<p>In case you want to go into Dynamic Stochastic General Equilibrium models, the book</p>

<p><a href="http://www.springer.com/economics/economic+theory/book/978-3-540-85684-9">"Dynamic General Equilibrium Modeling" 2009 (2nd ed.)</a> by B. Heer and Al. Mausser is a very useful companion.</p>

<p>For econometrics I would also suggest </p>

<p><a href="http://rads.stackoverflow.com/amzn/click/0521424089">"Probability Theory and Statistical Inference: Econometric Modeling with Observational Data"</a> 1999, by A. Spanos. It provides the statistical foundations of econometrics in a way no other book does.</p>

<p>To comment on some of the suggestions related to econometrics in the other answers:  </p>

<p><strong>"Econometric Analysis of Cross Section and Panel Data" by Wooldridge.</strong> has a very fresh approach, (chapter 2 "Conditional Expectations and Related Concepts in Econometrics" was long missing from any Econometrics book). </p>

<p><strong>"Econometrics" by Hayasi</strong>, except of presenting a new synthesis focused around Extremum Estimators (i.e. Maximum Likelihood and Generalized Method of Moments), and of giving space to Time Series, Unit root econometrics and Co-integration, it has theoretical depth alongside very practical applications, a combination which is not usually found.  </p>

<p><strong>"Econometric Analysis" by Greene</strong> is indeed a compendium of results -very useful for lookup purposes, but not really suitable for self-study.</p>

CC BY-SA 3.0
2014-11-19T20:02:43.983Z
2014-11-19T20:02:43.983Z
Alecos Papadopoulos
<p>Firstly, for basic introductory econometrics, the following is quite good:</p>

<blockquote>
  <p>"Introduction to Econometrics" by Stock and Watson.</p>
</blockquote>

<p>It is light on technical details, and heavy on intuition. This might not appeal to you if you are a math major, but it's the most important thing to get straight if you are interested in applying the empirical methods rather than developing new econometric methods.</p>

<p>Stock and Watson <em>is</em> very basic, so you will probably want to supplement it. Good choices are likely to be</p>

<blockquote>
  <p>"Mostly Harmless Econometrics" by Angrist and Pischke</p>
</blockquote>

<p>(this is another book that puts intuition first, but now with more formal detail), and for an advanced graduate treatment</p>

<blockquote>
  <p>"Econometric Analysis of Cross Section and Panel Data" by Wooldridge.</p>
</blockquote>

<p>I don't know Wooldridge very well, but I know that his book is popular and well-loved among econometrics grad students.</p>

<p>These books have a bias in favour of microeconometrics and deal less, if at all, with time series methods. More comprehensive coverage can be found in</p>

<blockquote>
  <p>"Econometrics" by Hayashi</p>
</blockquote>

<p>or</p>

<blockquote>
  <p>"Econometric Analysis" by Greene.</p>
</blockquote>

<p>The book by Hayashi is probably better for self-study; Greene is more of a comprehensive reference book.</p>

CC BY-SA 3.0
2014-12-05T17:03:35.697Z
Hayashi's book is really good! ;)
An old man in the sea.
CC BY-SA 3.0
2014-11-19T18:37:41.343Z
I second Hayashi, and add the note that he takes a Generalized Method of Moments (GMM) approach, which is really nice if you find yourself doing GMM or SMM estimators a lot.
CompEcon
CC BY-SA 3.0
2014-11-19T18:35:59.037Z
2015-10-08T15:53:09.847Z
2015-10-08T15:53:09.847Z
Ubiquitous
<p>In addition to the notes from @Ubiquitous, I'd recommend these excellent and free/open resources from a number of academics. These are all posted freely and openly by the authors, and are all high-quality (and all at the "graduate level").</p>

