ECON7020X:
I: SPSS, submit your syntax file and the output file. [5 points]
In the Guns dataset uploaded with this HW, there is data for 50 US states and the District of Columbia for twenty years from 1979-1999.
Data Description:
Variable
Definition
vio
Violent crime rate (incidents per 100,00 members of the population)
rob
Robbery rate (incidents per 100,000)
mur
Murder rate (incidents per 100,000)
shall
=1 if the state has a shall-carry law in effect for that year =0 otherwise
incarc_rate
Incarceration rate in the state in the previous year (sentenced prisoners per 100,000 residents; value for the previous year)
density
Population per square mile of land area, divided by 1000
avginc
Real per capita personal income in the state, in thousands of dollars
pop
State population, in millions of people
pm1029
Percentage of state population that is male, ages 10 to 29
pw1064
Percentage of state population that is white, ages 10 to 64
pb1064
Percentage of state population that is black, ages 10 to 64
stateid
ID number of states (Alabama = 1, Alaska = 2 etc.)
year
1979-99
1. Estimate a regression of ln(vio) against shall, incarc_rate, density, avginc, pop, pb1064, pw1064 and pm1029. Use HC1 standard errors. The regression model should have an intercept.
2. Add in state fixed effects to the regression in Q1. Use HC1. Do not include an intercept in this regression.
3. Add in time fixed effects to the regression in Q1. Use HC1. Do not include an intercept in this regression.
4. Add in both state and time fixed effects to the regression in Q1. Use HC1. Do not include an intercept in this regression.
5. Examine the results from the 4 models you’ve estimated. Comment specifically on the coefficient on shall. Does the magnitude or sign or significance of the variable change as you add in state, time or both state and time fixed effects? You can use a 5% level of significance to compare, if needed.
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