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Full-Text Articles in Econometrics
Testing For Heteroskedasticity And Spatial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Seuck Heun Song, Jae Hyeok Kwon
Testing For Heteroskedasticity And Spatial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Seuck Heun Song, Jae Hyeok Kwon
Center for Policy Research
A panel data regression model with heteroskedastic as well as spatially correlated disturbance is considered, and a joint LM test for homoskedasticity and no spatial correlation is derived. In addition, a conditional LM test for no spatial correlation given heteroskedasticity, as well as a conditional LM test for homoskedasticity given spatial correlation, are also derived. These LM tests are compared with marginal LM tests that ignore heteroskedasticity in testing for spatial correlation, or spatial correlation in testing for homoskedasticity. Monte Carlo results show that these LM tests as well as their LR counterparts perform well even for small N and …
Testing For Random Effects And Spatial Lag Dependence In Panel Data Models, Badi H. Baltagi, Long Liu
Testing For Random Effects And Spatial Lag Dependence In Panel Data Models, Badi H. Baltagi, Long Liu
Center for Policy Research
This paper derives a joint Lagrande Multiplier (LM) test which simultaneously tests for the absence of spatial lag dependence and random individual effects in a panel data regression model. It turns out that this LM statistic is the sum of two standard LM statistics. The first one tests for the absence of spatial lag dependence ignoring the random individual effects, and the second one tests for the absence of random individual effects ignoring the spatial lag dependence. This paper also derives two conditional LM tests. The first one tests for the absence of random individual effects without ignoring the possible …
Testing For Heteroskedasticity And Serial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Byoung Cheol Jung, Seuck Heun Song
Testing For Heteroskedasticity And Serial Correlation In A Random Effects Panel Data Model, Badi H. Baltagi, Byoung Cheol Jung, Seuck Heun Song
Center for Policy Research
This paper considers a panel data regression model with heteroskedastic as well as serially correlated disturbances, and derives a joint LM test for homoskedasticity and no first order serial correlation. The restricted model is the standard random individual error component model. It also derives a conditional LM test for homoskedasticity given serial correlation, as well as a conditional LM test for no first order serial correlation given heteroskedasticity, all in the context of a random effects panel data model. Monte Carlo results show that these tests, along with their likelihood ratio alternatives, have good size and power under various forms …
Cox-Mcfadden Partial And Marginal Likelihoods For The Proportional Hazard Model With Random Effects, Jan Ondrich
Cox-Mcfadden Partial And Marginal Likelihoods For The Proportional Hazard Model With Random Effects, Jan Ondrich
Center for Policy Research
In survival analysis, Cox's name is associated with the partial likelihood technique that allows consistent estimation of proportional hazard scale parameters without specifying a duration dependence baseline. In discrete choice analysis, McFadden's name is associated with the generalized extreme-value (GEV) class of logistic choice models that relax the independence of irrelevant alternatives assumption. This paper shows that the mixed class of proportional hazard specifications allowing consistent estimation of scale and mixing parameters using partial likelihood is isomorphic to the GEV class. Independent censoring is allowed and I discuss approximations to the partial likelihood in the presence of ties. Finally, the …