We predicted the number of corruption messages per day in each community (separately for messages with any engagement and corruption report) received from unique senders using the following randomly assigned independent variables: treatment versus placebo film, which was randomly assigned at the geographic level; and day of mass text message reception, which was assigned at the geographic level on a randomly chosen day following film distribution. For the corruption messages, we were able to determine each unique sender’s treatment status based on their geographical location, according to the phone company. In all analyses, we interact the film and mass text treatments and used fixed effects for the community matched pair, and we report cluster-robust SEs at the level of the community.Yit= treat_filmit+mass_textit+treat_filmit×mass_textit+pairi

We predict endline survey responses about social norms of corruption and corruption reporting in each community using the randomly assigned treatment versus placebo film variable. These regressions also control for community matched-pair fixed effects and calculate cluster-robust SEs at the level of community.Yit= treat_filmit+pairi

Note: The content above has been extracted from a research article, so it may not display correctly.



Q&A
Please log in to submit your questions online.
Your question will be posted on the Bio-101 website. We will send your questions to the authors of this protocol and Bio-protocol community members who are experienced with this method. you will be informed using the email address associated with your Bio-protocol account.



We use cookies on this site to enhance your user experience. By using our website, you are agreeing to allow the storage of cookies on your computer.