Assessing Studies Based on Multiple Regression
(SW Chapter 9) Lets step back and take a broader look at regression: Is there a systematic way to assess (critique) regression studies? We know the strengths but what are the pitfalls of multiple regression?
Quantitative Methods in Economics
The statistical analysis of economic (and related) data
Pascal Lavergne (from Stock and Watsons Introduction to Econometrics
1/2/3-1
Brief Overview of the Course
Economics suggests important relationships, often with poli
Linear Regression with One Regressor
(SW Chapters 4 and 5) The class size/test score policy question: What is the effect on test scores of reducing STR by one student/class? Test score . Object of policy interest: STR This is the causal effect on scores o
Multiple Regression
(SW Chapters 6)
OLS estimate of the Test Score/STR relation:
TestScore = 698.9 2.28STR, R2 = .05, SER = 18.6
(10.4) (0.52) Is this a credible estimate of the causal effect on test scores of a change in the student-teacher ratio? No: th
Hypothesis Tests and Confidence Intervals in Multiple Regression
(SW Chapter 7)
Outline 1. Hypothesis tests and confidence intervals for a single coefficient 2. Joint hypothesis tests on multiple coefficients 3. Other types of hypotheses involving multipl
Nonlinear Regression Functions
(SW Chapter 8) Everything so far has been linear in the Xs But the linear approximation is not always a good one The multiple regression framework can be extended to handle regression functions that are nonlinear in one or m
Regression with Panel Data
(SW Chapter 10) A panel dataset contains observations on multiple entities (individuals), where each entity is observed at two or more points in time. Hypothetical examples: Data on 420 California school districts in 1999 and ag
Regression with a Binary Dependent Variable (SW Ch. 11)
So far the dependent variable (Y) has been continuous: district-wide average test score traffic fatality rate But we might want to understand the effect of X on a binary variable: Y = get into colleg
Instrumental Variables Regression (SW Ch. 12)
Three important threats to internal validity are: omitted variable bias from a variable that is correlated with X but is unobserved, so cannot be included in the regression; simultaneous causality bias (X caus
Introduction to Time Series Regression and Forecasting (SW Chapter 14)
Time series data are data collected on the same observational unit at multiple time periods Aggregate consumption and GDP for a country (for example, 20 years of quarterly observations
Estimation of Dynamic Causal Effects (SW Chapter 15)
A dynamic causal effect is the effect on Y of a change in X over time. For example: The effect of an increase in cigarette taxes on cigarette consumption this year, next year, in 5 years; The effect of