Abstract
The circumstances under which the polynomial distributed lag method can be preferred to the ordinary least squares are discussed in this paper and both stochastic and deterministic restrictions are taken into consideration. The polynomial lag is mainly feasible in small sample situations when the error variance of the model is relatively high and the lag function not too peaked. Two recent Monte Carlo studies, one favouring the Almon lag, the other showing the opposite tendency, are reconsidered and their findings discussed in the light of known analytical results.
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TerÄsvirta, T. The polynomial distributed lag revisited. Empirical Economics 5, 69–81 (1980). https://doi.org/10.1007/BF01848044
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DOI: https://doi.org/10.1007/BF01848044