
Introduction to Econometrics 3rd Edition by James Stock, Mark Watson
Edition 3ISBN: 978-9352863501
Introduction to Econometrics 3rd Edition by James Stock, Mark Watson
Edition 3ISBN: 978-9352863501 Exercise 13
Some U.S. states have enacted laws that allow citizens to carry concealed weapons. These laws are known as "shall-issue" laws because they instruct local authorities to issue a concealed weapons permit to all applicants who are citizens, are mentally competent, and have not been convicted of a felony (some states have some additional restrictions). Proponents argue that if more people carry concealed weapons, crime will decline because criminals are deterred from attacking other people. Opponents argue that crime will increase because of accidental or spontaneous use of the weapon. In this exercise, you will analyze the effect of concealed weapons laws on violent crimes. On the textbook Web site www.pearsonhighered.com/stock_watson you will find a data file Guns that contains a balanced panel of data from 50 U.S. states plus the District of Columbia for the years 1977 through 1999. 3 A detailed description is given in Guns_Description, available on the Web site.
a. Estimate (1) a regression of ln( vio ) against shall and (2) a regression of ln( vio ) against shall, incarc_rate, density, avginc,pop,pb1064, pw1064, and pm1029.
i. Interpret the coefficient on shall in regression (2). Is this estimate large or small in a "real-world" sense
ii. Does adding the control variables in regression (2) change the estimated effect of a shall-carry law in regression (1) as measured by statistical significance As measured by the "real-world" significance of the estimated coefficient
iii. Suggest a variable that varies across states but plausibly varies little-or not at all-over time and that could cause omitted variable bias in regression (2).
b. Do the results change when you add fixed state effects If so, which set of regression results is more credible and why
c. Do the results change when you add fixed time effects If so, which set of regression results is more credible and why
d. Repeat the analysis using In (rob) and In (mur) in place of ln(Wo).
e. In your view, what are the most important remaining threats to the internal validity of this regression analysis
f. Based on your analysis, what conclusions would you draw about the effects of concealed-weapon laws on these crime rates
a. Estimate (1) a regression of ln( vio ) against shall and (2) a regression of ln( vio ) against shall, incarc_rate, density, avginc,pop,pb1064, pw1064, and pm1029.
i. Interpret the coefficient on shall in regression (2). Is this estimate large or small in a "real-world" sense
ii. Does adding the control variables in regression (2) change the estimated effect of a shall-carry law in regression (1) as measured by statistical significance As measured by the "real-world" significance of the estimated coefficient
iii. Suggest a variable that varies across states but plausibly varies little-or not at all-over time and that could cause omitted variable bias in regression (2).
b. Do the results change when you add fixed state effects If so, which set of regression results is more credible and why
c. Do the results change when you add fixed time effects If so, which set of regression results is more credible and why
d. Repeat the analysis using In (rob) and In (mur) in place of ln(Wo).
e. In your view, what are the most important remaining threats to the internal validity of this regression analysis
f. Based on your analysis, what conclusions would you draw about the effects of concealed-weapon laws on these crime rates
Explanation
b) The next regression updates part (a) ...
Introduction to Econometrics 3rd Edition by James Stock, Mark Watson
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