The relation between bank liquidity and stability: Does market power matter? My Nguyen, Michael Skully, Shrimal Perera 6th Financial Risks International Forum, Paris, France 26 March, 2013
Agenda 1. Introduction and definition 2. Motivation, research questions and academic contributions 3. Sample and methodology 4. Empirical results 5. Robustness tests 6. Additional contributions 7. Significance of the study 2
1. Introduction and definition
Introduction Research on the impact of bank liquidity on stability is important given the context of the Global financial crisis (Diamond and Rajan, 2011; Severo, 2011). Bank market power is a source of financial stability (Petersen and Rajan, 1995, Cetorelli and Peretto, 2000; Besanko and Thakor, 1993; Chen and Liao, 2011). Prior studies omit the interaction effect of market power and liquidity on bank stability. 4
Definition Bank stability: longer distance from default (Demirgüç-Kunt and Detragiache, 2011). Bank liquidity: meet unexpected withdrawals without affecting daily operations or financial condition (Acharya et al., 2011). Funding liquidity: meet financial obligations by raising funds on short notice (Brunnermeier, 2009). Asset liquidity: turn assets into cash quickly without affecting price (Brunnermeier, 2009). Bank market power: price products above marginal cost (Maudos and Fernández-de-Guevara, 2007). 5
2. Motivation, research questions and academic contributions
Motivation Studies on the effect of liquidity on stability obtain mixed results Positive impact: Liquidity reduces idiosyncratic shock (Carletti et al., 2007). Negative impact: Liquidity facilitates the sale of bank assets in crises and hence reduces banks incentive to avoid them. (Wagner, 2007; Tabak et al., 2012). We argue such inconsistency may be due to the impact of market power on bank risk taking behaviour. 7
Motivation Market power may impact the association between liquidity and stability in two ways: The competition-stability nexus: In order to offset the low returns from holding liquidity, banks with market power may charge higher loan rates or lend to risky borrowers and therefore exacerbate moral hazard problem (Stiglitz and Weiss, 1981) However, the competition-fragility view: Liquid banks with less market power (i.e. due to increased competition) earn less monopoly rent. This may encourage banks to lend to less creditworthy customers, thereby increasing their default risk (Keeley, 1990). 8
Motivation Recent studies only: Capture the additive effect of market power on stability (Turk-Ariss, 2010). Investigate banks choice of liquid assets (Acharya and Viswanathan, 2011) and their fear of fire sales (Diamond and Rajan, 2011). 9
Research questions RQ1: Does liquidity impact bank stability? RQ2: Is the relation between bank liquidity and stability impacted by market power? 10 10
Academic contributions This is the first study that examines: Whether the association between bank liquidity and stability is affected by market power. Such investigation is vital because market power may lead to an offsetting or even a reversal of the initial benefits of liquidity on bank stability. Market power in relation to bank liquidity and stability across 113 developed and developing countries. Such examination is essential because bank market power and their risk taking incentives differ with economic development and depend on environmental settings. 11 11
