Aaaand we're back!

Married and everything. Couldn't have asked for a better wedding, nor for a better trip to New Orleans! 

To get back in the swing of things a little bit (no WWP from this weekend because I was happily banned from doing work): because my PhD (if and when I eventually get it) will say "Agricultural" on it, I guess I should occasionally post something about agriculture. To that end, a few quick things to highlight:

Interesting that this is the first picture that comes up when I Google-image search "agriculture." I was expecting US maize (which, to be fair, was the next hit...). Source.

• Mike Roberts' has a compelling blog post which was inspired by Angus Deaton's Nobel Prize victory (which, of course, happened while I was away - but it's great to see a development economist with a bent towards empirics being awarded the Prize). Mike (an ARE grad himself, no less) has a nice little piece about Deaton's work on commodity prices, and the value of fully thinking through the implications of estimated empirical results.
• Planet Money continues its run of excellent episodes with a cool discussion of futures markets. Definitely worth a listen.
• Finally, (not directly ag) Max Auffhammer points out that this new project "has famous econometricians in it."

Also, in totally non-economics-related news, I couldn't finish this blog post without highlighting my alma mater's excellent performances at the Head of the Charles this weekend. The men came 3rd, for their best placing since 2011, and the women (for whom I coxed while I was there) won for the first time since my senior year. Awesome. 

Friday links: Night lights, monsoons, and guns.

I'm going to be away on my honeymoon next week, so no blog posts (by order of the totally-has-her-priorities-in-the-right-place fiancee). I'll leave you with one extra post this week, featuring some interesting tidbits from around the web.

India's border with Pakistan utilizes enough lighting to be seen from space.

Early map of the monsoon advance (from here).

India's weather forecasters did a much-better-than-usual job (take that, Quartz!) of forecasting the monsoon this year. (Though it's a little hard to know whether this was luck or actual improvements in the forecasting process, as the government suggests.) Getting these forecasts right is crucial: take a look at this really neat paper by Mark Rosenzweig and Chris Udry (two of my favorite authors in development economics) at Yale for reasons why.

Planet Money featured Berkeley economist David Card on the current influx of migrants to Europe. His results from Miami in the 1980s suggest that many peoples' fears about immigrants are unfounded.

A new paper in October's AEJ:Applied has a depressing title.

Economist Ryan Briggs has a moving piece on what development means in the wake of his newborn son's illness.

Cool maps (with really ugly color schemes) about the spatial organization of cities.

Trevor Noah has three great pieces: two on guns, and another on the one and only D. Trump.

Also, the Springboks are officially moving into the quarter finals of the Rugby World Cup (and Bryan Habana is now the all-time RWC leader in tries scored)!

Forget weatherization - how do we make evaluation work?

The New York Times put out an important article yesterday discussing the importance of credible policy evaluation, featuring work by the all-star team of Fowlie, Greenstone, and Wolfram. The upshot of the article? When program evaluation is done by people with a stake in seeing that same program succeed, we have reason to worry about the conclusions. The problem is the following: if non-independent evaluation teams suggest that a program is great, it's hard to know whether it's actually great or if existing incentives distorted the results.  

The Weatherization Assistance Program is a large effort by the US government to weatherize low-income households and make them more energy efficient. The aforementioned all-star team of economists put out a paper in June (now R&R at the QJE!) using a state-of-the-art randomized controlled trial to measure the energy savings from the program. They concluded, much to the chagrin of many energy efficiency advocates, that the costs of the program are twice the energy savings benefits among Michigan households.

Cheery weatherization clipart from here. 

The DOE recently released their own study of the program, in over 4,000 pages spread across 36 documents. If you're cynical like me, you're perhaps not shocked that the DOE's report finds that overall, the program benefit-cost ratio is 4:1. This takes into account non-energy benefits such as health that Meredith, Michael, and Catherine did not directly include in their original study (though to be fair, they did look at indoor temperature set-points, and find no evidence of changes - suggesting that there is little propensity for large health effects to result from reduced exposure to extreme temperatures among their sample).

What even a cynical reader might be surprised by is the magnitude of the problems with DOE's reports. From the Energy Institute blog (I also highly recommend that you read the accompanying deep dive into thermal-stress-related benefits):

“We have spent many hours poring over these opaque documents. Our judgment is that many of the DOE’s conclusions are based on dubious assumptions, invalid extrapolations, the invention of a new formula to measure benefits that does not produce meaningful results, and no effort to evaluate statistical significance. Using the DOE’s findings, we show below that costs exceed energy savings by a significant margin. We also document major problems with the valuation of non-energy benefits, which comprise the vast majority of estimated program benefits.

