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Imposing Observation-Varying Equality Constraints Using Generalised Restricted Least Squares

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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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File URL: http://www.uq.edu.au/economics/abstract/323.pdf
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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. Christopher J. O'Donnell & C. Richard Shumway & V. Eldon Ball, 1999. "Input Demands and Inefficiency in U.S. Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 81(4), pages 865-880.
  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.
  3. 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.
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Cited by:
  1. O'Donnell, Christopher J., 2006. "Some Econometric Options For Dealing With Unknown Functional Form," 2006 Conference (50th), February 8-10, 2006, Sydney, Australia 137787, Australian Agricultural and Resource Economics Society.

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