2026-09-21T11:30:47Z https://www.ideals.illinois.edu/oai-pmh

oai:www.ideals.illinois.edu:2142/22845 2023-07-10 col_2142_5131 col_2142_14830 com_2142_5130 com_2142_14829 com_2142_8903

ETDs are only available to UIUC Users without author permission U of I Only AAI9211051 Bera, Anil K. Yoon, Mann Joong 2011-05-07T13:53:24Z 2011-05-07T13:53:24Z 10000-01-01 1991 It is well known that most of the standard specification tests are not robust when the alternative is misspecified. We consider the three types of typical misspecification encountered in econometric model specification testing, namely, complete misspecification, underspecification, and overspecification. In the case of complete misspecification the distribution under the alternative hypothesis does not belong to the data generating process (DGP), while underspecification refers to the alternative being a subset of a more general model representing the DGP. Overspecification is the case when the alternative hypothesis is overstated. Most likely, the first two types of misspecification are common in one-directional testing situation whereas the last one happens when multi-directional joint tests are applied based on an overparametrized alternative model. Following Haavelmo's work, we provide a simple example to illustrate the effects of misspecification on testing economic hypothesis. Then we find the asymptotic distributions of standard one-directional and multi-directional Lagrange multiplier (LM) tests under these three kinds of misspecification. The asymptotic relative efficiency (ARE) of the misspecified tests are also evaluated. Next using these distributions, we suggest a robust specification test under misspecified alternatives. The new test is shown to be asymptotically equivalent to Neyman's $C(\alpha)$ test. Some applications are presented to illustrate our theoretical results. "Turning to a simultaneous approach to model specification testing, we develop some joint tests of non-nested models and simultaneous departures from homoskedasticity, serial independence and normality of the disturbance terms. Locally equivalent alternative models are used to construct joint tests since they provide a convenient way to incorporate more than one type of departure from the classical conditions. The joint tests represent a simple asymptotic solution to the ""pre-testing"" problem in the context of non-nested linear regression models. Our simulation results indicate that the proposed tests have good finite sample properties." Made available in DSpace on 2011-05-07T13:53:24Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9211051.pdf: 3481232 bytes, checksum: adaea30887144bf8e74fab8fb7dc753a (MD5) Previous issue date: 1991 Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T15:00:24Z Item is restricted indefinitely. Restriction data tranferred 2014-07-01T11:28:34-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission (UMI)AAI9211051 http://hdl.handle.net/2142/22845 eng Copyright 1991 Yoon, Mann Joong Economics, Theory Model specification tests with misspecified alternatives: Some robust and simultaneous approaches text Economics Economics University of Illinois at Urbana-Champaign Dissertation Ph.D.