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Introduction to Econometrics
A basic introduction written in non-technical language, this remarkable text keeps mathematical demands to a minimum so that students can spend less time on technicalities and more on understanding basic concepts. With many exercises in the text, a floppy disk containing data sets on
expenditure and price for different commodities, an unusually detailed teacher's manual with additional exercises and masters for overhead transparencies, and spectacular video graphic sequences, this uniquely rich introductory text will transform the teaching of the subject.
expenditure and price for different commodities, an unusually detailed teacher's manual with additional exercises and masters for overhead transparencies, and spectacular video graphic sequences, this uniquely rich introductory text will transform the teaching of the subject.
416 pages, Hardcover
First published March 12, 1992
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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