## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----lib---------------------------------------------------------------------- library(SDPDmod) ## ----data, eval=TRUE, echo=T, warning=FALSE, message=FALSE-------------------- data("Cigar",package = "plm") head(Cigar) data1<- Cigar data1$logc<-log(data1$sales) data1$logp<-log(data1$price/data1$cpi) data1$logy<-log(data1$ndi/data1$cpi) data1$lpm<-log(data1$pimin/data1$cpi) data("usa46",package="SDPDmod") ## binary contiguity matrix of 46 USA states str(usa46) W <- rownor(usa46) ## row-normalization isrownor(W) ## check if W is row-normalized ## ----m1, eval=TRUE, echo=T, warning=FALSE, message=FALSE---------------------- res1<-blmpSDPD(formula = logc ~ logp+logy, data = data1, W = W, index = c("state","year"), model = list("ols","sar","sdm","sem","sdem","slx"), effect = "individual") res1 ## ----m2, eval=TRUE, echo=T, warning=FALSE, message=FALSE---------------------- res2<-blmpSDPD(formula = logc ~ logp+logy, data = data1, W = W, index = c("state","year"), model = list("ols","sar","sdm","sem","sdem","slx"), effect = "time") ## ----m3, eval=TRUE, echo=T, warning=FALSE, message=FALSE---------------------- res3<-blmpSDPD(formula = logc ~ logp+logy, data = data1, W = W, index = c("state","year"), model = list("sar","sdm","sem","sdem"), effect = "twoways", prior = "beta") ## ----m4, eval=TRUE, echo=T, warning=FALSE, message=FALSE---------------------- res4<-blmpSDPD(formula = logc ~ logp+logy, data = data1, W = W, index = c("state","year"), model = list("sar","sdm","sem","sdem","slx"), effect = "twoways", ldet = "mc", ## log-determinant calculated with mcmc procedure dynamic = TRUE, prior = "uniform") ## ----m5, eval=TRUE, echo=T, warning=FALSE, message=FALSE---------------------- d2 <- plm::pdata.frame(data1, index=c('state', 'year')) d2$llogc<-plm::lag(d2$logc) ## add lagged variable data2<-d2[which(!is.na(d2$llogc)),] rownames(data2)<-1:nrow(data2) kk<-which(colnames(data2)=="llogc") kk res5<-blmpSDPD(formula = logc ~ logp+logy, data = data2, W = W, index = c("state","year"), model = list("sar","sdm","sem","sdem"), effect = "individual", ldet = "full", dynamic = TRUE, tlaginfo = list(ind=kk), prior = "beta") ## ----mod1, eval=TRUE, echo=T, warning=FALSE, message=FALSE-------------------- mod1<-SDPDm(formula = logc ~ logp+logy, data = data1, W = W, index = c("state","year"), model = "sar", effect = "individual") summary(mod1) mod1$rsqr mod1$sige ## ----mod2, eval=TRUE, echo=T, warning=FALSE, message=FALSE-------------------- mod2<-SDPDm(formula = logc ~ logp+logy, data = data1, W = W, index = c("state","year"), model = "sar", effect = "individual", dynamic = T, tlaginfo = list(ind = NULL, tl = T, stl = T)) summary(mod2) ## ----mod3, eval=TRUE, echo=T, warning=FALSE, message=FALSE-------------------- mod3<-SDPDm(formula = logc ~ logp+logy, data = data1, W = W, index = c("state","year"), model = "sar", effect = "individual", LYtrans = T, dynamic = T, tlaginfo = list(ind = NULL, tl = T, stl = T)) summary(mod3) ## ----mod4, eval=TRUE, echo=T, warning=FALSE, message=FALSE-------------------- mod4<-SDPDm(formula = logc ~ logp+logy, data = data2, W = W, index = c("state","year"), model = "sar", effect = "individual", LYtrans = T, dynamic = T, tlaginfo = list(ind = kk, tl = T, stl = F)) summary(mod4) ## ----mod5, eval=TRUE, echo=T, warning=FALSE, message=FALSE-------------------- mod5<-SDPDm(formula = logc ~ logp+logy, data = data1, W = W, index = c("state","year"), model = "sdm", effect = "twoways", LYtrans = T, dynamic = T, tlaginfo = list(ind = NULL, tl = T, stl = T)) summary(mod5) ## ----imp, eval=TRUE, echo=T, warning=FALSE, message=FALSE--------------------- imp <- impactsSDPDm(mod5) summary(imp)