<ul>
<li>John Cochrane's Time Series for Macro and Finance monograph <a href="http://www.computational-economics.net/_downloads/time_series_book.pdf" rel="nofollow">pdf</a></li>
<li>John Stachurski's <a href="http://johnstachurski.net/emet_book.html" rel="nofollow">intro grad textbook</a>, online</li>
<li>Michael Creel's <a href="http://pareto.uab.es/mcreel/Econometrics/" rel="nofollow">graduate econometrics notes</a>, with code</li>
<li>Kenneth Train's <a href="http://eml.berkeley.edu/~train/distant.html" rel="nofollow">course and textbook</a> on simulation-based econometrics</li>
<li>Bruce Hansen's all-around <a href="http://www.ssc.wisc.edu/~bhansen/econometrics/" rel="nofollow">graduate econometrics textbook</a></li>
</ul>

<p>Cochrane's monograph should be your first stop for time series, period. Stachurski covers some of the very cool theory behind 'metrics. Creel provides a very nice, slide-style set of notes -- gives you a chance to "quickly peruse" graduate econometric theory (as well as very cool parallel computation estimators). Train has nice chapters on simulation-based estimators. Hansen is an all-around textbook with reasonable depth. </p>

<p>Somewhat further afield, but perhaps useful for the intro level, are the "Think X" series of books from Green Tea Press:</p>

<ul>
<li><a href="http://greenteapress.com/thinkstats/" rel="nofollow">Think Stats</a> for basic statistics <a href="http://greenteapress.com/thinkstats2/index.html" rel="nofollow">second ed in progress</a></li>
<li><a href="http://greenteapress.com/thinkbayes/index.html" rel="nofollow">Think Bayes</a> for Bayesian estimation approaches</li>
</ul>

<p>These are truly intro-level books -- and very excellent as such. I use the "Train Problem/German Tank Problem" from Think Bayes whenever I need to illustrate the usefulness/intuition of Bayesian approaches to a beginner. </p>

<p>I will note that for self-study, Hayashi (noted in another answer) has a lot to offer.</p>

<p><strong>Edit</strong>: If you are looking for broad examples of methodologies, I would strongly recommend "Mostly Harmless Econometrics." The book has a particular focus and mild methodology bias (see Andrew Gelman's <a href="http://andrewgelman.com/2009/02/02/mostly_harmless/" rel="nofollow">nice review</a>, which points out some of the topics missing), but it is still excellent at diving directly into application of their ideas, via examples from the literature and replication. I strongly believe that replication is key for learning about research methods, so I like their approach quite a lot. One minor warning: to get to the applications, you have to get through their very long intro chapter on the basic of regression. But hang in there -- that chapter is great as well, and you'll then get to enjoy the fruits of application/replication after it.</p>

<p>Also, if you want to know a little more about what economists do, check out these two non-technical books: "Passion and Craft" and "Lives of the Laureates." ("The making of an economist, redux," is also good, but perhaps less ...exciting of a read. Take that for what its worth, since the first two books aren't necessarily action page turners.)</p>

<p><strong>Edit 2</strong>: as @cc7768 notes in the comments, John Stachurski and Tom Sargent's website, <a href="http://quant-econ.net" rel="nofollow">QuantEcon</a>, is absolutely fantastic. They essentially work through the major basic concepts you need for computational economics (and so many things are computational these days), and give you clear, working code examples for a vast number or major problem-types. You should very definitely check it out if you are interested in economic methodologies -- it's probably the first place I'd recommend you stop, actually. Very easy way to dip your feet into serious methodology examples. I learned an enormous amount from early versions of these notes.</p>

