http://stats.stackexchange.com/questions/15784/how-can-i-simulate-census-microdata-for-small-areas-using-a-1-microdata-sample

we use supercomputers to forecast the weather. why not public policy?

if they can do it with the universe, surely we can do it with our country: http://www.nature.com/nature/journal/v509/n7499/full/nature13316.html

make 100 difficult predictions. e-mail them to reporters? no action now: i will contact you in a year and remind you of this e-mail.

use PCA in the synthetic model? has to be survey-weighted.

the world needs small area estimation of climate change. “this is what will happen in my backyard”

training has always been in healthcare, so applying this broader model to answer health-related questions might be a safe way to start. here are five simulations: http://www.academyhealth.org/Training/ResourceDetail.cfm?ItemNumber=14458

does the first derivative matter? your healthcare costs might not depend on your healthcare costs last year as strongly as they depend on the rate of change over the past five years

are the records of publicly-listed companies available? if so, you need to incorporate them in your scraping & synthetic firm calculations as well

how should the results be presented? a locality-based lookup? https://github.com/impunation/presentation

http://hagutierrezro.blogspot.mx/2017/04/small-area-estimation-101.html