Here is an add-hoc collection of resources, notes and links, generally kept for my students or for myself.
The 2020 and 2021 AAEA Panel on Non-Academic Development Economics Jobs.
A geospatial data repository. Let me know if there’s something cool you think should be added!
In this dropbox link, you will find: (a) a short slide show on how to write economics introductions, and how to diagram introductions in existing, post-2010 papers from top journals, in order to learn how to write these intros yourself, and (b) two examples of such diagramming (in the text alongside each intro paragraph), for Fernando 2022 and Hornbeck 2010. I encourage you to do this exercise yourself for ~5 papers!
Other resources on writing economics papers:
- Keith Head’s introduction formula
- Marc Bellemare on conclusions
- Four Steps to an Applied Micro Paper, Jesse Shapiro
- Marc Bellemare again on the nitty-gritty of writing applied micro papers
On depression during a PhD, by Manuela Angelucci
Random code/nerd stuff:
- From DIME: Inspiration and code for data visualization in Stata and in R
- Color patterns listed by HEX and RBG at ColourLovers, ColorBrewer
- Convert arc-seconds / arc-minutes to meters by latitude here, and 1 degree to meters by latitude here.
- Combine marginsplots from multiple models in Stata
On economics journal ranking:
- Top 50 according to Kalaitzidakis, Mamuneas, and Stengos (2001), sponsored by the European Economics Association, listed with links by OSU’s Jason Blevins
- Rankings according to various impact audiences, by Kodrzycki and Yu (2006)
Useful links on running power calculations:
- A DIME page comparing Stata commands
- JPAL resources for power cals
- Dealing with imperfect compliance / incomplete take up: Section 4.3 of Duflo, Glennerster & Kremer’s book on randomization; This blog by David Mckenzie and even better this later blog on incomplete take-up under heterogeneous treatment effects
- Simulations for power cals in Stata: an overview, and more detail in a series by Stata’s Chuck Huber: part 1, part 2, part 3, and part 4
- Simulations for power calcs in R by Nick Huntington-Klein
On publication bias:
- In “Nudge” RCTs (DellaVigna and Linos 2020 working paper)
- In psychology (Kvarven, Strømland, Johannesson 2020)
On intergenerational mobility in the US:
- Blanden 2016: Intergenerational income elasticity (IGE) is lower in the US than it is in Europe or Canada; our mobility is close to that of many developing countries
- Palomino et al. 2017: The poorest quantile of the US experiences the worst mobility, and upper-middle class families the best; low income mobility linked to low educational mobility.
- World Bank: It is easier to climb from the bottom 50% to the top 25% in Tanzania, Ethiopia, China, and Indonesia than it is it the US? (Figure 3.6: 1980s cohort only)
- The geography of intergenerational mobility and how mobility differs by race and gender, both NYT summarizing work by Raj Chetty.