Between Mao and markets: new evidence on segmentation of the bank loan market in China

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<ul><li><p>This article was downloaded by: [Chinese University of Hong Kong]On: 20 December 2014, At: 21:23Publisher: RoutledgeInforma Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House,37-41 Mortimer Street, London W1T 3JH, UK</p><p>Applied Economics LettersPublication details, including instructions for authors and subscription information:http://www.tandfonline.com/loi/rael20</p><p>Between Mao and markets: new evidence onsegmentation of the bank loan market in ChinaMasanori Ohkuma aa Faculty of Education and Integrated Arts and Sciences , Waseda University , 1-6-1 Nishi-Waseda, Shinjuku-ku, Tokyo, 169-8050, JapanPublished online: 05 Aug 2009.</p><p>To cite this article: Masanori Ohkuma (2010) Between Mao and markets: new evidence on segmentation of the bank loanmarket in China, Applied Economics Letters, 17:12, 1213-1218, DOI: 10.1080/00036840902845426</p><p>To link to this article: http://dx.doi.org/10.1080/00036840902845426</p><p>PLEASE SCROLL DOWN FOR ARTICLE</p><p>Taylor &amp; Francis makes every effort to ensure the accuracy of all the information (the Content) containedin the publications on our platform. 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Terms &amp; Conditions of access and use can be found at http://www.tandfonline.com/page/terms-and-conditions</p><p>http://www.tandfonline.com/loi/rael20http://www.tandfonline.com/action/showCitFormats?doi=10.1080/00036840902845426http://dx.doi.org/10.1080/00036840902845426http://www.tandfonline.com/page/terms-and-conditionshttp://www.tandfonline.com/page/terms-and-conditions</p></li><li><p>Applied Economics Letters, 2010, 17, 12131218</p><p>Between Mao and markets: new</p><p>evidence on segmentation of the</p><p>bank loan market in China</p><p>Masanori Ohkuma</p><p>Faculty of Education and Integrated Arts and Sciences, Waseda University,</p><p>1-6-1 Nishi-Waseda, Shinjuku-ku, Tokyo 169-8050, Japan</p><p>E-mail: ohkuma@aoni.waseda.jp</p><p>This article examines the local bank lendings dependency upon local</p><p>deposits within China in the FeldsteinHorioka vein. In the case of</p><p>a transition economy like China, it would be appropriate to assume the</p><p>presence of a significant level of disparity in the cost of funds between</p><p>State-Owned Enterprises (SOEs) and non-SOEs. For this purpose,</p><p>a dataset of the provincial deposit rates and the provincial loan rates for</p><p>the state and the nonstate sectors is built. Even after controlling the</p><p>national- and province-specific shocks, the correlation between the local</p><p>deposit rates and the local loan rates for the nonstate sector, in contrast</p><p>with that for the state sector, is even higher than for the Organization for</p><p>Economic Co-operation and Development (OECD) member countries.</p><p>The findings suggest that serious asymmetric information problems</p><p>between banks and non-SOEs might impede cross-regional lending and</p><p>prevent the development of the nonstate sector within China.</p><p>I. Introduction</p><p>China has maintained a remarkable growth rate sincethe outset of the reform programme in the early1980s. One of the probable engines of Chinaseconomic growth is its financial sector. Since the1990s, there has been a growing consensus in theliterature that Schumpeter might be right (King andLevine, 1993). That is, development of the financialsector promotes economic growth, for instance, byreducing the disparity between the costs of internaland external funds (Rajan and Zingales, 1998), andpromoting the responsiveness to shocks towardsgrowth opportunities (Fisman and Love, 2004).Since the current Chinese financial system is domi-nated by a large banking sector and the role of the</p><p>stock market in allocating financial resources in theeconomy has been limited,1 the features of theChinese banking system have attracted much atten-tion in recent years to gain an insight into itseconomic growth pattern.