inst/tinytest/test_bootcluster.R

#  ------------------------------------------------------------------ # 
# test 1: bootcluster 
# Tests A1 and A2
# ------------------------------------------------------------------ # 

# library(fwildclusterboot)


# ---------------------------------------------------------------------------------------------- # 
# Part 1: one cluster variable - bootcluster = "min"
# ---------------------------------------------------------------------------------------------- # 

# ---------------------------------------------------------------------------------------------- # 
# Part A1: no fixed effect in model

library(lfe)
library(fixest)

lm_fit <- lm(proposition_vote ~ treatment + ideology1 + log_income + as.factor(Q1_immigration) , 
            data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit <- feols(proposition_vote ~ treatment + ideology1 + log_income + as.factor(Q1_immigration), 
                          data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit <- felm(proposition_vote ~ treatment + ideology1 + log_income + as.factor(Q1_immigration), 
                     data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit_c <- feols(proposition_vote ~ treatment + ideology1 + log_income + as.factor(Q1_immigration), 
                            cluster = "group_id1",
                            data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit_c <- felm(proposition_vote ~ treatment + ideology1 + log_income + as.factor(Q1_immigration) | 0 | 0 | group_id1,
                       data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))

boot_lm <-  suppressWarnings(boottest(object = lm_fit, clustid =  "group_id1", B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))
boot_fixest <- suppressWarnings(boottest(object = feols_fit, clustid = c("group_id1"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))
boot_felm <- suppressWarnings(boottest(object = felm_fit, clustid =  "group_id1", B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))
boot_fixest_c <- suppressWarnings(boottest(object = feols_fit_c, clustid = c("group_id1"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))
boot_felm_c <- suppressWarnings(boottest(object = felm_fit_c, clustid =  "group_id1", B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))

# point estimates
expect_equivalent(boot_lm$point_estimate, boot_fixest$point_estimate)
expect_equivalent(boot_fixest$point_estimate, boot_felm$point_estimate)
expect_equivalent(boot_felm$point_estimate, boot_fixest_c$point_estimate)
expect_equivalent(boot_fixest_c$point_estimate, boot_felm_c$point_estimate)
expect_equivalent(boot_felm_c$point_estimate, boot_lm$point_estimate)

# p-vals
expect_equivalent(boot_lm$p_val, boot_fixest$p_val)
expect_equivalent(boot_fixest$p_val, boot_felm$p_val)
expect_equivalent(boot_felm$p_val, boot_fixest_c$p_val)
expect_equivalent(boot_fixest_c$p_val, boot_felm_c$p_val)
expect_equivalent(boot_felm_c$p_val, boot_lm$p_val)

# t_stats
expect_equivalent(boot_lm$t_stat, boot_fixest$t_stat)
expect_equivalent(boot_fixest$t_stat, boot_felm$t_stat)
expect_equivalent(boot_felm$t_stat, boot_fixest_c$t_stat)
expect_equivalent(boot_fixest_c$t_stat, boot_felm_c$t_stat)
expect_equivalent(boot_felm_c$t_stat, boot_lm$t_stat)

# confidence intervals
expect_equivalent(boot_lm$conf_int, boot_fixest$conf_int)
expect_equivalent(boot_fixest$conf_int, boot_felm$conf_int)
expect_equivalent(boot_felm$conf_int, boot_fixest_c$conf_int)
expect_equivalent(boot_fixest_c$conf_int, boot_felm_c$conf_int)
expect_equivalent(boot_felm_c$conf_int, boot_lm$conf_int)



# ---------------------------------------------------------------------------------------------- # 
# Part 2: two cluster variables
# ---------------------------------------------------------------------------------------------- # 

# ---------------------------------------------------------------------------------------------- # 
# Part A2: no fixed effect in model

lm_fit <- lm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration , 
            data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                          data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                     data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit_c <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                            cluster = "group_id1",
                            data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit_c <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration | 0 | 0 | group_id1,
                       data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))

boot_lm <-  suppressWarnings(boottest(object = lm_fit, clustid =  c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))
boot_fixest <- suppressWarnings(boottest(object = feols_fit, clustid = c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))
boot_felm <- suppressWarnings(boottest(object = felm_fit, clustid =  c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))
boot_fixest_c <- suppressWarnings(boottest(object = feols_fit_c, clustid = c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))
boot_felm_c <- suppressWarnings(boottest(object = felm_fit_c, clustid =  c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "min"))