CC BY-SA 3.0
2016-02-12T14:52:35.353Z
As CompEcon mentioned he believes "that replication is key for learning about research methods" I'd like to point you to our [ReplicationWiki](http://replication.uni-goettingen.de) in which you find more than a thousand empirical studies with data and code for replication and an overview of methods used.
Jan Höffler
CC BY-SA 3.0
2014-11-19T18:59:11.677Z
Wow, these look like some excellent resources.
Ubiquitous
CC BY-SA 3.0
2014-11-19T21:52:21.687Z
I would have to disagree with you on Bruce Hansen's book. The only thing it has going for it is that it is free. Even then I think that is too steep a price to pay it. It has many typo's, including in one or two cases, referring to equation 1 when it means table one. Econometrics is difficult for sure, but it doesn't need to be as hard as Hansen makes it.
Jamzy
CC BY-SA 3.0
2014-11-19T22:47:58.703Z
@Jamzy, "typo's" is a typo in and of itself; the correct spelling of the plurality of "typo" is "typos" :) However, thanks for the insight!
daOnlyBG
CC BY-SA 3.0
2014-11-19T23:54:08.143Z
Haha you are right! It was early morning. I guess if I stand for anything, I should not publish my as a graduate textbook. :P
Jamzy
CC BY-SA 3.0
2014-11-20T03:13:16.680Z
Also just going through the monograph on time series. Thanks a lot!
Jamzy
CC BY-SA 3.0
2014-11-20T16:10:21.980Z
@Jamzy, I think that's a pretty valid point. I used it in concert with a lot of sources, so the issues didn't affect me as much -- if something was wonky I switched to another source. But that's not a good recommendation for the book as a single source, by a long shot.
CompEcon
CC BY-SA 3.0
2014-11-20T21:27:05.790Z
You mentioned John Stachurski's econometrics book, but maybe also worth mentioning (but not worth making this an answer) is John Stachurski and Tom Sargent's website called [QuantEcon](http://quant-econ.net).  It has some exposure to good material and the list of topics is growing (Also provides some good coding examples).
cc7768
CC BY-SA 3.0
2014-11-19T18:55:41.487Z
2016-02-09T13:46:48.623Z
2016-02-09T13:46:48.623Z
CompEcon
<p><strong>Mostly Harmless Econometrics</strong> is probably what you're looking for. However, that's because you're a math major--it's probably not a good recommendation for your average undergrad Econ major (the book itself is quirky and offbeat, which belies the sophistication of the mathematical methods presented).</p>

<p>In addition to the Econometrics textbooks mentioned by others, you might also want to look at <strong>A Guide to Econometrics</strong> by Peter Kennedy--it works well as a supplemental text and, like "Mostly Harmless", it's pretty cheap compared to those textbooks (ex: Wooldridge @ $250 on Amazon).</p>

<p>One last thing you need to check out (I've been recommending this as often as I can): Hal Varian--the chief economist at Google--recently wrote <a href="https://www.aeaweb.org/articles.php?doi=10.1257/jep.28.2.3" rel="nofollow">this</a> article for the <em>Journal of Economic Perspectives</em> ("<strong>Big Data: New Tricks for Econometrics</strong>"), detailing some of the techniques of Machine Learning most relevant to Econometrics (there's also a data set and <strong>R</strong> code which accompanies the article). And, if that piques your interest, you might want to look at <strong>The Elements of Statistical Learning</strong> by Hastie, et al.--or, for those looking for something less math-heavy--<strong>An Introduction to Statistical Learning</strong>, both of which expand on some of the methods detailed by Varian (and both are available in Hardback or as a free pdf from the authors' sites).</p>

CC BY-SA 3.0
2014-11-20T16:38:41.120Z
+1 for great references all around. Kennedy helped me nail down some concepts, but I couldn't use it as a sole guide.
CompEcon
CC BY-SA 3.0
2014-11-20T05:12:54.780Z
2014-11-20T05:12:54.780Z
Steve S
<p><a href="https://drive.google.com/file/d/0BzEnDoIVCepWc3dMSllfTmp3SzQ/edit" rel="nofollow">Here</a> is an introductory set of self-published notes by Tony Cookson from an honors-level undergraduate course.  They're clear in distinguishing causation from mere statistical relationships.</p>

CC BY-SA 3.0
2015-06-23T18:01:16.317Z
2015-06-23T18:01:16.317Z
Pat W.
<p>This question is more so geared toward anyone with research experience within economics, though of course, anyone is welcome to respond. </p>

