IsTrue <- function(x) { !is.na(x) & x }
load("_data/LSCMWG_working_class.RData", verbose = TRUE)
## Loading objects:
##   data
##   codebook
##   categories
##   variables
##   df
##   new
df <- new
RunModel <- function(equation, data = df) {
  fit <- eval(bquote(lm(.(equation), data = data)))
  print(list(
    classical = summary(fit), ## classical SEs
    robust = lmtest::coeftest(fit, vcov = sandwich::vcovHC(fit, type = "HC1")) ## CRSEs;  Stata robust default
    # can also use: coeftest(fit, vcov = vcovCL, cluster = ~ country)
  ))
  invisible(fit)
}

Life expectancy regressions

## Column 1:
fit <- RunModel(life_exp_wpp_growth1995_2015 ~ life_exp_wpp_1995 + imr_wpp_1995 + asfr_adol_wpp_1995 + conflict_internal_cumulative1989_1995 + deaths_civilians_int_rate_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1996_2015)
## $classical
## 
## Call:
## lm(formula = life_exp_wpp_growth1995_2015 ~ life_exp_wpp_1995 + 
##     imr_wpp_1995 + asfr_adol_wpp_1995 + conflict_internal_cumulative1989_1995 + 
##     deaths_civilians_int_rate_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + 
##     v2x_polyarchy_cumulative1996_2015, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -17.6774  -1.1287   0.2922   1.6213  16.8870 
## 
## Coefficients:
##                                                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                                    2.283e+01  7.850e+00   2.909 0.004191 ** 
## life_exp_wpp_1995                             -3.023e-01  1.025e-01  -2.949 0.003707 ** 
## imr_wpp_1995                                  -6.427e-02  2.615e-02  -2.458 0.015141 *  
## asfr_adol_wpp_1995                             5.056e-02  8.917e-03   5.670 7.25e-08 ***
## conflict_internal_cumulative1989_1995          6.015e-02  3.399e-02   1.770 0.078817 .  
## deaths_civilians_int_rate_cumulative1996_2015 -1.930e-01  3.088e-01  -0.625 0.532826    
## pc_rgdpe_avg_growth1995_2015                   6.300e-05  2.935e-05   2.147 0.033443 *  
## v2x_polyarchy_cumulative1996_2015              4.802e+00  1.418e+00   3.388 0.000904 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.574 on 148 degrees of freedom
##   (45 observations deleted due to missingness)
## Multiple R-squared:  0.4917, Adjusted R-squared:  0.4676 
## F-statistic: 20.45 on 7 and 148 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                                  Estimate  Std. Error t value Pr(>|t|)   
## (Intercept)                                    2.2831e+01  1.2595e+01  1.8127 0.071909 . 
## life_exp_wpp_1995                             -3.0228e-01  1.6772e-01 -1.8023 0.073530 . 
## imr_wpp_1995                                  -6.4271e-02  2.5243e-02 -2.5461 0.011917 * 
## asfr_adol_wpp_1995                             5.0559e-02  2.0100e-02  2.5153 0.012960 * 
## conflict_internal_cumulative1989_1995          6.0149e-02  3.5341e-02  1.7020 0.090864 . 
## deaths_civilians_int_rate_cumulative1996_2015 -1.9302e-01  9.7286e-02 -1.9840 0.049100 * 
## pc_rgdpe_avg_growth1995_2015                   6.2996e-05  2.3245e-05  2.7101 0.007522 **
## v2x_polyarchy_cumulative1996_2015              4.8021e+00  1.5203e+00  3.1587 0.001922 **
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
df$samplelife <- ifelse(df$country %in% 
                        na.omit(get_all_vars(fit$call$formula, data = df, country = country))[, "country"], 1, 0)
# auxilliary checks
# RunModel(life_exp_wpp_growth1995_2015 ~ life_exp_wpp_1995 + imr_wpp_1995 + asfr_adol_wpp_1995 + deaths_civilians_osv_rate_1995 + deaths_civilians_int_rate_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1996_2015)

## Column 2: (no lag DV)
RunModel(life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + conflict_internal_cumulative1989_1995 + deaths_civilians_int_rate_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
## $classical
## 
## Call:
## lm(formula = life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + 
##     conflict_internal_cumulative1989_1995 + deaths_civilians_int_rate_cumulative1996_2015 + 
##     pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995, 
##     data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -16.0744  -1.4512   0.2744   1.6872  19.1672 
## 
## Coefficients:
##                                                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                                   -1.363e-01  1.232e+00  -0.111 0.912026    
## imr_wpp_1995                                  -1.345e-01  1.305e-02 -10.311  < 2e-16 ***
## asfr_adol_wpp_1995                             4.738e-02  8.995e-03   5.267 4.76e-07 ***
## conflict_internal_cumulative1989_1995          6.478e-02  3.472e-02   1.866 0.064023 .  
## deaths_civilians_int_rate_cumulative1996_2015 -2.317e-01  3.121e-01  -0.742 0.459068    
## pc_rgdpe_avg_growth1995_2015                   5.446e-05  2.957e-05   1.842 0.067477 .  
## v2x_polyarchy_cumulative1991_1995              4.736e+00  1.371e+00   3.455 0.000718 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.632 on 149 degrees of freedom
##   (45 observations deleted due to missingness)
## Multiple R-squared:  0.4715, Adjusted R-squared:  0.4502 
## F-statistic: 22.16 on 6 and 149 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                                  Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                                   -1.3630e-01  1.4032e+00 -0.0971 0.9227476    
## imr_wpp_1995                                  -1.3453e-01  3.6797e-02 -3.6560 0.0003545 ***
## asfr_adol_wpp_1995                             4.7381e-02  2.1088e-02  2.2469 0.0261171 *  
## conflict_internal_cumulative1989_1995          6.4785e-02  3.4306e-02  1.8884 0.0609101 .  
## deaths_civilians_int_rate_cumulative1996_2015 -2.3171e-01  9.6238e-02 -2.4077 0.0172777 *  
## pc_rgdpe_avg_growth1995_2015                   5.4462e-05  2.3665e-05  2.3014 0.0227561 *  
## v2x_polyarchy_cumulative1991_1995              4.7361e+00  1.6544e+00  2.8626 0.0048068 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# auxilliary checks
# RunModel(life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + deaths_civilians_osv_rate_1995 + deaths_civilians_int_rate_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
# RunModel(life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + deaths_civilians_int_rate_1995 + deaths_civilians_int_rate_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
# RunModel(life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + conflict_internal_cumulative1989_1995 + deaths_civilians_osv_rate_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
# RunModel(life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + deaths_civilians_osv_rate_1995 + deaths_civilians_osv_rate_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
# RunModel(life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + deaths_civilians_int_rate_1995 + deaths_civilians_osv_rate_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
# RunModel(life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + conflict_internal_cumulative1989_1995 + conflict_internal_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
# RunModel(life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + deaths_civilians_osv_rate_1995 + conflict_internal_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
# RunModel(life_exp_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + deaths_civilians_int_rate_1995 + conflict_internal_cumulative1996_2015 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)

