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A Comparison of Direct and Iterated Multistep AR Methods for Forecasting Macroeconomic Time Series

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Author Info
Marcellino, Massimiliano
Stock, James H
Watson, Mark W

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Abstract

‘Iterated’ multiperiod ahead time series forecasts are made using a one-period ahead model, iterated forward for the desired number of periods, whereas ‘direct’ forecasts are made using a horizon-specific estimated model, where the dependent variable is the multi-period ahead value being forecasted. Which approach is better is an empirical matter: in theory, iterated forecasts are more efficient if correctly specified, but direct forecasts are more robust to model misspecification. This paper compares empirical iterated and direct forecasts from linear univariate and bivariate models by applying simulated out-of-sample methods to 171 US monthly macroeconomic time series spanning 1959-2002. The iterated forecasts typically outperform the direct forecasts, particularly if the models can select long lag specifications. The relative performance of the iterated forecasts improves with the forecast horizon.

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Paper provided by C.E.P.R. Discussion Papers in its series CEPR Discussion Papers with number 4976.

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Date of creation: Mar 2005
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Handle: RePEc:cpr:ceprdp:4976

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Related research
Keywords: forecast comparisons multistep forecasts VAR forecasts

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Find related papers by JEL classification:
C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation
E47 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Forecasting and Simulation

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