Document Type
Discussion Paper
Publication Date
1-1-1992
CFDP Number
1007
CFDP Pages
33
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 know simulation algorithms are then compared in terms of theoretical properties and practical performance.
Recommended Citation
Hajivassiliou, Vassilis A., "Simulation Estimation Methods for Limited Dependent Variable Models" (1992). Cowles Foundation Discussion Papers. 1250.
https://elischolar.library.yale.edu/cowles-discussion-paper-series/1250