R/mig_resid.R
mig_resid.RdEstimate net migration using residual methods: stock change, time even flow and cohort even flow
mig_resid( pop_m_mat, pop_f_mat, sr_m_mat, sr_f_mat, asfr_mat, srb_vec, ages = NULL, ages_asfr = NULL, years_pop = NULL, years_sr = NULL, years_asfr = NULL, years_srb = NULL, verbose = TRUE, method = c("stock", "cohort", "time") ) mig_resid_stock( pop_m_mat, pop_f_mat, sr_m_mat, sr_f_mat, asfr_mat, srb_vec, ages = NULL, ages_asfr = NULL, years_pop = NULL, years_sr = NULL, years_asfr = NULL, years_srb = NULL, verbose = TRUE ) mig_resid_cohort( pop_m_mat, pop_f_mat, sr_m_mat, sr_f_mat, asfr_mat, srb_vec, ages = NULL, ages_asfr = NULL, years_pop = NULL, years_sr = NULL, years_asfr = NULL, years_srb = NULL, verbose = TRUE ) mig_resid_time( pop_m_mat, pop_f_mat, sr_m_mat, sr_f_mat, asfr_mat, srb_vec, ages = NULL, ages_asfr = NULL, years_pop = NULL, years_sr = NULL, years_asfr = NULL, years_srb = NULL, verbose = TRUE )
| pop_m_mat | A |
|---|---|
| pop_f_mat | A |
| sr_m_mat | A |
| sr_f_mat | A |
| asfr_mat | A |
| srb_vec | A |
| ages | A |
| ages_asfr | A |
| years_pop | Years used in the column names of population. If
|
| years_sr | Years used in the column names of survival rates. If
|
| years_asfr | Years used in the column names of age-specific fertility rate. If codeasfr_r_mat doesn't have column names, these names are used. Otherwise ignored. |
| years_srb | Years used in the column names of sex-ratio at birth. If
|
| verbose | Default set to TRUE. If TRUE, the function prints important operations carried out in the function like if years were trimmed from the data. |
| method | which residual migration method to use. This only works when
using |
A list with two matrices. One is for males (called mig_m) and the
other for females (called mig_f). Both matrices contain net migration
estimates by age/period using one of the three methods.
The stock method (mig_resid_stock) is the difference in stocks that
survive between t and t+5, and the first age group is based on the difference
with the surviving births by sex. It provides net migrants by lexis cohort
parallelograms, and basically such info gets used as end-period migration
since the migrants don't get exposed to mortality within the period.
The time even flow (mig_resid_time) method uses the result from
the first option, but splits it back into lexis period squares and assumes
that half of the net migrants get exposed to the mortality risk during this
period. Such info can get used as evenly distributed migration by period,
but the assumptions lead to zig-zag age patterns that are highly implausible.
The cohort even flow (mig_resid_cohort) method provides the most
meaningful pattern of net migration by age consistent by cohort and assumes
an evenly distribution within the 5-year period, and half of the migrants
get exposed both fertility and mortality within this period.
mig_resid is a general function able to call the three methods only by
specifying the method argument. By default it is set to the
stock method. See the examples section.