<p>I'm an undergraduate math major with a minor in economics. I'd like to know which textbooks are decent for introducing one to research methods in economics? Graduate level is fine, perhaps even preferred. If a student was to take his research to "the next level" (publishing worthy), which textbooks would provide the rigor and insight to develop said research?</p>

<p>Also, any introductory recommendations for econometrics? </p>

<p>Thank you in advance. </p>

<p>ANNENDUM: 
From the limit experience I have in economics, I've found the following areas to fascinate me on multiple occasions (in no particular order):</p>

<ol>
<li>Game theory</li>
<li>Macroeconomics (monetary policy) </li>
<li>Microeconomics (i.e., commodity pricing) </li>
<li>Pricing theory</li>
</ol>

CC BY-SA 3.0
2014-11-19T18:30:58.460Z
I'm not sure this question is appropriate. SE generally frowns on lists and recommendations as too opinion based. I think the question could be made better by asking what are the canonical texts of a given area of economics although even that could be viewed as off topic. I am however open to reconsider.
Jason Nichols
CC BY-SA 3.0
2014-11-19T18:36:26.090Z
Agreed. Although I did benefit from some specific recommendations when I was a young and eager grad student.
CompEcon
CC BY-SA 3.0
2014-11-19T18:41:51.263Z
@JasonNichols I disagree. There are SE communities have tags for book recommendations; questions like this are common on SE. Furthermore, as CompEcon pointed out, this question could be useful for students in economics, a demographic I'd like to think Economics Stack Exchange would like to attract.
daOnlyBG
CC BY-SA 3.0
2014-11-19T18:42:44.567Z
Fair enough. As long as we're all in support, I'll support as well.
Jason Nichols
CC BY-SA 3.0
2014-11-19T18:51:16.003Z
I think the following question on the TeX SE is a real poster child for just how useful list questions can be if cultivated properly: http://tex.stackexchange.com/questions/339/latex-editors-ides
Ubiquitous
CC BY-SA 3.0
2014-11-19T21:28:53.277Z
should we have single entries and upvote, or should we try to make a community wiki and edit?
Jason Nichols
CC BY-SA 3.0
2014-11-19T22:24:52.190Z
@daOnlyBG: do you have a rough idea what your area of research interest is in? That might help steer recommendations.
CompEcon
CC BY-SA 3.0
2014-11-19T22:46:27.380Z
@CompEcon good question, I will amend the OP to reflect my interests. Thanks!
daOnlyBG
CC BY-SA 3.0
2014-11-20T03:47:40.803Z
Also, @daOnlyBG, have you thought about what sort of **software** you would want to use when actually *doing* your research?
Steve S
CC BY-SA 3.0
2014-11-20T03:51:28.187Z
@SteveS I can code in C#, MATLAB, R, Mathematica, and Java; I'd probably use one of the first three. I'm not one for Minitab; I'd be open toward learning JMP if I had to.
daOnlyBG
CC BY-SA 3.0
2014-11-20T21:19:02.767Z
I think this would fit better as a community wiki and we divide suggestions into subject categories (i.e. micro, macro, metrics --possibly sub-categories I guess) and maybe even into a "free" and "not free" list.
cc7768
CC BY-SA 3.0
2014-11-24T16:13:18.207Z
@daOnlyBG: I'd really like to point you to my "Edit 2" in my answer -- I think [QuantEcon](http://quant-econ.net) is really the first place you should stop and peruse. The great thing is that there are books which accompany it, if you want. But the site itself is an extremely nice way to immediately dip feet into grad-level economic methodology.
CompEcon
CC BY-SA 3.0
2014-11-24T16:25:56.527Z
@CompEcon: your response(s) are noted- thank you very much, I will go ahead and check the webpage out.
daOnlyBG
<soft-question><reference-request>
Book recommendations on empirical methods in economic research and econometrics?
daOnlyBG
# Book recommendations on empirical methods in economic research and econometrics?

(Asked by: username_0 on 2014-11-19)

This question is more so geared toward anyone with research experience within economics, though of course, anyone is welcome to respond.

