Journal Article

Macroeconomic forecasting and structural change

Gambetti, Luca, D'Agostino, Antonello, Giannone, Domenico

2013

Overview

The aim of this paper is to assess whether modeling structural change can help improving the accuracy of macroeconomic forecasts. We conduct a simulated real-time out-of-sample exercise using a time-varying coefficients vector autoregression (VAR) with stochastic volatility to predict the inflation rate, unemployment rate and interest rate in the USA. The model generates accurate predictions for the three variables. In particular, the forecasts of inflation are much more accurate than those obtained with any other competing model, including fixed coefficients VARs, time-varying autoregressions and the naïve random walk model. The results hold true also after the mid 1980s, a period in which forecasting inflation was particularly hard.

• Publisher: John Wiley & Sons, Ltd,John Wiley & Sons,Wiley-Blackwell,Wiley Periodicals Inc
• Subject: Analytical forecasting / Arbeitslosigkeit / Coefficients / Economic forecasting / Economic forecasting models / Economic forecasts / Economic inflation / Forecasting / Forecasting models / Inflation / Inflation expectations / Inflation rates / Inflationsrate / Interest rates / Macroeconomic modeling / Macroeconomics / Random walk theory / Regression analysis / Stochastic models / Structural adjustment / Structural change / Strukturwandel / Studies / Time out / Time series forecasting / Unemployment / Unemployment rates / USA / VAR-Modell / Vector autoregression / Vector-autoregressive models / Volatilität / Volkswirtschaft / Wirtschaftsprognose / Zins