Dependent-variable

A nice review of MLE-based methods for categorical, limited, and ordinal dependent variables. Most social science data is best thought of as categorical, ordinal, etc., not interval, and so a readable treatment of one approach to the analysis of such data that does not rely on intervality assumptions is worthwhile.

The author has a very clear explanation of topics such as how MLE works, some numerical methods for maximizing, various tests associated with MLEs, etc., all written at a intermediate level. It's not too advanced so readers won't be driven off but also isn't a cookbook. Lots of nice examples throughout.

It's definitely in standard regression mode, which is not to say bad, just limited. It doesn't cover (or indeed discuss) topics such as categorical multivariate analysis, alternate loss functions for estimating categorical or ordinal regressions, including alternating least squares approaches or quantile regression, categorical or ordinal time series, or instrumental variables.... It's not the last word on the topic, but is certainly a solid first word.

Since I do statistical modeling in industry, I was looking for a good book on Logistic regression that would give me a deep understanding of the subject; one that also had wide coverage (Poison regression, Tobit models, ..etc.). I decided on J. Scott Long's book, after considering Applied Logistic Regression by Hosmer and Lemeshow, and Limited Dependent and Qualitative Variables in Econometrics by Maddala. I must say I am very pleased with my choice. The topics are very clear, and the math is used as an aid to understanding, and you don't get bogged down in the math. It is a pleasure to read the book.

This book is especially useful to start understanding topics like ordered probit, multinomial logit, negative binomial regression and zero-inflated count models. Although it starts with a chapter on the linear regression model, it should not be mistaken for an introductory text. I would certainly advise readers with limited background in regression models to start with other books, like the one of Wooldridge (Introductory Econometrics). The quality of this book must be that I've yet to see a book that explains these topics more intuitively. That is not to say it is easy or without mathematics, it's not. It just looks like the mathematics is only used for better comprehension, not to give you the full proof. Furthermore, while reading it you get the feeling that the author understands what you, as a researcher, are interested in. This allows him to focus on the topics of interest, like model selection and testing and interpretation of output. So although this is not a cookbook, it may well be the closest thing to it, especially in combination with his new book on applying these models in Stata. It is a pity that the author stops short of non-parametric models (next edition?).

the biggest problem with this book is the poor index. it is pretty much only by author, with almost no subject listings. other than that this is one of the best guides to applied econometrics that i have seen.

Any graduate student must have this book on his shleves...Maddala explains probit, logit, tobit regressions very clearly....Examples are concrete and based on daily problems....A must have!!!

This book is a classic, having educated generations of Economists on how to do micro-econometrics. But, published in 1983, it is rather out of date and crying out for a new edition.

Ph.D students and researchers in applied microeconomics will enjoy this book, because this book is, to my knowledge, the first reasonably coherent and complete overview of semi-(non)parametric microeconometrics.

translated from Kwantitatieve Methoden 55, 1997 May.

The book does a very good job of surveying the literature on semiparametric methods for modeling choice. This is an important field, and is not well covered in other textbooks. Of course the book requires some sophistication on the part of the user, namely a graduate level backround in econometrics.

This is a good book. But the publisher (intentionally?) forgot to mention it is a translation of the 1990 French version. Instead, the publisher dated the book 2000. The lastest paper cited in the book was 1987. The publisher failed to mention the book's origin anywhere on its own web until you buy the book and find it on the inside cover.