Question 1

Which of the following are associated with larger omitted variable biases?

Accepted Answer

A)  The dependent variable is measured with error. 
B)  The relationship between the included and excluded variables is weak. 
C)  The relationship between the included and excluded variables is strong. 
D)  The relationship between the excluded variable and the dependent variable is weak. 
A)  The dependent variable is measured with error. 
B)  The relationship between the included and excluded variables is weak. 
C)  The relationship between the included and excluded variables is strong. 
D)  The relationship between the excluded variable and the dependent variable is weak.

Question 2

We necessarily do not have an omitted variable bias problem the omitted variable is uncorrelated with the included variable.

Accepted Answer

A) True 
 B)False

Which of the following are associated with larger omitted variable biases?

We necessarily do not have an omitted variable bias problem the omitted variable is uncorrelated with the included variable.

The Quest for Causality

Stats in the Wild: Good Data Practices

Bivariate Ols: the Foundation of Econometric Analysis

Hypothesis Testing and Interval Estimation: Answering Research

Dummy Variables: Smarter Than You Think

Specifying Models

Using Fixed Effects Models to Fight Endogeneity in Panel Data a

Instrumental Variables: Using Exogenous Variation to Fight Endogen

Experiments: Dealing With Real-World Challenges

Regression Discontinuity: Looking for Jumps in Data

Dummy Dependent Variables

Time Series: Dealing With Stickiness Over Time

Advanced Ols

Advanced Panel Data

Filters

Exam 5: Multivariate Ols: Where the Action Is

Which of the following are associated with larger omitted variable biases?

We necessarily do not have an omitted variable bias problem the omitted variable is uncorrelated with the included variable.

The Quest for Causality

Stats in the Wild: Good Data Practices

Bivariate Ols: the Foundation of Econometric Analysis

Hypothesis Testing and Interval Estimation: Answering Research

Dummy Variables: Smarter Than You Think

Specifying Models

Using Fixed Effects Models to Fight Endogeneity in Panel Data a

Instrumental Variables: Using Exogenous Variation to Fight Endogen

Experiments: Dealing With Real-World Challenges

Regression Discontinuity: Looking for Jumps in Data

Dummy Dependent Variables

Time Series: Dealing With Stickiness Over Time

Advanced Ols

Advanced Panel Data

Filters