《中国金融市场 Chinese Financial Markets》补充阅读文献：monetary policy and bank lending in china（2012-he dong）

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Monetary Policy and Bank Lending in China evidence from loan level data 1. Introduction The transmission mechanism of monetary policy in China is little understood and largely black box to both researchers and policy makers. To a significant extent this is borrowers are influenced by not only regulated interest rates and quantity-based Y due to the So-called"dual-track "interest rates system, under which banks and the instruments, but also by signals contained in the variations of the market-determined interest rates(He and Wang, 2012). Such market-determined interest rates serve as shadow prices of loans, which would affect lending and borrowing decisions on the margin. Secondly, most of the dominant Chinese commercial banks are majority state- owned and may be required by policy makers to direct their loans to certain firms, which further complicate banks'lending behavior(Berger et al., 2010); Thirdly, very little micro-level data has been available publicly to allow researchers to examine bank lendi in China This paper attempts to shed light into the black box in two steps: First, a simple theoretical model is constructed to show how bank lending is affected by monetary policy under the dual-track "interest rates system and market frictions. Second, a proprietary hand-collected loan-level dataset enables us to examine bank lending behavior systematically. The panel dataset comprises of more than 11, 000 loan-level observations from 672 listed firms in the Shenzhen Stock Exchange(szse) from 2002 to 2011.In d dition we have detailed balance sheet data of these listed firms which allow us to control for firms' characteristics and identify how monetary policy and market interest rates affect bank lending The existing literature on links between monetary policy and bank lending is typically based on monetary transmission in advanced economies, in which policy changes from central banks can be transmitted to the real economy through interest rate channel and bank lending channel (bernanke and blinder, 1992; Bernanke and gertler, 1995; Mishkin, 1996; Kashyap and Stein, 2000; among others). However, since Chinese commercial banks face more regulations and market frictions, many basic questions remain to be answered. This paper aims to address the following questions: Do monetary policy instruments effectively influence bank lending in China? Do they affect the price and quantities of loans differently? Is bank lending affected by signals from non-regulated capital markets, and how important is the impact? Does the impact of monetary policy on 2 The reason we choose listed firms in Shenzhen Stock Exchange is to have better coverage of small and medium size firms: the representation of smaller firms in better on the Shenzhen Stock Exchange than on however,not all firms report their loan information correctly and completely(especially loan rafe ge: the Shanghai Stock Exchange. There are about 1,500 listed firms traded in Shenzhen Stock Excha

2 Monetary Policy and Bank Lending in China —Evidence from loan level data 1. Introduction The transmission mechanism of monetary policy in China is little understood and largely remains a black box to both researchers and policy makers. To a significant extent this is due to the so-called “dual-track” interest rates system, under which banks and their borrowers are influenced by not only regulated interest rates and quantity-based instruments, but also by signals contained in the variations of the market-determined interest rates (He and Wang, 2012). Such market-determined interest rates serve as shadow prices of loans, which would affect lending and borrowing decisions on the margin. Secondly, most of the dominant Chinese commercial banks are majority stateowned and may be required by policy makers to direct their loans to certain firms, which further complicate banks’ lending behavior (Berger et al., 2010); Thirdly, very little micro-level data has been available publicly to allow researchers to examine bank lending in China. This paper attempts to shed light into the black box in two steps: First, a simple theoretical model is constructed to show how bank lending is affected by monetary policy under the “dual-track” interest rates system and market frictions. Second, a proprietary hand-collected loan-level dataset enables us to examine bank lending behavior systematically. The panel dataset comprises of more than 11,000 loan-level observations from 672 listed firms in the Shenzhen Stock Exchange (SZSE) from 2002 to 2011.2 In addition, we have detailed balance sheet data of these listed firms, which allow us to control for firms’ characteristics and identify how monetary policy and market interest rates affect bank lending. The existing literature on links between monetary policy and bank lending is typically based on monetary transmission in advanced economies, in which policy changes from central banks can be transmitted to the real economy through interest rate channel and bank lending channel (Bernanke and Blinder, 1992; Bernanke and Gertler, 1995; Mishkin, 1996; Kashyap and Stein, 2000; among others). However, since Chinese commercial banks face more regulations and market frictions, many basic questions remain to be answered. This paper aims to address the following questions: Do monetary policy instruments effectively influence bank lending in China? Do they affect the price and quantities of loans differently? Is bank lending affected by signals from non-regulated capital markets, and how important is the impact? Does the impact of monetary policy on 2 The reason we choose listed firms in Shenzhen Stock Exchange is to have better coverage of small and medium size firms: the representation of smaller firms in better on the Shenzhen Stock Exchange than on the Shanghai Stock Exchange. There are about 1,500 listed firms traded in Shenzhen Stock Exchange; however, not all firms report their loan information correctly and completely (especially loan rate information)

