Estimation Of Dynamic Econometric Models With Errors In Variables
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Estimation of Dynamic Econometric Models with Errors in Variables
Author: Jaime Terceiro Lomba
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
A new procedure for the maximum-likelihood estimation of dynamic econometric models with errors in both endogenous and exogenous variables is presented in this monograph. A complete analytical development of the expressions used in problems of estimation and verification of models in state-space form is presented. The results are useful in relation not only to the problem of errors in variables but also to any other possible econometric application of state-space formulations.
Omitted Variable Tests and Dynamic Specification
Author: Björn Schmolck
language: en
Publisher: Springer Science & Business Media
Release Date: 2012-12-06
This book deals with the omitted variable test for a multivariate time-series regression model. The empirical motivation is the homogeneity test for a consumer demand system. The consequences of using a dynamically misspecified omitted variable test are shown in detail. The analysis starts with the univariate t-test and is then extended to the multivariate regression system. The small sample performance of the dynamically correctly specified omitted variable test is analysed by simulation. Two classes of tests are considered: versions of the likelihood ratio test and the robust Wald test which is based on a heteroskedasticity and autocorrelation consistent variance-covariance estimator (HAC).
Applied Econometrics with R
Author: Christian Kleiber
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-12-10
R is a language and environment for data analysis and graphics. It may be considered an implementation of S, an award-winning language initially - veloped at Bell Laboratories since the late 1970s. The R project was initiated by Robert Gentleman and Ross Ihaka at the University of Auckland, New Zealand, in the early 1990s, and has been developed by an international team since mid-1997. Historically, econometricians have favored other computing environments, some of which have fallen by the wayside, and also a variety of packages with canned routines. We believe that R has great potential in econometrics, both for research and for teaching. There are at least three reasons for this: (1) R is mostly platform independent and runs on Microsoft Windows, the Mac family of operating systems, and various ?avors of Unix/Linux, and also on some more exotic platforms. (2) R is free software that can be downloaded and installed at no cost from a family of mirror sites around the globe, the Comprehensive R Archive Network (CRAN); hence students can easily install it on their own machines. (3) R is open-source software, so that the full source code is available and can be inspected to understand what it really does, learn from it, and modify and extend it. We also like to think that platform independence and the open-source philosophy make R an ideal environment for reproducible econometric research.