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A Re-interpretation of the Linear-Quadratic Model When Inventories and Sales are Polynomially Cointegrated

Author

Listed:
  • Anindya BANERJEE
  • Paul MIZEN

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 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.

Suggested Citation

  • Anindya BANERJEE & Paul MIZEN, 2003. "A Re-interpretation of the Linear-Quadratic Model When Inventories and Sales are Polynomially Cointegrated," Economics Working Papers ECO2003/11, European University Institute.
    • Handle: RePEc:eui:euiwps:eco2003/11
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    Cited by:

    1. Hualde, Javier, 2014. "Estimation of long-run parameters in unbalanced cointegration," Journal of Econometrics, Elsevier, vol. 178(2), pages 761-778.
    2. Gomez-Biscarri, Javier & Hualde, Javier, 2015. "A residual-based ADF test for stationary cointegration in I(2) settings," Journal of Econometrics, Elsevier, vol. 184(2), pages 280-294.
    3. John D. Tsoukalas, 2011. "Input and Output Inventories in the UK," Economica, London School of Economics and Political Science, vol. 78(311), pages 460-479, July.

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    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis

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