Author : Aris Spanos
Publisher : Cambridge University Press
Page : 722 pages
File Size : 42,14 MB
Release : 1986-10-30
Category : Business & Economics
ISBN : 9780521269124
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.
Author : Herman J. Bierens
Publisher : Cambridge University Press
Page : 356 pages
File Size : 29,75 MB
Release : 2004-12-20
Category : Business & Economics
ISBN : 9780521542241
This book is intended for use in a rigorous introductory PhD level course in econometrics.
Author : Aris Spanos
Publisher : Cambridge University Press
Page : 787 pages
File Size : 11,69 MB
Release : 2019-09-19
Category : Business & Economics
ISBN : 1107185149
This empirical research methods course enables informed implementation of statistical procedures, giving rise to trustworthy evidence.
Author : David F. Hendry
Publisher : Princeton University Press
Page : 378 pages
File Size : 38,69 MB
Release : 2012-06-21
Category : Business & Economics
ISBN : 1400845653
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.
Author : Albert Madansky
Publisher : Elsevier
Page : 275 pages
File Size : 18,80 MB
Release : 2014-07-22
Category : Business & Economics
ISBN : 1483275256
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.
Author : David F. Hendry
Publisher : Cambridge University Press
Page : 582 pages
File Size : 22,63 MB
Release : 1997-02-20
Category : Business & Economics
ISBN : 9780521588706
Collection of classic papers by pioneer econometricians
Author : Ron Mittelhammer (Prof.)
Publisher : Cambridge University Press
Page : 794 pages
File Size : 10,86 MB
Release : 2000-07-28
Category : Business & Economics
ISBN : 9780521623940
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.
Author : Hamid Seddighi
Publisher : Psychology Press
Page : 422 pages
File Size : 20,87 MB
Release : 2000
Category : Business & Economics
ISBN : 9780415156455
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.
Author : Peter Kennedy
Publisher : John Wiley & Sons
Page : 608 pages
File Size : 18,85 MB
Release : 2008-02-19
Category : Business & Economics
ISBN : 1405182571
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.
Author : Vance Martin
Publisher : Cambridge University Press
Page : 925 pages
File Size : 49,49 MB
Release : 2013
Category : Business & Economics
ISBN : 0521139813
"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.
