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Collectivism and corruption in bank lending

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Abstract

This paper examines how national culture, and collectivism in particular, influences corruption in bank lending. We hypothesize that interdependent self-construal and particularist norms in collectivist countries lead to a higher level of lending corruption through their influence both on the interactions between bank officers and bank customers and on the dynamics among bank colleagues. Using a sample covering 3835 firms across 38 countries, we find strong evidence that firms domiciled in collectivist countries perceive a higher level of lending corruption than firms domiciled in individualist countries. In terms of economic magnitude, the effect of collectivism is substantially larger than the effects of other cultural dimensions (uncertainty avoidance, masculinity, and power distance) and institutional factors identified in prior studies (bank supervision, bank competition, information sharing, and media monitoring). We further find that the positive relationship between collectivism and lending corruption is not driven by endogeneity, and that it is robust to different measures of bank corruption, different measures of collectivism, and different estimation methods. Finally, we find that the link between collectivism and lending corruption cannot be explained by the role of the government in the economy, political connections, biased responses from disgruntled borrowers, or relationship lending.

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Notes

  1. A closely related concept is cronyism. Khatri et al. (2006) define cronyism as “a reciprocal exchange transaction where party A shows favor to party B based on shared membership in a social network at the expense of party C's equal or superior claim to the valued resource”. They take cronyism to be a subset of corruption, since cronyism corresponds exclusively to a reciprocal exchange, while corruption may involve negotiated or reciprocal exchanges. In this paper, we focus on lending corruption, and consider both types of exchanges.

  2. For example, Zurcher, Meadow, and Zurcher (1965) survey 230 Mexican (CLT = 70), Mexican-American, and Anglo-American (CLT = 9) bank employees about their value orientation towards particularism and universalism. The authors find that Mexican bank employees are the most particularist, followed by Mexican-American and then Anglo-American employees. They argue that, when facing a conflict between duty to a friend and duty to society, Mexican bank employees tend to align themselves with the friend, while Anglo-American bank employees tend to choose the universalist alternative.

  3. We make this argument here without considering the effect of the second mechanism, which predicts that even when dealing with unrelated customers, the likelihood and extent of deviant behaviors among bank officers could be higher in collectivist societies than in individualist societies. We discuss the possibility that individualist bank officers may behave more opportunistically than their collectivist counterparts after Hypothesis 1.

  4. Collectivists see themselves as part of a group. However, one must be careful in generalizing about which “collectivity” a particular culture identifies with. For any given society, it is important to determine the group with which individuals have the closest identification (Trompenaars, 1993: 53).

  5. It is worth noting that when corrupt transactions are allowed to stand unchecked in collectivist societies, individual acts of corruption can become routine and widespread. Psychological numbing takes place as members of a group become repeatedly exposed to deviant behaviors (Earle et al., 2010: 221), and over time corrupt behavior becomes the norm. While such deviance normalization can occur in both individualist and collectivist countries, collectivists are more likely to build informal networks and create private understandings, as they place more weight on relationships than on societal codes (Trompenaars, 1993: 45–46). Therefore a collectivist culture is more likely to support an environment that permits side-payments between borrowers and lenders in the banking system, even in the case of arm's length transactions involving strangers.

  6. We thank an anonymous reviewer for providing insights to motivate the predictions behind this hypothesis.

  7. We additionally incorporate Leverage, which is defined as 100 times the difference between 1 and the percentage of a firm's financing (one year before the survey) from retained earnings and equity. (See Table 1 in the supplementary information on the JIBS website.) The fraction of financing from retained earnings and the fraction of financing from equity come from WBES. The results presented in Table 2 are not sensitive to the inclusion of Leverage, and the coefficient on Leverage is generally economically and statistically insignificant. Given the smaller sample size due to missing data for the leverage proxy, and the reduced comparability with previous studies such as Beck et al. (2006), we exclude Leverage from our main models.

  8. We also employ an ordered logistic model to estimate the regressions in Table 2 and calculate proportional odds ratios for each predictor. (See Table 2 in the supplementary information on the JIBS website.) This method leads to the same conclusions as Table 2 regarding the relations between lending corruption and the measures of collectivism, uncertainty avoidance, masculinity, as well as power distance. In particular, we find that the odds ratios for collectivism in Model 1 and Models 5–9 are greater than 1, suggesting a positive relationship between bank corruption and collectivism that is consistent with our findings reported in Table 2.

  9. In this model, the value of the goodness-of-fit measure, pseudo R 2, increases from 2% before the inclusion of CLT (unreported regression) to 5% after its inclusion. Despite our efforts to include every known determinant of corruption in bank lending in our regressions, the pseudo R 2s of our models may appear relatively low. Thus, for the sake of comparison, we appraise our R 2s in light of three related papers – Barth et al. (2009), Beck et al. (2006), and Houston et al. (2011) – that use the same data and estimation method, and predict the same outcome. Barth et al. (2009) do not report pseudo R 2s, but Beck et al. (2006) and Houston et al. (2011) both report pseudo R 2s around 0.05–0.06 in their main regressions. Moreover, according to Beck et al. (2006), a pseudo R 2 ranging from 5 to 9% is high for these types of cross-firm empirical studies.

  10. The arguments in Chen et al. (2002) may shed light on why the alternative prediction is rejected. Rather than generalize that individualists are more likely to be opportunistic than collectivist, the authors argue that the relationship between individualism/collectivism and opportunistic behaviors depends on relational factors. In individualist societies, justifications for morally questionable means to achieve desirable ends come primarily from self-interests, while in collectivist societies such justifications derive from self-interests, group interests, or both. The legitimacy of relationships above rules in collectivist societies makes opportunistic behaviors against out-groups morally less repugnant. Therefore, while an individualist loan officer may behave opportunistically towards loan applicants in general, a collectivist loan officer behaves more opportunistically towards loan applicants from his or her social network.

