# Predicting forecasting a regression

The reason for pointing out the FAQ: What's a reproducible example (`reprex`) and how do I do one? was to emphasize how difficult it can be to formulate an answer without a `reprex`, such as this example from the `plm` help page

``````library(plm)

data("Produc", package = "plm")
zz <- plm(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
data = Produc, index = c("state","year"))
summary(zz)
#> Oneway (individual) effect Within Model
#>
#> Call:
#> plm(formula = log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,
#>     data = Produc, index = c("state", "year"))
#>
#> Balanced Panel: n = 48, T = 17, N = 816
#>
#> Residuals:
#>      Min.   1st Qu.    Median   3rd Qu.      Max.
#> -0.120456 -0.023741 -0.002041  0.018144  0.174718
#>
#> Coefficients:
#>              Estimate  Std. Error t-value  Pr(>|t|)
#> log(pcap) -0.02614965  0.02900158 -0.9017    0.3675
#> log(pc)    0.29200693  0.02511967 11.6246 < 2.2e-16 ***
#> log(emp)   0.76815947  0.03009174 25.5273 < 2.2e-16 ***
#> unemp     -0.00529774  0.00098873 -5.3582 1.114e-07 ***
#> ---
#> Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
#>
#> Total Sum of Squares:    18.941
#> Residual Sum of Squares: 1.1112
#> R-Squared:      0.94134