3. Data and methodology
Data Data types Bank-specific data Industry-specific data Country-specific data Sources BankScope The Heritage Foundation and the Wall Street Journal (Miles, et al., 2011); Respective Sample Bank Websites; Barth, et al., (2002, 2004, 2008); International Association of Deposit Insurers (2012) World Development Indicator; International Financial Statistics; Laeven and Valencia (2008; 2010) 13
Sample selection Descriptions No. of banks No. of countries Initial sample 16,430 193 Exclude banks/countries without market power and liquidity data Exclude banks without other control variable data Exclude banks with less than threeconsecutive-yearly reports 7,314 80 1,385 2,126 Final sample banks/countries 5,605 113 14
Methodology Prior research finds an endogeneity problem between market power and stability (Berger, et al., 2009; Uhde and Heimeshoff, 2009). If endogeneity exists: the two-step Generalised Method of Moments (GMMs) is used (Arellano and Bover, 1995). If there is no endogeneity: the Panel Least Squares method will be used (Brooks, 2008). 15
Empirical formulations RQ1: Does liquidity impact bank stability? N C SSS i,j,t = ψ + β 1 LLL i,j,t + β 2 MM i,j,t + ε n + ε i,j,t 1 n=1 X n + ζ c i, j and t denote individual banks, countries and time horizon; n. indexes the control variables; c indexes dummy variables; STA is bank stability; Ψ is a constant; LIQ is bank liquidity proxies; MP represents for bank market power proxies; X and D indicate a vector of control variables; ε is a stochastic error term; and β, ε and ζ are parameters to be estimated. c=1 D c 16
Empirical formulations RQ2: Is the relation between liquidity and stability impacted by market power? N SSS i,j,t = ψ + β 3 MM i,j,t + β 4 LLL i,j,t + β 5 MM j,t LLL i,j,t + ε n C + ζ c c=1 n=1 D c + ε i,j,t. (2) β 4 and β 5 are expected to be statistically significant implying that the relation between liquidity and stability is impacted by bank market power X n 17 17
. Bank stability Z-index (Turk-Ariss, 2010) Z i,j,t = ROA i,j,t + E/TA i,j,t δ ROAi,j,t (3) i, j and t denote individual banks, countries and time horizon; ROA: return on assets; E: equity capital; TA: bank total assets; σ: dynamic SD of ROA 18
Bank liquidity Ratio of liquid assets to short term liabilities Liquid assets: a bank s trading securities, loans and advances to banks, reserve repos, cash, dues from banks minus mandatory reserves (Männasoo and Mayes, 2009; Fitch Ratings and Bureau van Dijk, 2011) Short term liabilities: the share of customer and short term funds Interbank ratio: interbank lending to borrowing (Schaeck and Cihák, 2010; Fitch Ratings and Bureau van Dijk, 2011) 19 19
Bank market power Conventional Lerner Index LLLLLL = PPP MMMM /PPP PTA: Price of total assets; MCTA: Marginal cost of total assets derived from: MMMM = CCCC η Q 1 + η 2 lll + κ 3 1 W k + ν 3TTTTT Cost is total costs, Q is total asset, W is a vector of three input prices (funds, physical capital and labour), Trend is time trend. CCCC, η 1, η 2, κ and ν 3 are derived from the translog cost function for each country (in Equation 5) Funding-adjusted Lerner: The cost of fund is omitted. 20
