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Imposing Observation-Varying Equality Constraints Using Generalised Restricted Least Squares

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Author Info
Dr Alicia Rambaldi ()
Dr Chris O'Donnell ()
Howard E.Doran (School of Economics, The University of Queensland)

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Abstract

Linear equality restrictions derived from economic theory are frequently observation-varying. Except in special cases, Restricted Least Squares (RLS) cannot be used to impose such restrictions without either underconstraining or overconstraining the parameter space. We solve the problem by developing a new estimator that collapses to RLS in cases where the restrictions are observation-invariant. We derive some theoretical properties of our so-called Generalised Restricted Least Squares (GRLS) estimator, and conduct a simulation experiment involving the estimation of a constant returns to scale production function. We find that GRLS significantly outperforms RLS in both small and large samples.

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Publisher Info
Paper provided by School of Economics, University of Queensland, Australia in its series Discussion Papers Series with number 323.

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Date of creation: 2003
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Handle: RePEc:qld:uq2004:323

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  1. Clements, Kenneth W & Izan, H Y, 1987. "The Measurement of Inflation: A Stochastic Approach," Journal of Business & Economic Statistics, American Statistical Association, vol. 5(3), pages 339-50, July.
  2. Doran, Howard E. & Rambaldi, Alicia N., 1997. "Applying linear time-varying constraints to econometric models: With an application to demand systems," Journal of Econometrics, Elsevier, vol. 79(1), pages 83-95, July. [Downloadable!] (restricted)
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This page was last updated on 2008-10-31.

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