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DSGE Model-Based Forecasting of Non-modelled Variables

Schorfheide, Frank - 2009

This paper develops and illustrates a simple method to generate a DSGE model-based forecast for variables that do not explicitly appear in the model (non-core variables). We use auxiliary regressions that resemble measurement equations in a dynamic factor model to link the non-core variables to...

Persistent link: https://www.econbiz.de/10012463776

Identifying Long-Run Risks : A Bayesian Mixed-Frequency Approach

Schorfheide, Frank - 2014

multiple stochastic volatility processes. The estimation is based on annual consumption data from 1929 to 1959, monthly … Bayesian estimation provides strong evidence for a small predictable component in consumption growth (even if asset return data … are omitted from the estimation). Three independent volatility processes capture different frequency dynamics; our …

Persistent link: https://www.econbiz.de/10012458363

Improving GDP Measurement : A Forecast Combination Perspective

Aruoba, S. Boragan - 2011

Two often-divergent U.S. GDP estimates are available, a widely-used expenditure side version, GDPE, and a much less widely-used income-side version GDPI . We propose and explore a "forecast combination" approach to combining them. We then put the theory to work, producing a superior combined...

Persistent link: https://www.econbiz.de/10012461237

Real-Time Forecasting with a (Standard) Mixed-Frequency VAR During a Pandemic

Schorfheide, Frank; Song, Dongho - National Bureau of Economic Research - 2021

-19 outbreak, except for the exclusion of crisis observations from the estimation sample. We compare the MF-VAR forecasts … is a promising way of handling VAR estimation going forward, as an alternative of a sophisticated modeling of outliers …

Persistent link: https://www.econbiz.de/10012794563

Forecasting with a Panel Tobit Model

Liu, Laura - 2019

We use a dynamic panel Tobit model with heteroskedasticity to generate point, set, and density forecasts for a large cross-section of short time series of censored observations. Our fully Bayesian approach allows us to flexibly estimate the cross-sectional distribution of heterogeneous...

Persistent link: https://www.econbiz.de/10012480513

Forecasting with Dynamic Panel Data Models

Liu, Laura - 2018

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 formula for the posterior mean of heterogeneous coefficients under a correlated random effects distribution. This...

Persistent link: https://www.econbiz.de/10012480753

Real-Time Forecast Evaluation of DSGE Models with Stochastic Volatility

Diebold, Francis X. - 2016

Recent work has analyzed the forecasting performance of standard dynamic stochastic general equilibrium (DSGE) models, but little attention has been given to DSGE models that incorporate nonlinearities in exogenous driving processes. Against that background, we explore whether incorporating...

Persistent link: https://www.econbiz.de/10012456064

Dynamic Prediction Pools : An Investigation of Financial Frictions and Forecasting Performance

Del Negro, Marco - 2014

We provide a novel methodology for estimating time-varying weights in linear prediction pools, which we call Dynamic Pools, and use it to investigate the relative forecasting performance of DSGE models with and without financial frictions for output growth and inflation from 1992 to 2011. We...

Persistent link: https://www.econbiz.de/10012458090

Real-Time Forecasting with a Mixed-Frequency VAR

Schorfheide, Frank - 2013

This paper develops a vector autoregression (VAR) for time series which are observed at mixed frequencies - quarterly and monthly. The model is cast in state-space form and estimated with Bayesian methods under a Minnesota-style prior. We show how to evaluate the marginal data density to...

Persistent link: https://www.econbiz.de/10012458951