marginal | R Documentation |
This function returns marginal effects of the inefficiency drivers from stochastic
frontier models estimated with sfacross
, sfalcmcross
,
or sfaselectioncross
.
## S3 method for class 'sfacross'
marginal(object, newData = NULL, ...)
## S3 method for class 'sfalcmcross'
marginal(object, newData = NULL, ...)
## S3 method for class 'sfaselectioncross'
marginal(object, newData = NULL, ...)
object |
A stochastic frontier model returned
by |
newData |
Optional data frame that is used to calculate the marginal
effect of |
... |
Currently ignored. |
marginal
operates in the presence of exogenous
variables that explain inefficiency, namely the inefficiency drivers
(uhet = ~ Z_u
or muhet = ~ Z_{mu}
).
Two components are computed for each variable: the marginal effects on the
expected inefficiency (\frac{\partial E[u]}{\partial Z_{mu}}
) and
the marginal effects on the variance of inefficiency (\frac{\partial
V[u]}{\partial Z_{mu}}
).
The model also allows the Wang (2002) parametrization of \mu
and
\sigma_u^2
by the same vector of exogenous variables. This double
parameterization accounts for non-monotonic relationships between the
inefficiency and its drivers.
marginal
returns a data frame containing the marginal
effects of the Z_u
variables on the expected inefficiency (each
variable has the prefix 'Eu_'
) and on the variance of the
inefficiency (each variable has the prefix 'Vu_'
).
In the case of the latent class stochastic frontier (LCM), each variable
ends with '_c#'
where '#'
is the class number.
Wang, H.J. 2002. Heteroscedasticity and non-monotonic efficiency effects of a stochastic frontier model. Journal of Productivity Analysis, 18:241–253.
sfacross
, for the stochastic frontier analysis model
fitting function using cross-sectional or pooled data.
sfalcmcross
, for the latent class stochastic frontier analysis
model fitting function using cross-sectional or pooled data.
sfaselectioncross
for sample selection in stochastic frontier
model fitting function using cross-sectional or pooled data.
## Not run:
## Using data on fossil fuel fired steam electric power generation plants in the U.S.
# Translog SFA (cost function) truncated normal with scaling property
tl_u_ts <- sfacross(formula = log(tc/wf) ~ log(y) + I(1/2 * (log(y))^2) +
log(wl/wf) + log(wk/wf) + I(1/2 * (log(wl/wf))^2) + I(1/2 * (log(wk/wf))^2) +
I(log(wl/wf) * log(wk/wf)) + I(log(y) * log(wl/wf)) + I(log(y) * log(wk/wf)),
udist = 'tnormal', muhet = ~ regu + wl, uhet = ~ regu + wl, data = utility,
S = -1, scaling = TRUE, method = 'mla')
marg.tl_u_ts <- marginal(tl_u_ts)
summary(marg.tl_u_ts)
## Using data on eighty-two countries production (GDP)
# LCM Cobb Douglas (production function) half normal distribution
cb_2c_h <- sfalcmcross(formula = ly ~ lk + ll + yr, udist = 'hnormal',
data = worldprod, uhet = ~ initStat + h, S = 1, method = 'mla')
marg.cb_2c_h <- marginal(cb_2c_h)
summary(marg.cb_2c_h)
## End(Not run)
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