bank lending vary with business cycles and overall stance of monetary policy, and do they differ across firms of different size? Previous studies on monetary policy in China mainly focus on the links between monetary policy and macroeconomic performance, and assume that the monetary transmission mechanism in China is the same as that in advanced economies(Qin et al (2005), Geiger(2006), Fan and Zhang(2007), Laurens and maino(2007); among others) A few recent studies discuss the transmission mechanism under regulated interest rates and find that monetary policy instruments are able to influence interest rates in money banking system)to the other(non-regulated money and bond markets)(Porter and Xy e and bond markets, suggesting policy signals can be transmitted from one track (regul 2009: Chen et al., 2011; He and wang, 2012) However, studies on the links between monetary policy and bank lending in China are rare. Bank lending, interest rate and asset price channels are found to exist in China(Sun et al., 2010), but the effectiveness of the bank lending channel varies across provinces and banks(Ho, 2012). More specifically, the impact of monetary policy on lending is weaker for larger banks and banks with lower levels of liquidity( Gunji and Yuan, 2010) However, none of these studies examines bank lending behavior using loan level data In this paper, we find that bank lending is not only affected by policy changes by the central bank, but also reacts to price changes in the non-regulated money and bond markets. Under the dual-track interest rates system, banks react to signals from both tracks when making loans The empirical analysis of the paper focuses on how the price and quantities of bank loan are affected by both monetary policy instruments and market-determined interest rates after controlling for loan features, bank types, macroeconomic variables and firm characteristics. We find that the People's Bank of China(PBc) can effectively influence loan rate through policy instruments, with the benchmark deposit rate being the most powerful instrument, followed by the Reserve Requirement Ratio(RRR). However, these two instruments have little impact on loan size. In contrast, both the price and quantity of loans are affected by the market-determined interest rates More interestingly, the impact from policy instruments and market interest rates would vary with firm size and the stance of monetary policy. While the effects on loan rates do not differ systematically across firms of different size, the effects on loan size are asymmetrical:, changes in benchmark deposit rate and market interest rates affect I firms more than smaller firms, but changes in RRR affect smaller firms more than firms The impact on loan rates from changes in the benchmark deposit rate and the rrr would also vary with the prevailing monetary policy stance. Changes in the benchmark deposit rate have larger effects on loan rates when monetary policy is being loosened than when Hereafter, the market interest rate means the representative interest rates(such as the 7-day Repo rate)in non-regulated money and bond markets

3 bank lending vary with business cycles and overall stance of monetary policy, and do they differ across firms of different size? Previous studies on monetary policy in China mainly focus on the links between monetary policy and macroeconomic performance, and assume that the monetary transmission mechanism in China is the same as that in advanced economies (Qin et al (2005), Geiger (2006), Fan and Zhang (2007), Laurens and Maino (2007); among others). A few recent studies discuss the transmission mechanism under regulated interest rates and find that monetary policy instruments are able to influence interest rates in money and bond markets, suggesting policy signals can be transmitted from one track (regulated banking system) to the other (non-regulated money and bond markets) (Porter and Xu, 2009; Chen et al., 2011; He and Wang, 2012). However, studies on the links between monetary policy and bank lending in China are rare. Bank lending, interest rate and asset price channels are found to exist in China (Sun et al., 2010), but the effectiveness of the bank lending channel varies across provinces and banks (Ho, 2012). More specifically, the impact of monetary policy on lending is weaker for larger banks and banks with lower levels of liquidity (Gunji and Yuan, 2010). However, none of these studies examines bank lending behavior using loan level data. In this paper, we find that bank lending is not only affected by policy changes by the central bank, but also reacts to price changes in the non-regulated money and bond markets. Under the dual-track interest rates system, banks react to signals from both tracks when making loans. The empirical analysis of the paper focuses on how the price and quantities of bank loans are affected by both monetary policy instruments and market-determined interest rates after controlling for loan features, bank types, macroeconomic variables and firm characteristics. We find that the People’s Bank of China (PBC) can effectively influence loan rate through policy instruments, with the benchmark deposit rate being the most powerful instrument, followed by the Reserve Requirement Ratio (RRR). However, these two instruments have little impact on loan size. In contrast, both the price and quantity of loans are affected by the market-determined interest rates.3 More interestingly, the impact from policy instruments and market interest rates would vary with firm size and the stance of monetary policy. While the effects on loan rates do not differ systematically across firms of different size, the effects on loan size are asymmetrical: ,changes in benchmark deposit rate and market interest rates affect larger firms more than smaller firms, but changes in RRR affect smaller firms more than larger firms. The impact on loan rates from changes in the benchmark deposit rate and the RRR would also vary with the prevailing monetary policy stance. Changes in the benchmark deposit rate have larger effects on loan rates when monetary policy is being loosened than when 3 Hereafter, the market interest rate means the representative interest rates (such as the 7-day Repo rate) in non-regulated money and bond markets

