# Data prep industrial policy
library(haven)
library(dplyr)
raw <- read_dta("replication_Nov_10_2014.dta")
dat3 <- raw %>%
filter(domprivate == 1) %>%
mutate_at(vars(year, idnew, sectoridnew, countycode_4digit, sectorid2digit, domprivate), as.character) %>%
mutate(competition = competition_lerner,
competition_square = competition^2)
# In Work
dat3 <- select(dat3, id = idnew,
industry = sectoridnew,
county = countycode_4digit,
year,
tfp = TFP_OP_all,
index_subsidy,
index_tax,
index_interest,
interestratio,
tariff,
competition,
competition_square,
cor_subsidy = cor_subsidy_lerner,
cor_tax = cor_tax_lerner,
cor_interest = cor_interest_lerner,
cor_tariff = cor_tariff_lerner,
compherf_subsidy = comp_herfsubsidy,
compherf_tax = comp_herftax,
compherf_interest = comp_herfinterest,
exportshare_industry = exportshare_sector,
stateshare,
horizontal,
backward,
forward,
lnTariff,
lnbwTariff,
lnfwTariff,
compherf_subsidy_size = comp_herfsubsidy_weightsize,
compherf_tax_size = comp_herftax_weightsize,
compherf_interest_size = comp_herfinterest_weightsize,
compherf_subsidy_age = comp_herfsubsidy_weightage,
compherf_tax_age = comp_herftax_weightage,
compherf_interest_age = comp_herfinterest_weightage)
saveRDS(dat3, file = "dat3.RDS")
#col = colorRampPalette(c("#BB4444", "#EE9988", "#FFFFFF", "#77AADD", "#4477AA"))
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