Instructor Reviews
I would like to wholeheartedly praise this book. I am totally impressed by its depth, clarity and applications of the book. The exercises are highly applied and coming from industry-relevant questions which will be of highly interests for economics, business, or even data science students. The Online Resources are great with clear and detailed codes and instructions in R, Stata, and Python, which provide a rich range of approaches for students. I will highly recommend this book for my students if they would like to develop the tools and understandings of econometrics and data science techniques. I would like to thanks Bekes and Kezdi for their excellent book. It’s one of the best textbook in econometrics and data science that I’ve ever read.
Dr. Canh Dang , LSE Fellow, Department of Economics, London School of Economics (UK)
I have reviewed the book, and I think it is excellent. I plan on using it as a supplemental book for my Business Strategy and Analytics module here at UCL School of Management. I find it to be quite exhaustive and very well organized. It is very consistent with how I organize my module. I think they covered nearly everything that I would want covered in a book like this.
Dr. Anil Doshi, Assistant Professor, UCL School of Management (UK)
“The structure of the book is revolutionary with respect to existing textbooks, both in terms of coverage and approach. In Part I (Data Exploration), rather than emphasising/pivoting around formal statistical procedures or properties of data generation processes, the authors focus on conceptual presentation and case studies, and yet, the intuitive concepts are rigorously framed. In Part II (Regression Analysis), I found Chapter 8 (‘Complicated Patterns and Messy Data’) particularly important to bridge the abstract, ideal configuration of regression analysis with practitioners’ problems emerging when facing actual data. Parts III and IV introduce frameworks allowing to predict (Part III) or explain (Part IV) a target variable. These latter parts evince epistemological depth in the authors’ conception of applied statistics, as well as an unrivalled, up-to-date organisation of topics, according to emerging trends in data science. Technical details are kept in “Under the hood” sections, allowing students to delve into more formal aspects of the topics presented. Finally, the distinction between ‘Practice Questions’ and ‘Data Exercises’ allows instructors to fine-tune practical sessions according to a differential emphasis on conceptual vis-a-vis hands-on aspects of module delivery.”
Dr. Ariel Wirkierman, Lecturer in Economics, Goldsmiths, University of London (UK)
“Data Analysis for Business, Economics and Policy is an excellent and much needed companion for practitioners in various policy fields. It is not simply a textbook on a broad range of methods, but a hands-on guide for data analysis in practice. It guides the reader firmly through the process of actual empirical analysis, demonstrating how to answer policy and business questions through a broad set of case studies. While covering a large variety of topics, the book never loses focus of the most acute problems practitioners are likely to face. It should be definitely included in the welcome package of every junior data analyst.”
Dr. G. Koltay, senior economist in the European Commission’s DG Competition Chief Economist Team (Belgium/EU).
“I have be using it as a supplementary textbook to a course in International economics at the Master level at Luiss University in Rome. The course has a data analysis component an the book is just what I needed. Updated, complete, full of practical examples and including R, Python and Stata codes. It is a pleasure to read and with a little bit of adaptation could fit well in any applied course in the social sciences.
I recommend it!”
Luca De Benedictis, Professor of International Economics at University of Macerata and LUISS Rome (Italy)
“I think what is amazing about it is not only how you „rush“ through important topics, which allows it to cover a lot in a short period of time. But what is really good is how you teach students to handle data, with recommendations on what to do with outliers etc. but also with lots of hands on.
As a teacher - and now I am not sure I can mention it - I found the slides of course amazing. I don’t know how much life time you saved me with that!!”
Alexandra Avdeenko, Uni Heidelberg, Research Director at the Center for Evaluation and Development (Germany)
