Wooldridge Source: A.J. Castillo-Freeman and R.B. Freeman (1992), “When the Minimum Wage Really Bites: The Effect of the U.S.-Level Minimum Wage on Puerto Rico,” in Immigration and the Work Force, edited by G.J. Borjas and R.B. Freeman, 177-211. Chicago: University of Chicago Press. The data are reported in the article. Data loads lazily.

data('prminwge')

Format

A data.frame with 38 observations on 25 variables:

  • year: 1950-1987

  • avgmin: weighted avg min wge, 44 indust

  • avgwage: wghted avg hrly wge, 44 indust

  • kaitz: Kaitz min wage index

  • avgcov: wghted avg coverage, 8 indust

  • covt: economy-wide coverage of min wg

  • mfgwage: avg manuf. wage

  • prdef: Puerto Rican price deflator

  • prepop: PR employ/popul ratio

  • prepopf: PR employ/popul ratio, alter.

  • prgnp: PR GNP

  • prunemp: PR unemployment rate

  • usgnp: US GNP

  • t: time trend: 1 to 38

  • post74: time trend: starts in 1974

  • lprunemp: log(prunemp)

  • lprgnp: log(prgnp)

  • lusgnp: log(usgnp)

  • lkaitz: log(kaitz)

  • lprun_1: lprunemp[_n-1]

  • lprepop: log(prepop)

  • lprep_1: lprepop[_n-1]

  • mincov: (avgmin/avgwage)*avgcov

  • lmincov: log(mincov)

  • lavgmin: log(avgmin)

Source

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

Notes

Given the ongoing debate on the employment effects of the minimum wage, this would be a great data set to try to update. The coverage rates are the most difficult variables to construct.

Used in Text: pages 356-357, 369-370, 420-421, 434

Examples

str(prminwge)
#> 'data.frame': 38 obs. of 25 variables: #> $ year : int 1950 1951 1952 1953 1954 1955 1956 1957 1958 1959 ... #> $ avgmin : num 0.198 0.209 0.225 0.311 0.313 ... #> $ avgwage : num 0.398 0.41 0.421 0.48 0.508 ... #> $ kaitz : num 0.155 0.164 0.18 0.229 0.211 ... #> $ avgcov : num 0.201 0.207 0.226 0.231 0.224 ... #> $ covt : num 0.29 0.29 0.29 0.29 0.29 ... #> $ mfgwage : num 0.43 0.45 0.48 0.5 0.52 ... #> $ prdef : num 0.859 0.881 0.953 0.97 1 ... #> $ prepop : num 0.47 0.449 0.434 0.428 0.415 ... #> $ prepopf : num 0.47 0.449 0.434 0.428 0.415 ... #> $ prgnp : num 879 925 1016 1081 1104 ... #> $ prunemp : num 15.4 16 14.8 14.5 15.3 ... #> $ usgnp : num 1204 1328 1380 1435 1416 ... #> $ t : int 1 2 3 4 5 6 7 8 9 10 ... #> $ post74 : int 0 0 0 0 0 0 0 0 0 0 ... #> $ lprunemp: num 2.73 2.77 2.69 2.67 2.73 ... #> $ lprgnp : num 6.78 6.83 6.92 6.99 7.01 ... #> $ lusgnp : num 7.09 7.19 7.23 7.27 7.26 ... #> $ lkaitz : num -1.86 -1.81 -1.71 -1.47 -1.56 ... #> $ lprun_1 : num NA -1.87 -1.83 -1.91 -1.93 ... #> $ lprepop : num -0.755 -0.801 -0.835 -0.849 -0.879 ... #> $ lprep_1 : num NA -0.755 -0.801 -0.835 -0.849 ... #> $ mincov : num 0.1 0.106 0.121 0.15 0.138 ... #> $ lmincov : num -2.3 -2.25 -2.11 -1.9 -1.98 ... #> $ lavgmin : num -1.62 -1.57 -1.49 -1.17 -1.16 ... #> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"