nonperforming loans may contribute to economic downturns, possibly through the savinginvestment link channels and/or the fiscal channel.

At the microeconomic level, measures of profitability (net interest margins and returns on assets) play a key role in explaining the causal link between nonperforming loans and banking sector variables. In particular, net interest margin is significant across the sub-panel of CFA and non-CFA countries, and Granger-causes nonperforming loans at one and in some cases up to two lags (see Tables 5a and 5b in Annex). This variable is significant at 1 percent level. Similarly, the variable returns on assets Granger-causes nonperforming loans in most countries. In Kenya where the null hypothesis of non causality is rejected at 1 percent level, it has a relatively large _F-Statistics_ .

Other key microeconomic determinants of nonperforming loans include “equity over total liquid assets” and interbank loans over total assets. These variables may also be viewed as proxy for moral hazard, to the extent that the recourse to highly-priced short-term loans may be an indication of erosion of bank capital and/or a reflection of a relatively low equity base. Indeed, in spite of their prohibitively high costs, interbank loans are heavily used during most of the crisis period. This variable is shown to Granger-cause nonperforming loans in a number of countries, including Botswana, Cameroon, Côte d’Ivoire, Mali and South Africa. The unidirectional causality of interbank loans suggests that the recourse to short-term financing at a high price might indeed have exacerbated the scope of banking crisis by contributing to a rapid accumulation of nonperforming loans, through the moral hazard channel that extended the operations of problems banks, and hence, the cost of the crisis.<sup>35</sup> The next section investigates the predictability of these variables in explaining the dynamics of nonperforming loans using pseudo-panel estimation techniques.

# **IV. Econometric Estimation and Prediction Model**

The estimation is based on pseudo-panel (unbalanced panel) models. A panel is said to be unbalanced when observations on different groups do not cover the same time period. Indeed, the time series provided by Bankscope is not uniform across the subset of countries. The series is shorter for a number of countries, and when the length of the data covers the entire reference period for most countries, missing values are observed in a few cases. This configuration has motivated the use of pseudo-panel models, which are especially suitable for econometric analysis in presence of missing values. There are several specifications for these models; this study uses the specification represented by equation (3) below.

Where _wit_ is the dependent variable, representing nonperforming loans expressed as a proportion of loan loss provisions. The variable _Vit_ is a non-constant vector of _i_ regressors, for _i_ = ,2,1 L _N_ . Each cross-section unit is observed for a period _t_ , with _t_ = ,2,1 L , _T_ , and varying across countries. The study focuses on fixed effect estimation, which allows the

> 35 Indeed an extension of operations carried out by troubled banks and financial institutions through access to shortterm financing can only exacerbate the crisis, especially if not accompanied by a systematic operational restructuring of banks coupled with portfolios restructuring.

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