fatemeh abdolshah; Saeed Moshiri
Abstract
Because of prevalence of non-performing loans in Iranian banking sector, it is important to estimate the default probability of borrowers in order to effectively manage credit risk. This paper conducts stress testing for default probabilities in banking industry of Iran. We apply the credit portfolio ...
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Because of prevalence of non-performing loans in Iranian banking sector, it is important to estimate the default probability of borrowers in order to effectively manage credit risk. This paper conducts stress testing for default probabilities in banking industry of Iran. We apply the credit portfolio approach model developed by Wilson (1997) and analyze the impacts of various macroeconomic shocks on default rates of banks. In the constructed model, we first estimate the effects of macroeconomics variables on default rate. Then the dynamic relationship between selected macroeconomics variables is estimated by a VAR model. Residuals obtained in the two previous steps were used to construct the covariance matrix for system of equations. Finally, using the Monte-Carlo method, a path of default probabilities is simulated in a one-year horizon under different scenarios. We compare default rates under different stress scenarios with baseline scenario to identify the effects of different shocks. The results of simulation show that unemployment rate shock has been the most harmful factor for default probabilities, followed by exchange rates shock. A shock to GDP growth also affects default rates significantly. Inflation shock generates the least important effect on default rates, consistent with the insignificant coefficient of inflation rate in the estimated default probability equation. A simultaneous shock to all macroeconomic variables has higher impact on the default rates in lower tails than upper tails. The results also show the effects of shocks decrease with the passage of time.
abolfazl ghiasvand; fatemeh abdolshah
Volume 15, Issue 59 , January 2016, , Pages 161-187
Abstract
In this paper, resilience of an economic system is measured by an overall index, based on the Borman et al. index, for the period of 1996-2013. The results are then compared with Briguglio index. To measure the final index, the first step is to make variables have a similar direction. The second step ...
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In this paper, resilience of an economic system is measured by an overall index, based on the Borman et al. index, for the period of 1996-2013. The results are then compared with Briguglio index. To measure the final index, the first step is to make variables have a similar direction. The second step is normalization of variables that their values reside between zero and one. In the last step we calculate the weighted average of variables. The value of Resilience Index is between zero and one. The closer the index to zero, the less resilient will be the economic system. In versus, The closer the index to one, the more resilient the economy. The results show that resilience was low during whole the period under consideration. Resilience reached its peak in 2001, because the budget deficit and inflation rate were reduced and governance has been improved. Then the trend started to decline. The Resilience index reached its minimum level after year 2007. According to the indeces, the main reasons were governance and market efficiency indeces.