</p><p>From among a series of inter-related questions thatneed to be addressed, I focus on the followingquestion: how much are Chinese intra-nationalbank loan markets integrated? Surprisingly, however,very few formal investigations have been conductedon domestic capital mobility within China. By way ofexception, Boyreau-Debray and Wei (2004) (hence-forth, BW) explore the segmentation of Chinesedomestic capital markets by applying the modifiedversion of the FeldsteinHorioka test (Feldstein andHorioka, 1980; henceforth, FH), the standard</p><p>1 See, for instance, Allen et al. (2008).</p><p>Applied Economics Letters ISSN 13504851 print/ISSN 14664291 online 2010 Taylor &amp; Francis 1213http://www.informaworld.com</p><p>DOI: 10.1080/00036840902845426</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Chi</p><p>nese</p><p> Uni</p><p>vers</p><p>ity o</p><p>f H</p><p>ong </p><p>Kon</p><p>g] a</p><p>t 21:</p><p>23 2</p><p>0 D</p><p>ecem</p><p>ber </p><p>2014</p><p>mailto:ohkuma@aoni.waseda.jphttp://www.informaworld.com</p></li><li><p>approach used in literature on international finance.They argue that, under perfect capital mobility, thereexists no necessary association between nationalsaving and investment, since financial resourcescan globally seek out the highest expected returns.A substantial amount of literature on this subjecthas expressed skepticism about the FH approach as amethod of measuring international capital mobilityfor various reasons (see for instance, Coakley et al.,1998). Despite this, the FH test has been regarded asa reasonable approach to measure intra-nationalcapital mobility (e.g. Yamori, 1995; BW, 2004).</p><p>An important drawback of BW (2004) is that it hasnot paid adequate attention to Chinas peculiaritiesas a transition economy.2 In a transition economylike China, it would be appropriate to assume thepresence of a significant level of disparity in the costof funds between State-Owned Enterprises (SOEs)and non-SOEs. If this is true, Chinese domesticcapital markets would be segmented, not only on thebasis of geographical units, but also the ownershipform of the borrowers. Unfortunately, however, thereis no satisfactory data available on loans decomposedon the basis of the borrowers ownership form,consistently published by Chinas national authori-ties. It is this lack of data that has preventedresearchers from directly testing the above-mentionedhypothesis.</p><p>The aim of this article is straightforward. I measurethe degree of domestic capital mobility within thebanking system, both in the state and the nonstatesector in China. For this purpose, I develop a pro-vincial-level panel data for deposits and loansdecomposed on the basis of the borrowers ownershipform using the method developed by Zhang et al.(2007), and apply a modified version of the FH test tothe data.</p><p>II. Data and Methodology</p><p>The data set used in this article covers 31 Chineseprovinces (or province-level autonomous regions orsuper-cities) on the mainland during 19992005. Thesources of data are the China Statistical Yearbook(National Bureau of Statistics of China, variousyears), the China Economic Census Yearbook-2004(The State Council of China, 2006) and the ChinaFinancial Statistics (19492005) (Beijing: Zhongguojinrong chubanshe, 2007).