Table D.1.
Quantile regression: Effect of congestion on different quantiles of investment rate.
| (1) |
(2) |
(3) |
|
|---|---|---|---|
| Percentile 5D | Percentile 75 | Percentile 90 | |
| Congestion declarative | −0.0018∗∗∗ (0.0002) |
−0.0104∗∗∗ (0.0015) |
−0.0397∗∗∗ (0.0044) |
| Cash flow | 0.0038∗∗∗ (0.0001) |
0.0512∗∗∗ (0.0013) |
0.1423∗∗∗ (0.0035) |
| EBIT/Assets | 0.0121∗∗∗ (0.0002) |
0.0916∗∗∗ (0.0011) |
0.1650∗∗∗ (0.0028) |
| Debt Burden | −0.0005∗∗∗ (0.0000) |
−0.0142∗∗∗ (0.0002) |
−0.0349∗∗∗ (0.0007) |
| Debt/Assets | 0.0000 (0.0000) |
0.0042∗∗∗ (0.0004) |
0.0064∗∗∗ (0.0014) |
| Sales growth |
0.0034∗∗∗ (0.0001) |
0.0484∗∗∗ (0.0007) |
0.0923∗∗∗ (0.0014) |
| Year FE | YES | YES | YES |
| Firm FE | NO | NO | NO |
| Observations | 3,523,890 | 3,523,890 | 3,523,890 |
| Pseudo R-squared | 0.0232 | 0.0338 | 0.0344 |
Standard errors in parentheses.
∗∗∗p < 0.01, ∗∗p < 0.05, ∗p < 0.1.
Note: This table reports the correlation between judicial inefficacy and different percentiles of the investment rate distribution, based on a quantile regression. The dependent variable is the investment rate. We account for year and province fixed effects. Firm-level controls include cash flows, EBIT/assets, debt burden, Debt/assets, and sales growth. Province-level controls include number of lawyers, the number courts over the total population, population growth, credit over GDP and unemployment rate. In column 1 we study the correlation between judicial inefficacy and the median investment rate. In column 2 we focus on the effect of congestion on the 75 percentile of the investment rate while column 3 considers the 90 percentile. All variables are lagged by one year. The considered sample covers the period 2002–2016.