This paper analyzes the higher-order properties of nested pseudo-likelihood (NPL) estimators and their practical implementation for parametric discrete Markov decision models in which the probability distribution is defined as a fixed point. We propose a new NPL estimator that can achieve...

To what extent does a tax credit affect firms’ R&D activity? What are the mechanisms? This paper examines the effect of R&D tax credits on firms’ R&D expenditure by exploiting the variation across firms in the changes in the eligible tax credit rate between 2000 and 2003. Estimating the...

type="main" <p>In this paper we propose a modified quasi-likelihood ratio test of the null hypothesis of one regime against the alternative of two regimes in Markov regime-switching models. The asymptotic distribution of the proposed test statistic is a simple function of Gaussian random variables,...</p>

type="main" xml:id="rssb12022-abs-0001" <title type="main">Summary</title> <p>We analyse the identifiability of the number of components in k-variate, M-component finite mixture models in which each component distribution has independent marginals, including models in latent class analysis. Without making parametric...</p>

This paper considers likelihood-based testing of the null hypothesis of <em>m0</em> components against the alternative of <em>m</em>0+1 components in a finite mixture model. The number of components is an important parameter in the applications of finite mixture models. Still, testing the number of components has...

To what extent does a tax credit affect firms’ R&D activity? What are the mechanisms? This paper examines the effect of R&D tax credits on firms’ R&D expenditure by exploiting the variation across firms in the changes in the eligible tax credit rate between 2000 and 2003. Estimating the...

This paper considers the estimation problem of structural models for which empirical restrictions are characterized by a fixed point constraint, such as structural dynamic discrete choice models or models of dynamic games. We analyze the conditions under which the nested pseudo-likelihood (NPL)...

In dynamic discrete choice analysis, controlling for unobserved heterogeneity is an important issue, and finite mixture models provide flexible ways to account for it. This paper studies nonparametric identifiability of type probabilities and type-specific component distributions in finite...

This paper analyzes the higher-order properties of the estimators based on the nested pseudo-likelihood (NPL) algorithm and the practical implementation of such estimators for parametric discrete Markov decision models. We derive the rate at which the NPL algorithm converges to the MLE and...