Overall, the poor quality of the DOE’s analysis fails to provide a credible basis for the conclusion that the benefits of energy efficiency investments conducted under WAP substantially outweigh the costs. This blog summarizes our assessment of the DOE’s analysis for a general audience. We provide a more technical discussion, using the important example of benefits relating to thermal stress, here.”

— Energy Institute at Haas blog, October 6, 2015

Eduardo Porter, author of the excellent New York Times article described above, also conducted a Q&A with Bruce Tonn, head of the DOE evaluation team. If you ask me, this is almost more damning than the original article - but I'll leave you to judge for yourself.

Full disclosure: I provided research assistance on the economists' response, helping to read over the thousands of pages of documents from DOE. So maybe I'm a less-than-impartial commentator. But I will say this: I would have been thrilled to see a DOE report that, using modern empirical techniques and direct measurements, was able to provide definitive proof of the existence of large and real health benefits from WAP. I'm disappointed that the evidence that DOE did provide was appears unconvincing and flawed. Getting climate policy right, and furthermore, getting low-income assistance right, in situations where governments have limited budgets, demands honest, sometimes hard-to-stomach, independent evaluation. Getting these policies right now will pay off in the long run - as will moving towards an institutional culture of proper ex post evaluation.

PPS: Not-at-all-humble brag moment - guess who the "graduate student" mentioned in the NYT article is? Hopefully not my last NYTimes mention...but my own work has a long way to go before being ready for anything like that, so I should stop writing this blog and get to writing a job market paper.

Disclaimer: I wrote this blog post without the supervision or knowledge of Meredith, Michael, and Catherine. I certainly do not speak for them, nor for the E2e project, EPIC, Energy Institute, etc, etc, etc. 

Wednesday websites

It's been a little bit of a crazy beginning of this week - I've finally scheduled my oral exam, I have a big RA task at the moment, and I'm getting married in less than 3 weeks! All of this is contributing to a lack of a thorough, thoughtful blog post this week (but hey - as a wise friend of mine once said, "Excuses are the bricks that build the house of failure.") In lieu of an actual post, here are some things that have popped up on my internet-radar this week (if it's good enough for Chris Blattman, it's good enough for me!)

A clear, well-done video about Syrian refugees. (h/t Erin)

A fascinating National Geographic article about traveling the Congo river.

VW epically cheated on its emissions testing. Vox explains. (As does Max.)

Buzzfeed has a quiz every climate nerd will enjoy. (h/t Sol)

Enjoy!

Back on track

I was going to make this post a Wednesday Working Paper, but because of my fantastic Seattle vacation (and less fantastic return to 2 vet trips in as many days with my cat), I haven't actually read anything new. Sorry I'm not sorry. To get the ball rolling agin, I want to highlight two great websites that were brought to my attention this week (both via Twitter. Have I mentioned my ongoing love affair with Twitter yet?)

Great data visualization or the greatest data visualization? Proof that both analysis of and presentation of (social science) data is hard.

First, FiveThirtyEight has a really nice piece on the state of science. Like the Economist article I blogged about a little while ago (first link to my own blog - oooh, meta), this post has an interactive infographic where you can play with p-hacking, this time using actual data to show statistically significant effects of Republicans/Democrats on the economy. The article does a nice job explaining potentially complex issues, like p-hacking, differences in methodological approaches by different disciplines, and the degree to which science is self-correcting, in a digestible way.  As a (social) scientist myself, I appreciate the article's headline and subtitle: ``Science Isn't Broken - It's just a hell of a lot harder than we give it credit for.'' Truth. One important thing missing from this article, though, is that the author spends essentially zero time talking about causality. The p-hacking exercise (and, as far as I can tell, the fascinating soccer player example...which includes an author from BITSS, Garret Christensen) deals only with correlations. Figuring out whether something is causal or merely correlational might be the biggest part of my job as a young economist - and actually nailing down causality is really hard to do. So consider that yet another (extremely large) item on the why-(social)-science-is-hard list. We would also benefit from more media highlighting the differences between causal and correlational work - both are very important, but should have different policy implications, but they're often treated as one and the same in newspaper or online articles about research. Kudos overall, though, to FiveThirtyEight for a detailed but readable piece on the challenges of doing science currently (and how far we've come at doing better science - we've got a ways to go, but I'm optimistic that a great deal of progress has already been made).

On a lighter note (and not to be outdone), here's what might be my new favorite time-waster website: bad data presentation from WTF Visualization. Seems like the creators of these awful graphics need to read some Tufte.