  11. Motivated by this evidence, we split the sample by the median (country) level of uncertainty avoidance in our sample. We find that the coefficient on CLT exhibits a positive sign at the 1% level in both subsamples, but has a smaller influence in countries with a high level of uncertainty avoidance. More specifically, a one standard deviation increase in CLT leads to a 3% (6%) increase in the probability that a firm will rate bank corruption as a major obstacle to its operation in high (low) UAI countries. These results suggest that a country's uncertainty-avoidance sentiment may mitigate the adverse effect of collectivism on the integrity of bank lending. We thank an anonymous reviewer for suggesting this additional analysis.

  12. One potential explanation for the unexpected sign on PDI could be the high correlation between PDI and CLT (0.5). (See Table 3 in the supplementary information on the JIBS website.) When orthogonalizing PDI and CLT, we find that the estimated coefficients on both orthogonal values are significantly positive.

  13. Reeb et al. (2012) provide a thorough summary of the remedies available to address non-random sample problems in international business research.

  14. To further reduce the concern that our findings simply reflect the influence of religion on lending corruption, we sequentially introduce the following religion-related variables from Guiso et al. (2003) as additional controls: percentage of population practicing the most influential religion in each country; percentage of population raised religiously; percentage of population attending religious ceremonies at least once a week; percentage of population attending religious ceremonies at least once a year; and percentage of population not believing in God. In untabulated results, we find that the positive and significant relationship between collectivism and lending corruption remains intact.

  15. Clawback provisions on executive compensation could change the incentives of bank loan officers. For example, Allen and Li (2011) find that clawback provision on bank lending agents in China reduces bank lending based on political connections, but increases lending based on economic fundamentals. In the US, Fried and Shilon (2011) find that on the eve of the 2010 Dodd–Frank Act, fewer than 2% of S&P 500 firms had robust clawback policies. To our best knowledge, information about clawback provisions on executive compensation across countries is not available. While China is not in our sample, we find that our core evidence on the effect of collectivism holds when we exclude firms from the US.

  16. Original genetic distance data are from Cavalli-Sforza, Menozzi, and Piazza (1994), who measure genetic distances between human populations. Genetic distance data between countries are available in an online appendix of Spolaore and Wacziarg (2009).

  17. Using an alternative dependent variable that captures lending cronyism helps alleviate the concern that these self-reported data reflect pure measurement errors, and provides further support to inferences based on our measure of bank corruption.

  18. We further replicate Table 2 with Need for Special Connections (proxy for lending cronyism) as an additional control. (See Table 5 in the supplementary information on the JIBS website.) The results show that the estimated coefficients on CLT do not change materially in terms of sign, statistical significance, or economic magnitude, suggesting that the relationship between collectivism and bank corruption goes beyond the effect of collectivism on lending cronyism.

  19. Tang and Koveos (2008) regress the four cultural dimensions on the set of determinants they identified, including average GDP per capita between 1970 and 1974. They then use the regression coefficients and insert the average GDP per capita between 1990 and 1994 to update Hofstede's cultural scores.

  20. As additional robustness check, we replicate Model 9 in Table 2 after replacing Hofstede's cultural indices with scores obtained from two alternative data sets of cultural dimensions: (1) GLOBE's cultural indices (“should be” values) on institutional collectivism, in-group collectivism, uncertainty avoidance, assertiveness, and power distance; and (2) Hofstede's four cultural indices updated by Tang and Koveos (2008). The results from these additional tests strongly support our earlier conclusions. (See Table 7 in the supplementary information on the JIBS website.)

  21. In unreported results, we continue to find evidence supporting the positive link between collectivism and corruption in bank lending when we also employ an ordinary least squares estimation, a weighted probit regression in which the weights are equal to the inverse of the number of firm observations in each country, an ordered probit with standard errors clustered at the country level, and an ordered logit estimation. (See Table 8 in the supplementary information on the JIBS website.)

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Acknowledgements

We would like to thank Najah Attig, Allen Berger, Narjess Boubakri, Nancy Buchan, Andy Spicer, Wook Sohn, and participants at meetings of the Academy of International Business (Nagoya), the 7th Annual Conference on Asia-Pacific Financial Markets (Seoul), the Financial Management Association (Denver), Southwestern Finance Association (New Orleans), where it received the best paper award in financial institutions, and the Northern Finance Association (Vancouver) for their constructive comments. We acknowledge financial support for this research project from Canada's Social Sciences and Humanities Research Council (SSHRC), the Center for International Business Education and Research (CIBER) at the University of South Carolina, and the Outstanding Researcher Support System (ORSS) at the Nottingham University Business School China.

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Authors and Affiliations

  1. Nottingham University Business School (NUBS) China, Ningbo, China

    Xiaolan Zheng

  2. Campus Saint-Jean, University of Alberta, Edmonton, Canada

    Sadok El Ghoul

  3. Moore School of Business, University of South Carolina, Columbia, USA

    Omrane Guedhami & Chuck C Y Kwok

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  1. Xiaolan Zheng
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  2. Sadok El Ghoul
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Correspondence to Chuck C Y Kwok.

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Supplementary information accompanies the paper on the Journal of International Business Studies website (www.palgrave-journals.com/jibs).

Accepted by David Reeb, Area Editor, 25 March 2013. This paper has been with the authors for three revisions.

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APPENDIX

APPENDIX

Table A1

Table A1 Variable definitions and sources
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Zheng, X., Ghoul, S., Guedhami, O. et al. Collectivism and corruption in bank lending. J Int Bus Stud 44, 363–390 (2013). https://doi.org/10.1057/jibs.2013.19

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