DSpace at VNU: Involuntary excess reserves, the reserve requirements and credit rationing in China

This article was downloaded by: [Purdue University] On: 18 January 2015, At: 12:49 Publisher: Routledge Informa Ltd Registered in England and Wales Registered Number: 1072954 Registered office: Mortimer House, 37-41 Mortimer Street, London W1T 3JH, UK Applied Economics Publication details, including instructions for authors and subscription information: http://www.tandfonline.com/loi/raec20 Involuntary excess reserves, the reserve requirements and credit rationing in China a b Vu Hong Thai Nguyen , Agyenim Boateng & David Newton c a International University, Vietnam National University, Ho Chi Minh City, Vietnam b Glasgow School of Business & Society, Glasgow Caledonian University, Glasgow, UK c Nottingham University Business School, University of Nottingham, Nottingham, UK Published online: 07 Jan 2015 Click for updates To cite this article: Vu Hong Thai Nguyen, Agyenim Boateng & David Newton (2015) Involuntary excess reserves, the reserve requirements and credit rationing in China, Applied Economics, 47:14, 1424-1437, DOI: 10.1080/00036846.2014.995362 To link to this article: http://dx.doi.org/10.1080/00036846.2014.995362 PLEASE SCROLL DOWN FOR ARTICLE Taylor & Francis makes every effort to ensure the accuracy of all the information (the “Content”) contained in the publications on our platform However, Taylor & Francis, our agents, and our licensors make no representations or warranties whatsoever as to the accuracy, completeness, or suitability for any purpose of the Content Any opinions and views expressed in this publication are the opinions and views of the authors, and are not the views of or endorsed by Taylor & Francis The accuracy of the Content should not be relied upon and should be independently verified with primary sources of information Taylor and Francis shall not be liable for any losses, actions, claims, proceedings, demands, costs, expenses, damages, and other liabilities whatsoever or howsoever caused arising directly or indirectly in connection with, in relation to or arising out of the use of the Content This article may be used for research, teaching, and private study purposes Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden Terms & Conditions of access and use can be found at http:// www.tandfonline.com/page/terms-and-conditions Applied Economics, 2015 Vol 47, No 14, 1424–1437, http://dx.doi.org/10.1080/00036846.2014.995362 Involuntary excess reserves, the reserve requirements and credit rationing in China Vu Hong Thai Nguyena, Agyenim Boatengb,* and David Newtonc Downloaded by [Purdue University] at 12:49 18 January 2015 a International University, Vietnam National University, Ho Chi Minh City, Vietnam b Glasgow School of Business & Society, Glasgow Caledonian University, Glasgow, UK c Nottingham University Business School, University of Nottingham, Nottingham, UK Using a sample of 95 banks that covers the period 2000–2011, this article examines Chinese banks’ credit lending behaviour in response to the changes in the reserve requirement ratio in the presence of involuntary excess reserves (IERs) in the banking system The study finds that Chinese banks with positive IERs one period after a reserve requirement shock experience a significantly increased credit supply in response to an increase in reserve requirement ratio However, the reserve requirements have no significant impact on the credit supply in Chinese banks that have negative IERs one period after a reserve requirement shock This article sheds lights on the effectiveness of Chinese monetary policy, which uses reserve requirements as the primary tool to sterilize excess liquidity and restrain credit expansion Keywords: involuntary reserve; credit rationing; Chinese banks; reserve requirement JEL Classification: E51; E52; E58 I Introduction Prior literature examining the liquidity effect of reserve requirements on the credit supply indicates that an increase in reserve requirement ratio drains liquidity and reduce the credit supply (Bernanke and Blinder, 1988; Takeda et al., 2005; Cargill and Mayer, 2006; Mora, 2009; Gunji and Yuan, 2010) Romer (1985) points out that increasing the reserve requirement ratio does not only drain banking liquidity but also imposes a tax on deposits by increasing the deposit costs for banks Deposit cost affects credit lending and other investment alternatives that are available to banks such as government securities investments (Thakor, 1996) While the funding cost for credit lending includes both a deposit cost and a capital requirement cost (Basel Accord), the cost of funding for government securities investments *Corresponding author E-mail: agyenim.boateng@gcu.ac.uk 1424 © 2015 Taylor & Francis Downloaded by [Purdue University] at 12:49 18 January 2015 Involuntary reserve, credit rationing, China consists of only a deposit cost (Thakor, 1996) An increase in the deposit cost reduces the capital requirement cost’s proportion in the cost of funding for credit lending In other words, upon the increase in the deposit cost, the cost of funding for credit lending falls relative to the cost of funding for government securities investments As a result, banks are induced to direct investment funds from government securities into credit lending, that is increase the credit supply (Thakor, 1996) The behaviour above contradicts the bank lending channel’s argument and implies that credit supply tends to increase in response to the increase in reserve requirement ratio It suggests that the liquidity effect and the cost of funding effect of the reserve requirements operate in opposing ways, thereby making the impact of reserve requirements on credit supply undetermined Despite this, the extant literature largely neglects the cost of funding effect and focuses mainly on the liquidity effect of reserve requirement shocks (Takeda et al., 2005; Cargill and Mayer, 