La visión de la mujer en los escritos de Blanca de los Ríos

Table 2.6a reports the estimation results of the influence of bank size on the impact of credit risk or income diversification on profitability. In these regressions the main concern is the coefficients of the interaction terms and their marginal effect.

Prior to describing the impact of credit risk or income diversification, it should be noted that, in the case of multiplicative terms in the models, based on simple t-statistics we cannot make accurate inference because model parameters do not provide adequate information (Brambor, Clark and Golder, 2006). Merely looking at the results without following correct procedures in the case of interaction terms would mislead the inference. Following Brambor, Clark and Golder (2006), we use marginal effect to show the influence of bank size on the impact of credit risk or income diversification26_{. A ‘Size Index’ is} created based on the 10th, 25th, 50th, 75th, 90th, 95th percentiles and mean values of bank

26 _{One may assume that the multicollinearity problem may arise if all constitutive terms are used in an}

interaction model. Brambor, Clark and Golder (2006) however state that multicollinearity may provide large standard errors but they are the correct standard errors.

size.

The coefficient of the interaction between credit risk and size is positive and insignificant. However, the positive sign implies that large banks are better able to manage their credit risk and earn higher profits. For a more precise analysis, we have calculated the marginal effect and standard errors of credit risk on profitability for different sizes of banks. From the marginal effects it can be envisaged that smaller banks (at 10th and 25th percentile in the Size Index) are vulnerable to higher credit risk and, hence earn less profit (Table 2.6b). The probable explanation is that the under-developed small banks tend to invest in risky projects or channel funds to lower quality borrowers. In addition, small banks have limited resources and limited ability to screen and monitor borrowers adequately in order to stem accumulating bad loans. It supports hypothesis 2 that the negative impact of credit risk on profitability in the form of NPLs varies with bank size.

The result also corroborates with the use of marginal effect graphs. Figure 2.3 shows the impact of credit risk or income diversification on profitability conditional on bank size. The graphs in the upper panel display the marginal effect of credit risk (i.e., thick solid line) at different levels of bank size on return on equity (left) or return on assets (right). It also confirms that the negative impact of credit risk diminishes as bank size increases. This in turn suggests that if the bank size is sufficiently high, then the marginal effect of credit risk may stop being negative and become positive. However, we have drawn two-tailed 95% confidence intervals around the marginal effect; the effect of credit risk is significant whenever the upper and lower bounds of the confidence intervals are both above (or below) the zero line. Therefore, it can be gleaned from Figure 2.3 that credit risk stops having a statistically significant effect on ROE and ROA once the bank size exceeds about Rs. 31.9 and 75.9 billion, respectively.

On the other hand, the coefficient of interaction between income diversification and bank size is positive and statistically significant at the 1% level. It suggests that large

banks are better able to diversify their income towards non-interest sources and earn higher profits than their smaller counterparts, supporting hypothesis 4 that the positive impact of income diversification on profitability in the form of non-interest income differs with bank size. The marginal effect and standard error are reported in table 6b. It suggests the impact of income diversification on bank profitability is conditional on bank size. As bank size increases, the positive impact of income diversification increases. These findings have reasonable economic interpretations. Since diversification acts as an inflator for the bank’s profitability, reasonable income stemming from non-interest sources would be ideal for Indian banks to maintain stability and fight against negative shocks. It is evident from this empirical estimation that larger banks with non-interest sources of income enjoy greater performance benefits than the smaller banks in the market. These favourable impacts increase as bank size increases. Though small banks have the highest diversified income from non-interest sources (recall table 2.3), overall it appears that larger banks achieve more favorable diversification benefits in the Indian banking industry. The probable reason could be the market power which allows them to enjoy cost synergies stemming from the economies of scale. It can be said that a bank with reasonable diversified income can water down any negative shocks better than a bank which has a trivial number of diversified portfolios. A well-diversified bank can increase returns substantially and hedge against risks.

The result is also verified in Figure 2.4. The graphs on the lower panel display the marginal effect of diversification at different levels of bank size on ROE (left) or ROA(right). It also confirms that the positive impact of diversification on profitability increases with bank size (in the case of ROA, we observe a marginal increase). These results also correspond with most of the previous studies on India, in which medium and large banks are found to be more efficient in terms of costs and profits (e.g., Das and

Ghosh, 2009; Bhattacharyya and Pal, 2013).

Figure 2.4

Marginal effect of credit risk or income diversification on bank profitability (e.g. return on equity and return on assets)

Note that it corresponds with our results in Tables 2.6a and 2.6b. The graphs on the upper panel display the marginal effect of credit risk at different levels of bank size on ROE (left) or ROA(right). It shows that the negative impact of credit risk diminishes as bank size increases. The thick line gives the marginal impact as estimated by∂Π ∂/ npl=β₁+β₃*Size, where ∏ is the banking profitability. The dotted lines represent the 95%

confidence interval. The graphs on the lower panel display the marginal effect of income diversification at different levels of bank size on ROE (left) or ROA(right). It shows that the positive impact of diversification increases as bank size increases. The thick line gives the marginal impact as estimated by

5 4

/ div β β *Size

∂Π ∂ = + .