Saturday, January 20, 2018

How to Write a Paper: The Part in Between the Introduction and Conclusion

I have blogged before about Keith Head's formula for writing an introduction as well as Marc Bellemare's formula for writing a conclusion. Marc has come through for us once again with a formula for writing all of the bits in between. Like Marc, I always start my papers with section titles. (Hmm..maybe it makes me feel like the paper is practically written, I just need to fill in some words.) Next, I take a stab at the introduction. This helps guide my research, think about a structure, etc.. After that, I start writing up different sections often based on my mood. But here's the key thing: after writing each section, I typically go back to the introduction. The introduction gets written and rewritten many, many times through the course of writing a paper. Yes, introductions are THAT important. The good news: no need to worry about getting it perfect the first time. 

Back to the structure of the paper. What to do when in the same paper you use different data sets and/or different empirical frameworks? Sometimes authors describe both data sets in the data section, then both estimating equations in the empirical framework section, etc. The problem with this approach is that by the time results are presented, readers have forgotten some of the details about the data or estimating equation. I prefer to start the paper with baseline results, then I describe any additional data sets and estimating equations (and further results) after that. This certainly makes for less boring repetition. 

Friday, January 12, 2018

How to Publish in AEJ: Applied

I also considered titling this post: what makes a great paper (but I had already used that title). 

David Deming is starting as co-editor of AEJ: Applied and has recently tweeted his thoughts on how he thinks about where a paper should be published. This week, I have spent a good chunk of my time advising students on which of their paper ideas are most promising to pursue as dissertation topics. David's tweets provide excellent guidance on this. The main thing:  

"The primary question I have in mind when reading a paper is “what have I learned from reading this that I did not already know?” This is a heuristic that helps me weigh impact/contribution vs. methodological strength. For RCTs and quasi-experiments - if the methodological approach is not convincing, it is hard to feel I’ve learned anything, so the question of impact is moot. However, if the question is uninteresting or has been studied many times before, even airtight identification still leaves me feeling like I have not learned anything So methodological strength and importance of question are strong complements." 

Read the entire thread! He also discusses his own very positive experience with a journal editor, and hopes to do the same. For all of you journal editors who help authors transform their "raw" ideas into excellent papers, thank you. On behalf of the entire profession. 

Thursday, January 4, 2018

Running of the Economists

To the graduate students who don't yet know about what it takes to get your first job, watch this. To those of you who have already gone through it, be prepared for it to bring back some pretty traumatizing memories. To those of you who are going through it right now, DURING A BOMB CYCLONE, good luck!!!!