Bank-specific and dummy control variables BANKSIZE Natural log of bank total assets Authors calculation using BankScope (+/-) EQUITY Ratio of total equity to total assets BankScope (+/-) Panel C:Bank-specific control variables BANKSIZE Natural log of bank total assets Authors calculation using A dummy variable that takes value of 1 for a bank that is BankScope EQUITY Ratio of total equity to total assets audited by one of the big four reputable auditors (Deloitte, BankScope EFFICIENCY Ratio of total cost to total income BankScope BIG4 Ernst &Young, KPMG, A PricewaterhouseCooper) dummy variable that takes value and of 1 for 0 a bank that is Authors calculation using otherwise audited by one of the big four reputable auditors BankScope A dummy variable that (Deloitte, takes the Ernst value &Young, of KPMG, 1 for banks that PricewaterhouseCooper) and 0 otherwise GOVERNMENT are 50% or more foreign A dummy owned, variable each that year takes the value of 1 for banks sample that Authors banks calculation website using A dummy variable that are takes 50% the or more value foreign of owned, 1 for banks each year that respective sample banks website FOREIGN >=50% A dummy variable that takes the value of 1 for banks that Authors calculation using are 50% or more foreign owned, each year sample banks website are 50% or more foreign owned, each year respective sample banks website FOREIGN>=30% A dummy variable that A takes dummy the variable value that of takes 1 for the banks value of that 1 for banks that Authors calculation using are 30% or more foreign owned, each year respective sample banks website LISTED are 30% or more foreign A dummy owned, variable each that year takes the value of 1 for banks sample with Authors banks calculation website using A dummy variable that stock takes exchange the value listings, of each 1 for year banks with respective sample banks website EDI A dummy variable that takes the value of 1 for banks in a Authors calculation using stock exchange listings, each year sample banks website country with explicit deposit insurance system, each year International Association of Deposit A dummy variable that takes the value of 1 for banks in a Insurers (2012) CRISIS Take on a value of 1 for crisis years, each country, each Laeven and Valencia (2008; 2010) country with explicit deposit insurance system, each year year EFFICIENCY Ratio of total cost to total income BankScope (+) BIG4 Authors calculation using BankScope (+) GOVERNMENT FOREIGN >=50% FOREIGN>=30% LISTED EDI Authors calculation using respective Authors calculation using respective Authors calculation using respective Authors calculation using respective Authors calculation using International Association of Deposit Insurers (2012) (+/-) (-) (-) (+) (+/-) CRISIS Take on a value of 1 for crisis years, each country, each year Laeven and Valencia (2008; 2010) (-) 21 21
Industry- and country-specific control variables Industry-specific variables 3k-CON Market share of the three largest banks Authors calculation using BankScope and International Financial Statistics (+/-) 5k-CON Market share of the five largest banks Authors calculation using BankScope and International Financial Statistics Panel C:Bank-specific control variables BANKSIZE Natural log of bank total assets Authors calculation using BankScope EQUITY Ratio of total equity to total assets BankScope EFFICIENCY Ratio of total cost to total income BankScope BIG4 A dummy variable that takes value of 1 for a bank that is Authors calculation using The number of entry applications denied as a fraction of the audited by one of the big four reputable auditors BankScope number of