# point estimates
expect_equivalent(boot_lm$point_estimate, boot_fixest$point_estimate)
expect_equivalent(boot_fixest$point_estimate, boot_felm$point_estimate)
expect_equivalent(boot_felm$point_estimate, boot_fixest_c$point_estimate)
expect_equivalent(boot_fixest_c$point_estimate, boot_felm_c$point_estimate)
expect_equivalent(boot_felm_c$point_estimate, boot_lm$point_estimate)

# p-vals
expect_equivalent(boot_lm$p_val, boot_fixest$p_val)
expect_equivalent(boot_fixest$p_val, boot_felm$p_val)
expect_equivalent(boot_felm$p_val, boot_fixest_c$p_val)
expect_equivalent(boot_fixest_c$p_val, boot_felm_c$p_val)
expect_equivalent(boot_felm_c$p_val, boot_lm$p_val)

# t_stats
expect_equivalent(boot_lm$t_stat, boot_fixest$t_stat)
expect_equivalent(boot_fixest$t_stat, boot_felm$t_stat)
expect_equivalent(boot_felm$t_stat, boot_fixest_c$t_stat)
expect_equivalent(boot_fixest_c$t_stat, boot_felm_c$t_stat)
expect_equivalent(boot_felm_c$t_stat, boot_lm$t_stat)

# confidence intervals
expect_equivalent(boot_lm$conf_int, boot_fixest$conf_int)
expect_equivalent(boot_fixest$conf_int, boot_felm$conf_int)
expect_equivalent(boot_felm$conf_int, boot_fixest_c$conf_int)
expect_equivalent(boot_fixest_c$conf_int, boot_felm_c$conf_int)
expect_equivalent(boot_felm_c$conf_int, boot_lm$conf_int)




# --------------------------------------------------------------------------- # 
# bootcluster is a variable in cluster_ids
# --------------------------------------------------------------------------- # 



lm_fit <- lm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration , 
             data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                           data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                      data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit_c <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                             cluster = "group_id1",
                             data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit_c <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration | 0 | 0 | group_id1,
                        data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))

boot_lm <-  suppressWarnings(boottest(object = lm_fit, clustid =  "group_id1", B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))
boot_fixest <- suppressWarnings(boottest(object = feols_fit, clustid = c("group_id1"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))
boot_felm <- suppressWarnings(boottest(object = felm_fit, clustid =  "group_id1", B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))
boot_fixest_c <- suppressWarnings(boottest(object = feols_fit_c, clustid = c("group_id1"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))
boot_felm_c <- suppressWarnings(boottest(object = felm_fit_c, clustid =  "group_id1", B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))

# point estimates
expect_equivalent(boot_lm$point_estimate, boot_fixest$point_estimate)
expect_equivalent(boot_fixest$point_estimate, boot_felm$point_estimate)
expect_equivalent(boot_felm$point_estimate, boot_fixest_c$point_estimate)
expect_equivalent(boot_fixest_c$point_estimate, boot_felm_c$point_estimate)
expect_equivalent(boot_felm_c$point_estimate, boot_lm$point_estimate)

# p-vals
expect_equivalent(boot_lm$p_val, boot_fixest$p_val)
expect_equivalent(boot_fixest$p_val, boot_felm$p_val)
expect_equivalent(boot_felm$p_val, boot_fixest_c$p_val)
expect_equivalent(boot_fixest_c$p_val, boot_felm_c$p_val)
expect_equivalent(boot_felm_c$p_val, boot_lm$p_val)

# t_stats
expect_equivalent(boot_lm$t_stat, boot_fixest$t_stat)
expect_equivalent(boot_fixest$t_stat, boot_felm$t_stat)
expect_equivalent(boot_felm$t_stat, boot_fixest_c$t_stat)
expect_equivalent(boot_fixest_c$t_stat, boot_felm_c$t_stat)
expect_equivalent(boot_felm_c$t_stat, boot_lm$t_stat)

# confidence intervals
expect_equivalent(boot_lm$conf_int, boot_fixest$conf_int)
expect_equivalent(boot_fixest$conf_int, boot_felm$conf_int)
expect_equivalent(boot_felm$conf_int, boot_fixest_c$conf_int)
expect_equivalent(boot_fixest_c$conf_int, boot_felm_c$conf_int)
expect_equivalent(boot_felm_c$conf_int, boot_lm$conf_int)



