Abstract
Are firms that are managed and owned by females-only appraised differently than those where genders mix at the top? To answer this question, we study 7,467 small and medium-sized firms from 22 countries. We find that—when borrowing from banks—firms that are both managed and owned by females more often report binding credit constraints and higher interest rate payments than male-only firms: differences that we can attribute to taste-based discrimination. In contrast, if the manager and the owner have a different gender, we find no such differences with male-only firms. Hence, interestingly banks seem to assume that women invariably play second fiddle in the mixed-gender firms. We also show that discrimination between female-only and other firms disappears from economically more developed regions and from credit markets that are more competitive or dominated by transactional lenders.
Plain English Summary
Is mixing genders at the top good or bad for firm financing? It may matter or not. To arrive at this answer, we study almost 7,500 small and medium-sized firms from 22 countries. When borrowing from banks, firms that are both managed and owned by females obtain less financing. In contrast, if the manager and the owner have a different gender, we find no such differences with male-only firms. The implication is that bankers rightly or wrongly seem to assume that women invariably play second fiddle in mixed-gender firms. More progress toward gender equality seems possible.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
Notes
The 22 countries include: Albania, Armenia, Azerbaijan, Belarus, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Estonia, Georgia, Hungary, Latvia, Lithuania, FYR Macedonia, Moldova, Montenegro, Poland, Romania, Serbia, Slovak Republic, Slovenia, and Ukraine.
BEEPS also collects information on the value of the collateral, but the information is very incomplete and there are many firms that do not report this information. For firms that do report the information, we use the value of the pledged collateral and the value of the loan at origination to calculate the loan-to-value ratio. The number is 80% on average, which is very reasonable.
The BEEPS survey mainly focus on SMEs and according to the European Commission’s “Enterprise and industry SBA Factsheet 2016: Poland”, in 2015, SMEs in Poland account for 99.8 percent of businesses in the Polish “non-financial business economy.”.
Although crime experience and product losses may correlate with the social or economic environments where the firm is located and thus contribute to credit access via local banking market competition, but in our analyses we have controlled the PSU fixed effects to address any regional differences and thus only focus on within region variation. Within each region, the social and economic environments are constant.
In BEEPS V, there is a module about information of top managers. But this module is only available for Turkey, which is not part of our final sample. However, using this module we can get some idea about if gender is related to differences in ability. Specifically, the module collects the top managers’ highest level of formal education, for a sample of 1,299 firms in Turkey. Within this sample, we find no significant correlation between gender and the level of education. This preliminary correlation result can give us some confidence that the ability of top managers is not gender-specific.
The matching process is done in Stata by the “psmatch2” command, and the results are unaffected if we use the “teffects” command.
We utilize both the inverse-probability-weighted (IPW) estimator and the IPW-regression-adjustment (IPWRA). The results are the same.
References
Alesina, A. F., Lotti, F., & Mistrulli, P. E. (2013). Do women pay more for credit? Evidence from Italy. Journal of the European Economic Association, 11(s1), 45–66. https://doi.org/10.1111/j.1542-4774.2012.01100.x
Altonji, J. G., Elder, T. E., & Taber, C. R. (2005). Selection on observed and unobserved variables: Assessing the effectiveness of Catholic schools. Journal of Political Economy, 113(1), 151–184. https://doi.org/10.1086/426036
Asiedu, E., Kalonda-Kanyama, I., Ndikumana, L., & Nti-Addae, A. (2013). Access to credit by firms in Sub-Saharan Africa: How relevant is gender? American Economic Review, 103(3), 293–297. https://doi.org/10.1257/aer.103.3.293
Aterido, R., Beck, T., & Iacovone, L. (2013). Access to finance in sub-Saharan Africa: Is there a gender gap? World Development, 47, 102–120. https://doi.org/10.1016/j.worlddev.2013.02.013
Beck, T., & Demirguc-Kunt, A. (2006). Small and medium-size enterprises: Access to finance as a growth constraint. Journal of Banking & Finance, 30(11), 2931–2943. https://doi.org/10.1016/j.jbankfin.2006.05.009
Beck, T., Degryse, H., De Haas, R., & Van Horen, N. (2018). When arms’ length is too far: Relationship banking over the business cycle. Journal of Financial Economics, 127(1), 174–196. https://doi.org/10.1016/j.jfineco.2017.11.007
Becker, G. S. (1957). The Economics of Discrimination. University of Chicago Press.
