MurderRates | R Documentation |

## 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))
```