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Simulation-Based Two-Step Estimation with Endogenous Regressors

This paper considers models with latent/discrete endogenous regressors and presents a simulation-based two-step (STS) estimator. The endogeneity is corrected by adopting a simulation-based control function approacy. The first step consists of simulating the residuals of the reduced-form equation for endogenous regressors. The second step is a regression model (linear, latent or discrete) with the simulated residual as an additional regressor. In this paper we develop the asymptotic theory for the STS estimator and its rate of convergence.

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Paper provided by Center for Policy Research, Maxwell School, Syracuse University in its series Center for Policy Research Working Papers with number 76.

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Length: 39 pages
Date of creation: Dec 2005
Date of revision:
Handle: RePEc:max:cprwps:76
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