by Portsmouth Polytechnic Dept. ofEconomics & Economic History in Portsmouth .
Written in English
|Series||Discussion papers / Portsmouth Polytechnic Department of Economics and Economic History -- no.3|
Semi-Nonparametric Estimation and Misspecification Testing of Diffusion Models Article in Journal of Econometrics () March with 32 Reads How we measure 'reads' The tests can detect a wide range of model misspecifications in the conditional mean of a dynamic panel data model, including functional form and lag :// /_Misspecification_test_methods_in_econometrics. We analyze their finite-sample properties in a Monte Carlo experiment along with those of two alternative tests for spatial lag dependence based on least squares and generalized least squares In this study, we introduce adjusted Rao's score test statistics (Lagrange multiplier (LM) tests) for a spatial dynamic panel data (SDPD) model that includes a contemporaneous spatial lag, a time
Bootstrap conditional distribution tests in the presence of dynamic misspecification. Author links open overlay panel Valentina Corradi a tests that are designed to have power against both uniformity and independence violations (i.e. tests that assume correct dynamic specification there are marked improvements in finite sample power Furthermore, there are several independence tests, e.g. the BDS tests proposed by Broock et al. () and the omnibus test of Hong and Lee () based on generalized spectral densities. A number of misspecification tests have also been proposed for the MEM of conditional duration :// Table 2 shows that the proposed test has good finite sample sizes at the nominal significance level 5%. The observed sizes converge to the nominal size with the increase of sample size and the rejection rates are almost equal to the nominal size when n = Compared to Table 3 in Campbell and Yogo (), which reports the simulated finite-sample rejection rates by using different test First, unlike Kan and Zhang (a), we study the asymptotic and finite-sample properties of misspecification-robust parameter tests and investigate whether the model misspecification adjustment can restore the validity of the standard inference in the presence of useless factors. In particular, we demonstrate that the misspecification-robust
Fig. 1, Fig. 2, Fig. 3, Fig. 4 display the main results for n = using Davidson and Mackinnon's () graphical representation to illustrate the finite-sample properties of the asymptotic and bootstrap-based tests for the ACD process with exponential, Weibull, Burr and generalized gamma errors, respectively. 1 Each figure consists of two columns of :// These tests are all asymptotic and distributed as X 2 variates. Since they do not require the computation of specific moments of the statistic, they are easy to implement and straightforward to interpret. However, they are all large sample tests and evidence on their finite sample properties is still :// Misspecification tests play an important role in detecting unreliable and inadequate economic models. This book brings together many results from the growing literature in econometrics on /_Testing_Conditional_Independence_Restrictions. “Some Tests for Misspecification in Bivariate Limited Dependent Variable Models”. Annales de l’INSEE, 59/60 (), “Wald Tests for the Independence of Stochastic Variables and Disturbance of a Single Linear Stochastic Simultaneous Equation”. Economics Letters, 17 (),