中国农村金融地理排斥的省内差异—基于“地理金融密度不平等系数”衡量指标

China's rural financial geography exclusive province-based on differences“Geographical financial density not equal coefficient”measure

　　陈莎 蒋莉莉 周立

ChenSha JiangLiLi ZhouLi

　　“金融排斥”是农村金融领域的一个常用概念，指的是一部分人由于各种原因被排斥在金融机构服务之外，无法获得如存款、贷款这样的基本金融服务。“金融排斥”通常分为六个维度：地理排斥、价格排斥、条件排斥、营销排斥、评估排斥和自我排斥。其中，地理排斥指的是金融机构的地理可及性问题，一些偏远落后地区设置的金融机构网点很少，人们到达金融机构网点十分不便。在中国农村地区，地理排斥仍然占有最基础性的地位。

“Financial exclusion”In the field of finance in rural areas is a general concept，Refers to the part of the people because all sorts of reasons being excluded from the financial services besides，Can't get such as deposits、Loans such basic financial services。“Financial exclusion”Usually divided into six dimensions：Geographical rejection、Price rejection、Conditions rejection、Marketing rejection、Evaluation rejection and self rejection。Among them，Geographical rejection refers to financial institutions geographical accessibility，Some remote backward area of financial institutions rarely set outlets，People arrived at financial institutions network is very inconvenient。In China's rural areas，The most basic geography rejection still holds the position。

　　在衡量地理排斥时，金融机构网点数量是最常用的指标。不少学者已经利用金融机构网点数量对各省的金融排斥情况进行了对比研究，这些研究的主要方法是选择省级层面的数据进行省市、地区对比，却没有考虑省内差异，而较高的省级平均水平却掩盖了省市内部农村地区金融排斥的严重程度。如图1所示，四川省的金融机构网点分布呈现明显的“东多西少”特征。2010年，在四川省的西部，各县金融机构网点数量均在48个以下，这部分地区在地理面积上约占四川省总面积的2/3。而四川省东部各县的网点数量较多。2010年，四川省盐源县仅有6个网点，而成都市金牛区则有287个营业网点，是盐源县网点数量的47.8倍。

In the measure of geographical rejection，Financial institutions network number is the most commonly used index。Many scholars have using financial institutional networks in all the provinces of the number of financial exclusion situation makes a comparative study，The main method is the choice of provincial level data provinces and cities、Area contrast，But have not consider province differences，And higher provincial average but covers the provinces and cities in rural internal to the severity of the financial exclusion。As shown in figure 1 shows，The province of sichuan financial institutions distribution outlets obviously“East west less”characteristics。2010 years，In sichuan province in the west，Counties financial institutions are in a number of outlets 48 below，This part of the region in the geography area in sichuan province, the total area accounts for about two-thirds。The eastern counties in sichuan province and the more outlets。2010 years，YanYuanXian sichuan province only 6 outlets，Chengdu jinniu district and is the 287 business outlets，Is YanYuanXian outlets number of 47.8 times。

　　因此，在对地理排斥地区差异的研究中，省内差异可以说是不可或缺的一部分内容。然而，由于全国省市数量众多，在度量省内差异时不可能按照每个省的情况分别进行省内的对比分析，因此，以往的研究方法均失效了。但有一个思路可以为我们展示省内差异：当我们知道了各省地理排斥的一般情况时，只要我们知道了省内农村地区银行网点布局的不平等程度，就能对省内差异有较好的理解。

so，In the regional differences of geographic rejection of the study，The province is an indispensable part of differences can say content。however，As the nation's provinces and cities in number，In the measure when difference may not according to the province of each province respectively the comparison of the province，so，Previous research methods all failed。But there is a train of thought can show us province differences：When we know the geography of the general conditions provinces reject，As long as we know the province rural banking network layout extent of inequality，The province is able to have a good understanding of the differences。

