Measuring bank competition in China: A comparison of new versus - PowerPoint PPT Presentation

Measuring bank competition in China: A comparison of new versus conventional approaches applied to loan markets. Bing Xu (Universidad Carlos III de Madrid) Adrian van Rixtel (Bank for International Settlements) Michiel van Leuvensteijn (APG) Michiel van Leuvensteijn (APG) VIII Annual Seminar on Risk, Financial Stability and Banking Banco Central do Brasil/Journal of Banking and Finance São Paulo, 8-9 August 2013. Restricted

Summary: What do we analyze?  How competitive are loan markets in China according to conventional and new measures?  How did competition in these markets develop over time?  What explains the differences between the results of the various measures (empirically and theoretically)? i ( i i ll d th ti ll )?  How to interpret the results over time (financial reform)?  How to interpret the results over time (financial reform)? 2 Restricted

Summary: How do we analyze it?  First paper that combines conventional and new measures.  Conventional approaches to measure bank competition (Panzar-Rosse H statistic and (elasticity-adjusted) Lerner index).  Relatively new approach to measure bank competition (Profit Elasticity (PE) indicator). El ti it (PE) i di t )  PE indicator: competition rewards efficiency and punishes  PE indicator: competition rewards efficiency and punishes inefficiency. If markets are more competitive, difference in profitability between efficient and less efficient banks is larger. 3 Restricted

Summary: What are our results?  Results of conventional measures indicate declining competition R l f i l i di d li i i i over time in Chinese loan markets.  Relatively new PE indicator shows improving competition.  Results PE indicator show that financial reform (based on three different indicators) is associated with improving competition (reverse finding for conventional measures) => not discussed.  Results for both conventional and new measures robust for alternative specifications. 4 Restricted

Summary: What explains the different results?  Conventional measures are biased due to regulation of interest rates:  Panzar-Rosse H-statistic will overestimate competition when due to interest rate regulation lending and deposit rates move in step move in step.  We demonstrate theoretically that the Lerner index is biased when interest regulation is binding. g g  The elasticity-adjusted Lerner index will overestimate competition when regulation of lending rate is binding.  We prove theoretically that the model underlying the PE indicator is robust under interest rate regulation. 5 Restricted

Structure presentation Institutional framework: Chinese banking. I. Methodological framework PE indicator. II. Results conventional vs. new measures. III. Conclusions. IV. 6 Restricted

I. Chinese banking: financial reform.  Financial reform (1978-1993, 1994-2002, 2003-present). Fi i l f (1978 1993 1994 2002 2003 ) November 2001: membership WTO approved. I. Interest rate deregulation: Interest rate deregulation: II II.  October 2004: elimination deposit rate floor and lending rate ceiling. g  Remaining deposit rate ceiling (binding) and lending rate floor (non-binding) (Feyzio ğ lu et al., 2009; He and Wang, 2011; Ma et al., 2011). l  Deposit rates capped at reference rates (until June 2012: 1.1x RR) RR) Reform of credit control system (binding credit plan system III. abolished in 1998) and other reforms. 7 Restricted

I. Empirical studies on Chinese banking  Most on efficiency (Berger et al., JBF 2009; Fu and Heffernan, JBF 2009 and AFE 2010; Matthews et al., HKMA 2009).  Financial reform (Berger et al., JBF 2010; Hasan and Xie, BOFIT 2012). i i l f l d i  Few on competition, both with H-stat (Yuan, JAE 2006; Bikker et al., DNB 2007; Fu BFR 2009) and Lerner index (Fungá č ová et al DNB 2007; Fu, BFR 2009) and Lerner index (Fungá č ová et al., BOFIT BOFIT 2012; Soedarmono et al., JIFM 2013): declining competition.  Fungá č ová et al. (2012): “… It is somewhat remarkable that China’s accession to WTO has not led to greater competition in the banking industry .”  P  Puzzle: despite process of financial reform, conventional measures l d it f fi i l f ti l show bank competition in China declining over time.  Empirical evidence EMEs: financial reform improved competition.  Empirical evidence EMEs: financial reform improved competition. 8 Restricted