applications (Deloitte, received Ernst from &Young, domestic KPMG, and foreign entities PricewaterhouseCooper) and 0 otherwise GOVERNMENT A dummy variable that takes the value of 1 for banks that Authors calculation using A dummy variable that are takes 50% or the more value foreign of owned, 1 when each there year are respective sample banks website FOREIGN multiple >=50% bank supervisors A dummy variable that takes the value of 1 for banks that are 50% or more foreign owned, each year Authors calculation using respective sample banks website FOREIGN>=30% A dummy variable that takes the value of 1 for banks that are 30% or more foreign owned, each year Authors calculation using respective sample banks website LISTED A dummy variable that takes the value of 1 for banks with stock exchange listings, each year Authors calculation using respective sample banks website EDI A dummy variable that takes the value of 1 for banks in a country with explicit deposit insurance system, each year Authors calculation using International Association of Deposit Insurers (2012) CRISIS Scale from 0 to 10 where Take a on score a value of 110 for indicates crisis years, very each country, little each Laeven and Valencia (2008; 2010) year DEPRATE The average deposit rate net of inflation World Development Indicator (-) ENTRY DENIED Barth et al. (2008) (+/-) MULGREG 22 22 (+/-) Barth et al. (2008) (+/-) Country-specific variables EFREEDOM Openness of a country s financial sector Barth et al. (2008) (+) BUSCYCLE Annual real GDP growth rate. International Financial Statistics (+) FINDEV Private credit to GDP International Financial Statistics (+/-) FREECORRUPT Miles et al. (2012) corruption and a score of 0 indicates a very corruption (-) government
3. Empirical results
Summary statistics Summary statistics Table 3 Summary statistics of regression variables in Equation 1 All countries All countries Developed countries Developing Obs Me Medi Max Mi Std Obs Me Medi Developed Max Mi Std Obs Mecountries Medi Max Mi Std Developing countries. an an. n... an an. n... an an. n.. Z_INDEX 42,3 21. 16.7 45.6 2.7 14. 20,9 23. 20.4 45.6 2.7 15. 21,4 18. 13.5 45.6 2.7 14. 08 07 5 2 0 98 01 78 9 2 0 08 07 42 2 2 0 39 RAROA 42,1 11. 42.5 1.4 10. 20,8 12. 42.5 1.4 10. 21,3 10. 42.5 1.4 10. 7.28 8.42 6.18 56 08 8 1 71 44 12 8 1 97 12 07 8 1 36 RAROE 42,4 13. 55.2 1.0 14. 20,9 15. 55.2 1.0 15. 21,4 10. 55.2 1.0 12. 7.91 9.90 6.63 68 28 8 9 09 81 76 8 9 53 87 87 8 9 03 NPL 25,6 5.2 23.7 0.1 6.3 10,3 3.3 23.7 0.1 4.2 15,3 6.6 23.7 0.1 7.0 2.77 1.64 3.66 80 8 0 3 3 32 1 0 3 8 48 0 0 3 9 LIQUIDASSET 46,5 0.2 0.0 0.2 22,4 0.2 0.0 0.2 24,0 0.3 0.0 0.1 0.23 0.81 0.18 0.81 0.25 0.81 06 9 3 2 50 8 3 5 56 0 3 9 INTERBANK 25,8 1.8 5.4 1.9 12,3 1.7 5.4 1.8 13,4 2.0 5.4 2.0 1.10 7.10 0.98 7.10 1.25 7.10 65 9 9 9 66 0 9 8 99 6 9 7 LOANDEPOSIT 41,8 1.2 0.2 0.9 20,0 1.0 0.2 0.8 21,8 1.3 0.2 1.0 0.88 4.18 0.88 4.18 0.89 4.18 79 0 0 7 17 8 0 4 62 0 0 7 CONLERNER - - - 45,1 0.2 0.2 23,7 0.1 0.2 21,4 0.4 0.4 0.32 0.67 0.0 0.20 0.41 0.0 0.42 0.67 0.0 91 3 5 59 8 5 32 0 5 9 1 9 FUNDLERNER - - - 45,1 0.2 0.2 23,7 0.2 0.2 21,4 0.4 0.4 0.29 0.71 0.1 0.19 0.46 0.0 0.49 0.71 0.1 36 8 3 23 0 2 13 7 8 2 8 2 BANKSIZE 46,6 6.4 10.2 2.9 2.0 22,5 7.1 10.2 2.9 1.8 24,1 5.7 10.2 2.9 1.9 6.36 7.13 5.60 37 4 0 3 3 29 5 0 3 5 08 9 0 3 7 EQUITY (%) 46,5 13. 45.9 2.9 11. 22,5 11. 45.9 2.9 10. 24,0 15. 11.6 45.9 2.9 11. 