## Column 3:(prediction)
RunModel(life_exp_wpp_growth1995_2015 ~ life_exp_wpp_1995 + imr_wpp_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1991_1995 + deaths_civilians_osv_rate_1995)
## $classical
## 
## Call:
## lm(formula = life_exp_wpp_growth1995_2015 ~ life_exp_wpp_1995 + 
##     imr_wpp_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1991_1995 + 
##     deaths_civilians_osv_rate_1995, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -17.4799  -1.4390   0.1647   1.7759  16.1383 
## 
## Coefficients:
##                                    Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                       21.098206   7.490453   2.817 0.005468 ** 
## life_exp_wpp_1995                 -0.259428   0.097265  -2.667 0.008439 ** 
## imr_wpp_1995                      -0.060609   0.024975  -2.427 0.016354 *  
## asfr_adol_wpp_1995                 0.044871   0.008668   5.177 6.73e-07 ***
## v2x_polyarchy_cumulative1991_1995  4.218479   1.230965   3.427 0.000777 ***
## deaths_civilians_osv_rate_1995     0.031814   0.014156   2.247 0.025995 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.525 on 159 degrees of freedom
##   (36 observations deleted due to missingness)
## Multiple R-squared:  0.483,  Adjusted R-squared:  0.4667 
## F-statistic:  29.7 on 5 and 159 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                    Estimate Std. Error t value Pr(>|t|)   
## (Intercept)                       21.098206  11.129314  1.8957 0.059810 . 
## life_exp_wpp_1995                 -0.259428   0.147355 -1.7606 0.080236 . 
## imr_wpp_1995                      -0.060609   0.024931 -2.4311 0.016166 * 
## asfr_adol_wpp_1995                 0.044871   0.017417  2.5764 0.010894 * 
## v2x_polyarchy_cumulative1991_1995  4.218479   1.407135  2.9979 0.003155 **
## deaths_civilians_osv_rate_1995     0.031814   0.018834  1.6891 0.093154 . 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# auxilliary checks
# RunModel(life_exp_wpp_growth1995_2015 ~ life_exp_wpp_1995 + imr_wpp_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1991_1995 + deaths_civilians_int_rate_1995)
# RunModel(life_exp_wpp_growth1995_2015 ~ life_exp_wpp_1995 + imr_wpp_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1991_1995 + conflict_internal_cumulative1989_1995)

## Column 4: performance version
RunModel(perf_life_exp_wpp_growth1995_2015 ~ perf_imr_wpp_1995 + perf_asfr_adol_wpp_1995 + conflict_internal_cumulative1989_1995 + pc_rgdpe_avg_1995 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
## $classical
## 
## Call:
## lm(formula = perf_life_exp_wpp_growth1995_2015 ~ perf_imr_wpp_1995 + 
##     perf_asfr_adol_wpp_1995 + conflict_internal_cumulative1989_1995 + 
##     pc_rgdpe_avg_1995 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995, 
##     data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -16.4210  -1.4487   0.3323   1.5494   9.4071 
## 
## Coefficients:
##                                         Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                           -2.306e+00  6.717e-01  -3.434 0.000772 ***
## perf_imr_wpp_1995                     -4.016e-02  1.432e-02  -2.805 0.005701 ** 
## perf_asfr_adol_wpp_1995                4.471e-02  8.443e-03   5.295 4.18e-07 ***
## conflict_internal_cumulative1989_1995  7.571e-02  3.182e-02   2.379 0.018604 *  
## pc_rgdpe_avg_1995                     -9.572e-05  4.779e-05  -2.003 0.047017 *  
## pc_rgdpe_avg_growth1995_2015           5.920e-05  3.026e-05   1.957 0.052266 .  
## v2x_polyarchy_cumulative1991_1995      4.742e+00  1.393e+00   3.404 0.000854 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 3.317 on 149 degrees of freedom
##   (45 observations deleted due to missingness)
## Multiple R-squared:  0.2138, Adjusted R-squared:  0.1821 
## F-statistic: 6.753 on 6 and 149 DF,  p-value: 2.4e-06
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                          Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                           -2.3063e+00  9.0631e-01 -2.5447 0.0119557 *  
## perf_imr_wpp_1995                     -4.0163e-02  2.3517e-02 -1.7078 0.0897525 .  
## perf_asfr_adol_wpp_1995                4.4710e-02  1.2603e-02  3.5475 0.0005204 ***
## conflict_internal_cumulative1989_1995  7.5710e-02  3.3879e-02  2.2347 0.0269220 *  
## pc_rgdpe_avg_1995                     -9.5721e-05  4.1330e-05 -2.3160 0.0219197 *  
## pc_rgdpe_avg_growth1995_2015           5.9202e-05  2.3780e-05  2.4896 0.0138889 *  
## v2x_polyarchy_cumulative1991_1995      4.7417e+00  1.5541e+00  3.0511 0.0026997 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# auxilliary checks
# RunModel(perf_life_exp_wpp_growth1995_2015 ~ perf_imr_wpp_1995 + perf_asfr_adol_wpp_1995 + deaths_civilians_osv_rate_1995 + pc_rgdpe_avg_1995 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)

