Ma, Lala

Project description: In the absence of prices for environmental amenities, hedonic property value models have been widely used as a revealed-preference approach to measuring the value individuals place on non-marketed goods, such as air quality, and policies that affect changes in those goods. However, this is likely to be complicated given the substantial provision of information to agents that accompanies policies before they are implemented. Using brownfield remediation as an application, this project builds and estimates a model of household moving decisions as a dynamic, discrete neighborhood-choice problem, where households update their knowledge of brownfield hazard information in a Bayesian fashion before making residential location decisions.

Research Activity: The main technique used to estimate the model will be maximum likelihood. Parameters estimated from this model can be used to recover willingnesses to pay for environmental amenities that account for learning and forward-looking behavior. In addition, the structural model allows estimating the value of information from counterfactual information provision schemes that may be useful for policy purposes.

Collaborators:

Currently there are no other collaborators for this project.

Software:

For this project I will use Matlab and Stata to generate the results. From Matlab, the following toolboxes will be used: Optimization, Econometrics, and Statistics.