　　要度量“各省地理排斥的一般情况”，笔者在《中国农村金融地理排斥的地区差异》一文（见本刊2012年第7期第106页）中构建了四个“金融密度”指标，其基本含义、计算方法及适用性如表1所示。

measure“Provinces of the general conditions geography rejection”，The author in《China's rural financial geography rejection of the regional differences》are（See this newspaper in 2012 7 (pp. 106-）The construction of the four“Financial density”index，The basic meaning、Calculation method and suitability as is shown in table 1。

　　此处的计算是以各县为基本计算单位，当要计算省的“金融密度”时，本文提出的方法是：计算出各县的四个“金融密度”后，以该省的中位数来代表该省的四个“金融密度”。同样的，在计算各地区和全国的四个“金融密度”时，也采用中位数方法。

The calculation is based on various counties as the basic unit of measure，When to calculate the province“Financial density”when，The method is put forward in this paper：Calculate the four counties“Financial density”after，To the province's median to represent the province's four“Financial density”。The same，In the calculation of regional and national four“Financial density”when，Also the median method。

　　四个“金融密度”在衡量各省农村金融地理排斥时具有不同的含义和代表性。中国广大的农村地区人口分散，因此，地理金融密度最符合中国农村地区的实际情况。地理金融密度也最符合地理排斥的内涵——地理可及性问题，即在同样的地理面积内，金融机构网点数量越多，人们就越能方便地选择离自己较近的网点获得金融服务。因此，本文最终选择“地理金融密度”作为衡量各省农村地区地理排斥程度的指标，并在此基础上仿照基尼系数的方法构建“地理金融密度不平等系数”这一指标，用以衡量各省农村地区银行网点分布的不平等性，以此度量各省农村金融地理排斥的省内差异，这样的研究在国内中还是首次。

four“Financial density”In the measure of rural financial geography rejection provinces, have a different meaning and representative。China's vast rural areas scattered population，so，Geographical financial density most conforms to the actual situation of China's rural areas。Geographical financial density and the most with the connotation of geographical rejection-geographic accessibility，That is in the same geographic area inside，The more net point of financial institutions，The more people can conveniently select from his more recent outlets for financial services。so，This paper finally choose“Geographical financial density”As a measure of provinces rural areas geographic rejection degree of index，And on this basis imitates the gini coefficient method of construction“Geographical financial density not equal coefficient”This indicator，Measure in rural provinces bank site distribution inequality，To measure rural financial geography exclusive province province differences，Such studies in China or in the first time。

　　测量指标：地理金融密度不平等系数 Measurement index：Geographical financial density not equal coefficient

　　为了能够度量省内农村地区的地理排斥程度差异，本文参照基尼系数的计算方法构建了用于衡量省内、地区内部金融排斥差异程度的指标——地理金融密度不平等系数。

In order to be able to measure the province of rural areas geographical rejection level differences，This paper reference gini coefficient calculation method for constructing used to measure the province、Internal financial exclusion difference in the degree of index-geographic financial density not equal coefficient。

　　基尼系数的计算方法如图2所示。将人口按照收入水平从低到高进行排序后，横轴表示的是人口的百分比，纵轴表示对应的人口拥有的收入所占的百分比。由此绘制出的代表各百分比人群拥有的收入占比曲线即为洛伦兹曲线。图中的对角线为完全平等线，表示的是人口的百分比与收入的百分比完全相等的情况。假设完全平等线与洛伦兹曲线之间的面积为A，洛伦兹曲线以下的面积为B。则基尼系数=A/（A+B）。

Gini coefficient calculation method as shown in figure 2 shows。In accordance with the income level population from low to after revision of the sort，The horizontal axis shows sales is the percentage of the population，The vertical axis of the corresponding population have said the percentage of income。Thus mapped represent each percentage of income than with the crowd of curve is the lorenz curve。In the chart the diagonal line for complete equality，That is the percentage of the population and the percentage of income of completely equal。Hypothesis of line and complete equality between the lorenz curve for A area，Lorenz curve the following area of B。The gini coefficient = A /（A + B）。

