RESERVE REQUIREMENTS AND THE BANK LENDING CHANNEL IN CHINA Zuzana Fungáčová (Bank of Finland) Riikka Nuutilainen (Bank of Finland) Laurent Weill (University of Strasbourg & Bank of Finland)

MOTIVATION The aim of this research is to provide new evidence on the transmission of monetary policy in China. This question is of high importance as banks play a key role in the Chinese financial system and provide most of the funding to firms. Bank loans are the largest source of external funding for firms with 75% of all external funding sources at the end of 2010. We investigate the effectiveness of the bank lending channel which is a key channel for the transmission of monetary policy.

MOTIVATION The bank lending channel is based on the idea that, owing to imperfect substitutability between bank lending and bonds, monetary policy influences the supply of bank loans. A monetary policy tightening increases the opportunity cost of holding deposits, resulting in a decrease in bank lending in line with the reduction in funding sources. It has been widely investigated in the US and in Europe (e.g., Gambacorta, 2005; Fungacova, Solanko and Weill, 2014), but less so in China (Gunji and Yuan, 2010).

MOTIVATION Major difference between China and developed countries: In China, reserve requirements ratio (RRR) has been intensively used as a regular policy tool, especially since the wake of the global financial crisis. In 2007 alone, the reserve requirements ratio was adjusted ten times, and it was changed 15 times between 2010 and 2013. To gauge the monetary policy transmission mechanism in China, it is therefore necessary to assess the effectiveness of this monetary policy tool.

AIM OF THIS PAPER To examine the effect of changing the reserve requirements ratios on the transmission of the monetary policy through the bank lending channel in China. We analyze the reaction of loan supply to monetary policy actions using the methodology of Kashyap and Stein (1995, 2000). Methodology commonly used in the literature on the bank lending channel (e.g. Gambacorta and Marques-Ibanez, 2010; Fungacova, Solanko and Weill, 2014). We use a large dataset on Chinese banks for 2004-2013. Unlike previous studies on Chinese banks where only the data on the largest or listed banks are used (e.g., Gunji and Yuan, 2010), we have over 170 banks in our current dataset.

CONTRIBUTION 1. Evidence on how changing the reserve requirements influences bank lending in China. We also consider other monetary policy tools including i.e. the overnight interbank rate to assess whether reserve requirement ratios are more effective than other monetary policy instruments. As such, the impact of reserve requirement ratios is of prime concern not only in absolute terms but also relative to other monetary policy tools.

CONTRIBUTION 2. Helps understanding how bank ownership can influence the transmission of monetary policy. Coexistence of different types of banks in terms of ownership in the Chinese banking industry. Bhaumik, Dang and Kutan (2013): evidence in India that bank ownership influences monetary policy transmission. We are therefore interested whether the effectiveness of changes in reserve requirements is influenced by bank ownership.

IMPLICATIONS 1. It provides evidence on the effectiveness of the reserve requirement ratio for the bank lending channel. As such it helps understand the transmission mechanism of monetary policy. 2. We contribute to the debate concerning bank ownership in China. We inform on the consequences of privatization and foreign entry policies on the transmission of monetary policy.

THE MONETARY POLICY FRAMEWORK IN CHINA Contrary to central banks in the advanced economies, the PBC employs a variety of policy instruments: price based tools, for example benchmark and other policy interest rates and open market operations quantity based tools, such as reserve requirement ratios, window guidance and other administrative measures. Monetary policy framework in China has evolved together with the economic development. The direct credit plans were abolished in 1998, when the policy was shifted to a more market based direction.

THE MONETARY POLICY FRAMEWORK IN CHINA RRR is considered to be among the most important policy instruments in China. Changes in reserve requirements tend to signal the policy aim to tighten or loosen the bank lending, and hence, the monetary policy stance. In 2004–2013 the RRR has been changed more frequently than the benchmark interest rates.

THE MONETARY POLICY FRAMEWORK IN CHINA All banks in China are required to hold central bank reserves, but the RRRs across banks differ. In 2008 the RRR system was differentiated for different types of banks. The largest commercial banks currently have two percentage points higher RRR than the smaller banks. In 2011 the PBC introduced an opaque ‘dynamically differentiated RRR’ scheme with an aim to countercyclically guide the aggregate credit supply. The RRRs for individual banks are adjusted taking into account, for example, the credit portfolio, soundness and systemic importance of the bank (People’s Bank of China, 2012, p. 15).