## no health variables (not reported)
RunModel(life_exp_wpp_growth1995_2015 ~ mys_ratio_hdr_1995 + deaths_civilians_int_rate_cumulative1996_2015)
## $classical
## 
## Call:
## lm(formula = life_exp_wpp_growth1995_2015 ~ mys_ratio_hdr_1995 + 
##     deaths_civilians_int_rate_cumulative1996_2015, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -16.690  -1.350  -0.124   1.295  36.538 
## 
## Coefficients:
##                                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                                    12.6545     1.3994   9.043 1.13e-15 ***
## mys_ratio_hdr_1995                             -8.5350     1.6707  -5.109 1.04e-06 ***
## deaths_civilians_int_rate_cumulative1996_2015  -0.6014     0.3833  -1.569    0.119    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.548 on 140 degrees of freedom
##   (58 observations deleted due to missingness)
## Multiple R-squared:  0.1621, Adjusted R-squared:  0.1501 
## F-statistic: 13.54 on 2 and 140 DF,  p-value: 4.203e-06
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                               Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)                                   12.65452    1.63756  7.7276 1.920e-12 ***
## mys_ratio_hdr_1995                            -8.53503    1.73123 -4.9301 2.292e-06 ***
## deaths_civilians_int_rate_cumulative1996_2015 -0.60141    0.12247 -4.9106 2.495e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
cor(df[df$samplelife == 1, c("life_exp_wpp_1995", "imr_wpp_1995")])
##                   life_exp_wpp_1995 imr_wpp_1995
## life_exp_wpp_1995         1.0000000    0.9615578
## imr_wpp_1995              0.9615578    1.0000000
cor(df[df$samplelife == 1, c("v2x_polyarchy_cumulative1996_2015", "v2x_polyarchy_cumulative1991_1995")])
##                                   v2x_polyarchy_cumulative1996_2015 v2x_polyarchy_cumulative1991_1995
## v2x_polyarchy_cumulative1996_2015                         1.0000000                         0.9027603
## v2x_polyarchy_cumulative1991_1995                         0.9027603                         1.0000000
cor(df[df$samplelife == 1, c("perf_life_exp_wpp_growth1995_2015", "life_exp_wpp_1995")])
##                                   perf_life_exp_wpp_growth1995_2015 life_exp_wpp_1995
## perf_life_exp_wpp_growth1995_2015                        1.00000000        0.07597425
## life_exp_wpp_1995                                        0.07597425        1.00000000

