Wooldridge Source: From C. Cornwell and W. Trumball (1994), “Estimating the Economic Model of Crime with Panel Data,” Review of Economics and Statistics 76, 360-366. Professor Cornwell kindly provided the data. Data loads lazily.

data('crime4')

Format

A data.frame with 630 observations on 59 variables:

  • county: county identifier

  • year: 81 to 87

  • crmrte: crimes committed per person

  • prbarr: 'probability' of arrest

  • prbconv: 'probability' of conviction

  • prbpris: 'probability' of prison sentenc

  • avgsen: avg. sentence, days

  • polpc: police per capita

  • density: people per sq. mile

  • taxpc: tax revenue per capita

  • west: =1 if in western N.C.

  • central: =1 if in central N.C.

  • urban: =1 if in SMSA

  • pctmin80: perc. minority, 1980

  • wcon: weekly wage, construction

  • wtuc: wkly wge, trns, util, commun

  • wtrd: wkly wge, whlesle, retail trade

  • wfir: wkly wge, fin, ins, real est

  • wser: wkly wge, service industry

  • wmfg: wkly wge, manufacturing

  • wfed: wkly wge, fed employees

  • wsta: wkly wge, state employees

  • wloc: wkly wge, local gov emps

  • mix: offense mix: face-to-face/other

  • pctymle: percent young male

  • d82: =1 if year == 82

  • d83: =1 if year == 83

  • d84: =1 if year == 84

  • d85: =1 if year == 85

  • d86: =1 if year == 86

  • d87: =1 if year == 87

  • lcrmrte: log(crmrte)

  • lprbarr: log(prbarr)

  • lprbconv: log(prbconv)

  • lprbpris: log(prbpris)

  • lavgsen: log(avgsen)

  • lpolpc: log(polpc)

  • ldensity: log(density)

  • ltaxpc: log(taxpc)

  • lwcon: log(wcon)

  • lwtuc: log(wtuc)

  • lwtrd: log(wtrd)

  • lwfir: log(wfir)

  • lwser: log(wser)

  • lwmfg: log(wmfg)

  • lwfed: log(wfed)

  • lwsta: log(wsta)

  • lwloc: log(wloc)

  • lmix: log(mix)

  • lpctymle: log(pctymle)

  • lpctmin: log(pctmin)

  • clcrmrte: lcrmrte - lcrmrte[_n-1]

  • clprbarr: lprbarr - lprbarr[_n-1]

  • clprbcon: lprbconv - lprbconv[_n-1]

  • clprbpri: lprbpri - lprbpri[t-1]

  • clavgsen: lavgsen - lavgsen[t-1]

  • clpolpc: lpolpc - lpolpc[t-1]

  • cltaxpc: ltaxpc - ltaxpc[t-1]

  • clmix: lmix - lmix[t-1]

Source

https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041

Notes

Computer Exercise C16.7 shows that variables that might seem to be good instrumental variable candidates are not always so good, especially after applying a transformation such as differencing across time. You could have the students do an IV analysis for just, say, 1987.