# ---------------------------------------------------------------------------------------------- # 
# Part 2: two cluster variables
# ---------------------------------------------------------------------------------------------- # 

# ---------------------------------------------------------------------------------------------- # 
# Part A2: no fixed effect in model

lm_fit <- lm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration , 
             data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                           data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                      data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit_c <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                             cluster = "group_id1",
                             data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit_c <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration | 0 | 0 | group_id1,
                        data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))

boot_lm <-  suppressWarnings(boottest(object = lm_fit, clustid =  c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))
boot_fixest <- suppressWarnings(boottest(object = feols_fit, clustid = c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))
boot_felm <- suppressWarnings(boottest(object = felm_fit, clustid =  c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))
boot_fixest_c <- suppressWarnings(boottest(object = feols_fit_c, clustid = c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))
boot_felm_c <- suppressWarnings(boottest(object = felm_fit_c, clustid =  c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = "group_id1"))

# point estimates
expect_equivalent(boot_lm$point_estimate, boot_fixest$point_estimate)
expect_equivalent(boot_fixest$point_estimate, boot_felm$point_estimate)
expect_equivalent(boot_felm$point_estimate, boot_fixest_c$point_estimate)
expect_equivalent(boot_fixest_c$point_estimate, boot_felm_c$point_estimate)
expect_equivalent(boot_felm_c$point_estimate, boot_lm$point_estimate)

# p-vals
expect_equivalent(boot_lm$p_val, boot_fixest$p_val)
expect_equivalent(boot_fixest$p_val, boot_felm$p_val)
expect_equivalent(boot_felm$p_val, boot_fixest_c$p_val)
expect_equivalent(boot_fixest_c$p_val, boot_felm_c$p_val)
expect_equivalent(boot_felm_c$p_val, boot_lm$p_val)
# 
# t_stats
expect_equivalent(boot_lm$t_stat, boot_fixest$t_stat)
expect_equivalent(boot_fixest$t_stat, boot_felm$t_stat)
expect_equivalent(boot_felm$t_stat, boot_fixest_c$t_stat)
expect_equivalent(boot_fixest_c$t_stat, boot_felm_c$t_stat)
expect_equivalent(boot_felm_c$t_stat, boot_lm$t_stat)

# confidence intervals
expect_equivalent(boot_lm$conf_int, boot_fixest$conf_int)
expect_equivalent(boot_fixest$conf_int, boot_felm$conf_int)
expect_equivalent(boot_felm$conf_int, boot_fixest_c$conf_int)
expect_equivalent(boot_fixest_c$conf_int, boot_felm_c$conf_int)
expect_equivalent(boot_felm_c$conf_int, boot_lm$conf_int)



# --------------------------------------------------------------------------- # 
# bootcluster is of length 2: variable from cluster var and fixed effect
# --------------------------------------------------------------------------- # 



lm_fit <- lm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration , 
             data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                           data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                      data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit_c <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                             cluster = "group_id1",
                             data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit_c <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration | 0 | 0 | group_id1,
                        data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))

boot_lm <-  suppressWarnings(boottest(object = lm_fit, clustid =  "group_id1", B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))
boot_fixest <- suppressWarnings(boottest(object = feols_fit, clustid = c("group_id1"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))
boot_felm <- suppressWarnings(boottest(object = felm_fit, clustid =  "group_id1", B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))
boot_fixest_c <- suppressWarnings(boottest(object = feols_fit_c, clustid = c("group_id1"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))
boot_felm_c <- suppressWarnings(boottest(object = felm_fit_c, clustid =  "group_id1", B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))

# point estimates
expect_equivalent(boot_lm$point_estimate, boot_fixest$point_estimate)
expect_equivalent(boot_fixest$point_estimate, boot_felm$point_estimate)
expect_equivalent(boot_felm$point_estimate, boot_fixest_c$point_estimate)
expect_equivalent(boot_fixest_c$point_estimate, boot_felm_c$point_estimate)
expect_equivalent(boot_felm_c$point_estimate, boot_lm$point_estimate)
# 
#p-vals
expect_equivalent(boot_lm$p_val, boot_fixest$p_val)
expect_equivalent(boot_fixest$p_val, boot_felm$p_val)
expect_equivalent(boot_felm$p_val, boot_fixest_c$p_val)
expect_equivalent(boot_fixest_c$p_val, boot_felm_c$p_val)
expect_equivalent(boot_felm_c$p_val, boot_lm$p_val)

