Section 3: Some Basics, Econometrics, & Discounting . Jisung Park: firstname.lastname@example.org February 22 2013. (Based in part on slides by Liz Walker and Rich Sweeney). Outline. Some Important Preambles The Bigger Picture Basic Econometric Techniques and Intuition
Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.
Section 3: Some Basics, Econometrics, & Discounting
Jisung Park: email@example.com
February 22 2013
(Based in part on slides by Liz Walker and Rich Sweeney)
Welcome to the Club!
“Ϛ-σ = ∑√τλβ∞η”
“Voulez-vouscoucher avec moi, cesoir?”
This red line comes from Ordinary Least Square Regression (OLS), which shows the impact of income on water use
Y (wateruse) = 1201.124 + 47.54*income
Yi = β0 + β1Xi + εi
i = each observation
Y = Dependent Variable (water use)
X = Independent Variable (income)
εi= Error term
β0 = intercept. It tells us the predicted value of Y when X = 0.
β1 = The coefficient that tells us how Y changes for unit change in X.
What sources of error can you imagine?
Yi= β0 + β1Xi1 + β2Xi2 + β3Xi3 + εi
Micro-Theory of the Firm
e.g. Hedonic Regression, Travel Cost
e.g. Cost-Benefit Analysis
Suppose we wanted to study the variation in housing prices due to proximity to an airport (which generates noise, a negative environmental externality)
Price = β0+ β1*Bedrooms + β2*Bathrooms + β3*Airport + β4*Crime + β5*Scores + β6*Sold2008 + error
r = ρ + ηg