Template-Type: ReDIF-Paper 1.0
Author-Name: Anil Bera
Author-Name-First: Anil
Author-Name-Last: Bera
Author-Name: Walter Sosa Escudero 
Author-Name-First: Walter
Author-Name-Last: Sosa Escudero
Author-Name: Mann Yoon
Author-Name-First: Mann
Author-Name-Last: Yoon
Title: Test for the Error Component Model in the Presence of Local Misspecification 
Abstract: It is well known that most of the standard speci¯cation tests are not valid when the alternative hypothesis is misspecified. This is particularly true in the error componentmodel, when one tests for either random e®ects or serial correlation without taking account of the presence of the other effect. In this paper we study the size and power of the standard Rao's score tests analytically and by simulation when the data is contaminated by local misspecification. These tests are adversely affected under misspecification. We suggest simple procedures to test for random effects (or serial correlation) in the presence of local serial correlation (or random effects), and these tests require ordinary least squares residuals only. Our Monte Carlo results demonstrate that the suggested tests have good finite sample properties for local misspecification, and in some cases even for far distant misspecification. Our tests are also capable of detecting the right direction of the departure from the null hypothesis. We also provide some empirical illustrations to highlight the usefulness of our tests.
Length:  29 pages
Creation-Date:  2000-03
File-URL: https://www.depeco.econo.unlp.edu.ar/wp/wp-content/uploads/2017/05/doc22.pdf
File-Format: Application/pdf
Handle: RePEc:akh:wpaper:022