it is being tightened, but chanages in the rrr have larger effects on loan rates when monetary policy stance in being tightened than when it is loosened. In addition, changes the market interest rates have larger effect on loan size when being loosened than when it is being tightened The rest of the paper is organized as follows. The next section briefly reviews the institutional background of the Chinese monetary policy framework and the banking sector. Section 3 develops a simple theoretical model and discusses its predictions Section 4 describes the specifications of empirical models and the estimation strategy Section 5 describes the data and discusses sample selection. Section 6 reports the estimation results and discusses two caveats. Section 7 concludes the paper 2. Institutional Background 2.1 The monetary policy framework in China According to the Law on the People's Bank of China, "the aim of monetary policies shall be to maintain the stability of the currency and thereby promote economic growth. Thus the pbc has a dual mandate. similar to that of the us Federal reserve. Even though it is not explicitly stated in the law, there is also an understanding that the PbC has the mandate to maintain the stability of the Chinese financial system, reflecting its role as the lender of last resort. The policy implementation framework has evolved since the mid-1990s from relying on quantity-based instruments into a mixture of both quantity and price-based instruments. (He and Pauwels, 2008) Key to a good understanding of China's monetary policy framework is the"dual-track interest-rate system: on the one hand, bank deposit and lending rates are regulated by the central bank (i. e, the imposition of a deposit-rate ceiling and a lending- rate floor ) on the other hand, interest rates in money and capital markets are market-determined. At the same time, the ceiling or the floor may not necessarily be binding in practice. The deposit-rate ceiling is generally considered binding while actual lending data since 2004 suggests the lending- rate floor is generally not binding(He and wang, 2012) Price distortions (rates ceiling and floor)in the banking system mean that the pbc m also rely on quantity-based instruments to achieve its targets. For example, a lower Qust deposit rate ceiling(compared to its equilibrium level) causes the loan supply curve of commercial banks to shift to the right(Graph 1, S1>S2), where Si is the loan supply curve without the deposit rate ceiling. The shifted loan supply curve(S2)means that banks are willing to lend to firms at lower loan rates because the funding cost of banks (deposit rate) is lower than it should be(P2Q1). This means that both commercial banks and firms benefit from lower loan rates but at the expense of depositors in the economy who receive lower rates on their deposits However, the new equilibrium under the deposit rate ceiling(P2, Q2)means that there will be more credit(Q2>Q1)in the economy compared to its original equilibrium(Pl

4 it is being tightened, but chanages in the RRR have larger effects on loan rates when monetary policy stance in being tightened than when it is loosened. In addition, changes in the market interest rates have larger effect on loan size when monetary policy stance is being loosened than when it is being tightened. The rest of the paper is organized as follows. The next section briefly reviews the institutional background of the Chinese monetary policy framework and the banking sector. Section 3 develops a simple theoretical model and discusses its predictions. Section 4 describes the specifications of empirical models and the estimation strategy. Section 5 describes the data and discusses sample selection. Section 6 reports the estimation results and discusses two caveats. Section 7 concludes the paper. 2. Institutional Background 2.1 The monetary policy framework in China According to the Law on the People’s Bank of China, “the aim of monetary policies shall be to maintain the stability of the currency and thereby promote economic growth.” Thus, the PBC has a dual mandate, similar to that of the US Federal Reserve. Even though it is not explicitly stated in the law, there is also an understanding that the PBC has the mandate to maintain the stability of the Chinese financial system, reflecting its role as the lender of last resort. The policy implementation framework has evolved since the mid-1990s from relying on quantity-based instruments into a mixture of both quantityand price-based instruments. (He and Pauwels, 2008). Key to a good understanding of China’s monetary policy framework is the “dual-track” interest-rate system: on the one hand, bank deposit and lending rates are regulated by the central bank (i.e., the imposition of a deposit-rate ceiling and a lending-rate floor); on the other hand, interest rates in money and capital markets are market-determined. At the same time, the ceiling or the floor may not necessarily be binding in practice. The deposit-rate ceiling is generally considered binding while actual lending data since 2004 suggests the lending-rate floor is generally not binding (He and Wang, 2012). Price distortions (rates ceiling and floor) in the banking system mean that the PBC must also rely on quantity-based instruments to achieve its targets. For example, a lower deposit rate ceiling (compared to its equilibrium level) causes the loan supply curve of commercial banks to shift to the right (Graph 1, S1S2), where S1 is the loan supply curve without the deposit rate ceiling. The shifted loan supply curve (S2) means that banks are willing to lend to firms at lower loan rates because the funding cost of banks (deposit rate) is lower than it should be (P2Q1). This means that both commercial banks and firms benefit from lower loan rates but at the expense of depositors in the economy who receive lower rates on their deposits. However, the new equilibrium under the deposit rate ceiling (P2, Q2) means that there will be more credit (Q2>Q1) in the economy compared to its original equilibrium (P1

