Abstract
This paper investigates the effect of revenue diversification on bank performance and risk. Using a panel dataset of 226 listed banks across 11 emerging economies and a new methodological approach, System Generalized Method of Moments estimators (System GMM), the results in this paper provide empirical evidence of the impact of the observed shift towards non-interest income generating activities on insolvency risk and bank performance. The core finding is that diversification across and within both interest and non-interest income generating activities decrease insolvency risk and enhance profitability. The results also show that these benefits are largest for banks with moderate risk exposures. By extension, these results have significant strategic implications for bank managers, regulators and supervisors who share a common interest in boosting bank performance and stability.
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Notes
Revenue diversification is an avenue through which credit risk, which would normally be concentrated in a bank’s loan portfolio, can spread to the other non-interest generating activities that a bank engages in. As in developed economies, revenue diversification in emerging economies means that banks are able to engage in diverse non-interest income activities such as securities underwriting, insurance and real estate investment. Importantly, this paper reports -for the first time—evidence of a shift towards these activities in emerging economies.
The concern here is that some explanatory variables (e.g. profitability ratios) may be related to measures of diversification. For example, the benefits of diversification for an ailing bank that has chosen to diversify in order to improve its performance may be understated.
Researchers such as Stiroh and Rumble (2006); use standard estimators such as fixed effects estimators to eliminate the potential bias caused by omitted heterogeneity. The fixed effect estimator, which is a method of moment estimator based on the data after subtracting time averages, is popular for three reasons: it is simple, easily understood and robust standard errors are readily available. In fixed effects estimators there are two common assumptions, first; an assumption of strict exogeneity for the covariates, which is crucial for the consistency of the fixed effects estimator; and an assumption about the constant variance and no serial correlation used primarily to simplify calculations of standard errors. However, if either heteroskedasticity or serial correlation is present a Generalized Method of Moments procedure can be more efficient than the fixed effects estimators (Wooldridge 2001).
The x i,t may be endogenous in that they are correlated with v i,t and earlier shocks, but uncorrelated with v i,t−1 and subsequent shocks; predetermined in the sense that x i,t and v i,t are also uncorrelated, but may still be correlated with v i,t−1 and earlier shocks; or strictly exogenous, uncorrelated with all past, present and future realizations of v i,t (Bond 2002; Roodman 2006).
The natural logarithm (log) of total employees of a firm can also be used to proxy its size (we thank an anonymous referee for drawing our attention to this). However, due to data limitations we are unable to employ this measure in our analysis.
Unconsolidated data is preferred in this analysis to separate the actions of the parent company from its other subsidiaries that may or may not operate in the same jurisdiction or under the same banking law.
Note: An increase in HHI(rev) is an increase in concentration.
We estimate the economic magnitude of a particular variable by multiplying its standard deviation by the ratio of its regression coefficient to the mean of the dependent variable.
The intuition is that the level of insolvency risk is a proxy for both the willingness and the ability of banks to monitor their assets. The 75th percentile corresponds to 22.13, and 64 banks had Z-score higher than this and were excluded from the sample.
Banking freedom is a country specific annual index that captures the following aspects of bank regulation: operating freedom of foreign banks and financial services firms, ease of opening domestic banks and other financial services firms, stringency of the regulatory environment; presence of state-owned banks, government’s influence on the allocation of credit; and freedom to provide customers with insurance and invest in securities and vice-versa (The Heritage Foundation 2009). The results in Table 4 are replicated when the static measure of bank activity restriction in Barth et al. (2004) is used.
It is not necessary to control for firm level measures of investor protection for two main reasons; first, firm level protection is more valuable when state level protection is weak, therefore variations in state level protection is of greater interest. It is also important to bear in mind that firm-level protection mechanisms, for example, increased disclosure are designed originally as regulatory incentives to increase market discipline and not to primarily substitute state level protection, using them in this manner in empirical estimations may unnecessarily increase the “noise” around coefficient estimates. Second, listed banks may already be subject to increased disclosure requirements in which case firm-level variations is minimal. Considering both arguments, we find that state protection will better capture the effect of expropriation risk to these banks.
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Acknowledgments
We thank Robert Sauer, John Micklewright, Klaus Schaeck, Mohammed Amidu, Alistair Milne and an anonymous referee for helpful comments. The views expressed in this Paper are those of the authors and do not necessarily represent those of the IMF or IMF policy. Any remaining errors are ours.