THE MONETARY POLICY FRAMEWORK IN CHINA Most of the policy decisions, including interest rate changes, have to be approved by the State Council before their execution. Nevertheless, the reserve requirements ratio (RRR) can be changed directly by the People’s Bank of China (PBC). That is why this instrument plays a special role in the Chinese monetary policy. Hence as the PBC enjoys greater discretion in making reserve requirement ratio decisions, it makes RRR a more timely instrument.

LITERATURE REVIEW Few empirical studies on the monetary policy transmission in China using the different instruments with somewhat contradictory findings. He, Leung and Chong (2013): the Chinese economy responds strongly to total lending and money supply shocks and only mildly to benchmark lending rate, market interest rate and other “market-based” shocks in 1998–2010. Fernald, Spiegel and Swanson (2015): the RRR and benchmark interest rate instruments are found to be effective in determining inflation and economic activity in 2000–2013. Money supply and loan growth play insignificant role => monetary policy transmission mechanism in China is beginning to look ‘more standard’.

LITERATURE REVIEW Only one study examining the bank lending channel with the Kashyap and Stein (1995, 2000)’s approach like us: Gunji and Yuan (2010). On a small sample of 19 banks for the period 1985-2007, they consider several monetary policy instruments including reserve requirements. Focus on the influence of profitability. They find limited evidence for the bank lending channel when considering banks’ responses to monetary policy depending on their capitalization, liquidity, and size (only for size). They observe that greater profitability of banks makes them less sensitive to monetary policy.

LITERATURE REVIEW Other related studies from Nguyen and Boateng (2013), Xiong (2013) and Hou and Wang (2013) looking respectively at the impact of involuntary excess reserves, implementation of capital requirements and banking marketization on the bank lending channel.

DATA Yearly bank-level financial statement data of Chinese banks from Bankscope complemented by hand-collected data from annual reports Unique dataset that contains over 950 observations for 170 banks i.e. higher than in other studies Time period 2004 – 2013 Information on monetary policy tools from the website of the PBC Macroeconomic variables from National Bureau of Statistics of China Classification of banks by the Chinese Banking Regulatory Commission

TYPES OF BANKS Large commercial banks Joint-stock commercial banks Four main banks established in 1984 (ABC, BoC, CCB, ICBC) and Bank of Communications Provide nationwide wholesale and retail services Very large publicly listed institutions also at the global scale Account for 43% of the banking sector assets (despite their growth, their share has been declining) Despite presence of foreign investors, still majority state-owned Joint-stock commercial banks 12 joint-stock commercial banks, operate nationwide Constitute 18% of total banking sector assets – their share has been increasing at the expense of large state-owned banks Operate on a commercial basis and have private domestic and foreign shareholders but the state-owned entities are still important shareholders for many of these banks

TYPES OF BANKS City commercial banks Rural financial institutions Originally carried out the local government lending operations and some of the banks are still owned by the local governments Typically operate in their local banking markets serving especially local small and medium businesses Important in providing financing to the SMEs Account for about 10% of banking sector assets (growing share) Rural financial institutions Serve rural population and usually operate within the small township or village Account for about 13% of banking sector assets Transformation of rural credit cooperatives into rural commercial banks and rural cooperative banks

TYPES OF BANKS Foreign banks Foreign ownership in Chinese banks Account for about 2 % of the banking sector assets Around 40 foreign financial institutions operating in China First allowed to offer just foreign currency services, then from 2004 could provide local currency services and after December 2006 in connection to WTO agreement foreign banks could also enter retail market Foreign ownership in Chinese banks Many of the banks where the state holds a majority stake also have foreign owners Nowadays still restrictions maximum foreign share for individual investor in commercial banks is 20% maximum total foreign investment is 25%

METHODOLOGY Following Kashyap and Stein (1995,2000) and Ehrmann et al. (2003) changes in a bank’s loan supply are estimated where i identifies the bank, t time period, Lit total loans to private non-banking sectors, MP monetary policy indicator, GDP real GDP, Xi bank-specific characteristics Control variables lagged one period to ease possible endogeneity Panel fixed-effect estimations But in our case the results indicate that the lagged value of loan growth is not significant, which casts serious doubt on the benefits of using difference or system GMM. As we use annual, instead of higher frequency data, the result is not entirely surprising. There certainly can be convincing reasons why lending in the previous quarter may influence current lending, but it is much harder to find an economic rationale for why lending last year should influence current lending. As the lagged dependent variable is not statistically significant and we do not find a strong economic rationale for including the variable as a regressor, we prefer to estimate equation (10) without the lagged dependent variable in a standard fixed-effect panel regression framework. Several papers have estimated this equation with the difference GMM method developed by Arellano and Bond (1991). However this technique is not as relevant in the context of annual data as it can be with monthly or quarterly data. Indeed the lagged value of loan growth is not significant in that case: there is no economic rationale to support the view that current lending growth should influence lending growth next year. We then follow the approach from Fungacova, Solanko and Weill (2014) on annual data for the Eurozone and estimate the equation in a standard fixed effects panel regression framework without the lagged dependent variable.

