Benedicta Marzinotto

ALT Image of Figure 2: Distribution of the Number of Tight Financial Constraints. This is a bar chart showing the distribution of the number of tight financial constraints across firms from 1990 to 2020. The x-axis displays the number of constraints from 0 to 8, while the y-axis shows the fraction of firms, ranging from 0 to approximately 0.3. The highest fraction (approximately 0.3) is observed for firms with 1 tight constraint, followed by firms with 2 constraints (approximately 0.28) and firms with 0 constraints (approximately 0.19). The fraction decreases as the number of constraints increases, with approximately 0.13 for 3 constraints, 0.05 for 4 constraints, and 0.02 for 5 constraints. Very few firms (less than 0.01) have 6 constraints, and apparently none have 7 or 8 constraints.

ALT Image of Figure 6: Relationship between Number of Financial Constraints and Responsiveness to Easing and Tightening Shocks. This is a line graph showing the relationship between the number of financial constraints (x-axis, ranging from 0 to 8) and the predicted effect of monetary policy on external financing (y-axis, ranging from approximately -15 to 10). The chart displays two series with confidence intervals shown as vertical error bars: "Contractionary Shock" (red line with red error bars) and "Accommodative Shock" (blue line with blue diamonds and blue error bars). As the number of constraints increases from 0 to 8, the contractionary shock effect becomes increasingly negative, declining from around -4 to -10. Conversely, the accommodative shock effect becomes increasingly positive, rising from around -3 to approximately +3. The confidence intervals (error bars) for both series widen as the number of constraints increases, indicating greater uncertainty in the estimates at higher c