Last data update: 2014.03.03
|
R: More Guns, Less Crime?
More Guns, Less Crime?
Description
Guns is a balanced panel of data on 50 US states, plus the District of Columbia (for a
total of 51 states), by year for 1977–1999.
Usage
data("Guns")
Format
A data frame containing 1,173 observations on 13 variables.
- state
factor indicating state.
- year
factor indicating year.
- violent
violent crime rate (incidents per 100,000 members of the population).
- murder
murder rate (incidents per 100,000).
- robbery
robbery rate (incidents per 100,000).
- prisoners
incarceration rate in the state in the previous year
(sentenced prisoners per 100,000 residents; value for the previous year).
- afam
percent of state population that is African-American, ages 10 to 64.
- cauc
percent of state population that is Caucasian, ages 10 to 64.
- male
percent of state population that is male, ages 10 to 29.
- population
state population, in millions of people.
- income
real per capita personal income in the state (US dollars).
- density
population per square mile of land area, divided by 1,000.
- law
factor. Does the state have a shall carry law in effect in that year?
Details
Each observation is a given state in a given year.
There are a total of 51 states times 23 years = 1,173 observations.
Source
Online complements to Stock and Watson (2007).
http://wps.aw.com/aw_stock_ie_2/0,12040,3332253-,00.html
References
Ayres, I., and Donohue, J.J. (2003). Shooting Down the ‘More Guns Less Crime’ Hypothesis.
Stanford Law Review, 55, 1193–1312.
Stock, J.H. and Watson, M.W. (2007). Introduction to Econometrics, 2nd ed. Boston: Addison Wesley.
See Also
StockWatson2007
Examples
## data
data("Guns")
## visualization
library("lattice")
xyplot(log(violent) ~ as.numeric(as.character(year)) | state, data = Guns, type = "l")
## Stock & Watson (2007), Empirical Exercise 10.1, pp. 376--377
fm1 <- lm(log(violent) ~ law, data = Guns)
coeftest(fm1, vcov = sandwich)
fm2 <- lm(log(violent) ~ law + prisoners + density + income +
population + afam + cauc + male, data = Guns)
coeftest(fm2, vcov = sandwich)
fm3 <- lm(log(violent) ~ law + prisoners + density + income +
population + afam + cauc + male + state, data = Guns)
printCoefmat(coeftest(fm3, vcov = sandwich)[1:9,])
fm4 <- lm(log(violent) ~ law + prisoners + density + income +
population + afam + cauc + male + state + year, data = Guns)
printCoefmat(coeftest(fm4, vcov = sandwich)[1:9,])
Results
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(AER)
Loading required package: car
Loading required package: lmtest
Loading required package: zoo
Attaching package: 'zoo'
The following objects are masked from 'package:base':
as.Date, as.Date.numeric
Loading required package: sandwich
Loading required package: survival
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/AER/Guns.Rd_%03d_medium.png", width=480, height=480)
> ### Name: Guns
> ### Title: More Guns, Less Crime?
> ### Aliases: Guns
> ### Keywords: datasets
>
> ### ** Examples
>
> ## data
> data("Guns")
>
> ## visualization
> library("lattice")
> xyplot(log(violent) ~ as.numeric(as.character(year)) | state, data = Guns, type = "l")
>
> ## Stock & Watson (2007), Empirical Exercise 10.1, pp. 376--377
> fm1 <- lm(log(violent) ~ law, data = Guns)
> coeftest(fm1, vcov = sandwich)
t test of coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 6.134919 0.019287 318.078 < 2.2e-16 ***
lawyes -0.442965 0.047488 -9.328 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> fm2 <- lm(log(violent) ~ law + prisoners + density + income +
+ population + afam + cauc + male, data = Guns)
> coeftest(fm2, vcov = sandwich)
t test of coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.9817e+00 6.0668e-01 4.9149 1.016e-06 ***
lawyes -3.6839e-01 3.4654e-02 -10.6304 < 2.2e-16 ***
prisoners 1.6126e-03 1.8000e-04 8.9591 < 2.2e-16 ***
density 2.6688e-02 1.4294e-02 1.8671 0.062142 .
income 1.2051e-06 7.2498e-06 0.1662 0.868007
population 4.2710e-02 3.1345e-03 13.6255 < 2.2e-16 ***
afam 8.0853e-02 1.9916e-02 4.0598 5.241e-05 ***
cauc 3.1200e-02 9.6897e-03 3.2200 0.001317 **
male 8.8709e-03 1.2014e-02 0.7384 0.460435
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> fm3 <- lm(log(violent) ~ law + prisoners + density + income +
+ population + afam + cauc + male + state, data = Guns)
> printCoefmat(coeftest(fm3, vcov = sandwich)[1:9,])
Estimate Std. Error t value Pr(>|t|)
(Intercept) 4.0368e+00 3.7479e-01 10.7708 < 2.2e-16 ***
lawyes -4.6141e-02 1.9435e-02 -2.3741 0.01776 *
prisoners -7.1008e-05 9.4831e-05 -0.7488 0.45414
density -1.7229e-01 1.0221e-01 -1.6857 0.09213 .
income -9.2037e-06 6.5619e-06 -1.4026 0.16102
population 1.1525e-02 9.4572e-03 1.2186 0.22325
afam 1.0428e-01 1.6133e-02 6.4636 1.526e-10 ***
cauc 4.0861e-02 5.2487e-03 7.7850 1.585e-14 ***
male -5.0273e-02 7.5923e-03 -6.6215 5.518e-11 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
> fm4 <- lm(log(violent) ~ law + prisoners + density + income +
+ population + afam + cauc + male + state + year, data = Guns)
> printCoefmat(coeftest(fm4, vcov = sandwich)[1:9,])
Estimate Std. Error t value Pr(>|t|)
(Intercept) 3.9720e+00 4.3322e-01 9.1685 < 2.2e-16 ***
lawyes -2.7994e-02 1.8692e-02 -1.4976 0.1345
prisoners 7.5994e-05 8.0008e-05 0.9498 0.3424
density -9.1555e-02 6.2588e-02 -1.4628 0.1438
income 9.5859e-07 6.9440e-06 0.1380 0.8902
population -4.7545e-03 6.4673e-03 -0.7351 0.4624
afam 2.9186e-02 2.0298e-02 1.4379 0.1507
cauc 9.2500e-03 8.2188e-03 1.1255 0.2606
male 7.3326e-02 1.8116e-02 4.0475 5.542e-05 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
>
>
>
>
>
> dev.off()
null device
1
>
|
|