We propose a new model in which relationship-specific effects or shocks are identified in a bipartite network under mild covariance restrictions, generalizing the influential Abowd et al. (1999) framework. For example, separate demand shocks are identified for each bank from which a firm borrows. We show how previous approaches break down when confronted with such heterogeneity, while our novel identification strategy yields a simple estimator that is consistent and asymptotically normal, under weaker network density assumptions than previous approaches.

Abhik Bhatt, Anthony M. Diercks, Benjamin Eyal, and Arsenios SkaperdasThis paper uses a natural experiment to measure the causal effect of an expected debt-financed fiscal stimulus on interest rates. We find that a 1 percentage point increase in the expected US debt-to-GDP ratio leads to an increase of about 1-2 basis points in the longer-run neutral rate (r∗) and of about 2–3 basis points in the 10-year Treasury term premium.

Statistical Notices update the definitions and guidance contained in the Banking Statistics Yellow Folder

This paper studies the employment effects of carbon pricing under the European Union’s Emissions Trading System (EU-ETS). I refer to standard methods from the literature to define and measure the environmental properties of jobs along two dimensions: how “green” a job is, and how polluting it is. I then leverage a series of shocks to EU-ETS prices to estimate their dynamic impacts on employment. The panel local projections estimates reveal that an exogenous 1% increase in EU-ETS prices leads to a roughly 0.2% decline in employment after one and a half years.