Multiple-membership logit models with random effects are logit models for clustered binary data, where each statistical unit can belong to more than one group. For these models, the likelihood function is analytically intractable. We propose two different approaches for parameter estimation:...

A direct Maximum Likelihood (ML) procedure to estimate the "generally unidentified" across-regime correlation parameter in a two-regime endogenous switching model is here provided. The results of a Monte Carlo experiment confirm consistency of our direct ML procedure, and its relative efficiency...

Given a set of continuous variables with missing data, we prove in this paper that the iterative application of a simple “least-squares estimation/multivariate normal simulation” procedure produces an efficient parameters estimator. There are two main assumptions behind our proof: (1) the...

Simulation estimators, such as indirect inference or simulated maximum likelihood, are successfully employed for estimating models where the likelihood function does not have a simple analytical expression. They adjust for the bias (inconsistency) produced by the estimation of an auxiliary model...

Logit models with random effects are now widely used in applied Statistics and Econometrics. They usually lead to intractable likelihood functions, as they involve integrals without closed form solution. Numerical integration can be used to compute the likelihood and software is available...

The alpha-stable family of distributions constitutes a generalization of the Gaussian distribution, allowing for asymmetry and thicker tails. Its many useful properties, including a central limit theorem, are especially appreciated in the financial field. However, estimation difficulties have up...

The use of Monte Carlo methods to generate exam data sets is nowadays a well-established practice among econometrics examiners all over the world. Its advantages are well known: providing each student a different data set ensures that estimates are actually computed individually, rather than...

The alpha-stable family of distributions constitutes a generalization of the Gaussian distribution, allowing for asymmetry and thicker tails. Its practical usefulness is coupled with a marked theoretical appeal, as it stems from a generalized version of the central limit theorem in which the...