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Name:

Description:

a panel of 90 observations from 1981 to 1987

number of observations : 630

observation : regional

country : United States

Variables:

A dataframe containing :

county

county identifier

year

year from 1981 to 1987

crmrte

crimes committed per person

prbarr

'probability' of arrest

prbconv

'probability' of conviction

prbpris

'probability' of prison sentence

avgsen

average sentence, days

polpc

police per capita

density

hundreds of people per square mile

taxpc

tax revenue per capita

region

one of 'other', 'west' or 'central'

smsa

'yes' or 'no' if in SMSA

pctmin

percentage minority in 1980

wcon

weekly wage in construction

wtuc

weekly wage in trns, util, commun

wtrd

weekly wage in whole sales and retail trade

wfir

weekly wage in finance, insurance and real estate

wser

weekly wage in service industry

wmfg

weekly wage in manufacturing

wfed

weekly wage of federal employees

wsta

weekly wage of state employees

wloc

weekly wage of local governments employees

mix

offence mix: face-to-face/other

pctymle

percentage of young males

Link To Google Sheets:

Rows:

Columns:

License Type:

References/Notes/Attributions:

Note

Thanks to Yungfong "Frank" Tang for identifying an error in the description of "density", previously documented erroneously as only "people per square mile".

Source

Cornwell, C. and W.N. Trumbull (1994) “Estimating the economic model of crime with panel data”, Review of Economics and Statistics, 76, 360–366.

Baltagi, B. H. (forthcoming) “Estimating an economic model of crime using panel data from North Carolina”, Journal of Applied Econometrics.

CRIME4.DES

References

Baltagi, Badi H. (2003) Econometric analysis of panel data, John Wiley and sons, http://www.wiley.com/legacy/wileychi/baltagi/, .

Journal of Applied Econometrics data archive : http://qed.econ.queensu.ca/jae/.

See Also

Index.Source, Index.Economics, Index.Econometrics, Index.Observations, Index.Time.Series, Crime

R Dataset Upload:

Use the following R code to directly access this dataset in R.

d <- read.csv("https://www.key2stats.com/Crime_in_North_Carolina_530_36.csv")

R Coding Interface:


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