9.79 8.14 89 60 2 0 08 09 53 2 0 40 80 53 3 2 0 35 EFFICIENCY (%) 45,7 64. 63.0 110. 27. 21. 22,1 63. 62.9 110. 27. 20. 23,5 64. 63.2 110. 27. 22. 41 37 4 00 27 48 43 89 0 00 27 16 98 81 4 00 27 65 BIG4 82,4 0.3 0.0 0.4 35,8 0.3 0.0 0.4 46,5 0.2 0.0 0.4 10 2 0 6 35 5 0 8 75 9 0 5 STATE 82,4 0.0 0.0 0.1 35,8 0.0 0.0 0.0 46,5 0.0 0.0 0.1 10 2 0 3 35 1 0 7 75 3 0 6 LISTED 82,0 0.7 0.0 0.4 35,8 0.8 0.0 0.3 46,2 0.5 0.0 0.4 1.00 1.00 1.00 1.00 1.00 1.00 48 1 0 5 33 7 0 4 15 9 0 9 FOREIGN>=50% 80,0 0.2 0.0 0.4 33,4 0.2 0.0 0.4 46,5 0.1 0.0 0.3 14 0 0 0 54 6 0 4 60 5 0 5 EDI 82,3 0.8 0.0 0.4 35,8 0.9 0.0 0.2 46,5 0.6 0.0 0.4 1.00 1.00 1.00 1.00 1.00 1.00 75 0 0 0 00 6 0 0 75 8 0 7 3k-CON 77,3 0.5 0.1 0.2 33,1 0.6 0.2 0.2 44,1 0.5 0.1 0.2 0.58 0.98 0.73 0.98 0.52 0.98 64 9 9 3 75 8 0 2 89 3 9 3 DEPRATE - - - 81,8 2.5 21.5 4.7 35,6 2.8 21.5 4.9 46,2 2.3 21.5 4.5 0.23 0.5 0.49 0.5 0.06 0.5 60 7 0 0 30 6 0 1 30 5 0 2 6 6 6 MULREG 81,8 0.0 0.0 0.2 35,3 0.1 0.0 0.3 46,5 0.0 0.0 0.1 85 9 0 9 10 8 0 8 75 2 0 5 RESTRICTION 81,8 9.5 14.0 6.0 2.1 35,3 8.9 14.0 6.0 2.0 46,5 9.9 14.0 6.0 2.2 9.00 9.00 9.00 85 1 0 0 8 10 8 0 0 1 75 0 0 0 2 ENTRYDENIED 81,8 0.2 12.0 0.0 1.4 35,3 0.0 0.0 0.1 46,5 0.3 12.0 0.0 1.8 0.00 0.00 85 2 0 0 1 10 3 0 1 75 6 0 0 5 FINDEV (%) 81,0 49. 32.9 147. 7.1 41. 35,5 60. 48.9 147. 7.1 43. 45,4 41. 28.2 147. 7.1 38. 32 83 0 56 7 90 97 03 8 56 7 95 35 83 2 56 7 36 EFREEDOM 78,8 65. 63.2 88.0 39. 13. 33,6 59. 59.1 88.0 39. 10. 45,1 69. 66.7 88.0 39. 14. 20 32 0 0 10 99 79 97 0 0 10 80 41 32 0 0 10 75 BUSCYCLE - - - 82,3 2.8 3.5 35,7 2.3 3.6 46,5 3.2 3.4 2.97 8.65 5.0 2.30 8.65 5.0 3.35 8.65 5.0 07 5 6 51 5 0 56 3 8 1 1 1 FREECORRUPT 78,4 53. 50.0 100. 4.0 28. 33,8 46. 40.0 100. 10. 26. 44,6 59. 53.0 100. 4.0 28. 41 67 0 00 0 51 07 43 0 00 00 67 19 17 0 00 0 63 CRISIS 82,4 0.2 0.0 0.4 35,8 0.2 0.0 0.4 46,5 0.3 0.0 0.4 10 6 0 4 35 1 0 1 75 0 0 6 Note: This table provides summary statistics (numbers of bank-year observations, mean, median, maximum, minimum and standard deviation) of main regression variables in Equation 1. While Panel A describes descriptive statistics for entire 113 developed and developing, Panels B and C show descriptive statistics for developing countries (69 countries; 3,026 banks) and developed countries (44 countries; 2,576 banks), respectively. Mean Med. Max. Min. Std. Mean Med. Max. Min. Std. Mean Med. Max. Min. Std. Z_INDEX 21.07 16.75 45.62 2.70 14.98 23.78 20.49 45.62 2.70 15.08 18.42 13.52 45.62 2.70 14.39 LIQUIDASSET 0.29 0.23 0.81 0.03 0.22 0.28 0.18 0.81 0.03 0.25 0.30 0.25 0.81 0.03 0.19 INTERBANK 1.89 1.10 7.10 5.49 1.99 1.70 0.98 7.10 5.49 1.88 2.06 1.25 7.10 5.49 2.07 CONLERNER 0.23 0.32 0.67-0.09 0.25 0.18 0.20 0.41-0.01 0.25 0.40 0.42 0.67-0.09 0.45 FUNDLERNER 0.28 0.29 0.71-0.12 0.23 0.20 0.19 0.46-0.08 0.22 0.47 0.49 0.71-0.12 0.48 24 24
RQ1: Does liquidity impact on bank stability? Dependent variable: Z-INDEX All countries Developed countries Developing countries Methods GMM GMM GMM PLS PLS PLS GMM GMM GMM GMM GMM GMM -0.15*** -2.54*** -0.89*** -1.12** -0.15*** -1.25*** CONLERNER (-0.66) (-2.16) (-0.95) (-3.46) (-3.79) (- 5.8800) FUNDLERNER LIQUIDASSET INTERBANK -0.51*** -0.19*** -1.63*** -1.03*** -0.47*** -0.86*** (-0.97) (-0.22) (-1.63) (-2.75) (-0.90) (-0.72) 1.58*** 1.93*** 4.87*** 4.86** 0.74*** 0.03*** (2.42) (2.92) (3.46) (2.78) (0.49) (0.9) 0.00*** 0.00*** -0.00-0.00 0.00*** 0.00*** Banks with more liquid assets and those that are net lenders in the interbank markets are more stable. (4.34) (1.15) (-0.13) (-1.29) (0.8) (0.91) 25 25 21