2006; Mora, 2009) While a recent study by Nguyen and Boateng (2013) examined the impact of involuntary excess reserve (IER) on monetary policy transmission in China, it is important to point out that they did not analyse the impact of reserve requirements on the credit supply Yet several studies such as Anderson (2009), Conway et al (2010), Ma et al (2011) indicate that the large excess reserves1 in the Chinese banking system is one of the reasons behind the employment of reserve requirements by the People’s Bank of China (PBC) as a monetary policy tool to manage excess liquidity in China The main objective of this article is to examine the Chinese banks’ credit lending behaviour in response to the changes in the reserve requirement ratio, where IERs which are defined as the excess reserves beyond precautionary levels are present in the banking system (i.e the excess liquidity situation) Examining this behaviour is significant because credit supply is the primary funding source in China, which drives Chinese economic growth (Hansakul et al., 2009; Liu and Zhang, 2010) This article therefore contributes to the bank lending literature in two important ways First, this study identifies the liquidity effect and the cost of funding effect of reserve requirements on the credit supply, which is important because 1425 these two effects provide conflicting predictions of credit supply’s response The failure to capture the cost of funding effect may result in an unexpected credit supply expansion after the PBC increases the reserve requirement ratio Second, this study sheds lights on the impact of reserve requirements on credit lending behaviour of Chinese banks in the context where IERs are present This is important because the presence of IERs may attenuate the liquidity effect of reserve requirements This study finds that Chinese banks with positive IERs one period after a reserve requirement shock significantly increase the credit supply in response to an increase in reserve requirement ratio However, the reserve requirements have no significant impact on the credit supply in Chinese banks that have negative IERs one period after a reserve requirement shock The remainder of the study is organized as follows: Section II presents the theoretical background, Section III discusses the methodology and data analysis; Section IV interprets the estimation results Additional analyses and robustness tests are provided in Section V Finally, Section VI concludes the study II Theoretical Background The credit rationing theory contends that banks decline to screen a credit application if the net loan benefit (the difference between loan return and credit lending cost) fails to cover the credit screening cost (Thakor, 1996) A higher credit lending cost reduces the net loan benefit, which leads to an increase in the probability of credit rationing Thakor (1996) identifies the cost of funding and the opportunity cost relative to alternative investments (e.g government securities’ return) as two components of credit lending cost (the cost to supply credit) Although the cost of funding for credit lending includes a deposit cost and a capital requirement cost (the cost to hold required capital to back up bad loans), the cost of fund for investing in government securities consists of the only deposit cost (Thakor, 1996) An increase in the reserve requirements raises the deposit cost because a higher reserve requirement ratio reduces The aggregate excess reserves beyond statutory requirements in Chinese banking system stood at an average of 10% of deposit base in the 1990s and the early 2000s (Anderson, 2009), although the ratio gradually fell to 2.3% in 2011, but compared to banks in the US and Euro-zone countries, it is considered high Downloaded by [Purdue University] at 12:49 18 January 2015 1426 the fraction of deposits that banks can use to finance loans (Romer, 1985; Vargas et al., 2011) In line with the argument of Thakor (1996), it is assumed that reserve requirement changes not greatly affect the loan return rate, the capital requirement cost and government securities’ return (opportunity cost) in the short run These assumptions are argued to hold in the Chinese banking market because the reserve requirements in China are primarily used as a tool to moderate excess reserves, not reflect the monetary policy stance of the PBC (Anderson, 2009) and appear to have an insignificant effect on the interbank market rate (Chen et al., 2011) An increase in deposit cost and unchanged capital requirement cost reduces the capital requirement cost’s proportion in the cost of funding for credit lending In other words, the cost of funding for credit lending falls relative to the cost of fund for government securities investments However, the opportunity cost and loan return not change greatly Therefore, banks are induced to direct investment funds from government securities to credit lending The primary limitation of the credit rationing theory is that it does not consider the liquidity cost Bank credit tends be a long-term commitment and costly to liquidate at short notice (Brunnermeier and Pedersen, 2009) In contrast, government securities can easily be converted into cash, which make them ideal for liquidity contingency Therefore, banks face a higher illiquidity risk (which is equivalent to a higher liquidity cost) when they direct resources to credit lending instead of government securities For this reason, it is argued that the cost of credit lending includes not only the cost of funding and the opportunity cost as proposed by Thakor (1996), but also the liquidity cost compared with the cost of investing in government securities Because a rise in the statutory reserve requirements drains liquidity from the banking system and curtails banks’ ability to raise deposits (Bernanke and Blinder, 1988), the likelihood of a liquidity shortage increases under this circumstance, and the liquidity cost also increases