VARIABLES Monetary policy indicator Bank-specific variables Main indicator: reserve requirements ratio reported for the largest banks, small and medium banks and rural credit cooperatives Other indicators: overnight interbank rate, lending rate Bank-specific variables Bank size (log of total assets) Capitalization (equity to total assets) Liquidity (liquid assets to total assets) In line with the bank lending channel literature, we consider three bank-specific characteristics: bank size, capitalization, and liquidity. All of these factors influence bank access to external funding which further impacts bank ability to supply loans. High levels of liquidity may also allow a bank to draw on its own liquid funds instead of relying on the market in the presence of monetary tightening.

RESULTS Main results with reserve requirement ratios as monetary policy instrument 2004 – 2013 Subperiods accounting for active usage of reserve requirements and crisis period Other monetary policy instruments Different types of banks

MAIN ESTIMATIONS

MAIN RESULTS Loan growth adversely affected by tightening reserve requirements Estimated coefficient is significant and negative in all specifications Reserve requirements are effective monetary policy instrument Most monetary policy interaction terms not significant Bank size and liquidity do not influence how bank lending reacts to changes in monetary policy Capitalization is negative and significant Reserve requirements do not influence transmission of monetary policy through the bank lending channel Results valid for different subperiods First, we find evidence that loan growth is adversely affected by a tightening in reserve requirements. The coefficient of reserve requirements, which captures the direct impact of monetary policy on loan growth, is significant and negative in all estimations, in line with the expectations. An increase (decrease) in reserve requirements leads to a decrease (increase) in loan growth rate. Hence we support the view that reserve requirements are an effective monetary policy instrument. Second, the monetary policy interaction terms for liquidity and size are overall not significant, meaning that both of these bank-specific characteristics do not influence how bank lending reacts to changes in monetary policy. In addition, the interaction term between monetary policy and capitalization is significant but negative. Our results for the monetary policy interaction terms do not then support the existence of a bank lending channel in China through the use of reserve requirements. This channel predicts that banks with lower capitalization, liquidity, and size, should increase their credit supply more, while we do not observe any of these results. In analyzing the other variables, we point out that the coefficients of capitalization and liquidity are significant and positive, while they are significant and negative for size in all estimations. These results mean that well-capitalized, highly-liquid and small banks achieve more robust loan growth. We also observe that changes in economic activity, measured by GDP growth, are positively related to loan growth. Interestingly these results fully corroborate with those observed in other countries, like for instance for euro zone countries (Fungacova, Solanko and Weill, 2014). In a nutshell, our estimations show that the RRR does not influence monetary policy through the bank lending channel, even if it exerts an impact on loan growth

ESTIMATIONS WITH OTHER MONETARY POLICY INSTRUMENTS Our evidence that reserve requirements do not affect loan growth through the bank lending channel raises the question if this result is specific to this monetary policy instrument or if it is a general conclusion for monetary policy instruments in China. Former studies on this issue tend to show that evidence on the bank lending channel in China should not be taken for granted. Gunji and Yuan (2010) find limited evidence with only influence of size on the transmission of monetary policy. We perform estimations with three alternative monetary policy measures: overnight interbank rate, deposit rate, and lending rate. These three instruments are all regularly changed by the PBC to influence bank credit in China. They are commonly used as the monetary policy instruments in China (e.g., Gunji and Yuan, 2010). Table 3 displays the results with these instruments for the full sample covering the period 2004-2013. Two main conclusions emerge.

