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Studies in Global Econometrics is a collection of essays on the use of cross-country data based on purchasing power parities. The two major applications are the development over time of per capital gross domestic products, (including that of their inequalities among countries and regions) and the fitting of cross-country demand equations for broad groups of consumer goods. The introductory chapter provides highlights of the author's work as relating to these developments. One of the main topics of the work is a system of demand equations for broad groups of consumer goods fitted by means of cross-country data. These data are from the International Comparison Program, which provides PPP-based figures for a number of years and countries. Similar data are used for the measurement of the dispersion of national per capita incomes between and within seven geographic regions.
The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed. For first-year graduate courses in Econometrics for Social Scientists. This text serves as a bridge between an introduction to the field of econometrics and the professional literature for graduate students in the social sciences, focusing on applied econometrics and theoretical concepts.
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.
This text prepares first-year graduate students and advanced undergraduates for empirical research in economics, and also equips them for specialization in econometric theory, business, and sociology. A Course in Econometrics is likely to be the text most thoroughly attuned to the needs of your students. Derived from the course taught by Arthur S. Goldberger at the University of Wisconsin-Madison and at Stanford University, it is specifically designed for use over two semesters, offers students the most thorough grounding in introductory statistical inference, and offers a substantial amount of interpretive material. The text brims with insights, strikes a balance between rigor and intuition, and provokes students to form their own critical opinions. A Course in Econometrics thoroughly covers the fundamentals--classical regression and simultaneous equations--and offers clear and logical explorations of asymptotic theory and nonlinear regression. To accommodate students with various levels of preparation, the text opens with a thorough review of statistical concepts and methods, then proceeds to the regression model and its variants. Bold subheadings introduce and highlight key concepts throughout each chapter. Each chapter concludes with a set of exercises specifically designed to reinforce and extend the material covered. Many of the exercises include real microdata analyses, and all are ideally suited to use as homework and test questions.
"This book examines the application of econometric methods as used by researchers in academia, public policy, and areas in social science and business"--
Exploring and understanding the analysis of economic development is essential as global economies continue to experience extreme fluctuation. Econometrics brings together statistical methods for practical content and economic relations. Econometric Methods for Analyzing Economic Development is a comprehensive collection that focuses on various regions and their economies at a pivotal time when the majority of nations are struggling with stabilizing their economies. Outlining areas such as employment rates, utilization of natural resources, and regional impacts, this collection of research is an excellent tool for scholars, academics, and professionals looking to expand their knowledge on today’s turbulent and changing economy.
Why Care About Causation?
For courses in Introductory Econometrics Engaging applications bring the theory and practice of modern econometrics to life. Ensure students grasp the relevance of econometrics with Introduction to Econometrics-the text that connects modern theory and practice with motivating, engaging applications. The Third Edition Update maintains a focus on currency, while building on the philosophy that applications should drive the theory, not the other way around. This program provides a better teaching and learning experience-for you and your students. Here's how: Personalized learning with MyEconLab-recommendations to help students better prepare for class, quizzes, and exams-and ultimately achieve improved comprehension in the course. Keeping it current with new and updated discussions on topics of particular interest to today's students. Presenting consistency through theory that matches application. Offering a full array of pedagogical features. Note: You are purchasing a standalone product; MyEconLab does not come packaged with this content. If you would like to purchase both the physical text and MyEconLab search for ISBN-10: 0133595420 ISBN-13: 9780133595420. That package includes ISBN-10: 0133486877 /ISBN-13: 9780133486872 and ISBN-10: 0133487679/ ISBN-13: 9780133487671. MyEconLab is not a self-paced technology and should only be purchased when required by an instructor.
The second edition of a comprehensive state-of-the-art graduate level text on microeconometric methods, substantially revised and updated. The second edition of this acclaimed graduate text provides a unified treatment of two methods used in contemporary econometric research, cross section and data panel methods. By focusing on assumptions that can be given behavioral content, the book maintains an appropriate level of rigor while emphasizing intuitive thinking. The analysis covers both linear and nonlinear models, including models with dynamics and/or individual heterogeneity. In addition to general estimation frameworks (particular methods of moments and maximum likelihood), specific linear and nonlinear methods are covered in detail, including probit and logit models and their multivariate, Tobit models, models for count data, censored and missing data schemes, causal (or treatment) effects, and duration analysis. Econometric Analysis of Cross Section and Panel Data was the first graduate econometrics text to focus on microeconomic data structures, allowing assumptions to be separated into population and sampling assumptions. This second edition has been substantially updated and revised. Improvements include a broader class of models for missing data problems; more detailed treatment of cluster problems, an important topic for empirical researchers; expanded discussion of "generalized instrumental variables" (GIV) estimation; new coverage (based on the author's own recent research) of inverse probability weighting; a more complete framework for estimating treatment effects with panel data, and a firmly established link between econometric approaches to nonlinear panel data and the "generalized estimating equation" literature popular in statistics and other fields. New attention is given to explaining when particular econometric methods can be applied; the goal is not only to tell readers what does work, but why certain "obvious" procedures do not. The numerous included exercises, both theoretical and computer-based, allow the reader to extend methods covered in the text and discover new insights.