Controversias con el Ateneo y la Real Academia

Table 2.5 reports the empirical results for a bank’s return on equity for the Indian banking industry through the first three models (i.e. 1, 2 and 3). It also reports the results for a bank’s return on assets for India through the last three models (i.e. 4, 5 and 6). Since bank ownership does not change over time, we use year dummies (i.e. time trend) in all regressions.

Models 1-3 of table 2.5 show that concentration (HHI) coefficients are always positive and significantly related to return on equity at the conventional statistical level, whereas the coefficients of market share are always negative and insignificant. This indicates that market concentration dominates the market share for the Indian banking industry, supporting the traditional interpretation of the structure-conduct-performance (SCP) hypothesis and rejecting the relative-market-power (RMP) hypothesis. We find similar results when return on assets is used as the dependent variable. These findings suggest that profitability for the Indian banking sector is determined by the concentration not by the market share of banks. It should be noted that the five largest banks of India have almost half of the market share of the Indian banking industry. These findings accord with much of the existing literature on emerging markets, which finds a positive and statistically significant relationship between market concentration and banking profitability (e.g., Al-Muharrami and Matthews, 2009; Bhatti and Hussain, 2010; Sufian, 2010; Ahamed, 2012).

Interpreting the bank-specific variable, we find that all of the coefficients are significant in models at least at the conventional statistical significance level except for the liquidity risk and growth rate of total assets. The coefficient of bank size (i.e. logarithm of total assets) is always positive and statistically significant, implying the existence of economies of scale in the Indian banking sector. This is an indication that size-induced

differences between banks lead to higher returns because larger banks operate at the most efficient scale (i.e., increasing return portion of their average cost curve). The scale efficiencies of larger banks also resonate with the positive impact of concentration on profitability in the banking sector. The empirical literature on optimal bank size is conflicting. However, a large number of studies find similar results to ours that larger banks enjoy economies of scale and scope whereas smaller banks suffer from diseconomies of scale and scope (e.g., Mirzaei, Moore and Liu, 2013).24

We find a negative and statistically significant relationship between credit risk and profitability. Since nonperforming loans are costly to the banks and a higher accumulation of unpaid loans renders lower profits, the negative relationship between credit risk and profitability is consistent with a priori expectations. Based on model 1, we find that a 1% decrease in net NPLs leads to a 0.12% increase in return on equity. However, the detailed explanations on the influence of bank size and ownership on the impact of credit risk are discussed in sub-sections 2.6.2 and 2.6.3, respectively.

The income diversification (DIV), measured as non-interest income to total income, appears to be instrumental for the profitability of the Indian banking sector.25 The positive relationship between diversification and profitability is consistent with a priori

expectations, and significant for all models at the 1% level, implies that banks with higher non-interest sources of income are more profitable. This result is consistent with Baele, De Jonghe and Vander Vennet (2007) and Chiorazzo, Milani and Salvini (2008). Similar to credit risk, the detailed explanations on the influence of bank size and ownership in the impact of diversification are also discussed in sub-sections 2.6.2 and 2.6.3, respectively.

24 _{According to the total assets size of individual banks, we created a dummy for the large bank group and}

ran regression on the entire sample. We find that large banks are statistically significant at the 1% level and positively related with return on equity (not with return on assets). It confirms that bank size has a significant impact on profitability.

25 _{We run a Durbin–Wu–Hausman test to check for endogeneity of the independent variable income}

diversification; the result obtained suggests that there is no endogeneity between profitability and diversification.

Capitalisation (EQA) is one of the most important bank-specific factors with a significant impact on the profitability of Indian banks. The capitalisation is negative and significant with return on equity. It reflects the expected theoretical relationship between risk and return, that is banks with a high-level of equity capital (i.e., low bankruptcy risk) lose potential profitable trading opportunities, and thereby earn lower profits (e.g., Berger, 1995b; Goddard, Molyneux and Wilson, 2004). However, it is positive and statistically significant with return on assets, indicating the soundness of Indian banks. A bank with higher equity capital can reduce bankruptcy costs, and hence earn higher profits through charging higher interest on loans and/or paying less on deposits (Ben Naceur and Goaied, 2008). The shareholders’ intense monitoring of bank managers’ activities can have a significant impetus on profitability as well. Recent studies that find a significant positive relationship between capitalisation and return on assets include Demirgüç-Kunt and Huizinga (1999), Chortareas, Garza-Garcia and Girardone (2011), Garza-Garcia (2012) and Berger and Bouwman (2013).

The liquidity risk (LTA), measured as the ratio of total loans over total assets, does not have a significant impact on profitability. However, the negative coefficient suggests that greater composition of assets in the form of loans may have a negative impact on returns. It is also consistent with a priori expectations and in line with the findings of Garza-Garcia (2012). The negative impact on profitability may be due to the high operating costs associated with servicing and monitoring a large number of loans.

The operational inefficiency measure (OPT) is negative and significant for models 1-4. The negative relationship between OPT and profitability is consistent with a priori

expectations and in line with the findings of Athanasoglou, Brissimis and Delis (2008). The negative coefficient suggests the existence of the X-efficiency hypothesis in which banks with efficient management are able to cut their operating expenses, and thereby increase profitability. The growth rate of total assets (GTA) does not have any significant

impact on profitability. However, the positive coefficient indicates that banks with higher growth rate in terms of total assets earn greater returns.

Explaining macroeconomic variables, we find inflation (INF) is always negative and statistically significant with profitability. This relationship indicates that bank managers were unable to anticipate inflation accurately over the sample period and act accordingly to adjust interest rates, resulting in faster increase of costs rather than revenues. The real interest rate (INT) is negative and significantly related with return on equity. The probable explanation for the negative coefficient is that real interest rate in India has risen significantly over the study period, which may have provided stringent economic conditions for the banking sector. Since banks transfer the interest rate risk to consumers, a high real interest rate may have reduced the amount of credit and financial services and, therefore they were unable to reap higher returns. This result contrasts with Bourke (1989), who finds a positive relationship between interest rate and profitability. However, the negative relationship is an indication that banks can be more profitable if they pursue non-interest sources of income in conjunction with their interest income. The final macroeconomic factor is the real GDP growth rate. We find a robust link between GDP and bank profitability. It does not conform to a priori expectations that higher growth rate results in higher returns for banks. However, we find a negative relationship between them. The increasing competition in the banking sector may have contributed to this inverse relationship. It is reasonable to understand that during a boom period banks tend to compete with each other fiercely for the deposits and loans as well as for other non- interest income, and thus respond in an anti-cyclical manner.

Models 3 and 6 show the estimation results of the dummy variables used in this study. The coefficient of the dummy variable of public banks is positive and statistically significant with return on equity. The dummy variable for foreign-owned banks does not have a statistically significant relationship with profitability but it is negatively related. The

possible explanation is that private foreign banks are slightly in a disadvantaged position in India due to lacking cultural, political and language knowledge. Since public sector banks are not wholly owned by public we add the percentage of government ownership at public banks to examine the impact of the level of government ownership on profitability. In doing so, we find a significant negative relationship with returns on equity at the 1% level. This strong negative relationship suggests that public banks with a higher level of government ownership earn significantly lower profits. The coefficient of old banks (i.e., any banks established before liberalisation in 1992) is positive and significant with return on assets, indicating that old banks in India earn higher returns than any bank that entered into the banking sector after the liberalization process began.