Indeed, the probability of credit rationing increases because of a higher liquidity cost, and banks tend to reduce the credit supply in response to the increase in reserve requirement ratio An increase in the reserve requirement ratio leads to two conflicting effects: although the cost of V H T Nguyen et al funding for credit lending falls relative to the cost of funding for government securities investment caused by an increase in the deposit cost, the liquidity cost increases Because a decrease in the cost of funding for credit lending augments the credit supply and an increasing liquidity cost discourages the credit supply, the effect of an increase in reserve requirements on the credit supply is undetermined However, in the presence of IERs, the cost of funding effect may dominate the liquidity effect Ceteris paribus, an increase in reserve requirement ratio reduces the IERs (Agénor et al., 2004) The presence of the IERs one period after a reserve requirement shock indicates that the increase in reserve requirements fail to eliminate unwanted liquidity in the banks Therefore, the increase in reserve requirements may have an insignificant impact on the liquidity of the banks If the amount of IERs is positive one period after an increase in the reserve requirement ratio, the fall in the cost of funding dominates the increasing liquidity cost, which results in a greater credit supply However, if the amount of IERs is negative one period after a reserve requirement shock, both the liquidity effect and the cost of funding effect are at work in opposing ways, and the impact of reserve requirement shocks on the credit supply remains undetermined Under the credit rationing theory, banks ration credit applications because the information asymmetry between banks and potential borrowers may lead to moral hazards and excessive credit risks to the banks (Thakor, 1996) In the context of China, the problem of information asymmetry between banks and firms is severe because of the poor credit history of the private sector (Firth et al., 2009) In addition, the majority of private firms in China are small and medium enterprises (SMEs) (Allen et al., 2009), and the asymmetric information that exists with respect to SMEs arises from the lack of transparency, less information disclosure, an informal accounting system and weak internal control and governance systems (Berger and Udell, 2006) In Thakor’s (1996) model, government securities not involve capital back-up (Basel I), although this pattern does not hold for Basel II2 and Basel III frameworks, which require banks to take interestrate risks from the securities that they hold into account as a part of the capital requirement The Basel Committee on Banking Supervision, Principles for the Management of Interest Rate Risk, September 1997 Downloaded by [Purdue University] at 12:49 18 January 2015 Involuntary reserve, credit rationing, China Furfine (2001) argues that loans are considered more risky than securities and that the loans therefore require a higher percentage of equity to reflect their larger risk weight In other words, the cost of funding for credit lending always bears an additional capital requirement cost compared to the cost of funding for securities investment In addition, the Chinese bond-market capitalization is very small relative to the credit volume, and the majority of the bond market consists of central-bank bills (Hansakul et al., 2009) whose size is too small to sterilize the excess liquidity in the Chinese banking market (Conway et al., 2010) Moreover, Chinese commercial banks are not allowed to engage in trust investment or stock broking (PRC, 1995, Article 43), which limits the securities investment opportunities of Chinese banks Therefore, in the Chinese banking market, the credit rationing theory is analogous to credit lending versus hoarding IERs, rather than versus investing in securities As IERs are not subject to capital requirement regulations, the capital requirement cost is only present in credit lending Regarding the opportunity cost, the PBC maintains the interest on excess reserves at a fixed rate below deposit benchmark rate; indeed, there were only two adjustments in the period 2000– 2011 (Anderson, 2009; Laurens and Maino, 2009; Ma et al., 2011) For this reason, reserve requirement shocks not affect the opportunity cost In the presence of IERs in the Chinese banking market, it is argued that an increase in reserve requirement ratio does not affect the loan return, opportunity cost or the liquidity cost, but it reduces the relative cost of funding for credit lending This is because the rising deposit cost renders the (additional) capital requirement cost less significant Consequently, Chinese banks tend to expand the credit supply in response to the increase in reserve requirements In light of the above discussion, for banks that have positive IERs one period after a reserve requirement shock, it is expected that the credit supply has a positive relationship with the change in the reserve requirement ratio However, for banks with negative IERs one period after a reserve requirement shock, the liquidity effect and the cost of fund effect operate in opposing ways; hence, the impact of reserve requirement shocks on the credit supply is undetermined 1427 III Methods and Data Analysis Data and the measure of IER Banking data covering the period from 2000 to 2011 are collected from Bankscope-Fitch’s International Bank Database Only commercial banks whose data are available for at least three consecutive years are considered Other types of banks (i.e policy banks, cooperative banks and investment banks) are not included because they may have different objectives rather than profitability The final sample consists of 95 banks and 552 annual observations Monetary policy data are collected from the PBC website Furthermore, other macro data (e.g national and provincial growth rates of the real GDP) are