‘Econometric Analysis of Panel Data’ (ISBN 978-3-030-53952-8) provides up-to-date coverage of basic panel data techniques, illustrated with real economic applications and datasets. However, importing the original data from the book into R is not straightforward because some of the datasets are available in Microsoft Word format. I provide the datasets in tidy format, expecting that this will allow students to focus on the econometric techniques rather than on data wrangling.
You can install the development version of baltagi like so:
remotes::install_github("pachadotdev/baltagi")
Baltagi, Song and Jung (2001) investigated the productivity of public capital in each US state’s private output, which is discussed in section 9.6.1 of the book (Empirical Example: Nested States Public Capital Productivity).
The original dataset is in Microsoft Word format (DOCX). To read it, you
would need to copy it in Notepad, save as CSV , and then import it into
R to find that there are data wrangling steps involved to make it
usable. Alternatively, you can read the DOCX file directly in R with the
readtext
package and then proceed to the data wrangling.
baltagi
saves all those steps and you can jump directly to the
econometric analysis.
library(baltagi)
library(plm)
fit <- plm(
log(gsp) ~ log(priv_cap) + log(hwy) + log(water) + log(util) + log(emp) +
unemp,
data = produc,
index = c("st_abb", "year")
)
summary(fit)
#> Oneway (individual) effect Within Model
#>
#> Call:
#> plm(formula = log(gsp) ~ log(priv_cap) + log(hwy) + log(water) +
#> log(util) + log(emp) + unemp, data = produc, index = c("st_abb",
#> "year"))
#>
#> Balanced Panel: n = 48, T = 17, N = 816
#>
#> Residuals:
#> Min. 1st Qu. Median 3rd Qu. Max.
#> -0.1207980 -0.0228756 -0.0015757 0.0183999 0.1548035
#>
#> Coefficients:
#> Estimate Std. Error t-value Pr(>|t|)
#> log(priv_cap) 0.23580111 0.02621777 8.9939 < 2.2e-16 ***
#> log(hwy) 0.07747252 0.03125904 2.4784 0.01341 *
#> log(water) 0.07821567 0.01500290 5.2134 2.391e-07 ***
#> log(util) -0.11438336 0.01815255 -6.3012 4.992e-10 ***
#> log(emp) 0.79958666 0.02974239 26.8837 < 2.2e-16 ***
#> unemp -0.00519584 0.00098018 -5.3009 1.510e-07 ***
#> ---
#> Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Total Sum of Squares: 18.941
#> Residual Sum of Squares: 1.0313
#> R-Squared: 0.94555
#> Adj. R-Squared: 0.94177
#> F-statistic: 2205.54 on 6 and 762 DF, p-value: < 2.22e-16