What do you think?
Rate this book
Introduction to Econometrics
Introduction to Econometrics provides an introduction to econometrics using analytical and intuitive methods of the classical linear regression model. Mathematical notation is kept simple and step-by-step explanations of mathematical proofs are provided to facilitate learning. The text also
provided to facilitate learning. The text also contains a large number of practical exercises, enabling students to practice what they have learned.
This new edition has been substantially updated and revised with the inclusion of new material on specification tests, binary choice models, tobit analysis, sample selection bias, nonstationary time series, and unit root tests and basic cointegration. The new edition is also accompanied by a
website with Powerpoint slideshows giving a parallel graphical treatment of topics treated in the book, cross-section and time series data sets, manuals for practical exercises, and lecture note extending the text.
provided to facilitate learning. The text also contains a large number of practical exercises, enabling students to practice what they have learned.
This new edition has been substantially updated and revised with the inclusion of new material on specification tests, binary choice models, tobit analysis, sample selection bias, nonstationary time series, and unit root tests and basic cointegration. The new edition is also accompanied by a
website with Powerpoint slideshows giving a parallel graphical treatment of topics treated in the book, cross-section and time series data sets, manuals for practical exercises, and lecture note extending the text.
480 pages, Paperback
First published March 12, 1992
8 people are currently reading
102 people want to read
Ratings & Reviews
Friends & Following
Create a free account to discover what your friends think of this book!
Community Reviews
Displaying 1 - 2 of 2 reviews
October 19, 2024
I finished reading (Introduction to Econometrics) by Professor Christopher Doughtery!
Here's my review and a couple of things I've learned.
This book serves as "a year-long undergraduate course in econometrics" for Econometrics students. I'm not an Econometrics student, I'm an Engineering student; I finished it in exactly 3 months. My approach to going through this book is for it to serve as a "Ground truth" and a backbone to my journey in data science, statistical learning, and maybe finance. While the book served its purpose well, for the most part, it was very frustrating as a self-learning resource. The ground-up approach of this book is, in my opinion, not suited for someone trying to get a comprehensive understanding of Econometrics as a social science, but rather someone intending to learn and apply those techniques as they go with no particular interest in the realization of the topics, problems, and most importantly the fruit of this field. in a conversation with an econ graduate friend of mine about Econometrics, he said that his problem with this subject is the fact that as you go through the material, it seems like what you learn contradicts what came before it; while I slightly disagree, I reckon learning Econometric methods as solutions to real-world problems with all the theory and traditional development left behind is a much better path for someone of my background.
In a nutshell, always putting the data first, in terms of collection, data is either (Cross-sectional, Time series, or Panel data); there is a standard regression model for each type, each with its assumptions and trade-offs, eventually used for many regression usages.
The book starts with a revision of a few prerequisites, then simple regression and its properties, Multiple regression and its intricacies, Time series regression and its problems, and a very short introduction to panel data.
Overall it's a solid book that deserves taking a look at if you are into Statistical learning, Data science, Quant Finance, or of course, an aspiring Econometrician!
Here's my review and a couple of things I've learned.
This book serves as "a year-long undergraduate course in econometrics" for Econometrics students. I'm not an Econometrics student, I'm an Engineering student; I finished it in exactly 3 months. My approach to going through this book is for it to serve as a "Ground truth" and a backbone to my journey in data science, statistical learning, and maybe finance. While the book served its purpose well, for the most part, it was very frustrating as a self-learning resource. The ground-up approach of this book is, in my opinion, not suited for someone trying to get a comprehensive understanding of Econometrics as a social science, but rather someone intending to learn and apply those techniques as they go with no particular interest in the realization of the topics, problems, and most importantly the fruit of this field. in a conversation with an econ graduate friend of mine about Econometrics, he said that his problem with this subject is the fact that as you go through the material, it seems like what you learn contradicts what came before it; while I slightly disagree, I reckon learning Econometric methods as solutions to real-world problems with all the theory and traditional development left behind is a much better path for someone of my background.
In a nutshell, always putting the data first, in terms of collection, data is either (Cross-sectional, Time series, or Panel data); there is a standard regression model for each type, each with its assumptions and trade-offs, eventually used for many regression usages.
The book starts with a revision of a few prerequisites, then simple regression and its properties, Multiple regression and its intricacies, Time series regression and its problems, and a very short introduction to panel data.
Overall it's a solid book that deserves taking a look at if you are into Statistical learning, Data science, Quant Finance, or of course, an aspiring Econometrician!
April 30, 2016
Got to love textbook humour : "Let us consider an even simpler example of a random variable, the number obtained when you throw just one die. (Pedantic note : this is the singular of the word whose plural is dice. Two dice, one die. Like two mice, one mie.)(Well, two mice, one mouse. Like two hice, one house. Peculiar language, English.)"
Displaying 1 - 2 of 2 reviews