Simulation Estimation Methods for Limited Dependent Variable Models

Vassilis Hajivassiliou

No 1007, Cowles Foundation Discussion Papers from Cowles Foundation for Research in Economics, Yale University

Abstract: This chapter discusses simulation estimation methods that overcome the computational intractability of classical estimation of limited dependent variable models with flexible correlation structures in the unobservable stochastic terms. These difficulties arise because of the need to evaluate accurately very high dimensional integrals. The methods based on simulation do not require the exact evaluation of these integrals and hence are feasible using computers of even moderate power. I first discuss a series of ideas that had been used in efforts to circumvent these computational problems by employing standard numerical analysis approximation methods. I then show how simulation techniques solve the computational problems without the need to resort to either generally unsatisfactory numerical approximations. All currently known simulation algorithms are then compared in terms of theoretical properties and practical performance.

Keywords: Simulation methods; econometric modeling; model estimation; correlation structures (search for similar items in EconPapers)
JEL-codes: C13 C15 C51 (search for similar items in EconPapers)
Pages: 33 pages
Date: 1991-12
Note: CFP 862.
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (22)

Published in G.S. Maddala, C.R. Rao and H.D. Vinod, eds., Handbook of Statistics, Vol. 11, Elsevier, 1993, pp. 519-543

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