IMR regressions

## base model
fit <- RunModel(imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + pc_rgdpe_avg_1995 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
## $classical
## 
## Call:
## lm(formula = imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + 
##     pc_rgdpe_avg_1995 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995, 
##     data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -32.444  -3.100   0.671   4.527  40.262 
## 
## Coefficients:
##                                     Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                       -1.300e+00  3.201e+00  -0.406   0.6852    
## imr_wpp_1995                      -6.283e-01  3.505e-02 -17.927  < 2e-16 ***
## asfr_adol_wpp_1995                 1.234e-01  2.497e-02   4.941 2.05e-06 ***
## pc_rgdpe_avg_1995                 -2.361e-04  1.491e-04  -1.584   0.1153    
## pc_rgdpe_avg_growth1995_2015       1.367e-04  8.955e-05   1.526   0.1291    
## v2x_polyarchy_cumulative1991_1995  8.966e+00  4.089e+00   2.193   0.0299 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.756 on 150 degrees of freedom
##   (45 observations deleted due to missingness)
## Multiple R-squared:  0.8237, Adjusted R-squared:  0.8178 
## F-statistic: 140.2 on 5 and 150 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                      Estimate  Std. Error t value Pr(>|t|)    
## (Intercept)                       -1.3005e+00  3.1101e+00 -0.4181 0.676439    
## imr_wpp_1995                      -6.2831e-01  7.9151e-02 -7.9381 4.44e-13 ***
## asfr_adol_wpp_1995                 1.2340e-01  4.6823e-02  2.6356 0.009283 ** 
## pc_rgdpe_avg_1995                 -2.3611e-04  8.9850e-05 -2.6278 0.009488 ** 
## pc_rgdpe_avg_growth1995_2015       1.3666e-04  6.1377e-05  2.2265 0.027469 *  
## v2x_polyarchy_cumulative1991_1995  8.9656e+00  3.8235e+00  2.3448 0.020345 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
car::vif(fit)
##                      imr_wpp_1995                asfr_adol_wpp_1995                 pc_rgdpe_avg_1995      pc_rgdpe_avg_growth1995_2015 v2x_polyarchy_cumulative1991_1995 
##                          3.421349                          2.826401                          3.050122                          1.703255                          1.962740
RunModel(imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995)
## $classical
## 
## Call:
## lm(formula = imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + 
##     pc_rgdpe_avg_growth1995_2015 + v2x_polyarchy_cumulative1991_1995, 
##     data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -31.940  -3.829   0.631   5.039  40.076 
## 
## Coefficients:
##                                     Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                       -2.345e+00  3.148e+00  -0.745    0.458    
## imr_wpp_1995                      -6.343e-01  3.502e-02 -18.113  < 2e-16 ***
## asfr_adol_wpp_1995                 1.134e-01  2.428e-02   4.670  6.6e-06 ***
## pc_rgdpe_avg_growth1995_2015       6.844e-05  7.891e-05   0.867    0.387    
## v2x_polyarchy_cumulative1991_1995  5.793e+00  3.583e+00   1.617    0.108    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.804 on 151 degrees of freedom
##   (45 observations deleted due to missingness)
## Multiple R-squared:  0.8208, Adjusted R-squared:  0.816 
## F-statistic: 172.9 on 4 and 151 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                      Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                       -2.3447e+00  3.0532e+00 -0.7680   0.44371    
## imr_wpp_1995                      -6.3430e-01  7.8520e-02 -8.0782 1.941e-13 ***
## asfr_adol_wpp_1995                 1.1341e-01  4.6422e-02  2.4429   0.01572 *  
## pc_rgdpe_avg_growth1995_2015       6.8444e-05  4.9415e-05  1.3851   0.16807    
## v2x_polyarchy_cumulative1991_1995  5.7926e+00  3.4269e+00  1.6903   0.09303 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RunModel(imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + pc_rgdpe_avg_1995 + v2x_polyarchy_cumulative1991_1995)
## $classical
## 
## Call:
## lm(formula = imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + 
##     pc_rgdpe_avg_1995 + v2x_polyarchy_cumulative1991_1995, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -32.902  -2.869   0.770   4.638  40.818 
## 
## Coefficients:
##                                     Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                        0.3767356  3.0199654   0.125   0.9009    
## imr_wpp_1995                      -0.6192508  0.0346939 -17.849  < 2e-16 ***
## asfr_adol_wpp_1995                 0.1227485  0.0250792   4.894 2.51e-06 ***
## pc_rgdpe_avg_1995                 -0.0001267  0.0001313  -0.965   0.3359    
## v2x_polyarchy_cumulative1991_1995  6.7246256  3.8330061   1.754   0.0814 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.798 on 151 degrees of freedom
##   (45 observations deleted due to missingness)
## Multiple R-squared:  0.821,  Adjusted R-squared:  0.8162 
## F-statistic: 173.1 on 4 and 151 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                      Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                        3.7674e-01  2.8316e+00  0.1330   0.89433    
## imr_wpp_1995                      -6.1925e-01  7.8932e-02 -7.8453 7.306e-13 ***
## asfr_adol_wpp_1995                 1.2275e-01  4.7162e-02  2.6027   0.01017 *  
## pc_rgdpe_avg_1995                 -1.2672e-04  8.2751e-05 -1.5313   0.12778    
## v2x_polyarchy_cumulative1991_1995  6.7246e+00  3.4972e+00  1.9228   0.05638 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
cor(df[df$samplelife == 1, c("pc_rgdpe_avg_1995", "pc_rgdpe_avg_growth1995_2015")])
##                              pc_rgdpe_avg_1995 pc_rgdpe_avg_growth1995_2015
## pc_rgdpe_avg_1995                    1.0000000                    0.5629647
## pc_rgdpe_avg_growth1995_2015         0.5629647                    1.0000000
## Prediction model
RunModel(imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995)
## $classical
## 
## Call:
## lm(formula = imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995, 
##     data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -32.523  -2.572   0.160   4.370  46.318 
## 
## Coefficients:
##                    Estimate Std. Error t value Pr(>|t|)    
## (Intercept)         1.82430    1.28442   1.420    0.157    
## imr_wpp_1995       -0.58266    0.02761 -21.104  < 2e-16 ***
## asfr_adol_wpp_1995  0.09618    0.02192   4.388 1.96e-05 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.568 on 177 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  0.8172, Adjusted R-squared:  0.8151 
## F-statistic: 395.6 on 2 and 177 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                     Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)         1.824303   0.923965  1.9744   0.04989 *  
## imr_wpp_1995       -0.582661   0.067295 -8.6583 2.896e-15 ***
## asfr_adol_wpp_1995  0.096178   0.044498  2.1614   0.03201 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RunModel(imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995, data = df[df$samplelife == 1, ])
## $classical
## 
## Call:
## lm(formula = imr_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995, 
##     data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -33.088  -2.691   0.678   4.585  42.255 
## 
## Coefficients:
##                    Estimate Std. Error t value Pr(>|t|)    
## (Intercept)         2.50881    1.40996   1.779   0.0772 .  
## imr_wpp_1995       -0.60508    0.03077 -19.665  < 2e-16 ***
## asfr_adol_wpp_1995  0.11356    0.02412   4.708 5.56e-06 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 9.836 on 153 degrees of freedom
## Multiple R-squared:  0.8172, Adjusted R-squared:  0.8148 
## F-statistic:   342 on 2 and 153 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                     Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)         2.508809   0.974347  2.5749   0.01098 *  
## imr_wpp_1995       -0.605078   0.071949 -8.4098 2.684e-14 ***
## asfr_adol_wpp_1995  0.113563   0.048050  2.3634   0.01936 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

