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Now in its third edition, Essential Econometric Techniques: A Guide to Concepts and Applications is a concise, student-friendly textbook which provides an introductory grounding in econometrics, with an emphasis on the proper application and interpretation of results. Drawing on the author’s extensive teaching experience, this book offers intuitive explanations of concepts such as heteroskedasticity and serial correlation, and provides step-by-step overviews of each key topic. This new edition contains more applications, brings in new material including a dedicated chapter on panel data techniques, and moves the theoretical proofs to appendices. After Chapter 7, students will be able to design and conduct rudimentary econometric research. The next chapters cover multicollinearity, heteroskedasticity, and autocorrelation, followed by techniques for time-series analysis and panel data. Excel data sets for the end-of-chapter problems are available as a digital supplement. A solutions manual is also available for instructors, as well as PowerPoint slides for each chapter. Essential Econometric Techniques shows students how economic hypotheses can be questioned and tested using real-world data, and is the ideal supplementary text for all introductory econometrics courses.
This economical text is intended for use as a universal supplement to introductory econometrics courses. This edition contains two new chapters on economic forecasting. Extensive online supplements include teaching PowerPoints, solutions to test questions/problems, new instructor questions, and software programs with data to download.
This economical text is intended for use as a universal supplement to introductory econometrics courses. This edition contains two new chapters on economic forecasting. Extensive online supplements include teaching PowerPoints, solutions to test questions/problems, new instructor questions, and software programs with data to download.
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.
Score your highest in econometrics? Easy. Econometrics can prove challenging for many students unfamiliar with the terms and concepts discussed in a typical econometrics course. Econometrics For Dummies eliminates that confusion with easy-to-understand explanations of important topics in the study of economics. Econometrics For Dummies breaks down this complex subject and provides you with an easy-to-follow course supplement to further refine your understanding of how econometrics works and how it can be applied in real-world situations. An excellent resource for anyone participating in a college or graduate level econometrics course Provides you with an easy-to-follow introduction to the techniques and applications of econometrics Helps you score high on exam day If you're seeking a degree in economics and looking for a plain-English guide to this often-intimidating course, Econometrics For Dummies has you covered.
A comprehensive guide to financial econometrics Financial econometrics is a quest for models that describe financial time series such as prices, returns, interest rates, and exchange rates. In Financial Econometrics, readers will be introduced to this growing discipline and the concepts and theories associated with it, including background material on probability theory and statistics. The experienced author team uses real-world data where possible and brings in the results of published research provided by investment banking firms and journals. Financial Econometrics clearly explains the techniques presented and provides illustrative examples for the topics discussed. Svetlozar T. Rachev, PhD (Karlsruhe, Germany) is currently Chair-Professor at the University of Karlsruhe. Stefan Mittnik, PhD (Munich, Germany) is Professor of Financial Econometrics at the University of Munich. Frank J. Fabozzi, PhD, CFA, CFP (New Hope, PA) is an adjunct professor of Finance at Yale University’s School of Management. Sergio M. Focardi (Paris, France) is a founding partner of the Paris-based consulting firm The Intertek Group. Teo Jasic, PhD, (Frankfurt, Germany) is a senior manager with a leading international management consultancy firm in Frankfurt.
In this short and very practical 2002 introduction to econometrics Philip Hans Franses guides the reader through the essential concepts of econometrics. Central to the book are practical questions in various economic disciplines, which can be answered using econometric methods and models. The book focuses on a limited number of the essential, most widely used methods, before going on to review the basics of econometrics. The book ends with a number of case studies drawn from recent empirical work to provide an intuitive illustration of what econometricians do when faced with practical questions. Throughout the book Franses emphasises the importance of specification, evaluation and implementation of models appropriate to the data. Assuming basic familiarity only with matrix algebra and calculus the book is designed to appeal as either a short stand-alone introduction for students embarking on an empirical research project or as a supplement to any standard introductory textbook.
This best-selling textbook addresses the need for an introduction to econometrics specifically written for finance students. Key features: • Thoroughly revised and updated, including two new chapters on panel data and limited dependent variable models • Problem-solving approach assumes no prior knowledge of econometrics emphasising intuition rather than formulae, giving students the skills and confidence to estimate and interpret models • Detailed examples and case studies from finance show students how techniques are applied in real research • Sample instructions and output from the popular computer package EViews enable students to implement models themselves and understand how to interpret results • Gives advice on planning and executing a project in empirical finance, preparing students for using econometrics in practice • Covers important modern topics such as time-series forecasting, volatility modelling, switching models and simulation methods • Thoroughly class-tested in leading finance schools. Bundle with EViews student version 6 available. Please contact us for more details.
A Guide to Econometric Methods for the Energy-Growth Nexus presents, explains and compares all the available econometrics methods pertinent to the energy-growth nexus. Chapters cover methods and applications, starting with older econometric methods and moving toward new ones. Each chapter presents the method and facts about its applications, providing step-by-step explanations about the ways the method meets the demands of the field. In addition, applied case studies and practical research steps are included to enhance the learning process. By touching on all relevant econometric methods for the energy-growth nexus, this book gives energy-growth researchers and students all they need to tackle the subject matter. - Presents econometric methods for short- and long-term forecasting - Provides methods and step-by-step explanations on the ways the method meets the demands of the field - Contains applied case studies and practical research steps
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.