Tag: A&E seminar
A Correlated Random Coefficient Panel Model with Time – Varying Endogeneity
The Effects of Gender and Parental Occupation in the Apprenticeship Market: An Experimental Evaluation
Skill and Value Creation in the Mutual Fund Industry
Olivier Scaillet.
(Geneva Finance Research Institute).
Skill and Value Creation in the Mutual Fund Industry.
Attendance confirmation.
Olivier Scaillet.
(Geneva Finance Research Institute).
Skill and Value Creation in the Mutual Fund Industry.
Attendance confirmation.
A Revealed-Preference Approach to Measuring Information Frictions in Migration Decisions
Eduardo Morales.
(Princeton University).
A Revealed-Preference Approach to Measuring Information Frictions in Migration Decisions.
Abstract
“Labor demand shocks differ widely across regions within countries. Yet, migration patterns often do not respond to these regional shocks. Are workers’ limited migration responses due to lack of information about the potential net gains from regional migration? To answer this question, we analyze the mobility decisions of all formally employed workers in Brazil over 15 years. First, using a reduced-form approach, we document heterogeneous delay in reaction to positive local labor demand shocks: workers living in more distant regions and in regions with a lower degree of internet penetration tend to react more slowly to positive local labor demand shocks happening in other regions within the same country. Second, using a structural approach, we use model-based moment conditions and tests of overidentifying restrictions to test for the content of migrants’ information sets. Our preliminary results indicate that the precision of the information that workers have about labor market conditions in regions other than their region of residence decays strongly with distance. Agents located in regions with a better access to internet also appear to have more precise information.”
Attendance confirmation.
Eduardo Morales.
(Princeton University).
A Revealed-Preference Approach to Measuring Information Frictions in Migration Decisions.
Abstract
“Labor demand shocks differ widely across regions within countries. Yet, migration patterns often do not respond to these regional shocks. Are workers’ limited migration responses due to lack of information about the potential net gains from regional migration? To answer this question, we analyze the mobility decisions of all formally employed workers in Brazil over 15 years. First, using a reduced-form approach, we document heterogeneous delay in reaction to positive local labor demand shocks: workers living in more distant regions and in regions with a lower degree of internet penetration tend to react more slowly to positive local labor demand shocks happening in other regions within the same country. Second, using a structural approach, we use model-based moment conditions and tests of overidentifying restrictions to test for the content of migrants’ information sets. Our preliminary results indicate that the precision of the information that workers have about labor market conditions in regions other than their region of residence decays strongly with distance. Agents located in regions with a better access to internet also appear to have more precise information.”
Attendance confirmation.
General Equilibrium Indirect Effects in Space: Theory and Measurement
Costas Arkolakis.
(Yale University).
General Equilibrium Indirect Effects in Space: Theory and Measurement.
Attendance confirmation.
Costas Arkolakis.
(Yale University).
General Equilibrium Indirect Effects in Space: Theory and Measurement.
Attendance confirmation.
Does Economics Make You Sexist?
Cronyism in State Violence: Evidence from Labor Repression During Argentina’s Last Dictatorship
Esteban Klor.
(The Hebrew University of Jerusalem).
Cronyism in State Violence: Evidence from Labor Repression During Argentina’s Last Dictatorship.
Attendance confirmation.
Esteban Klor.
(The Hebrew University of Jerusalem).
Cronyism in State Violence: Evidence from Labor Repression During Argentina’s Last Dictatorship.
Attendance confirmation.
Functional Sequential Treatment Allocation
Anders Kock.
(University of Oxford).
Functional Sequential Treatment Allocation.
Attendance confirmation.
Anders Kock.
(University of Oxford).
Functional Sequential Treatment Allocation.
Attendance confirmation.
Distribution Regression with Sample Selection, with an Application to Wage Decompositions in the UK
Ivan Fernandez-Val.
(Boston University).
Distribution Regression with Sample Selection, with an Application to Wage Decompositions in the UK.
Attendance confirmation.
Ivan Fernandez-Val.
(Boston University).
Distribution Regression with Sample Selection, with an Application to Wage Decompositions in the UK.
Attendance confirmation.
Imperfect Competition, Compensating Differentials and Rent Sharing in the U.S. Labor Market
Magne Mogstad.
(University of Chicago).
Imperfect Competition, Compensating Differentials and Rent Sharing in the U.S. Labor Market.