</p><p>As mentioned above, since the panel data on banklending decomposed on the basis of the borrowersownership form are not published by Chinasnational authorities on a consistent basis, Iconstruct this data using the method developed byZhang et al. (2007). Following them, considerEquation 1</p><p>Loan=LocalGDPi,t 01SOEOutput=theTotali,t2SOEOutput=the Totali,tCoastDummyiX</p><p>i</p><p>iProvinceDummyii,t</p><p>i,t i,t12i,t jj51 1</p><p>where the dependent variable is the total loan asa share of the provincial Gross Domestic Product(GDP) for province i at time t, the independentvariables are the industrial output share of SOEs andits interaction term with a dummy variable for theprovinces located in the coastal region (that equalsone if the province is located in the coastal region,and zero otherwise),3 province-specific effects, and i,tis the disturbance term. Furthermore, I specify a firstorder autoregressive process, AR(1), to correct forserial correlation in the disturbance term.</p><p>If bank loans are allocated to the state and thenonstate sectors depending on their output share ofthe total, then 1(SOE Output/the Total) or1 2(SOE Output/the Total) would capture theamount of loans to the state sector as a share of theprovincial GDP. Note that the total bankloans should be classified into two components, thatis, that issued to the state sector and the rest issuedto the others. Then the outstanding amount ofloans to the nonstate sector (as a share of provincialGDP) can be obtained by deducting the valuesyielded by the estimated amount of loans to thestate sector (as a share of the provincial GDP)from the total amount of loans (as a share of theprovincial GDP).</p><p>Table 1 reports the estimation results. The esti-mated signs of the output share of SOE are positiveand significant at the 1 and 5% levels (row 1).</p><p>III. Empirical Tests</p><p>Table 2 reports the results. The averaged correlationbetween the deposit rates and the loan rates for the</p><p>2 Payne and Mohammadi (2006) examine the association between saving and investment among transition economies.3 Following the literature, the coastal region in this study includes Beijing, Tianjin, Hebei, Liaoning, Shangdong, Shanghai,Jiangsu, Zhejiang, Fujian, Guangdong, Hainan and Guangxi.</p><p>1214 M. Ohkuma</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Chi</p><p>nese</p><p> Uni</p><p>vers</p><p>ity o</p><p>f H</p><p>ong </p><p>Kon</p><p>g] a</p><p>t 21:</p><p>23 2</p><p>0 D</p><p>ecem</p><p>ber </p><p>2014</p></li><li><p>nonstate sector is 0.91 (row 1). On the other hand, the</p><p>corresponding figure for the state sector is practically</p><p>zero (row 4). For the purpose of comparison, the</p><p>correlation coefficients for the national economies of</p><p>OECD member countries reported in BW (2004) are</p><p>quoted (row 9). Surprisingly, the magnitude of the</p><p>correlation across the OECD member countries</p><p>(0.62) is much lower than that for the nonstate</p><p>sector in China. These comparisons suggest that the</p><p>degree of domestic capital mobility within the bank-</p><p>ing system in the nonstate sector, in contrast with that</p><p>in the state one, is much lower than international</p><p>capital mobility among the OECD member countries.Figure 1 shows the local deposit rates and the local</p><p>loan rates for the state sector (and the nonstate</p><p>sector) averaged over the years 1999 to 2005. As</p><p>shown in Fig. 1, the averaged values of deposit and</p><p>loan rates for Beijing are relatively high. This could</p><p>be due to the fact that the headquarters of the</p><p>Big Four banks in China (Bank of China, China</p><p>Construction Bank, Industrial and Commercial</p><p>Bank of China and Agricultural Bank of China),</p><p>are all located in Beijing. To remove its effects,</p><p>I recalculate the simple correlation excluding</p><p>Beijing, then the new coefficient for the nonstate</p><p>sector (the state sector) is 0.80 (0.06). The results</p><p>remain practically unchanged.Simple correlations, however, only provide</p><p>a preliminary measure of the domestic integration</p><p>of the bank loan market. National- and province-</p><p>specific shocks that can affect the magnitude of</p><p>correlation coefficients between deposit and loan</p><p>rates, other than those owing to the integration of</p><p>the bank loan market, should be controlled.