　　当以地理金融密度为指标衡量各省农村地区的金融排斥程度时，如果省内各个县之间的地理金融密度完全平等，则意味着全省每平方公里拥有的网点数量相等。换句话说，就是各县地理面积占比与各县拥有的金融机构网点数量占比是相等的。由此，本文仿照着基尼系数的定义也构造了一个“地理金融密度不平等系数”(见图3)——用各县的地理面积代替基尼系数中的人口数，用各县的金融机构网点数量代替基尼系数中的收入。只不过，本文的分析单位不是个人，而是以县为基本的计算单位。其计算方法与基尼系数一致，都是用A/(A+B)而得到。

When with geographic financial density of measures in rural provinces financial exclusion degree，If each county of geographic province between financial density complete equality，It means the per square kilometer have equal number of outlets。In other words，Is the geographical area accounts for the counties than the counties of financial institutions and with the number of outlets than is equal。this，In this paper the definition of imitates the gini coefficient and construct a“Geographical financial density not equal coefficient”(See figure 3)With the geographical area of the counties-instead of gini coefficient of the population，The counties of financial institutions with the number of outlets instead of gini coefficient income。just，This paper analysis the unit is not personal，But as for basic computing unit county。The calculation methods and gini coefficient is consistent，Is to use A /(A + B)And get。

　　中国农村金融地理排斥的省内差异 China's rural financial geography exclusive province differences

　　通过计算，各省市的地理金融密度和地理金融密度不平等系数（以下简称“不平等系数”）如表2所示。

Through the calculation，The provinces and cities geographical financial density and geographic financial density not equal coefficient（Hereinafter referred to as“Inequality coefficient”）As shown in chart 2。

　　表2将各省、各地区的不平等系数按照从低到高进行排序。由于上海、天津和北京三市内农村地区的县的数量太少（最多的天津农村地区仅包括3个县），因此三者的不平等系数小，均在0.1以下。安徽、江西、山东、海南和贵州等地的不平等系数均在0.2～0.3之间，属于农村地区地理金融密度较为平等的省份。四川、甘肃、西藏、内蒙古、新疆和青海的不平等系数均在0.5以上，地理金融密度极不平等。其中，青海的不平等系数为0.74，为各省最大值。同时，青海的地理金融密度仅0.1个/百平方公里。这就意味着：青海省不仅农村金融排斥严重，而且各县之间的农村金融排斥程度存在极大的差异，其省内每平方公里上分布的网点数量极不平等。在青海农村地区的42个县中，共有20个县的行政金融密度不足10个，这20个县的地理金融密度最大者也仅为0.15个/百平方公里。其中，有6个县都只有1个有贷款功能的网点。难以想象，在这样的地区，农民是如何经过步行、骑马、坐车才能获得金融服务的。

Table 2 will provinces、Parts of the world do not equal coefficient from low to order according to height。Due to the Shanghai、Tianjin and Beijing three city of the number of rural area county too little（Most of the tianjin rural areas include only three county），So the three small coefficient of inequality，All in 0.1 the following。anhui、jiangxi、shandong、Hainan and guizhou and inequality coefficients was between 0.2 and 0.3，Belong to rural areas more equal geographical financial density provinces。sichuan、gansu、Tibet、Inner Mongolia、Xinjiang and qinghai inequality coefficients in more than 0.5，Geographical financial density was unfair。Among them，Qinghai inequalities coefficient is 0.74，For maximum provinces。At the same time，Qinghai geographical financial density is only 0.1 a/the square kilometers。This means that：Qinghai province is not only the rural financial exclusion serious，And between counties of rural financial exclusion degree is a great difference，The province each square kilometers on the distribution network number was unfair。In rural areas of qinghai 42 in the county，There were 20 counties administrative financial density under 10，The 20 counties geographic financial density is only 0.15 attributes for the square kilometers /。Among them，There are six counties only 1 a loan function network。Hard to imagine，In this area，Farmers are how to pass on foot、riding、By car to get financial services。

　　为了更直观地反映各省市在不平等系数方面的差异，本文绘制出了全国各省市的不平等系数分布图，如图4所示。

In order to more directly reflected in the provinces and cities do not equal the differences of the coefficient，This paper draw out of all provinces and cities not equal distribution coefficient，As shown in figure 4 shows。

