银行业空间演化与企业信贷
作者简介:姚晓明(1986-),男,辽宁沈阳人,博士研究生,主要从事金融地理及产业动态演化研究。E-mail: yaoxm8042@163.com
收稿日期: 2018-01-14
要求修回日期: 2018-03-05
网络出版日期: 2019-02-10
基金资助
国家自然科学基金项目(41701115)资助
The Spatial Evolution of Banking Industry and Firm Credit
Received date: 2018-01-14
Request revised date: 2018-03-05
Online published: 2019-02-10
Supported by
National Natural Science Foundation of China (41701115).
Copyright
在梳理中国银行业改革历程和银行网点分布时空特征的基础上,提出银行空间扩张和地方性银行兴起是中国银行业空间演化的主要动力,并将该过程分解为银行操作距离和银行功能距离。在分析银行业空间演化过程的基础上,进一步引入地方银行业特征变量作为制约企业信贷获得的解释变量。实证结果表明,减小银行操作距离只能改善西部和东北地区企业信贷环境,而降低银行功能距离则能有效提高企业信贷获得,竞争型的地方银行市场能够提高非国有企业的信贷获得,银行本地化进程亦能提高非国有企业信贷获得。在转型经济的制度背景下,市场化力量能够有效扩大银行的安全信贷范围,而分权化过程有效地维护了地方信贷环境。
姚晓明 , 朱晟君 . 银行业空间演化与企业信贷[J]. 地理科学, 2019 , 39(2) : 294 -304 . DOI: 10.13249/j.cnki.sgs.2019.02.014
Under the background of China's transitional economy, the spatial organization structure of banks has been adjusted, and firm credit environment has changed accordingly. This article argues that spatial expansion of banks and rising of local banks are the main motive force for the spatial evolution of banking in China. We use operational distance and functional distance to describe the spatial evolution of banks. Based on the analysis of the spatial evolution of banking industry, this article introduces the local banking characteristics variables as the explanatory variables that restrict firm credit. The empirical results show that reducing the operational distance can only improve the corporate credit environment in the western and northeastern regions of China while reducing the functional distance can effectively improve firm credit. The competitive local banking market can enhance the credit access of non-state-owned enterprises. The localization of banks also increased the access of non-state-owned enterprises to credit, and so on. In the context of transitional economy, marketization forces can effectively increase the range of security credit, while the decentralization process has effectively improved the credit environment of enterprises.
Fig.1 China’s operational distance and functional distance during 2005-2013图1 2005~2013年中国平均操作距离和功能距离的变化趋势 |
Fig.2 The average of operational distance and functional distance at the provincial level from 2008 to 2011图2 2008~2011年中国各省市自治区平均操作距离和平均功能距离 未包括港澳台数据 |
Fig.3 Change of operational and functional distance in 2006-2013图3 全国各省市自治区操作距离和功能距离变化情况 |
Table 1 Regression results表1 回归结果 |
| 企业是否获得银行贷款(Probit模型) | 企业利息支出占比(Tobit模型) | |||||
|---|---|---|---|---|---|---|
| 模型(1) | 模型(2) | 模型(3) | 模型(4) | 模型(5) | 模型(6) | |
| OD | 0.00119*** | 0.00127*** | 0.00131*** | 0.00004*** | 0.00004*** | 0.00004*** |
| FD | -0.0200*** | -0.0161*** | -0.000508* | -0.000263 | ||
| HHI | -0.823*** | -0.0896*** | ||||
| LOC | 2.372*** | 0.156*** | ||||
