- Ted Miguel is teaching a course on research transparency methods in the social sciences. Berkeley is posting the lectures on YouTube. Lecture 1 is now up.
- Chris Blattman on a paper looking at how the tendency to publish null results varies by scientific field.
- In Science, Jorge Guzman and Scott Stern on predicting entrepreneurial quality
- Ben Olken’s forthcoming JEP paper on pre-analysis plans in economics: this is a very nuanced and well-written piece, discussing both pros and cons – it notes a reaction I am increasingly persuaded by, which is that RCTs don’t really seem to have a lot of data-mining problems in the first place…and also that “most of these papers are too complicated to be fully pre-specified ex-ante”…main conclusion is benefits are highest from pre-specifying just a few key primary outcomes, and for specifying heterogeneity analysis and econometric specifications – less clear for specifying causal chain/mechanisms/secondary outcomes which can too easily get too complicated/conditional.
This is a very simple (and for once short) post, but since I have been asked this question quite a few times by people who are new to doing experiments, I figured it would be worth posting. It is also useful for non-experimental comparisons of a treatment and a control group.
I finally got around to reading an intriguing paper by Banerjee, Duflo and Hornbeck that has been on my reading list for a while. This paper is a nice example of making lemonade out of lemons – they had intended to evaluate a health insurance product that a microfinance organization in India made mandatory for its clients in selected villages.
- HBR provides an update on the working from home experiment done by Nick Bloom and co-authors. This experiment worked with China’s largest travel agency, and randomly choose workers to be allowed to work from home. They find workers are more productive when they do so. The interesting new finding is that when, at the end of the experiment, the treatment group was given a choice “half of the home-workers changed their minds and returned to the office and three quarters of the control group — who had initially all requested to work from home — decided to stay in the office” – the authors find it is the most productive workers who prefer to work from home.
I thank Annette Brown and Benjamin Wood (B&W from hereon) for their response to my previous post about the 3ie replication window. It not only clarified some of the thinking behind their approach, but arrived at an opportune moment – just as I was preparing a new post on part 2 of the replication (or reanalysis as they call it) of Miguel and Kremer’s 2004 Econometrica paper titled “Worms: Identifying Impacts on Education and Health in the Presence of Treatment Externalities,” by Davey et al. (2014b) and the response (Hicks, Kremer, and Miguel 2014b, HKM from hereon). While I appreciate B&W’s clarifications, I respectfully disagree on two key points, which also happen to illustrate why I think the reanalysis of the original data by Davey et al. (2014b) ends up being flawed.
A few months ago, Berk Ozler wrote an impressive blog post about 3ie’s replication program that posed the question “how scientific are scientific replications?” As the folks at 3ie who oversee the replication program, we want to take the opportunity to answer that question. Our simple answer is, they are not meant to be.
- Soap Operas and Development: Business Week summarizes a lot of recent work and some ongoing work on using soap operas to change behaviors.
- When the nudge unit went to Guatemala – results from efforts to increase tax collection from changes in the phrasing of tax letters etc.
- The Deliberative Lives Project: “The goal of the project is to do something similar as “Portfolios of the Poor” or “Economic Lives of the Poor”, but for thoughts and decisions. A novel feature is that everyone can contribute to design and data analysis: the (de-identified) data will be posted online in real-time as it is collected, and anyone can download and analyze it. Similarly, questionnaires will be developed with input from anyone who wants to give it.”
You are feeling not so well. You go to the doctor. She is a good doctor. She runs some tests, tells you nothing is wrong with you and you leave, ready to get back to work. Why are you so much more ready to work now then you were before you saw your doctor?
Alternative title (since that one sounds a bit 1984 doublespeak-ish): Can Governments Leverage Tax Morale to Increase Tax Compliance?
- How to measure risky sex? In VoxEU, Lucia Corno and Áureo de Paula argue that self-reported data may therefore be a more reliable measure of risky behaviours than the prevalence of sexually transmitted infections when the probability of transmission is low.