TablesFinal

source("build_objects.R")

## Loading required package: zoo

## 
## Attaching package: 'zoo'

## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric

## Loading required package: MASS

## Loading required package: strucchange

## Loading required package: sandwich

library(dplyr)

## Warning: package 'dplyr' was built under R version 4.4.3

## 
## Attaching package: 'dplyr'

## The following object is masked from 'package:MASS':
## 
##     select

## The following objects are masked from 'package:stats':
## 
##     filter, lag

## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union

library(knitr)

## Warning: package 'knitr' was built under R version 4.4.3

library(kableExtra)

## 
## Attaching package: 'kableExtra'

## The following object is masked from 'package:dplyr':
## 
##     group_rows

library(lmtest)
library(urca)
library(vars)
library(tibble)

## Warning: package 'tibble' was built under R version 4.4.3

knitr::opts_chunk$set(echo = TRUE, warning = FALSE, message = FALSE)
source("build_objects.R")

## The following objects are masked from USA_data (pos = 7):
## 
##     CO, COUNTRY, COUNTRYCODE, CU, CUR, EMPL, EXR, GO, GU, HCAP, IO, IU,
##     KO, MO, MU, POP, XO, XU, YEAR, YO, YU

# =========================================================
# GLOBAL TABLE RENDERER FOR R MARKDOWN
# =========================================================



make_pretty_table <- function(df, title_text = NULL, digits = 4) {
  df %>%
    as.data.frame() %>%
    mutate(across(where(is.numeric), ~ round(.x, digits))) %>%
    knitr::kable(
      caption = title_text,
      align = "l",
      booktabs = TRUE
    ) %>%
    kableExtra::kable_styling(full_width = FALSE)
}

rbind_fill <- function(...) {
  dfs <- list(...)
  all_names <- unique(unlist(lapply(dfs, names)))
  
  dfs_aligned <- lapply(dfs, function(df) {
    missing <- setdiff(all_names, names(df))
    if (length(missing) > 0) {
      for (m in missing) df[[m]] <- NA
    }
    df[, all_names, drop = FALSE]
  })
  
  out <- do.call(rbind, dfs_aligned)
  rownames(out) <- NULL
  out
}

safe_whitefit_p <- function(model) {
  aux <- data.frame(
    u2 = residuals(model)^2,
    fitvals = fitted(model)
  )
  white_aux <- lm(u2 ~ fitvals + I(fitvals^2), data = aux)
  bptest(white_aux)$p.value
}

collect_diag_tests <- function(model, model_name) {
  data.frame(
    model = model_name,
    BG_p = bgtest(model, order = 4)$p.value,
    LjungBox_p = Box.test(resid(model), lag = 12, type = "Ljung-Box")$p.value,
    BP_p = bptest(model)$p.value,
    WhiteFit_p = safe_whitefit_p(model),
    RESET2_p = resettest(model, power = 2, type = "fitted")$p.value,
    RESET23_p = resettest(model, power = 2:3, type = "fitted")$p.value
  )
}

# ## ADF Tables
make_best_lag_table <- function(adf_table) {
  best_AIC <- do.call(
    rbind,
    lapply(split(adf_table, adf_table$series), function(x) x[which.min(x$AIC), ])
  )
  
  best_BIC <- do.call(
    rbind,
    lapply(split(adf_table, adf_table$series), function(x) x[which.min(x$BIC), ])
  )
  
  best_summary <- merge(
    best_AIC[, c("series", "type", "lag", "tau_stat", "AIC")],
    best_BIC[, c("series", "lag", "tau_stat", "BIC")],
    by = "series",
    suffixes = c("_AIC", "_BIC")
  )
  
  names(best_summary) <- c(
    "series",
    "type",
    "best_lag_AIC",
    "tau_stat_AIC",
    "AIC",
    "best_lag_BIC",
    "tau_stat_BIC",
    "BIC"
  )
  
  rownames(best_AIC) <- NULL
  rownames(best_BIC) <- NULL
  rownames(best_summary) <- NULL
  
  list(
    full = adf_table,
    best_AIC = best_AIC,
    best_BIC = best_BIC,
    summary = best_summary
  )
}

adf_tables_levels <- make_best_lag_table(adf_lag_table)
adf_tables_logs   <- make_best_lag_table(adf_lag_table_log)
adf_tables_dlog   <- make_best_lag_table(adf_lag_table_dlog)

make_pretty_table(adf_tables_levels$full,     "ADF LEVEL VARIABLES - FULL LAG TABLE")

