Tommaso Monacelli.
(Universitá Bocconi).
Bewley Banks (co-authored with R. Jamilov).
Tag: Macroeconomics
Bewley Banks
Inequality of Fear and Self Quarantine: Is There a Trade-off between GDP and Public Health?
Sang Yoon (Tim) Lee.
(Queen Mary University of London).
Inequality of Fear and Self Quarantine: Is There a Trade-off between GDP and Public Health?.
Virtual seminar – Enter the session through this link.
Sang Yoon (Tim) Lee.
(Queen Mary University of London).
Inequality of Fear and Self Quarantine: Is There a Trade-off between GDP and Public Health?.
Virtual seminar – Enter the session through this link.
Fiscal Paradoxes in a Liquidity Trap
Francisco Buera
(Washington University)
“Fiscal Paradoxes in a Liquidity Trap”
Virtual seminar – Join the session here
Francisco Buera
(Washington University)
“Fiscal Paradoxes in a Liquidity Trap”
Virtual seminar – Join the session here
Redrawing the Map of Global Capital Flows: The Role of Cross-Border Financing and Tax Havens
Matteo Maggiori.
(Stanford Graduate School of Business).
“Redrawing the Map of Global Capital Flows: The Role of Cross-Border Financing and Tax Havens” (co-authored with A. Coppola, B. Neiman, J. Schreger).
Virtual seminar – Join the session through this link.
Matteo Maggiori.
(Stanford Graduate School of Business).
“Redrawing the Map of Global Capital Flows: The Role of Cross-Border Financing and Tax Havens” (co-authored with A. Coppola, B. Neiman, J. Schreger).
Virtual seminar – Join the session through this link.
An economic model of the Covid-19 pandemic with young and old agents: Behavior, testing and policies
Philipp Kircher.
(European University Institute).
An economic model of the Covid-19 pandemic with young and old agents: Behavior, testing and policies.
Virtual seminar – Join the session through this link.
Philipp Kircher.
(European University Institute).
An economic model of the Covid-19 pandemic with young and old agents: Behavior, testing and policies.
Virtual seminar – Join the session through this link.
The Job Ladder: Inflation vs. Reallocation
Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach
Andreas Gulyas.
(University of Mannheim).
Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach.
Abstract:
We document the sources behind earnings losses after job displacement adapting the generalized random forest due to Athey et al. (2019). Using administrative data from Austria over three decades, we show that displaced workers face large and persistent earnings losses. We identify substantial heterogeneity in losses across workers. A quarter of workers face cumulative 11-year losses higher than 2 times their pre-displacement annual income, while another quarter experiences losses less than 1.1 times their income. The most vulnerable are older high-income workers employed at well-paying firms in the manufacturing sector. Our methodology allows us to consider many competing theories of earnings losses prominently discussed in the literature. The two most important factors are the displacement firm’s wage premia and the availability of well paying jobs in the local labor market. Our overall findings provide evidence that earnings losses can be understood by mean reversion in firm rents and losses in match quality, rather than by a destruction of firm-specific human capital.
Attendance confirmation.
Andreas Gulyas.
(University of Mannheim).
Understanding the Sources of Earnings Losses After Job Displacement: A Machine-Learning Approach.
Abstract:
We document the sources behind earnings losses after job displacement adapting the generalized random forest due to Athey et al. (2019). Using administrative data from Austria over three decades, we show that displaced workers face large and persistent earnings losses. We identify substantial heterogeneity in losses across workers. A quarter of workers face cumulative 11-year losses higher than 2 times their pre-displacement annual income, while another quarter experiences losses less than 1.1 times their income. The most vulnerable are older high-income workers employed at well-paying firms in the manufacturing sector. Our methodology allows us to consider many competing theories of earnings losses prominently discussed in the literature. The two most important factors are the displacement firm’s wage premia and the availability of well paying jobs in the local labor market. Our overall findings provide evidence that earnings losses can be understood by mean reversion in firm rents and losses in match quality, rather than by a destruction of firm-specific human capital.
Attendance confirmation.
Stock Market Participation, Inequality, and Monetary Policy
Vincent Sterk.
(UCL).
Stock Market Participation, Inequality, and Monetary Policy.
Attendance confirmation.
Vincent Sterk.
(UCL).
Stock Market Participation, Inequality, and Monetary Policy.
Attendance confirmation.
Bad jobs and low inflation
Leonardo Melosi.
(Federal Reserve Bank of Chicago).
Bad jobs and low inflation.
Attendance confirmation.
Leonardo Melosi.
(Federal Reserve Bank of Chicago).
Bad jobs and low inflation.
Attendance confirmation.
Healthy Dietary Choices in Distorted Food Environments
Roberto Pancrazi.
(University of Warwick).
Healthy Dietary Choices in Distorted Food Environments.
We analyze how distortions in the food market limit the achievement of a healthy diet. Using Nielsen data we document a novel pattern on the relationship between healthy diet and income. We then build and estimate a tractable general equilibrium model in which difference in diet across income can be determined by preferences and/or by economic factors. We estimate the model so that it is able to account for the relevant stylized facts and we use as laboratory to study which policies could enhance healthy diets across different income levels.
Attendance confirmation.
Roberto Pancrazi.
(University of Warwick).
Healthy Dietary Choices in Distorted Food Environments.
We analyze how distortions in the food market limit the achievement of a healthy diet. Using Nielsen data we document a novel pattern on the relationship between healthy diet and income. We then build and estimate a tractable general equilibrium model in which difference in diet across income can be determined by preferences and/or by economic factors. We estimate the model so that it is able to account for the relevant stylized facts and we use as laboratory to study which policies could enhance healthy diets across different income levels.