| size | 0.142*** | 0.143*** | 0.144*** | 0.00621*** | 0.00633*** | 0.00632*** |
| age | 0.00280*** | 0.00276*** | 0.00265*** | 0.00021*** | 0.00021*** | 0.00020*** |
| SOE | 0.261*** | 0.258*** | 0.254*** | 0.0197*** | 0.0194*** | 0.0189*** |
| CPOE | 0.563*** | 0.560*** | 0.552*** | 0.0241*** | 0.0238*** | 0.0232*** |
| FE | 0.0182 | 0.0128 | 0.00263 | -0.000843 | -0.00140 | -0.00207 |
| exp | 0.0936*** | 0.0926*** | 0.0918*** | 0.00463*** | 0.00447*** | 0.00455*** |
| ind | 0.0410*** | 0.0400*** | 0.0409*** | 0.00642*** | 0.00628*** | 0.00644*** |
| region | Included | Included | Included | Included | Included | Included |
| industry | Included | Included | Included | Included | Included | Included |
| 常数 | -0.253*** | -0.0256 | -0.464*** | -0.0571*** | -0.0313*** | -0.0659*** |
| N | 268821 | 268821 | 268821 | 268821 | 268821 | 268821 |
| log L | -132553.5 | -132542.8 | -132488.6 | 136127.1 | 136150.9 | 136177.6 |
| LR chi2 | 21465.7 | 21487.3 | 21595.5 | 5120.8 | 5168.3 | 5221.7 |
注:***,P<0.01,**,P<0.05,*,P<0.1。空白处为相关性较强的变量拆分到不同的模型中,下表同。“Included”为回归过程中已经控制了空间差异和行业差异,下表同。 |
Table 2 Regression results categorized by 4 economic plants表2 分四大经济区域的回归结果 |
| 东部 | 中部 | 西部 | 东北 | ||||||
|---|---|---|---|---|---|---|---|---|---|
| 模型(1) | 模型(2) | 模型(3) | 模型(4) | 模型(5) | 模型(6) | 模型(7) | 模型(8) | 模型(9) | |
| OD | 0.139*** | 0.151*** | 0.10*** | 0.09*** | -0.0004*** | -0.0005*** | -0.16*** | -0.084*** | |
| FD | -0.098*** | -1.254*** | 0.193*** | 10.33*** | |||||
| HHI | -23.04*** | 25.80*** | -0.237 | 124.1*** | |||||
| LOC | 33.24*** | 75.19*** | -2.039 | -93.50*** | |||||
| size | 0.144*** | 0.152*** | 0.135*** | 0.132*** | 0.059*** | 0.056*** | 0.151*** | 0.158*** | 0.151*** |
| age | 0.003*** | 0.003*** | 0.006*** | 0.006*** | -0.00162 | -0.00165 | -0.000591 | -0.00126 | -0.000591 |
| SOE | 0.229*** | 0.196*** | -0.0772 | 0.0578 | 0.139 | 0.136 | 0.122 | 0.179 | 0.122 |
| CPOE | 0.510*** | 0.426*** | 0.346*** | 0.474*** | 0.405*** | 0.390*** | 0.194** | 0.262*** | 0.194** |
| FE | -0.00409 | -0.068*** | -0.0782 | 0.0251 | 0.00939 | 0.00492 | 0.0328 | 0.106 | 0.0328 |
| exp | 0.138*** | 0.157*** | 0.0264 | 0.0168 | 0.0443 | 0.0563 | 0.255*** | 0.183*** | 0.255*** |
| ind | 0.090*** | 0.109*** | -0.00839 | 0.0126* | 0.070*** | 0.076*** | 0.070*** | 0.073*** | 0.070*** |
| industry | Included | Included | Included | Included | Included | Included | Included | Included | Included |
| 常数 | 5.897*** | -3.278*** | -1.869*** | -3.663*** | -0.217 | 1.104*** | -54.98*** | -35.50*** | 10.82*** |
| N | 173262 | 173262 | 51205 | 51205 | 25191 | 25191 | 19163 | 19163 | 19163 |
| log L | -90415.8 | -88576.4 | -16167.6 | -15509.5 | -6294.6 | -6325.6 | -10588.2 | -11362.7 | -10588.2 |
| LR chi2 | 20497.7 | 24176.6 | 3540.5 | 4856.6 | 291.0 | 228.9 | 3444.0 | 1895.1 | 3444.0 |
