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SAUSS: Stochastic Approximation with Unbiased Simulated Scores for Limited Dependent Variable Models
Simulated maximum likelihood is widely used in latent-variable models where likelihood evaluation requires intractable integrals or probabilities. With a fixed number of simulation draws, its estimating equation is generally biased. We develop Stochastic Approximation with Unbiased Simulated Scores
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