collected from the China Securities Market and Accounting Research database and the China Statistical Yearbook (the National Bureau of Statistics of China) Following the studies of Agénor et al (2004); Nguyen and Boateng (2013), we decompose IERs from precautionary excess reserves IERs ratio is the difference between the ratio of actual excess reserves to deposit and the ratio of the estimated precautionary excess reserves to deposit Excess reserves are defined as the current account holdings of banks, with the central bank that are beyond the required amount of reserves (Bindseil et al., 2006) Aikaeli (2011) modifies the precautionary-excess-reserves model by arguing that banks tend to demand more excess reserves to buffer the credit risk Following Agénor et al (2004), Aikaeli (2011), and Nguyen and Boateng (2013), we model the demand for precautionary excess reserves, and the estimation residual is recorded in the form of IER ERit ẳ ỵ ERi;t1 ỵ LịLR ỵ LịCASH ỵ LịYR ỵ LịARRR ỵ LịR þ α7 YEARt þ εit (1) where τ is a constant term, εit is a well-behaved error term and αj ð LÞ are lag polynomials, which are defined as follows: V H T Nguyen et al 1428 αj ¼ þ αj1 L þ þ αjp Lp ; j ! (2) Table SGMM estimation for precautionary excess reserves Downloaded by [Purdue University] at 12:49 18 January 2015 Dependent Variable: ER ER is the ratio of excess reserves to deposits ER is measured as the ratio of the difference between a bank’s current account balance with the central bank and the required reserve3 over the total customer deposit Following Aikaeli (2011), the loanreturn volatility (LR) is used to capture the credit risk that may trigger deposit withdrawals; LR is measured as the absolute value of the deviation of loan interest income from its trend, which is identified by the filter method that was developed by Hodrick and Prescott (1997) Loan interest income is the ratio of interest income on loan to total customer deposit In addition, the Hodrick–Prescott filter (HP) is a standard method for removing trend movements in the business cycle literature (Ravn and Uhlig, 2002) CASH reflects the cashholding preferences of depositors, which are measured based on the volatility of the ratio of vault cash to total customer deposit by HP filter YR is the ratio of real GDP growth rate to its trend (HP filter), which captures the demand for cash Moreover, ARRR and R are the average reserve requirement ratio set by the PBC within a certain year and the refinance interest rate, respectively; the latter term is the rate that the PBC charges when lending to financial institutions for short-term liquidity support (20-day call loan rate) and reflects the penalty cost if a bank falls short of the required amount of reserves The summary on the statistics and the results on the unit-root tests for the variables of precautionary excess reserve estimation are provided in Appendices and The model is estimated by a System Generalized Method of Moments (SGMM), which was developed by Arellano and Bond (1991), Arellano and Bover (1995) and Blundell and Bond (1998) The number of lags is based on the Aikaike Information Criteria The error term εit which is free of unit-root and serial correlations is collected to index the IER ratio The estimation results in Table show that the demand for precautionary excess reserves has a significantly positive relationship with the credit Constant ER (lag1) LR CASH YR ARRR R Number of observations Number of groups Number of instruments Hansen p-value Second order Arellano–Bond test p-value −0.006 (0.07) 0.44 (0.27) 0.88** (0.38) 0.22 (0.5) −0.04 (0.04) −0.38 (0.32) 3.86** (1.81) 457 95 68 0.927 0.101 Notes: ** denotes statistical significance at 1% level Robust SE are reported in parentheses risk, which confirms the evidence from the study of Aikaeli (2011) SGMM and variable definitions Following Gambacorta (2005), Gunji and Yuan (2010), and Nguyen and Boateng (2013), the following dynamic model is used to examine the impact of reserve requirement shocks on the credit supply in the presence of IERs in China Since the sample covers a relatively short period, only the first lag of dependent variable is considered, and this is in line with prior studies (see Altunbaş et al., 2002; Tabak et al., 2010) LOANit ẳ i ỵ LOANi;t1 ỵ LIQi;t1 ỵ SIZEi;t1 ỵ CAPi;t1 ỵ IERi;t1 ỵ NIMi;t1 ỵ IPt1 ỵ Yt1 þ β9 RRRtÀ1 þ β10 DIERit þ β11 DIERit  RRRt1 ỵ it (3) where i is a constant term and εit is a wellbehaved error term The required reserve is measured as the product of the total customer deposit and the reserve requirement ratio for domestic currency deposits Because the reserve requirement ratio for foreign currency deposits is smaller than what is required for Renminbi (RMB) deposits, the total estimated required reserves is slightly higher than the actual value However, a comparison with this actual value (where available) shows that the real and estimated required reserves are very close because foreign currency deposits account for a very small fraction of the total customer deposit Involuntary reserve, credit rationing, China 1429 Downloaded by [Purdue University] at 12:49 18 January 2015 The IER is obtained as the residuals from the estimation of precautionary excess reserves Following Gambacorta (2005), we include bank-specific characteristics, namely, liquidity (LIQ), bank size (SIZE), capitalization (CAP) and net interest margin (NIM) to control for the bank lending channel Following Gambacorta (2005), the size (SIZE) is normalized not just with respect to the mean over the whole sample period but also with respect to each single period to remove unwanted trends because size is measured in nominal terms As IER is obtained as regression residuals whose sample mean equals zero, IER will not be normalized Following Gambacorta (2005), other bank-specific variables (LIQ, CAP and NIM) are normalized using the mean of the sample as follows: PN SIZEit ¼ log Ait À log Ait Nt i¼1 ! T PN X Lit