Conscientia Beam || conscientiabeam.com

Export to

Citations

Contact Us

For Marketing, Sales and Subscriptions Inquiries

2637 E Atlantic Blvd #43110
Pompano Beach, FL 33062

USA

Conference List

International Journal of Business, Economics and Management

May 2020, Volume 7, 5, pp 310-330

The Effects of Macroeconomic Variables on Bank Default: A Case Study in Brazil

Mateus Feld

Wagner Eduardo Schuster

Mateus Feld¹ ^,

Wagner Eduardo Schuster¹

Universidade do Vale do Rio dos Sinos, Av. Dr. Nilo Peçanha, Porto Alegre, RS, Brazil. ¹

on Google Scholar

on PubMed

Pages: 310-330

DOI: 10.18488/journal.62.2020.75.310.330

Article History:

Received: 06 July, 2020
Revised: 14 July, 2020
Accepted: 17 July, 2020
Published: 23 July, 2020

View Citation

345Views

Create Citation Alert

Abstract:

With the end of the recession from 2014 to 2016, Brazil began a gradual recovery process, with a positive impact on some economic variables — among them, credit financing. Despite this, a robust recovery was not seen in 2019, and 2020 was marked by the arrival of the Covid-19 pandemic, which raises questions about the stability of the financial system and the control of defaults. Considering this, the present study explores how macroeconomic variables affected the default of a financial institution’s credit portfolio between January 2014 and April 2019. To perform this analysis, we built a Vector Error Correction (VEC) model that captured the long-term relationships between the default of different credit products and the selected macroeconomic variables. The results indicate that the macroeconomic variables do in fact impact default, however, this behavior is not homogeneous. In general, different credit products respond in different ways to each of the macroeconomic entities: while part of our findings is in line with others in the literature, we also found surprising results for some of the studied relationships.

Contribution/ Originality
This study contributes to the existing literature by demonstrating, through a case study in Brazil, the unique effects of the macroeconomic environment on the default of different and specific credit products, while most of the recent research focuses on aggregated data or default indexes.

Keywords:

Bank default, Brazil, Credit, Finance, Macroeconomic variables, Time series, VAR/VEC models.

Reference:

BACEN - Central Bank of Brazil. (2019). SGS - time series management system. Retrieved from: https://www3.bcb.gov.br/sgspub/consultarvalores/telaCvsSelecionarSeries.paint. [Accessed March 30, 2020].

BACEN - Central Bank of Brazil. (2020a). Banking economics report. Retrieved from: https://www.bcb.gov.br/content/publicacoes/relatorioeconomiabancaria/reb_2019.pdf . [Accessed April 12, 2020].

BACEN - Central Bank of Brazil. (2020b). Financial stability report. Retrieved from: www.bcb.gov.br/content/publicacoes/ref/202004/RELESTAB202004-refPub.pdf . [Accessed April 21, 2020].

Bonfim, D. (2009). Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics. Journal of Banking & Finance, 33(2), 281–299.Available at: https://doi.org/10.1016/j.jbankfin.2008.08.006.

Bueno, R. D. L. D. S. (2011). Time series econometrics (2nd ed.). São Paulo: Cengage.

CODACE - Economic Cycles Dating Committee. (2017). Announcement of dating of Brazilian monthly cycles. Retrieved from: https://portalibre.fgv.br/estudos-e-pesquisas/codace/codace.htm. [Accessed April 8, 2020].

Guo, L., & Bruneau, C. (2014). Macroeconomic variables and default risk: An application of the FAVAR model. Political Economy Review, 124(5), 817-857.

IBGE - Brazilian Institute of Geography and Statistics. (2019). Produto interno bruto – PIB. Retrieved from: http://www.ibge.gov.br/ . [Accessed March 30, 2020].

IMF - International Monetary Fund. (2006). Financial soundness indicators: Compilation guide 2006 - contents. Retrieved from: https://www.imf.org/external/pubs/ft/fsi/guide/2006/index.htm . [Accessed April 11, 2020].

IPEA - Institute of Applied Economic Research. (2019). Retrieved from: http://www.ipeadata.gov.br . [Accessed March 30, 2020].

Jakubik, P. (2007). Macroeconomic environment and credit risk. Czech Journal of Economics and Finance, 57(1-2), 60-78.

Laurin, M., & Martynenko, O. (2009). The influence of macroeconomic factors on the probability of default: A study of the relationship between default probabilities and macroeconomic variables (Thesis). Retrieved from: https://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=1486524&fileOId=1647104. [Accessed April 18, 2020].

MacKinnon, J. G., Haug, A. A., & Michelis, L. (1999). Numerical distribution functions of likelihood ratio tests for cointegration. Journal of Applied Econometrics, 14(5), 563- 577.Available at: https://doi.org/10.1002/(sici)1099-1255(199909/10)14:5%3C563::aid-jae530%3E3.0.co;2-r.

Podpiera, J., & Weill, L. (2008). Bad luck or bad management? Emerging banking market experience. Journal of Financial Stability, 4(2), 135-148.Available at: https://doi.org/10.1016/j.jfs.2008.01.005.

Schumpeter, J. (1911). The theory of economic development. USA: Harvard University Press.

Securato, J. R. (2013). Credit: Risk analysis and assessment (2nd ed.). São Paulo: Saint Paul.

SERASA. (2019). Economic indicators. Retrieved from: https://www.serasaexperian.com.br/amplie-seus-conhecimentos/indicadores-economicos . [Accessed April 28, 2020].

Sommar, P. A., & Shahnazarian, H. (2008). Macroeconomic impact on expected default frequency. SSRN Electronic Journal.Available at: https://doi.org/10.2139/ssrn.1088626.

Stiglitz, J. E., & Weiss, A. (1981). Credit rationing in markets with imperfect information. The American Economic Review, 71(3), 393-410.

Tabak, B. M., Craveiro, G. L., & Cajueiro, D. O. (2010). Bank efficiency and default: Causality tests. Retrieved from: https://www.bcb.gov.br/pec/wps/port/TD220.pdf . [Accessed April 18, 2020].

Yanaka, G. M. (2014). Tests in risk management and banking regulation (Thesis). Retrieved from: https://bibliotecadigital.fgv.br/dspace/handle/10438/13133. [Accessed March 28, 2020].