RQ2: Is the relation between liquidity and stability impacted by market power? Dependent variable: Z-INDEX All countries Developed countries Developing countries Methods GMM GMM GMM PLS PLS PLS GMM GMM GMM GMM GMM GMM LIQUIDASSET 0.71*** 0.44** - - 0.69*** 3.37*** - - 0.06*** 2.87*** - - (1.84) (1.55) - - (0.95) (1.11) - - (4.32) (5.6) - - LIQUIDCON -4.64*** - - - -2.96** - - - -0.66*** - - - (-2.96) - - - (-0.89) - - - (-4.02) - - - LIQUIDFUND - -3.57*** - - - -1.86** - - - -0.40*** - - - (-2.53) - - - (-0.56) - - (-0.84) - - INTERBANK - - 0.07*** 0.01* - - 0.12*** 0.07*** - - 0.27** 0.27*** - - (2.41) (2.5) - - (3.67) (2.82) - - (5.4) (5.88) Liquidity enhances bank stability. Market power reduces the positive impact of liquidity on bank stability. INTERCON - - -0.10*** - - - -0.16** - - - -0.37*** - - - (-2.33) - - - (-3.62) - - - (-5.49) - INTERFUND - - - -2.50*** - - - -0.09** - - - -0.33* - - - (-2.14) - - - (-2.75) - - - (-5.98) 26
Bank-specific and dummy control variable results BANKSIZE EQUITY EFFICIENCY BIG4 GOVERNMENT LISTED All countries Developed countries Developing countries GMM GMM GMM PLS PLS PLS GMM GMM GMM GMM GMM PLS 0.96* -1.41*** -0.69-1.33-0.90*** -0.86*** -2.33*** -1.57*** 2.46*** 3.75*** 5.56*** 5.21*** (3.75) (-5.30) (-1.14) (-3.89) (-2.75) (-2.09) (-3.50) (-2.53) (6.36) (7.17) (6.46) (7.17) 0.15*** 0.17*** 0.09*** 0.24* 0.31*** 0.32** 0.05** 0.11** 0.13*** 0.15*** 0.23*** 0.28*** (11.32) (11.06) (2.52) (6.91) (8.83) (6.44) (0.86) (1.83) (6.41) (5.76) (4.11) (5.21) -0.10*** -0.10*** -0.07*** -0.06*** -0.05*** -0.05** -0.01** -0.02** -0.18*** -0.22*** -0.21*** -0.21*** (-15.01) (-16.20) (-5.67) (-7.40) (-4.26) (-3.79) (-0.36) (-1.40) (-12.99) (-11.80) (-9.71) (-10.80) 0.60*** 1.91*** 0.61*** 4.55*** 0.02*** 0.05** 0.91** 0.49** 0.33*** 1.23*** 1.91 2.62*** (2.12) (6.34) (1.47) (1.94) (1.44) (2.16) (1.58) (1.00) (0.82) (2.19) (2.28) (3.16) 0.77 0.81 2.93 - - - -4.01** -2.64 3.09*** 2.86*** 1.27 0.87*** (1.22) (1.29) (3.49) - - - (-0.94) (-0.68) (4.15) (2.99) (0.87) (0.60) 3.32*** 3.14*** 3.84*** 6.28*** 6.49** 6.95 5.94 5.23-0.50 0.07*** 0.39*** 1.21*** (9.52) (10.48) (8.02) (3.19) (0.79) (1.50) (7.69) (8.08) (-1.19) (0.15) (-0.48) (-1.53) Larger banks in developing countries are more stable than those in developed counterparts FOREIGN >=50% EDI -1.45*** -1.58*** -3.09*** -2.12*** -4.22** -4.17-6.44** -5.61** 0.64-0.16*** -2.88*** -1.36 (-5.07) (-5.58) (-6.83) (-3.12) (-0.34) (-7.26) (-9.94) (-10.83) 1.38 (-0.29) (-2.83) (-1.49) -2.03*** -1.74*** -2.98*** -6.89*** -2.38** -2.27*** -3.13** -3.44** -2.24*** -1.86*** -3.02*** 2.34 (-4.89) (-4.01) (-5.15) (-3.25) (-0.37) (-0.25) (-2.34) (-2.72) (-4.1100) (-2.66) (-2.77) (2.22) CRISIS -0.32*** -0.51*** -0.64-0.15*** -0.23*** -0.20-0.49*** -0.39-0.45*** 0.7638-0.44 0.18 (-1.42) (-2.12) (-1.83) (-0.48) (-0.61) (-0.49) (-0.80) (-0.68) (-1.36) (1.69) (-0.58) (0.26) 27 27
