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dc.contributor.authorBANERJEE, Anindya
dc.contributor.authorMIZEN, Paul
dc.date.accessioned2011-04-19T12:46:40Z
dc.date.available2011-04-19T12:46:40Z
dc.date.issued2006
dc.identifier.citationJournal of Applied Econometrics, 2006, 21, 8, 1249-1264
dc.identifier.issn0883-7252
dc.identifier.urihttp://hdl.handle.net/1814/16395
dc.description.abstractEstimation of the linear quadratic model, the workhorse of the inventory literature, traditionally takes inventories and sales to be first-difference stationary series, and the ratio of the two variables to be stationary. However, these assumptions do not always match the properties of the data for the last two decades in the United States. We propose a model that allows for the non-stationary characteristics of the data, using polynomial cointegration. We show that the closed-form solution has other recent models as special cases. The resulting model performs well on aggregate and disaggregated data. Copyright (c) 2006 John Wiley & Sons, Ltd.
dc.language.isoen
dc.publisherJohn Wiley & Sons Ltd
dc.titleA Re-Interpretation of the Linear-Quadratic Model When Inventories and Sales Are Polynomially Cointegrated
dc.typeArticle
dc.identifier.doi10.1002/jae.892
dc.neeo.contributorBANERJEE|Anindya|aut|
dc.neeo.contributorMIZEN|Paul|aut|
dc.identifier.volume21
dc.identifier.startpage1249
dc.identifier.endpage1264
eui.subscribe.skiptrue
dc.identifier.issue8


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