SeatBelt: Seat Belt Usage and Traffic Fatalities

In pder: Panel Data Econometrics with R

Description

yearly observations of 51 states from 1983 to 1997

number of observations : 765

number of time-series : 15

country : United States

package : panel

JEL codes: R41, K42

Chapter : 06

Usage

data(SeatBelt)

Format

A dataframe containing:

state

the state code

year

the year

farsocc

the number of traffic fatalities of drivers and passengers (of any seating position) of a motor vehicule in transport

farsnocc

the number of traffic fatalities of pedestrians and bicyclists

usage

rate of seat belt usage

percapin

median income in current US dollars

unemp

unemployment rate

meanage

mean age

precentb

the percentage of african-americans in the state population

precenth

the percentage of people of hispanic origin in the state population

densurb

traffic density urban ; registered vehicules per unit length of urban roads in miles

densrur

traffic density rural ; registered vehicules per unit length of urban roads in miles

viopcap

number of violent crimes (homicide, rape and robbery) per capita

proppcap

number of preperty rimes (burglary, larceny and auto theft) per capita

vmtrural

vehicule miles traveled on rural roads

vmturban

vehicule miles traveled on urban roads

fueltax

fuel tax (in curent cents)

lim65

65 miles per hour speed limit (55 mph is the base category)

lim70p

70 miles per hour or above speed limit (55 mph is the base caegory)

mlda21

a dummy variable that is equal to 1 for a minimum for a minimum legal drinking age of 21 years (18 years is the base category)

bac08

a dummy variable that is equal to 1 foe a maximum of 0.08 blood alcohol content (0.1 is the base category)

ds

a dummy equal to 1 for the periods in which the state had a secondary-enforcement mandatory seat belt law, or a primary-enforcement law that preceded by a secondary-enforcement law (no seat belt law is the base category)

dp

a dummy variable eqal to 1 for the periods in which the state had a primary-enforcement mandatory seat belt law that was not preceded by a secondary-enforcement law (no seat belt is the base category)

dsp

a dummy variable equal to 1 for the periods in which the state had a primary-enforcement mandatory seat belt law that was preceded by a secondary enforcement law (no seat belt law is the base category

Source

author's website https://leinav.people.stanford.edu

References

Cohen, Alma and Liran Einav (2003) “The Effects of Mandatory Seat Belt Laws on Driving Behavior and Traffic Fatalities”, The Review of Economics and Statistics, 85(4), 828-843, doi: 10.2139/ssrn.293582 .

Examples

#### Example 6-1

## ------------------------------------------------------------------------
## Not run: 
library("plm")

## ------------------------------------------------------------------------
y ~ x1 + x2 + x3 | x1 + x3 + z
y ~ x1 + x2 + x3 | . - x2 + z

## ------------------------------------------------------------------------

data("SeatBelt", package = "pder")
SeatBelt$occfat <- with(SeatBelt, log(farsocc / (vmtrural + vmturban)))
ols <- plm(occfat ~ log(usage) + log(percapin) + log(unemp) + log(meanage) + 
           log(precentb) + log(precenth)+ log(densrur) + 
           log(densurb) + log(viopcap) + log(proppcap) +
           log(vmtrural) + log(vmturban) + log(fueltax) +
           lim65 + lim70p + mlda21 + bac08, SeatBelt, 
           effect = "time")
fe <- update(ols, effect = "twoways")
ivfe <- update(fe, . ~ . |  . - log(usage) + ds + dp +dsp)

rbind(ols = coef(summary(ols))[1,],
      fe = coef(summary(fe))[1, ],
      w2sls = coef(summary(ivfe))[1, ])

## ------------------------------------------------------------------------
SeatBelt$noccfat <- with(SeatBelt, log(farsnocc / (vmtrural + vmturban)))
nivfe <- update(ivfe, noccfat ~ . | .)
coef(summary(nivfe))[1, ]

## End(Not run)

pder documentation built on Jan. 27, 2022, 1:12 a.m.