A Re-interpretation of the Linear-Quadratic Model When Inventories and Sales are Polynomially Cointegrated
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 to be stationary. However, these assumptions do not match the properties of the data for the last two decades in the US and the UK. We offer 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 and shows good forecasting properties.
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Date of creation: 2003
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cointegration; linear quadratic; inventories;
Other versions of this item:
- Paul Mizen & Anindya Banerjee, 2006. "A re-interpretation of the linear quadratic model when inventories and sales are polynomially cointegrated," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(8), pages 1249-1264.
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
This paper has been announced in the following NEP Reports:
- NEP-ALL-2003-07-29 (All new papers)
- NEP-ECM-2003-08-01 (Econometrics)
- NEP-ETS-2003-07-29 (Econometric Time Series)
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