library(DemoTools) # The data is loaded with DemoTools ################ Stock change method ##################### # Generic mig_resid method which allows to choose either stock, # cohort or time method for five year ages groups mig_res <- mig_resid( pop_m_mat = pop_m_mat_five, pop_f_mat = pop_f_mat_five, sr_m_mat = sr_m_mat_five, sr_f_mat = sr_f_mat_five, asfr_mat = asfr_mat_five, srb_vec = srb_vec_five, ages = ages_five, ages_asfr = ages_asfr_five, # With the stock method method = "stock" )#> Using stock residual migration method# For single ages mig_res <- mig_resid( pop_m_mat = pop_m_mat_single, pop_f_mat = pop_f_mat_single, sr_m_mat = sr_m_mat_single, sr_f_mat = sr_f_mat_single, asfr_mat = asfr_mat_single, srb_vec = srb_vec_single, ages = ages_single, ages_asfr = ages_asfr_single, # With the stock method method = "stock" )#> Using stock residual migration method# Or directly the mid_resid_stock function # (works for both single and five year age groups) mig_res <- mig_resid_stock( pop_m_mat = pop_m_mat_five, pop_f_mat = pop_f_mat_five, sr_m_mat = sr_m_mat_five, sr_f_mat = sr_f_mat_five, asfr_mat = asfr_mat_five, srb_vec = srb_vec_five, ages = ages_five, ages_asfr = ages_asfr_five ) # Net migration for males using stock change method mig_res$mig_m#> 1950 1955 1960 1965 1970 #> 0 1.7899322803 3.919021e+00 -5.8543069648 12.9092374640 2.921119e+01 #> 5 51.6027045000 5.385321e+01 22.2235544078 22.9335351570 3.470664e+01 #> 10 29.1541335600 2.840815e+01 8.0306470720 19.3499225033 3.062147e+01 #> 15 7.3711371748 4.381831e+00 -5.0199593568 15.8034252562 3.131827e+01 #> 20 21.6150524800 1.566065e+01 -2.0994925197 40.1160914300 5.180611e+01 #> 25 47.8647752800 6.026311e+01 23.3854103582 84.5010463454 8.870085e+01 #> 30 37.0250555000 4.779935e+01 15.9943014370 54.4810744403 5.262150e+01 #> 35 37.0572080800 3.955049e+01 9.4550107496 26.9198029920 2.392796e+01 #> 40 26.6996119446 1.316362e+01 0.9599276814 8.9668772707 1.721723e+01 #> 45 19.3238383059 8.535687e+00 -5.7535831006 7.5537018836 4.394683e+00 #> 50 10.8706376948 5.802709e+00 0.6788420915 0.5444807024 1.053791e+01 #> 55 -0.4710838276 2.382475e+00 -3.2403068092 6.2785759004 -7.931068e-01 #> 60 -2.6739240018 -5.165887e-01 0.4397308595 6.8077825892 9.082899e+00 #> 65 8.2682526723 9.950218e+00 4.2594462540 9.7035767336 8.412578e+00 #> 70 5.1050824363 5.938504e+00 5.7341530320 1.5588869257 6.650109e+00 #> 75 -0.5308153600 3.023748e-01 -0.9342732742 -1.0616547642 1.687302e-01 #> 80 2.6458591680 2.923921e+00 2.3863401360 3.0909371135 -6.546424e-01 #> 85 -0.0002322246 6.833100e-05 -0.0016322983 0.0003876803 -2.982705e-04 #> 90 -0.0007090603 -4.370166e-04 0.0007138143 0.0007593676 4.629872e-05 #> 95 -0.0004184120 8.371022e-05 -0.0002732981 -0.0013148423 -9.538320e-05 #> 100 0.0003631314 -3.905702e-04 0.0004240167 -0.0001150535 1.791806e-04 #> 1975 1980 1985 1990 1995 #> 0 14.4819380766 15.0050326629 30.6160862966 2.279134e+01 33.4094386250 #> 5 24.2440961290 14.9144048249 39.4586215291 3.366381e+01 27.6300354900 #> 10 19.8909763056 12.9976172834 31.3140753898 3.926617e+01 35.2017492389 #> 15 34.5412167950 31.1408714290 53.7835608961 5.806982e+01 56.4028387060 #> 20 35.7746574910 48.8141184045 46.6091830651 3.355813e+01 46.6090142025 #> 25 12.2320674097 15.7490655447 