i¼1 Lit =Ait =T LIQit ¼ À Ait Nt t¼1 Cit À CAPit ¼ Ait ! T PN X i¼1 Cit =Ait =T Nt t¼1 ! T PN X i¼1 NIMRit =T NIMit ¼ NIMRit À Nt t¼1 (4) (5) (6) (7) where N and T are the numbers of observations and years, respectively Moreover, L denotes liquid assets as defined by BankScope, which includes cash, government bonds, short-term claims on other banks (including certificates of deposit) and, where appropriate, the trading portfolio C and A refer to equity (capital) and total assets, respectively Because an increase in reserve requirements is considered to be a tax on the banks, if the banks fail to completely pass this tax onto their borrowers (in the form of higher lending rates) or depositors (in the form of lower deposit rates), the banks’ net interest margin will shrink, thereby reducing the credit supply (Romer, 1985) The model includes net interest margin (NIM) to take the tax effect into account In line with Bankscope’s definition, the net interest margin ratio (NIMR) is measured as the ratio of net interest revenue to total earning assets Credit supply (LOAN) is defined as the change in the natural logarithm of gross loan ( Δln(grossloan)), where grossloan is the total amount of credits that a bank issues during a particular year Interest rate policy (IP) is included to control for the impact of monetary policy stance on credit supply (see Borio and Zhu, 2012) Liu et al (2009) and He and Wang (2012) argue that the open market operation rate (the rate at which the central bank sells or buys government bonds on the open market) in China does not signal the monetary policy stance of the PBC The monetary policy interest rate in China (IP) is proxied by the change in the one-year deposit benchmark (ceiling) rate (DB) because the policy deposit ceiling rates are strictly binding and signal a marketclearing equilibrium in China, but the lending benchmark rate is not (Anderson, 2009; Porter and Xu, 2009) The real GDP growth rate (Y ) is used to capture the credit demand Regarding reserve requirement shock index (RRR), the average of all of the reserve requirement ratios (ARRR) within a certain year is taken; then the reserve requirement ratio shock (RRR) is defined as the change in the average reserve requirement ratio (ARRR) from the previous year Previous studies in the area of monetary policy transmission (e.g Altunbaş et al., 2002; Gambacorta, 2005) point out that the credit supply’s response to the change in the monetary policy rates rather than the monetary policy rate levels can capture the monetary policy effectiveness For this reason, the change in reserve requirement ratio (RRR) instead of the reserve requirement level (ARRR) is used to reflect the policy shocks to the credit supply market DIER is a dummy variable with the value of if IER is positive (IER > 0), and with the value of if IER is negative (IER ≤ 0) The coefficient of the interaction (β11 ) reflects the difference on credit lending in response to reserve requirement shocks of the two groups, that is banks with positive IER versus banks with negative IER one period after the shock A summary of the variable statistics is presented in Table The IER ranges from −22% to 33% of the total deposit and is positive in 43% of the observations During the sample period, the average reserve requirement ratio (ARRR) has a mean of 12.1% and reaches a peak of 20.36% for the six largest banks and 18.36% for the other smaller banks (the PBC has V H T Nguyen et al 1430 Downloaded by [Purdue University] at 12:49 18 January 2015 Table Summary statistics for reserve requirement impact estimations variables Variable Mean SD Skewness Kurtosis Min Max Jarque-bera L/A LIQ C/A CAP SIZE IER DB IP Y LOAN NIMR NIM ARRR RRR 0.25 −0.009 0.085 −0.005 0 0.026 0.001 0.099 0.208 2.58 −0.35 0.121 0.015 0.125 0.125 0.111 0.111 2.058 0.046 0.005 0.005 0.010 0.191 0.82 0.82 0.04 0.019 1.923 1.923 3.84 3.84 0.522 1.35 0.877 −0.669 −0.136 1.670 0.642 0.642 0.033 −0.353 5.427 5.427 17.135 17.135 0.006 11.712 0.146 1.876 −0.494 14.029 1.55 1.55 −1.336 −0.825 0.035 −0.223 −0.137 −0.229 −4.724 −0.219 0.0198 −0.0234 0.071 −0.559 0.195 −2.739 0.06 −0.0217 0.893 0.635 0.872 0.78 5.202 0.328 0.0459 0.0095 0.114 1.761 5.652 2.718 0.2036 0.042 1064* 1064* 8486* 8486* 26.53* 2651* 99.91* 169.3* 10.44* 4104* 95.31* 95.31* 37.6* 24.89* Note: *denotes the rejection of normal distribution at the 1% significance level maintained a two-tier reserve requirement system since 2008) From 2000 to 2002, the PBC kept the reserve requirement ratio constant In contrast, from 2002 to 2011, the reserve requirement ratio was increased every year except 2009 Table presents the panel unit-root tests results for all variables Augmented Dickey–Fuller and Phillips–Perron unit root tests (Fisher-type tests defined by Maddala and Wu, 1999; and Choi, 2001) for panel data indicate that all variables are stationary Because OLS is biased in dynamic models, ‘System’ GMM estimator is used Arellano and Bover (1995) and Blundell and Bond (1998) developed SGMM based on Arellano and Bond (1991) ‘difference’ GMM (DGMM) SGMM is able to deal with the endogeneity and fixed effects in dynamic Table Unit root tests for reserve requirement impact estimations variables Variable Augmented Dickey–Fuller Phillips–Perron IP Y LOAN NIM IER LIQ CAP SIZE RRR 167.9752* 644.8130* 604.7481* 600.7662* 575.7617* 311.8068* 244.7292* 252.3623* 240.9465* 267.9752* 334.8188* 604.7481* 600.7662* 575.7617* 311.8068* 244.7292* 262.1405* 265.6243* Note: *denotes the rejection of the unit root hypothesis at the 1% significance level models (Arellano and Bover, 1995); furthermore, it can overcome the weakness of ‘difference’ GMM, which is inconsistent in the estimations on unbalanced panel data (Roodman, 2006) The lags of regressors are used as instruments IP, RRR and the interaction are treated as endogenous variables Y is treated as an exogenous variable Other variables are considered to be predetermined SGMM is implemented