OTHER MONETARY POLICY INSTRUMENTS Negative and significant coefficients for all monetary policy instruments All the instruments seem to be effective Interactions between monetary policy and bank-specific variables Never positive and significant, mostly not significant => No support for the bank lending channel i.e. neither small, nor less-capitalized or less-liquid banks incur greater increase of loan supply when MP is relaxed Results in line with the main findings No bank lending channel regardless of the MP instrument In line with related studies (e.g. Gunji and Yuan, 2010) First, the coefficients of monetary policy are significantly negative for all three estimations. The growth rate of loans declines when the PBC tightens its monetary policy through any of the three instruments. These results are in line with the expectation that they are effective monetary policy instruments. Second, the interaction terms between monetary policy instruments and the three bank-specific characteristics are never significantly positive. In most cases they are not significant. Only the interaction term with size is negative and significant for the deposit rate and the lending rate. This result again indicates no support for the bank lending channel. Neither smaller banks, nor less-capitalized or less-liquid banks have greater increase of their credit supply when monetary policy is relaxed. As a consequence, the main conclusion is that the RRR cannot be considered a different monetary policy tool from the effectiveness perspective. On the one hand, changes in reserve requirements contribute in a similar way as changes in overnight interbank rate, deposit rate, or lending rate to influence loan growth. Tightening of any of these four instruments deteriorates loan growth. PBC can then use these four instruments in a similar way to influence loan growth. On the other hand, changes in reserve requirements do not influence loan supply through the bank lending channel, nor changes in the three alternative monetary policy instruments do. Hence reserve requirements are an effective monetary policy instrument in China but not through the bank lending channel. Nevertheless, the reason for this result is not related to the nature of this instrument but to the absence of the bank lending channel in China. All in all, our study tends to support the view of the absence of bank lending channel in China. This finding is not at odds with former studies. As stressed above, related studies are still scarce and the closest one from Gunji and Yuan (2010) finds limited evidence. In addition, this study has been done on a limited sample of 19 large Chinese banks on a period ending in 2007.

ESTIMATIONS FOR DIFFERENT TYPES OF BANKS To test the hypothesis that ownership influences the bank lending channel, we perform new estimations by adding four interaction terms to our main regressions. We create five dummy variables corresponding to each bank ownership type: Big Five, joint-stock banks, city commercial banks, rural commercial banks, and foreign banks. We add an interaction variable between the difference in reserve requirements and each bank type dummy variable to consider the possibility that changes in reserve requirements exert a different influence on loan growth based on ownership type. We include three interaction variables between the difference in reserve requirements, each bank-specific characteristic (capitalization, liquidity, size), and each bank type dummy variable and perform five estimations by considering separately each type of banks. This way, the results are easier to interpret to know if any ownership type differs from the others for the transmission of monetary policy changes.

ESTIMATIONS FOR DIFFERENT TYPES OF BANKS Impact of changes in reserve requirements on loan growth differs across types of banks Interaction term between MP and the type of banks Significantly negative for city commercial and rural commercial banks => loan growth of these banks is more adversely affected by a tightening in reserve requirements Significantly positive for foreign banks => foreign banks can weaken the effectiveness of monetary transmission (Jeon and Wu, 2014)

ESTIMATIONS FOR DIFFERENT TYPES OF BANKS Differences in transmission of monetary policy through bank lending channel across bank types – limited evidence for the bank lending channel Interaction term for capitalization positive for Big 5 => less-capitalized Big 5 tend to increase their credit supply more when RRR are reduced Interaction term for size positive for city commercial banks => smaller city commercial banks increase their supply more when RRR are reduced

ESTIMATIONS FOR DIFFERENT TYPES OF BANKS Estimations with other monetary policy proxies (interbank rate, lending rate) provide results in line with reserve requirements Overnight interbank rate as monetary policy proxy provides slightly different resuls Interaction term between MP and type of bank is significant for joint-stock, city commercial and foreign banks No results supporting bank lending channel Estimations for different types of banks overall Some evidence for bank lending channel for some types of banks Stress the importance of bank type

CONCLUSION Three main findings. 1. The bank lending channel is not effective through reserve requirements in China But this conclusion also stands for changes in other monetary policy measures. => we tend to support the absence of the bank lending channel in China.

CONCLUSION 2. Changes in reserve requirements influence loan growth directly We support the effectiveness of monetary policy through reserve requirements in China. We obtain the same finding for the other monetary policy instruments. => Monetary policy is effective through multiple instruments including reserve requirements.

CONCLUSION 3. The ownership structure of the banking industry influences the transmission of monetary policy The impact of changes in reserve requirements on loan growth differs across types of banks.

IMPLICATIONS In terms of instruments: reserve requirements constitute an effective monetary policy instrument that can be used as a substitute to other monetary policy instruments in China. In terms of channels of transmission: the bank lending channel does not play a major role in the transmission of monetary policy in China. In terms of banking structure: changes in the ownership structure (privatization, foreign bank entry) can foster or hamper the effectiveness of the monetary policy.

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