Q1), which might conflict with the PBC's inflation target. In order to prevent a deviation from its inflation target, the PBC will have to constrain the credit supply in the economy At least two measures are introduced for this purpose: First, a lending rate floor is used to reduce loan demand from firms through higher loan rates(P3>P2). This floor, coupled with the deposit rate ceiling, also means that a decent profit margin is guaranteed for banks in the sector. Second, multiple quantity-based instruments such as a credit quota and the rrR are introduced to restrain credit supply in the banking system in order to keep inflation low in the economy From the simple analysis above, we can see that distortions caused by price regulations have to be corrected by quantity-based instruments, which is why the Pbc has to use both price-based and quantity-based instruments in its framework. On the other hand money and bond markets have also emerged since the 1990s, where interest rates have been largely determined by market forces. Commercial banks can choose to borrow and lend in money and bond markets whilst they are subject to regulated interest rates in the banking sector. Understanding the mechanisms of such a dual-track interest rate system is essential to an understanding of the links between monetary policy and bank lending Lower deposit SI loan supply S2 PI Graph 1: loan market in banking system 2.2 The Chinese banking sector The financial system in China has gone through a fundamental structural transformation since the late 1990s. Although bank credit is still the dominant form of financial intermediation, off-balance sheet activities(such as trust and entrusted loans)and market- based financial intermediation have grown very fast in recent years. Indeed, the share of bank credit in total social financing, a measure of the aggregate volume of financial intermediation through both the banking sector and capital markets, had fallen from more than two thirds in early 2000s to under 50% in the second half of 2011(PBC, 2012)

5 Q1), which might conflict with the PBC’s inflation target. In order to prevent a deviation from its inflation target, the PBC will have to constrain the credit supply in the economy. At least two measures are introduced for this purpose: First, a lending rate floor is used to reduce loan demand from firms through higher loan rates (P3>P2). This floor, coupled with the deposit rate ceiling, also means that a decent profit margin is guaranteed for banks in the sector. Second, multiple quantity-based instruments such as a credit quota and the RRR are introduced to restrain credit supply in the banking system in order to keep inflation low in the economy. From the simple analysis above, we can see that distortions caused by price regulations have to be corrected by quantity-based instruments, which is why the PBC has to use both price-based and quantity-based instruments in its framework. On the other hand, money and bond markets have also emerged since the 1990s, where interest rates have been largely determined by market forces. Commercial banks can choose to borrow and lend in money and bond markets whilst they are subject to regulated interest rates in the banking sector. Understanding the mechanisms of such a dual-track interest rate system is essential to an understanding of the links between monetary policy and bank lending. Graph 1: loan market in banking system 2.2 The Chinese banking sector The financial system in China has gone through a fundamental structural transformation since the late 1990s. Although bank credit is still the dominant form of financial intermediation, off-balance sheet activities (such as trust and entrusted loans) and marketbased financial intermediation have grown very fast in recent years. Indeed, the share of bank credit in total social financing, a measure of the aggregate volume of financial intermediation through both the banking sector and capital markets, had fallen from more than two thirds in early 2000s to under 50% in the second half of 2011 (PBC, 2012). P Q Q1 Q2 S2 S1 P1 P2 D Lower deposit ceiling leads loan supply curve to shift to right Lending rate P3 floor

Within the banking sector itself, although it is still dominated by majority-state owned big five"banks which hold about 47%o of industry assets and roughly the same share of total deposits in the sector, contestability of the sector has also increased (PBC FSr Report, 2012). Admittedly, bank competition is to a significant extent constrained by relatively high entry barriers and interest rate regulation The existing literature on the efficiency of the Chinese banking sector has mixed findings Banks undergoing a foreign acquisition or public listing are found to have better pre event performance, but little performance changes were recorded after changes of ownership(Lin and Zhang, 2009). On the other hand, there is evidence that the Chinese banking system has benefited from the entry of foreign investors through higher profitability and incr reased efficiency in the banking system( Garcia-Herrero and Santabarbara, 2008). City commercial banks were found to outperform state-owned commercial banks, suggesting diversity in terms of ownership is key to better banking in China(ferri, 2009). Changes in ownership also has an impact on the lending behavior of banks, as lending by state-owned banks were found to be less prudent than lending by joint-Stock banks Jia, 2007) However, the benefits and efficiency improvements are not distributed evenly across banks and lenders. Smaller, less-regulated financial institutions appear more commercially oriented and gained more market shares in some areas after the reforms (Podpiera, 2006). Higher contestability in the banking sector helps alleviate financing constraints for small and medium enterprises( Chong et al., 2012). Joint-stock banks and city commercial banks were also found to have gained higher total factor productivity growth than state-owned banks in recent years( Chang et al, 2012) 3. A Stylized Model on Dual-Track Interest Rates System The setting of the model is similar to the framework in Chen et al. (201 1)and He and Wang(2012), which extend the model developed in Freixas and Rochet(2008). As in He and wang(2012), we introduce a dual-track interest rates system and focus on fund flows between the regulated banking system(the first track) and non-regulated money and bond market(the second track). In the banking sector, the central bank influence bank lending using the benchmark deposit rate and the rrr. In addition, bank lending can be affected by changes in the market price of funds due to arbitrage between the banking sector and capital markets. In this sense, the market price of funds in the money and bond markets is a shadow price to bank lending. In contrast to He and Wang(2012) which focuses on how monetary policy changes affect market interest rates, the new model in this paper pays more attention to how monetary policy and market interest rate affect both the price and quantity of bank lending. In order The"big five"banks are Industry and Commercial bank of China(ICBc), Bank of China(boc) Construction Bank of China(CBC), Agricultural Bank of China(ABC) and Bank of Communications BOCOM)

