to shrink small or weakly significant regressors to zero. Because of the shrinkage that the Lasso imposes in the penalized least squares estimation, parameter estimates are intentionally biased. For this reason, once the relevant set of final regressors has been determined with the Lasso procedure, we use the Ordinary Least Squares (OLS) estimator to obtain unbiased estimates of the regression parameters that are not shrunk to 0.

# **3.2. Data**

The source of our data set is the IMF’s International Financial Statistics (IFS) database. All data is on a quarterly basis. The maximum possible sample size in the time dimension is from 1980:Q1 to 2010:Q3. The cross sectional dimension of the panel data set, i.e., the number of countries that are included, is 49.<sup>19</sup> The credit variable that we use is defined as total bank credit to the private sector, expressed in local (national) currency units. Since the scale of private sector credit can be very different across the countries, we create a credit index, with the base of the index (where the value of the index is equal to 100) being 2001:Q1. The index version of the credit variable is then log transformed before used in the analysis.

The real GDP data (GDP for short henceforth) and GDP Deflator data are taken from volume measures, and are hence also index measures with different base years. Both, GDP and the GDP Deflator are also log transformed. The lending to deposit rate spread is computed as the lending rate minus the deposit rate. We use Consumer Price Inflation (CPI) data to construct an ex-post measure of the real interest rate. This is done by computing CPI inflation as 100 times the year-on-year inflation rate, ie., as 100 _×_ (ln( _CPIit_ ) _−_ ln( _CPIit−_ 4)).<sup>20</sup> The real interest rate is then calculated as the lending rate minus yearon-year inflation. The alternative cost of borrowing variable, which captures the cost of borrowing in foreign currency, is calculated as the country specific lending rate minus the world interest rate minus the in the rate. The year-on-year change exchange exchange rate is defined as the number of local currency units per one US dollar, so that a declining value indicates an appreciation of the respective country’s currency against the US dollar. To avoid unnecessary volatility in the exchange rate series, we use quarterly averages rather than end-of-quarter values. For the US, we use (the inverse) of the Trade Weighted Exchange Index of major currencies to get a measure of the exchange rate impact on credit.<sup>21</sup> The world lending rate is approximated by the US dollar lending rate.

> 19We do not provide a separate table that lists the countries included in the panel data set to conserve space, nonetheless, the _x−_ axis labels of Figure 2 show explicitly which countries are included in the panel. 20We use year-on-year values, rather than annualised quarter-on-quarter values, to reduce the volatility of

> 21This series was obtained from the FRED2 database of the Federal Reserve Bank of St. Louise. The series code is DTWEXM. The series was also aggregated to the quarterly average. We use the inverse to be consistent with the definition of a decreasing value implying an appreciation of the domestic currency for non-US countries in the cross-section.

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