Guns {AER} | R Documentation

## 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).

### 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,])

[Package AER version 1.2-5 Index]