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

Chihwa Kao, Lung-Fei Lee and Mark Pitt (mark_pitt@brown.edu)

Annals of Economics and Finance, 2001, vol. 2, issue 1, 215-235

Abstract: 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.

Keywords: Simulated likelihood; Linear expenditure system; Non-negativity constraints; Multivariate censored variables; Nonlinear simultaneous equations (search for similar items in EconPapers)
JEL-codes: C15 C34 D12 (search for similar items in EconPapers)
Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

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Working Paper: Simulated Maximum Likelihood Estimation of the Linear Expenditure System with Binding Non-Negativity Constraints (2001)
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Persistent link: https://EconPapers.repec.org/RePEc:cuf:journl:y:2001:v:2:i:1:p:215-235

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