36.0248896021 2.994211e+01 35.2341965234 #> 30 15.2768180385 15.1454438950 48.9912652841 2.939288e+01 43.0299390765 #> 35 3.4133017642 2.6512718093 35.7081057973 2.377502e+01 38.0465234759 #> 40 11.3648881127 0.9157143211 26.0002282136 1.815304e+01 25.2147939559 #> 45 -0.9025899903 -6.1414794104 9.4697258728 9.669273e+00 15.3801489305 #> 50 4.1228516807 1.9180957545 11.4602048293 7.420501e-01 9.1744221357 #> 55 2.8324768102 8.0029005255 13.9249297918 9.461663e+00 7.0314765200 #> 60 5.9587573287 6.1901407708 12.8552522823 1.254064e+01 5.9398053623 #> 65 5.0265223258 6.1334063238 15.3105496329 6.693441e+00 6.2767061297 #> 70 3.0667904029 2.1040520686 8.0829480782 9.051541e-01 4.9118127171 #> 75 1.1085509966 0.4440585403 4.6902499048 -1.740263e+00 1.6956094777 #> 80 -0.3545171554 -1.0788234380 -0.8912981728 -3.259234e+00 1.0782154117 #> 85 -0.0007250264 -0.0003707507 0.0009264276 -1.502028e-03 0.0006504005 #> 90 -0.0010096296 -0.0013578629 -0.0001364608 -1.536187e-03 0.0002672308 #> 95 -0.0005597711 0.0002593028 0.0006724129 4.940180e-06 0.0000220428 #> 100 -0.0002663077 0.0002379727 0.0001025889 -1.467865e-04 -0.0004672003 #> 2000 2005 2010 2015 2020 #> 0 35.2063149299 2.574073e+01 1.686618e+01 3.726188e+01 3.596241e+01 #> 5 39.7815636351 5.198246e+01 3.545773e+01 1.621746e+01 1.572724e+01 #> 10 43.6134320305 4.087724e+01 2.529691e+01 1.243047e+01 1.205461e+01 #> 15 69.4862261899 6.151655e+01 1.053807e+02 6.337355e+01 6.148319e+01 #> 20 61.4795683305 1.081416e+02 1.462701e+02 1.140761e+02 1.106660e+02 #> 25 40.9816130294 9.212637e+01 2.026667e+01 1.096321e+02 1.063574e+02 #> 30 54.2000383773 6.484557e+01 5.491794e+01 8.303648e+01 8.055508e+01 #> 35 54.3621106693 6.210615e+01 4.419383e+01 5.759037e+01 5.586794e+01 #> 40 46.1009769761 4.050389e+01 2.708597e+01 3.866853e+01 3.751901e+01 #> 45 24.3645150956 3.725019e+01 8.129041e+00 2.565676e+01 2.489228e+01 #> 50 19.0808001159 1.891404e+01 1.625201e+01 1.695107e+01 1.644513e+01 #> 55 0.6483630675 1.268029e+01 3.792549e+01 1.118371e+01 1.085143e+01 #> 60 15.0435641770 1.036964e+01 1.188830e+01 7.376952e+00 7.159785e+00 #> 65 6.2874481579 8.037788e+00 3.314290e+01 4.860257e+00 4.720100e+00 #> 70 1.6845365642 1.544022e+00 1.088919e+00 3.201408e+00 3.110899e+00 #> 75 1.7851618553 2.240903e+00 2.708415e+00 2.114225e+00 2.050721e+00 #> 80 4.4904038435 1.151357e+01 -2.168209e+00 1.393847e+00 1.351674e+00 #> 85 0.0003877412 -3.414889e-04 1.892320e-03 1.947218e-03 -5.815492e-05 #> 90 -0.0002732069 3.774664e-04 -1.778366e-03 -4.196944e-04 6.462397e-04 #> 95 0.0003672265 -2.385004e-04 -1.187608e-03 9.547959e-04 -4.276800e-04 #> 100 0.0004257843 1.591630e-04 -5.068183e-05 -3.603256e-04 -1.501552e-04 #> 2025 2030 2035 2040 2045 #> 0 3.713937e+01 3.872296e+01 38.710244991 3.875942e+01 3.884919e+01 #> 5 1.624346e+01 1.692868e+01 16.922542527 1.694990e+01 1.698616e+01 #> 10 1.245485e+01 1.298092e+01 12.972254791 1.299493e+01 1.303085e+01 #> 15 6.348393e+01 6.617035e+01 66.152791816 6.626290e+01 6.641678e+01 #> 20 1.142679e+02 1.191112e+02 119.075586720 1.192639e+02 1.195424e+02 #> 25 1.098159e+02 1.144742e+02 114.442603943 1.146180e+02 1.148904e+02 #> 30 8.317144e+01 8.669744e+01 86.667686177 8.681930e+01 8.701090e+01 #> 35 5.769732e+01 6.012598e+01 60.113368482 6.020745e+01 