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Regional Differences of Rural Financial Exclusion ——In Gansu and Jiangsu Province

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Regional Differences of Rural Financial Exclusion ——In Gansu and Jiangsu Province Regional Differences of Rural Financial Exclusion ——in Gansu and Jiangsu Province Yuying Zhao Department of Agricultural Economics University of Arkansas [email protected] Selected Paper prepared for presentation at the Southern Agricultural Economics Association’s 2016 Annual Meeting, San Antonio, Texas. February 6-9, 2016. Copyright 2016 by Yuying Zhao. All rights reserved. Readers may verbatim copies of this document for non-commercial purposes by any means, provided this copyright notice appears on all such copies. Abstract At present, China is facing a serious problem of financial exclusion in rural areas, which restricts the development of rural economy and even the comprehensive, balanced and sustainable development of the overall real economy. From the perspective of regional differences in Gansu and Jiangsu provinces and between these two provinces, this paper establishes the Index of Rural Financial Exclusion, and explores the relationship between the refined indicators. Combining the economic theory, this paper uses double logarithmic models to analyze empirically on the relationship between the balance of loans per person and two factors: the density of branches with respect to population and GDP per capita and then compares these two models. We use this model to discuss the driving factor that can help to alleviate rural financial exclusion in different regions. In this paper, comparative analysis, theoretical analysis, empirical analysis, qualitative analysis and quantitative analysis are methods used to analyze the statistical data issued by the China Banking Regulatory Commission. This paper integrates the analyses of rural financial exclusion in provinces and between provinces, and comes to these conclusions about the rural financial exclusion problem of Gansu Province and Jiangsu Province in micro and macro level: (1) the forms of rural financial difference between areas are diverse. The degree of financial exclusion in Gansu are higher than that in Jiangsu, (2) the policy-related loans issued in Gansu are effective, (3) deposits absorbed in areas that are highly financial excluded flow to the regions facing relatively slighter exclusion. The capital allocation function of rural financial markets in Gansu should be improved, (4) two indicators, balance of loans per capita and the number of financial institution branches per 10,000 populations, are positively related. If the number of financial institutions branches in Gansu Province is increased, the balance of credit per capita will be increased, further, it will alleviate rural financial exclusion effectively. Key words: Rural finance， Financial exclusion， Regional differences， Double logarithmic model 2 Introduction Since 2004, Chinese central government has issued twelve No. 1 Central Documents, each as the first policy document of each year, stressing the importance of agriculture and rural reforms, known as “San-nong” policies. “San-nong” is a Chinese term put forward by Wen (1996) with the meaning of a combination of agricultural, rural areas and farmers. Policies related to these three rural issues have been the top priority of Chinese government. The rural finance is a significant component of “San-nong” policies. However, rural finance is a weak section throughout the whole financial service system, containing problems such as inefficiency, imbalance between capital supply and demand, etc. Now China is facing serious financial exclusion in rural areas, and there are mutual inhibition "Matthew Effect" between the rural economy and rural finance. So if rural financial problems cannot be resolved, it will restrict the development of rural economy and even the overall development of real economy. To solve this, rural financial reforms have been launched, hoping financial exclusion can be eased. In recent No.1 Central Documents, directions such as speeding up innovation of rural financial system and pushing forward rural financial reforms have been pointed out. A more accessible rural financial system as a goal, is considered positively related to the development of agriculture industry, farmers’ income improvement, rural economic growth, and many other key issues in rural areas. Financial exclusion measures the development of the inclusive financial system from an opposite side, and an inclusive financial system is one of the aims of China’s rural financial reforms. Studies focusing on financial exclusion in China can provide theoretical basis and practical guidance to China's rural financial reforms. While the economies in rural areas differ significantly across regions, financial exclusion may show different patterns in different regions. Among all provinces and autonomous regions, Gansu, a province located in western China, is 3 underdeveloped, and ranked the 27th in terms of competitiveness of agriculture; Jiangsu, a province located in eastern costal area, is more developed, and ranked the 3rd in terms of competitiveness of agriculture (Qi, 2007). So Gansu and Jiangsu are representative with respect to both agricultural and overall economic development, and they can represent less developed and more developed provinces, respectively. Taking these two provinces as examples to study rural financial exclusion may well reflect the regional differences of rural financial exclusion. The ideology of financial exclusion first appeared in Mckinnon’s and Shaw’s theory of financial repression, but the study of financial exclusion really began in the early 1990s (Leyshon & Thrift, 1993). There is no standard definition of financial exclusion, but the basic content is certain: some customers are unable to obtain necessary financial services through appropriate channels (Panigyrakis et al., 2002). Financial exclusion is a dynamic compound concept, including following five dimensions of factors: access (geographical) exclusion, condition exclusion, price exclusion, marketing exclusion and self-exclusion (Kempson & Whyley, 1999) this classification method was later accepted by most scholars. But subsequent studies have also pointed out the shortcomings of the method: overlapping among dimensions and measuring difficulties. Financial Services Authority (FSA) (2000) noted that the existence of financial exclusion would have serious impact on regional economy. In areas which are highly-financial excluded, financial exclusion will lead to problems such as stagnant economy, poverty, unequal income distribution, seriously affecting regional development and stability (Leyshon & Thrift, 1995). Scholars also investigated in factors that can cause financial exclusion, such as Kempson & Whyley (1999) believe that the financial exclusion is related to income, language, culture, ethnicity, religion, age and other factors, such as geographical location, marketing strategy and legislation, etc. World Bank (2008a; 2008b) illustrated that income, social class and transaction costs played a leading role in the resulting 4 financial exclusion, using a sample of 54 countries. In the aspects of regional differences in financial exclusion and depicting the extent of exclusion, Devlin (2005) conducted his research from the aspect of regional differences of financial exclusion, and proved that the development level of regional finance residents can significantly impact financial exclusion. Studies have confirmed the existence of financial institutions branches can effectively alleviate financial exclusion (Dymski & Veitch, 1996). Although branches are not the only way to provide financial services, it does have a close link between the size of financial branches’ network and the availability of financial services. Leyshon et al. (2006) pointed out that the existence of financial institution branches can reduce the information asymmetry between institutions and clients, and improve the degree of mutual trust, while maintaining the cost for the poor to access appropriate financial services at a certain level. Due to multidimensional property of financial exclusion, scholars have been exploring a more accurate way to measure the extent of financial exclusion. Southeast England Development Agency (SEEDA) used a large amount of first-hand and second-hand data to calculate the Index of Multiple Deprivation which has highly positive correlation with financial exclusion. Beck et al. (2007) proposed eight financial indicators to measure inclusiveness of finance: the number of financial institution branches per 10 thousand population, the number of financial institution branches per 100 square kilometers, the number of ATMs per 10 thousand population, the number of ATMs per 100 square kilometers, savings per capita/GDP per capita; loans per capita/ GDP per capita, the number of savings account per thousand population, the number of loans account per thousand population. An Index of Financial Inclusion (IFI) was developed by Sarma (2008) to measure the extent of comprehensive financial inclusion of a region, including the following three dimensions: the depth of financial services, the availability of financial services and the usage of 5 financial services. Their IFI simplify all the dimensions of financial inclusion to an index to measure the specific circumstances of financial exclusion in a particular area. Data and Methodology Methodology Developing an Index of Rural Financial Exclusion (IRFE) Beck et al. (2007) first proposed eight financial indicators to measure inclusiveness of finance, but how to select the appropriate indicators to represent the financial inclusion with a comprehensive
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