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A Concise Introduction to Econometrics: An Intuitive Guide
This book is an ideal introduction for beginning students of econometrics that assumes only basic familiarity with matrix algebra and calculus. It features practical questions which can be answered using econometric methods and models. Focusing on a limited number of the most basic and widely used methods, the book reviews the basics of econometrics before concluding with a number of recent empirical case studies. The volume is an intuitive illustration of what econometricians do when faced with practical questions.
132 pages, Paperback
First published January 1, 2002
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Displaying 1 - 3 of 3 reviews
August 21, 2015
A Demonstrable Problem
Philip Hans Franses takes the reader through the most elementary concepts of econometrics, or as much as is possible in such a short book. This is well supplemented by a series of practical research questions in various economic disciplines, which are then ‘demonstrated� for the reader by showing how they can be answered using econometric methods and models.
This makes the book a good introduction to the empirical practices of the ‘real� econometric world, which, as the author takes pains to emphasize is slightly different from the typical text book assumed world where the data is reliable, the questions are already framed and the variables are not suspect, with only the modeling (even the models are often taken for granted in standard textbooks!) and the statistical tools occupying center stage.
This format of a typical econometrics textbook has its origin in a traditional view of econometrics, where the were supposed to match (mainly macro-) economic theories to data, often with an explicit goal to substantiate the theory. In the unlucky event that the failed to provide evidence in favor of the theory, it was usually perceived that perhaps the data were wrong or the estimation method was incorrect, implying that the econometrician could start all over again.
This view assumed that most aspects of a model, like the relevant variables, the way they are measured, the data themselves, and the functional form, are already available to the econometrician, and the only thing s/he needs to do is to fit the model to the data. The model components are usually assumed to originate from an (often macro-) economic theory, and there is great confidence in its validity.
A consequence of this confidence is that if the data cannot be summarized by this model, the econometric textbook first advises us to consider alternative estimation techniques. Finally, and conditional upon a successful result, the resultant empirical econometric model is used to confirm (and perhaps in some cases, to disconfirm) the thoughts summarized in the economic theory.
The author instead realizes that the most common refrain from newbie researches out in the field is “where do I start?� and takes his discussion forward from there. With this introduction that shows the process of econometric research in simplistic but essential detail, Franses makes sure that the student will be less clueless when confronting a possible opportunity to pose a useful question.
The most valuable chapter in the book (Chapter 4) addresses this problem even more directly and contains step-by-step discussion of sample research case studies. These are meant to indicate that the main ideas in the book shine through present-day applied econometrics. These illustrations suggest that there is a straight line from understanding how to handle the basic to handling regime-switching models and a multinomial probit model, for example.
To conclude, I quote the concluding paragraph from the introduction, which I simply loved. It is a valuable economic exercise to indulge in, to strengthen the analytic muscles or even just to pass time!
Finally, as a way of examining whether a reader has appreciated the content of this book, one might think about the following exercise. Take a newspaper or a news magazine and look for articles on economic issues. In many articles are reports on decisions which have been made, forecasts that have been generated, and questions that have been answered. Take one of these articles, and then ask whether these decisions, forecasts, and answers could have been based on the outcomes of an econometric model. What kind of data could one have used? What could the model have looked like? Would one have great confidence in these outcomes, and how does this extend to the reported decisions, forecasts, and answers?
December 24, 2018
Even too intuitive, at times. Too light-weight, in my opinion. However, the things that were discussed, I loved the approach to them.
October 26, 2021
Pretty decent read as a mathematician, but there were two issues I found quite early on - one, Franses advises readers to read another textbook instead of this book, as he himself thinks that his book may not be adequate enough; and two, he quickly delves into advanced matters in statistics - which makes this supposed introduction unsuitable for the general public (and also, econometricians (especially from the Econometric Society) usually have "no connections to societies of professional mathematicians or statisticians").
Contents:
1. Introduction
2. A few basic tools
3. Econometrics, a guided tour
4. Seven case studies
5. Conclusion
Would read again though, maybe after I finish my modules in statistics at university, and update this review accordingly.
Contents:
1. Introduction
2. A few basic tools
3. Econometrics, a guided tour
4. Seven case studies
5. Conclusion
Would read again though, maybe after I finish my modules in statistics at university, and update this review accordingly.
Displaying 1 - 3 of 3 reviews
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