Wooldridge Source: I collected these data from the 1997 Economic Report of the President. Specifically, the data come from Tables B-71, 15, 29, and 32. Data loads lazily.
data('consump')
A data.frame with 37 observations on 24 variables:
year: 1959-1995
i3: 3 mo. T-bill rate
inf: inflation rate; CPI
rdisp: disp. inc., 1992 $, bils.
rnondc: nondur. cons., 1992 $, bils.
rserv: services, 1992 $, bils.
pop: population, 1000s
y: per capita real disp. inc.
rcons: rnondc + rserv
c: per capita real cons.
r3: i3 - inf; real ex post int.
lc: log(c)
ly: log(y)
gc: lc - lc[_n-1]
gy: ly - ly[_n-1]
gc_1: gc[_n-1]
gy_1: gy[_n-1]
r3_1: r3[_n-1]
lc_ly: lc - ly
lc_ly_1: lc_ly[_n-1]
gc_2: gc[_n-2]
gy_2: gy[_n-2]
r3_2: r3[_n-2]
lc_ly_2: lc_ly[_n-2]
https://www.cengage.com/cgi-wadsworth/course_products_wp.pl?fid=M20b&product_isbn_issn=9781111531041
For a student interested in time series methods, updating this data set and using it in a manner similar to that in the text could be acceptable as a final project.
Used in Text: pages 377-378, 408-409, 442, 570-571, 579, 673
#> 'data.frame': 37 obs. of 24 variables: #> $ year : int 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 ... #> $ i3 : num 3.41 2.93 2.38 2.78 3.16 ... #> $ inf : num 0.7 1.7 1 1 1.3 ... #> $ rdisp : num 1530 1565 1616 1694 1756 ... #> $ rnondc : num 606 615 627 646 660 ... #> $ rserv : num 687 717 746 783 819 ... #> $ pop : num 177830 180671 183691 186538 189242 ... #> $ y : num 8604 8664 8796 9080 9276 ... #> $ rcons : num 1294 1333 1373 1430 1479 ... #> $ c : num 7275 7377 7476 7665 7814 ... #> $ r3 : num 2.71 1.23 1.38 1.78 1.86 ... #> $ lc : num 8.89 8.91 8.92 8.94 8.96 ... #> $ ly : num 9.06 9.07 9.08 9.11 9.14 ... #> $ gc : num NA 0.0139 0.0133 0.0251 0.0192 ... #> $ gy : num NA 0.00696 0.01511 0.03171 0.02145 ... #> $ gc_1 : num NA NA 0.0139 0.0133 0.0251 ... #> $ gy_1 : num NA NA 0.00696 0.01511 0.03171 ... #> $ r3_1 : num NA 2.71 1.23 1.38 1.78 ... #> $ lc_ly : num -0.168 -0.161 -0.163 -0.169 -0.172 ... #> $ lc_ly_1: num NA -0.168 -0.161 -0.163 -0.169 ... #> $ gc_2 : num NA NA NA 0.0139 0.0133 ... #> $ gy_2 : num NA NA NA 0.00696 0.01511 ... #> $ r3_2 : num NA NA 2.71 1.23 1.38 ... #> $ lc_ly_2: num NA NA -0.168 -0.161 -0.163 ... #> - attr(*, "time.stamp")= chr "25 Jun 2011 23:03"