Used in Text: pages 471-472, 479, 504, 580

Examples

str(crime4)
#> 'data.frame': 630 obs. of 59 variables: #> $ county : int 1 1 1 1 1 1 1 3 3 3 ... #> $ year : int 81 82 83 84 85 86 87 81 82 83 ... #> $ crmrte : num 0.0399 0.0383 0.0303 0.0347 0.0366 ... #> $ prbarr : num 0.29 0.338 0.33 0.363 0.325 ... #> $ prbconv : num 0.402 0.433 0.526 0.605 0.579 ... #> $ prbpris : num 0.472 0.507 0.48 0.52 0.497 ... #> $ avgsen : num 5.61 5.59 5.8 6.89 6.55 ... #> $ polpc : num 0.00179 0.00177 0.00184 0.00189 0.00192 ... #> $ density : num 2.31 2.33 2.34 2.35 2.36 ... #> $ taxpc : num 25.7 24.9 26.5 26.8 28.1 ... #> $ west : int 0 0 0 0 0 0 0 0 0 0 ... #> $ central : int 1 1 1 1 1 1 1 1 1 1 ... #> $ urban : int 0 0 0 0 0 0 0 0 0 0 ... #> $ pctmin80: num 20.2 20.2 20.2 20.2 20.2 ... #> $ wcon : num 206 213 220 223 244 ... #> $ wtuc : num 334 369 1395 399 359 ... #> $ wtrd : num 182 190 197 201 207 ... #> $ wfir : num 272 301 310 350 383 ... #> $ wser : num 216 232 240 252 261 ... #> $ wmfg : num 229 240 270 282 299 ... #> $ wfed : num 409 420 439 459 490 ... #> $ wsta : num 236 254 250 262 281 ... #> $ wloc : num 231 237 249 264 289 ... #> $ mix : num 0.0999 0.103 0.0807 0.0785 0.0932 ... #> $ pctymle : num 0.0877 0.0864 0.0851 0.0838 0.0823 ... #> $ d82 : int 0 1 0 0 0 0 0 0 1 0 ... #> $ d83 : int 0 0 1 0 0 0 0 0 0 1 ... #> $ d84 : int 0 0 0 1 0 0 0 0 0 0 ... #> $ d85 : int 0 0 0 0 1 0 0 0 0 0 ... #> $ d86 : int 0 0 0 0 0 1 0 0 0 0 ... #> $ d87 : int 0 0 0 0 0 0 1 0 0 0 ... #> $ lcrmrte : num -3.22 -3.26 -3.5 -3.36 -3.31 ... #> $ lprbarr : num -1.24 -1.08 -1.11 -1.01 -1.12 ... #> $ lprbconv: num -0.911 -0.837 -0.643 -0.503 -0.547 ... #> $ lprbpris: num -0.75 -0.679 -0.735 -0.654 -0.699 ... #> $ lavgsen : num 1.72 1.72 1.76 1.93 1.88 ... #> $ lpolpc : num -6.33 -6.34 -6.3 -6.27 -6.25 ... #> $ ldensity: num 0.836 0.846 0.851 0.853 0.861 ... #> $ ltaxpc : num 3.25 3.21 3.28 3.29 3.34 ... #> $ lwcon : num 5.33 5.36 5.39 5.41 5.5 ... #> $ lwtuc : num 5.81 5.91 7.24 5.99 5.88 ... #> $ lwtrd : num 5.21 5.24 5.28 5.3 5.33 ... #> $ lwfir : num 5.61 5.71 5.74 5.86 5.95 ... #> $ lwser : num 5.37 5.44 5.48 5.53 5.56 ... #> $ lwmfg : num 5.43 5.48 5.6 5.64 5.7 ... #> $ lwfed : num 6.01 6.04 6.08 6.13 6.2 ... #> $ lwsta : num 5.46 5.54 5.52 5.57 5.64 ... #> $ lwloc : num 5.44 5.47 5.52 5.58 5.66 ... #> $ lmix : num -2.3 -2.27 -2.52 -2.54 -2.37 ... #> $ lpctymle: num -2.43 -2.45 -2.46 -2.48 -2.5 ... #> $ lpctmin : num 3.01 3.01 3.01 3.01 3.01 ... #> $ clcrmrte: num NA -0.0394 -0.2353 0.1362 0.0518 ... #> $ clprbarr: num NA 0.1545 -0.0229 0.0926 -0.1081 ... #> $ clprbcon: num NA 0.0741 0.194 0.14 -0.0439 ... #> $ clprbpri: num NA 0.071 -0.0553 0.0809 -0.0453 ... #> $ clavgsen: num NA -0.00357 0.03688 0.17221 -0.05061 ... #> $ clpolpc : num NA -0.0114 0.0384 0.0269 0.0202 ... #> $ cltaxpc : num NA -0.0326 0.0615 0.0147 0.0472 ... #> $ clmix : num NA 0.0309 -0.2447 -0.0273 0.1721 ... #> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"