6 Within the banking sector itself, although it is still dominated by majority-state owned “big five” banks which hold about 47% of industry assets and roughly the same share of total deposits in the sector, contestability of the sector has also increased (PBC FSR Report, 2012).4 Admittedly, bank competition is to a significant extent constrained by relatively high entry barriers and interest rate regulation. The existing literature on the efficiency of the Chinese banking sector has mixed findings. Banks undergoing a foreign acquisition or public listing are found to have better preevent performance, but little performance changes were recorded after changes of ownership (Lin and Zhang, 2009). On the other hand, there is evidence that the Chinese banking system has benefited from the entry of foreign investors through higher profitability and increased efficiency in the banking system (Garcia-Herrero and Santabarbara, 2008). City commercial banks were found to outperform state-owned commercial banks, suggesting diversity in terms of ownership is key to better banking in China (Ferri, 2009). Changes in ownership also has an impact on the lending behavior of banks, as lending by state-owned banks were found to be less prudent than lending by joint-stock banks (Jia, 2007). However, the benefits and efficiency improvements are not distributed evenly across banks and lenders. Smaller, less-regulated financial institutions appear more commercially oriented and gained more market shares in some areas after the reforms (Podpiera, 2006). Higher contestability in the banking sector helps alleviate financing constraints for small and medium enterprises (Chong et al., 2012). Joint-stock banks and city commercial banks were also found to have gained higher total factor productivity growth than state-owned banks in recent years (Chang et al., 2012). 3. A Stylized Model on Dual-Track Interest Rates System The setting of the model is similar to the framework in Chen et al. (2011) and He and Wang (2012), which extend the model developed in Freixas and Rochet (2008). As in He and Wang (2012), we introduce a dual-track interest rates system and focus on fund flows between the regulated banking system (the first track) and non-regulated money and bond market (the second track). In the banking sector, the central bank influence bank lending using the benchmark deposit rate and the RRR. In addition, bank lending can be affected by changes in the market price of funds due to arbitrage between the banking sector and capital markets. In this sense, the market price of funds in the money and bond markets is a shadow price to bank lending. In contrast to He and Wang (2012) which focuses on how monetary policy changes affect market interest rates, the new model in this paper pays more attention to how monetary policy and market interest rate affect both the price and quantity of bank lending. In order 4 The “big five” banks are Industry and Commercial bank of China (ICBC), Bank of China(BOC), Construction Bank of China(CBC), Agricultural Bank of China(ABC) and Bank of Communications (BOCOM)

to analyse whether the impact is symmetric across firms of different size and across different phases of monetary policy stance, we introduce several cases with specific SSumptions into the model. In addition, loan demand and deposit supply functions are specified in the model to facilitate the computation of derivatives A Stylized Model Similar to previous studies, we assume N independent banks in the competitive banking sector and that n is sufficiently large so that each bank is a price taker. Each bank takes deposits(d)from households and makes loans(l) to firms in the loan market. Each bank has to submit required reserves to the central bank according to rrr(a) set by the PBC. In addition, each bank can buy central bank bills(Bi), on which the interest rate is set by the PBC (exogenous to each bank), and each bank can also invest in bonds or other financial products(NR, in the money and bond markets The key feature of the dual-track interest rate system is there exist a deposit-rate ceiling and a lending rate floor imposed by PbC in the banking sector. The deposit ceiling is in general considered binding while the lending-rate floor is not binding in most cases unable to maximize their profits as they do in a free market. In other words, the depos a ( Feyzioglu et. Al, 2009; He and Wang, 2012). The binding price control means banks market can not be cleared by market forces when the deposit rate ceiling is binding When the deposit ceiling is binding in the banking sector, bank i maximizes its profit as follows. I= Max(r L +raD+B+n D-C(D, L)(1) st.r≤rb Where r is the lending rate, r, is the deposit rate, r is the deposit rate ceiling, r, is the interest rate paid on required reserves, and r, is the market rate in the non-regulated market. C(D, L) is the bank's managing cost, which is a function of deposits and loans NR is the net position of bank i in the non-regulated market, which is given by NR1=D1-L-0D1-B;(2) Given that the deposit rate is binding and that the lending rate is not binding, the profit maximization function changes as follows I,= Max(L+raD(a)+,B,+r -PD ()-C(D, L))(3) Note that here the deposit function is determined solely by the supply of savings, and therefore, D is a function solely of r. In the capital wholesale market, the supply function S(r, Ir)is also a function of r, where r is exogenous and is determined by

