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 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...

To what extent does a tax credit affect firms' R&D activity? What are the mechanisms? This paper examines the effect of the 2003 Japanese tax credit reform on firms' R&D investment by exploiting cross-sectional variation across firms in the changes in the effective tax credit rate between 2002...

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

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)...

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...

We study nonparametric identifiability of finite mixture models of k-variate data with M subpopulations, in which the components of the data vector are independent conditional on belonging to a subpopulation. We provide a sufficient condition for nonparametrically identifying M subpopulations...

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...

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