ADF LEVEL VARIABLES - FULL LAG TABLE

series	type	lag	tau_stat	AIC	BIC
wage_gap	trend	0	-2.7571	-1508.5606	-1467.0968
wage_gap	trend	1	-2.4823	-1494.5787	-1439.3621
wage_gap	trend	2	-2.5016	-1479.5305	-1410.5958
wage_gap	trend	3	-2.4518	-1463.9835	-1381.3655
wage_gap	trend	4	-2.4808	-1450.7254	-1354.4591
wage_gap	trend	5	-2.5487	-1435.7025	-1325.8234
wage_gap	trend	6	-2.5227	-1420.7702	-1297.3138
wage_gap	trend	7	-2.3474	-1405.7865	-1268.7885
wage_gap	trend	8	-2.1043	-1391.7888	-1241.2853
treasury_gdp	trend	0	0.1365	-1885.5109	-1844.0471
treasury_gdp	trend	1	-0.5479	-1905.5294	-1850.3128
treasury_gdp	trend	2	-0.7891	-1892.7755	-1823.8408
treasury_gdp	trend	3	-1.3553	-1891.7857	-1809.1677
treasury_gdp	trend	4	-1.7103	-1882.2027	-1785.9365
treasury_gdp	trend	5	-1.7473	-1865.3189	-1755.4398
treasury_gdp	trend	6	-1.7151	-1847.9130	-1724.4566
treasury_gdp	trend	7	-1.9354	-1832.6533	-1695.6553
treasury_gdp	trend	8	-1.7991	-1815.5498	-1665.0462
trade_deficit_gdp	trend	0	-1.8462	-2074.7900	-2033.3261
trade_deficit_gdp	trend	1	-2.4129	-2071.3929	-2016.1763
trade_deficit_gdp	trend	2	-2.1759	-2055.0474	-1986.1127
trade_deficit_gdp	trend	3	-2.2058	-2037.7789	-1955.1609
trade_deficit_gdp	trend	4	-1.9272	-2022.1232	-1925.8570
trade_deficit_gdp	trend	5	-1.8965	-2004.0925	-1894.2134
trade_deficit_gdp	trend	6	-2.1246	-1989.0557	-1865.5992
trade_deficit_gdp	trend	7	-2.1929	-1971.5282	-1834.5302
trade_deficit_gdp	trend	8	-2.1749	-1953.5381	-1803.0345
fdi_outward_gdp	trend	0	-3.8745	-1216.8683	-1175.4045
fdi_outward_gdp	trend	1	-3.9051	-1203.0267	-1147.8101
fdi_outward_gdp	trend	2	-4.2030	-1191.5900	-1122.6552
fdi_outward_gdp	trend	3	-3.9048	-1177.9087	-1095.2906
fdi_outward_gdp	trend	4	-3.7429	-1163.7040	-1067.4378
fdi_outward_gdp	trend	5	-4.0111	-1151.9735	-1042.0944
fdi_outward_gdp	trend	6	-3.6366	-1138.9931	-1015.5367
fdi_outward_gdp	trend	7	-3.2733	-1126.8173	-989.8193
fdi_outward_gdp	trend	8	-2.9407	-1114.6101	-964.1066
imports_ind_real_gdp	trend	0	-2.0670	-2221.4416	-2179.9778
imports_ind_real_gdp	trend	1	-3.4170	-2246.1708	-2190.9542
imports_ind_real_gdp	trend	2	-2.7130	-2235.0666	-2166.1319
imports_ind_real_gdp	trend	3	-2.7453	-2216.5180	-2133.8999
imports_ind_real_gdp	trend	4	-2.1751	-2205.0220	-2108.7557
imports_ind_real_gdp	trend	5	-2.3500	-2187.7172	-2077.8381
imports_ind_real_gdp	trend	6	-2.2639	-2168.9548	-2045.4983
imports_ind_real_gdp	trend	7	-2.1340	-2150.3726	-2013.3746
imports_ind_real_gdp	trend	8	-1.8352	-2134.2289	-1983.7254
min_wage_real	trend	0	-1.9475	-2261.5597	-2220.0959
min_wage_real	trend	1	-1.9533	-2244.8119	-2189.5952
min_wage_real	trend	2	-1.7413	-2227.3488	-2158.4140
min_wage_real	trend	3	-1.6808	-2208.6825	-2126.0645
min_wage_real	trend	4	-3.0574	-2249.8385	-2153.5723
min_wage_real	trend	5	-2.8241	-2234.9761	-2125.0970
min_wage_real	trend	6	-2.8897	-2216.3938	-2092.9373
min_wage_real	trend	7	-2.9857	-2198.1344	-2061.1364
min_wage_real	trend	8	-3.1007	-2184.9929	-2034.4893
long_rate	trend	0	-2.5048	339.9844	381.4482
long_rate	trend	1	-2.8036	332.1495	387.3661
long_rate	trend	2	-2.5976	338.9532	407.8879
long_rate	trend	3	-2.7630	341.3623	423.9803
long_rate	trend	4	-2.7532	348.3269	444.5931
long_rate	trend	5	-2.5205	352.7278	462.6069
long_rate	trend	6	-2.6795	358.9543	482.4108
long_rate	trend	7	-2.3556	362.0712	499.0692
long_rate	trend	8	-2.3193	368.8120	519.3155

make_pretty_table(adf_tables_levels$best_AIC, "ADF LEVEL VARIABLES - BEST LAG BY AIC")

ADF LEVEL VARIABLES - BEST LAG BY AIC

series	type	lag	tau_stat	AIC	BIC
fdi_outward_gdp	trend	0	-3.8745	-1216.8683	-1175.4045
imports_ind_real_gdp	trend	1	-3.4170	-2246.1708	-2190.9542
long_rate	trend	1	-2.8036	332.1495	387.3661
min_wage_real	trend	0	-1.9475	-2261.5597	-2220.0959
trade_deficit_gdp	trend	0	-1.8462	-2074.7900	-2033.3261
treasury_gdp	trend	1	-0.5479	-1905.5294	-1850.3128
wage_gap	trend	0	-2.7571	-1508.5606	-1467.0968

make_pretty_table(adf_tables_levels$best_BIC, "ADF LEVEL VARIABLES - BEST LAG BY BIC")

ADF LEVEL VARIABLES - BEST LAG BY BIC

series	type	lag	tau_stat	AIC	BIC
fdi_outward_gdp	trend	0	-3.8745	-1216.8683	-1175.4045
imports_ind_real_gdp	trend	1	-3.4170	-2246.1708	-2190.9542
long_rate	trend	0	-2.5048	339.9844	381.4482
min_wage_real	trend	0	-1.9475	-2261.5597	-2220.0959
trade_deficit_gdp	trend	0	-1.8462	-2074.7900	-2033.3261
treasury_gdp	trend	1	-0.5479	-1905.5294	-1850.3128
wage_gap	trend	0	-2.7571	-1508.5606	-1467.0968

make_pretty_table(adf_tables_levels$summary,  "ADF LEVEL VARIABLES - BEST LAG SUMMARY")

ADF LEVEL VARIABLES - BEST LAG SUMMARY

series	type	best_lag_AIC	tau_stat_AIC	AIC	best_lag_BIC	tau_stat_BIC	BIC
fdi_outward_gdp	trend	0	-3.8745	-1216.8683	0	-3.8745	-1175.4045
imports_ind_real_gdp	trend	1	-3.4170	-2246.1708	1	-3.4170	-2190.9542
long_rate	trend	1	-2.8036	332.1495	0	-2.5048	381.4482
min_wage_real	trend	0	-1.9475	-2261.5597	0	-1.9475	-2220.0959
trade_deficit_gdp	trend	0	-1.8462	-2074.7900	0	-1.8462	-2033.3261
treasury_gdp	trend	1	-0.5479	-1905.5294	1	-0.5479	-1850.3128
wage_gap	trend	0	-2.7571	-1508.5606	0	-2.7571	-1467.0968

make_pretty_table(adf_tables_logs$full,     "ADF LOG VARIABLES - FULL LAG TABLE")