7 to analyse whether the impact is symmetric across firms of different size and across different phases of monetary policy stance, we introduce several cases with specific assumptions into the model. In addition, loan demand and deposit supply functions are specified in the model to facilitate the computation of derivatives. A Stylized Model Similar to previous studies, we assume N independent banks in the competitive banking sector and that N is sufficiently large so that each bank is a price taker. Each bank takes deposits ( ) Di from households and makes loans ( ) Li to firms in the loan market. Each bank has to submit required reserves to the central bank according to RRR (α ) set by the PBC. In addition, each bank can buy central bank bills ( ) Bi , on which the interest rate is set by the PBC (exogenous to each bank), and each bank can also invest in bonds or other financial products ( ) NRi in the money and bond markets. The key feature of the dual-track interest rate system is there exist a deposit-rate ceiling and a lending rate floor imposed by PBC in the banking sector. The deposit ceiling is in general considered binding while the lending-rate floor is not binding in most cases (Feyzioglu et. Al, 2009; He and Wang, 2012). The binding price control means banks are unable to maximize their profits as they do in a free market. In other words, the deposit market can not be cleared by market forces when the deposit rate ceiling is binding. When the deposit ceiling is binding in the banking sector, bank i maximizes its profit as follows: { ( , )} , , l i r i b i nr i d i i i Li Di Bi Πi = Max r L + rαD + r B + r NR − r D −C D L (1) st. b d d r ≤ r Where l r is the lending rate, d r is the deposit rate, b d r is the deposit rate ceiling, r r is the interest rate paid on required reserves, and nr r is the market rate in the non-regulated market. ) ( , C Di Li is the bank’s managing cost, which is a function of deposits and loans. NRi is the net position of bank i in the non-regulated market, which is given by NRi = Di − Li −αDi − Bi (2) Given that the deposit rate is binding and that the lending rate is not binding, the profit maximization function changes as follows: { ( ) ( ) ( , )} , , i i b d s i b b i nr i d b d s l i r i Li Di Bi Πi = Max r L + rαD r + r B + r NR − r D r −C D L (3) Note that here the deposit function is determined solely by the supply of savings, and therefore, s D is a function solely of b d r . In the capital wholesale market, the supply function ( , ) nr b d S r r is also a function of b d r , where b d r is exogenous and is determined by

the central bank. Based on the above simple model, we try to answer our research questions one by one It can be proved that, under this scenario the equilibrium loan rate and loan size can be written as follows(proofs can be found in Appendix a): AD+N N+8 L-N(AD-A'2 (5) Where AD is aggregate demand for loans in the economy, S, is managing cost in the banking sector and a, is firms'price sensitivity for banking loans. From the above two equations, we can see that four factors could affect loan rate and loan size: r,(the market interest rate in free capital market), AD, 8 and A. Interestingly, changes of monetary policy instruments such as benchmark deposit rate or rrr do not enter loan equations directly, however, they could affect loan pricing and loan size indirectly since monetary policy changes will affect the market interest rate(Proofs can be found in Appendix A) Theoretical predictions When the deposit rate ceiling is binding and lending rate floor is not binding, loan rate increases with the market interest rate, while loan quantity decreases with the market interest rate. Monetary policy instruments can also affect bank lending through th market interest rate: loan rate increases with the benchmark deposit rate and RRR, while the loan quantity decreases when the Pbc raises the benchmark deposit rate and rRR 4. Empirical Analysis 4.1 Empirical Specification The goal of empirical models is to test the theoretical predictions and the theoretical model provides a good guideline for empirical specification. However the reality is much more complicated than that in the simple model. First, we need to identify the most likely scenario in the real world: the deposit rate ceiling is binding while the lending rate floor is not binding. Even though the credit quota may be imposed on the banking sector when necessary, it is generally believed that the PbC tends to use it as little as possible, especially in recent years. Therefore, our empirical models are based on the simple scenario without credit quota, although the potential impact of credit quota will be discussed in the caveat. Now we discuss empirical factors impacting bank lending one by a) Policy instruments and the market interest rate The first theoretical prediction illustrates that when the deposit rate ceiling is binding and lending rate floor is not binding, loan rate increases with the market interest rate in the

8 the central bank. Based on the above simple model, we try to answer our research questions one by one. It can be proved that, under this scenario the equilibrium loan rate and loan size can be written as follows (proofs can be found in Appendix A): L l L nr l N AD Nr r δ λ δ + + = * (4) L l l nr N N AD r L δ λ λ + − = ( ) * (5) Where AD is aggregate demand for loans in the economy, L δ is managing cost in the banking sector and λl is firms’ price sensitivity for banking loans. From the above two equations, we can see that four factors could affect loan rate and loan size: nr r (the market interest rate in free capital market), AD , L δ and λl . Interestingly, changes of monetary policy instruments such as benchmark deposit rate or RRR do not enter loan equations directly, however, they could affect loan pricing and loan size indirectly since monetary policy changes will affect the market interest rate (Proofs can be found in Appendix A). Theoretical predictions When the deposit rate ceiling is binding and lending rate floor is not binding, loan rate increases with the market interest rate, while loan quantity decreases with the market interest rate. Monetary policy instruments can also affect bank lending through the market interest rate: loan rate increases with the benchmark deposit rate and RRR, while the loan quantity decreases when the PBC raises the benchmark deposit rate and RRR. 4. Empirical Analysis 4.1 Empirical Specification The goal of empirical models is to test the theoretical predictions and the theoretical model provides a good guideline for empirical specification. However the reality is much more complicated than that in the simple model. First, we need to identify the most likely scenario in the real world: the deposit rate ceiling is binding while the lending rate floor is not binding. Even though the credit quota may be imposed on the banking sector when necessary, it is generally believed that the PBC tends to use it as little as possible, especially in recent years. Therefore, our empirical models are based on the simple scenario without credit quota, although the potential impact of credit quota will be discussed in the caveat. Now we discuss empirical factors impacting bank lending one by one. a). Policy instruments and the market interest rate The first theoretical prediction illustrates that when the deposit rate ceiling is binding and lending rate floor is not binding, loan rate increases with the market interest rate in the

