Applied Econometrics Syllabus
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Applied Econometrics with R
Author: Christian Kleiber
language: en
Publisher: Springer Science & Business Media
Release Date: 2008-12-10
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.
Econometrics by Example
Author: Damodar Gujarati
language: en
Publisher: Bloomsbury Publishing
Release Date: 2014-11-20
Damodar Gujarati is the author of bestselling econometrics textbooks used around the world. In his latest book, Econometrics by Example, Gujarati presents a unique learning-by-doing approach to the study of econometrics. Rather than relying on complex theoretical discussions and complicated mathematics, this book explains econometrics from a practical point of view, with each chapter anchored in one or two extended real-life examples. The basic theory underlying each topic is covered and an appendix is included on the basic statistical concepts that underlie the material, making Econometrics by Example an ideally flexible and self-contained learning resource for students studying econometrics for the first time. The book includes: - a wide-ranging collection of examples, with data on mortgages, exchange rates, charitable giving, fashion sales and more - a clear, step-by-step writing style that guides you from model formulation, to estimation and hypothesis-testing, through to post-estimation diagnostics - coverage of modern topics such as instrumental variables and panel data - extensive use of Stata and EViews statistical packages with reproductions of the outputs from these packages - an appendix discussing the basic concepts of statistics - end-of-chapter summaries, conclusions and exercises to reinforce your learning - a companion website containing PowerPoint slides and a full solutions manual to all exercises for instructors, and downloadable data sets and chapter summaries for students.
Econometric Methods with Applications in Business and Economics
Nowadays applied work in business and economics requires a solid understanding of econometric methods to support decision-making. Combining a solid exposition of econometric methods with an application-oriented approach, this rigorous textbook provides students with a working understanding and hands-on experience of current econometrics. Taking a 'learning by doing' approach, it covers basic econometric methods (statistics, simple and multiple regression, nonlinear regression, maximum likelihood, and generalized method of moments), and addresses the creative process of model building with due attention to diagnostic testing and model improvement. Its last part is devoted to two major application areas: the econometrics of choice data (logit and probit, multinomial and ordered choice, truncated and censored data, and duration data) and the econometrics of time series data (univariate time series, trends, volatility, vector autoregressions, and a brief discussion of SUR models, panel data, and simultaneous equations). · Real-world text examples and practical exercise questions stimulate active learning and show how econometrics can solve practical questions in modern business and economic management. · Focuses on the core of econometrics, regression, and covers two major advanced topics, choice data with applications in marketing and micro-economics, and time series data with applications in finance and macro-economics. · Learning-support features include concise, manageable sections of text, frequent cross-references to related and background material, summaries, computational schemes, keyword lists, suggested further reading, exercise sets, and online data sets and solutions. · Derivations and theory exercises are clearly marked for students in advanced courses. This textbook is perfect for advanced undergraduate students, new graduate students, and applied researchers in econometrics, business, and economics, and for researchers in other fields that draw on modern applied econometrics.