ADF LOG VARIABLES - FULL LAG TABLE

series	type	lag	tau_stat	AIC	BIC
log_wage_gap	trend	0	-2.1528	-1644.5272	-1603.0634
log_wage_gap	trend	1	-1.9157	-1630.0405	-1574.8239
log_wage_gap	trend	2	-2.0328	-1615.4071	-1546.4724
log_wage_gap	trend	3	-1.8955	-1599.6429	-1517.0248
log_wage_gap	trend	4	-1.8800	-1586.4856	-1490.2194
log_wage_gap	trend	5	-1.8510	-1570.6030	-1460.7239
log_wage_gap	trend	6	-1.8013	-1555.5103	-1432.0539
log_wage_gap	trend	7	-1.6070	-1540.9641	-1403.9661
log_wage_gap	trend	8	-1.4448	-1526.2226	-1375.7191
log_treasury_gdp	trend	0	-0.8771	-632.1951	-590.7313
log_treasury_gdp	trend	1	-1.4879	-639.5084	-584.2918
log_treasury_gdp	trend	2	-1.7828	-632.2816	-563.3468
log_treasury_gdp	trend	3	-2.5728	-644.7672	-562.1492
log_treasury_gdp	trend	4	-3.1193	-644.0367	-547.7705
log_treasury_gdp	trend	5	-3.0454	-648.9133	-539.0342
log_treasury_gdp	trend	6	-2.9435	-636.9720	-513.5156
log_treasury_gdp	trend	7	-2.3934	-628.8569	-491.8589
log_treasury_gdp	trend	8	-2.4976	-623.3850	-472.8815
log_trade_balance	trend	0	-2.1101	-987.0529	-945.5890
log_trade_balance	trend	1	-2.4616	-980.3904	-925.1738
log_trade_balance	trend	2	-2.2269	-969.9012	-900.9665
log_trade_balance	trend	3	-2.4366	-959.7117	-877.0937
log_trade_balance	trend	4	-2.3814	-946.7807	-850.5145
log_trade_balance	trend	5	-2.3368	-933.4958	-823.6167
log_trade_balance	trend	6	-2.6546	-926.9172	-803.4607
log_trade_balance	trend	7	-2.7862	-915.8556	-778.8576
log_trade_balance	trend	8	-2.6386	-902.7240	-752.2205
log_fdi_outward_gdp	trend	0	-3.4518	-474.7437	-433.2799
log_fdi_outward_gdp	trend	1	-3.3874	-463.6518	-408.4352
log_fdi_outward_gdp	trend	2	-3.4626	-453.1305	-384.1958
log_fdi_outward_gdp	trend	3	-3.2252	-442.5004	-359.8824
log_fdi_outward_gdp	trend	4	-3.3656	-432.5517	-336.2855
log_fdi_outward_gdp	trend	5	-3.4248	-421.9654	-312.0863
log_fdi_outward_gdp	trend	6	-3.2585	-410.9269	-287.4704
log_fdi_outward_gdp	trend	7	-2.9572	-400.9779	-263.9799
log_fdi_outward_gdp	trend	8	-2.9770	-390.1059	-239.6024
log_imports_ind_real_gdp	trend	0	-1.7780	-479.4511	-437.9873
log_imports_ind_real_gdp	trend	1	-2.3232	-484.6957	-429.4791
log_imports_ind_real_gdp	trend	2	-2.4258	-475.2361	-406.3013
log_imports_ind_real_gdp	trend	3	-2.2511	-465.6324	-383.0144
log_imports_ind_real_gdp	trend	4	-1.9039	-460.6499	-364.3837
log_imports_ind_real_gdp	trend	5	-1.9542	-450.7028	-340.8237
log_imports_ind_real_gdp	trend	6	-2.2041	-442.7818	-319.3254
log_imports_ind_real_gdp	trend	7	-2.1102	-432.6514	-295.6534
log_imports_ind_real_gdp	trend	8	-2.3221	-429.6479	-279.1444
log_min_wage_real	trend	0	-1.8149	-1027.1857	-985.7219
log_min_wage_real	trend	1	-1.8176	-1015.3303	-960.1137
log_min_wage_real	trend	2	-1.6280	-1002.8295	-933.8947
log_min_wage_real	trend	3	-1.5882	-989.4126	-906.7946
log_min_wage_real	trend	4	-2.9269	-1031.2886	-935.0224
log_min_wage_real	trend	5	-2.7067	-1020.2860	-910.4069
log_min_wage_real	trend	6	-2.7646	-1006.9439	-883.4874
log_min_wage_real	trend	7	-2.8604	-993.9505	-856.9525
log_min_wage_real	trend	8	-2.9303	-984.1421	-833.6386
log_long_rate	trend	0	-2.5540	-357.4551	-315.9913
log_long_rate	trend	1	-3.2730	-373.5768	-318.3602
log_long_rate	trend	2	-2.7674	-367.8754	-298.9406
log_long_rate	trend	3	-2.8578	-358.4412	-275.8232
log_long_rate	trend	4	-3.0606	-349.4439	-253.1777
log_long_rate	trend	5	-3.1636	-339.6914	-229.8123
log_long_rate	trend	6	-3.1934	-330.4749	-207.0185
log_long_rate	trend	7	-2.8178	-321.5077	-184.5097
log_long_rate	trend	8	-2.5009	-313.5662	-163.0627

make_pretty_table(adf_tables_logs$best_AIC, "ADF LOG VARIABLES - BEST LAG BY AIC")

ADF LOG VARIABLES - BEST LAG BY AIC

series	type	lag	tau_stat	AIC	BIC
log_fdi_outward_gdp	trend	0	-3.4518	-474.7437	-433.2799
log_imports_ind_real_gdp	trend	1	-2.3232	-484.6957	-429.4791
log_long_rate	trend	1	-3.2730	-373.5768	-318.3602
log_min_wage_real	trend	4	-2.9269	-1031.2886	-935.0224
log_trade_balance	trend	0	-2.1101	-987.0529	-945.5890
log_treasury_gdp	trend	5	-3.0454	-648.9133	-539.0342
log_wage_gap	trend	0	-2.1528	-1644.5272	-1603.0634

make_pretty_table(adf_tables_logs$best_BIC, "ADF LOG VARIABLES - BEST LAG BY BIC")

ADF LOG VARIABLES - BEST LAG BY BIC

series	type	lag	tau_stat	AIC	BIC
log_fdi_outward_gdp	trend	0	-3.4518	-474.7437	-433.2799
log_imports_ind_real_gdp	trend	0	-1.7780	-479.4511	-437.9873
log_long_rate	trend	1	-3.2730	-373.5768	-318.3602
log_min_wage_real	trend	0	-1.8149	-1027.1857	-985.7219
log_trade_balance	trend	0	-2.1101	-987.0529	-945.5890
log_treasury_gdp	trend	0	-0.8771	-632.1951	-590.7313
log_wage_gap	trend	0	-2.1528	-1644.5272	-1603.0634

make_pretty_table(adf_tables_logs$summary,  "ADF LOG VARIABLES - BEST LAG SUMMARY")

ADF LOG VARIABLES - BEST LAG SUMMARY

series	type	best_lag_AIC	tau_stat_AIC	AIC	best_lag_BIC	tau_stat_BIC	BIC
log_fdi_outward_gdp	trend	0	-3.4518	-474.7437	0	-3.4518	-433.2799
log_imports_ind_real_gdp	trend	1	-2.3232	-484.6957	0	-1.7780	-437.9873
log_long_rate	trend	1	-3.2730	-373.5768	1	-3.2730	-318.3602
log_min_wage_real	trend	4	-2.9269	-1031.2886	0	-1.8149	-985.7219
log_trade_balance	trend	0	-2.1101	-987.0529	0	-2.1101	-945.5890
log_treasury_gdp	trend	5	-3.0454	-648.9133	0	-0.8771	-590.7313
log_wage_gap	trend	0	-2.1528	-1644.5272	0	-2.1528	-1603.0634

make_pretty_table(adf_tables_dlog$full,     "ADF DIFFERENCED VARIABLES - FULL LAG TABLE")

