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Regression for WVS.R
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Regression for WVS.R
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####################################
# SETTING UP FOR REGRESSION OF WVS #
####################################
WVS_01 <- WVS_01 %>%
select(-"tinh")
WVS_01 <- merge(WVS_01, WVS_preBTA_tariffs, by = "XVIE_V225D")
WVS_05 <- WVS_05 %>%
select(-"tinh")
WVS_05 <- merge(WVS_05, WVS_postBTA_tariffs, by = "V257")
# Renaming variables
WVS_01 <- WVS_01 %>%
rename(job_scarce = V78,
working_mother = V115,
housewife = V116,
both_contribute = V117,
provtariff = preprov_tariff,
provtariff_k = preprov_tariff_k,
sex = V223,
age = V225,
educ = V226,
emp = V230,
divorce = V211) %>%
mutate(female = as.numeric(sex > 1),
year = 2001) %>%
select(tinh, provtariff, provtariff_k, female, emp, age, educ, housewife, job_scarce, divorce, year)
WVS_05 <- WVS_05 %>%
rename(job_scarce = V44,
housewife = V60,
provtariff = postprov_tariff,
provtariff_k = postprov_tariff_k,
sex = V235,
educ = V238,
age = V237,
emp = V242,
divorce = V205) %>%
mutate(female = as.numeric(sex > 1),
year = 2005) %>%
select(tinh, provtariff, provtariff_k, female, emp, age, educ, housewife, job_scarce, divorce, year)
WVS_0105 <- bind_rows(WVS_01, WVS_05) %>%
mutate(housewife = as.numeric(housewife < 3),
job_scarce = as.numeric(job_scarce < 2)) %>%
filter(divorce = as.numeric(divorce == 1, 1, 0))
#####################
# REGRESSION OF WVS #
#####################
# Housewife
etable(list(
feols(housewife ~ provtariff + as.factor(female) + age + as.factor(educ) + as.factor(emp) | year + tinh,
WVS_0105,
vcov = ~tinh),
feols(housewife ~ provtariff_k + as.factor(female) + age + as.factor(educ) + as.factor(emp) | year + tinh,
WVS_0105,
vcov = ~tinh)
), tex = TRUE)
etable(list(
feols(housewife ~ provtariff + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 1),
vcov = ~tinh),
feols(housewife ~ provtariff_k + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 1),
vcov = ~tinh)
), tex = TRUE)
etable(list(
feols(housewife ~ provtariff + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 0),
vcov = ~tinh),
feols(housewife ~ provtariff_k + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 0),
vcov = ~tinh)
), tex = TRUE)
# Job scarcity
etable(list(
feols(job_scarce ~ provtariff + as.factor(female) + age + as.factor(educ) + as.factor(emp) | year + tinh,
WVS_0105,
vcov = ~tinh),
feols(job_scarce ~ provtariff_k + as.factor(female) + age + as.factor(educ) + as.factor(emp) | year + tinh,
WVS_0105,
vcov = ~tinh)
), tex = TRUE)
etable(list(
feols(job_scarce ~ provtariff + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 1),
vcov = ~tinh),
feols(job_scarce ~ provtariff_k + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 1),
vcov = ~tinh)
), tex = TRUE)
etable(list(
feols(job_scarce ~ provtariff + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 0),
vcov = ~tinh),
feols(job_scarce ~ provtariff_k + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 0),
vcov = ~tinh)
), tex = TRUE)
# Divorce
etable(list(
feols(divorce ~ provtariff + as.factor(female) + age + as.factor(educ) + as.factor(emp) | year + tinh,
WVS_0105,
vcov = ~tinh),
feols(divorce ~ provtariff_k + as.factor(female) + age + as.factor(educ) + as.factor(emp) | year + tinh,
WVS_0105,
vcov = ~tinh)
), tex = TRUE)
etable(list(
feols(divorce ~ provtariff + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 1),
vcov = ~tinh),
feols(divorce ~ provtariff_k + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 1),
vcov = ~tinh)
), tex = TRUE)
etable(list(
feols(divorce ~ provtariff + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 0),
vcov = ~tinh),
feols(divorce ~ provtariff_k + age + as.factor(educ) + as.factor(emp) | year + tinh,
subset(WVS_0105, female == 0),
vcov = ~tinh)
), tex = TRUE)