MurderRates {AER}

Determinants of Murder Rates in the United States

Description

Cross-section data on states in 1950.

Usage

data("MurderRates")

Format

A data frame containing 44 observations on 8 variables.

rate

Murder rate per 100,000 (FBI estimate, 1950).

convictions

Number of convictions divided by number of murders in 1950.

executions

Average number of executions during 1946–1950 divided by convictions in 1950.

time

Median time served (in months) of convicted murderers released in 1951.

income

Median family income in 1949 (in 1,000 USD).

lfp

Labor force participation rate in 1950 (in percent).

noncauc

Proportion of population that is non-Caucasian in 1950.

southern

Factor indicating region.

Source

Maddala (2001), Table 8.4, p. 330

References

Maddala, G.S. (2001). Introduction to Econometrics, 3rd ed. New York: John Wiley.

McManus, W.S. (1985). Estimates of the Deterrent Effect of Capital Punishment: The Importance of the Researcher's Prior Beliefs. Journal of Political Economy, 93, 417–425.

Stokes, H. (2004). On the Advantage of Using Two or More Econometric Software Systems to Solve the Same Problem. Journal of Economic and Social Measurement, 29, 307–320.

Examples

data("MurderRates")

## Maddala (2001, pp. 331)
fm_lm <- lm(rate ~ . + I(executions > 0), data = MurderRates)
summary(fm_lm)

model <- I(executions > 0) ~ time + income + noncauc + lfp + southern
fm_lpm <- lm(model, data = MurderRates)
summary(fm_lpm)

## Binomial models. Note: southern coefficient
fm_logit <- glm(model, data = MurderRates, family = binomial)
summary(fm_logit)

fm_logit2 <- glm(model, data = MurderRates, family = binomial,
  control = list(epsilon = 1e-15, maxit = 50, trace = FALSE))
summary(fm_logit2)

fm_probit <- glm(model, data = MurderRates, family = binomial(link = "probit"))
summary(fm_probit)

fm_probit2 <- glm(model, data = MurderRates , family = binomial(link = "probit"),
  control = list(epsilon = 1e-15, maxit = 50, trace = FALSE))
summary(fm_probit2)

## Explanation: quasi-complete separation
with(MurderRates, table(executions > 0, southern))