Industry- and country-specific control variables 3k_CON All countries Developed countries Developing countries -5.73*** -5.17*** -6.72*** -6.14*** -2.22** -2.13*** -4.10-7.29* -9.59-10.37-1.86*** -1.38*** (-11.09) (-9.36) (-5.94) (-3.41) (-1.32) (-1.07) (-2.21) (-5.70) (-8.28) (-7.32) (-5.31) (-4.93) RDEPRATE MULREG ENTRY DENIED FINDEV EFREEDOM BUSCYCLE FREE CORRUPT ψ -0.28*** -0.28*** -0.39*** 0.03*** -0.50*** 0.50-0.56** -0.41** -0.35*** -0.38*** -0.27*** -0.36*** (-11.52) (-11.67) (-8.60) (0.72) (-12.66) (10.29) (-4.30) (-4.13) (-9.78) (-8.46) (-3.78) (-5.38) -2.67*** -3.06*** 2.4134 0.65-11.04** -11.03*** -5.53*** -6.71*** -1.14*** -1.35*** -1.74*** -1.96*** (-5.45) (-6.39) (1.79) (0.23) (-3.56) (-2.61) (-1.83) (-2.78) (-1.12) (-0.69) (-1.74) (-1.12) -0.17*** -0.19*** -0.04*** -0.89*** -0.99** -1.04** 3.95-4.47** -0.51*** -0.57*** -1.42* -0.92*** (-1.72) (-1.97) (-0.22) (-5.58) (-0.27) (-0.23) (-2.10) (-2.52) (-3.80) (-3.42) (-5.45) (-3.39) -0.01-0.01*** 0.01-0.06-0.12-0.12*** -0.01-0.02 0.03*** 0.04 0.05* 0.06** (-3.53) (-3.30) (0.59) (-5.78) (-10.63) (-8.37) (-1.67) (-3.15) (5.53) (5.92) (3.88) (4.79) 0.07*** 0.0743*** 0.06*** 0.10*** 0.04*** 0.04* 0.35** 0.40 1.52*** 1.75*** 1.63*** 1.46*** (5.64) (5.69) (3.43) (2.06) (0.13) (0.12) (2.07) (2.57) (10.94) (10.11) (6.68) (6.39) 0.22 0.24* 0.26 0.23 0.09*** 0.09*** 0.34** 0.32** 0.15*** 0.17*** 0.13 0.30*** (7.59) (7.96) (5.94) (5.46) (2.44) (2.02) (4.52) (4.67) (3.12) (2.76) (1.30) (3.11) 0.07*** 0.07** 0.07* 0.13 0.04** 0.04** 0.07** -0.07 0.04*** 0.05*** 0.05 0.07*** (13.79) (13.73) (9.09) (5.85) (1.91) (1.57) (6.47) (-6.99) (3.75) (4.02) (2.71) (3.50) 0.48*** 1.15*** -0.74*** 0.78*** 0.02*** 0.02*** -1.00*** -0.33*** 0.04*** 0.38*** 0.93*** 0.57*** (5.06) (6.45) (-0.68) (1.5) (3.34) (3.37) (-2.26) (-1.12) (4.47) (5.72) (5.24) (5.78) R-squared 0.12 0.09 0.12 0.13 0.14 0.12 0.10 0.11 0.12 0.13 0.10 0.09 Bank stability is also positively associated with financial development in developing countries while the opposite effect is observed for developed nations Bank-year obs. 21,088 21,066 12,027 13,127 10,435 10,427 5,649 5,641 11,157 11,143 6,378 6,364 28 28
5. Robustness tests Robustness tests on the findings include using Alternative measure of individual bank stability: risk-adjusted measures of return on assets and risk-adjusted return on equity (Turk-Ariss, 2010). Other measure of bank liquidity: loan to deposit ratio (Agoraki et al., 2011) Other proxy for market concentration: the fraction of the total banking system s assets held by the five largest domestic and foreign banks for each country (Carletti et al., 2007). 30% foreign ownership as an alternative classification of foreign bank (Jeon, et al., 2011) 29
6. Additional contributions Besides the academic contributions of the two research questions, this study improves on prior methodology in respect to Using a GMM estimator developed by Arellano and Bover (1995) and Blundell and Bond (1998) instead of using the Two- Stages Least Squares (2SLS) method. Using Lerner index as bank-specific measures of market power instead of bank performance, HHI, k-bank concentration ratio and Panzar-Rosse H statistics. 30
7. Significance of the study These findings should also have important implications for: Policy makers and regulators: whether the new international standards on bank liquidity should incorporate an adjustment to reflect bank market power avoid a one size fit all approach as the impact of market power on the association between liquidity and stability differs with country financial development Central bankers: should assess the impact of market power on stability and liquidity relation when extending liquidity support Depositors: note how their bank stability is impacted as this improves their bank selection and reduce risk of loss from their bank insolvencies 31