################################################################################
#
# PhD. European convergence 02-03-2016
# Function. Estimate convergence models from decomposed data
# Ilya Kashnitsky, ilya.kashnitsky@gmail.com
#
# NOTE: this funcrion depends on other own defined functions:
# ik_an_multiple.y.lm.list() AND ik_an_extract.lm()
#
################################################################################
ik_phd_estimate.conv.models.dec <- function(df,years){
require(dplyr)
require(tidyr)
require(data.table)
jan1.years <- paste0('y',years)
fullyears <- jan1.years[-length(jan1.years)]
est.l <- list()
for (i in 1:length(fullyears)) {
di <- filter(df, year==fullyears[i])
modelsi <- ik_an_multiple.y.lm.list(di,y=3:8,x=10)
tablei <- ik_an_extract.lm(modelsi,round = F) %>%
mutate(year = fullyears[i]) %>%
gather('variable','value',2:7)
tablei$model_y.x <- factor(c("(A). Level 1. Overall model","(B). Level 2. Non-working age","(C). Level 2. Working age",
"(F). Level 3. Mortality","(E). Level 3. Migration","(D). Level 3. Cohort turnover"))
est.l[[i]] <- tablei
names(est.l)[i] <- fullyears[i]
}
est <- rbind_all(est.l) %>%
spread(variable,value) %>%
mutate(year=factor(year)) %>%
group_by(model_y.x) %>%
mutate(group.mean = mean(coef)) %>%
ungroup()
return(est)
}
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