I'm an undergraduate math major with a minor in economics. I'd like to know which textbooks are decent for introducing one to research methods in economics? Graduate level is fine, perhaps even preferred. If a student was to take his research to "the next level" (publishing worthy), which textbooks would provide the rigor and insight to develop said research?

Also, any introductory recommendations for econometrics?

Thank you in advance.

ANNENDUM:
From the limit experience I have in economics, I've found the following areas to fascinate me on multiple occasions (in no particular order):

1. Game theory
2. Macroeconomics (monetary policy)
3. Microeconomics (i.e., commodity pricing)
4. Pricing theory

**Tags:** soft-question, reference-request

> **Comments:**
> **username_1**: I'm not sure this question is appropriate. SE generally frowns on lists and recommendations as too opinion based. I think the question could be made better by asking what are the canonical texts of a given area of economics although even that could be viewed as off topic. I am however open to reconsider.  
> **username_2**: Agreed. Although I did benefit from some specific recommendations when I was a young and eager grad student.  
> **username_0**: @JasonNichols I disagree. There are SE communities have tags for book recommendations; questions like this are common on SE. Furthermore, as username_2 pointed out, this question could be useful for students in economics, a demographic I'd like to think Economics Stack Exchange would like to attract.  
> **username_1**: Fair enough. As long as we're all in support, I'll support as well.  
> **username_3**: I think the following question on the TeX SE is a real poster child for just how useful list questions can be if cultivated properly: http://tex.stackexchange.com/questions/339/latex-editors-ides  
> **username_1**: should we have single entries and upvote, or should we try to make a community wiki and edit?  
> **username_2**: @username_0: do you have a rough idea what your area of research interest is in? That might help steer recommendations.  
> **username_0**: @username_2 good question, I will amend the OP to reflect my interests. Thanks!  
> **username_4**: Also, @username_0, have you thought about what sort of **software** you would want to use when actually *doing* your research?  
> **username_0**: @SteveS I can code in C#, MATLAB, R, Mathematica, and Java; I'd probably use one of the first three. I'm not one for Minitab; I'd be open toward learning JMP if I had to.  
> **username_5**: I think this would fit better as a community wiki and we divide suggestions into subject categories (i.e. micro, macro, metrics --possibly sub-categories I guess) and maybe even into a "free" and "not free" list.  
> **username_2**: @username_0: I'd really like to point you to my "Edit 2" in my answer -- I think [QuantEcon](http://quant-econ.net) is really the first place you should stop and peruse. The great thing is that there are books which accompany it, if you want. But the site itself is an extremely nice way to immediately dip feet into grad-level economic methodology.  
> **username_0**: @username_2: your response(s) are noted- thank you very much, I will go ahead and check the webpage out.  

---

## 5 answers

### Answer by username_3 on 2014-11-19. Score: 11

Firstly, for basic introductory econometrics, the following is quite good:

> "Introduction to Econometrics" by Stock and Watson.

It is light on technical details, and heavy on intuition. This might not appeal to you if you are a math major, but it's the most important thing to get straight if you are interested in applying the empirical methods rather than developing new econometric methods.

Stock and Watson *is* very basic, so you will probably want to supplement it. Good choices are likely to be

> "Mostly Harmless Econometrics" by Angrist and Pischke

(this is another book that puts intuition first, but now with more formal detail), and for an advanced graduate treatment

> "Econometric Analysis of Cross Section and Panel Data" by Wooldridge.

I don't know Wooldridge very well, but I know that his book is popular and well-loved among econometrics grad students.

These books have a bias in favour of microeconometrics and deal less, if at all, with time series methods. More comprehensive coverage can be found in

> "Econometrics" by Hayashi

or

> "Econometric Analysis" by Greene.

The book by Hayashi is probably better for self-study; Greene is more of a comprehensive reference book.

