As we draw to the close of our second week here in Menomonie, I have come to realize that I have learned an immense amount in a very short period of time. Presenting in front of the other groups has made me realize how many new techniques I have been introduced to. It also made me realize that I am extremely passionate about the economics project that we have jumped into. The more I learn about Menomonie and Chetek, the more I care. It’s not just a matter of cleaning a lake or delving into local politics. These lakes are the hearts and identities of these towns, and the survival of these economies and people relies largely on its maintenance. Further beyond that, I hope that the work we do here can be a case study for other areas. If we can find solutions here, in the most polluted and impaired of Wisconsin’s lakes, then the possibilities and ramifications of our projects to help other parts of the world are immense.
Thus, the basis of our project is to get a deeper understanding of the two things: the value of the lake (particularly the value of a clean lake) and how the lake impacts different dimensions of the local economy. As the value of environmental goods is not set on a market price like other commodities are, we need to construct certain models and alternative ways to create a market demand schedule for the lakes. We are using a contingent valuation study method to do so. This involves asking residents and business (in both Menomonie and Chetek) how willing they are to pay certain amounts in order to either maintain the lake, or in an alternative question, to improve the quality of the lake. This willingness to pay will be asked, among various other questions about use and value of the water to the individuals, in surveys we mail out. Other questions in the survey ask businesses current revenue measures and projected measures in hypothetical situations of both increased lake quality and a deteriorating condition. This will help to get a sense of how much tourism and lake activities play a role in the local economy and will hopefully allow us to generate a dollar value to represent the impact of water quality.
The second facet to the project uses a Hedonic pricing model to value homes around the lakes. We are looking at home values on Lakes Menomin, Tainter, and Chetek and the surrounding areas. Controlling for factors such as bedroom/bathroom number, garage size, remodeling, property size and more, we hope to run a regression that will tell us two different things. One, it will help us to see how the distance to the lake impacts house price. Essentially this helps answer the question: are houses on the lake more expensive because they are closer to the lake itself, or is it because the lakefront homes tend to be merely nicer homes; and if so, how much more value does the lake add? Furthermore, doing a difference in difference model of this derived value for both a clean lake and dirty lake would give us the value of clean water, not simply water itself. This is an immensely valuable estimation that could help to incentive homeowners and policy makers to support cleaning the lake, as they will be shown the concrete financial interest they have in doing so.
As I have yet to take econometrics and have only a basic statistics background, I hope to learn more about how to perform these regression models as well as become more familiar with the Stata software. It is a bit intimidating to be the only member in my group that hasn’t taken a formal econometrics class, but I will be able to gain knowledge in these areas through the analysis we will do. Since I am a visual learner, this is a perfect opportunity for me to learn by doing- an opportunity I most definitely will not take for granted. It may be overwhelming to learn it at first, but this is the most hands-on learning I have ever experienced, and it is thrilling. What better way to learn than through real life application of statistics that have the potential to make a difference? In addition to the econometrics bits, I would like to learn a bit more about GIS. I plan on taking a GIS class in the spring of the coming academic year, but once again I am presented with the opportunity to learn through practical application before stepping foot in a formal classroom setting, and I couldn’t be happier. We need GIS for assistance retrieving some of the housing data so this perfect opportunity to learn more about the GIS software. Also, an idea that I have been toying with is the possibility of mapping the levels of household willingness to pay (WTP). I do not know if this will be possible, no less if WTP will show a relevant pattern/spread, but this is something that I hope to learn and look into. Overall, though I have learned so much already, there is much to do and learn in the six short weeks we have left. Let the fun begin!
As I have yet to take econometrics and have only a basic statistics background, I hope to learn more about how to perform these regression models as well as become more familiar with the Stata software. It is a bit intimidating to be the only member in my group that hasn’t taken a formal econometrics class, but I will be able to gain knowledge in these areas through the analysis we will do. Since I am a visual learner, this is a perfect opportunity for me to learn by doing- an opportunity I most definitely will not take for granted. It may be overwhelming to learn it at first, but this is the most hands-on learning I have ever experienced, and it is thrilling. What better way to learn than through real life application of statistics that have the potential to make a difference? In addition to the econometrics bits, I would like to learn a bit more about GIS. I plan on taking a GIS class in the spring of the coming academic year, but once again I am presented with the opportunity to learn through practical application before stepping foot in a formal classroom setting, and I couldn’t be happier. We need GIS for assistance retrieving some of the housing data so this perfect opportunity to learn more about the GIS software. Also, an idea that I have been toying with is the possibility of mapping the levels of household willingness to pay (WTP). I do not know if this will be possible, no less if WTP will show a relevant pattern/spread, but this is something that I hope to learn and look into. Overall, though I have learned so much already, there is much to do and learn in the six short weeks we have left. Let the fun begin!
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