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Macroeconomic shocks and credit risk stress testing the Iranian banking sector

Fatemeh Abdolshah (Faculty of Economics, Allameh Tabatabai University, Tehran, Iran)
Saeed Moshiri (Department of Economics, St. Thomas More College, University of Saskatchewan, Saskatoon, Canada)
Andrew Worthington (Department of Accounting, Finance and Economics, Griffith University, Queensland, Australia)

Journal of Economic Studies

ISSN: 0144-3585

Article publication date: 7 September 2020

Issue publication date: 2 February 2021

513

Abstract

Purpose

The Iranian banking industry has been greatly affected by dramatic changes in macroeconomic conditions over the past several decades owing to volatile oil revenues, changing fiscal and monetary policies, and the imposition of US sanctions. The main objective of this paper is to estimate potential credit losses in the Iranian banking sector due to macroeconomic shocks and assess the minimum economic capital requirements under the baseline and distressed scenarios. The paper also contrasts the applications of linear and nonlinear models in estimating the impacts of macroeconomic shocks on financial institutions.

Design/methodology/approach

The paper uses a multistage approach to derive the portfolio loss distribution for banks. In the first step, the dynamic relationship between the selected macroeconomic variables are estimated using a VAR model to generate the stress scenarios. In the second step, the default probabilities are estimated using a quantile regression model and the results are compared with those of the conventional linear models. Finally, the default probabilities are simulated for a one-year time horizon using Monte-Carlo method and the portfolio loss distribution is calculated for hypothetical portfolios. The expected loss includes the loss given default for loans drawn randomly and uniformly distributed and exposed at default values when loans are assigned a fixed value.

Findings

The results indicate that the loss distributions under all scenarios are skewed to the right, with the linear model results being very similar to those of quantile at the 50% quantile, but very unlike those at the 10% and 90% quantiles. Specifically, the quantile model for the 90% (10%) quantile generates estimates of minimum economic capital requirement that are considerably higher (lower) than those using the linear model.

Research limitations/implications

The study has focused on credit risk because of lack of data on other types of risk at individual bank level. The future studies can estimate the aggregate economic capital using a risk aggregation approach and a panel data (not presently available), which could further improve the accuracy of the estimates.

Practical implications

The fiscal and monetary authorities in developing countries, specially oil-exporting countries, can follow the risk assessment approach to assess the health of their banking system and adapt policies to mitigate the impacts of large macroeconomic shocks on their financial markets.

Originality/value

This is the first paper estimating the portfolio loss distribution for the Iranian banks under turbulent macroeconomic conditions using linear and nonlinear models. The case study can be applied to other developing and emerging countries, particularly those highly dependent on natural resources, prone to extreme macroeconomic shocks.

Keywords

Citation

Abdolshah, F., Moshiri, S. and Worthington, A. (2021), "Macroeconomic shocks and credit risk stress testing the Iranian banking sector", Journal of Economic Studies, Vol. 48 No. 2, pp. 275-295. https://doi.org/10.1108/JES-11-2019-0498

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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