# t_stats
expect_equivalent(boot_lm$t_stat, boot_fixest$t_stat)
expect_equivalent(boot_fixest$t_stat, boot_felm$t_stat)
expect_equivalent(boot_felm$t_stat, boot_fixest_c$t_stat)
expect_equivalent(boot_fixest_c$t_stat, boot_felm_c$t_stat)
expect_equivalent(boot_felm_c$t_stat, boot_lm$t_stat)

# confidence intervals
expect_equivalent(boot_lm$conf_int, boot_fixest$conf_int)
expect_equivalent(boot_fixest$conf_int, boot_felm$conf_int)
expect_equivalent(boot_felm$conf_int, boot_fixest_c$conf_int)
expect_equivalent(boot_fixest_c$conf_int, boot_felm_c$conf_int)
expect_equivalent(boot_felm_c$conf_int, boot_lm$conf_int)



# ---------------------------------------------------------------------------------------------- # 
# Part 2: two cluster variables
# ---------------------------------------------------------------------------------------------- # 

# ---------------------------------------------------------------------------------------------- # 
# Part A2: no fixed effect in model

lm_fit <- lm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration , 
            data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                          data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                     data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
feols_fit_c <- feols(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration, 
                            cluster = "group_id1",
                            data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))
felm_fit_c <- felm(proposition_vote ~ treatment + ideology1 + log_income + Q1_immigration | 0 | 0 | group_id1,
                       data = fwildclusterboot:::create_data(N = 10000, N_G1 = 20, icc1 = 0.01, N_G2 = 10, icc2 = 0.01, numb_fe1 = 10, numb_fe2 = 10, seed = 1234))

boot_lm <-  suppressWarnings(boottest(object = lm_fit, clustid =  c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))
boot_fixest <- suppressWarnings(boottest(object = feols_fit, clustid = c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))
boot_felm <- suppressWarnings(boottest(object = felm_fit, clustid =  c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))
boot_fixest_c <- suppressWarnings(boottest(object = feols_fit_c, clustid = c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))
boot_felm_c <- suppressWarnings(boottest(object = felm_fit_c, clustid =  c("group_id1", "group_id2"), B = 2999, seed = 911, param = "treatment", conf_int = TRUE, bootcluster = c("group_id1", "Q1_immigration")))

# point estimates
expect_equivalent(boot_lm$point_estimate, boot_fixest$point_estimate)
expect_equivalent(boot_fixest$point_estimate, boot_felm$point_estimate)
expect_equivalent(boot_felm$point_estimate, boot_fixest_c$point_estimate)
expect_equivalent(boot_fixest_c$point_estimate, boot_felm_c$point_estimate)
expect_equivalent(boot_felm_c$point_estimate, boot_lm$point_estimate)

# p-vals
expect_equivalent(boot_lm$p_val, boot_fixest$p_val)
expect_equivalent(boot_fixest$p_val, boot_felm$p_val)
expect_equivalent(boot_felm$p_val, boot_fixest_c$p_val)
expect_equivalent(boot_fixest_c$p_val, boot_felm_c$p_val)
expect_equivalent(boot_felm_c$p_val, boot_lm$p_val)

# t_stats
expect_equivalent(boot_lm$t_stat, boot_fixest$t_stat)
expect_equivalent(boot_fixest$t_stat, boot_felm$t_stat)
expect_equivalent(boot_felm$t_stat, boot_fixest_c$t_stat)
expect_equivalent(boot_fixest_c$t_stat, boot_felm_c$t_stat)
expect_equivalent(boot_felm_c$t_stat, boot_lm$t_stat)

# confidence intervals
expect_equivalent(boot_lm$conf_int, boot_fixest$conf_int)
expect_equivalent(boot_fixest$conf_int, boot_felm$conf_int)
expect_equivalent(boot_felm$conf_int, boot_fixest_c$conf_int)
expect_equivalent(boot_fixest_c$conf_int, boot_felm_c$conf_int)
expect_equivalent(boot_felm_c$conf_int, boot_lm$conf_int)

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fwildclusterboot documentation built on Sept. 14, 2021, 5:15 p.m.