R/ffd_opt_caschool_input_ib.R
df_opt_caschool_input_ib.Rd\(\text{ID}_i\): individual id \(A_{i,l=0}\): A when considering the lth allocation for ith person, expected outcome without the lth allocation \(\alpha^{\text{o}}_{i}\): see df_casch_prep_i, observed/random/uniform allocation's marginal effect. Note since \(\alpha_{il}\) considers only additional allocation, with existing allocations embeded in \(D_{il}\), \(\alpha^{\text{o}}_{i}\) also only includes additional allocations that is not already embeded in \(\A_{i,l=0}\). \(\beta_{i}\): i specific preference
data(df_opt_caschool_input_ib)csv
https://fmwww.bc.edu/ec-p/data/stockwatson/caschool.des https://fanwangecon.github.io/PrjOptiAlloc/articles/ffv_opt_sodis_rkone_casch_allrw.html
Stock, James H. and Mark W. Watson (2003) Introduction to Econometrics, Addison-Wesley Educational Publishers, chapter 4–7.
data(df_opt_caschool_input_ib)
head(df_opt_caschool_input_ib, 30)
#> id_i A_i_l0 alpha_o_i beta_i
#> 1 1 690.8000 2.372592 0.002380952
#> 2 2 654.2762 2.920114 0.002380952
#> 3 3 640.8497 2.761831 0.002380952
#> 4 4 641.2885 2.664680 0.002380952
#> 5 5 639.3850 2.625868 0.002380952
#> 6 6 625.4803 2.837696 0.002380952
#> 7 7 612.8571 2.827339 0.002380952
#> 8 8 617.2157 2.942918 0.002380952
#> 9 9 624.6470 3.017952 0.002380952
#> 10 10 621.9968 3.063044 0.002380952
#> 11 11 626.0318 2.956175 0.002380952
#> 12 12 621.1129 2.936083 0.002380952
#> 13 13 621.7829 2.986830 0.002380952
#> 14 14 634.4715 3.043577 0.002380952
#> 15 15 636.8020 2.553091 0.002380952
#> 16 16 624.3424 2.823611 0.002380952
#> 17 17 622.0817 2.524999 0.002380952
#> 18 18 634.4041 2.272017 0.002380952
#> 19 19 620.7221 3.310311 0.002380952
#> 20 20 622.3484 2.886947 0.002380952
#> 21 21 622.0775 2.749844 0.002380952
#> 22 22 623.8981 3.148392 0.002380952
#> 23 23 635.8420 2.830685 0.002380952
#> 24 24 617.1388 3.790356 0.002380952
#> 25 25 623.6784 3.019650 0.002380952
#> 26 26 631.0983 2.708787 0.002380952
#> 27 27 617.4778 3.310343 0.002380952
#> 28 28 623.3784 2.793508 0.002380952
#> 29 29 627.5394 2.843753 0.002380952
#> 30 30 631.8025 2.749774 0.002380952