Espinoza, Raphael, and A. Prasad, 2010, “Nonperforming Loans in the GCC Banking System and their Macroeconomic Effects,” IMF Working Paper 10/224, International Monetary Fund, Washington.
International Monetary Fund (IMF), 2014, “Assessing Concentration Risks in GCC Banks,” Prepared for the Annual Meeting of Ministers of Finance and Central Bank Governors in Gulf Cooperation Council, International Monetary Fund, Washington.
International Monetary Fund (IMF), 2015, “Assessing the Importance of Oil and Interest Rate Spillovers for Saudi Arabia.” Saudi Arabia Article IV Consultation Selected Issues, IMF country Report, Washington.
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Prepared by Ken Miyajima.
Based on the publicly available bank-by-bank data used in this note.
The NPL ratio exhibits a strong autocorrelation and the data’s time series dimension is short relative to its cross-sectional dimension. This argues for a GMM estimation approach rather than a fixed effects approach–the latter suffers from a downward Nickell bias in such circumstances. Indeed, the coefficient on the autoregressive NPL ratio is smaller when estimated using a fixed effects approach. This would make the trajectory of projected NPL ratios higher compared to the results reported in this note.
NPL ratios are introduced after a logit transformation. Fisher-type panel unit root tests reject the null hypothesis that all panels contain unit roots. Time dummy variables were introduced in the regressions to control for events other than oil price developments that potentially led to an increase in NPL ratios around the time of the global financial crisis. In particular, two large family-owned conglomerates defaulted on loans in 2009 due to events unrelated to the decline in oil prices.
Real oil prices used for regression and projection are converted to nominal prices for discussion. Using the simple average of prices of U.K. Brent. Dubai Fatch, and West Texas Intermediate crude oil.
The range is estimated considering only the coefficients on the autoregressive term which has a large impact on the projected path of NPL ratios. Other sources of uncertainty include the estimated coefficients Following Espinoza and Prasad (2010), bank by bank variables are considered as endogenous and aggregate variables predetermined in this analysis.