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.

Introductory Econometrics: Intuition, Proof, and Practice attempts to distill econometrics into a form that preserves its essence, but that is acceptable—and even appealing—to the student's intellectual palate. This book insists on rigor when it is essential, but it emphasizes intuition and seizes upon entertainment wherever possible. Introductory Econometrics is motivated by three beliefs. First, students are, perhaps despite themselves, interested in questions that only econometrics can answer. Second, through these answers, they can come to understand, appreciate, and even enjoy the enterprise of econometrics. Third, this text, which presents select innovations in presentation and practice, can provoke readers' interest and encourage the responsible and insightful application of econometric techniques. In particular, author Jeffrey S. Zax gives readers many opportunities to practice proofs—which are challenging, but which he has found to improve student comprehension. Learning from proofs gives readers an organic understanding of the message behind the numbers, a message that will benefit them as they come across statistics in their daily lives. An ideal core text for foundational econometrics courses, this book is appropriate for any student with a solid understanding of basic algebra—and a willingness to use that tool to investigate complicated issues.

Presents an up-to-date treatment of the models and methodologies of financial econometrics by one of the world's leading financial econometricians.

A compact, master's-level textbook on financial econometrics, focusing on methodology and including real financial data illustrations throughout. The mathematical level is purposely kept moderate, allowing the power of the quantitative methods to be understood without too much technical detail.

This highly accessible and innovative text with supporting web site uses Excel (R) to teach the core concepts of econometrics without advanced mathematics. It enables students to use Monte Carlo simulations in order to understand the data generating process and sampling distribution. Intelligent repetition of concrete examples effectively conveys the properties of the ordinary least squares (OLS) estimator and the nature of heteroskedasticity and autocorrelation. Coverage includes omitted variables, binary response models, basic time series, and simultaneous equations. The authors teach students how to construct their own real-world data sets drawn from the internet, which they can analyze with Excel (R) or with other econometric software. The accompanying web site with text support can be found at www.wabash.edu/econometrics.

Financial Econometrics Using Stata is an essential reference for graduate students, researchers, and practitioners who use Stata to perform intermediate or advanced methods. After discussing the characteristics of financial time series, the authors provide introductions to ARMA models, univariate GARCH models, multivariate GARCH models, and applications of these models to financial time series. The last two chapters cover risk management and contagion measures. After a rigorous but intuitive overview, the authors illustrate each method by interpreting easily replicable Stata examples.

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.

Taking a modern approach to the subject, this text provides students with a solid grounding in econometrics, using non-technical language wherever possible.

Introduce your students to how empirical researchers actually think about and apply econometric methods with the practical, professional approach in Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 5E. Unlike traditional texts, this book's unique presentation demonstrates how econometrics can be used to empirically study and answer questions across a variety of disciplines. A reflection of how econometric instruction has evolved, INTRODUCTORY ECONOMETRICS is organized around the type of data being analyzed with a systematic approach, where assumptions are introduced only as they are needed to obtain a certain result. This approach simplifies the exposition and makes the text's material easier for students to comprehend. Packed with timely, relevant applications the text emphasizes examples that have implications for policy or provide evidence for or against economic theories. More than 100 intriguing data sets are now available in six formats for your teaching flexibility. A wealth of new and revised instructor resources, written by the author, is provided at no cost to the instructor. The Instructor's Manual with Solutions contains answers to all problems and exercises, teaching tips on how to present the material in each chapter and also sources for each of the data files, with many suggestions on how to use them on problem sets, exams, and term papers. For the first time ever, a new Test Bank has been created to aid instructors as they teach the course. PowerPoint slides and Scientific Word slides are also new to this edition. The updated Data Set Handbook is also available to help instructors present the latest emerging developments in the field. Give your students a full understanding of how econometrics is genuinely useful for answering questions in business, policy evaluation, and forecasting environments with INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 5E. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Gain an understanding of how econometrics can answer today's questions in business, policy evaluation and forecasting with Wooldridge's INTRODUCTORY ECONOMETRICS: A MODERN APPROACH, 7E. This edition's practical, yet professional, approach demonstrates how econometrics has moved beyond a set of abstract tools to become genuinely useful for answering questions across a variety of disciplines. Information is organized around the type of data being analyzed, using a systematic approach that only introduces assumptions as they are needed. This makes the material easier to understand and, ultimately, leads to better econometric practices. Packed with relevant applications, this edition incorporates more than 100 intriguing data sets in different formats. Updates introduce the latest developments in the field, including recent advances in the so-called “causal effects” or “treatment effects” literature, for an understanding of the impact and importance of econometrics today. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.