MYS regressions

## Column 1: MYS base
fit <- RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + deaths_civilians_osv_rate_1995 + deaths_civilians_osv_rate_cumulative1996_2015)
## $classical
## 
## Call:
## lm(formula = mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + 
##     asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + 
##     deaths_civilians_osv_rate_1995 + deaths_civilians_osv_rate_cumulative1996_2015, 
##     data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.31990 -0.03001 -0.00116  0.03829  0.22606 
## 
## Coefficients:
##                                                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                                    0.4703940  0.0369701  12.724  < 2e-16 ***
## mys_ratio_hdr_1995                            -0.3679736  0.0366792 -10.032  < 2e-16 ***
## asfr_adol_wpp_1995                             0.0005884  0.0001570   3.748 0.000268 ***
## v2x_polyarchy_cumulative1996_2015             -0.0619265  0.0289468  -2.139 0.034293 *  
## deaths_civilians_osv_rate_1995                 0.0005321  0.0007670   0.694 0.489092    
## deaths_civilians_osv_rate_cumulative1996_2015 -0.0120285  0.0075595  -1.591 0.114016    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.07593 on 129 degrees of freedom
##   (66 observations deleted due to missingness)
## Multiple R-squared:  0.5207, Adjusted R-squared:  0.5021 
## F-statistic: 28.03 on 5 and 129 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                                  Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                                    0.47039395  0.05822775  8.0785 4.058e-13 ***
## mys_ratio_hdr_1995                            -0.36797358  0.05698236 -6.4577 1.976e-09 ***
## asfr_adol_wpp_1995                             0.00058841  0.00025587  2.2996  0.023076 *  
## v2x_polyarchy_cumulative1996_2015             -0.06192649  0.02998664 -2.0651  0.040913 *  
## deaths_civilians_osv_rate_1995                 0.00053207  0.00030452  1.7472  0.082981 .  
## deaths_civilians_osv_rate_cumulative1996_2015 -0.01202851  0.00403426 -2.9816  0.003429 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
df$samplemys <- ifelse(df$country %in% na.omit(get_all_vars(fit$call$formula, data = df, country = country))[, "country"], 1, 0)
## (checks)
RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015)
## $classical
## 
## Call:
## lm(formula = mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + 
##     asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.31620 -0.03485 -0.00049  0.03812  0.23190 
## 
## Coefficients:
##                                     Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                        0.4540970  0.0356750  12.729  < 2e-16 ***
## mys_ratio_hdr_1995                -0.3521799  0.0353851  -9.953  < 2e-16 ***
## asfr_adol_wpp_1995                 0.0006143  0.0001567   3.922 0.000141 ***
## v2x_polyarchy_cumulative1996_2015 -0.0579819  0.0289274  -2.004 0.047089 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.07616 on 131 degrees of freedom
##   (66 observations deleted due to missingness)
## Multiple R-squared:  0.5104, Adjusted R-squared:  0.4992 
## F-statistic: 45.52 on 3 and 131 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                      Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                        0.45409698  0.05671760  8.0063 5.586e-13 ***
## mys_ratio_hdr_1995                -0.35217995  0.05547580 -6.3484 3.285e-09 ***
## asfr_adol_wpp_1995                 0.00061434  0.00025367  2.4218   0.01681 *  
## v2x_polyarchy_cumulative1996_2015 -0.05798192  0.02997314 -1.9345   0.05521 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + deaths_civilians_osv_rate_cumulative1996_2015)
## $classical
## 
## Call:
## lm(formula = mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + 
##     asfr_adol_wpp_1995 + deaths_civilians_osv_rate_cumulative1996_2015, 
##     data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.33205 -0.03716 -0.00080  0.03107  0.25119 
## 
## Coefficients:
##                                                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                                    0.4430044  0.0355191  12.472  < 2e-16 ***
## mys_ratio_hdr_1995                            -0.3853944  0.0348511 -11.058  < 2e-16 ***
## asfr_adol_wpp_1995                             0.0005098  0.0001531   3.329  0.00112 ** 
## deaths_civilians_osv_rate_cumulative1996_2015 -0.0077667  0.0056477  -1.375  0.17130    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.07653 on 138 degrees of freedom
##   (59 observations deleted due to missingness)
## Multiple R-squared:  0.4958, Adjusted R-squared:  0.4849 
## F-statistic: 45.24 on 3 and 138 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                                  Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                                    0.44300440  0.05574523  7.9469 6.087e-13 ***
## mys_ratio_hdr_1995                            -0.38539437  0.05222073 -7.3801 1.346e-11 ***
## asfr_adol_wpp_1995                             0.00050976  0.00024098  2.1154   0.03619 *  
## deaths_civilians_osv_rate_cumulative1996_2015 -0.00776666  0.00330679 -2.3487   0.02026 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + deaths_civilians_osv_rate_1995)
## $classical
## 
## Call:
## lm(formula = mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + 
##     asfr_adol_wpp_1995 + deaths_civilians_osv_rate_1995, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.32901 -0.03781 -0.00205  0.02889  0.25218 
## 
## Coefficients:
##                                  Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                     0.4326449  0.0348616  12.410  < 2e-16 ***
## mys_ratio_hdr_1995             -0.3735969  0.0339026 -11.020  < 2e-16 ***
## asfr_adol_wpp_1995              0.0005287  0.0001533   3.448  0.00075 ***
## deaths_civilians_osv_rate_1995 -0.0002817  0.0005778  -0.487  0.62670    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.07699 on 138 degrees of freedom
##   (59 observations deleted due to missingness)
## Multiple R-squared:  0.4898, Adjusted R-squared:  0.4787 
## F-statistic: 44.16 on 3 and 138 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                   Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                     0.43264491  0.05528980  7.8250 1.193e-12 ***
## mys_ratio_hdr_1995             -0.37359686  0.05167064 -7.2304 3.004e-11 ***
## asfr_adol_wpp_1995              0.00052871  0.00024076  2.1960   0.02976 *  
## deaths_civilians_osv_rate_1995 -0.00028167  0.00021614 -1.3032   0.19469    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + deaths_civilians_osv_rate_cumulative1996_2015)
## $classical
## 
## Call:
## lm(formula = mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + 
##     asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + 
##     deaths_civilians_osv_rate_cumulative1996_2015, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.31986 -0.02988 -0.00078  0.03859  0.22660 
## 
## Coefficients:
##                                                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                                    0.4691358  0.0368518  12.730  < 2e-16 ***
## mys_ratio_hdr_1995                            -0.3673320  0.0365943 -10.038  < 2e-16 ***
## asfr_adol_wpp_1995                             0.0005910  0.0001566   3.773 0.000244 ***
## v2x_polyarchy_cumulative1996_2015             -0.0608017  0.0288437  -2.108 0.036953 *  
## deaths_civilians_osv_rate_cumulative1996_2015 -0.0085193  0.0056064  -1.520 0.131052    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.07578 on 130 degrees of freedom
##   (66 observations deleted due to missingness)
## Multiple R-squared:  0.5189, Adjusted R-squared:  0.5041 
## F-statistic: 35.06 on 4 and 130 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                                  Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                                    0.46913575  0.05809470  8.0754 3.975e-13 ***
## mys_ratio_hdr_1995                            -0.36733204  0.05684898 -6.4615 1.902e-09 ***
## asfr_adol_wpp_1995                             0.00059103  0.00025452  2.3221   0.02178 *  
## v2x_polyarchy_cumulative1996_2015             -0.06080170  0.02975832 -2.0432   0.04306 *  
## deaths_civilians_osv_rate_cumulative1996_2015 -0.00851929  0.00343039 -2.4835   0.01428 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
cor(df[df$samplemys == 1, c("deaths_civilians_osv_rate_1995", "deaths_civilians_osv_rate_cumulative1996_2015")])
##                                               deaths_civilians_osv_rate_1995 deaths_civilians_osv_rate_cumulative1996_2015
## deaths_civilians_osv_rate_1995                                     1.0000000                                     0.6895246
## deaths_civilians_osv_rate_cumulative1996_2015                      0.6895246                                     1.0000000
# auxilliary checks
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + deaths_civilians_int_rate_1995 + deaths_civilians_osv_rate_cumulative1996_2015)
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + conflict_internal_cumulative1989_1995 + deaths_civilians_osv_rate_cumulative1996_2015)
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + deaths_civilians_osv_rate_1995 + conflict_internal_cumulative1996_2015)
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + deaths_civilians_osv_rate_1995 + deaths_civilians_int_rate_cumulative1996_2015)
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + deaths_civilians_int_rate_1995 + deaths_civilians_osv_rate_cumulative1996_2015)
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + deaths_civilians_int_rate_1995 + conflict_internal_cumulative1996_2015)
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + conflict_internal_cumulative1989_1995 + conflict_internal_cumulative1996_2015)
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1996_2015 + conflict_internal_cumulative1989_1995 + deaths_civilians_int_rate_cumulative1996_2015)

