Question 1

Suppose you are interested in testing the claim that students who participate in band perform better on standardized tests but you are worried that the results might be biased because individuals are likely to self-select into joining the band.You only have test scores for those students that participate in band.Suppose that for a sample of 14,111 6^th-grade students you estimate the Heckman selection model (marginal effects listed,standard errors in parentheses) Second-Stage: $$\begin{aligned} Tes\widehat {t S}core _ { i } = & 58.932 +& 1.374 \lambda _ { i } +& 0.583 \text { Income } _ { i } + &2.156 \text { Male } _ { i } \ & ( 7.961 ) &( 0.358 )& ( 0.136 )&(1.679) \end{aligned}$$ First-Stage: $$\begin{array} { l } {\widehat{\text { Band }_{i}}}=&0.261+&0.045 \text { Siblings in Band }_{i}+&0.048 \text { Income }_{i}+&0.125 \text { Male }_{i}\ &( 0.043 ) &( 0.022 ) &( 0.012 )&(0.103) \ \end{array}$$ a)Explain why OLS is inappropriate in this circumstance and how this model improves on OLS. b)Which variable are you using to identify the model? Does this choice seem correct? Explain. c)Discuss the results above.

Accepted Answer

The answer of Suppose you are interested in testing the...

Question 2

What is quantile regression? When might it be preferred to OLS? Explain.

Accepted Answer

The answer of What is quantile regression? When might it...

Question 3

What is non-negative count data? Why does it present a concern for OLS? How might you control for non-negative count data in the estimation process? Explain.

Accepted Answer

The answer of What is non-negative count data? Why does...

Question 4

In which of the following cases would you want to use difference-in-difference estimation?
A)When individuals non-randomly select different outcomes of the dependent variable.
B)When you are attempting to replicate a randomized clinical trial.
C)When you are dealing with non-negative count data.
D)When you suspect that the marginal effects are different for different values of the dependent variable.

Accepted Answer

Difference-in-difference estimation is particularly useful when trying to replicate a randomized clinical trial. It is a quasi-experimental design that compares the change in the outcome variable over time between a treatment group and a control group. This is particularly useful in situations where it is not ethical or feasible to conduct a randomized trial. The other options do not necessarily require difference-in-difference estimation to be the best choice.

Question 5

Suppose you are interested in explaining the number of surfers surfing at your favorite spot on a given day.After collecting data on the number of surfers,the height of the waves (in feet),the water temperature,and whether the day was a weekend on a sample of 92 days,you estimate the following marginal effects for the Poisson model $$\begin{array} { lll l} 
\text { Surfers } _ { i } = & 13.653 + 6.029 \text { Height } _ { i } +& 0.596 \text { Temperature } _ { i } +& 4.076 \text { Weekend } _ { i } \
&( 3.824 ) ( 2.137 ) & ( 0.202 ) & ( 1.382 )
\end{array}$$ 
a)Why is OLS not appropriate in this circumstance? How does a Poisson model improve on OLS?
b)Discuss the results.
c)What assumption is necessary for Poisson to be the appropriate model? How would you test this assumption? If this assumption fails,what alternative model could you estimate?

Accepted Answer

The answer of Suppose you are interested in explaining the...

Question 6

Suppose you are interested in explaining the effect that family income (thousands)has on child birth weight and you are concerned that the true marginal effects differ for at different points in the birth weight distribution.In a sample of 22,365 live births,you estimate following $\begin{array}{llll}
10^{\text {th }}  \text { Percentile:} &  Burt \widehat {h W }etght _ { i } =&5.583+0.086 \text { Income }_{i}&+0.084 \text { Education }_{i} \
&& (1.473)(0.032)&( (0.029)\
25^{\text {th }}\text { Percentile:} &  Burt \widehat {h W }etght _ { i } =& 6.012+0.073 \text { Income }_{i}&+0.076 \text { Education }_{i}\
&& (2.533)   (0.027)& (0.038) \
50^{\text {th }} \text { Percentile:} &  Burt \widehat {h W }etght _ { i } =& 6.309+0.069 \text { Income }_{i}&+0.091 \text { Education }_{i}\
&& (1.925)(0.022)&(0.042) \
75^{\text {th }} \text { Percentile:} &  Burt \widehat {h W }etght _ { i } =& 6.733+0.057 \text { income }_{i}&+0.074 \text { Education }_{i}\
&& (2.437)(0.026)& (0.029) \
90^{\text {th }} \text { Percentile:} &  Burt \widehat {h W }etght _ { i } =& 7.024+0.033 \text { Income }_{i}&+0.065 \text { Education }_{i}\
&& (1.847)(0.013) & (0.031) \
\end{array}$
 
a)What is quantile regression? Which variable is the quantile of?
b)In what circumstances would quantile regression be preferable to OLS?
c)Discuss the results presented above.

Accepted Answer

The answer of Suppose you are interested in explaining the...

Question 7

What is sample-selection bias? Why does it present a problem for OLS? How can you control for its presence? Explain.

Accepted Answer

The answer of What is sample-selection bias? Why does it...

Question 8

Suppose you observe that several different communities in a large metropolitan area raised their sales tax by one percentage point in 2012 while several others did not.In an effort to determine how the increase affected car sales in the affected communities you estimate a difference-in-difference estimator for 2011 and 2013 car sales and get $$\begin{array} { l } 
\text { Car Sales }_{i}=&987.25+&17.082013_{i}+&1.47 \text { Treatment }_{i}-&8.32(2013 * \text { Treatment })_{i}\
&(311.24) &(5.33)&(0.56)&(2.46)  \
\end{array}$$ 
a)Why would you want to estimate a difference in difference model?
b)Draw a graph with the 4 means on it and explain where the difference in difference estimator is on the graph.

Accepted Answer

The answer of Suppose you observe that several different communities...

Question 9

What is a difference-in-difference estimator? When is it appropriate to use one? How do you do so? Explain.

Accepted Answer

The answer of What is a difference-in-difference estimator? When is...

Quiz 15: Quantile Regression, Count Data, Sample Selection Bias, and Quasi-Experimental Methods

What is quantile regression? When might it be preferred to OLS? Explain.

What is non-negative count data? Why does it present a concern for OLS? How might you control for non-negative count data in the estimation process? Explain.

In which of the following cases would you want to use difference-in-difference estimation?

What is sample-selection bias? Why does it present a problem for OLS? How can you control for its presence? Explain.

What is a difference-in-difference estimator? When is it appropriate to use one? How do you do so? Explain.