IRCA: Data on the Evaluation of the Immigration Reform and Control...

In nndd: Nearest Neighbour Matching (NN) followed by a Linear Model with Difference in Differences (DD)

Description

The data is adapted data of Baker(2015). The author used the original data to examine the effects of the Immigration Reform and Control Act on crime. The IRCA was implemented in 1986 and forbid to hire or recruit undocumented immigrants. However the IRCA also implemented a near-universal legalization of immigrants in the United States. The theory behind a positive impact of the IRCA on crime is that an increased labour market opportunity due to IRCA increases legal work and decreases crime. The labour market opportunity is expected to increase because legal (documented) immigrants have a higher salary and lower change to be fired.

Usage

data("IRCA")

Format

A data frame containing 31206 observations on 21 variables. In detail it is a balanced data panel of 1486 US counties over 21 years (the time span is 1980 till 2000).

county

Observation county.

year

Observation year.

pop

Log population.

immigrants_pc

CumWeightedAllImmPerCap.

unemprate

Unemployment rate.

povrate

Poverty rate.

immigrant_all

AllTimeWeightedImm.

crack_index

Crack Index

abortions

Number of abortions lag 13 per capita.

crimes

The logarithm of the total amount of all crimes per capita.

v_crime

The logarithm of the total amount of violent crimes per capita.

p_crime

The logarithm of the total amount of property crimes per capita.

officers_pc

Number of officers per capita.

income

The logarithm of the average income.

empl

The logarithm of the employment.

sim_CumWeightedAllImmPerCap

sim_CumWeightedAllImmPerCap.

sim_diff

sim_diff.

treated

Treated states. Defined as stated which immigrants_pc was larger then 0 after the reform.

post

Identifier for the post treatment period.

StateFIPS

StateFIPS

CountyFIPS

CountyFIPS

Source

Adapted supplementary material of Baker(2015).

References

Baker, S. R. (2015). Effects of Immigrant Legalization on Crime, American Economic Review, 105(5): 210-213.

Examples

data("IRCA", package = "nndd")
library(Formula)
formula <- Formula(treated | v_crime ~ officers_pc + income + p_crime | 
					officers_pc + income + p_crime + crack_index + unemprate) 
					
ma <- nndd(formula = formula, data = IRCA, 
			index = c("county", "year"), 
			nn_time = c("1985","1985" ), t_time = "1986" )

ma
#plot(ma, IRCA)

nndd documentation built on May 2, 2019, 6:52 p.m.