## Column 2 MYS predict
RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1991_1995 + deaths_civilians_osv_rate_1995)
## $classical
## 
## Call:
## lm(formula = mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + 
##     asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1991_1995 + 
##     deaths_civilians_osv_rate_1995, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.31906 -0.03509 -0.00162  0.03749  0.24241 
## 
## Coefficients:
##                                     Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                        0.4522830  0.0357438  12.653  < 2e-16 ***
## mys_ratio_hdr_1995                -0.3535040  0.0363858  -9.715  < 2e-16 ***
## asfr_adol_wpp_1995                 0.0006197  0.0001583   3.916 0.000145 ***
## v2x_polyarchy_cumulative1991_1995 -0.0558200  0.0285711  -1.954 0.052882 .  
## deaths_civilians_osv_rate_1995    -0.0003653  0.0005752  -0.635 0.526509    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.07643 on 130 degrees of freedom
##   (66 observations deleted due to missingness)
## Multiple R-squared:  0.5106, Adjusted R-squared:  0.4956 
## F-statistic: 33.91 on 4 and 130 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                      Estimate  Std. Error t value  Pr(>|t|)    
## (Intercept)                        0.45228297  0.05762723  7.8484 1.364e-12 ***
## mys_ratio_hdr_1995                -0.35350403  0.05630502 -6.2784 4.726e-09 ***
## asfr_adol_wpp_1995                 0.00061975  0.00025583  2.4225   0.01679 *  
## v2x_polyarchy_cumulative1991_1995 -0.05582001  0.03069189 -1.8187   0.07126 .  
## deaths_civilians_osv_rate_1995    -0.00036530  0.00020619 -1.7716   0.07880 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
# auxilliary checks
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1991_1995 + deaths_civilians_int_rate_1995)
# RunModel(mys_ratio_hdr_growth1995_2015 ~ mys_ratio_hdr_1995 + asfr_adol_wpp_1995 + v2x_polyarchy_cumulative1991_1995 + conflict_internal_cumulative1989_1995)