by comment xtabond2 in STATA The optimal model is selected based on the criteria suggested by Arellano and Bond (1991) and Roodman (Roodman, 2006, 2009) in Appendix IV Estimations Results and Discussion The results from the estimations are reported in Table (estimation 1), and the residuals are free of unit-root and serial correlation Regarding the control variables, IER significantly increases credit supply Bank size (SIZE) and capital (CAP) have positive impacts, while liquidity (LIQ) has a negative impact on credit supply at significant level of 10% Net interest margin (NIM), monetary policy interest rate (IP) and GDP (Y) not statistically affect credit supply The IER dummy variable (DIER) is not statistically significant, indicating that there is no difference in credit supply between banks with positive and negative IERs, ceteris paribus The impact of reserve requirement shock on credit supply is measured as follows: Involuntary reserve, credit rationing, China 1431 Downloaded by [Purdue University] at 12:49 18 January 2015 Table SGMM estimations for reserve requirement impact on credit supply (LOAN) Dependent variable: LOAN (1) IER > (2) Constant LOAN (lag1) RRR DIER RRR × DIER IER LIQ SIZE CAP NIM IP Y Number of observations Number of groups Number of instruments Hansen p-value Second order Arellano–Bond test p-value 0.04 (0.7) 0.17** (0.08) −0.92 (1.36) −0.002 (0.05) 4.09** (2.05) 0.55** (0.26) −0.41* (0.24) 0.04* (0.02) 0.66* (0.36) −0.003 (0.04) −7.94 (6.28) 1.03 (3.48) 331 89 80 0.798 0.851 IER < (3) −0.34 (0.47) 0.62*** (0.16) 2.41** (1.09) −0.04 (1.03) 0.08 (0.25) −1.37 (2.14) 0.64** (0.28) −0.2 (0.44) −0.04 (0.04) 0.32 (0.72) −0.02 (0.05) −14.54** (8.07) 4.04 4.51 151 69 37 0.901 0.278 1.22* (0.73) −0.38 (0.66) −0.03 (0.07) 0.82 (1.09) 0.12 (0.11 −7.55 (16.88) 2.94 (10.59) 186 71 23 0.752 0.616 Notes: ***, ** and * denote statistical significance at the 1%, 5% and 10% significance levels, respectively Robust SE are reported in parentheses @LOAN ẳ ỵ 11 DIER @RRR (8) For banks with negative IER one period after reserve requirement shocks (the value of DIER equals 0), the impact of reserve requirement shocks on credit supply is reflected on β9 , which is negative and not statistically significant This supports the argument that the liquidity effect and the cost of fund effect operate in opposing ways in response to reserve requirement shocks for banks with negative IERs, and hence, the impact of reserve requirement shocks on the credit supply is undetermined For banks with positive IERs one period after reserve requirement shocks (the value of DIER equals 1), the impact of reserve requirement shocks on credit supply is @LOAN ¼ β9 þ β11 ¼ À0:92 þ 4:09 ¼ 3:17 @RRR The result shows that the coefficient of the interaction β11 is positive, statistically significant and much greater than β9 The sum of β9 and β11 is positive, indicating that banks with positive IERs one period after reserve requirement shocks tend to increase credit supply in response to increases in reserve requirement ratio The model is further estimated separately for two groups, that is banks with negative IERs (IERit ≤ 0) and positive IERs (IERit > 0) one period after reserve requirement shocks (RRRt−1) without the IER dummy and the interaction The results in Table (estimations and 3) show that the impact of reserve requirement shock (β9 ) on credit supply is positive and statistically significant for banks with positive IERs but not significant for banks with negative IERs This evidence supports the following argument: if an increase in the reserve requirement ratio fails to eliminate IERs completely (i.e if positive IERs remain one period after the hike in reserve requirement ratio), banks tend to expand their credit supply in response to this increase in reserve requirement ratio This finding contradicts the evidence from prior studies, which report the negative relationship between the reserve requirement ratio and the credit supply (e.g see Takeda et al., 2005; Cargill and Mayer, 2006; Mora, 2009) One possible reason for the difference is that the prior studies not consider IERs and the cost of funding effect These studies therefore overestimate the liquidity effect and deduce that there is a negative relationship between the reserve requirement ratio and the credit supply However, this finding supports the study of Qin et al (2005) who find that an increase in reserve requirement ratio generates a small rise in GDP growth rate in China V H T Nguyen et al 1432 V Additional Analysis and Robustness Tests The robustness tests are reported in Table 5, and the tests are summarized in Table The PBC employs a loan ceiling as a monetary policy tool to moderate the credit supply; its primary target is the four stateowned commercial banks (SOCB) (Geiger, 2008) These loan limits may make the four state-owned commercial banks less responsive to reserve requirement shocks To address the effect of loan limits, we exclude the four state-owned banks from the sample Table Estimation results for additional analysis and Robustness tests Dependent variable: LOAN (4) (without SOCB) (5) (6) Constant −0.41 (0.8) −0.02 (0.25) −0.9 (1.05) −0.02 (0.05) 3.14** (1.41) 0.94*** (0.34) −0.1 (0.29) 0.01 (0.02) 0.99 (0.99) 0.06 (0.06) −15.97 (12.4) 6.53 (8.03) −0.25 −0.35 −0.44 (0.38) (0.25) (0.61) 0.19** 0.11 0.21 (0.09) (0.09) (0.2) −1.04 −0.24 −0.57 (1.53) (1.01) (1.34) 0.02 −0.003 0.02 (0.05) (0.04) (0.05) 4.62** 3.15** 4.42** (2.32) (1.48) (2.27) 0.62** 0.54** 0.92** (0.25) (0.26) (0.44) −0.06 −0.26 −0.08 (0.28) (0.19) (0.22) 0.05** 0.06* −0.02 (0.03) (0.03) (0.02) 0.51 0.75 0.41 (0.36) (0.51) (0.53) 0.009 −0.005 −0.57 (0.05) (0.04) (0.07) −12.69** −13.96*** −17.46 (6.34) (3.71) (10.7) 2.94 6.09 (3.36) (6.32) LOAN (lag1) Downloaded by [Purdue University] at 12:49 18 January 2015 RRR DIER RRR × DIER IER LIQ SIZE CAP NIM IP Y LP 0.09 (0.41) 0.17** (0.08) −1.13 (1.22) 0.006 (0.04) 3.97** (1.91) 0.61** (0.26) −0.42* (0.25) 0.05** (0.02) 0.64 (0.26) 0.004 (0.04) 0.5 (3.91) −5.32 (5.86) IOR (7) (8) (9) (10) 0.39 (0.37) 0.17* (0.09) 0.28 (1.08) 0.06 (0.05) 2.69* (1.55) 0.52** (0.24) 0.13 (0.3) 0.06** (0.03) 0.72** .