Mines in Wisconsin: An examination of health and wealth effects
Mentor 1
Eylem Ersal-Kiziler
Mentor 2
Matthew Winden
Location
Union Wisconsin Room
Start Date
24-4-2015 10:30 AM
End Date
24-4-2015 11:45 AM
Description
This paper examines the effect that the presence of a mine has on a community in two regards: health and wealth levels. This is done using data from counties in Wisconsin provided by the CDC. Several types of models are used to estimate the dollar value of health costs imposed by mines as well as the probability that a mine’s presence will result in above average healthcare costs. Finally, the economic benefits of a mine on a community will be examined here using average income in the community as a measure of wealth. / / The methodologies used in this analysis are linear regression, a linear probability model, and a probit model. The OLS regression searches for causal relationships between the independent variables used in the model and healthcare costs in a community. The linear probability model looks to establish causality for above average healthcare expenditures. The probit model seeks to estimate the probability that an observation will fall into one of two categories. In this case whether observing a mine will result in above average health expenditures or not. Some of the independent variables in the study include an education index, expenditures on tobacco products, and insurance and pensions. / / Our paper found that the presence of a mine does not significantly affect healthcare costs in a community using the OLS regression, and a mine has significant, positive income effects using the OLS regression. However, the probability models fail to give us any significant results, this problem likely stems from a lack of observable data. This is important as it contributes to the research on whether a mine is or is not good for a community. /
Mines in Wisconsin: An examination of health and wealth effects
Union Wisconsin Room
This paper examines the effect that the presence of a mine has on a community in two regards: health and wealth levels. This is done using data from counties in Wisconsin provided by the CDC. Several types of models are used to estimate the dollar value of health costs imposed by mines as well as the probability that a mine’s presence will result in above average healthcare costs. Finally, the economic benefits of a mine on a community will be examined here using average income in the community as a measure of wealth. / / The methodologies used in this analysis are linear regression, a linear probability model, and a probit model. The OLS regression searches for causal relationships between the independent variables used in the model and healthcare costs in a community. The linear probability model looks to establish causality for above average healthcare expenditures. The probit model seeks to estimate the probability that an observation will fall into one of two categories. In this case whether observing a mine will result in above average health expenditures or not. Some of the independent variables in the study include an education index, expenditures on tobacco products, and insurance and pensions. / / Our paper found that the presence of a mine does not significantly affect healthcare costs in a community using the OLS regression, and a mine has significant, positive income effects using the OLS regression. However, the probability models fail to give us any significant results, this problem likely stems from a lack of observable data. This is important as it contributes to the research on whether a mine is or is not good for a community. /
