### Review of Dougherty "Introduction to Econometrics" 4th edition, Oxford, 2011.

The 5th edition is already available but I don't have it.

### What I like

The book is as comprehensive as it can be, given its target audience (undergraduate programs) and Math constraints (matrix algebra is not required). It goes through all major topics usually included in such texts and has much more: three chapters on models with time series data and panel data models.

The economic side of the subject is always in focus, and that makes the book a good reference for practitioners. The Math is kept at a manageable level, to my taste. Specifically, the derivations related to simple regression are detailed, and the reader is expected to be able to handle proofs up to two pages long. Longer derivations and proofs, which are in fact a subject of journal publications, are, naturally, omitted.

Probably, the most part of the material can be taught with even less algebra, because the author provides PowerPoint slides which illuminate intuition. On the other hand, many statements sound vague without derivations, and the book presents challenges for those who want to understand everything. When my students complain that my explanation is not in the book, I tell them that they have to read between the lines. Somebody on Amazon.com said that the book is impossible to understand without instructor's help. That is occasionally true. Moreover, as a person who has taken bachelor, master's and PhD courses and given a bachelor course in Econometrics in the US, I think the level corresponds to the master's level in an average US university.

### What I don't like

In the 3rd edition, the author used the short notation for OLS estimators that all professionals and I use. In the 4th edition he switched to that awkward notation with summation signs, which made most derivations at least a quarter longer. Probably, this change was caused by the fact that students were not familiar with properties of covariances and variances. Dougherty has a Statistics review chapter for a reason.

In general, the instructor may decide whether to keep the level low or to engage at full throttle. It's not like that at my university. The book is a required reading at affiliate centers of the University of London, and we are one of them. We have an unusual practice of separating weaker students from stronger ones. I teach the stronger ones. Even in my group, half of students struggle with summation signs. I think instead of switching from the professional notation to the longer one, it would be better to adjust the prerequisite Statistics courses. The University of London lives in its own universe anyway.

The biggest challenge is not the book itself but the UoL Econometrics exam.

Christopher Dougherty visited Almaty, and we had some good time together. He said he is not the one who composes the UoL exams. Therefore, some discrepancy between the book's content and the exam questions is inevitable. However, when exams require more theory than the book has, that's not normal. For example, the theorem I prove here is not in the book.

The exams coverage is also a problem. The book, as I said, is comprehensive and almost encyclopedic for a one-year course. Every little detail may appear on the exam. Even I, after teaching this course for many years, don't remember all the details.

The exams require a much higher level of formal thinking and proficiency in algebra than the book implies. For instance, the genuine understanding of the notion of cointegration hinges upon linear independence of infinite-dimensional vectors. When I told my American friend that we give cointegration and panel data models, he was very impressed. Thank God, in the last two years panel data models have been dropped from the curriculum. The purpose of this whole site is to help Econometrics students of the UoL.

### Summary

Highly recommend: the coverage and the balance between intuition and Math can satisfy the needs of many instructors and courses.

The combination book+exam at affiliate centers of the UoL creates huge problems. If you want to use the Econometrics course as a screening device for potential Nobel laureates, that's fine. But then you have to prepare the students for the challenges of the course. Our students have two years to study Statistics. Of these two years, three semesters they spend at the AP Stats level (only intuition, no algebra or formal proofs), see Statistics 1 Guide by J. Abdey. And then in one semester they are expected to leap to the level required by Dougherty's book and UoL exams, see Statistics 2 Guide. The learning curve is flat for three semesters, steep in the fourth semester, and then the students have to fly beyond the clouds for one year!

I've been talking about this since 2011, but the decision makers at the UoL wouldn't listen to me. Formally, most prerequisites are covered in Statistics 1 and 2 (J. Abdey told me that he included in his guides what was requested by the Econometrics people of the LSE). But developing logic takes much longer than one semester. That's what nobody wants to understand.