(0.35) 0.03 (0.04) −4.37 (6.12) −2.08 (3.45) 0.1 (0.38) 0.21** (0.09) −1.09 (1.75) −0.01 (0.67) 4.84* (2.91) 0.65** (0.26) −0.44* (0.26) 0.04* (0.02) 0.59 (0.39) −0.01 (0.04) −7.4 (6.33) 0.36 (3.49) 10.38* (5.56) RGDP 4.3** (2.03) OWNERSHIP_NSOB OWNERSHIP_F −0.01 (0.09) −0.2 (0.16) ACCOUNTING −0.09*** (0.03) M&A Number of observations 306 Number of groups 85 Number of instruments 38 Hansen p-value 0.661 Second order Arellano–Bond test 0.708 p-value 331 89 82 0.824 0.988 331 89 67 0.621 0.698 331 89 82 0.862 0.486 331 89 54 0.469 0.794 331 89 83 0.882 0.896 Notes: ***, ** and * denote statistical significance at the 1%, 5% and 10% significance levels, respectively Robust SE are reported in parentheses −0.08 (0.06) 331 89 62 0.496 0.765 Involuntary reserve, credit rationing, China 1433 Table Summary on additional analysis and Robustness tests Issue Test performed Specification Downloaded by [Purdue University] at 12:49 18 January 2015 Loan ceilings set for four SGMM estimation for The four state-owned banks are excluded from the sample the sample without state-owned commercial the four state-owned banks commercial banks Finding No significant difference in the results compared with the main estimation, which includes the four state-owned commercial banks in the sample No significant difference in the results compared with the main estimation, which uses deposit benchmark rate as an index for monetary policy No significant difference in the results compared with the main estimation, which does not include without interest on excess reserve No significant difference in the results compared with the main estimation where national real GDP growth rate is used for all banks Alternative index of monetary policy SGMM estimation including lending benchmark rate Lending benchmark rate is used instead of deposit benchmark rate to index monetary policy Excess reserve remuneration SGMM estimation including interest on excess reserves Interest on excess reserve is used to capture the effect of excess reserve remuneration Provincial operation SGMM estimation with provincial GDP growth rate Ownership structure and operational objective SGMM estimations with ownership dummies Data consistency: introduction of two-tier reserve requirement system and changes in Chinese accounting standards in 2008 Merger and Acquisition (M&A) SGMM estimations with accounting dummies National real GDP growth rate is applied for State-owned commercial banks, joint stock commercial banks and foreign banks Provincial real GDP growth rate is applied for city commercial banks and rural commercial banks No significant difference in the Include Ownership Dummies results compared with the main such that 1, and are estimation, which does not dummies for state-owned, include ownership dummies nonstate-owned and foreignowned banks, respectively No significant difference in the Include Accounting Dummies results compared with the main such that and are dummies estimation which does not for periods prior to and after include accounting dummies 2008, respectively SGMM estimations controlled for M&A Include M&A dummies with value of for merger and acquisition event and otherwise However, the estimations without the four stateowned commercial banks have similar results to the estimations that include these four banks To further check for the robustness, the model is estimated using lending benchmark (LP) rate as an index for monetary policy interest rate as contrast to the deposit benchmark rate in the main estimation The robustness test’s results show no significant difference to that of the main estimation In addition, as excess reserve remuneration may affect credit supply, the robustness test including interest on excess reserves (IOR) is carried out, and there is no No significant difference in the results compared with the main estimation which does not include M&A dummies significant difference in the results compared to the main estimation, which does not include IOR Xu (2011) points out that city commercial banks and rural commercial banks in China tend to operate on a provincial scale rather than a national scale To take into account the effect of credit demand, the provincial GDP growth rate is used for both city commercial banks and rural commercial banks, whereas the national GDP growth rate is applied to other types of banks The results show no significant difference from the main estimation, where the national GDP growth rate is applied to all banks Downloaded by [Purdue University] at 12:49 18 January 2015 1434 Moreover, it is argued that the Chinese monetary policy is more enforceable against Chinese stateowned banks than nonstate-owned banks (Geiger, 2008) It has also been suggested that foreign banks are less prone to liquidity effect of reserve requirement shocks because foreign banks can receive liquidity support from their home banks (Tabak et al., 2010; Ahtik, 2012) To ensure that the effects of reserve requirements on the credit lending behaviours of banks that have and lack IERs are robust across different ownership structures, we include ownership dummies, that is state-owned, nonstate-owned (OWNERSHIP_NSOB) and foreign ownership (OWNERSHIP_F) in the estimations The results are more or less identical to the main estimation, which has no ownership dummies Since 2008, the PBC has adopted a two-tier reserve requirements system in which the reserve requirement ratio for the six largest commercial banks is 2% higher than that applied to other banks (Ma et al., 2011) In addition, the new accounting standards introduced in China in 2008 may cause data inconsistency To take into account the effects from these events, the robustness test is conducted by including an accounting dummy (ACCOUNTING) to capture the