Abstract: The primary goal of our paper is to quantify the importance of imperfect competition in the U.S. labor market by estimating the size of rents earned by American firms and workers from ongoing employment relationships. To this end, we construct a matched employer-employee panel data set by combining the universe of U.S. business and worker tax records for the period 2001-2015. Using this panel data, we describe several important features of the U.S. labor market, including the size of firm-specific wage premiums, the sorting of workers to firms, the production complementarities between high ability workers and productive firms, and the pass-through of firm and market shocks to workers’ wages. Guided by these empirical results, we develop, identify and estimate an equilibrium model of the labor market with two-sided heterogeneity where workers view firms as imperfect substitutes because of heterogeneous preferences over non-wage job characteristics. The model allows us to draw inference about imperfect competition, compensating differentials and rent sharing. We also use the model to quantify the relevance of non-wage job characteristics and imperfect competition for inequality and tax policy, to assess the economic determinants of worker sorting, and to offer a unifying explanation of key empirical features of the U.S. labor market.
Attendance confirmation.
Magne Mogstad.
(University of Chicago).
Imperfect Competition, Compensating Differentials and Rent Sharing in the U.S. Labor Market.
Abstract: The primary goal of our paper is to quantify the importance of imperfect competition in the U.S. labor market by estimating the size of rents earned by American firms and workers from ongoing employment relationships. To this end, we construct a matched employer-employee panel data set by combining the universe of U.S. business and worker tax records for the period 2001-2015. Using this panel data, we describe several important features of the U.S. labor market, including the size of firm-specific wage premiums, the sorting of workers to firms, the production complementarities between high ability workers and productive firms, and the pass-through of firm and market shocks to workers’ wages. Guided by these empirical results, we develop, identify and estimate an equilibrium model of the labor market with two-sided heterogeneity where workers view firms as imperfect substitutes because of heterogeneous preferences over non-wage job characteristics. The model allows us to draw inference about imperfect competition, compensating differentials and rent sharing. We also use the model to quantify the relevance of non-wage job characteristics and imperfect competition for inequality and tax policy, to assess the economic determinants of worker sorting, and to offer a unifying explanation of key empirical features of the U.S. labor market.
Attendance confirmation.
Detecting deviations from stationarity of functional time series
Alexander Aue.
(UC Davis).
Detecting deviations from stationarity of functional time series.
Abstract:
The advent of complex data has led to increased research in virtually all areas of statistics, including functional data analysis (FDA). Within the purview of FDA, the use of methods for serially correlated functions is often prudent. As for simpler univariate time series models, the theoretical foundations of methodology are often laid exploiting the notion of stationarity, while data analysis is often conducted on data violating this assumption. This talks looks into ways of discovering departures from stationarity in two ways. In the first part, structural breaks are considered, such that the sample is split into segments in a non-smooth fashion. The methodology to be presented does not rely on the usual dimension reduction techniques, which might be advantageous if the structural break is not sparse (that is, not concentrated within the primary modes of variation of the data). In the second part, local stationarity is introduced as a smooth deviation from stationarity. Here methods in the frequency domain are considered, based on the general result that (second-order) stationarity is equivalent to a functional version of the peridogram being uncorrelated at the Fourier frequencies. Both sets of methods are illustrated with annual Australian temperature profiles. The talk is based on joint work with Anne van Delft (Bochum), Greg Rice (Waterloo) and Ozan Sönmez (Davis).
Attendance confirmation.
Alexander Aue.
(UC Davis).
Detecting deviations from stationarity of functional time series.
Abstract:
The advent of complex data has led to increased research in virtually all areas of statistics, including functional data analysis (FDA). Within the purview of FDA, the use of methods for serially correlated functions is often prudent. As for simpler univariate time series models, the theoretical foundations of methodology are often laid exploiting the notion of stationarity, while data analysis is often conducted on data violating this assumption. This talks looks into ways of discovering departures from stationarity in two ways. In the first part, structural breaks are considered, such that the sample is split into segments in a non-smooth fashion. The methodology to be presented does not rely on the usual dimension reduction techniques, which might be advantageous if the structural break is not sparse (that is, not concentrated within the primary modes of variation of the data). In the second part, local stationarity is introduced as a smooth deviation from stationarity. Here methods in the frequency domain are considered, based on the general result that (second-order) stationarity is equivalent to a functional version of the peridogram being uncorrelated at the Fourier frequencies. Both sets of methods are illustrated with annual Australian temperature profiles. The talk is based on joint work with Anne van Delft (Bochum), Greg Rice (Waterloo) and Ozan Sönmez (Davis).