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 arc citizens, are mentally competent, and have not been convicted of a felony (some states have some additional restrictions). Proponents argue that. it 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. 

a. Estimate a regression of ln(vio) against shall and (2) a regression of ln( yin) against shalt incarcrate, density, avginc. pop, pb1064, pw!064. and pni1029.

i. Interpret the coefficient on shall in regression (2). Is this estimatc 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 tw
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 vari;thIC
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 tn(rob) and ln(misr) in place of ln(vio).

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?