Minimum detectable effect size for main outcomes (accounting for sample design and clustering)
The pre-analysis plan will specify the full set of power estimates based on the sampclus command in STATA, Optimal Design, and simulations in R.
In short, power calculations were conducted using data gathered in Kananga in previous years. I do not have access to the exact outcome variables I plan to collect. However, I do have several analogs that were conducted for other research in Kananga in past years. Specifically, a version of the Random Allocation Game with the Government as the Player 2 was administered in 2013-2014, which is one of the anticipated measures of views of the government. The outcome is the amount allocated to the second player, an integer between 0 and 3000 Congolese Francs (CF). Second, in past years, information on trust in the provincial government was collected; this is a reasonable approximation of some of the survey-based outcome variables I aim to use gauging citizens’ views of the government. This question uses an ordinal 1-5 Likert-style scale, increasing in trust. The data are on the individual level. The standard deviation for the RAG outcome is 441.25 (CF), and the standard deviation for the trust survey outcome is 1.05. Standard errors are clustered by polygon.
In the simplest specification, regressing the outcome on a treatment dummy, the estimated MDE with power of 0.8 for the RAG outcome is 0.201 and 0.204 for the trust questions. In a regression that includes dummies for all four treatment cells (audit + information, etc), MDEs on the coefficients of interest range from 0.26 to 0.29.
For the corruption outcomes, the only available proxy for the anticipated dependent variables is a binary bribe indicator taken from surveys with motorbike drivers at tolls in Kananga (in a separate experiment with Otis Reid also currently underway). The standard deviation for this variable is 0.47. According to this estimated dependent variable and a power level of 0.80, the MDE for the coefficient on dummies for each treatment cell of interest (audit + information, etc) range from 0.185 to 0.191. Again, see the Pre-Analysis Plan for more details on these power calculations.