ADF DIFFERENCED VARIABLES - FULL LAG TABLE

series	type	lag	tau_stat	AIC	BIC
d_log_wage_gap	drift	0	-16.7974	-1642.1847	-1614.5764
d_log_wage_gap	drift	1	-10.6977	-1627.0257	-1585.6649
d_log_wage_gap	drift	2	-9.2263	-1611.7481	-1556.6695
d_log_wage_gap	drift	3	-8.0964	-1598.7755	-1530.0140
d_log_wage_gap	drift	4	-7.2923	-1583.0089	-1500.5995
d_log_wage_gap	drift	5	-6.5658	-1568.0048	-1471.9832
d_log_wage_gap	drift	6	-6.4879	-1554.0093	-1444.4109
d_log_wage_gap	drift	7	-6.3710	-1539.6252	-1416.4859
d_log_wage_gap	drift	8	-5.1014	-1529.3345	-1392.6904
d_log_treasury_gdp	drift	0	-11.3562	-650.6504	-623.0421
d_log_treasury_gdp	drift	1	-7.9120	-643.0935	-601.7327
d_log_treasury_gdp	drift	2	-5.2182	-653.2464	-598.1677
d_log_treasury_gdp	drift	3	-4.5025	-648.9344	-580.1729
d_log_treasury_gdp	drift	4	-5.2040	-652.5928	-570.1834
d_log_treasury_gdp	drift	5	-4.9001	-641.5546	-545.5329
d_log_treasury_gdp	drift	6	-5.1387	-636.7122	-527.1138
d_log_treasury_gdp	drift	7	-5.2491	-629.4731	-506.3338
d_log_treasury_gdp	drift	8	-5.3455	-620.4230	-483.7790
d_log_trade_balance	drift	0	-13.0963	-989.7602	-962.1519
d_log_trade_balance	drift	1	-10.4955	-980.5509	-939.1900
d_log_trade_balance	drift	2	-8.1644	-969.2259	-914.1473
d_log_trade_balance	drift	3	-7.4637	-956.4267	-887.6651
d_log_trade_balance	drift	4	-6.8487	-943.2919	-860.8826
d_log_trade_balance	drift	5	-5.3757	-935.3624	-839.3407
d_log_trade_balance	drift	6	-4.7795	-923.6881	-814.0897
d_log_trade_balance	drift	7	-4.8065	-911.3541	-788.2148
d_log_trade_balance	drift	8	-4.5686	-898.6340	-761.9900
d_log_fdi_outward_gdp	drift	0	-15.8068	-468.2576	-440.6493
d_log_fdi_outward_gdp	drift	1	-10.8942	-457.1867	-415.8259
d_log_fdi_outward_gdp	drift	2	-9.6216	-448.0581	-392.9794
d_log_fdi_outward_gdp	drift	3	-7.8913	-437.1507	-368.3891
d_log_fdi_outward_gdp	drift	4	-6.9790	-426.1148	-343.7055
d_log_fdi_outward_gdp	drift	5	-6.7407	-416.1221	-320.1004
d_log_fdi_outward_gdp	drift	6	-6.8355	-408.0002	-298.4018
d_log_fdi_outward_gdp	drift	7	-6.2301	-396.9641	-273.8249
d_log_fdi_outward_gdp	drift	8	-6.1765	-387.2809	-250.6369
d_log_imports_ind_real_gdp	drift	0	-11.7843	-492.8260	-465.2177
d_log_imports_ind_real_gdp	drift	1	-9.5115	-482.3944	-441.0336
d_log_imports_ind_real_gdp	drift	2	-7.8676	-474.2596	-419.1809
d_log_imports_ind_real_gdp	drift	3	-8.2399	-470.0969	-401.3353
d_log_imports_ind_real_gdp	drift	4	-7.4100	-459.4572	-377.0479
d_log_imports_ind_real_gdp	drift	5	-5.9553	-450.7682	-354.7465
d_log_imports_ind_real_gdp	drift	6	-5.8909	-440.6498	-331.0514
d_log_imports_ind_real_gdp	drift	7	-6.0112	-434.8993	-311.7600
d_log_imports_ind_real_gdp	drift	8	-5.4969	-433.7182	-297.0741
d_log_min_wage_real	drift	0	-15.5722	-1027.8304	-1000.2221
d_log_min_wage_real	drift	1	-11.7091	-1015.9080	-974.5472
d_log_min_wage_real	drift	2	-9.3595	-1002.5671	-947.4884
d_log_min_wage_real	drift	3	-5.4337	-1038.6180	-969.8564
d_log_min_wage_real	drift	4	-5.7810	-1028.8107	-946.4014
d_log_min_wage_real	drift	5	-5.3741	-1015.1140	-919.0923
d_log_min_wage_real	drift	6	-4.9175	-1001.5437	-891.9453
d_log_min_wage_real	drift	7	-4.2986	-991.2804	-868.1412
d_log_min_wage_real	drift	8	-4.1492	-978.3714	-841.7274
d_long_rate	drift	0	-11.9035	324.2814	351.8897
d_long_rate	drift	1	-10.1106	329.9770	371.3378
d_long_rate	drift	2	-7.3740	333.1767	388.2553
d_long_rate	drift	3	-6.9320	340.1683	408.9299
d_long_rate	drift	4	-7.2029	343.4078	425.8171
d_long_rate	drift	5	-6.4492	350.5815	446.6032
d_long_rate	drift	6	-6.8947	352.0574	461.6558
d_long_rate	drift	7	-5.9475	358.5412	481.6804
d_long_rate	drift	8	-5.7258	365.7572	502.4012

make_pretty_table(adf_tables_dlog$best_AIC, "ADF DIFFERENCED VARIABLES - BEST LAG BY AIC")

ADF DIFFERENCED VARIABLES - BEST LAG BY AIC

series	type	lag	tau_stat	AIC	BIC
d_log_fdi_outward_gdp	drift	0	-15.8068	-468.2576	-440.6493
d_log_imports_ind_real_gdp	drift	0	-11.7843	-492.8260	-465.2177
d_log_min_wage_real	drift	3	-5.4337	-1038.6180	-969.8564
d_log_trade_balance	drift	0	-13.0963	-989.7602	-962.1519
d_log_treasury_gdp	drift	2	-5.2182	-653.2464	-598.1677
d_log_wage_gap	drift	0	-16.7974	-1642.1847	-1614.5764
d_long_rate	drift	0	-11.9035	324.2814	351.8897

make_pretty_table(adf_tables_dlog$best_BIC, "ADF DIFFERENCED VARIABLES - BEST LAG BY BIC")

ADF DIFFERENCED VARIABLES - BEST LAG BY BIC

series	type	lag	tau_stat	AIC	BIC
d_log_fdi_outward_gdp	drift	0	-15.8068	-468.2576	-440.6493
d_log_imports_ind_real_gdp	drift	0	-11.7843	-492.8260	-465.2177
d_log_min_wage_real	drift	0	-15.5722	-1027.8304	-1000.2221
d_log_trade_balance	drift	0	-13.0963	-989.7602	-962.1519
d_log_treasury_gdp	drift	0	-11.3562	-650.6504	-623.0421
d_log_wage_gap	drift	0	-16.7974	-1642.1847	-1614.5764
d_long_rate	drift	0	-11.9035	324.2814	351.8897

make_pretty_table(adf_tables_dlog$summary,  "ADF DIFFERENCED VARIABLES - BEST LAG SUMMARY")