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Appendix
Appendix
1.1 Literature review
In this appendix, we provide a more detailed review of the relevant literature on the impact of bank diversification activities. Kwan (1998), using a sample of 23 domestic U.S bank holding companies with Section 20 subsidiaries, over the period 1990 to 1997 show that diversification into securities activities increased risk of U.S bank holding companies with Section 20 subsidiaries. This result is echoed in Lang and Stulz (1994, 2009), DeYoung and Roland (2001), Morgan and Samolyk (2003), and Acharya et al. (2006). Stiroh (2004a) examines how non-interest income affects variations in bank profits and risk. Results from both aggregate and bank data provide little evidence that diversification benefits exist. The results are attributed to the fact that potential diversification benefits are receding as the correlation between net and non-interest income growth increases for the average bank in the sample. This result is also corroborated when Stiroh (2006a), use the same portfolio framework on equity market data for U.S. BHC’s during the period 1997 to 2004. Furthermore, Stiroh and Rumble (2006) comprehensively analyze balance sheet data for US financial holding companies (FHC’s) using both panel and cross sectional analysis. Their analysis show the “double-edged” nature of this phenomenon as revenue diversification does bring benefits however there are greater offsetting effects from an increased reliance on non-interest income, which are more volatile and not necessarily more profitable than interest generating activities. Goddard et al. (2008), in their study of diversification for small US credit unions find similar results.
1.2 The need to correct for endogeneity
A number of studies using balance sheet data have highlighted the need to correct for the endogeneity of the diversification decision since they find that high-risk banks in their sample were more likely to diversify (Lang and Stulz (1994) and Acharya et al. (2006)).
Templeton and Severiens (1992), find diversification to be beneficial for high-risk banks after identifying and controlling for the endogeneity of the diversification decision. Berger and Ofek (1995) without controlling for endogeneity find that diversification reduces franchise value especially when the diversification is within unrelated industries. However, when Campa and Kedia (2002), Hyland and Diltz (2002) and Villalonga (2004) replicate the work of Berger and Ofek (1995) and control for endogeneity they find the opposite. More specifically, when systematic differences in diversified and non-diversified firms are controlled for the diversification discount disappears or even turns into a premium.
The debate regarding whether a diversification discount or premium exists in diversifying firms remain unresolved. Khanna and Yafeh (2007), in their study of business groups in emerging markets allude to the “theoretical wisdom” that corporate diversification is a risk mitigating strategy especially where external markets are inefficient. However, their empirical results are inconclusive since they find evidence of both a diversification premium and a discount for their sample of firms. The complexities of these “business groups” make it difficult to generalize across this category of institutions. On the contrary, Elsas et al. (2010) in their cross-country study of revenue diversification consistently find that diversification increases bank value. Their results contradict earlier findings by Laeven and Levine (2007) who find no evidence of a diversification premium. Hund et al. (2010) shed some light on the debate in their study of the uncertainty about how average profitability of the bank biases the impact of diversification on bank value—an endogeneity problem that exists in cross-sectional studies of diversified firms. As an illustration, they find that diversified firms in their sample are consistently older with more market experience and have more stable expected earnings. Thus, a simple-cross sectional analysis that does not account for this de facto difference between the types of firms that diversify as oppose to focus their activities may yield erroneous results. Some salient points for the future of this debate: First, the importance of methods that exploit the panel, -more dynamic—as opposed to cross sectional features of a bank cannot be overemphasized. Since there are underlying differences between diversified and focused firms that will bias the relationship between diversification, value and risk in these firms. Also for the same reason, empirical research should control for the endogeneity of the diversification decision.
Regarding the use of balance sheet data, most of the disparity in results in the literature on revenue diversification stems from studies that have analyzed balance sheet data. These studies are often plagued with inconsistencies in the dataset and econometric methodology. For example, the segmented structure of the U.S banking system and the relative shorter history of diversification make it more likely that diversification benefits in U.S banks are lower compared to their European counterparts. Regarding the structure of the banking system, a number of studies particularly in the U.S, have found benefits of diversification for medium to large banks. According to Goddard et al. (2008) this is due to their expertise and technological advancement in effectively diversify away from their core product of loan provision, the benefits of diversification for small banks are virtually non-existent for the same reasons even in European banks (Mercieca et al. 2007; Goddard et al. 2008). Hence irrespective of the geographic location of banks, there are differences in diversification benefits across asset classes. There is also sufficient evidence to show that the endogeneity of the diversification decision biases the relationship between diversification and bank performance. According to Santomero and Chung (1992), a deeper look at the shortcomings of balance sheet data analysis suggest that the existence of diversification benefits as suggested by portfolio theory should not be discredited.
With the exception of studies such as (Stiroh 2006a) based on U.S banks, most studies on the third approach, using stock market data, have addressed the data segmentation problem endemic in analysis of the U.S banking sector. Thus, whilst the volatility of stock market data is relatively higher than balance sheet data, there appears to be a consensus on the fact that the benefits of diversification exist. This result may be because the listed banks are larger banks with less financing constraints, and generally more homogenous in characteristics compared to if the banks were randomly sampled. Therefore introducing this sample selection criterion makes it easier to carry out cross-country analysis and increases the general applicability of the result as shown in Baele et al. (2007).
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Sanya, S., Wolfe, S. Can Banks in Emerging Economies Benefit from Revenue Diversification?. J Financ Serv Res 40, 79–101 (2011). https://doi.org/10.1007/s10693-010-0098-z
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DOI: https://doi.org/10.1007/s10693-010-0098-z