Open AccessSpecification testing in random coefficient models
Author(s) -
Breunig Christoph,
Hoderlein Stefan
Publication year - 2018
Publication title -
quantitative economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.062
H-Index - 27
eISSN - 1759-7331
pISSN - 1759-7323
DOI - 10.3982/qe757
Subject(s) - nonparametric statistics , estimator , monte carlo method , random variable , mathematics , sieve (category theory) , nonlinear system , specification , random effects model , econometrics , function (biology) , statistics , physics , discrete mathematics , medicine , meta analysis , quantum mechanics , evolutionary biology , biology
In this paper, we suggest and analyze a new class of specification tests for random coefficient models. These tests allow to assess the validity of central structural features of the model, in particular linearity in coefficients, generalizations of this notion like a known nonlinear functional relationship, or degeneracy of the distribution of a random coefficient, that is, whether a coefficient is fixed or random, including whether an associated variable can be omitted altogether. Our tests are nonparametric in nature, and use sieve estimators of the characteristic function. We provide formal power analysis against global as well as against local alternatives. Moreover, we perform a Monte Carlo simulation study, and apply the tests to analyze the degree of nonlinearity in a heterogeneous random coefficients demand model. While we find some evidence against the popular QUAIDS specification with random coefficients, it is not strong enough to reject the specification at the conventional significance level.