Tests of specification for parametric and semiparametric models

Specification Tests for Semiparametric Instrumental Variables

Semi-Parametric Specification Tests for Discrete Probability Models

Loss functions play an important role in analyzing insurance portfolios. A fundamental issue in the study of loss functions involves the selection of probability models for claim frequencies. In this article, we propose a semiparametric approach based on the generalized method of moments (GMM) to solve the specification problems concerning claim frequency distributions. The GMM-based testing pr...

Semi-parametric specification tests for mixing distributions

We present a semi-parametric method for testing mixing distributions in the mixed Poisson model. The proposed method, which is based on the generalized method of moments, does not demand the complete specification of the probability function but only requires a specification of a set of moment conditions which the model should satisfy. We demonstrate that an explicit expression for moment relat...

Specification Tests in Parametric Value-at-risk Models

One of the implications of the creation of Basel Committee on Banking Supervision was the implementation of Value-at-Risk (VaR) as the standard tool for measuring market risk and of out-of-sample backtesting for banking risk monitoring. We stress in this article that the results derived from this exercise can be spurious if one does not carry out a previous in-sample specification test to deter...

Consistent Specification Tests for Semiparametric/Nonparametric Models Based on Series Estimation Methods

This paper considers the problem of consistent model specification tests using series estimation methods. The null models we consider in this paper all contain some nonparametric components. A leading case we consider is to test for an additive partially linear model. The null distribution of the test statistic is derived using a central limit theorem for Hilbert valued random arrays. The test ...