I spent this Thursday with Team Math and it was fascinating to learn about their project. They are using python to build a model of the lake which will allow them to tweak advection and diffusion rates and tell whether or not a lake will experience an algae bloom under particular conditions. Apart from being a really cool and interesting application of math, it fits in pretty well with what economics is working towards.
Part of what we are looking at is people’s willingness to pay for cleaner lake water. So math’s project can tell us which conditions we could tweak to suppress a bloom and if we could find the estimated cost of some technology to mimic that we could use our data to tell whether it would be economically feasible and beneficial.
I’ve also done a fair about of work with Sociology doing Stata stuff with them. Part of what they are doing is creating an index to measure a respondent's trust of society and level of community involvement to eventually see if this affects whether or not a landowner requires BMP stipulations in their lease. I’d never thought of making an index for something so intangible but I think such indices would be extraordinarily useful in economics! It made me think about the way we could turn some of our survey data into scales to use in regression. Such as an index for investment in the future made up from some weighted combination of age of respondents and whether they have kids or grandkids.