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| Author | : Hugo Kruiniger |
| Publisher | : |
| Total Pages | : 42 |
| Release | : 1998 |
| Genre | : Economics |
| ISBN | : |
| Author | : Hugo Kruiniger |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2002 |
| Genre | : |
| ISBN | : |
This paper considers inference procedures for two types of dynamic linear panel data models with fixed effects (FE). First, it shows that the closures of stationary ARMAFE models can be consistently estimated by Conditional Maximum Likelihood Estimators and it derives their asymptotic distributions. Then it presents an asymptotically equivalent Minimum Distance Estimator which permits an analytic comparison between the CMLE for the ARFE (1) model and the GMM estimators that have been considered in the literature. The CMLE is shown to be asymptotically less efficient than the most efficient GMM estimator when N approaches the limit infinity but T is fixed. Under normality some of the moment conditions become asymptotically redundant and the CMLE attains the Cramer-Rao lowerbound when T approaches the limit infinity as well. The paper also presents likelihood based unit root tests. Finally, the properties of CML, GMM, and Modified ML estimators for dynamic panel data models that condition on the initial observations are studied and compared. It is shown that for finite T the MMLE is less efficient than the most efficient GMM estimator.
| Author | : Maurice J. G. Bun |
| Publisher | : |
| Total Pages | : 0 |
| Release | : 2017 |
| Genre | : |
| ISBN | : |
We analyse the finite sample properties of maximum likelihood estimators for dynamic panel data models. In particular, we consider transformed maximum likelihood (TML) and random effects maximum likelihood (RML) estimation. We show that TML and RML estimators are solutions to a cubic first-order condition in the autoregressive parameter. Furthermore, in finite samples both likelihood estimators might lead to a negative estimate of the variance of the individual-specific effects. We consider different approaches taking into account the non-negativity restriction for the variance. We show that these approaches may lead to a solution different from the unique global unconstrained maximum. In an extensive Monte Carlo study we find that this issue is non-negligible for small values of T and that different approaches might lead to different finite sample properties. Furthermore, we find that the Likelihood Ratio statistic provides size control in small samples, albeit with low power due to the flatness of the log-likelihood function. We illustrate these issues modelling US state level unemployment dynamics.
| Author | : Francesco Bartolucci |
| Publisher | : |
| Total Pages | : 31 |
| Release | : 2010 |
| Genre | : |
| ISBN | : |
We show how the dynamic logit model for binary panel data may be approximated by a quadratic exponential model. Under the approximating model, simple sufficient statistics exist for the subject-specific parameters introduced to capture the unobserved heterogeneity between subjects. The latter must be distinguished from the state dependence which is accounted for by including the lagged response variable among the regressors. By conditioning on the sufficient statistics, we derive a pseudo conditional likelihood estimator for the structural parameters of the dynamic logit model which is very simple to compute. Asymptotic properties of this estimator are derived. Simulation results show that the estimator is competitive in terms of efficiency with estimators very recently proposed in the econometric literature. We also show how the approach may be exploited to construct a Wald-type test for state dependence.
| Author | : Zhen Ma |
| Publisher | : |
| Total Pages | : 114 |
| Release | : 2012 |
| Genre | : |
| ISBN | : 9781267684585 |
This thesis consists of two chapters. Chapter one summarizes three estimators of dynamic panel data models: Generalized Method of Moments (GMM) with fixed effects, Wooldridge Conditional Maximum Likelihood (CML) with random effects and a Maximum Simulated Likelihood (MSL) random effects dynamic probit. Chapter two presents their applications and empirical findings. I examine the impact of the large price increases in cigarettes after the Master Settlement Agreement (MSA) on drinking behavior using data from the Panel Study of Income Dynamics (PSID). Alcohol consumption, drinking participation and heavy drinking participation (three or more drinks per day) are considered for the full sample, as well as for sub-samples stratified by age group and gender. Estimation results are relatively stable across estimators. I find that the cross-price effects of cigarettes on alcohol consumption are insignificant showing that averaging on all consumption levels, the number of drinks consumed per day is not affected by the increases in cigarette prices; and that the cross-price effects of cigarettes on drinking participation are mostly positive and significant, indicating drinking is an economic substitute for smoking; also, cigarette prices do not affect heavy drinking prevalence.
| Author | : Chung-Jung Lee |
| Publisher | : |
| Total Pages | : 404 |
| Release | : 2000 |
| Genre | : Binary system (Mathematics) |
| ISBN | : |
| Author | : Cheng Hsiao |
| Publisher | : |
| Total Pages | : 27 |
| Release | : 1998 |
| Genre | : |
| ISBN | : |
| Author | : William Gould |
| Publisher | : Stata Press |
| Total Pages | : 352 |
| Release | : 2010-10-27 |
| Genre | : Mathematics |
| ISBN | : 9781597180788 |
Maximum Likelihood Estimation with Stata, Fourth Edition is written for researchers in all disciplines who need to compute maximum likelihood estimators that are not available as prepackaged routines. Readers are presumed to be familiar with Stata, but no special programming skills are assumed except in the last few chapters, which detail how to add a new estimation command to Stata. The book begins with an introduction to the theory of maximum likelihood estimation with particular attention on the practical implications for applied work. Individual chapters then describe in detail each of the four types of likelihood evaluator programs and provide numerous examples, such as logit and probit regression, Weibull regression, random-effects linear regression, and the Cox proportional hazards model. Later chapters and appendixes provide additional details about the ml command, provide checklists to follow when writing evaluators, and show how to write your own estimation commands.
| Author | : Marc Nerlove |
| Publisher | : Cambridge University Press |
| Total Pages | : 388 |
| Release | : 2005-11-10 |
| Genre | : Business & Economics |
| ISBN | : 9780521022460 |
This volume collects seven classic essays on panel data econometrics, and a cogent essay on the history of the subject.
| Author | : Kazuhiko Hayakawa |
| Publisher | : |
| Total Pages | : 40 |
| Release | : 2014 |
| Genre | : |
| ISBN | : |
