Empirical Model for Credit Risk: Implications of Results from African Countries. by Charles Augustine Abuka Director, Financial Stability Department BANK OF UGANDA Prepared for the CMI Course on Macro stress testing Wednesday 21 August, 2013 KSMS, Nairobi, Kenya

Studies of Macro-financial Linkages 2

Determinants of Asset Quality Studies Relevant to Africa – Fofack [2005] – Khemraj and Pasha [forthcoming] – Babihuga [2007] estimates a model, with the share of nonperforming loans in total loans as a function of macroeconomic variables including: unemployment, changes in inflation, real interest rates in previous years, the business cycle, exchange rates. 3

Determinants of Asset Quality The model controlled for the quality of banking supervision and other industry characteristics including income and financial depth. The basic specification was as follows: npli,t = α1 + β1bcyclei,t + β2inflationi,t + β3reeri,t + β4int_ri,t + β5unratei,t + β6t_trade +β7bcpi,t +β8bcp*cyclei,t + εi,t (3) for panel data i = 1,...., 96 and t = 1998,....,

Determinants of Asset Quality The choice of explanatory macroeconomic variables in the model reflects the evidence provided by the large empirical literature showing that a collapse in borrowers’ credit worthiness and the subsequent deterioration in the value of collateral are the main transmission mechanisms of a macroeconomic shock to banks’ portfolios: – Thus during periods of financial distress, credit quality emerges as an important source of vulnerability and non- performing loans deteriorate quickly before bank failures. – Therefore in order to assess the impact of macroeconomic conditions on asset quality, we focus on macroeconomic variables that potentially affect borrowers’ credit worthiness. 5

Determinants of Asset Quality 6

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– The coefficient on the business cycle variable is negative, significant and robust across all specifications, implying that economic booms are associated with improvements in asset quality. – Higher inflation, interest rates and unemployment worsen asset quality (increasing NPLs). – An improvement in the terms of trade index appears to have a positive effect on asset quality. 8

Determinants of Asset Quality – A real depreciation in the exchange rate appears to have a negative effect on asset quality. However, the overall impact for exporters and producers of tradable goods, to which the banking system is exposed, will depend on which effect dominates, – The quality of regulatory supervision has a positive impact on asset quality. This finding is consistent with Podpiera (2004). 9

Possible variables for investigation Explanatory Variables – The ratio of nonperforming to total loans for individual banks; – The ratio of loan loss reserves to total loans. 10

Possible variables for investigation Macro Variables – the annual growth in real GDP at time, – the real interest rates (measured as the difference between the weighted average lending rate and the annual inflation rate), – the real effective exchange rate, – the annual inflation rate, 11

Possible variables for investigation Macroeconomic variables – Unemployment rate, – Annual growth rate of M2, – GDP per capita, – Output gap or business cycle component of GDP – Terms of trade – Investment to GDP ratio – Real estate price inflation 12

Possible variables for investigation Macroeconomic Variables – Growth of real fixed investment – Growth of real consumption – Growth in exports and imports – Industrial production – Oil prices – Nominal interest rates – Nominal exchange rates 13

The NPL Equation Estimation Bank Specific Variables – Size of the ratio of the relative market share of each bank’s assets that capture the size of the institution, – the loans to total asset ratio for bank, – represents the growth in loans for each bank – the real interest rates (measured as the difference between the weighted average lending rate of each bank and the annual inflation rate), 14

The NPL Equation Estimation Bank Specific Variables – Profit margins, – efficiency, – terms of credit (size, maturity, interest rate), – risk profile (proxied by capital/assets ratio), – Loan to asset ratio, – Equity to asset ratio, – Cost to income ratio, – Liquidity ratio, 15

R EFERENCES 16

R EFERENCES Baltagi B.D., 2001 Econometric Analysis of Panel Data, John Willwy and Sons, LTD. Eviews 6 and 7 Users Guides Green, W.H., 2005 Econometric Analysis, Prentice Hall. Wooldridge, J.M, 2002 Econometric Analysis of Cross Section and Panel Data, The MIT Press. 17