Reddit reviews Introductory Econometrics: A Modern Approach (Upper Level Economics Titles)

Both time series and regression are not strictly econometric methods per se, and there are a range of wonderful statistics textbooks that detail them. If you're looking for methods more closely aligned with econometrics (e.g. difference in difference, instrumental variables) then the recommendation for Angrist 'Mostly Harmless Econometrics' is a good one. Another oft-prescribed econometric text that goes beyond Angrist is Wooldridge 'Introductory Econometrics: A Modern Approach'.

For a very well considered and basic approach to statistics up to regression including an excellent treatment of probability theory and the basic assumptions of statistical methodology, Andy Field (and co's) books 'Discovering Statistics Using...' (SPSS/SAS/R) are excellent.

Two excellent all-rounders are Cohen and Cohen 'Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences' and Gelman and Hill 'Data Analysis Using Regression and Multilevel/Hierarchical Modelling' although I would suggest both are more advanced than I am guessing you need right now.

For time series I can recommend Rob Hyndman's book/s on forecasting (online copy freely available)

For longitudinal data analysis I really like Judith Singer's book 'Applied Longitudinal Data Analysis'.

It sounds however as if you're looking for a bit of a book to explain why you would want to use one method over another. In my experience I wanted to know this when I was just starting. It really comes down to your own research questions and the available data. For example I had to learn Longitudinal/fixed/random effects modelling because I had to do a project with a longitudinal survey. Only after I put it into practice (and completed my stats training) did I come to understand why the modelling I used was appropriate.

Wooldridge's introductory text is the standard.

I'm a Political Methodologist; I'm happy to give you some help. It would be useful to know what your mathematical background is, and what sort of things you're interested in doing. You have to understand, to me, this question is a little bit like "I'm interested in American Politics; suggest an introductory text, please." There's a huge variety of stuff going on here, it's hard to know where to start.

Do you want to be able to read statistics wrt PoliSci? Or are you interested in figuring out how everything works, so that you can create / replicate?

If you want something very undergraduate centric, my undergrad research methods class used the Kellstedt and Whitten book. It was fine, but obviously very rudimentary. It will get you to understand some of the big picture type stuff, as well as some of the simple statistical nuts and bolts you'd want to understand. This class also used the everpresent King, Keohane and Verba text, which is oriented around qualitative work, but Gary King is the foremost quantitative methodologist in the discipline, so it's still pretty good (and "qualitative" certainly doesn't mean "non-rigorous" -- it's cited a lot because it really delves into deeply into research design). That said, I don't remember a whole lot about this class anymore, and I haven't looked in these books for ages. My feeling is that both of these books will probably be close to what you're looking for -- they're oriented around intuition and identifying the main issues in inference in the social sciences, without getting too bogged down in all of the math.

That said, if you have more math background, I'd suggest Mostly Harmless Econometrics which is often used as a first year graduate level quant methods book. It's absolutely fantastic, but it isn't easy if you don't have the math background. It may also assume some preexisting rudimentary probability or statistical knowledge. I'd also suggest the Morgan and Winship. These two books are structured more around causal inference, which is a subtle reframing of the whole "statistics in the social sciences".

For more nuts and bolts econometrics, Baby Wooldridge is one of the standards. I think it's pretty often used in undergrad econ classes.

In general, though, statistics is statistics, so if you want to learn it, find an appropriate level of statistics/econometrics book.

Take a look at those books in your library/online/etc and see if any of them are what you're looking for.

>but then throw in things

I'm a statistician. It's common for us to look down on social studies :P anything that isn't supported by some kind of legitimate measurement makes our blood boil.

As for that obvious hatred: you should look inwards for that. I hold no feelings towards feminism; you're projecting your own insecurity onto an internet stranger.

If you'd like to question the statistics themselves, however, I'd like to recommend textbooks you could use as references to further your own knowlege. This one is an excellent introduction to the techniques statisticians use to measure and analyze time-series data. This one is the more advanced version that delves into the more complex cross section analysis, as well as the growing-in-importance panel data techniques used today.

