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Inoue, Atsushi; Kilian, Lutz - C.E.P.R. Discussion Papers - 2003

It is standard in applied work to select forecasting models by ranking candidate models by their prediction mean squared error (PMSE) in simulated out-of-sample (SOOS) forecasts. Alternatively, forecast models may be selected using information criteria (IC). We compare the asymptotic and...

Persistent link: https://www.econbiz.de/10005504404

Do DSGE Models Forecast More Accurately Out-of-Sample than VAR Models?

Gürkaynak, Refet S.; Kisacikoglu, Burçin; Rossi, Barbara - C.E.P.R. Discussion Papers - 2013

Recently, it has been suggested that macroeconomic forecasts from estimated DSGE models tend to be more accurate out-of-sample than random walk forecasts or Bayesian VAR forecasts. Del Negro and Schorfheide(2013) in particular suggest that the DSGE model forecast should become the benchmark for...

Persistent link: https://www.econbiz.de/10011083411

Window Selection for Out-of-Sample Forecasting with Time-Varying Parameters

Inoue, Atsushi; Jin, Lu; Rossi, Barbara - C.E.P.R. Discussion Papers - 2014

develop a novel method for selecting the estimation window size for forecasting. Specifically, we propose to choose the …

Persistent link: https://www.econbiz.de/10011083425

Economic theory and forecasting: lessons from the literature

Giacomini, Raffaella - C.E.P.R. Discussion Papers - 2014

Does economic theory help in forecasting key macroeconomic variables? This article aims to provide some insight into … the question by drawing lessons from the literature. The definition of "economic theory" includes a broad range of … examples of theory-based forecasting that have not proven useful, such as theory-driven variable selection and some popular …

Persistent link: https://www.econbiz.de/10011084122

Joint Confidence Sets for Structural Impulse Responses

Inoue, Atsushi; Kilian, Lutz - C.E.P.R. Discussion Papers - 2014

Many users of structural VAR models are primarily interested in learning about the shape of structural impulse response functions. This requires joint inference about sets of structural impulse responses, allowing for dependencies across time as well as across response functions. Such joint...

Persistent link: https://www.econbiz.de/10011084610

Model Averaging and Value-at-Risk Based Evaluation of Large Multi-Asset Volatility Models for Risk Management

Pesaran, M Hashem; Zaffaroni, Paolo - C.E.P.R. Discussion Papers - 2005

This paper considers the problem of model uncertainty in the case of multi-asset volatility models and discusses the use of model averaging techniques as a way of dealing with the risk of inadvertently using false models in portfolio management. Evaluation of volatility models is then considered...

Persistent link: https://www.econbiz.de/10005067642

Factor Forecasts for the UK

Artis, Michael J; Banerjee, Anindya; Marcellino, … - C.E.P.R. Discussion Papers - 2002

Time series models are often adopted for forecasting because of their simplicity and good performance. The number of parameters in these models increases quickly with the number of variables modelled, so that usually only univariate or small-scale multivariate models are considered. Yet, data...

Persistent link: https://www.econbiz.de/10005661430

How Useful is Bagging in Forecasting Economic Time Series? A Case Study of US CPI Inflation

Inoue, Atsushi; Kilian, Lutz - C.E.P.R. Discussion Papers - 2005

This paper explores the usefulness of bagging methods in forecasting economic time series from linear multiple regression models. We focus on the widely studied question of whether the inclusion of indicators of real economic activity lowers the prediction mean-squared error of forecast models...

Persistent link: https://www.econbiz.de/10005661494

Properties of Optimal Forecasts

Patton, Andrew J; Timmermann, Allan G - C.E.P.R. Discussion Papers - 2003

Evaluation of forecast optimality in economics and finance has almost exclusively been conducted under the assumption of mean squared error loss. Under this loss function optimal forecasts should be unbiased and forecast errors serially uncorrelated at the single-period horizon with increasing...

Persistent link: https://www.econbiz.de/10005661998

Do Local Projections Solve the Bias Problem in Impulse Response Inference?

Kilian, Lutz; Kim, Yun Jung - C.E.P.R. Discussion Papers - 2009

It is well documented that the small-sample accuracy of asymptotic and bootstrap approximations to the pointwise distribution of VAR impulse response estimators is undermined by the estimator’s bias. A natural conjecture is that impulse response estimators based on the local projection (LP)...

Persistent link: https://www.econbiz.de/10005666791