　　在图4中，红色越深的地方，其不平等系数越大，表示地理金融密度的省内差异越严重。从图4中可以直观地看到，西部地区除贵州、广西外，普遍呈深红色，其不平等系数很大，省内差异巨大；东部地区红色较浅，其不平等系数小，省内差异也较小，但广东省、浙江省的不平等系数依然较大,剔出城市后，这两个发达地区留下的县域，发展程度差异很大，网点数量也差异很大；中部地区安徽、江西两省不平等系数较小，其余省市依然处于居中水平。

In figure 4，The deeper the red place，Its not equal the greater the coefficient，Geographical financial density of province said the more serious differences。In figure 4 from can be directly to see，The western region in addition to guizhou、The guangxi，Common in deep red，Its not equal coefficient is very large，Great differences in；East is red light，Its not equal small coefficient，The province is lesser also differences，But the guangdong province、Zhejiang inequality still have large coefficient,Eliminating the city after，The two developed area of the left the county，Development degree difference is very big，Network number also difference is very big；In anhui province in central China、Jiangxi provinces not equal coefficient is small，The rest of the provinces and cities are still in household level。

　　中国农村金融地理排斥的地区内部差异 China's rural financial geography exclusive area internal differences

　　表3直观地展示了中国中东西部的地理金融密度不平等系数。从中可以看到，中部地区和西部地区的不平等系数约为0.4左右，虽然已经达到基尼系数的0.4的“警戒线”，但和西部地区比起来，其银行网点分布不平等状况已经较为轻松了。西部地区的不平等系数为0.78，内部发展极不平衡。而从全国范围内来看，由于全国各省之间差异较大，尤其西部地区的银行网点分布极不平等，因此全国的不平等系数也非常大，为0.73。

Table 3 intuitively showed the Chinese Middle East west geographical financial density not equal coefficient。From which we can see，The central region and the western area of the inequality is about 0.4 or so，Already at gini coefficient of 0.4“cordon”，But the western region and than up，The bank branch inequality in distribution has been relatively relaxed。The western area of the inequality coefficient is 0.78，Inside the uneven development。And from a nationwide and see，Due to the differences between the provinces，Especially the western area of the banking network distribution was unfair，So the national inequality coefficient is very big，For 0.73。

　　进一步的讨论：四种地理排斥类型 Further discussion：Four geographic rejection type

　　通过将不平等系数与地理金融密度的数值进行对比分析，可以将全国31个省归为如图5所示的四类情况。

Through the will not equal coefficient and the geography of the numerical value of financial density are compared and analyzed，Can the 31 provinces to as as shown in figure 5 shows the four categories。

　　本文将地理金融密度为4个/百平方公里作为划分标准，4个/百平方公里以上的归入“农村金融排斥较轻”一组，本文将这样的状态简称为“富”，4个/百平方公里以下的省归入“农村金融排斥严重”一组，简称为“不富”；将不平等系数为0.4以下的归入“不平等状况较轻”一组，简称为“均”，0.4以上的归入“不平等状况严重”一组，简称为“不均”。这样的划分法是综合考虑了各省的地理金融密度和不平等系数，也考虑到基尼系数以0.4作为社会分配不平等的警戒线这一因素。由此，图5被分为“富而且均”、“富而不均”、“均而不富”和“不富不均”四大类型，通过这四个类型的划分，可以大致看出我国各省农村地区整体的地理排斥状况和银行网点布局的不平等情况。

This paper will geographic financial density of four/hundred square kilometers as the division standard，Four/the square km above the as“The rural financial exclusion is lighter”A group of，This paper will such a state referred to as "“rich”，Four/hundred square kilometers of the province as the following“The rural financial exclusion serious”A group of，Referred to as"“Not to be rich”；Will not equal coefficient is 0.4 the following into“Inequalities is lighter”A group of，Referred to as"“are”，As the above 0.4“Inequality in serious condition”A group of，Referred to as"“inequality”。This division method is considering the geography in all the provinces of the financial density and inequality coefficient，Also consider the gini coefficient to 0.4 as a social inequality cordon this factor。this，Figure 5 is divided into“Rich and all”、“Rich and uneven”、“Are not rich”and“Uneven not rich”Four types，Through these four types of classification，Can see our provinces roughly in rural areas of the whole geographical rejection status and banking network layout of inequality。

