Modeling trends

Christopher Sims ()

No 22, Discussion Paper / Institute for Empirical Macroeconomics from Federal Reserve Bank of Minneapolis

Abstract: Models of low-frequency behavior of time series may have strongly conflicting substantive implications while fitting the data nearly equally well. We should develop methods which display the resulting uncertainty rather than adopt modeling conventions which hide it. One step toward this goal may be to consider “overparameterized” stationary ARMA models.

Keywords: Econometric; models (search for similar items in EconPapers)
Date: Written
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