Anna Rogantini Picco*, Russell Cooper**

Thematic seminars
Macro and labor market seminar

Anna Rogantini Picco*, Russell Cooper**

Sveriges Riksbank*, European University Institute**
Dynamic Credit Constraints: Theory and Evidence from Credit Lines*
Determining Gender Differences in Education and Labor Market Outcomes**
Joint with
Niklas Amberg, Tor Jacobson, Vincenzo Quadrini*
Carla Varona Cervantes**

IBD Salle 17

Îlot Bernard du Bois - Salle 17

5-9 boulevard Maurice Bourdet
13001 Marseille

Friday, May 24 2024| 11:30am to 2:30pm

Marco Fongoni: marco.fongoni[at]
Francesco Gaudio: francesco-saverio.gaudio[at]


*We use a comprehensive Swedish credit register data to document that firms throughout the size distribution have access to fairly large and reasonably priced credit lines. However, they borrow relatively little from the credit lines. We also find that credit lines utilization is negatively related to real and financial uncertainty, suggesting that the observed low utilization is the result of tight `dynamic' credit constraints, rather than unneeded funds. To understand some of the factors that affect the financial decision of firms and, especially, the low utilization of credit, we use a simple theoretical model we estimate for each firm. The estimation allows us to derive measures of borrowing capacity for each firm. We find that the estimated credit capacities are highly correlated with direct empirical measures of credit limits based committed amounts of credit lines. Through counterfactual simulations we also find that (future) financial uncertainty is more important than (future) real uncertainty for the low utilization of credit.

**This paper studies gender differences in educational attainment and labor market outcomes. Across 21 OECD countries, though men are paid more than women, the college attainment rates and college premia are (mostly) higher for women. This paper explains these patterns through the lens of a dynamic choice model of education and labor market outcomes. Using the estimated model, we decompose the observed gender gaps through a series of counterfactual exercises. One finding is that these gaps are driven mainly by gender differences in the average compensation at non-college jobs. The estimated lower compensation for non-college women generates for them larger college premia and higher incentives to attend college relative to men. A second finding is that distributions matter: the observed gender wage gap for college workers can be created by differences in the gender specific distributions across signals of ability rather than wage differences across genders given a signal.