Description Usage Arguments Details Value Author(s) References See Also Examples
View source: R/tool_ranfixef.R
This function gives an overall intercept for within models and its accompanying standard error or an within model with the overall intercept
1 2 3 4 | within_intercept(object, ...)
## S3 method for class 'plm'
within_intercept(object, vcov = NULL, return.model = FALSE, ...)
|
object |
object of class |
... |
further arguments (currently none). |
vcov |
if not |
return.model |
a logical to indicate whether only the overall intercept
( |
The (somewhat artificial) intercept for within models (fixed effects models) was made popular by Stata of StataCorp \insertCite@see @GOUL:13plm, EViews of IHS, and gretl \insertCite@gretl p. 160-161, example 18.1plm, see for treatment in the literature, e.g., \insertCiteGREE:12;textualplm, Ch. 11.4.4, p. 364. It can be considered an overall intercept in the within model framework and is the weighted mean of fixed effects (see Examples for the relationship).
within_intercept
estimates a new model which is
computationally more demanding than just taking the weighted
mean. However, with within_intercept
one also gets the
associated standard error and it is possible to get an overall
intercept for twoway fixed effect models.
Users can set argument vcov
to a function to calculate a
specific (robust) variance–covariance matrix and get the
respective (robust) standard error for the overall intercept,
e.g., the function vcovHC()
, see examples for
usage. Note: The argument vcov
must be a function, not a
matrix, because the model to calculate the overall intercept for
the within model is different from the within model itself.
If argument return.model = TRUE
is set, the full model object is returned,
while in the default case only the intercept is returned.
Depending on argument return.model
: If FALSE
(default), a named
numeric
of length one: The overall intercept for the estimated within model
along attribute "se" which contains the standard error for the intercept.
If return.model = TRUE
, the full model object, a within model with the
overall intercept (NB: the model identifies itself as a pooling model, e.g.,
in summary()).
Kevin Tappe
fixef()
to extract the fixed effects of a within model.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 | data("Hedonic", package = "plm")
mod_fe <- plm(mv ~ age + crim, data = Hedonic, index = "townid")
overallint <- within_intercept(mod_fe)
attr(overallint, "se") # standard error
# overall intercept is the weighted mean of fixed effects in the
# one-way case
weighted.mean(fixef(mod_fe), pdim(mod_fe)$Tint$Ti)
### relationship of type="dmean", "level" and within_intercept
## one-way balanced case
data("Grunfeld", package = "plm")
gi <- plm(inv ~ value + capital, data = Grunfeld, model = "within")
fx_level <- fixef(gi, type = "level")
fx_dmean <- fixef(gi, type = "dmean")
overallint <- within_intercept(gi)
all.equal(overallint + fx_dmean, fx_level, check.attributes = FALSE) # TRUE
## two-ways unbalanced case
gtw_u <- plm(inv ~ value + capital, data = Grunfeld[-200, ], effect = "twoways")
int_tw_u <- within_intercept(gtw_u)
fx_dmean_tw_i_u <- fixef(gtw_u, type = "dmean", effect = "individual")[index(gtw_u)[[1L]]]
fx_dmean_tw_t_u <- fixef(gtw_u, type = "dmean", effect = "time")[index(gtw_u)[[2L]]]
fx_level_tw_u <- as.numeric(fixef(gtw_u, "twoways", "level"))
fx_level_tw_u2 <- int_tw_u + fx_dmean_tw_i_u + fx_dmean_tw_t_u
all.equal(fx_level_tw_u, fx_level_tw_u2, check.attributes = FALSE) # TRUE
## overall intercept with robust standard error
within_intercept(gi, vcov = function(x) vcovHC(x, method="arellano", type="HC0"))
## have a model returned
mod_fe_int <- within_intercept(gi, return.model = TRUE)
summary(mod_fe_int)
# replicates Stata's robust standard errors
summary(mod_fe_int, vcvov = function(x) vcovHC(x, type = "sss"))
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