　　为更直观地展示各省农村地理排斥的类型，本文绘制了中国各省农村地理排斥类型图，如图6所示。

For more intuitive to show the type of rural provinces geographical rejection，This paper to draw the Chinese provinces rural geographic rejection type figure，As shown in figure 6 shows。

　　一是“富而且均”型，即地理金融密度高于4个/百平方公里、不平等系数小于0.4的省份，包括：上海、天津、山东、江苏、河南、重庆和安徽7个省市。

One is“Rich and all”type，That is higher than the density of geographical financial four/hundred square kilometers、Inequality coefficient is less than 0.4 province，including：Shanghai、tianjin、shandong、jiangsu、henan、Chongqing and anhui 7 provinces and cities。

　　二是“富而不均”型。即地理金融密度高于4个/百平方公里、不平等系数大于0.4的省份。“富而不均”类省份包括河北和浙江两省。因此，在这两个省份中，应该着力改善银行网点分布不平等的状况，首先追求“公平”，其次才是“效率”。

2 it is“Rich and uneven”type。That is higher than the density of geographical financial four/hundred square kilometers、Inequality coefficient is greater than 0.4 province。“Rich and uneven”Kind of provinces including hebei and zhejiang provinces。so，In these two provinces，Should strive to improve banking network distribution inequality,，First pursuit“fair”，This is followed by“efficiency”。

　　三是“均而不富”型。即地理金融密度低于4个/百平方公里、不平等系数小于0.4的省份。“均而不富”类包括：北京、江西、海南、湖南、辽宁、湖北、山西、贵州、广西、吉林、黑龙江、陕西和云南这13省（市、区）。在这类地区，容易产生追求“效率”、忽视“公平”的倾向，金融机构网点的增加往往也是分布在城市地区，因此会导致农村地区的网点数量相对减少，不平等系数有增大的趋势。

Three is“Are not rich”type。That is less than four geographical financial density/hundred square kilometers、Inequality coefficient is less than 0.4 province。“Are not rich”Category includes：Beijing、jiangxi、hainan、hunan、liaoning、hubei、shanxi、guizhou、guangxi、jilin、heilongjiang、Shaanxi province and yunnan the 13（city、area）。In these areas，Easy to produce the pursuit“efficiency”、ignore“fair”tendency，Financial institutions of the network increase was often the distribution in urban areas，So will lead to rural areas relative quantity to reduce the network，Inequality coefficient increase with the rising of。

　　四是“不富不均”型。即地理金融密度低于4个/百平方公里、不平等系数在0.4以上（包括0.4）的省份，包括：福建、广东、宁夏、四川、甘肃、西藏、内蒙古、新疆和青海这9省（区）。其中，福建、广东这两个经济发达地区，提出“城市”后的县域发展程度较低，网点分布也不均。青海、新疆、西藏和内蒙古4省（区）的地理金融密度很低，都在0.5个/百平方公里以下，农村金融排斥程度极其严重。若考虑到县域内部也存在地理金融密度极其不平等的状况，则实际的金融排斥程度要比我们想象的严重得多。

Four is“Uneven not rich”type。That is less than four geographical financial density/hundred square kilometers、Inequality coefficient in more than 0.4（Including 0.4）province，including：fujian、guangdong、ningxia、sichuan、gansu、Tibet、Inner Mongolia、Xinjiang in qinghai province and the 9（area）。Among them，fujian、Guangdong the two economic developed area，Put forward“city”After the county development degree is low，Network distribution uneven also。qinghai、xinjiang、Tibet and Inner Mongolia four provinces（area）Geographical financial density is very low，Is in 0.5 a/the square kilometers below，The rural financial exclusion degree very serious。If considering the county also exist within geographic financial density extremely unequal status，The actual financial exclusion degree than we can imagine is much more serious。

