VAR, error correction and pretest forecasts at long horizons

Article Abstract:

Long-horizon interval and point forecasting is a very difficult activity as a typical four-year forecast is usually constructed based on 20 to 40 years' worth of information. The difficulty often lies in the presence of persistence in the form of unit or near-unit autoregressive roots. Even by using efficient pre-testing or model-selection procedures, these difficulties are hard to overcome. As such, long-horizon and point forecasting sometimes leads to forecasts that have large asymptotic root mean squared errors and very wide prediction intervals.

Analysis, Stochastic processes

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Specifying and testing output and pricing structures of alternative macroeconomic models

Article Abstract:

A study has been conducted to develop a framework which can be used to assist the economic modeller in making a more informed choice between the various economic models. Findings indicated that the two other important macroeconomic models, namely the imperfect substitutes model and the model with traded and non-traded goods, are special cases of the more general three-goods model. A simple two-stage test has been developed to help the macroeconomic modeller to choose the particular model structure on the basis of economic data.

Models, Macroeconomics, Capital assets pricing model, Capital asset pricing model

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VAR, error correction and pretest forecasts at long horizons

Article Abstract:

An analysis is presented of methods of estimating errors in interval forecasts and pretest forecasts for long horizon forecasting in multivariate systems. Strategies include the use of vector autoregression (VAR), vector error correction model (VECM), and unit root and cointegration pretests. Numerical data suggest that, even for 10% or 20% sample size, the distortions and biases of VAR and VECM point forecasts and coverage rates, respectively, are strong.

Error analysis (Mathematics), Error analysis

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