difference between the two periods (prior to and after 2008) The results show no significant difference from the main estimation, which does not include an accounting dummy Moreover, we control for the effects of mergers and acquisitions (M&A) on the reporting of financial statements by including an M&A dummy; the results are essentially identical to the main estimations which lacks an M&A dummy VI Summary and Policy Implications This study examines the impact of the changes in the reserve requirement ratio on the credit lending behaviour of banks in China, where IERs in the banking system are high This study argues that reserve requirement shocks impose not only a liquidity effect but also the cost of funding effect on the credit supply An increase in the reserve requirement ratio appears to increase the liquidity cost but reduce the cost of fund for credit lending relative to the cost of funding for securities investments The findings of this study indicate that IERs render the liquidity V H T Nguyen et al effects of reserve requirement shocks insignificant Therefore, in the presence of IERs, the cost of funding effect dominates the liquidity effect The study finds that banks with positive IERs one period after a reserve requirement shock tend to increase the credit supply in response to an increase in the reserve requirement ratio However, the impact of reserve requirement shocks on the credit supply appears to be insignificant for banks with negative IERs one period after a reserve requirement shock The PBC actively uses reserve requirements as a monetary policy tool to reduce excess liquidity and moderate the credit supply in the Chinese banking market (Anderson, 2009; Conway et al., 2010; Ma et al., 2011) However, if an increase in the reserve requirement ratio fails to completely eliminate IERs, this increase in reserve requirements unexpectedly tends to induce Chinese banks to increase the credit supply, which makes the reserve requirement instrument not only ineffective but also counterproductive For this reason, it is suggested that the PBC should take into account the trade-off effect of the reserve requirements between the reduction of excess liquidity and the expansion of credit In addition, to discourage lending, the PBC should consider increasing the interest rate on excess reserves At a higher interest rate for excess reserves’ remuneration, the opportunity cost on the credit supply increases and banks may therefore increase credit rationing and reduce the credit supply This study has examined an under-researched area with respect to the impacts of reserve requirements on the credit supply in an emerging market economy, where the level IERs consistently appears to be high The findings are interesting but preliminary because of the sample size When quarterly data becomes available, further studies appear to be warranted to better capture the instantaneous credit supply response to reserve requirement shocks Acknowledgement The authors would like to thank the Journal’s referees for helpful comments on earlier drafts of the 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Note: * denotes the rejection of normal distribution at 1% significance level Involuntary reserve, credit rationing, China 1437 Appendix Unit root tests for variables of precautionary excess reserve estimation Variables Augmented Dickey–Fuller(1) Phillips–Perron(1) KPSS(2) ER LR CASH YR ARRR R 569.5294* 433.4773* 515.2204* −3.462* 0.459 −3.117** 569.5294* 433.4773* 515.2204* −3.746* 1.122 −2.221 0.182* 0.0987*** Notes: * and ** denote the rejection of the unit root hypothesis at 1% and 5% significance levels, respectively * and *** denote the fail to reject the trend stationarity at 1% and 10% significance levels, respectively Downloaded by [Purdue University] at 12:49 18 January 2015 Appendix xtabond2 model selection criteria Criteria Requirements description F-test Arellano–Bond test Reject the null hypothesis that independent variables are jointly equal to zero First-order serial correlation but no second-order serial correlation in the residuals (Arellano and Bond, 1991) Sargan statistic is biased in one-step estimator with ‘Robust’ option (Roodman, 2006) Therefore, Sargan Test is not considered Sargan Test ● p-value ≥0.25 (Roodman, 2009) Hansen J-statistic Difference-in-Hansen ● p-value of is the sign of inappropriate model (Roodman, 2009) Steady state The estimated coefficient on the lagged dependent variable should have a value less than (absolute) unity (Roodman, 2009) Number of The number of instruments should not exceed the number of groups (i.e number of banks) instruments (Roodman, 2009) Optimal instruments Roodman (Roodman, 2006, Roodman, 2009) suggests reporting how the optimal number of instruments The standard treatment on lag-limits is used, such that lag-limits start from lag2 for endogenous variable (and from lag1 for exogenous and predetermined) to the most available lag The ‘collapse’ option is used to keep the number of instruments within Stata’s size limit A number of other regressions are estimated by adjusting the upper and lower lag-limits The regression which satisfies all the criteria listed above and has highest p-value of Hansen J test is selected as the optimal regression Note: Compiled by the authors based on Roodman (2006); Roodman (2009); Arellano and Bond (1991)  ... investment opportunities of Chinese banks Therefore, in the Chinese banking market, the credit rationing theory is analogous to credit lending versus hoarding IERs, rather than versus investing... Introduction Prior literature examining the liquidity effect of reserve requirements on the credit supply indicates that an increase in reserve requirement ratio drains liquidity and reduce the. .. response to the increase in reserve requirement ratio It suggests that the liquidity effect and the cost of funding effect of the reserve requirements operate in opposing ways, thereby making the impact