free capital markets, while loan quantity decreases with the market interest rate. The central bank can also impact bank lending through the market interest rate: loan rate increases with the benchmark deposit rate and rrR, while the loan quantity decreases when the PBC raises the benchmark deposit rate and RRR. The benchmark deposit rate is well defined in reality: we use one-year deposit rate set by PBC as the benchmark deposit rate in empirical models. However, the role of rrR has changes a lot because the liquidity situation in Chinese banking system is overwhelmed by large foreign exchange purchases in recent years and rrr has been used as a main ool to drain the liquidity released from the sterilization. Therefore, we also include foreign exchange purchases in our empirical models to better identify the impact from the RRR In addition to shocks from the central bank, it is easy to see that bank lending could be impacted by various shocks from financial markets and the real economy through the market interest rate. For example, large fund-raising events like large IPOs in the stock market withdraw a lot of liquidity from the market, which could push the market interest rate higher and affect bank lending. Shocks from the real economy such as capital inflows/outflows also affect the market interest rate and bank lending which suggests the market interest rate includes more information other than monetary policy changes Therefore, in this empirical analysis we also include the market interest rate from non regulated markets after controlling for monetary policy changes. In the empirical model, we use 7-day Repurchase Agreement interest rate(7-day Repo) to represent the market interest rate in the free capital market since the 7-day repo rate is the most widely used indicator for capital price in non-regulated market b). Aggregate loan demand It is easy to see that both price and quantity of loans depend positively on aggregate loan demand because better economic conditions increase the profitability of projects and hence increase the demand for credit(Kashyap et al., 1994). Empirically, we use fixed asset investment growth as the proxy to represent loan demand in banking sector since most loans in our sample are for medium-long term investment projects. In reality the nominal interest rate on loans is also affected by macroeconomic variables such as money supply and inflation. Therefore, we also include money supply and inflation in the empirical models to control for macroeconomic conditions c). Credit risk The management of risk is a major issue for loan making as banks have to control various risks(credit risks, liquidity risks and market risks etc. ) that are inherent in their business Among these risks, credit risk is the most important in bank lending and banks charge borrowers different risk premium according to their features. Measuring credit risk means evaluating the probability of default by a particular borrower after taking into account various risk diversification and hedging arrangements In theory, issuing central bank bills could impact the market interest rate, however, the impact is not significant empirically(He and Wang, 2012) 6 The level of risks related to bank loans also depends on many institutional arrangements, and a

9 free capital markets, while loan quantity decreases with the market interest rate. The central bank can also impact bank lending through the market interest rate: loan rate increases with the benchmark deposit rate and RRR, while the loan quantity decreases when the PBC raises the benchmark deposit rate and RRR. The benchmark deposit rate is well defined in reality: we use one-year deposit rate set by PBC as the benchmark deposit rate in empirical models. However, the role of RRR has changes a lot because the liquidity situation in Chinese banking system is overwhelmed by large foreign exchange purchases in recent years and RRR has been used as a main tool to drain the liquidity released from the sterilization. Therefore, we also include foreign exchange purchases in our empirical models to better identify the impact from the RRR.5 In addition to shocks from the central bank, it is easy to see that bank lending could be impacted by various shocks from financial markets and the real economy through the market interest rate. For example, large fund-raising events like large IPOs in the stock market withdraw a lot of liquidity from the market, which could push the market interest rate higher and affect bank lending. Shocks from the real economy such as capital inflows/outflows also affect the market interest rate and bank lending, which suggests the market interest rate includes more information other than monetary policy changes. Therefore, in this empirical analysis we also include the market interest rate from nonregulated markets after controlling for monetary policy changes. In the empirical model, we use 7-day Repurchase Agreement interest rate (7-day Repo) to represent the market interest rate in the free capital market since the 7-day Repo rate is the most widely used indicator for capital price in non-regulated markets. b). Aggregate loan demand It is easy to see that both price and quantity of loans depend positively on aggregate loan demand because better economic conditions increase the profitability of projects and hence increase the demand for credit (Kashyap et al., 1994). Empirically, we use fixedasset investment growth as the proxy to represent loan demand in banking sector since most loans in our sample are for medium-long term investment projects. In reality the nominal interest rate on loans is also affected by macroeconomic variables such as money supply and inflation. Therefore, we also include money supply and inflation in the empirical models to control for macroeconomic conditions. c). Credit risk The management of risk is a major issue for loan making as banks have to control various risks (credit risks, liquidity risks and market risks etc.) that are inherent in their business. Among these risks, credit risk is the most important in bank lending and banks charge borrowers different risk premium according to their features. Measuring credit risk means evaluating the probability of default by a particular borrower after taking into account various risk diversification and hedging arrangements.6 5 In theory, issuing central bank bills could impact the market interest rate, however, the impact is not significant empirically (He and Wang, 2012). 6 The level of risks related to bank loans also depends on many institutional arrangements, and a