ADF DIFFERENCED VARIABLES - BEST LAG SUMMARY

series	type	best_lag_AIC	tau_stat_AIC	AIC	best_lag_BIC	tau_stat_BIC	BIC
d_log_fdi_outward_gdp	drift	0	-15.8068	-468.2576	0	-15.8068	-440.6493
d_log_imports_ind_real_gdp	drift	0	-11.7843	-492.8260	0	-11.7843	-465.2177
d_log_min_wage_real	drift	3	-5.4337	-1038.6180	0	-15.5722	-1000.2221
d_log_trade_balance	drift	0	-13.0963	-989.7602	0	-13.0963	-962.1519
d_log_treasury_gdp	drift	2	-5.2182	-653.2464	0	-11.3562	-623.0421
d_log_wage_gap	drift	0	-16.7974	-1642.1847	0	-16.7974	-1614.5764
d_long_rate	drift	0	-11.9035	324.2814	0	-11.9035	351.8897

# ## Engle-Granger Tables
collect_eg_results <- function(eg_obj, model_label) {
  data.frame(
    model = model_label,
    best_lag_AIC = eg_obj$best_AIC$lag,
    tau_stat_AIC = eg_obj$best_AIC$tau_stat,
    AIC = eg_obj$best_AIC$AIC,
    best_lag_BIC = eg_obj$best_BIC$lag,
    tau_stat_BIC = eg_obj$best_BIC$tau_stat,
    BIC = eg_obj$best_BIC$BIC
  )
}

eg_table_no_break <- rbind(
  collect_eg_results(eg_baseline, "baseline"),
  collect_eg_results(eg_pathway1, "pathway1_imports"),
  collect_eg_results(eg_pathway2, "pathway2_longrate"),
  collect_eg_results(eg_optional, "optional_both_pathways")
)
rownames(eg_table_no_break) <- NULL

eg_table_break <- rbind(
  collect_eg_results(eg_baseline_break, "baseline_break"),
  collect_eg_results(eg_pathway1_break, "pathway1_break"),
  collect_eg_results(eg_pathway2_break, "pathway2_break"),
  collect_eg_results(eg_fdi_break, "fdi_break"),
  collect_eg_results(eg_optional_break, "optional_break"),
  collect_eg_results(eg_optional_breakFDI, "optional_breakFDI")
)
rownames(eg_table_break) <- NULL

make_pretty_table(eg_table_no_break, "ENGLE-GRANGER RESULTS - NO BREAK")

ENGLE-GRANGER RESULTS - NO BREAK

model	best_lag_AIC	tau_stat_AIC	AIC	best_lag_BIC	tau_stat_BIC	BIC
baseline	0	-2.1752	-1391.764	0	-2.1752	-1377.943
pathway1_imports	0	-2.1204	-1414.749	0	-2.1204	-1400.928
pathway2_longrate	0	-2.5252	-1347.957	0	-2.5252	-1334.135
optional_both_pathways	0	-3.4033	-1319.774	0	-3.4033	-1305.953

make_pretty_table(eg_table_break, "ENGLE-GRANGER RESULTS - BREAK MODELS")

ENGLE-GRANGER RESULTS - BREAK MODELS

model	best_lag_AIC	tau_stat_AIC	AIC	best_lag_BIC	tau_stat_BIC	BIC
baseline_break	0	-4.0864	-1513.723	0	-4.0864	-1499.902
pathway1_break	0	-5.6014	-1515.975	0	-5.6014	-1502.153
pathway2_break	0	-4.6279	-1495.590	0	-4.6279	-1481.769
fdi_break	0	-3.9769	-1532.493	0	-3.9769	-1518.671
optional_break	0	-5.6480	-1516.875	0	-5.6480	-1503.054
optional_breakFDI	0	-5.6453	-1517.047	0	-5.6453	-1503.226

# ## Long-Run Regression Fit Tables
collect_lm_fit_stats <- function(model, model_label) {
  s <- summary(model)
  data.frame(
    model = model_label,
    n = length(resid(model)),
    R2 = s$r.squared,
    Adj_R2 = s$adj.r.squared,
    Resid_SE = s$sigma,
    F_stat = unname(s$fstatistic[1]),
    F_df1 = unname(s$fstatistic[2]),
    F_df2 = unname(s$fstatistic[3]),
    F_p = pf(
      unname(s$fstatistic[1]),
      unname(s$fstatistic[2]),
      unname(s$fstatistic[3]),
      lower.tail = FALSE
    )
  )
}

longrun_fit_no_break <- rbind(
  collect_lm_fit_stats(eg_baseline$long_run, "baseline"),
  collect_lm_fit_stats(eg_pathway1$long_run, "pathway1_imports"),
  collect_lm_fit_stats(eg_pathway2$long_run, "pathway2_longrate"),
  collect_lm_fit_stats(eg_optional$long_run, "optional_both_pathways")
)
rownames(longrun_fit_no_break) <- NULL

longrun_fit_break <- rbind(
  collect_lm_fit_stats(eg_baseline_break$long_run, "baseline_break"),
  collect_lm_fit_stats(eg_pathway1_break$long_run, "pathway1_break"),
  collect_lm_fit_stats(eg_pathway2_break$long_run, "pathway2_break"),
  collect_lm_fit_stats(eg_fdi_break$long_run, "fdi_break"),
  collect_lm_fit_stats(eg_optional_break$long_run, "optional_break"),
  collect_lm_fit_stats(eg_optional_breakFDI$long_run, "optional_breakFDI")
)
rownames(longrun_fit_break) <- NULL

make_pretty_table(longrun_fit_no_break, "LONG-RUN REGRESSION FIT - NO BREAK")

LONG-RUN REGRESSION FIT - NO BREAK

model	n	R2	Adj_R2	Resid_SE	F_stat	F_df1	F_df2	F_p
baseline	235	0.8866	0.8852	0.0456	602.1818	3	231	0
pathway1_imports	235	0.8879	0.8860	0.0455	455.4543	4	230	0
pathway2_longrate	235	0.9136	0.9121	0.0399	607.9992	4	230	0
optional_both_pathways	235	0.9430	0.9417	0.0325	757.0053	5	229	0

make_pretty_table(longrun_fit_break, "LONG-RUN REGRESSION FIT - BREAK MODELS")

LONG-RUN REGRESSION FIT - BREAK MODELS

model	n	R2	Adj_R2	Resid_SE	F_stat	F_df1	F_df2	F_p
baseline_break	235	0.9806	0.9801	0.0190	2309.792	5	229	0
pathway1_break	235	0.9885	0.9882	0.0146	3279.853	6	228	0
pathway2_break	235	0.9830	0.9825	0.0178	2196.393	6	228	0
fdi_break	235	0.9812	0.9807	0.0187	1981.612	6	228	0
optional_break	235	0.9887	0.9884	0.0145	2847.196	7	227	0
optional_breakFDI	235	0.9887	0.9883	0.0145	2480.330	8	226	0

