Lecture Notes
ECON 30331/Econometrics
Spring 2009
·
Class introduction, Monday, January 19: [Download notes in
PPT handout mode]
·
Chapters 1, Scatter Plots and Correlation
Coefficients, Monday, January 19
PPT notes, Chapter 1,
·
Chapter 2, The bivariate
regression model, Wednesday, January 21 through Wednesday, January 28
PPT notes, Chapter 2, the Bivariate
model
Detailed derivations. This is a 15-page
handout that includes all the important derivations I will do at the board for
this chapter, the topics include:
Important properties of
summations
Deriving the OLS
estimates
Deriving the R-squares
OLS estimates are unbiased
The
variance of OLS estimates
·
Chapter 3, The multivariate model, February
2nd and 4th
PPT notes, Chapter 3
Detailed derivations
Deriving the estimates in multivariate models
Omitted variables bias in the MV
model
The “Partialling” out
property of MV regressions
·
Chapter
4, Statistical inference (February 9, 11, 16)
PPT notes, Part 1: Inference about 1
parameter
PPT notes, Part 2: Tests of multiple parameters
·
Chapter 7, Dummy variables in regression
models, Feb 18
PPT notes, Chapter 7
·
Review Sheet – how to interpret regression coefficients
·
Notes for Bertrand
and Mullinathian, February 23
STATA
data set that will allow you to replicate basic results in Table 1
·
Notes for Sacerdote, February 23 and 25
·
Notes for
Duggan/Levitt and Fisman/Miguel, Feb 25, March 2
·
Chapter 5, the consistency of OLS estimates,
Monday, Match 16th
Detailed
derivations
The
consistency of OLS estimates
The
impact of measurement error in x
·
Chapter 10-12 – Some topics in Time Series
Analysis
Time Series, part I, PPT slide show, March 18 and 23
Time Series, Part II, PPT slide show, March 25
Critical
values for Durbin-Watson Statistic (Use Table A2)
Notes for
Wilcox paper, March 25
Detailed
derivations, impact of autocorrelation on mean and variance of B1
·
Chapter 13 -- Difference in Difference Models
Tyler
et al., Ayers & Levitt, PPT slide show
·
Chapter 15 – Two-Stage Least Squares (2SLS)
·
Regression discontinuity models