I. Our sample of banks in China  State Owned Commercial Banks (SOCBs): Bank of China, Agricultural Bank of China, China Construction Bank and Industrial and Commercial Bank of China (“Big Four”) Provide Industrial and Commercial Bank of China ( Big Four ). Provide nationwide wholesale and retail banking services.  Joint Stock Commercial Banks (JSCBs) (13): partially owned by Jo t Stoc Co e c a a s (JSC s) ( 3): pa t a y o ed by local government, state owned enterprises and private sector. Operate at national and regional level.  City Commercial Banks (CCBs): operate at city level. In recent years though, this geographic restriction has been loosened.  Foreign banks (FBs): foreign exchange services nationwide  Foreign banks (FBs): foreign exchange services nationwide, renminbi services at city level.  In total 127 different banks, 714 observations. 9 Restricted

II. New measure: Profit Elasticity (PE) indicator.  Boone or Profit Elasticity (PE) indicator (Jan Boone, Tilburg University, CEPR); underlying theoretical model of Relative University, CEPR); underlying theoretical model of Relative Profit Differences (RPD).  Boone et al. (2007), Boone (EJ 2008): RPD/PE indicator are more robust both from a theoretical and an empirical point of view than PCM-based indicators (eg. Lerner index).  Our earlier work on competition in various countries and  Our earlier work on competition in various countries and impact competition on pass-through interest rates (Van Leuvensteijn et al., AE 2011, AE 2013).  Widely accepted: ECB, IMF, other central banks; academic publications (Tabak et al., JBF 2012). 10 Restricted

II. PE indicator.  Competition rewards efficiency and punishes inefficiency: linkage between efficiency (relative marginal costs) and performance (i.e. relative profits or market share) relative profits or market share).  Efficient banks are in general more profitable than inefficient banks. The more competitive the market, the larger the difference.  To obtain the PE indicator, estimate the relationship between profits and marginal costs (MC) for each bank i: ln (profits it ) = α + β t ln (MC it )+  t d t + u ilt (1)  β t is the PE indicator, d t is a time dummy.  β t should be negative: if markets are competitive, profits increase  β h ld b ti if k t titi fit i for banks having lower marginal costs relative to their competitors. The smaller β t , the stronger is competition. p β t g p 11 Restricted

III. Results: conventional measures, Panzar-Rosse H- statistic and (elasticity-adjusted) Lerner index.  Panzar-Rosse  Panzar Rosse H statistic: H-statistic: Results Results show show broadly broadly declining declining competition over time.  Lerner index and elasticity-adjusted Lerner index: Results show y j that competition declined after 2002. 12 Restricted

III. Results: new measure, PE indicator. Step 1: Estimation Translog Cost Function (TCF). Step 1: Estimation Translog Cost Function (TCF). Step 2: Calculate marginal costs (MCs): MCs of loans are the first derivative of the TCF for loans. Step 3: Estimate PE indicator:  Estimate relationship between profits and MCs: ln π ilt = α +  t=1,..,(T-1)  t d t +  t=1,..,T β t d t ln mc ilt + u ilt where π ilt stands for profits, d t is a time dummy, mc ilt for marginal costs i refers to bank i l to output type “loans” marginal costs, i refers to bank i, l to output type loans .  β t = PE indicator for year t.  β t is negative in theory: profits increase for banks having lower  β t is negative in theory: profits increase for banks having lower marginal costs relative to their competitiors.  The more competitive the market, the lower the value of β t . 13 Restricted

III. Results: new measure, PE indicator.  Competition improved after WTO accession in 2001. 7 5 3 1 PE indicator -1 1 1997 1997 1998 1998 1999 1999 2000 2000 2001 2001 2002 2002 2003 2003 2004 2004 2005 2005 2006 2006 2007 2007 2008 2008 -3 -5 -7  Sub-sample estimates: competition in post-WTO sign. higher. 1996-2008 1996-2001 2002-2008 PE Indicator -2.388*** -1.514 -3.570*** (-5.78) (-1.43) (-7.74)  Results robust for alternative specifications. 14 Restricted

IV. Conclusions: H-stat less appropriate for China.  Interest rate regulation in China.  H-stat: if input and output prices move in step, higher value of H-stat and interpretation of higher competition.  H-stat picks up the co-movement of regulated deposit and lending rates in China (Bikker et al lending rates in China (Bikker et al., DNB 2007; Feyzio ğ lu et al., DNB 2007; Feyzio ğ lu et al IMF 2009) =>it measures the degree in which the regulator sets deposit and lending rates jointly.  Lending rate ceiling abolished in 2004: may have reduced this bias somewhat =>  Our findings for the elasticity of interest revenue with respect to O fi di f h l i i f i i h the funding rate are much higher in pre-WTO period than in post-WTO period. p p 15 Restricted