Misspecification Testing in a Class of Conditional Distributional Models
نویسندگان
چکیده
Misspecification Testing in a Class of Conditional Distributional Models We propose a specification test for a wide range of parametric models for the conditional distribution function of an outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted estimate of the joint distribution function of the data, and a restricted estimate that imposes the structure implied by the model. The procedure is straightforward to implement, is consistent against fixed alternatives, has non-trivial power against local deviations of order n -1/2 from the null hypothesis, and does not require the choice of smoothing parameters. In an empirical application, we use our test to study the validity of various models for the conditional distribution of wages in the US. JEL Classification: C12, C14, C31, C52, J31
منابع مشابه
Double Robust Semiparametric Efficient Tests for Distributional Treatment Effects under the Conditional Independence Assumption
This note describes methods to test for distributional treatment effects under the conditional independence assumption. The differences between latent outcome distributions are judged by testing hypotheses of distributional equality and stochastic dominance. Furthermore, semiparametric efficient versions of the test statistics are given. The latter test statistics are double robust, i.e., they ...
متن کاملMisspecification tests for periodic long memory GARCH models
Distributional theory for Quasi-Maximum Likelihood estimators in long memory conditional heteroskedastic models is not formally defined, even asympotically. Because of that, this paper analyses the performance of the Likelihood Ratio and the Lagrange Multiplier misspecification tests for Periodic Long Memory GARCH models. The real size and power of these tests are studied by means of Monte Carl...
متن کاملEvaluating Models of Autoregressive Conditional Duration
This article contains two novelties. First, a unified framework for testing and evaluating the adequacy of an estimated autoregressive conditional duration (ACD) model is presented. Second, two new classes of ACD models, the smooth transition ACD model and the time-varying ACD model, are introduced and their properties discussed. New misspecification tests for the ACD class of models are introd...
متن کاملAn Encompassing Approach to Conditional Mean Tests with Applications to Testing Nonnested Hypotheses
A general class of tests designed to detect conditional mean misspecification for cross section or time series applications is proposed. The tests are derived from a particular application of the encompassing principle. The resulting conditional mean encompassing (CME) tests contain as special cases a version of the Lagrange Multiplier test for nested models, a new test in the presence of nonne...
متن کاملSpecification Testing for Functional Forms in Dynamic Panel Data Models
The most popular econometric models in the panel data literature are the class of linear panel data models with unobserved individualand/or time-specific effects. The consistency of parameter estimators and the validity of their economic interpretations as marginal effects crucially depend on the correct functional form specification of the linear panel data model. Based on an individual-specif...
متن کامل