# ## Short-Run Regression Tables
collect_short_run_stats <- function(model, model_label, key_vars = NULL) {
  s <- summary(model)
  coefs <- s$coefficients
  
  out <- data.frame(
    model = model_label,
    n = length(resid(model)),
    R2 = s$r.squared,
    Adj_R2 = s$adj.r.squared,
    Resid_SE = s$sigma,
    F_stat = unname(s$fstatistic[1]),
    F_p = pf(
      unname(s$fstatistic[1]),
      unname(s$fstatistic[2]),
      unname(s$fstatistic[3]),
      lower.tail = FALSE
    )
  )
  
  if (!is.null(key_vars)) {
    for (v in key_vars) {
      out[[paste0(v, "_coef")]] <- if (v %in% rownames(coefs)) coefs[v, 1] else NA_real_
      out[[paste0(v, "_p")]]    <- if (v %in% rownames(coefs)) coefs[v, 4] else NA_real_
    }
  }
  
  out
}

short_run_table_basic <- rbind_fill(
  collect_short_run_stats(
    mod_dlog_baseline, "baseline",
    key_vars = c("d_log_treasury_gdp", "d_log_trade_balance", "d_log_min_wage_real")
  ),
  collect_short_run_stats(
    mod_dlog_fdi, "pathway_fdi",
    key_vars = c("d_log_fdi_outward_gdp")
  ),
  collect_short_run_stats(
    mod_dlog_imports, "pathway_imports",
    key_vars = c("d_log_imports_ind_real_gdp")
  ),
  collect_short_run_stats(
    mod_dlog_longrate, "pathway_longrate",
    key_vars = c("d_long_rate")
  ),
  collect_short_run_stats(
    mod_dlog_full_with_fdi, "full_with_fdi",
    key_vars = c("d_log_fdi_outward_gdp", "d_log_imports_ind_real_gdp", "d_long_rate")
  ),
  collect_short_run_stats(
    mod_dlog_full_no_fdi, "full_no_fdi",
    key_vars = c("d_log_imports_ind_real_gdp", "d_long_rate")
  )
)

short_run_table_pandemic <- rbind_fill(
  collect_short_run_stats(
    mod_dlog_fdi_pandemic,
    "fdi_pandemic",
    key_vars = c("d_log_fdi_outward_gdp", "pandemic_q1")
  ),
  collect_short_run_stats(
    mod_dlog_full_with_fdi_pandemic,
    "full_with_fdi_pandemic",
    key_vars = c("d_log_fdi_outward_gdp", "d_log_imports_ind_real_gdp", "d_long_rate", "pandemic_q1")
  ),
  collect_short_run_stats(
    mod_dlog_fdi_break,
    "fdi_break",
    key_vars = c("d_log_fdi_outward_gdp", "pandemic_q1", "D2000", "DT2000")
  )
)

make_pretty_table(short_run_table_basic, "SHORT-RUN DIFFERENCED MODELS - FIT AND KEY COEFFICIENTS")

SHORT-RUN DIFFERENCED MODELS - FIT AND KEY COEFFICIENTS

model	n	R2	Adj_R2	Resid_SE	F_stat	F_p	d_log_treasury_gdp_coef	d_log_treasury_gdp_p	d_log_trade_balance_coef	d_log_trade_balance_p	d_log_min_wage_real_coef	d_log_min_wage_real_p	d_log_fdi_outward_gdp_coef	d_log_fdi_outward_gdp_p	d_log_imports_ind_real_gdp_coef	d_log_imports_ind_real_gdp_p	d_long_rate_coef	d_long_rate_p
baseline	234	0.0154	0.0025	0.0069	1.1952	0.3123	0.0097	0.1971	-0.002	0.9022	-0.0237	0.179	NA	NA	NA	NA	NA	NA
pathway_fdi	234	0.0602	0.0438	0.0068	3.6663	0.0065	NA	NA	NA	NA	NA	NA	0.0171	0.0011	NA	NA	NA	NA
pathway_imports	234	0.0240	0.0070	0.0069	1.4093	0.2317	NA	NA	NA	NA	NA	NA	NA	NA	-0.0078	0.1551	NA	NA
pathway_longrate	234	0.0171	-0.0001	0.0069	0.9946	0.4113	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	-6e-04	0.5268
full_with_fdi	234	0.0723	0.0477	0.0068	2.9470	0.0087	NA	NA	NA	NA	NA	NA	0.0178	0.0007	-0.0090	0.1069	-2e-04	0.8792
full_no_fdi	234	0.0244	0.0030	0.0069	1.1396	0.3402	NA	NA	NA	NA	NA	NA	NA	NA	-0.0074	0.1926	-3e-04	0.7729

make_pretty_table(short_run_table_pandemic, "SHORT-RUN PANDEMIC / BREAK MODELS - FIT AND KEY COEFFICIENTS")

SHORT-RUN PANDEMIC / BREAK MODELS - FIT AND KEY COEFFICIENTS

model	n	R2	Adj_R2	Resid_SE	F_stat	F_p	d_log_fdi_outward_gdp_coef	d_log_fdi_outward_gdp_p	pandemic_q1_coef	pandemic_q1_p	d_log_imports_ind_real_gdp_coef	d_log_imports_ind_real_gdp_p	d_long_rate_coef	d_long_rate_p	D2000_coef	D2000_p	DT2000_coef	DT2000_p
fdi_pandemic	234	0.0793	0.0591	0.0067	3.9281	0.0020	0.0149	0.0051	-0.0150	0.0306	NA	NA	NA	NA	NA	NA	NA	NA
full_with_fdi_pandemic	234	0.0922	0.0640	0.0067	3.2778	0.0024	0.0154	0.0037	-0.0153	0.0270	-0.009	0.1028	-3e-04	0.7759	NA	NA	NA	NA
fdi_break	234	0.0798	0.0513	0.0068	2.7985	0.0082	0.0148	0.0056	-0.0148	0.0349	NA	NA	NA	NA	3e-04	0.8366	0	0.7392

# ## Short-Run Diagnostics Table
short_run_diag_table <- rbind(
  collect_diag_tests(mod_dlog_fdi, "mod_dlog_fdi"),
  collect_diag_tests(mod_dlog_full_with_fdi, "mod_dlog_full_with_fdi"),
  collect_diag_tests(mod_dlog_fdi_pandemic, "mod_dlog_fdi_pandemic"),
  collect_diag_tests(mod_dlog_full_with_fdi_pandemic, "mod_dlog_full_with_fdi_pandemic"),
  collect_diag_tests(mod_dlog_fdi_break, "mod_dlog_fdi_break")
)
rownames(short_run_diag_table) <- NULL

make_pretty_table(short_run_diag_table, "SHORT-RUN MODEL DIAGNOSTICS")

SHORT-RUN MODEL DIAGNOSTICS

model	BG_p	LjungBox_p	BP_p	WhiteFit_p	RESET2_p	RESET23_p
mod_dlog_fdi	0.5724	0.3458	0.5605	0.0000	0.7353	0.8377
mod_dlog_full_with_fdi	0.5761	0.3153	0.7066	0.0000	0.1670	0.0997
mod_dlog_fdi_pandemic	0.8281	0.3754	0.4630	0.0016	0.6625	0.9033
mod_dlog_full_with_fdi_pandemic	0.8045	0.3303	0.5737	0.0000	0.0993	0.0166
mod_dlog_fdi_break	0.8121	0.3675	0.0815	0.0047	0.7879	0.8701

