A Guide to Modern Econometrics PDF Download

Author: Marno Verbeek
Publisher: John Wiley & Sons
ISBN: 0470517697
Category : Business & Economics
Languages : en
Pages : 489

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Book Description
This revised and updated edition of A Guide to Modern Econometrics continues to explore a wide range of topics in modern econometrics by focusing on what is important for doing and understanding empirical work. It serves as a guide to alternative techniques with the emphasis on the intuition behind the approaches and their practical relevance. New material includes Monte Carlo studies, weak instruments, nonstationary panels, count data, duration models and the estimation of treatment effects. Features of this book include: Coverage of a wide range of topics, including time series analysis, cointegration, limited dependent variables, panel data analysis and the generalized method of moments Empirical examples drawn from a wide variety of fields including labour economics, finance, international economics, environmental economics and macroeconomics. End-of-chapter exercises review key concepts in light of empirical examples.

Author: Patrick Mair
Publisher: Waxmann Verlag
ISBN: 9783830966111
Category : Log-linear models
Languages : en
Pages : 168

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Book Description
Log-linear models can be used to analyze the relationships among categorical variables. The nature of these relationships is described based on the interpretation. This framework includes the usual standard models, but also nonstandard and non-hierarchical models. Alexander von Eye, Michigan State University.

Author: Maxwell L. King
Publisher: Routledge
ISBN: 1351140663
Category : Business & Economics
Languages : en
Pages : 550

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Book Description
Originally published in 1987. This collection of original papers deals with various issues of specification in the context of the linear statistical model. The volume honours the early econometric work of Donald Cochrane, late Dean of Economics and Politics at Monash University in Australia. The chapters focus on problems associated with autocorrelation of the error term in the linear regression model and include appraisals of early work on this topic by Cochrane and Orcutt. The book includes an extensive survey of autocorrelation tests; some exact finite-sample tests; and some issues in preliminary test estimation. A wide range of other specification issues is discussed, including the implications of random regressors for Bayesian prediction; modelling with joint conditional probability functions; and results from duality theory. There is a major survey chapter dealing with specification tests for non-nested models, and some of the applications discussed by the contributors deal with the British National Accounts and with Australian financial and housing markets.

Author: Michael H. Kutner
Publisher: McGraw-Hill/Irwin
ISBN: 9780072386882
Category : Mathematics
Languages : en
Pages : 1396

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Book Description
Linear regression with one predictor variable; Inferences in regression and correlation analysis; Diagnosticis and remedial measures; Simultaneous inferences and other topics in regression analysis; Matrix approach to simple linear regression analysis; Multiple linear regression; Nonlinear regression; Design and analysis of single-factor studies; Multi-factor studies; Specialized study designs.

Author: Christian Kleiber
Publisher: Springer Science & Business Media
ISBN: 0387773185
Category : Business & Economics
Languages : en
Pages : 229

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Book Description
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.

Author: Paul Turner
Publisher: Mercury Learning and Information
ISBN: 1683926587
Category : Computers
Languages : en
Pages : 438

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Book Description
This book covers the econometric methods necessary for a practicing applied economist or data analyst. This requires both an understanding of statistical theory and how it is used in actual applications. Chapters 1 to 9 present the material concerned with basic statistical theory. Chapters 10 to 13 introduce a number of topics which form the basis of more advanced option modules, such as time series methods in applied econometrics. To get the most out of these topics, companion files include Excel datasets and 4-color figures. It includes pull down menus to graph the data, calculate sample statistics and estimate regression equations. FEATURES: Integration of econometrics methods with statistical foundations Worked examples of all models considered in the text Includes Excel datasheets to facilitate estimation and application of models Features instructor ancillaries for use as a textbook The companion files and/or instructor resources are available online by emailing the publisher with proof of purchase at [email protected].

Author: Basilio de Bragança Pereira
Publisher: Springer
ISBN: 3662537362
Category : Mathematics
Languages : en
Pages : 105

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Book Description
This book discusses the problem of model choice when the statistical models are separate, also called nonnested. Chapter 1 provides an introduction, motivating examples and a general overview of the problem. Chapter 2 presents the classical or frequentist approach to the problem as well as several alternative procedures and their properties. Chapter 3 explores the Bayesian approach, the limitations of the classical Bayes factors and the proposed alternative Bayes factors to overcome these limitations. It also discusses a significance Bayesian procedure. Lastly, Chapter 4 examines the pure likelihood approach. Various real-data examples and computer simulations are provided throughout the text.

Author: Stephen W. Raudenbush
Publisher: SAGE
ISBN: 9780761919049
Category : Mathematics
Languages : en
Pages : 520

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Book Description
New edition of a text in which Raudenbush (U. of Michigan) and Bryk (sociology, U. of Chicago) provide examples, explanations, and illustrations of the theory and use of hierarchical linear models (HLM). New material in Part I (Logic) includes information on multivariate growth models and other topics.

Author: Wai-sum Chan
Publisher: World Scientific
ISBN: 1783261668
Category : Mathematics
Languages : en
Pages : 396

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Book Description
Contents:Heavy-Tailed and Nonlinear Continuous-Time ARMA Models for Financial Time Series (P J Brockwell)Nonlinear State Space Model Approach to Financial Time Series with Time-Varying Variance (G Kitagawa & S Sato)Nonparametric Estimation and Bootstrap for Financial Time Series (J-P Kreiβ)A Note on Kernel Estimation in Integrated Time Series (Y-C Xia et al.)Stylized Facts on the Temporal and Distributional Properties of Absolute Returns: An Update (C W J Granger et al.)Volatility Computed by Time Series Operators at High Frequency (U A Müller)Missing Values in ARFIMA Models (W Palma)Second Order Tail Effects (C G de Vries)Bayesian Estimation of Stochastic Volatility Model via Scale Mixtures Distributions (S T B Choy & C M Chan)On a Smooth Transition Double Threshold Model (Y N Lee & W K Li)Interval Prediction of Financial Time Series (B Cheng & H Tong)A Decision Theoretic Approach to Forecast Evaluation (C W J Granger & M H Pesaran)Portfolio Management and Market Risk Quantification Using Neural Networks (J Franke)Detecting Structural Changes Using Genetic Programming with an Application to the Greater-China Stock Markets (X B Zhang et al.)and other papers Readership: Researchers in finance, time series analysis, economics and actuarial science, as well as investment bankers, stock market analysts and risk managers. Keywords:Proceedings;Workshop;Statistics;Finance;Hongkong (China)

Author: Bhaskara B. Rao
Publisher: Springer
ISBN: 1349235296
Category : Business & Economics
Languages : en
Pages : 247

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Book Description
`This most commendable volume brings together a set of papers which permits ready access to the means of estimating quantitative relationships using cointegration and error correction procedures. Providing the data to show fully the basis for calculation, this approach is an excellent perception of the needs of senior undergraduates and graduate students.' - Professor W.P. Hogan, The University of Sydney Applied economists, with modest econometric background, are now desperately looking for expository literature on the unit roots and cointegration techniques. This volume of expository essays is written for them. It explains in a simple style various tests for the existence of unit roots and how to estimate cointegration relationships. Original data are given to enable easy replications. Limitations of some existing unit root tests are also discussed.