A Re-Interpretation of the Linear-Quadratic Model When Inventories and Sales Are Polynomially Cointegrated

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dc.contributor.author BANERJEE, Anindya
dc.contributor.author MIZEN, Paul
dc.date.accessioned 2011-04-19T12:46:40Z
dc.date.available 2011-04-19T12:46:40Z
dc.date.issued 2006
dc.identifier.citation Journal of Applied Econometrics, 2006, 21, 8, 1249-1264
dc.identifier.issn 0883-7252
dc.identifier.uri http://hdl.handle.net/1814/16395
dc.description.abstract Estimation 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.iso en
dc.publisher John Wiley & Sons Ltd
dc.title A Re-Interpretation of the Linear-Quadratic Model When Inventories and Sales Are Polynomially Cointegrated
dc.type Article
dc.identifier.doi 10.1002/jae.892
dc.neeo.contributor BANERJEE|Anindya|aut|
dc.neeo.contributor MIZEN|Paul|aut|
dc.identifier.volume 21
dc.identifier.startpage 1249
dc.identifier.endpage 1264
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dc.identifier.issue 8


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