--- product_id: 831742545 title: "A Course in Econometrics" price: "1053 zł" currency: PLN in_stock: true reviews_count: 5 url: https://www.desertcart.pl/products/831742545-a-course-in-econometrics store_origin: PL region: Poland --- # A Course in Econometrics **Price:** 1053 zł **Availability:** ✅ In Stock ## Quick Answers - **What is this?** A Course in Econometrics - **How much does it cost?** 1053 zł with free shipping - **Is it available?** Yes, in stock and ready to ship - **Where can I buy it?** [www.desertcart.pl](https://www.desertcart.pl/products/831742545-a-course-in-econometrics) ## Best For - Customers looking for quality international products ## Why This Product - Free international shipping included - Worldwide delivery with tracking - 15-day hassle-free returns ## Description 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. Review: The best econometrics text, period! - I would give this book 6 stars if I could. I think James Heckman has called this book a masterpiece, and I would fully agree. This is a unique text that takes a distinctive approach -- one which, in my opinion, is essential for really understanding econometrics. I am a PhD in economics, and I explored a great many econometrics texts in my quest to get a better handle on the subject. I found that while I can follow all the proofs in standard texts like Greene, I didn't really get the intuition behind how things worked. All that changed once I picked up Goldberger. Goldberger takes what I would call the "identification" approach (an approach emphasized by other well regarded econometricians such as Heckman and Manski). The identification part of econometrics is the link between a model and the probability distribution function of observed variables. If you had an infinitely large sample, so you knew the joint probability distribution exactly, how does that help you identify some interesting parameter in your model? Secondary to this is the issue that in real life, you have only finite samples, and you estimate parameters of the joint pdf only with uncertainty. This is where standard errors and confidence intervals come in. But the identification part is really the core part of econometrics, and is very simple. Most econometrics texts mix identification and estimation, and so unnecessarily confuse the issue. For instance, in the standard approach, the fact that OLS estimates are biased when there is measurement error in the independent variable is usually directly proved by algebraically manipulating the OLS estimator. But this can be seen in the identification part alone, without any reference directly to the OLS estimator. Goldberger makes clear that the OLS estimator is still a great estimator of the best linear predictor (BLP) of the distribution. But the BLP no longer tells you what you need to know given that there is measurement error. So your attention is rightfully directed to why the BLP no longer tells you what you want when there is measurement error, rather than why the OLS estimator is biased. This really simplifies and clarifies everything for me. (Note: I don't recall whether Goldberger directly discusses measurement error; this was just an example to highlight the difference in appraoch). While it is true that this book was published nearly 20 years ago and may not be up to date with all the latest techniques, it is still the best way to learn econometrics, in my opinion. Once you really understand the fundamentals, everything else becomes a clearer. Review: Exceptional - This book offers a rare bridge between undergraduate and graduate econometrics. The book is well written, with consistent notation, clear exposition, and provides coverage of topics too advanced for undergrad curricula and often not covered by graduate instructors. I highly recommend this book. It will provide you with the necessary foundation to tackle Green, Cameron & Trivedi, etc. This book should be mandatory reading for all first year graduate students in the social sciences. ## Technical Specifications | Specification | Value | |---------------|-------| | Amazon Bestseller | #255,535 in Foreign Language Books ( See Top 100 in Foreign Language Books ) #341 in Econometrics #863 in Accounting & Finance Economics #6,057 in Mathematics (Foreign Language Books) | | Customer Reviews | 4.3 out of 5 stars 17 Your Review | ## Images ![A Course in Econometrics - Image 1](https://m.media-amazon.com/images/I/51vglGniJWL.jpg) ## Customer Reviews ### ⭐⭐⭐⭐⭐ The best econometrics text, period! *by B***. on March 17, 2010* I would give this book 6 stars if I could. I think James Heckman has called this book a masterpiece, and I would fully agree. This is a unique text that takes a distinctive approach -- one which, in my opinion, is essential for really understanding econometrics. I am a PhD in economics, and I explored a great many econometrics texts in my quest to get a better handle on the subject. I found that while I can follow all the proofs in standard texts like Greene, I didn't really get the intuition behind how things worked. All that changed once I picked up Goldberger. Goldberger takes what I would call the "identification" approach (an approach emphasized by other well regarded econometricians such as Heckman and Manski). The identification part of econometrics is the link between a model and the probability distribution function of observed variables. If you had an infinitely large sample, so you knew the joint probability distribution exactly, how does that help you identify some interesting parameter in your model? Secondary to this is the issue that in real life, you have only finite samples, and you estimate parameters of the joint pdf only with uncertainty. This is where standard errors and confidence intervals come in. But the identification part is really the core part of econometrics, and is very simple. Most econometrics texts mix identification and estimation, and so unnecessarily confuse the issue. For instance, in the standard approach, the fact that OLS estimates are biased when there is measurement error in the independent variable is usually directly proved by algebraically manipulating the OLS estimator. But this can be seen in the identification part alone, without any reference directly to the OLS estimator. Goldberger makes clear that the OLS estimator is still a great estimator of the best linear predictor (BLP) of the distribution. But the BLP no longer tells you what you need to know given that there is measurement error. So your attention is rightfully directed to why the BLP no longer tells you what you want when there is measurement error, rather than why the OLS estimator is biased. This really simplifies and clarifies everything for me. (Note: I don't recall whether Goldberger directly discusses measurement error; this was just an example to highlight the difference in appraoch). While it is true that this book was published nearly 20 years ago and may not be up to date with all the latest techniques, it is still the best way to learn econometrics, in my opinion. Once you really understand the fundamentals, everything else becomes a clearer. ### ⭐⭐⭐⭐⭐ Exceptional *by D***Y on May 27, 2017* This book offers a rare bridge between undergraduate and graduate econometrics. The book is well written, with consistent notation, clear exposition, and provides coverage of topics too advanced for undergrad curricula and often not covered by graduate instructors. I highly recommend this book. It will provide you with the necessary foundation to tackle Green, Cameron & Trivedi, etc. This book should be mandatory reading for all first year graduate students in the social sciences. ### ⭐⭐⭐ Blah. *by C***R on November 28, 2013* This book does not have the best explanations and there is little to no examples but the basic material is there. --- ## Why Shop on Desertcart? - 🛒 **Trusted by 1.3+ Million Shoppers** — Serving international shoppers since 2016 - 🌍 **Shop Globally** — Access 737+ million products across 21 categories - 💰 **No Hidden Fees** — All customs, duties, and taxes included in the price - 🔄 **15-Day Free Returns** — Hassle-free returns (30 days for PRO members) - 🔒 **Secure Payments** — Trusted payment options with buyer protection - ⭐ **TrustPilot Rated 4.5/5** — Based on 8,000+ happy customer reviews **Shop now:** [https://www.desertcart.pl/products/831742545-a-course-in-econometrics](https://www.desertcart.pl/products/831742545-a-course-in-econometrics) --- *Product available on Desertcart Poland* *Store origin: PL* *Last updated: 2026-05-24*