An introduction to growth accounting using R

suppressWarnings(suppressMessages({ #library(pwt9) library(pwt10) library(tidyverse) library(ExPanDaR) library(plotly) })) options(warn = -1, scipen = 10000, repr.plot.width = 6, repr.plot.height = 4)

data("pwt10.0")

pwt <- pwt10.0 head(pwt)

df <- pwt %>% filter(country %in% c("China", "India", "Japan")) %>% select(year, isocode, rgdpna, rkna, emp, labsh) %>% filter(year >= 1980, year <= 2000) %>% na.omit()

df

# Compute log of GDP per worker, log Capital per worker, and capital share df <- df %>% mutate(ln_y = log(rgdpna / emp), ln_k = log(rkna / emp), alpha = 1 - labsh)

# Order by year (this is very important because we are using a panel data structure) df <- df %>% arrange(year)

# For each country calculate growth rates and solow residual df <- df %>% group_by(isocode) %>% mutate(g_y = (ln_y - lag(ln_y)) * 100, g_k = (ln_k - lag(ln_k)) * 100, g_A = g_y - alpha * g_k) %>% na.omit()

df %>% select(g_A, g_y, g_k, alpha)

solow <- df %>% summarise(G_y = mean(g_y), G_A = mean(g_A), G_ak = mean(alpha * g_k), A_share = mean(g_A) / mean(g_y), ak_share = mean(alpha * g_k) / mean(g_y), alpha = mean(alpha))

solow

round_df <- function(df, digits) { nums <- vapply(df, is.numeric, FUN.VALUE = logical(1)) df[,nums] <- round(df[,nums], digits = digits) (df) }

round_df(solow, digits=2)

p <- ggplot(data=solow, aes(x=isocode, y=G_y)) + geom_bar(stat="identity") + xlab("") + ylab("Growth") ggplotly(p)

solow_long <- solow %>% select(isocode, G_A, G_ak) %>% pivot_longer(!isocode, names_to = "Growth", values_to = "Values") solow_long

p <- ggplot(solow_long, aes(fill=Growth, y=Values, x=isocode)) + geom_bar(position=position_dodge(), stat="identity") + xlab("") + ylab("Growth") ggplotly(p)

p <- ggplot(solow_long, aes(fill=Growth, y=Values, x=isocode)) + geom_bar(position="stack", stat="identity") + xlab("") + ylab("Growth") ggplotly(p)

p <- ggplot(solow_long, aes(fill=Growth, y=Values, x=isocode)) + geom_bar(position="fill", stat="identity") + xlab("") + ylab("Growth") ggplotly(p)