Seemingly Unrelated Regression Equations Models

Seemingly Unrelated Regression Equations Models
Author: Virendera K. Srivastava
Publisher: CRC Press
Total Pages: 392
Release: 2020-08-13
Genre: Mathematics
ISBN: 1000105725

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This book brings together the scattered literature associated with the seemingly unrelated regression equations (SURE) model used by econometricians and others. It focuses on the theoretical statistical results associated with the SURE model.

Seemingly Unrelated Regression Equations Models

Seemingly Unrelated Regression Equations Models
Author: Virendera K. Srivastava
Publisher: CRC Press
Total Pages: 398
Release: 1987-05-29
Genre: Mathematics
ISBN: 9780824776107

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The seemingly unrelated regression equations model; The least squares estimator and its variants; Approximate destribution theory for feasible generalized least squares estimators; Exact finite-sample properties of feasible generalized least squares estimators; Iterative estimators; Shrinkage estimators; Autoregressive disturbances; Heteroscedastic disturbances; Constrained error covariance structures; Prior information; Some miscellaneous topics.

Seemingly Unrelated Regression Equations Models

Seemingly Unrelated Regression Equations Models
Author: Virendera K. Srivastava
Publisher: CRC Press
Total Pages: 398
Release: 2020-08-14
Genre: Mathematics
ISBN: 1000148939

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This book brings together the scattered literature associated with the seemingly unrelated regression equations (SURE) model used by econometricians and others. It focuses on the theoretical statistical results associated with the SURE model.

Econometrics

Econometrics
Author: Badi Hani Baltagi
Publisher: Springer Science & Business Media
Total Pages: 426
Release: 2002
Genre: Business & Economics
ISBN: 9783540435013

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As well as specification testing, Gauss-Newton regressions and regression diagnostics. In addition, the book features a set of empirical illustrations that demonstrate some of the basic results. The empirical exercises are solved using several econometric software packages.

Inference in Seemingly Unrelated Regression Equations Models

Inference in Seemingly Unrelated Regression Equations Models
Author: Nagabhushana Rao R.V.S.S.
Publisher: LAP Lambert Academic Publishing
Total Pages: 316
Release: 2013
Genre:
ISBN: 9783659364945

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This book has brought out the current estimation methods, stressing the basic inferential methods and discussing the various related problems arising in applying the methods to SURE models. Firstly, the SURE model with first-order scalar autoregressive errors; secondly, an Estimation procedure has been developed for SURE model with first-order scalar autoregressive errors; thirdly, the SURE model with first-order vector autoregressive errors has been specified and a new inferential techniques has been developed for its estimation; fourthly, an adaptable Ridge Regression estimation technique has been proposed for the SURE model under the problem of multicollinearity; finally, two new test procedures have been developed for testing nested and non-nested general linear hypotheses about the parameters to the SURE modeLS

Applied Econometrics with R

Applied Econometrics with R
Author: Christian Kleiber
Publisher: Springer Science & Business Media
Total Pages: 229
Release: 2008-12-10
Genre: Business & Economics
ISBN: 0387773185

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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.

Dynamic Linear Models with R

Dynamic Linear Models with R
Author: Giovanni Petris
Publisher: Springer Science & Business Media
Total Pages: 258
Release: 2009-06-12
Genre: Mathematics
ISBN: 0387772383

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State space models have gained tremendous popularity in recent years in as disparate fields as engineering, economics, genetics and ecology. After a detailed introduction to general state space models, this book focuses on dynamic linear models, emphasizing their Bayesian analysis. Whenever possible it is shown how to compute estimates and forecasts in closed form; for more complex models, simulation techniques are used. A final chapter covers modern sequential Monte Carlo algorithms. The book illustrates all the fundamental steps needed to use dynamic linear models in practice, using R. Many detailed examples based on real data sets are provided to show how to set up a specific model, estimate its parameters, and use it for forecasting. All the code used in the book is available online. No prior knowledge of Bayesian statistics or time series analysis is required, although familiarity with basic statistics and R is assumed.

Using R for Principles of Econometrics

Using R for Principles of Econometrics
Author: Constantin Colonescu
Publisher: Lulu.com
Total Pages: 278
Release: 2017-12-28
Genre: Business & Economics
ISBN: 1387473611

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This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.