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Mind your Ps and Qs! Improving ARMA forecasts with RBC priors

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Author Info
Kirdan Lees
Troy Matheson (Reserve Bank of New Zealand)

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Abstract

We utilise prior information from a simple RBC model to improve ARMA forecasts of post-war US GDP. We develop three alternative ARMA forecasting processes that use varying degrees of information from the Campbell (1994) flexible labour model. Directly calibrating the model produces poor forecasting performance whereas a model that uses a Bayesian framework to take the model to the data, yields forecasting performance comparable to a purely statistical ARMA process. A final model that uses theory only to restrict the order of the ARMA process (the ps and qs), but that estimates the ARMA parameters using maximum likelihood, yields improved forecasting performance.

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File URL: http://www.rbnz.govt.nz/research/discusspapers/dp05_02.pdf
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Paper provided by Reserve Bank of New Zealand in its series Reserve Bank of New Zealand Discussion Paper Series with number DP2005/02.

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Length: 25 p.
Date of creation: Oct 2005
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Handle: RePEc:nzb:nzbdps:2005/02

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Find related papers by JEL classification:
C11 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: General - - - Bayesian Analysis
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models
E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation

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