In theory it can be proved that the risk premium charged by banks increases with the debt-to-asset ratio and maturity of loans( Freixas and Rochet, 2008). In practice, many banks employ various models to measure credit risks. Those models generally have multiple indicators outlining various aspects of the risk related to borrowing firms The most commonly used indicators include total asset, total employment, liquid asset ratio, debt-to-asset ratio, profit margin and equity-to-debt ratio etc. In addition, some qualitative indicators are also included: The sector of the firm, the area where the firm is located, the ownership of the firm etc(Mu, 2007). Of course, the riskiness of loans is affected by the existence of collateral, which will be considered in loan pricing On the other hand various contract features are also used to mitigate credit risk in bank lending practice to enhance their ability to monitor borrowers over the course of the relationship(Strahan, 1999). Loan size is one of these features, which limits the banks potential exposure to credit risk of a specific borrower. Other features such as maturity and collateral of loans also play important roles in reducing credit risk in lending practice d ). Bank efficiency and price sensitivity of loans According to Equations(4)and (5), both loan rate and loan amount are also affected by efficiency of bank lending, which can be largely measured by managing costs of banks such as screening, monitoring and branching costs etc. dr N(AD-2r) >0 since ad-2r>0 and. >r d6(N+824)2 dL -N2(AD-1rnr) o8(N+84) 0, and n,>0 (7) From Equation(6)and(7)it is easy to see that loan pricing is positively correlated to banks' managing costs and the opposite applies to loan amount. However, in the empirical analysis it is hard to get detailed data about managing cost of screening and monitoring since this data is usually commercially confidential. The way we deal with this issue is to include dummies variables for banks so as to control for divergent efficiency across them. Another factor impacting loan pricing is price sensitivity of loans, which is clearl negatively related to loan rate from Equation(4). Intuitively it makes perfect sense that banks could charge a firm with higher prices when loan demands from firms are insensitive to loan rates. In the empirical study we assume the price sensitivity of loans can in general be captured by a firm' s characteristics and dummies representing firm's industries 4.2 What determines loan rate and loan size? comprehensive discussion about this can be found at Chapter 8 in Freixas and Rochet (2008). ompanies like Standard Poor's, Moody's Analytics, Fitch Ratings, and Dun and Bradstreet provide such services. Most Chinese commercial banks have adopted quantitative credit risk evaluation models, for example, ICBC use s rating system similar to Standard Poors to evaluate credit risk from borrowers(Mu

10 In theory it can be proved that the risk premium charged by banks increases with the quasi debt-to-asset ratio and maturity of loans (Freixas and Rochet, 2008). In practice, many banks employ various models to measure credit risks.7 Those models generally have multiple indicators outlining various aspects of the risk related to borrowing firms. The most commonly used indicators include total asset, total employment, liquid asset ratio, debt-to-asset ratio, profit margin and equity-to-debt ratio etc. In addition, some qualitative indicators are also included: The sector of the firm, the area where the firm is located, the ownership of the firm etc (Mu, 2007). Of course, the riskiness of loans is affected by the existence of collateral, which will be considered in loan pricing. On the other hand, various contract features are also used to mitigate credit risk in bank lending practice to enhance their ability to monitor borrowers over the course of the relationship (Strahan, 1999). Loan size is one of these features, which limits the bank’s potential exposure to credit risk of a specific borrower. Other features such as maturity and collateral of loans also play important roles in reducing credit risk in lending practice. d). Bank efficiency and price sensitivity of loans According to Equations (4) and (5), both loan rate and loan amount are also affected by efficiency of bank lending, which can be largely measured by managing costs of banks such as screening, monitoring and branching costs etc. 2 ( ) ( ) L l l nr L l N r N AD r δ λ λ δ + − = ∂ ∂ >0 since l l AD − λ r >0 and l nr r > r (6) 0 ( ) ( ) 2 0, and λl >0 (7) From Equation (6) and (7) it is easy to see that loan pricing is positively correlated to banks’ managing costs and the opposite applies to loan amount. However, in the empirical analysis it is hard to get detailed data about managing cost of screening and monitoring since this data is usually commercially confidential. The way we deal with this issue is to include dummies variables for banks so as to control for divergent efficiency across them. Another factor impacting loan pricing is price sensitivity of loans, which is clearly negatively related to loan rate from Equation (4). Intuitively it makes perfect sense that banks could charge a firm with higher prices when loan demands from firms are insensitive to loan rates. In the empirical study we assume the price sensitivity of loans can in general be captured by a firm’s characteristics and dummies representing firm’s industries. 4.2 What determines loan rate and loan size? comprehensive discussion about this can be found at Chapter 8 in Freixas and Rochet (2008). 7 Companies like Standard & Poor's, Moody's Analytics, Fitch Ratings, and Dun and Bradstreet provide such services. Most Chinese commercial banks have adopted quantitative credit risk evaluation models, for example, ICBC use s rating system similar to Standard & Poor's to evaluate credit risk from borrowers (Mu, 2007)

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