A Method for Smoothing Simulated Moments of Discrete Probabilities in Multinomial Probit Models

By Steven Stern. 1992

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Citations in the corpus

Panel Data Discrete Choice Models of Consumer Demand (2013, methodology): “A potential solution to this problem, proposed by Berkovec and Stern (1991) and Stern (1992), is to reformulate the model to ―add noise‖ and ―smooth out‖ the indicator functions in (19).”
Likelihood approximation by numerical integration on sparse grids (2008, background): “…smoothness of the integrand, although with a ﬁnite number of simulation draws, smooth integrands also help to improve the approximation performance (Stern 1992). e d In all cases, ill-behaved integrands such as functions with discontinuities can be expected to hamper a satisfactory approximation.”
Regulator reputation, enforcement, and environmental compliance (2005, background): “regulator reputation-based deterrence component of an additional fine induces an approximately 64 percent reduction in the statewide probability of a violation in the year following a fine.(24) We emphasize that this is an average reduction for all plants within a state; the impact is not limited to”
Alternative sampling methods for estimating multivariate normal probabilities (2003, methodology): “This was followed by several improvements later on (e.g., McFadden, 1989; Stern, 1992).”
Extended discrete choice models : integrated framework, flexible error structures, and latent variables (2001, methodology): “Hence, the algorithms and specifications were designed to eventually remove the additive “contamination” element from the model (for example, McFadden, 1989) or ensure that it did not interfere with the pure probit specification (for example, Stern, 1992).”