　　在图5中，深蓝色点表示西部地区，橙色点表示中部地区，红色点表示东部地区。可以看到，红色点分布在四个区域中，说明东部地区内部各省的地理排斥类型差异很大，四种类型均有。其中，浙江、河北、福建和广东四省县域的不平等系数大，因此，要尤其注意向“公平”的方向发展。中部地区各省不平等系数小，只是大部分省的地理金融密度都较低。因此，中部地区各省内要协调发展，既要注重“效率”，也要关注“公平”。西部地区除重庆这个直辖市外，所有的省份地理金融密度都较低，且有7个省不平等系数在0.4以上。西部地区内金融发展水平低、且不平等，这样的状况令人堪忧。

In figure 5，Dark blue dots mean to the western regions，Orange point said central regions，Red dots mean region in the east。Can see，Red point distribution in four areas，In eastern provinces that internal geographical rejection type difference is very big，Four types are all available。Among them，zhejiang、hebei、Fujian and guangdong provinces of inequality county four big coefficient，so，To pay particular attention to“fair”The direction of development。The central region provinces equality small coefficient，Just the majority of provinces geographical financial density of low。so，The central region in the provinces to coordinate development，Should not only pay attention to“efficiency”，Also want to pay attention“fair”。In the western region of chongqing outside of municipality directly under the central government，All the provinces geographic financial density of low，And there are 7 provinces not equal coefficient in more than 0.4。The western region development level of financial low、And inequality，This situation is concerned。

　　从图5中也可以看到，不平等系数与地理金融密度大致有负相关的关系。这也就意味着：金融发展平均水平越高的省份，金融的发展也更均等；金融发展平均水平越低的地区，金融发展越不均等。尤其要注意的就是“不富不均”型，在这样的地区，金融机构新增网点时依然会考虑在经济较为发达的城市地区，而不会选择落后的农村地区。因此，会导致其不平等系数的增大，落入“不平等陷阱”，即金融发展越不平等的地方，其金融发展将越来越不平等。这是一个可怕的结论，它意味着“马太效应”已经扩散到金融发展之中。因此，如果不改变当前追求“效率”、忽视“公平”的发展思路，这类地区的前途是让人极其担忧的。同时，这类地区的经济落后，若因只追求“公平”而在农村地区新增网点，也可能导致这些网点经营困难、亏损严重。因此，如何平衡“效率”和“公平”、如何寻找一条适合“三农”特征的农村金融发展之路，将是当前和未来一段时间内农村金融领域的重要课题。

From the figure 5 also can see，Inequality coefficient and geographic financial density to roughly negative correlation relationship。This also means：The higher the level of financial development average provinces，The development of more equal financial also；Financial development, the lower the average of the region，The financial development not equal。Pay particular attention to is“Uneven not rich”type，In this area，Financial institutions when new outlets will still be considered in the economy more developed city area，And would not choose backward in rural areas。so，Can lead to the increase of inequality coefficient，Fall into“Inequality trap”，Namely the financial development of the inequality of the place，Its financial development will more and more inequality。This is a shocking conclusion，It means that“Matthew effect”Has spread to financial developing。so，If you don't change the current pursuit“efficiency”、ignore“fair”Ideas of developing，This kind of region's future is to let a person extremely worrying。At the same time，This kind of region economy behind，If by only for“fair”And new outlets in rural areas，Also may lead to these network management difficulties、loss。so，How to balance“efficiency”and“fair”、How to find a suitable“Agriculture, rural areas and farmers”Characteristics of rural financial development way，Is the current and future within a period of time an important issue in the field of rural finance。

　　（作者单位：重庆农村商业银行江北支行，西华师范大学管理学院，中国人民大学农业与农村发展学院）

（The author unit：Chongqing jiangbei rural commercial bank branch，Sherwood normal university school of management，The people's university of China agriculture and rural development institute）

　　项目研究得到国家自然科学基金（71073163）和教育部博士点基金（20110004110003）资助

Research project by the national natural science funds（71073163）And elsevier（20110004110003）funding