> **Comments:**
> **username_2**: I second Hayashi, and add the note that he takes a Generalized Method of Moments (GMM) approach, which is really nice if you find yourself doing GMM or SMM estimators a lot.  
> **username_7**: Hayashi's book is really good! ;)  

---

### Answer by username_6 on 2014-11-19. Score: 6

In case you want to go into Dynamic Stochastic General Equilibrium models, the book

["Dynamic General Equilibrium Modeling" 2009 (2nd ed.)](http://www.springer.com/economics/economic+theory/book/978-3-540-85684-9) by B. Heer and Al. Mausser is a very useful companion.

For econometrics I would also suggest

["Probability Theory and Statistical Inference: Econometric Modeling with Observational Data"](http://rads.stackoverflow.com/amzn/click/0521424089) 1999, by A. Spanos. It provides the statistical foundations of econometrics in a way no other book does.

To comment on some of the suggestions related to econometrics in the other answers:

**"Econometric Analysis of Cross Section and Panel Data" by Wooldridge.** has a very fresh approach, (chapter 2 "Conditional Expectations and Related Concepts in Econometrics" was long missing from any Econometrics book).

**"Econometrics" by Hayasi**, except of presenting a new synthesis focused around Extremum Estimators (i.e. Maximum Likelihood and Generalized Method of Moments), and of giving space to Time Series, Unit root econometrics and Co-integration, it has theoretical depth alongside very practical applications, a combination which is not usually found.

**"Econometric Analysis" by Greene** is indeed a compendium of results -very useful for lookup purposes, but not really suitable for self-study.


---

### Answer by username_2 on 2014-11-19. Score: 5

In addition to the notes from @username_3, I'd recommend these excellent and free/open resources from a number of academics. These are all posted freely and openly by the authors, and are all high-quality (and all at the "graduate level").

* John Cochrane's Time Series for Macro and Finance monograph [pdf](http://www.computational-economics.net/_downloads/time_series_book.pdf)
* John Stachurski's [intro grad textbook](http://johnstachurski.net/emet_book.html), online
* Michael Creel's [graduate econometrics notes](http://pareto.uab.es/mcreel/Econometrics/), with code
* Kenneth Train's [course and textbook](http://eml.berkeley.edu/~train/distant.html) on simulation-based econometrics
* Bruce Hansen's all-around [graduate econometrics textbook](http://www.ssc.wisc.edu/~bhansen/econometrics/)

Cochrane's monograph should be your first stop for time series, period. Stachurski covers some of the very cool theory behind 'metrics. Creel provides a very nice, slide-style set of notes -- gives you a chance to "quickly peruse" graduate econometric theory (as well as very cool parallel computation estimators). Train has nice chapters on simulation-based estimators. Hansen is an all-around textbook with reasonable depth.

Somewhat further afield, but perhaps useful for the intro level, are the "Think X" series of books from Green Tea Press:

* [Think Stats](http://greenteapress.com/thinkstats/) for basic statistics [second ed in progress](http://greenteapress.com/thinkstats2/index.html)
* [Think Bayes](http://greenteapress.com/thinkbayes/index.html) for Bayesian estimation approaches

These are truly intro-level books -- and very excellent as such. I use the "Train Problem/German Tank Problem" from Think Bayes whenever I need to illustrate the usefulness/intuition of Bayesian approaches to a beginner.

I will note that for self-study, Hayashi (noted in another answer) has a lot to offer.

**Edit**: If you are looking for broad examples of methodologies, I would strongly recommend "Mostly Harmless Econometrics." The book has a particular focus and mild methodology bias (see Andrew Gelman's [nice review](http://andrewgelman.com/2009/02/02/mostly_harmless/), which points out some of the topics missing), but it is still excellent at diving directly into application of their ideas, via examples from the literature and replication. I strongly believe that replication is key for learning about research methods, so I like their approach quite a lot. One minor warning: to get to the applications, you have to get through their very long intro chapter on the basic of regression. But hang in there -- that chapter is great as well, and you'll then get to enjoy the fruits of application/replication after it.

