Statistical Foundations of Econometric Modelling

Statistical Foundations of Econometric Modelling PDF Author: Aris Spanos
Publisher: Cambridge University Press
ISBN: 9780521269124
Category : Business & Economics
Languages : en
Pages : 722

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Book Description
A thorough foundation in probability theory and statistical inference provides an introduction to the underlying theory of econometrics that motivates the student at a intuitive as well as a formal level.

Statistical Foundations of Econometric Modelling

Statistical Foundations of Econometric Modelling PDF Author: Aris Spanos
Publisher: Cambridge University Press
ISBN: 9780521269124
Category : Business & Economics
Languages : en
Pages : 722

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Book Description
A thorough foundation in probability theory and statistical inference provides an introduction to the underlying theory of econometrics that motivates the student at a intuitive as well as a formal level.

Introduction to the Mathematical and Statistical Foundations of Econometrics

Introduction to the Mathematical and Statistical Foundations of Econometrics PDF Author: Herman J. Bierens
Publisher: Cambridge University Press
ISBN: 9780521542241
Category : Business & Economics
Languages : en
Pages : 356

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Book Description
This book is intended for use in a rigorous introductory PhD level course in econometrics.

Probability Theory and Statistical Inference

Probability Theory and Statistical Inference PDF Author: Aris Spanos
Publisher: Cambridge University Press
ISBN: 1107185149
Category : Business & Economics
Languages : en
Pages : 787

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Book Description
This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.

Econometric Modeling

Econometric Modeling PDF Author: David F. Hendry
Publisher: Princeton University Press
ISBN: 1400845653
Category : Business & Economics
Languages : en
Pages : 378

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Book Description
Econometric Modeling provides a new and stimulating introduction to econometrics, focusing on modeling. The key issue confronting empirical economics is to establish sustainable relationships that are both supported by data and interpretable from economic theory. The unified likelihood-based approach of this book gives students the required statistical foundations of estimation and inference, and leads to a thorough understanding of econometric techniques. David Hendry and Bent Nielsen introduce modeling for a range of situations, including binary data sets, multiple regression, and cointegrated systems. In each setting, a statistical model is constructed to explain the observed variation in the data, with estimation and inference based on the likelihood function. Substantive issues are always addressed, showing how both statistical and economic assumptions can be tested and empirical results interpreted. Important empirical problems such as structural breaks, forecasting, and model selection are covered, and Monte Carlo simulation is explained and applied. Econometric Modeling is a self-contained introduction for advanced undergraduate or graduate students. Throughout, data illustrate and motivate the approach, and are available for computer-based teaching. Technical issues from probability theory and statistical theory are introduced only as needed. Nevertheless, the approach is rigorous, emphasizing the coherent formulation, estimation, and evaluation of econometric models relevant for empirical research.

Foundations of Econometrics

Foundations of Econometrics PDF Author: Albert Madansky
Publisher: Elsevier
ISBN: 1483275256
Category : Business & Economics
Languages : en
Pages : 275

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Book Description
Advanced Textbooks in Economics, Volume 7: Foundations of Econometrics focuses on the principles, processes, methodologies, and approaches involved in the study of econometrics. The publication examines matrix theory and multivariate statistical analysis. Discussions focus on the maximum likelihood estimation of multivariate normal distribution parameters, point estimation theory, multivariate normal distribution, multivariate probability distributions, Euclidean spaces and linear transformations, orthogonal transformations and symmetric matrices, and determinants. The manuscript then ponders on linear expected value models and simultaneous equation estimation. Topics include random exogenous variables, maximum likelihood estimation of a single equation, identification of a single equation, linear stochastic difference equations, and errors-in-variables models. The book takes a look at a prolegomenon to econometric model building, tests of hypotheses in econometric models, multivariate statistical analysis, and simultaneous equation estimation. Concerns include maximum likelihood estimation of a single equation, tests of linear hypotheses, testing for independence, and causality in economic models. The publication is a valuable source of data for economists and researchers interested in the foundations of econometrics.

The Foundations of Econometric Analysis

The Foundations of Econometric Analysis PDF Author: David F. Hendry
Publisher: Cambridge University Press
ISBN: 9780521588706
Category : Business & Economics
Languages : en
Pages : 582

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Book Description
Collection of classic papers by pioneer econometricians

Econometric Foundations Pack with CD-ROM

Econometric Foundations Pack with CD-ROM PDF Author: Ron Mittelhammer (Prof.)
Publisher: Cambridge University Press
ISBN: 9780521623940
Category : Business & Economics
Languages : en
Pages : 794

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Book Description
The text and accompanying CD-ROM develop step by step a modern approach to econometric problems. They are aimed at talented upper-level undergraduates, graduate students, and professionals wishing to acquaint themselves with the pinciples and procedures for information processing and recovery from samples of economic data. The text fully provides an operational understanding of a rich set of estimation and inference tools, including tradional likelihood based and non-traditional non-likelihood based procedures, that can be used in conjuction with the computer to address economic problems.

Econometrics

Econometrics PDF Author: Hamid Seddighi
Publisher: Psychology Press
ISBN: 9780415156455
Category : Business & Economics
Languages : en
Pages : 422

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Book Description
Recognising the fact that A level mathematics is no longer a necessary prerequisite for economics courses, this text introduces this key subdivision of economics to an audience who might otherwise have been deterred by its complexity.

A Guide to Econometrics

A Guide to Econometrics PDF Author: Peter Kennedy
Publisher: John Wiley & Sons
ISBN: 1405182571
Category : Business & Economics
Languages : en
Pages : 608

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Book Description
Dieses etwas andere Lehrbuch bietet keine vorgefertigten Rezepte und Problemlösungen, sondern eine kritische Diskussion ökonometrischer Modelle und Methoden: voller überraschender Fragen, skeptisch, humorvoll und anwendungsorientiert. Sein Erfolg gibt ihm Recht.

Econometric Modelling with Time Series

Econometric Modelling with Time Series PDF Author: Vance Martin
Publisher: Cambridge University Press
ISBN: 0521139813
Category : Business & Economics
Languages : en
Pages : 925

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Book Description
"Maximum likelihood estimation is a general method for estimating the parameters of econometric models from observed data. The principle of maximum likelihood plays a central role in the exposition of this book, since a number of estimators used in econometrics can be derived within this framework. Examples include ordinary least squares, generalized least squares and full-information maximum likelihood. In deriving the maximum likelihood estimator, a key concept is the joint probability density function (pdf) of the observed random variables, yt. Maximum likelihood estimation requires that the following conditions are satisfied. (1) The form of the joint pdf of yt is known. (2) The specification of the moments of the joint pdf are known. (3) The joint pdf can be evaluated for all values of the parameters, 9. Parts ONE and TWO of this book deal with models in which all these conditions are satisfied. Part THREE investigates models in which these conditions are not satisfied and considers four important cases. First, if the distribution of yt is misspecified, resulting in both conditions 1 and 2 being violated, estimation is by quasi-maximum likelihood (Chapter 9). Second, if condition 1 is not satisfied, a generalized method of moments estimator (Chapter 10) is required. Third, if condition 2 is not satisfied, estimation relies on nonparametric methods (Chapter 11). Fourth, if condition 3 is violated, simulation-based estimation methods are used (Chapter 12). 1.2 Motivating Examples To highlight the role of probability distributions in maximum likelihood estimation, this section emphasizes the link between observed sample data and 4 The Maximum Likelihood Principle the probability distribution from which they are drawn"-- publisher.