6.034099e+01 #> 40 3.874399e+01 4.037813e+01 40.365452745 4.042687e+01 4.052742e+01 #> 45 2.570411e+01 2.679773e+01 26.784212118 2.683642e+01 2.688482e+01 #> 50 1.699112e+01 1.771062e+01 17.697703877 1.773515e+01 1.777363e+01 #> 55 1.120040e+01 1.167745e+01 11.672268085 1.169656e+01 1.172089e+01 #> 60 7.386918e+00 7.707266e+00 7.697176849 7.715443e+00 7.730054e+00 #> 65 4.878769e+00 5.078950e+00 5.072805619 5.084954e+00 5.100982e+00 #> 70 3.212492e+00 3.348749e+00 3.347115246 3.356025e+00 3.363517e+00 #> 75 2.116043e+00 2.206720e+00 2.205534484 2.206645e+00 2.212107e+00 #> 80 1.392679e+00 1.453848e+00 1.454611333 1.461609e+00 1.459596e+00 #> 85 5.095878e-04 1.592002e-03 -0.003113428 -1.789957e-04 -1.280066e-03 #> 90 6.580606e-04 -6.258823e-04 0.001700642 -2.324909e-03 1.481708e-03 #> 95 5.002212e-05 -3.570606e-04 -0.001343537 1.088385e-03 9.059035e-05 #> 100 6.132923e-05 -2.312750e-04 0.000230856 -1.040497e-04 4.127133e-05# Net migration for females using stock change method mig_res$mig_f#> 1950 1955 1960 1965 1970 1975 #> 0 113.17293508 114.89636101 90.23263311 87.45872642 90.0432974 70.4587935 #> 5 95.34564459 97.41671484 70.19452018 65.87207075 59.8263941 44.5359312 #> 10 39.38203524 37.98494056 21.59118455 30.06125339 40.8511939 25.2266777 #> 15 18.93727890 15.46635355 15.01716094 35.73093675 43.5519113 44.4185849 #> 20 35.06866853 38.29910784 32.49304247 61.96567298 71.3823189 60.4114357 #> 25 46.52931657 51.15055184 29.78558329 69.40305410 73.3726655 28.8506481 #> 30 49.26659651 53.64077560 28.11913980 41.28897946 46.1446383 30.6183323 #> 35 42.94237789 47.62602471 24.65857528 25.85740478 24.8366719 12.9039601 #> 40 29.40340471 20.97115764 13.49470393 11.16104258 23.5821805 19.5062463 #> 45 18.57086996 17.19342125 7.68481801 16.01699993 16.0862520 12.4982334 #> 50 13.71191120 17.11939842 13.92770203 13.62686866 27.4480823 18.0019021 #> 55 10.00669977 14.47415466 10.65372584 22.55101461 15.3631445 21.7322432 #> 60 11.50849438 12.18200068 18.50430067 27.64042225 28.9167882 29.1498623 #> 65 22.50025175 25.23334367 26.44347204 35.00252644 34.6956380 36.6317503 #> 70 29.00954957 31.29857322 32.48545915 32.31809795 32.5289233 38.7470346 #> 75 16.82217097 18.04473806 21.47476384 30.18757231 33.0546994 39.0628759 #> 80 19.08659895 21.79087700 26.53310358 31.16165091 30.7052393 36.2665503 #> 85 7.00799770 9.63018174 11.75234533 16.01617288 19.8479281 24.8705826 #> 90 2.73784736 3.09952968 4.37523028 5.83026818 8.0543360 11.6835028 #> 95 0.47757027 0.63464332 0.73783617 1.16624771 1.6228540 2.8761175 #> 100 0.03766896 0.04934962 0.06275325 0.08664575 0.1430509 0.2940806 #> 1980 1985 1990 1995 2000 2005 #> 0 65.4905895 76.3891331 68.7130184 70.2702199 57.8078009 48.4244763 #> 5 33.0373278 54.3669316 47.8767793 41.8410746 46.4490916 53.0134297 #> 10 23.5971948 35.5482798 42.9332129 37.8361399 48.9140770 41.0945558 #> 15 30.0666391 49.2268809 54.1049977 53.0111697 61.1189534 59.3054565 #> 20 51.8729917 66.5234561 53.3486767 57.1899226 80.8186413 108.2549385 #> 25 24.8247651 59.2788922 49.3469215 48.0041198 67.9264170 111.1587027 #> 30 30.4020995 63.2339790 44.9045881 54.5849296 74.0834107 103.0106675 #> 35 13.7500933 46.1317183 42.2221569 54.2424859 64.2324081 79.7542022 #> 40 16.8177810 42.4617981 35.6323975 