Panel Data Econometrics: Advanced Texts in Econometrics
In: The economic journal: the journal of the Royal Economic Society, Band 114, Heft 499, S. F558-F559
ISSN: 1468-0297
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In: The economic journal: the journal of the Royal Economic Society, Band 114, Heft 499, S. F558-F559
ISSN: 1468-0297
In: Journal of economic studies, Band 27, Heft 4/5, S. 316-325
ISSN: 1758-7387
Econometrics labours under the same limitations as economics: it rests on unrealistic hypotheses (and non‐operational concepts) and is isolated from other sciences. It should try to test economic hypotheses and estimate relationships that constitute theory, notwithstanding the poor available data. Many econometrists are no longer interested in measurement, but in art for art's sake: econometrics becomes abstract mathematisation.
In: Mathematical social sciences, Band 27, Heft 1, S. 115
In: International journal of forecasting, Band 5, Heft 4, S. 612-614
ISSN: 0169-2070
In: International journal of forecasting, Band 12, Heft 2, S. 306-308
ISSN: 0169-2070
In: Statistica Neerlandica, Band 45, Heft 2, S. 73-84
ISSN: 1467-9574
Unobservable variables in econometrics are represented in one of three ways: by variables contaminated by measurement errors, by proxy variables, or by various manifest indicators and/or causes. This paper contains a discussion of models involving each of these representations, and highlights certain interesting implications that have been insufficiently emphasized or completely unrecognized in the literature.
In: International journal of forecasting, Band 20, Heft 1, S. 139
ISSN: 0169-2070
In: International journal of forecasting, Band 10, Heft 1, S. 163-164
ISSN: 0169-2070
In: The Canadian journal of economics: the journal of the Canadian Economics Association = Revue canadienne d'économique, Band 35, Heft 4, S. 615-645
ISSN: 1540-5982
The astonishing increase in computer performance over the past two decades has made it possible for economists to base many statistical inferences on simulated, or bootstrap, distributions rather than on distributions obtained from asymptotic theory. In this paper, I review some of the basic ideas of bootstrap inference. I discuss Monte Carlo tests, several types of bootstrap test, and bootstrap confidence intervals. Although bootstrapping often works well, it does not do so in every case. Inférence par la méthode d'auto–amorçage (bootstrap) en économétrie. L'incroyable accroissement dans la puissance des ordinateurs au cours des deux dernières décennies a permis aux économistes de fonder plusieurs inférences sur des distributions simulées, ou obtenues par auto–amorçage, plutôt que sur des distributions obtenues par la théorie aymptotique. Dans ce texte, l'auteur passe en revue quelques–unes des idées de base de l'inférence par la méthode d'auto–amorçage. Le texte discute aussi des tests de Monte Carlo, de divers types de tests et des intervalles de confiance obtenus par la méthode d'auto–amorçage. Même si le processus d'auto–amorçage fonctionne souvent bien, cela n'est pas toujours le cas.
In: International journal of forecasting, Band 5, Heft 1, S. 143-144
ISSN: 0169-2070
In: International journal of forecasting, Band 4, Heft 2, S. 298-300
ISSN: 0169-2070
In: International journal of forecasting, Band 4, Heft 4, S. 614-616
ISSN: 0169-2070
In: Economica, Band 60, Heft 239, S. 369
In: International journal of forecasting, Band 4, Heft 4, S. 614
ISSN: 0169-2070
In: The economic journal: the journal of the Royal Economic Society, Band 113, Heft 488, S. F397-F398
ISSN: 1468-0297