Bellucci, A., Borisov, A., & Zazzaro, A. (2010). Does gender matter in bank–firm relationships? Evidence from small business lending. Journal of Banking & Finance, 34(12), 2968–2984. https://doi.org/10.1016/j.jbankfin.2010.07.008
Berkovec, J. A., Canner, G. B., Gabriel, S. A., & Hannan, T. H. (1998). Discrimination, competition, and loan performance in FHA mortgage lending. Review of Economics and Statistics, 80(2), 241–250. https://doi.org/10.1162/003465398557483
Chen, X., Huang, B., & Ye, D. (2020). Gender gap in peer-to-peer lending: Evidence from China. Journal of Banking & Finance, 112, 105633. https://doi.org/10.1016/j.jbankfin.2019.105633
Comanor, W. S. (1973). Racial discrimination in American industry. Economica, 40(160), 363–378. https://doi.org/10.2307/2553319
Davison, H. K., & Burke, M. J. (2000). Sex discrimination in simulated employment contexts: A meta-analytic investigation. Journal of Vocational Behavior, 56(2), 225–248. https://doi.org/10.1006/jvbe.1999.1711
De Andrés, P., Gimeno, R., & de Cabo, R. M. (2020). The gender gap in bank credit access. Journal of Corporate Finance.https://doi.org/10.1016/j.jcorpfin.2020.101782
Degryse, H., & Ongena, S. (2005). Distance, lending relationships, and competition. Journal of Finance, 60(1), 231–266. https://doi.org/10.1111/j.1540-6261.2005.00729.x
Degryse, H., Kim, M., & Ongena, S. (2009). Microeconometrics of banking: Methods, applications, and results. Oxford University Press.
Gavazza, A., Nardotto, M., & Valletti, T. (2019). Internet and politics: Evidence from UK local elections and local government policies. Review of Economic Studies, 86(5), 2092–2135. https://doi.org/10.1093/restud/rdy028
Gorodnichenko, Y., & Schnitzer, M. (2013). Financial constraints and innovation: Why poor countries don’t catch up. Journal of the European Economic Association, 11(5), 1115–1152. https://doi.org/10.1111/jeea.12033
Heckman, J. J. (1979). Statistical models for discrete panel data. Department of Economics and Graduate School of Business, University of Chicago.
Heilman, M. E., & Haynes, M. C. (2005). No credit where credit is due: Attributional rationalization of women’s success in male-female teams. Journal of Applied Psychology, 90(5), 905–916. https://doi.org/10.1037/0021-9010.90.5.905
Heilman, M. E., Block, C. J., & Martell, R. F. (1995). Sex stereotypes: Do they influence perceptions of managers? Journal of Social Behavior and Personality, 10(4), 237–252.
Heilman, M. E., Block, C. J., Martell, R. F., & Simon, M. C. (1989). Has anything changed? Current characterizations of men, women, and managers. Journal of Applied Psychology, 74(6), 935–942. https://doi.org/10.1037/0021-9010.74.6.935
Heimer, R. Z., Myrseth, K. O. R., & Schoenle, R. S. (2019). YOLO: Mortality beliefs and household finance puzzles. Journal of Finance, 74(6), 2957–2996. https://doi.org/10.1111/jofi.12828
Ilgen, D. R., & Pulakos, E. D. (1999). The changing nature of performance: Implications for staffing, motivation, and development. Frontiers of industrial and organizational psychology. Jossey-Bass Inc.
