Description Details Author(s) References Examples
Fit a spatial instrumental-variable regression by two-stage least squares.
Package: | S2sls |
Type: | Package |
Version: | 1.0 |
Date: | 2016-01-06 |
License: | GPL-3 |
S2sls(Y~X,data,W) Spatial Two Stage Least Squares Estimation computes spatial instrumental variables s2SLS estimation where Y is the vector of the dependant variable, X is the matrix of the independent variables and W is the contiguity matrix.
Taha Zaghdoudi
Taha Zaghdoudi <zedtaha@gmail.com>
Amemiyia T. (1971), The estimation of the variances in a variance–components model, International Economic Review, 12, pp.1–13.
Baltagi B.H. (1981), Simultaneous equations with error components, Journal of econometrics, 17, pp.21–49.
Baltagi B.H. (2001), Econometric Analysis of Panel Data. John Wiley and sons. ltd.
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/.
1 2 3 4 5 6 7 8 9 10 | # Load data
data(Produc,package="spanel")
data(usaww,package="spanel")
# The contiguity matrix w must be a square matrix with size[nrow(log(gsp)),nrow(log(gsp))]
# so for our example we transform usaww to a square matrix:
ww<-as.matrix(usaww)
h<-kronecker(ww,diag(17))
# fit spatial two stage least squares model
ran<-s2sls(log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp,Produc,h)
summary(ran)
|
Attaching package: 'S2sls'
The following object is masked from 'package:base':
summary
Formula:log(gsp) ~ log(pcap) + log(pc) + log(emp) + unemp
Estimates Std.Err T-value P-Value
(Intercept) 1.7427498 0.0895334 19.4648 < 2.2e-16 ***
log(pcap) 0.1479031 0.0178019 8.3083 4.069e-16 ***
log(pc) 0.3092135 0.0102474 30.1748 < 2.2e-16 ***
log(emp) 0.6021717 0.0148472 40.5579 < 2.2e-16 ***
unemp -0.0062039 0.0014595 -4.2508 2.378e-05 ***
-0.0087338 0.0060310 -1.4482 0.148
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Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
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