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. Unlike traditional texts, this book'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. The author has organized the book's presentation around the type of data being analyzed with 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, the text incorporates more than 100 data sets in different formats. Updates introduce the latest developments in the field, including the recent advances in the so-called "causal effects" or "treatment effects," to provide a complete understanding of the impact and importance of econometrics today.

This title has been adapted for use in Europe, the Middle East and Africa and has been tailored to meet the demands of today's lecturers and students. Jeffrey M. Wooldridge's Introduction to Econometrics shows how econometrics is a useful tool for answering questions in business, policy evaluation and forecasting environments. Packed with timely, relevant applications, the text incorporates close to 100 intriguing data sets, available in six formats, with appendices and questions available online. Unique organization pioneered by the author clearly presents applications for today's students. This comprehensive econometrics text pioneered the approach of explicitly covering cross-sectional applications first, followed by time series applications, and, ultimately, panel data applications in the advanced chapters. Practical application prepares students to use econometrics in business today. This unique, comprehensive text applies econometrics to actual real business problems, demonstrating how each method answers a particular issue facing researchers who are analyzing non-experimental data.