Between those two textbooks, you will know the rudimentary statistics to recognize the models used when hot air is blown your way. More importantly, you'll recognize it as hot air. I'll warn you though: be prepared to sharpen your teeth on some matrix algebra.

Finally, a word of wisdom: the social studies are changing. It is no longer acceptable to create a thought experiment, write a paper, and get it published. Researchers are expected to research. Theoretical papers are loaded with incredibly complex mathematics, often simplified with assumptions. Empirical papers are case studies, peer edited, and transparent in methodology and modeling. Always be wary of the author that doesn't discuss his or her methodology. Always be wary of papers that hide behind statistics without referring to the original data. And most importantly, always be wary of theoretical papers that don't translate their concepts to mathematics. They are the papers being laughed at in academia today.

i'm not a economist, but from what i know, the intro books are Gujarati

and Woolridge

Those are courses in statistics / econometrics. Time series will probably cover topics in a book like this. http://www.amazon.com/Econometrics-Financial-Markets-John-Campbell/dp/0691043019/

Multivariate analysis sounds like a general econometrics course which would likely cover topics from a book like this.
http://www.amazon.com/Introductory-Econometrics-Modern-Approach-Economics/dp/1111531048/

The first book is probably more advanced than what will be covered in the courses, the second book is probably more introductory than what will be covered the courses. In my opinion anyone who thinks they might work with observational data someday should find econometrics quite useful.

[It says 'introductory' right there in the title!] (https://www.amazon.co.uk/Introductory-Econometrics-Approach-Jeffrey-Wooldridge/dp/1111531048)

First of all, I recommend you make Python your first language.

Secondly, econometrics is reasonably straightforward when taught well. The equations and derivations are reasonably straightforward. I'd recommend reading Wooldridge's book, which is very simple and straight forward.

Thirdly, the choice between Python 2 and 3 for econometric work is immaterial, so it won't have a dramatic impact on your work either way. I'm too lazy to convert to Python 3, so I use 2.7.

Lastly, as a point of reference, I started programming with STATA, then moved to R, and then moved to Python.

Read this and this and see how you go.

I did well in both Econometrics courses (399,497), and would say definitely check this text book out. You should be able to find a PDF somewhere. In my section with Fossati there was some really basic coding (Shazam), and the stats/maths were very introductory. Understanding basic calculus (multivariate inc.) as well as introductory stats (distributions, expected values, hypothesis testing) is most the course imo.

They're also both a lot of fun. :) If you're looking for interesting Econ courses, those specific 400 level ones are pretty interesting, since you typically get directed to read papers with substantial findings and get a good taste of that particular field. Labor Economics and Urban Economics are both great.

Putting in a vote for Econometrics.

I was a math undergrad and took Econometrics as an elective and I loved it. If you're into applied statistics, then I definitely recommend it. I've heard good things about this book if you're looking for an undergrad level book to read through in your free time (there should be a free pdf online if you do it a Google). You should be able to do all of the required computations in Excel, so no other software is needed.

Also, I'm not sure what your stats background is, so I'll just leave you a link to a fantastic source provided by PSU. It has online notes for many stats courses starting from the basics, if you're interested.

for an undergrad introduction, see wooldridge. It's reads pretty nice, you can find a digital copy in the web and you can buy a much cheaper international version by mail too!

I've heard this line before.

Normally, I would say, see Professor Granger's work on statistical proof of causality, for which (I think) he won the 2003 Nobel Prize.

But, also, I can recommend the two most standard textbooks on use of statistical methodology for economics (which one uses to prove ones argument mathematically), for students in second and third-year econ courses requiring use of empirical methodology.

• Wooldridge
  
  
• Greene
  
  

Basic logic and an understanding of statistics. Don't make low effort comments.

Take a class or read an undergraduate textbook on econometrics

https://www.amazon.com/Econometric-Analysis-7th-William-Greene/dp/0131395386

https://www.amazon.com/Introductory-Econometrics-Modern-Approach-Economics/dp/1111531048

(Free Hansen book if you understand linear algebra)
https://www.ssc.wisc.edu/~bhansen/econometrics/