中國影子銀行之空間分析

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2018

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Abstract

本研究探討「地級市」空間單元之各項環境變數對「中國影子銀行」之影響。其中,透過「社會融資規模增量」、「信託與委託貸款及未貼現銀行承兌匯票增量」、「人民幣貸款」、「委託貸款」、「房地產業貸款餘額」、「規模以上中小企業資產」、「小額貸款公司貸款餘額」等變數對中國影子銀行進行估計。所使用的研究方法包括「空間影響性局部指標」(LISA)分析以及「地理加權迴歸」(GWR)分析,並將實證分析的環境自變數區分為四大類之「外商銀行」變數、「金融發展」變數、「經濟發展」變數以及「地理區位」變數,探討四類環境變數中,對中國影子銀行具影響性之變數。   實證結果顯示,「外商銀行家數」、「進出口總額」、「GDP占該省比重」、「經濟基礎評分」、「人均生活用電量」、「社會消費品零售總額」對於中國影子銀行相關變數之影響性,在整體中國幾乎一致呈現「顯著正相關」,影響性亦同時存在於金融中心城市。唯「信託與委託貸款及未貼現銀行承兌匯票增量」及「小額貸款公司貸款餘額」影響性呈現不穩定,因存在較大「地理空間異質」。研究發現,整體中國的區域經濟與金融發展情況,存在大程度的地理區位異質性。
This study aimed at analyzing the influence on China’s shadow banking which is defined as “aggregate financing to the real economy” including trust loans, entrusted loan, undiscounted bankers’ acceptances, RMB loans, SME’s assets (Small and Me-dium-sized Enterprises) and microloans. Spatial analysis method is adopted for statis-tical data of prefecture-level cities in China, and is used to analyze the spatial distribu-tion of the shadow banking in China by using LISA and GWR analysis. The impact factors can be divided into 4 categories; they are foreign bank variables, financial de-velopment variables, economic development variables and geographical location var-iables. The empirical results of China’s shadow banking show that foreign banks, im-ports and exports, province-level divisions by each province's GDP, the score of economy and infrastructure, electricity consumption per capita, total retail sales of consumer goods are significant variables which have strong positive correlation with China’s shadow banking. These situations also exist in financial centers, such as “Shanghai” and “Beijing”. The study found that there is a high degree of geographical heterogeneity in the overall financial development of China’s regional economy.

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中國影子銀行, 空間分析, 外商銀行區位, 地級城市, 空間異質, 地理加權迴歸, China’s shadow banking, spatial analysis, the location of foreign banks, prefecture-level cities, geographical heterogeneity, geographically weighted regression

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