ASFR regressions

## column 3 ASFR base
RunModel(asfr_adol_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + v2x_partip_cumulative1996_2015)
## $classical
## 
## Call:
## lm(formula = asfr_adol_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + 
##     v2x_partip_cumulative1996_2015, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -34.911  -7.445  -1.282   7.761  61.765 
## 
## Coefficients:
##                                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                     16.40420    4.56065   3.597 0.000428 ***
## imr_wpp_1995                     0.13589    0.04772   2.848 0.004976 ** 
## asfr_adol_wpp_1995              -0.26485    0.03617  -7.322  1.1e-11 ***
## v2x_partip_cumulative1996_2015 -16.37478    7.31741  -2.238 0.026607 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 15.08 on 161 degrees of freedom
##   (36 observations deleted due to missingness)
## Multiple R-squared:  0.3436, Adjusted R-squared:  0.3314 
## F-statistic: 28.09 on 3 and 161 DF,  p-value: 1.154e-14
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                  Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)                     16.404200   4.523728  3.6263 0.0003855 ***
## imr_wpp_1995                     0.135888   0.056584  2.4015 0.0174663 *  
## asfr_adol_wpp_1995              -0.264851   0.040582 -6.5263  8.36e-10 ***
## v2x_partip_cumulative1996_2015 -16.374776   7.167537 -2.2846 0.0236437 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Column 4 ASFR predict
RunModel(asfr_adol_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + v2x_partip_cumulative1991_1995)
## $classical
## 
## Call:
## lm(formula = asfr_adol_wpp_growth1995_2015 ~ imr_wpp_1995 + asfr_adol_wpp_1995 + 
##     v2x_partip_cumulative1991_1995, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -38.678  -7.391  -1.063   7.520  59.743 
## 
## Coefficients:
##                                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                     16.12952    4.38460   3.679 0.000319 ***
## imr_wpp_1995                     0.15124    0.05002   3.023 0.002909 ** 
## asfr_adol_wpp_1995              -0.27077    0.03644  -7.431 5.98e-12 ***
## v2x_partip_cumulative1991_1995 -16.91978    7.41271  -2.283 0.023766 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 15.07 on 161 degrees of freedom
##   (36 observations deleted due to missingness)
## Multiple R-squared:  0.3444, Adjusted R-squared:  0.3322 
## F-statistic: 28.19 on 3 and 161 DF,  p-value: 1.047e-14
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                  Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)                     16.129525   5.026114  3.2091  0.001607 ** 
## imr_wpp_1995                     0.151241   0.060255  2.5100  0.013061 *  
## asfr_adol_wpp_1995              -0.270770   0.040426 -6.6979 3.358e-10 ***
## v2x_partip_cumulative1991_1995 -16.919783   8.630271 -1.9605  0.051661 .  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Conflict regressions

## column 1
RunModel(conflict_internal_cumulative1996_2015 ~ life_exp_wpp_1995 + conflict_internal_cumulative1989_1995)
## $classical
## 
## Call:
## lm(formula = conflict_internal_cumulative1996_2015 ~ life_exp_wpp_1995 + 
##     conflict_internal_cumulative1989_1995, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -14.1947  -1.2910  -0.4390   0.2839  17.2139 
## 
## Coefficients:
##                                       Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                            7.71326    2.05804   3.748 0.000241 ***
## life_exp_wpp_1995                     -0.10295    0.03066  -3.358 0.000961 ***
## conflict_internal_cumulative1989_1995  0.40713    0.03702  10.997  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.046 on 177 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  0.471,  Adjusted R-squared:  0.465 
## F-statistic: 78.79 on 2 and 177 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                        Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)                            7.713265   1.938085  3.9798 0.0001005 ***
## life_exp_wpp_1995                     -0.102954   0.028389 -3.6266 0.0003754 ***
## conflict_internal_cumulative1989_1995  0.407134   0.057764  7.0483 3.896e-11 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## column 2
RunModel(conflict_internal_cumulative1996_2015 ~ imr_wpp_1995 + conflict_internal_cumulative1989_1995)
## $classical
## 
## Call:
## lm(formula = conflict_internal_cumulative1996_2015 ~ imr_wpp_1995 + 
##     conflict_internal_cumulative1989_1995, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -14.1504  -1.2528  -0.2816   0.1024  17.0852 
## 
## Coefficients:
##                                        Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                           -0.247889   0.477170  -0.519 0.604063    
## imr_wpp_1995                          -0.026544   0.007672  -3.460 0.000677 ***
## conflict_internal_cumulative1989_1995  0.404067   0.037110  10.888  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.038 on 177 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  0.4729, Adjusted R-squared:  0.467 
## F-statistic: 79.41 on 2 and 177 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                         Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)                           -0.2478888  0.3651575 -0.6789 0.4981168    
## imr_wpp_1995                          -0.0265442  0.0073516 -3.6107 0.0003975 ***
## conflict_internal_cumulative1989_1995  0.4040668  0.0580755  6.9576 6.467e-11 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## column 3
RunModel(conflict_internal_cumulative1996_2015 ~ mys_ratio_hdr_1995 + conflict_internal_cumulative1989_1995)
## $classical
## 
## Call:
## lm(formula = conflict_internal_cumulative1996_2015 ~ mys_ratio_hdr_1995 + 
##     conflict_internal_cumulative1989_1995, data = data)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -13.3847  -1.3420  -0.5707   0.1365  15.5020 
## 
## Coefficients:
##                                       Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                            5.26590    1.46941   3.584 0.000467 ***
## mys_ratio_hdr_1995                    -5.00249    1.68116  -2.976 0.003445 ** 
## conflict_internal_cumulative1989_1995  0.37396    0.04491   8.326 6.81e-14 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.437 on 140 degrees of freedom
##   (58 observations deleted due to missingness)
## Multiple R-squared:  0.4134, Adjusted R-squared:  0.405 
## F-statistic: 49.32 on 2 and 140 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                        Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)                            5.265902   1.742356  3.0223  0.002984 ** 
## mys_ratio_hdr_1995                    -5.002492   1.927099 -2.5959  0.010441 *  
## conflict_internal_cumulative1989_1995  0.373965   0.070379  5.3136 4.136e-07 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## column 4
RunModel(deaths_civilians_int_rate_cumulative1996_2015 ~ mys_ratio_hdr_1995)
## $classical
## 
## Call:
## lm(formula = deaths_civilians_int_rate_cumulative1996_2015 ~ 
##     mys_ratio_hdr_1995, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -0.3920 -0.1561 -0.0910 -0.0562 11.4696 
## 
## Coefficients:
##                    Estimate Std. Error t value Pr(>|t|)  
## (Intercept)          0.5487     0.3040   1.805   0.0732 .
## mys_ratio_hdr_1995  -0.4975     0.3647  -1.364   0.1747  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.9993 on 141 degrees of freedom
##   (58 observations deleted due to missingness)
## Multiple R-squared:  0.01303,    Adjusted R-squared:  0.006028 
## F-statistic: 1.861 on 1 and 141 DF,  p-value: 0.1747
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                    Estimate Std. Error t value Pr(>|t|)  
## (Intercept)         0.54873    0.25566  2.1463  0.03356 *
## mys_ratio_hdr_1995 -0.49752    0.22654 -2.1962  0.02971 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## column 5
RunModel(deaths_civilians_osv_rate_cumulative1996_2015 ~ mys_ratio_hdr_1995 + deaths_civilians_osv_rate_1995)
## $classical
## 
## Call:
## lm(formula = deaths_civilians_osv_rate_cumulative1996_2015 ~ 
##     mys_ratio_hdr_1995 + deaths_civilians_osv_rate_1995, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -1.4803 -0.2503 -0.0644  0.0458  6.0644 
## 
## Coefficients:
##                                 Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                     1.372358   0.270651   5.071 1.24e-06 ***
## mys_ratio_hdr_1995             -1.421716   0.321995  -4.415 2.00e-05 ***
## deaths_civilians_osv_rate_1995  0.068299   0.006422  10.634  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 0.8568 on 140 degrees of freedom
##   (58 observations deleted due to missingness)
## Multiple R-squared:  0.5401, Adjusted R-squared:  0.5336 
## F-statistic: 82.22 on 2 and 140 DF,  p-value: < 2.2e-16
## 
## 
## $robust
## 
## t test of coefficients:
## 
##                                  Estimate Std. Error t value  Pr(>|t|)    
## (Intercept)                     1.3723582  0.5071527  2.7060  0.007657 ** 
## mys_ratio_hdr_1995             -1.4217164  0.5431403 -2.6176  0.009829 ** 
## deaths_civilians_osv_rate_1995  0.0682991  0.0076293  8.9522 1.914e-15 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Non-regression evidence of virtuous and vicious circles