Also, if you want to know a little more about what economists do, check out these two non-technical books: "Passion and Craft" and "Lives of the Laureates." ("The making of an economist, redux," is also good, but perhaps less ...exciting of a read. Take that for what its worth, since the first two books aren't necessarily action page turners.)

**Edit 2**: as @username_5 notes in the comments, John Stachurski and Tom Sargent's website, [QuantEcon](http://quant-econ.net), is absolutely fantastic. They essentially work through the major basic concepts you need for computational economics (and so many things are computational these days), and give you clear, working code examples for a vast number or major problem-types. You should very definitely check it out if you are interested in economic methodologies -- it's probably the first place I'd recommend you stop, actually. Very easy way to dip your feet into serious methodology examples. I learned an enormous amount from early versions of these notes.

> **Comments:**
> **username_3**: Wow, these look like some excellent resources.  
> **username_9**: I would have to disagree with you on Bruce Hansen's book. The only thing it has going for it is that it is free. Even then I think that is too steep a price to pay it. It has many typo's, including in one or two cases, referring to equation 1 when it means table one. Econometrics is difficult for sure, but it doesn't need to be as hard as Hansen makes it.  
> **username_0**: @username_9, "typo's" is a typo in and of itself; the correct spelling of the plurality of "typo" is "typos" :) However, thanks for the insight!  
> **username_9**: Haha you are right! It was early morning. I guess if I stand for anything, I should not publish my as a graduate textbook. :P  
> **username_9**: Also just going through the monograph on time series. Thanks a lot!  
> **username_2**: @username_9, I think that's a pretty valid point. I used it in concert with a lot of sources, so the issues didn't affect me as much -- if something was wonky I switched to another source. But that's not a good recommendation for the book as a single source, by a long shot.  
> **username_5**: You mentioned John Stachurski's econometrics book, but maybe also worth mentioning (but not worth making this an answer) is John Stachurski and Tom Sargent's website called [QuantEcon](http://quant-econ.net).  It has some exposure to good material and the list of topics is growing (Also provides some good coding examples).  
> **username_8**: As username_2 mentioned he believes "that replication is key for learning about research methods" I'd like to point you to our [ReplicationWiki](http://replication.uni-goettingen.de) in which you find more than a thousand empirical studies with data and code for replication and an overview of methods used.  

---

### Answer by username_4 on 2014-11-20. Score: 3

**Mostly Harmless Econometrics** is probably what you're looking for. However, that's because you're a math major--it's probably not a good recommendation for your average undergrad Econ major (the book itself is quirky and offbeat, which belies the sophistication of the mathematical methods presented).

In addition to the Econometrics textbooks mentioned by others, you might also want to look at **A Guide to Econometrics** by Peter Kennedy--it works well as a supplemental text and, like "Mostly Harmless", it's pretty cheap compared to those textbooks (ex: Wooldridge @ $250 on Amazon).

One last thing you need to check out (I've been recommending this as often as I can): Hal Varian--the chief economist at Google--recently wrote [this](https://www.aeaweb.org/articles.php?doi=10.1257/jep.28.2.3) article for the *Journal of Economic Perspectives* ("**Big Data: New Tricks for Econometrics**"), detailing some of the techniques of Machine Learning most relevant to Econometrics (there's also a data set and **R** code which accompanies the article). And, if that piques your interest, you might want to look at **The Elements of Statistical Learning** by Hastie, et al.--or, for those looking for something less math-heavy--**An Introduction to Statistical Learning**, both of which expand on some of the methods detailed by Varian (and both are available in Hardback or as a free pdf from the authors' sites).

> **Comments:**
> **username_2**: +1 for great references all around. Kennedy helped me nail down some concepts, but I couldn't use it as a sole guide.  

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### Answer by username_10 on 2015-06-23. Score: 1

[Here](https://drive.google.com/file/d/0BzEnDoIVCepWc3dMSllfTmp3SzQ/edit) is an introductory set of self-published notes by Tony Cookson from an honors-level undergraduate course. They're clear in distinguishing causation from mere statistical relationships.


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