# ## ECM Fit Table
collect_ecm_stats <- function(model, model_label, ect_name, extra_vars = NULL) {
  s <- summary(model)
  coefs <- s$coefficients
  
  out <- data.frame(
    model = model_label,
    n = length(resid(model)),
    R2 = s$r.squared,
    Adj_R2 = s$adj.r.squared,
    Resid_SE = s$sigma,
    F_stat = unname(s$fstatistic[1]),
    F_p = pf(
      unname(s$fstatistic[1]),
      unname(s$fstatistic[2]),
      unname(s$fstatistic[3]),
      lower.tail = FALSE
    ),
    ECT_coef = if (ect_name %in% rownames(coefs)) coefs[ect_name, 1] else NA_real_,
    ECT_p = if (ect_name %in% rownames(coefs)) coefs[ect_name, 4] else NA_real_,
    pandemic_coef = if ("pandemic_q1_d" %in% rownames(coefs)) coefs["pandemic_q1_d", 1] else NA_real_,
    pandemic_p = if ("pandemic_q1_d" %in% rownames(coefs)) coefs["pandemic_q1_d", 4] else NA_real_
  )
  
  if (!is.null(extra_vars)) {
    for (v in extra_vars) {
      out[[paste0(v, "_coef")]] <- if (v %in% rownames(coefs)) coefs[v, 1] else NA_real_
      out[[paste0(v, "_p")]]    <- if (v %in% rownames(coefs)) coefs[v, 4] else NA_real_
    }
  }
  
  out
}

ecm_fit_table <- rbind_fill(
  collect_ecm_stats(
    ecm_pathway1_break,
    "ecm_pathway1_break",
    "ect_pathway1_break_dd",
    extra_vars = c("d_log_imports_ind_real_gdp")
  ),
  collect_ecm_stats(
    ecm_pathway2_break,
    "ecm_pathway2_break",
    "ect_pathway2_break_dd",
    extra_vars = c("d_long_rate")
  ),
  collect_ecm_stats(
    ecm_optional_break,
    "ecm_optional_break",
    "ect_optional_break_dd",
    extra_vars = c("d_log_imports_ind_real_gdp", "d_long_rate")
  ),
  collect_ecm_stats(
    ecm_optional_breakFDI,
    "ecm_optional_breakFDI",
    "ect_optional_breakFDI_dd",
    extra_vars = c("d_log_imports_ind_real_gdp", "d_long_rate", "d_log_fdi_outward_gdp")
  )
)

make_pretty_table(ecm_fit_table, "ECM MODELS - FIT AND KEY COEFFICIENTS")

ECM MODELS - FIT AND KEY COEFFICIENTS

model	n	R2	Adj_R2	Resid_SE	F_stat	F_p	ECT_coef	ECT_p	pandemic_coef	pandemic_p	d_log_imports_ind_real_gdp_coef	d_log_imports_ind_real_gdp_p	d_long_rate_coef	d_long_rate_p	d_log_fdi_outward_gdp_coef	d_log_fdi_outward_gdp_p
ecm_pathway1_break	234	0.1507	0.1283	0.0065	6.7140	0.000	-0.1495	0.000	-0.0140	0.0341	-0.0081	0.1146	NA	NA	NA	NA
ecm_pathway2_break	234	0.0937	0.0698	0.0067	3.9134	0.001	-0.0838	0.001	-0.0156	0.0224	NA	NA	-7e-04	0.4669	NA	NA
ecm_optional_break	234	0.1558	0.1296	0.0065	5.9579	0.000	-0.1543	0.000	-0.0141	0.0332	-0.0064	0.2276	-6e-04	0.5000	NA	NA
ecm_optional_breakFDI	234	0.1734	0.1440	0.0064	5.9003	0.000	-0.1427	0.000	-0.0116	0.0824	-0.0075	0.1592	-5e-04	0.5865	0.0112	0.0301

# ## ECM Diagnostics Table
ecm_test_table <- rbind(
  collect_diag_tests(ecm_pathway1_break, "ecm_pathway1_break"),
  collect_diag_tests(ecm_pathway2_break, "ecm_pathway2_break"),
  collect_diag_tests(ecm_optional_break, "ecm_optional_break"),
  collect_diag_tests(ecm_optional_breakFDI, "ecm_optional_breakFDI")
)
rownames(ecm_test_table) <- NULL

make_pretty_table(ecm_test_table, "ECM MODEL DIAGNOSTICS")

ECM MODEL DIAGNOSTICS

model	BG_p	LjungBox_p	BP_p	WhiteFit_p	RESET2_p	RESET23_p
ecm_pathway1_break	0.7717	0.6634	0.7964	0.1626	0.7817	0.8326
ecm_pathway2_break	0.8738	0.6228	0.7956	0.9249	0.3372	0.4511
ecm_optional_break	0.8361	0.7127	0.8663	0.1594	0.9689	0.7007
ecm_optional_breakFDI	0.8769	0.5594	0.6033	0.0006	0.4928	0.6231

# ## VAR Overview and Diagnostics Tables
collect_var_info <- function(var_obj, model_name) {
  roots_vals <- roots(var_obj)
  data.frame(
    model = model_name,
    n = var_obj$obs,
    K = var_obj$K,
    p = var_obj$p,
    max_root = max(Mod(roots_vals)),
    min_root = min(Mod(roots_vals))
  )
}

collect_var_tests <- function(var_obj, model_name) {
  serial_p <- serial.test(var_obj, lags.pt = 12, type = "PT.asymptotic")$serial$p.value
  arch_p <- arch.test(var_obj, lags.multi = 4)$arch.mul$p.value
  normality_p <- normality.test(var_obj)$jb.mul$JB$p.value
  
  data.frame(
    model = model_name,
    Serial_p = serial_p,
    ARCH_p = arch_p,
    Normality_p = normality_p,
    max_root = max(Mod(roots(var_obj)))
  )
}

var_overview_table <- rbind(
  collect_var_info(var_fdi, "var_fdi"),
  collect_var_info(var_no_fdi, "var_no_fdi")
)
rownames(var_overview_table) <- NULL

var_diag_table <- rbind(
  collect_var_tests(var_fdi, "var_fdi"),
  collect_var_tests(var_no_fdi, "var_no_fdi")
)
rownames(var_diag_table) <- NULL

make_pretty_table(var_overview_table, "VAR MODELS - OVERVIEW")

VAR MODELS - OVERVIEW

model	n	K	p	max_root	min_root
var_fdi	232	2	2	0.3393	0.0553
var_no_fdi	232	3	2	0.4134	0.2952

make_pretty_table(var_diag_table, "VAR MODEL DIAGNOSTICS")

VAR MODEL DIAGNOSTICS

model	Serial_p	ARCH_p	Normality_p	max_root
var_fdi	0.1547	0.983	0	0.3393
var_no_fdi	0.0750	0.000	0	0.4134