hist(df$life_exp_wpp_growth1995_2015) 

summary(df$life_exp_wpp_growth1995_2015)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
## -10.430   3.678   4.985   5.835   7.495  44.000      21
summary(df$class_low_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.3278  1.0000  1.0000      21
summary(df$class_low_1995[df$life_exp_wpp_growth1995_2015 < 2.3])
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.2222  0.0000  1.0000      21
summary(df$class_upp_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.2278  0.0000  1.0000      21
summary(df$class_upp_1995[df$life_exp_wpp_growth1995_2015 < 2.3])
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##       0       0       0       0       0       0      21
hist(df$imr_wpp_growth1995_2015)

summary(df$imr_wpp_growth1995_2015)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  -2.540   6.106  14.768  22.861  32.947 156.846      21
summary(df$class_low_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.3278  1.0000  1.0000      21
summary(df$class_low_1995[df$imr_wpp_growth1995_2015 < 2.71])
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
## 0.00000 0.00000 0.00000 0.05556 0.00000 1.00000      21
summary(df$class_upp_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.2278  0.0000  1.0000      21
summary(df$class_upp_1995[df$imr_wpp_growth1995_2015 < 2.71])
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.4444  1.0000  1.0000      21
hist(df$mys_ratio_hdr_growth1995_2015)

summary(df$mys_ratio_hdr_growth1995_2015)
##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max.     NA's 
## -0.39343  0.02266  0.08174  0.09543  0.15823  0.42727       59
summary(df$class_low_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.3278  1.0000  1.0000      21
summary(df$class_low_1995[df$mys_ratio_hdr_growth1995_2015 < -0.00437])
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
## 0.00000 0.00000 0.00000 0.06667 0.00000 1.00000      59
summary(df$class_upp_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.2278  0.0000  1.0000      21
summary(df$class_upp_1995[df$mys_ratio_hdr_growth1995_2015 < -0.00437])
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.4667  1.0000  1.0000      59
hist(df$asfr_adol_wpp_growth1995_2015)

summary(df$asfr_adol_wpp_growth1995_2015)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
## -12.038   9.311  19.250  22.539  31.081  91.781      21
summary(df$class_low_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.3278  1.0000  1.0000      21
summary(df$class_low_1995[df$asfr_adol_wpp_growth1995_2015 < 2.7085])
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.1667  0.0000  1.0000      21
summary(df$class_upp_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.2278  0.0000  1.0000      21
summary(df$class_upp_1995[df$asfr_adol_wpp_growth1995_2015 < 2.7085])
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.3889  1.0000  1.0000      21
hist(df$pc_rgdpe_avg_growth1995_2015)

summary(df$pc_rgdpe_avg_growth1995_2015) 
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  -20670    1494    5664    8543   12341  105491      32
summary(df$class_low_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.3278  1.0000  1.0000      21
summary(df$class_low_1995[df$pc_rgdpe_avg_growth1995_2015 < 144]) 
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##    0.00    0.75    1.00    0.75    1.00    1.00      32
summary(df$class_upp_1995)
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##  0.0000  0.0000  0.0000  0.2278  0.0000  1.0000      21
summary(df$class_upp_1995[df$pc_rgdpe_avg_growth1995_2015 < 144])
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max.    NA's 
##   0.000   0.000   0.000   0.125   0.000   1.000      32
df$authority <- df$v2x_polyarchy_cumulative1996_2015 - df$v2x_polyarchy_cumulative1991_1995
hist(df$authority)

summary(df$authority)
##     Min.  1st Qu.   Median     Mean  3rd Qu.     Max.     NA's 
## -0.28685  0.00020  0.02600  0.06046  0.10390  0.44620       36