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Staff working papers

Staff working papers provide a forum for staff to publish work-in-progress research intended for journal publication.

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1284 result(s)

Should Banks Be Worried About Dividend Restrictions?

Staff Working Paper 2023-49 Josef Schroth
A regulator would want to restrict dividends to force banks to rebuild capital during a crisis. But such a policy is not time-consistent. A time-consistent policy would let banks gradually rebuild capital and pay dividends even when their equity remains below pre-crisis levels.

The Macroeconomic Effects of Debt Relief Policies During Recessions

Staff Working Paper 2023-48 Soyoung Lee
A large-scale reduction in mortgage principal can strengthen a recovery, support house prices and lower foreclosures. The nature of the intervention shapes its impact, which rests on how resources are redistributed across households. The availability of bankruptcy on unsecured debt changes the response to large-scale mortgage relief by reducing precautionary savings.

Labour Supply and Firm Size

Staff Working Paper 2023-47 Lin Shao, Faisal Sohail, Emircan Yurdagul
This paper documents a systematic pattern of how wages, hours and their relationship vary across firms of different sizes. Using a model with heterogeneous firms and workers, we show how the interplay between wages, hours and firm size affect worker sorting and inequality.
Content Type(s): Staff research, Staff working papers Topic(s): Firm dynamics, Labour markets JEL Code(s): E, E2, E24, J, J2, J3, J31

International Economic Sanctions and Third-Country Effects

Staff Working Paper 2023-46 Fabio Ghironi, Daisoon Kim, Galip Kemal Ozhan
We study the transmission and third-country effects of international sanctions. A sanctioned country’s losses are mitigated, and the sanctioning country’s losses amplified, if a third country does not join the sanctions, but the third country benefits from not joining.

Combining Large Numbers of Density Predictions with Bayesian Predictive Synthesis

Staff Working Paper 2023-45 Tony Chernis
I show how to combine large numbers of forecasts using several approaches within the framework of a Bayesian predictive synthesis. I find techniques that choose and combine a handful of forecasts, known as global-local shrinkage priors, perform best.
Content Type(s): Staff research, Staff working papers Topic(s): Econometric and statistical methods JEL Code(s): C, C1, C11, C5, C52, C53, E, E3, E37

A Behavioral New Keynesian Model of a Small Open Economy Under Limited Foresight

Staff Working Paper 2023-44 Seunghoon Na, Yinxi Xie
This paper studies exchange rate dynamics by incorporating bounded rationality, that is, limited foresight, in a small open-economy model. This behavior of limited foresight helps explain several observations and puzzles in the data of exchange rate movements.

Competition for Exclusivity and Customer Lock-in: Evidence from Copyright Enforcement in China

Staff Working Paper 2023-43 Youming Liu
This paper studies the music streaming industry and argues that having exclusive rights granted by copyright law drives firms to offer exclusive content to lock in customers. I employ theoretical and descriptive empirical analysis, along with a dynamic structural model, to support the argument and explore policies for improving competition.

Understanding DeFi Through the Lens of a Production-Network Model

Staff Working Paper 2023-42 Jonathan Chiu, Thorsten Koeppl, Hanna Yu, Shengxing Zhang
We develop a production-network model to capture how decentralized finance (DeFi) has evolved across different sectors of financial services. The model allows us to measure the value added by different DeFi sectors and to study how the connections across the sectors influence token prices.

Flagship Entry in Online Marketplaces

Staff Working Paper 2023-41 Ginger Zhe Jin, Zhentong Lu, Xiaolu Zhou, Lu Fang
In this paper, we empirically study how flagship entry in an online marketplace affects consumers, the platform, and various sellers on the platform. We find flagship entry may benefit consumers by expanding the choice set, by intensifying price competition within the entry brand, and by improving consumer perception for parts of the platform.

Generalized Autoregressive Gamma Processes

Staff Working Paper 2023-40 Bruno Feunou
We introduce generalized autoregressive gamma (GARG) processes, a class of autoregressive and moving-average processes in which each conditional moment dynamic is driven by a different and identifiable moving average of the variable of interest. We show that using GARG processes reduces pricing errors by substantially more than using existing autoregressive gamma processes does.
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