# ## VAR Granger Tables
collect_granger_result <- function(var_obj, cause_var, model_name) {
  g <- causality(var_obj, cause = cause_var)
  
  data.frame(
    model = model_name,
    cause = cause_var,
    Granger_p = g$Granger$p.value,
    Instant_p = g$Instant$p.value
  )
}

var_fdi_granger_table <- rbind(
  collect_granger_result(var_fdi, "d_log_fdi_outward_gdp", "var_fdi"),
  collect_granger_result(var_fdi, "d_log_wage_gap", "var_fdi")
)
rownames(var_fdi_granger_table) <- NULL

var_no_fdi_granger_table <- rbind(
  collect_granger_result(var_no_fdi, "d_log_imports_ind_real_gdp", "var_no_fdi"),
  collect_granger_result(var_no_fdi, "d_long_rate", "var_no_fdi"),
  collect_granger_result(var_no_fdi, "d_log_wage_gap", "var_no_fdi")
)
rownames(var_no_fdi_granger_table) <- NULL

make_pretty_table(var_fdi_granger_table, "VAR WITH FDI - GRANGER CAUSALITY")

VAR WITH FDI - GRANGER CAUSALITY

model	cause	Granger_p	Instant_p
var_fdi	d_log_fdi_outward_gdp	0.3540	0.0066
var_fdi	d_log_wage_gap	0.0059	0.0066

make_pretty_table(var_no_fdi_granger_table, "VAR WITHOUT FDI - GRANGER CAUSALITY")

VAR WITHOUT FDI - GRANGER CAUSALITY

model	cause	Granger_p	Instant_p
var_no_fdi	d_log_imports_ind_real_gdp	0.7000	0.0021
var_no_fdi	d_long_rate	0.0388	0.0055
var_no_fdi	d_log_wage_gap	0.0005	0.3147

# ## IRF Tables
collect_irf_table <- function(irf_obj, model_name, impulse_name, response_name) {
  data.frame(
    model = model_name,
    impulse = impulse_name,
    response = response_name,
    horizon = seq_along(irf_obj$irf[[1]]),
    irf = as.numeric(irf_obj$irf[[1]]),
    lower = as.numeric(irf_obj$Lower[[1]]),
    upper = as.numeric(irf_obj$Upper[[1]])
  )
}

irf_table_fdi_on_wage <- collect_irf_table(
  irf_fdi_on_wage,
  "var_fdi",
  "d_log_fdi_outward_gdp",
  "d_log_wage_gap"
)

irf_table_wage_on_fdi <- collect_irf_table(
  irf_wage_on_fdi,
  "var_fdi",
  "d_log_wage_gap",
  "d_log_fdi_outward_gdp"
)

irf_table_imports_on_wage <- collect_irf_table(
  irf_imports_on_wage,
  "var_no_fdi",
  "d_log_imports_ind_real_gdp",
  "d_log_wage_gap"
)

irf_table_longrate_on_wage <- collect_irf_table(
  irf_longrate_on_wage,
  "var_no_fdi",
  "d_long_rate",
  "d_log_wage_gap"
)

make_pretty_table(irf_table_fdi_on_wage, "IRF TABLE - FDI SHOCK ON WAGE GAP")

IRF TABLE - FDI SHOCK ON WAGE GAP

model	impulse	response	horizon	irf	lower	upper
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	1	0e+00	0.0000	0e+00
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	2	-6e-04	-0.0014	2e-04
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	3	0e+00	-0.0010	8e-04
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	4	0e+00	-0.0002	3e-04
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	5	0e+00	-0.0001	1e-04
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	6	0e+00	0.0000	1e-04
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	7	0e+00	0.0000	0e+00
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	8	0e+00	0.0000	0e+00
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	9	0e+00	0.0000	0e+00
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	10	0e+00	0.0000	0e+00
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	11	0e+00	0.0000	0e+00
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	12	0e+00	0.0000	0e+00
var_fdi	d_log_fdi_outward_gdp	d_log_wage_gap	13	0e+00	0.0000	0e+00

make_pretty_table(irf_table_wage_on_fdi, "IRF TABLE - WAGE GAP SHOCK ON FDI")

IRF TABLE - WAGE GAP SHOCK ON FDI

model	impulse	response	horizon	irf	lower	upper
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	1	0.0151	0.0016	0.0284
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	2	0.0086	-0.0018	0.0187
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	3	0.0138	0.0028	0.0240
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	4	-0.0024	-0.0070	0.0003
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	5	0.0004	-0.0018	0.0037
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	6	-0.0004	-0.0015	0.0009
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	7	0.0001	-0.0001	0.0008
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	8	0.0000	-0.0004	0.0001
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	9	0.0000	-0.0001	0.0002
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	10	0.0000	-0.0001	0.0000
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	11	0.0000	0.0000	0.0000
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	12	0.0000	0.0000	0.0000
var_fdi	d_log_wage_gap	d_log_fdi_outward_gdp	13	0.0000	0.0000	0.0000

make_pretty_table(irf_table_imports_on_wage, "IRF TABLE - IMPORTS SHOCK ON WAGE GAP")

IRF TABLE - IMPORTS SHOCK ON WAGE GAP

model	impulse	response	horizon	irf	lower	upper
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	1	0e+00	0.0000	0e+00
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	2	-2e-04	-0.0010	6e-04
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	3	-7e-04	-0.0013	2e-04
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	4	-1e-04	-0.0003	1e-04
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	5	-1e-04	-0.0003	1e-04
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	6	0e+00	0.0000	1e-04
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	7	0e+00	0.0000	1e-04
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	8	0e+00	0.0000	0e+00
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	9	0e+00	0.0000	0e+00
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	10	0e+00	0.0000	0e+00
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	11	0e+00	0.0000	0e+00
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	12	0e+00	0.0000	0e+00
var_no_fdi	d_log_imports_ind_real_gdp	d_log_wage_gap	13	0e+00	0.0000	0e+00

make_pretty_table(irf_table_longrate_on_wage, "IRF TABLE - LONG RATE SHOCK ON WAGE GAP")

IRF TABLE - LONG RATE SHOCK ON WAGE GAP

model	impulse	response	horizon	irf	lower	upper
var_no_fdi	d_long_rate	d_log_wage_gap	1	0e+00	0.0000	0e+00
var_no_fdi	d_long_rate	d_log_wage_gap	2	-8e-04	-0.0017	1e-04
var_no_fdi	d_long_rate	d_log_wage_gap	3	-4e-04	-0.0010	3e-04
var_no_fdi	d_long_rate	d_log_wage_gap	4	-2e-04	-0.0003	1e-04
var_no_fdi	d_long_rate	d_log_wage_gap	5	0e+00	-0.0001	2e-04
var_no_fdi	d_long_rate	d_log_wage_gap	6	0e+00	0.0000	1e-04
var_no_fdi	d_long_rate	d_log_wage_gap	7	0e+00	0.0000	1e-04
var_no_fdi	d_long_rate	d_log_wage_gap	8	0e+00	0.0000	0e+00
var_no_fdi	d_long_rate	d_log_wage_gap	9	0e+00	0.0000	0e+00
var_no_fdi	d_long_rate	d_log_wage_gap	10	0e+00	0.0000	0e+00
var_no_fdi	d_long_rate	d_log_wage_gap	11	0e+00	0.0000	0e+00
var_no_fdi	d_long_rate	d_log_wage_gap	12	0e+00	0.0000	0e+00
var_no_fdi	d_long_rate	d_log_wage_gap	13	0e+00	0.0000	0e+00