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Simulated Maximum Likelihood Estimation of the Linear Expenditure System with Binding Non-Negativity Constraints

  • Chihwa Kao

    (Department of Economics and Center for Policy Research, Syracuse University)

  • Lung-fei Lee


    (Department of Economics, The Ohio State University)

  • Mark M. Pitt

    (Department of Economics, Brown University)

This paper discusses issues on the estimation of consumer demand equations subject to binding non-negative constraints. We propose computationally feasible specifications and a simulated maximum likelihood (SML) method for demand systems. Our study shows that the econometric implementation of the SML estimates can avoid high-dimensional integration problems. As contrary to the simulation method of moments and simulated pseudo-likelihood methods that require the simulation of demand quantities subject to nonnegativity constraints for consumers in the sample, the SML approach requires only simulation of the likelihood function. The SML approach avoids solving for simulated demand quantities because the likelihood function is conditional on observed demand quantities. We have applied SML approach for the linear expenditure system (LES) with non-negativity constraints. The results of a seven-goods demand system are presented. The results provide empirical evidence on the importance of taking into account possible cross equation correlations in disturbances.

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Paper provided by China Economics and Management Academy, Central University of Finance and Economics in its series CEMA Working Papers with number 50.

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Length: 21 pages
Date of creation: May 2000
Date of revision: Apr 2001
Publication status: Published in Annals of Economics and Finance, May 2001, pages 215-235
Handle: RePEc:cuf:wpaper:50
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