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Titlebook: Econometrics; Badi H. Baltagi Textbook 20023rd edition Springer-Verlag Berlin Heidelberg 2002 Microeconometrics.econometrics.panel data.re

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21#
發(fā)表于 2025-3-25 05:10:49 | 只看該作者
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22#
發(fā)表于 2025-3-25 08:08:03 | 只看該作者
23#
發(fā)表于 2025-3-25 12:06:31 | 只看該作者
Violations of the Classical AssumptionsIn this chapter, we relax the assumptions made in Chapter 3 one by one and study the effect of that on the OLS estimator. In case the OLS estimator is no longer a viable estimator, we derive an alternative estimator and propose some tests that will allow us to check whether this assumption is violated.
24#
發(fā)表于 2025-3-25 16:40:52 | 只看該作者
25#
發(fā)表于 2025-3-26 00:04:28 | 只看該作者
26#
發(fā)表于 2025-3-26 03:53:30 | 只看該作者
Seemingly Unrelated Regressionsany univariate results could be carried over to apply to the multivariate system and the analysis of the multivariate system is much simplified notationally, algebraically and, conceptually. “ Read the interview of Professor Arnold Zellner by Rossi (1989, p. 292).
27#
發(fā)表于 2025-3-26 06:26:30 | 只看該作者
28#
發(fā)表于 2025-3-26 10:24:45 | 只看該作者
Bastian Schirmer,Roland Seifert-Jenkins and . (VAR) methods for time-series analysis. Section 14.5 considers a random walk model and various tests for the existence of a .. Section 14.6 studies . and . versus . models. Section 14.7 gives a simple explanation of the concept of . and illustrates it with an economic example. Finally, section 14.8 looks at . (ARCH) time-series.
29#
發(fā)表于 2025-3-26 13:24:20 | 只看該作者
Valentina Coca,Katrin Nink,Helmut Schr?derhe concepts of independence, Bayes Theorem and several continuous and discrete probability distributions. These distributions include: the Bernoulli, Binomial, Poisson, Geometric, Uniform, Normal, Gamma, Chi-squared (χ.), Exponential, Beta, . and . distributions.
30#
發(fā)表于 2025-3-26 20:22:00 | 只看該作者
Basic Statistical Conceptshe concepts of independence, Bayes Theorem and several continuous and discrete probability distributions. These distributions include: the Bernoulli, Binomial, Poisson, Geometric, Uniform, Normal, Gamma, Chi-squared (χ.), Exponential, Beta, . and . distributions.
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