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(a) Explain one by one the interpretation of the estimates in model (3.2)?
(b) Based on the estimates in (3.1) and (3.2), from 2006 to 2010, what is the average
price change for all houses in Sydenham?
(c) Explain why we cannot infer from the estimates in (3.1) that the location of the
hospital caused the price of houses located nearby to increase? What evidence from
model (3.2) supports this conclusion?
(d) Using the information from models (3.1) and (3.2), calculate the dierence-in-dierences
estimate of the impact of the new hospital on the price of nearby houses?
(e) Propose a linear regression model that can directly estimate the eect of new hospital
on housing price.
GLS
• GLS estimation is a way of addressing heteroskedasticity
• GLS works by transforming the regression by weighting each observation to put less weight on the observations that vary a lot, and more weight on the observations that vary a little
• Must mention: you can only use GLS if you know the form of the heteroskedasticity
• The form of the heteroskedasticity is used to weight the regression
1 Introduction, Linear Regression with Treatment Effects
2 OLS and GLS in Matrix, Panel Data Models
3 Endogeneity, Pooled IV and 2SLS Estimators
4 Pooled OLS, First Difference Estimator, Pooled 2SLS
5 Fixed-Effect and Random-Effect Estimators
6 Social and Natural Experiments, DID Estimation
7 Mid-semester Exam
8 Modeling Issues in Panel Data
9 Generalized Method of Moments (GMM) and MLE
10 Dynamic Linear Panel Data Models
11 Simultaneous Equation Models for Panel Data
12 Discrete Choice Models for Panel Data
13 Review
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