注:***,P<0.01;**,P<0.05;*,P<0.1。表中结果均采用Probit模型估计,下表同。 |
Table 3 Regression results categorized by firm ownership表3 区分企业所有制类型的回归结果 |
| 国有企业 | 非国有企业 | |||||
|---|---|---|---|---|---|---|
| 模型(1) | 模型(2) | 模型(3) | 模型(4) | 模型(5) | 模型(6) | |
| OD | 0.000547* | 0.000506 | 0.000604* | 0.00128*** | 0.00138*** | 0.00143*** |
| FD | 0.0269 | 0.00231 | -0.0287*** | -0.0244*** | ||
| HHI | 5.775*** | -0.893*** | ||||
| LOC | -6.398*** | 2.968*** | ||||
| size | 0.212*** | 0.206*** | 0.210*** | 0.115*** | 0.116*** | 0.118*** |
| age | -0.00214* | -0.00216* | -0.00214* | 0.00407*** | 0.00402*** | 0.00387*** |
| exp | 0.376*** | 0.388*** | 0.379*** | -0.0719*** | -0.0733*** | -0.0742*** |
| ind | 0.239*** | 0.239*** | 0.239*** | 0.0487*** | 0.0475*** | 0.0482*** |
| region | Included | Included | Included | Included | Included | Included |
| industry | Included | Included | Included | Included | Included | Included |
| 常数 | -0.524*** | -2.118*** | -0.0936 | 0.474*** | 0.717*** | 0.173*** |
| N | 4975 | 4975 | 4975 | 263846 | 263846 | 263846 |
| log L | -2338.6 | -2326.1 | -2328.5 | -132154.7 | -132142.2 | -132060.0 |
| LR chi2 | 651.6 | 676.6 | 671.7 | 16934.5 | 16959.6 | 17124.0 |
注:***,P<0.01;**,P<0.05;*,P<0.1。 |
Table 4 Regression results with intersection表4 含有交叉项的回归结果 |
| 模型(1) | 模型(2) | 模型(3) | |
|---|---|---|---|
| OD | 0.00119*** | -0.00120*** | 0.01325*** |
| FD | -0.0200*** | 0.627*** | -3.27*** |
| ODLIB | 0.00271*** | ||
| FDLIB | -0.674*** | ||
| ODDPT | -0.0012*** | ||
| FDDPT | 0.340*** | ||
| LIB | 3.913*** | ||
| DPT | -2.6123*** | ||
| size | 0.142*** | 0.143*** | 0.144*** |
| age | 0.00280*** | 0.00274*** | 0.00538*** |
| SOE | 0.261*** | 0.254*** | 0.138*** |
| CPOE | 0.563*** | 0.561*** | 0.371*** |
| FE | 0.0182 | 0.0161 | 0.0271 |
| exp | 0.0936*** | 0.0943*** | 0.2062*** |
| ind | 0.0410*** | 0.0408*** | 0.1085*** |
| region | Included | Included | Included |
| industry | Included | Included | Included |
| 常数 | -0.253*** | -4.004*** | 24.47*** |
| N | 268821 | 268806 | 265151 |
| log L | -132553.5 | -132450.7 | -124428.25 |
| LR chi2 | 21465.7 | 21661.2 | 35365.1 |
注:***,P<0.01;**,P<0.05;*,P<0.1。 |
The authors have declared that no competing interests exist.
| [1] |
|
| [2] |
|
| [3] |
|
| [4] |
[
|
| [5] |
|
| [6] |
[
|
| [7] |
[
|
| [8] |
[
|
| [9] |
[
|
| [10] |
[
|
| [11] |
[
|
| [12] |
[
|
| [13] |
[
|
| [14] |
[
|
| [15] |
[
|
| [16] |
[
|
| [17] |
|
| [18] |
[
|
| [19] |
|
| [20] |
|
| [21] |
|
| [22] |
|
| [23] |
|
| [24] |
|
| [25] |
|
| [26] |
|
| [27] |
|
| [28] |
|
| [29] |
|
| [30] |
|
| [31] |
|
| [32] |
|
| [33] |
|
| [34] |
|
| [35] |
|
| [36] |
|
| [37] |
[
|
| [38] |
[
|
| [39] |
|
| [40] |
[
|
| [41] |
[
|
| [42] |
|
| [43] |
|
| [44] |
[
|
| [45] |
[
|
| [46] |
[
|
/
| 〈 |
|
〉 |