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The authors thank Ratna Sahay, country economists from the Middle East and Central Asia Department of the IMF, and participants in the MCM/RES Surveillance Meeting on June 14th, 2010 for their insightful and very helpful comments on earlier drafts.
Egypt, Jordan, Morocco, Saudi Arabia, Sudan, and Tunisia.
Basher, Dalla and Hesse (2010) examine the prospects and importance of local currency bond markets in the GCC.
A series of interviews with leading financial sector analysts in the MENA region, conducted during February-March 2010, revealed divergent views on the future of name lending in the region. While some believed that it is destined to disappear going forward, most saw its slowdown as the more likely scenario, and that banking practices in the region were likely to undergo a structural change in the coming years. See IMF (2010) for a summary of the interviews.
The latest data obtained were for May 2009 (Sudan), June 2009 (Iran), November 2009 (Djibouti), December 2009 (Iraq and Yemen), January 2010 (Kuwait and Tunisia), February 2010 (Oman, Algeria, and Lebanon), March 2010 (Bahrain, the UAE, Libya, Egypt, Morocco, Pakistan, and Syria), and April 2010 (Qatar, Saudi Arabia, and Jordan).
Note that each of the net claims terms can be either positive or negative. Based on IFS categories, net claims on the NFPS were defined as claims on the NFPS minus government deposits; those on the central bank were defined as reserves and other claims on the central bank minus credit from the central bank; and those on the rest of the world were defined as foreign assets minus foreign liabilities. Finally, all other items not included in net claims or in deposits were grouped in a residual category, “capital and others”.
The interpretation of capital and others is not as straightforward as that of other categories, as it includes residual items.
The Hausman specification test indicates that the fixed effects estimator tends to be preferred over the random effects models. We did not estimate dynamic panel models using GMM for this study given the large heterogeneity of the banks in the sample.
At the time of the study, balance sheet and income statement information was not yet available for the majority of the banks for 2009.
Consolidated balance sheet and income statement data was used when available, but when consolidated data was not available for a bank, unconsolidated data was used instead. In addition, some obvious outliers were eliminated.
A more direct measure of loan quality is the nonperforming loan ratio. However, this variable was not available for a number of banks, and therefore it was not used.
Ideally, a more direct measure of loan quality, such as the ratio of nonperforming loans, would have been used. However, it was not available for a large number of bank-years within this sample, and would have greatly reduced the number of usable observations.
As robustness tests (not shown in Table 2), we also estimated quantile regressions at the 25th and 75th percentile of credit growth. As expected, for banks with higher lending growth at the 75th percentile, bank fundamentals such as deposit and net margin growth as well as capitalization were the main drivers. Overall, the results in the quantile regressions were broadly consistent with the baseline fixed effects regressions.