Common use of Augmented Sample Clause in Contracts

Augmented Sample. To further investigate the issue of missing firm characteristics, we match loan contracts to BelFirst, a dataset containing yearly balance and profit/loss statements of more than 250,000 Belgian corporations. Conservatively matching by tax identification numbers, we track 1,008 firms.69 Quite a few Sole Proprietorships are not listed in BelFirst. Nevertheless, the means of most loan and firm characteristics of the Augmented Sample (see Table 9) are surprisingly similar to the means for the entire dataset. Most importantly, the means of both distance measures and the loan rate are not significantly different between the Full and the newly constructed Augmented Samples. The differences in the other variables constitute an additional powerful robustness check on the empirical work we have reported so far. We study accounting data from the year preceding the origination date of the loan contract. To evaluate firm risk and funding needs, we compare means of firm Assets and the ratios of Earnings, Short-Term Debt, Net Trade Credit, and Intangible Assets over Assets between the two relative distance groups.70 The means are displayed in the last two columns in Table 9. More distant firms are somewhat larger, more intangible, and obtain larger or longer term loans than closer firms. Otherwise, more distant and closer firms are seemingly similar in profitability and debt structure. Loan Size / Assets does not significantly differ across groups. If anything, more distant firms seem less credit constrained once they obtain a loan. We also track 936 firms through time, and use the Earnings in 2 Years / Assets in 2 Years (after the loan origination year) and Assets in 2 Years / Assets as admittedly ad-hoc measures of expected future profitability and growth. Distant firms outperform close firms on average - both in earnings and asset growth, but the differences are not significant and the measures are fraught with survivorship biases (we cannot establish for sure why BelFirst ceased reporting the records of some firms). Next, we introduce the new firm characteristics in a few basic specifications in Table 12. Model I features the Age of the firm, which we collected separately, while Models II and III include the newly constructed accounting measures. Despite the endogeneity issue, we also add Earnings in 2 Years / Assets in 2 Years and Assets in 2 Years / Assets in Models IV and V. All specifications further incorporate three Firm Size dummies, eight Postal Area dummies, two Industry Sector dummies capturing respectively Agriculture / Fishing / Mining and Manufacturing (collinearity precludes employing the Industry dummies), the Interest Rates Variables, and an Intercept. We find that smaller and more indebted firms and firms taking out smaller loans (either absolute or relative to its assets size) end up paying higher loan rates. The distance coefficients increase in absolute value to more than 20. But these coefficients are estimated less precisely and remain significant only at a 5% level in all but one model (the standard deviations on the coefficients increase to more than 10). Again, we cannot reject the equality restriction on our distance measures at a 1%-level of significance. Excluding these newly introduced variables in the just reported specifications does not alter the estimated parameters of the other variables. Adding firm Age to Models II to V further reduces the number of observations (to 936 and 792, respectively) and precision of the estimates, but does not qualitatively affect the results. To conclude, more distant firms are somewhat larger and take out loans that are significantly larger in absolute, though not in relative size. Otherwise, distant and close firms do not differ significantly. Controlling for the additional firm characteristics does not affect the distance – loan rate correspondence. We contend that these empirical results are fully in line with price discrimination on the basis of transportation costs. Remember that our estimates of the distance coefficients by loan size imply almost the same imputed traveling cost per minute. These estimates and the results in this section indicate that borrowers, because of the fixed cost nature of traveling, will consider driving to more distant lenders when seeking larger loans. On average, somewhat larger firms seek and obtain these larger amounts of funding.71