</p><p>I, therefore, apply the conditional FH test developed</p><p>by Iwamoto and van Wincoop (2000) to the Chinese</p><p>provinces to control for these factors.4 The steps</p><p>are as follows. First, I control for national</p><p>Table 1. Estimation of b with AR(1)/fixed effect</p><p>(1) (2)</p><p>Regression of total loans/provincial GDP on Coefficient p-value Coefficient p-value</p><p>SOE output/total output 0.478 (0.179) 0.008 0.459 (0.203) 0.025(SOE output/total output) (Coastal dummy) 0.068 (0.620) 0.913AR(1) 0.448 (0.118) 0.000 0.450 (0.110) 0.000Province dummy Yes YesR2 0.921 0.920Obs. 186 186</p><p>Notes: The dependant variable is the total loan as a share of the provincial GDP during 19992005; SOE output/total outputis the output share of state-owned enterprises; Coastal dummy is a dummy variable that equals one if the province is locatedin the coastal region (Beijing, Tianjin, Hebei, Liaoning, Shangdong, Shanghai, Jiangsu, Zhejiang, Fujian, Guangdong,Hainan and Guangxi) and zero otherwise. Regressions are estimated with AR(1) and fixed effects. Robust SEs, which havebeen corrected for cross-section heteroscedasticity, appear in round brackets.</p><p>Table 2. Correlation between local loan rates and local deposit rates</p><p>Sector Method Period Author Coefficient</p><p>China Nonstate U 19992005 This article 0.909***China Nonstate C (FE) 19992005 This article 0.818***China Nonstate C (2SLS/FE) 19992005 This article 0.839***China State U 19992005 This article 0.040China State C (FE) 19992005 This article 0.024China State C (2SLS/FE) 19992005 This article 0.011China All U 19902001 BW (2004) 0.505**China All C (FE) 19902001 BW (2004) 0.580**OECD All U 19902001 BW (2004) 0.617**OECD All C (FE) 19902001 BW (2004) 0.285**</p><p>Notes: The Two-Stage Least Squares (2SLS) method is used with the lagged right-hand-side variables and province-specificeffects as instruments. *** and ** indicate significance at the 1 and 5% levels, respectively.</p><p>4 Iwamoto and van Wincoop (2000) themselves implement this methodology to examine financial integration across Japaneseprefectures.</p><p>New evidence on segmentation of the bank loan market in China 1215</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Chi</p><p>nese</p><p> Uni</p><p>vers</p><p>ity o</p><p>f H</p><p>ong </p><p>Kon</p><p>g] a</p><p>t 21:</p><p>23 2</p><p>0 D</p><p>ecem</p><p>ber </p><p>2014</p></li><li><p>and province-specific shocks by regressing the</p><p>provincial deposit rates, the provincial loan rates</p><p>for the state sector, and the provincial loan rates</p><p>for the nonstate sector on province-specific determi-</p><p>nants that can affect co-movements between depos-</p><p>its and loans:</p><p>Loan Rate for SOEsi;t 0 YLocal Business Conditioni;t FGovt Consumption=Local GDPi;t</p><p>X</p><p>i</p><p>iProvince Dummyi</p><p>X</p><p>t</p><p>tYearly Dummyt eSLi;t 2</p><p>Loan Rate for Non-SOEsi;t 0 YLocal Business Conditioni;t FGovt Consumption=Local GDPi;tX</p><p>i</p><p>iProvince Dummyi</p><p>X</p><p>t</p><p>tYearly Dummyt eNSLi;t 3</p><p>Deposit Ratei;t 0 YLocal Business Conditioni;t FGovt Consumption=Local GDPi;tX</p><p>i</p><p>iProvince Dummyi</p><p>X</p><p>t</p><p>tYearly Dummyt eDi;t 4</p><p>Fig. 1. Averaged local deposit and loan rates over 19992005Notes: average values of deposits and loans for the state sector (a) and those for the nonstate sector (b) as a share of theprovincial GDP.</p><p>1216 M. Ohkuma</p><p>Dow</p><p>nloa</p><p>ded </p><p>by [</p><p>Chi</p><p>nese</p><p> Uni</p><p>vers</p><p>ity o</p><p>f H</p><p>ong </p><p>Kon</p><p>g] a</p><p>t 21:</p><p>23 2</p><p>0 D</p><p>ecem</p><p>ber </p><p>2014</p></li><li><p>The right-hand-side va...</p></li></ul>