Wooldridge Source: From Businessweek R&D Scoreboard, October 25, 1991. Data loads lazily.

data('rdchem')

Format

A data.frame with 32 observations on 8 variables:

  • rd: R&D spending, millions

  • sales: firm sales, millions

  • profits: profits, millions

  • rdintens: rd as percent of sales

  • profmarg: profits as percent of sales

  • salessq: sales^2

  • lsales: log(sales)

  • lrd: log(rd)

Source

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

Notes

It would be interesting to collect more recent data and see whether the R&D/firm size relationship has changed over time.

Used in Text: pages 64, 139-140, 159-160, 204, 218, 327-329, 339

Examples

str(rdchem)
#> 'data.frame': 32 obs. of 8 variables: #> $ rd : num 430.6 59 23.5 3.5 1.7 ... #> $ sales : num 4570 2830 597 134 42 ... #> $ profits : num 186.9 467 107.4 -4.3 8 ... #> $ rdintens: num 9.42 2.08 3.94 2.62 4.05 ... #> $ profmarg: num 4.09 16.5 18 -3.22 19.05 ... #> $ salessq : num 20886730 8008900 356170 17849 1764 ... #> $ lsales : num 8.43 7.95 6.39 4.89 3.74 ... #> $ lrd : num 6.065 4.078 3.157 1.253 0.531 ... #> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"