spml {splm} | R Documentation |
Spatial Panel Model by Maximum Likelihood
Description
Maximum likelihood (ML) estimation of spatial panel models, possibly with fixed or random effects.
Usage
spml(formula, data, index=NULL, listw, listw2=listw, na.action,
model=c("within","random","pooling"),
effect=c("individual","time","twoways"),
lag=FALSE, spatial.error=c("b","kkp","none"),
...)
## S3 method for class 'splm_ML'
impacts(obj, listw = NULL,
time = NULL, ...,
tr = NULL, R = 200,
type = "mult",
empirical = FALSE, Q = NULL)
## S3 method for class 'splm_GM'
impacts(obj, ..., tr=NULL,
R=NULL, listw=NULL,
type = "mult",
time = NULL,
evalues=NULL, tol=1e-6,
empirical=FALSE, Q=NULL,
KPformula = FALSE, prt = TRUE)
Arguments
formula |
a symbolic description of the model to be estimated |
data |
an object of class |
index |
if not NULL (default), a character vector to identify the indexes among the columns of the |
listw |
an object of class |
listw2 |
an object of class |
na.action |
see spdep for more details. |
model |
one of |
effect |
one of |
lag |
default= |
spatial.error |
one of |
... |
additional argument to pass over to other functions |
obj |
fitted model object |
time |
??time?? |
tr |
A vector of traces of powers of the spatial weights matrix created using 'trW', for approximate impact measures |
R |
If given, simulations are used to compute distributions for the impact measures, returned as 'mcmc' objects |
type |
Either "mult" (default) for powering a sparse matrix (with moderate or larger N, the matrix becomes dense, and may lead to swapping), or "MC" for Monte Carlo simulation of the traces (the first two simulated traces are replaced by their analytical equivalents), or "moments" to use the looping space saving algorithm proposed by Smirnov and Anselin (2009) - for "moments", 'W' must be symmetric, for row-standardised weights through a similarity transformation |
empirical |
Argument passed to 'mvrnorm' (default FALSE) |
Q |
default NULL, else an integer number of cumulative power series impacts to calculate if 'tr' is given |
evalues |
vector of eigenvalues of spatial weights matrix for impacts calculations |
tol |
Argument passed to 'mvrnorm' |
KPformula |
not yet implemented |
prt |
not yet implemented |
Details
The models are estimated by two-step Maximum Likelihood.
Further optional parameters to be passed on to the estimator may be:
pvar: if TRUE
the pvar
function is called
hess: if TRUE
use numerical Hessian instead of GLS for the
standard errors of the estimates
quiet: if FALSE
report function and parameters values during
optimization
initval: one of c("zeros", "estimate")
, the initial values for
the parameters. If "zeros"
a vector of zeros is used. if
"estimate"
the initial values are retreived from the estimation
of the nested specifications. Alternatively, a numeric vector can be
specified.
x.tol: Tolerance. See nlminb
for details.
rel.tol: Relative tolerance. See nlminb
for details.
Value
An object of class "splm"
.
coefficients |
coefficients estimate of the model parameters |
arcoef |
the coefficient for the spatial lag on |
errcomp |
the estimates of the error variance components |
vcov |
the asymptotic variance covariance matrix of the estimated coefficients |
vcov.arcoef |
the asymptotic variance of the estimated spatial lag parameter |
vcov.errcomp |
the asymptotic variance covariance matrix of the estimated error covariance parameters |
type |
'random effects ML' |
residuals |
the model residuals |
fitted.values |
the fitted values, calculated as |
sigma2 |
GLS residuals variance |
model |
the matrix of the data used |
call |
the call used to create the object |
logLik |
the value of the log likelihood function at the optimum |
errors |
the value of the |
Author(s)
Giovanni Millo
References
Baltagi, B.H., Song, S.H., Jung B. and Koh, W. (2007) Testing panel data regression models with spatial and serial error correlation. Journal of Econometrics, 140, 5-51.
Millo, G., Piras, G. (2012) splm: Spatial Panel Data Models in R. Journal of Statistical Software, 47(1), 1–38. URL http://www.jstatsoft.org/v47/i01/.
See Also
spgm
Examples
data(Produc, package = "plm")
data(usaww)
fm <- log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp
## the two standard specifications (SEM and SAR) one with FE
## and the other with RE:
## fixed effects panel with spatial errors
fespaterr <- spml(fm, data = Produc, listw = spdep::mat2listw(usaww),
model="within", spatial.error="b", Hess = FALSE)
summary(fespaterr)
## random effects panel with spatial lag
respatlag <- spml(fm, data = Produc, listw = spdep::mat2listw(usaww),
model="random", spatial.error="none", lag=TRUE)
summary(respatlag)
## calculate impact measures
#impac1 <- impacts.splm(respatlag, listw = spdep::mat2listw(usaww, #style = "W"), time = 17)
#summary(impac1, zstats=TRUE, short=TRUE)