Abstract
Prediction formulas for multi-step forecasts and geometric distributed leads of stationary time series are derived using classical, frequency domain methods. Starting with the Wold representation, optimal squared-error loss predictions are derived using the analytic function theory approach of Whittle. This approach is easily adapted to the problem of making predictions that are robust under model misspecification. Forecasts and expected present value calculations are illustrated under both objectives for low-order autoregressive and moving average processes.
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Hansen, L.P., and T.J. Sargent. 1980. Formulating and estimating dynamic linear rational expectations models. Journal of Economic Dynamics and Control 2: 7–46.
Hansen, L.P., and T.J. Sargent. 2007. Robustness. Princeton: Princeton University Press.
Kasa, K. 2001. A robust Hansen–Sargent prediction formula. Economic Letters 71: 43–48.
Nehari, Z. 1957. On bounded bilinear forms. Annals of Mathematics 65(1): 153–162.
Sargent, T.J. 1987. Macroeconomic theory. New York: Academic Press.
Whiteman, C.H. 1983. Linear rational expectations: A user ’s guide. Minneapolis: University of Minnesota Press.
Whittle, P. 1983. Prediction and regulation by linear least-square methods. 2nd ed. Minneapolis: University of Minnesota Press.
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Whiteman, C.H., Lewis, K.F. (2018). Prediction Formulas. In: The New Palgrave Dictionary of Economics. Palgrave Macmillan, London. https://doi.org/10.1057/978-1-349-95189-5_2180
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DOI: https://doi.org/10.1057/978-1-349-95189-5_2180
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Publisher Name: Palgrave Macmillan, London
Print ISBN: 978-1-349-95188-8
Online ISBN: 978-1-349-95189-5
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