4 citations · 9 across the 7 of their papers we have counts for
9 papers · 1 filter
Optimal Estimation of Two-Way Effects under Limited Mobility
Xu Cheng, Sheng Chao Ho, Frank Schorfheide
We propose an empirical Bayes estimator for two-way effects in linked data sets based on a novel prior that leverages patterns of assortative matching observed in the data. To capt…
Misspecification-Robust Shrinkage and Selection for VAR Forecasts and IRFs
Oriol González-Casasús, Frank Schorfheide
Vector autoregressions (VARs) are vulnerable to dynamic misspecification, forcing researchers to navigate complex bias-variance trade-offs when forecasting or estimating impulse re…
Bayesian Estimation of Panel Models under Potentially Sparse Heterogeneity
Hyungsik Roger Moon, Frank Schorfheide, Boyuan Zhang
We incorporate a version of a spike and slab prior, comprising a pointmass at zero ("spike") and a Normal distribution around zero ("slab") into a dynamic panel data framework to m…
Optimal Decision Rules when Payoffs are Partially Identified
Timothy Christensen, Hyungsik Roger Moon, Frank Schorfheide
We derive asymptotically optimal statistical decision rules for discrete choice problems when payoffs depend on a partially-identified parameter and the decision maker can use…
Sequential Monte Carlo With Model Tempering
Marko Mlikota, Frank Schorfheide
Modern macroeconometrics often relies on time series models for which it is time-consuming to evaluate the likelihood function. We demonstrate how Bayesian computations for such mo…
Forecasting with a Panel Tobit Model
Laura Liu, Hyungsik Roger Moon, Frank Schorfheide
We use a dynamic panel Tobit model with heteroskedasticity to generate forecasts for a large cross-section of short time series of censored observations. Our fully Bayesian approac…
Robust Forecasting
Timothy Christensen, Hyungsik Roger Moon, Frank Schorfheide
We use a decision-theoretic framework to study the problem of forecasting discrete outcomes when the forecaster is unable to discriminate among a set of plausible forecast distribu…
Forecasting with Dynamic Panel Data Models
Laura Liu, Hyungsik Roger Moon, Frank Schorfheide
This paper considers the problem of forecasting a collection of short time series using cross sectional information in panel data. We construct point predictors using Tweedie's for…
Inference for VARs Identified with Sign Restrictions
Eleonora Granziera, Hyungsik Roger Moon, Frank Schorfheide
There is a fast growing literature that set-identifies structural vector autoregressions (SVARs) by imposing sign restrictions on the responses of a subset of the endogenous variab…