Jensen, N. M., Li, Q., & Rahman, A. (2010). Understanding corruption and firm responses in cross-national firm-level surveys. Journal of International Business Studies, 41, 1481–1504. https://doi.org/10.1057/jibs.2010.8
Jianakoplos, N. A., & Bernasek, A. (1998). Are women more risk averse? Economic Inquiry, 36(4), 620–630. https://doi.org/10.1111/j.1465-7295.1998.tb01740.x
Klumpp, T., & Su, X. (2013). Second-order statistical discrimination. Journal of Public Economics, 97, 108–116. https://doi.org/10.1016/j.jpubeco.2012.09.004
Kysucky, V., & Norden, L. (2016). The benefits of relationship lending in a cross-country context: A meta-analysis. Management Science, 62(1), 90–110. https://doi.org/10.1287/mnsc.2014.2088
Liberti, J. M., & Petersen, M. A. (2019). Information: Hard and soft. Review of Corporate Finance Studies, 8(1), 1–41. https://doi.org/10.1093/rcfs/cfy009
Mammen, K., & Paxson, C. (2000). Women’s work and economic development. Journal of Economic Perspectives, 14(4), 141–164. https://doi.org/10.1257/jep.14.4.141
Mc Cartan-Quinn, D., & Carson, D. (2003). Issues which impact upon marketing in the small firm. Small Business Economics, 21(2), 201–213. https://doi.org/10.1023/A:1025070107609
Moro, A., Wisniewski, T. P., & Mantovani, G. M. (2017). Does a manager’s gender matter when accessing credit? Evidence from European data. Journal of Banking & Finance, 80, 119–134. https://doi.org/10.1016/j.jbankfin.2017.04.009
Mukhtar, S. M. (2002). Differences in male and female management characteristics: A study of owner-manager businesses. Small Business Economics, 18(4), 289–310. https://doi.org/10.1023/A:1015235402335
Mulligan, C. B., & Rubinstein, Y. (2008). Selection, investment, and women’s relative wages over time. Quarterly Journal of Economics, 123(3), 1061–1110. https://doi.org/10.1162/qjec.2008.123.3.1061
Muravyev, A., Talavera, O., & Schäfer, D. (2009). Entrepreneurs’ gender and financial constraints: Evidence from international data. Journal of Comparative Economics, 37(2), 270–286. https://doi.org/10.1016/j.jce.2008.12.001
Nkurunziza, J. D. (2010). The effect of credit on growth and convergence of firm size in Kenyan manufacturing. Journal of International Trade & Economic Development, 19(3), 465–494. https://doi.org/10.1080/09638190802617670
Ongena, S., & Popov, A. (2016). Gender bias and credit access. Journal of Money, Credit and Banking, 48(8), 1691–1724. https://doi.org/10.1111/jmcb.12361
Oster, E. (2019). Unobservable selection and coefficient stability: Theory and evidence. Journal of Business & Economic Statistics, 37(2), 187–204. https://doi.org/10.1080/07350015.2016.1227711
Pham, T., & Talavera, O. (2018). Discrimination, social capital, and financial constraints: The case of Viet Nam. World Development, 102, 228–242. https://doi.org/10.1016/j.worlddev.2017.10.005
Popov, A., & Udell, G. F. (2012). Cross-border banking, credit access, and the financial crisis. Journal of International Economics, 87(1), 147–161. https://doi.org/10.1016/j.jinteco.2012.01.008
Powell, M., & Ansic, D. (1997). Gender differences in risk behaviour in financial decision-making: An experimental analysis. Journal of Economic Psychology, 18(6), 605–628. https://doi.org/10.1016/S0167-4870(97)00026-3
Qi, S., & Ongena, S. (2019). Will money talk? Firm bribery and credit access. Financial Management, 48(1), 117–157. https://doi.org/10.1111/fima.12218
Qi, S., & Ongena, S. (2020). Fuel the engine: Bank credit and firm innovation. Journal of Financial Services Research, 57(2), 115–147. https://doi.org/10.1007/s10693-019-00316-6
Schein, V. E. (2001). A global look at psychological barriers to women’s progress in management. Journal of Social Issues, 57(4), 675–688. https://doi.org/10.1111/0022-4537.00235
Tabellini, M. (2020). Gifts of the immigrants, woes of the natives: Lessons from the age of mass migration. Review of Economic Studies, 87(1), 454–486. https://doi.org/10.1093/restud/rdz027
Wisner, P. S., & Feist, H. A. (2001). Does TEAMIN pay off? Strategic Finance, 82(8), 58–58.
Acknowledgements
The authors would like to thank two anonymous referees, Yangming Bao, Jia He, Mingming Jiang, Da Ke, Esteban Lafuente (Editor), Jakob Madsen, and participants at Australasian Finance & Banking Conference, China International Conference in Finance (Tianjin), Great China Area Finance Conference (Xiamen), Nankai University Young Scholars in Finance Conference (Tianjin), 11th International Conference of Methods in International Finance Network (Ji’nan), and Dongbei University of Finance and Economics Workshop (Dalian) for useful comments. Shusen Qi acknowledges financial support from the National Natural Science Foundation of China (71903164, 71790601) and Social Science Foundation of Fujian Province (FJ2019B140). Steven Ongena acknowledges financial support from ERC ADG 2016—GA 740272 lending.
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Information
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Qi, S., Ongena, S. & Cheng, H. Working with women, do men get all the credit?. Small Bus Econ 59, 1427–1447 (2022). https://doi.org/10.1007/s11187-021-00579-1
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11187-021-00579-1