Panel data on gross investment for 11 US firms over 20 years (1935–1954),
originally from Grunfeld (1958). This is a classic panel dataset used for
validating the IPCA estimator against the Python ipca package
(Kelly, Pruitt, Su, 2019).
Format
A data.frame with 220 rows and 5 variables:
- firm
Character; firm name (11 unique firms).
- year
Integer; year of observation (1935–1954).
- invest
Numeric; gross investment (millions of dollars).
- value
Numeric; market value of the firm (millions of dollars).
- capital
Numeric; stock of plant and equipment (millions of dollars).
Source
Grunfeld, Y. (1958). The Determinants of Corporate Investment.
Ph.D. thesis, Department of Economics, University of Chicago.
Loaded from the statsmodels Python package
(statsmodels.datasets.grunfeld).
References
Kelly, B. T., Pruitt, S., and Su, Y. (2019). Characteristics are Covariances: A Unified Model of Risk and Return. Journal of Financial Economics, 134(3), 501–524. doi:10.1016/j.jfineco.2019.05.001
Examples
head(grunfeld)
#> firm year invest value capital
#> 1 American Steel 1935 2.938 30.284 52.011
#> 2 American Steel 1936 5.643 43.909 52.903
#> 3 American Steel 1937 10.233 107.020 54.499
#> 4 American Steel 1938 4.046 68.306 59.722
#> 5 American Steel 1939 3.326 84.164 61.659
#> 6 American Steel 1940 4.680 69.157 62.243
# Reshape for ipca_est(): T x N matrix and T x N x L array
firms <- sort(unique(grunfeld$firm))
years <- sort(unique(grunfeld$year))
N <- length(firms)
TT <- length(years)
ret <- matrix(NA, TT, N)
Z <- array(NA, dim = c(TT, N, 2))
for (i in seq_along(firms)) {
idx <- grunfeld$firm == firms[i]
ret[, i] <- grunfeld$invest[idx]
Z[, i, 1] <- grunfeld$value[idx]
Z[, i, 2] <- grunfeld$capital[idx]
}
fit <- ipca_est(ret, Z, nfac = 1)
print(fit)
#> <sdim_fit [ipca]>
#> Observations : 20
#> Characteristics : 2
#> Factors : 1
#> Factor mean : zero