry groups are more obvious, and the evolution trend of intra-industry gap and inter-industry gap is inconsistent, Among them, the internal gaps of capital investment-driven industry groups are expanding, The internal gap of technology innovation-driven industry group fluctuates the most, and the gap between labor intensive advantage industry group and technology innovation-driven industry group is the largest. (4) in addition, the convergence model considering time and space factors shows that in the two sample time periods of 2008-2013 and 2014-2017, although the spatio-temporal convergence rate of credit allocation in China is different, its spatio-temporal convergence is obvious, however, since the economy entered the new normal, the speed of catch-up from the periphery to the center has slowed down.