R/ffd_opt_lalonde_training_employ.R
df_opt_lalonde_training_employ.Rdappended onto the raw Lalonde binary targeting queue rank info based on different planner inequality aversion. includes min and max rank. Based on training logit regressin.
data(df_opt_lalonde_training_employ)csv
https://fanwangecon.github.io/PrjOptiAlloc/articles/ffv_opt_sobin_rkone_allfc_training_logit.html
Lalonde, R. (1986) "Evaluating the Econometric Evaluations of Training Programs with Experimental Data", American Economic Review, 604–620.
data(df_opt_lalonde_training_employ)
head(df_opt_lalonde_training_employ, 10)
#> id A_i_employ alpha_i_employ beta_i_employ rank_min_employ rank_max_employ
#> 1 1 0.5906437 0.09506257 0.001385042 88 1
#> 2 2 0.8108942 0.04660746 0.001385042 605 587
#> 3 3 0.5975632 0.09429401 0.001385042 94 6
#> 4 4 0.6162286 0.07639905 0.001385042 294 146
#> 5 5 0.6356172 0.08947954 0.001385042 210 36
#> 6 6 0.6147834 0.07654263 0.001385042 286 133
#> 7 7 0.6356172 0.08947954 0.001385042 210 36
#> 8 8 0.6675923 0.07051941 0.001385042 463 290
#> 9 9 0.7926912 0.05022472 0.001385042 591 578
#> 10 10 0.6162294 0.07639897 0.001385042 295 147
#> avg_rank_employ trt age educ black hisp marr nodeg re74 re75 re78
#> 1 37.93333 ntran 23 10 1 0 0 1 0 0.000 0.000
#> 2 598.36667 ntran 26 12 0 0 0 0 0 0.000 12383.680
#> 3 45.16667 ntran 22 9 1 0 0 1 0 0.000 0.000
#> 4 213.30000 ntran 34 9 1 0 0 1 NA 4368.413 14051.160
#> 5 110.76667 ntran 18 9 1 0 0 1 0 0.000 10740.080
#> 6 202.96667 ntran 45 11 1 0 0 1 0 0.000 11796.470
#> 7 110.76667 ntran 18 9 1 0 0 1 0 0.000 9227.052
#> 8 376.90000 ntran 27 12 1 0 0 0 NA 2483.851 3552.268
#> 9 585.06667 ntran 24 8 0 0 0 1 0 0.000 10569.270
#> 10 214.30000 ntran 34 11 1 0 1 1 0 0.000 6040.335
#> re75_zero emp78 emp75 race age_m2 age_m3 p_mpg p_mpg_hp p_mpg_hp_bi0
#> 1 1 0 0 1 1 2 0.6783821 0.5906437 0.5906437
#> 2 1 1 0 0 2 2 0.8897568 0.8108942 0.8108942
#> 3 1 0 0 1 1 2 0.6883859 0.5975632 0.5975632
#> 4 0 1 1 1 2 3 0.6383402 0.6162286 0.6162286
#> 5 1 1 0 1 1 1 0.7042022 0.6356172 0.6356172
#> 6 1 1 0 1 2 3 0.5762456 0.6147834 0.6147834
#> 7 1 1 0 1 1 1 0.7042022 0.6356172 0.6356172
#> 8 0 1 1 1 2 3 0.7123512 0.6675923 0.6675923
#> 9 1 1 0 0 2 2 0.8749490 0.7926912 0.7926912
#> 10 1 1 0 1 2 3 0.6934077 0.6162294 0.6162294
#> p_mpg_hp_bi1 rho_c1_rk_employ rho_c2_rk_employ rho_c3_rk_employ
#> 1 0.6857062 1 1 1
#> 2 0.8575016 605 605 605
#> 3 0.6918572 6 6 6
#> 4 0.6926277 294 294 294
#> 5 0.7250968 36 36 36
#> 6 0.6913261 286 286 274
#> 7 0.7250968 36 36 36
#> 8 0.7381117 463 463 463
#> 9 0.8429159 591 591 591
#> 10 0.6926284 295 295 295
#> rho_c4_rk_employ rho_c5_rk_employ rho_c6_rk_employ rho_c7_rk_employ
#> 1 1 1 1 1
#> 2 605 605 605 605
#> 3 6 6 6 6
#> 4 294 282 282 273
#> 5 36 36 36 36
#> 6 274 274 273 260
#> 7 36 36 36 36
#> 8 463 463 454 454
#> 9 591 591 591 591
#> 10 295 283 283 274
#> rho_c8_rk_employ rho_c9_rk_employ rho_c10_rk_employ rho_c11_rk_employ
#> 1 1 1 1 1
#> 2 605 605 604 604
#> 3 6 6 6 6
#> 4 268 268 268 253
#> 5 36 36 36 36
#> 6 260 260 256 241
#> 7 36 36 36 36
#> 8 454 450 447 447
#> 9 591 591 591 590
#> 10 269 269 269 254
#> rho_c12_rk_employ rho_c13_rk_employ rho_c14_rk_employ rho_c15_rk_employ
#> 1 1 1 1 1
#> 2 604 604 604 604
#> 3 6 6 6 6
#> 4 246 233 217 212
#> 5 36 53 90 103
#> 6 230 225 209 204
#> 7 36 53 90 103
#> 8 444 435 416 397
#> 9 589 587 587 587
#> 10 247 234 218 213
#> rho_c16_rk_employ rho_c17_rk_employ rho_c18_rk_employ rho_c19_rk_employ
#> 1 12 45 64 68
#> 2 604 601 597 597
#> 3 33 67 73 79
#> 4 211 207 199 177
#> 5 113 122 124 133
#> 6 203 198 191 169
#> 7 113 122 124 133
#> 8 375 349 330 314
#> 9 586 584 584 582
#> 10 212 208 200 178
#> rho_c20_rk_employ rho_c21_rk_employ rho_c22_rk_employ rho_c23_rk_employ
#> 1 75 78 81 87
#> 2 593 593 591 590
#> 3 83 86 92 94
#> 4 155 155 147 147
#> 5 157 172 181 197
#> 6 147 147 139 139
#> 7 157 172 181 197
#> 8 307 297 293 293
#> 9 581 581 579 579
#> 10 156 156 148 148
#> rho_c24_rk_employ rho_c25_rk_employ rho_c26_rk_employ rho_c27_rk_employ
#> 1 87 87 87 88
#> 2 589 588 588 588
#> 3 94 94 94 94
#> 4 147 146 146 146
#> 5 198 202 206 210
#> 6 138 138 136 133
#> 7 198 202 206 210
#> 8 292 292 292 290
#> 9 578 578 578 578
#> 10 148 147 147 147
#> rho_c28_rk_employ rho_c29_rk_employ rho_c30_rk_employ
#> 1 88 88 88
#> 2 588 588 587
#> 3 94 94 94
#> 4 146 146 146
#> 5 210 210 210
#> 6 133 133 133
#> 7 210 210 210
#> 8 290 290 290
#> 9 578 578 578
#> 10 147 147 147