44.6059232 63.2572127 59.0680211 #> 45 10.6764505 24.0128959 31.6798027 36.3022661 41.1520887 57.4674939 #> 50 19.1201073 21.6856843 25.6122443 28.1799534 37.8505654 39.2408961 #> 55 27.1662997 25.9759242 32.3966763 25.4397052 35.6465904 39.5720843 #> 60 31.4169027 32.3333678 33.6616631 29.4462690 42.3024418 45.1001209 #> 65 38.5246016 46.0765985 37.8977766 37.4361944 40.0309377 44.4626225 #> 70 41.3330306 45.5233111 45.3688341 47.3005896 48.0556069 45.6277274 #> 75 43.8517132 52.2627443 48.9690557 59.9854503 61.9408546 63.0543494 #> 80 39.1634375 44.2990904 50.6981503 60.8224943 76.3761824 86.1956876 #> 85 30.2454966 34.3783368 40.9716493 47.5660261 54.0094551 70.3597063 #> 90 15.3906445 17.5112915 20.6083492 22.8002233 27.7876959 34.3398055 #> 95 4.4186387 5.1672347 5.9996563 6.0220990 6.9467713 9.5562259 #> 100 0.5528349 0.7229901 0.8275142 0.6994879 0.6407134 0.8698355 #> 2010 2015 2020 2025 2030 #> 0 40.893862 54.2482009 3.639646e+01 3.756888e+01 3.915000e+01 #> 5 44.012591 21.6549536 1.571378e+01 1.622971e+01 1.691831e+01 #> 10 28.495198 15.8682358 1.285681e+01 1.327584e+01 1.383276e+01 #> 15 93.817691 72.3096374 6.796569e+01 7.018092e+01 7.315433e+01 #> 20 150.599940 125.3306506 1.182762e+02 1.221251e+02 1.272877e+02 #> 25 82.384536 118.5424184 1.095158e+02 1.130743e+02 1.178537e+02 #> 30 100.055532 89.6012339 7.987071e+01 8.246815e+01 8.595619e+01 #> 35 66.203624 64.3219840 5.333906e+01 5.508070e+01 5.740907e+01 #> 40 51.479253 46.0958958 3.449321e+01 3.560806e+01 3.711957e+01 #> 45 25.465817 34.5174228 2.203458e+01 2.275099e+01 2.371591e+01 #> 50 36.408361 29.2195403 1.402299e+01 1.447923e+01 1.509269e+01 #> 55 46.657383 32.4093781 8.899044e+00 9.189698e+00 9.580706e+00 #> 60 37.500438 38.5073520 5.651936e+00 5.833683e+00 6.079587e+00 #> 65 53.185508 47.8148003 3.591765e+00 3.699831e+00 3.864664e+00 #> 70 55.705684 62.3853696 2.279530e+00 2.350295e+00 2.453483e+00 #> 75 65.979261 71.5828801 1.447269e+00 1.494431e+00 1.554029e+00 #> 80 75.191382 78.4085394 9.191045e-01 9.422448e-01 9.851964e-01 #> 85 75.580026 73.6692924 2.023718e-03 -1.309560e-03 -3.205581e-03 #> 90 44.131329 45.7727592 -4.575784e-05 -1.760394e-03 5.530703e-05 #> 95 11.032250 13.0486004 -6.680146e-04 1.115547e-03 2.261978e-04 #> 100 0.919266 0.8355002 -3.823113e-06 -6.037463e-04 1.228691e-05 #> 2035 2040 2045 #> 0 3.915065e+01 3.921944e+01 3.931634e+01 #> 5 1.691457e+01 1.693440e+01 1.697581e+01 #> 10 1.383380e+01 1.385223e+01 1.388592e+01 #> 15 7.313045e+01 7.324795e+01 7.341229e+01 #> 20 1.272581e+02 1.274533e+02 1.277532e+02 #> 25 1.178278e+02 1.180086e+02 1.182870e+02 #> 30 8.594408e+01 8.607590e+01 8.627359e+01 #> 35 5.739172e+01 5.748318e+01 5.762230e+01 #> 40 3.711233e+01 3.716508e+01 3.724629e+01 #> 45 2.371210e+01 2.374261e+01 2.380269e+01 #> 50 1.509005e+01 1.510669e+01 1.514986e+01 #> 55 9.583997e+00 9.598664e+00 9.619318e+00 #> 60 6.081444e+00 6.084633e+00 6.102345e+00 #> 65 3.859534e+00 3.866878e+00 3.879600e+00 #> 70 2.451742e+00 2.453048e+00 2.460003e+00 #> 75 1.554556e+00 1.562182e+00 1.559817e+00 #> 80 9.835399e-01 9.827943e-01 9.950495e-01 #> 85 2.799884e-03 3.560486e-03 -4.231530e-03 #> 90 -7.542806e-04 2.292086e-03 -1.102522e-03 #> 95 7.982875e-04 2.063124e-03 -4.913987e-04 #> 100 -5.497503e-04 -2.754639e-04 -2.854814e-05################ cohort even flow method ##################### # We reuse the same data from before # Either use the generic mig_resid choosing 'cohort' # Five year age groups mig_res <- mig_resid( pop_m_mat = pop_m_mat_five, pop_f_mat = pop_f_mat_five, sr_m_mat = sr_m_mat_five, sr_f_mat = sr_f_mat_five, asfr_mat = asfr_mat_five, srb_vec = srb_vec_five, ages = ages_five, ages_asfr = ages_asfr_five, # With the cohort method method = "cohort" )#> Using cohort residual migration method# Single ages mig_res <- mig_resid( pop_m_mat = pop_m_mat_single, pop_f_mat = pop_f_mat_single, sr_m_mat = sr_m_mat_single, sr_f_mat = sr_f_mat_single, asfr_mat = asfr_mat_single, srb_vec = srb_vec_single, ages = ages_single, ages_asfr = ages_asfr_single, # With the stock method method = "cohort" )#> Using cohort residual migration method# Or directly the mid_resid_cohort function mig_res <- mig_resid_cohort( pop_m_mat = pop_m_mat_five, pop_f_mat = pop_f_mat_five, sr_m_mat = sr_m_mat_five, sr_f_mat = sr_f_mat_five, asfr_mat = asfr_mat_five, srb_vec = srb_vec_five, ages = ages_five, ages_asfr = ages_asfr_five ) # Net migration for males using the cohort even flow method mig_res$mig_m#> 1950 1955 1960 1965 1970 #> 0 27.7345854720 31.0019371482 5.1942053540 24.5624659219 4.688525e+01 #> 5 40.5102116592 41.2343357598 15.1606536999 21.1793513869 3.271567e+01 #> 10 18.3013151966 16.4222220410 1.5058793365 17.6053516384 3.102412e+01 #> 15 14.5468170638 10.0564010777 -3.5687147753 28.0614898551 4.172147e+01 #> 20 34.8888314231 38.1140374410 10.6856647744 62.5658663403 7.055654e+01 #> 25 42.6329532877 54.2516150063 19.7676547862 69.7666525943 7.093797e+01 #> 30 37.2248714152 43.8717655890 12.7781665228 40.8677327075 3.842664e+01 #> 35 32.0814535293 26.5020660760 5.2333131522 18.0380639382 2.068785e+01 #> 40 23.2334561570 10.9459192982 -2.4258656763 8.3347645192 1.089106e+01 #> 45 15.3265554535 7.2748524613 -2.5633574346 4.0973563278 7.587504e+00 #> 50 5.3028125043 4.1864884603 -1.3245914367 3.5133073257 4.957193e+00 #> 55 -1.6476700692 0.9576589788 -1.4395096532 6.8074763188 4.347471e+00 #> 60 3.0476956367 5.0897985122 2.5236522427 8.7981552818 9.271884e+00 #> 65 7.2975977560 8.6761911905 5.4904630231 6.0964521738 8.217822e+00 #> 70 2.5311742841 3.4940993902 2.6452918966 0.2448806986 3.800742e+00 #> 75 1.3981785084 2.0660658863 0.9794162929 1.3492354084 -3.171552e-01 #> 80 1.7122472632 1.8870772095 1.5306732316 1.9744450576 -4.164296e-01 #> 85 -0.0008180112 -0.0003418182 -0.0005657794 0.0009453795 -1.747616e-04 #> 90 -0.0011282773 -0.0002951569 0.0003245206 -0.0008184162 -6.416606e-05 #> 95 -0.0009690561 0.0001945259 -0.0006136342 -0.0029657259 -2.079006e-04 #> 100 0.0003631314 -0.0003905702 0.0004240167 -0.0001150535 1.791806e-04 #> 1975 1980 1985 1990 1995 #> 0 26.7290464322 22.5514135124 50.5005203859 3.971947e+01 4.733699e+01 #> 5 22.0962653344 13.9694166410 35.4141109601 3.648698e+01 3.143147e+01 #> 10 27.2613524622 22.0997423995 42.5971117509 4.871322e+01 4.583846e+01 #> 15 35.2720807678 40.0886284255 50.3067733763 4.589406e+01 5.158882e+01 #> 20 24.1056789950 32.3931085097 41.4420067581 3.183571e+01 4.101680e+01 #> 25 13.8048985375 15.4971051546 42.6358411330 2.975410e+01 3.922889e+01 #> 30 9.3790926968 8.9270470232 42.4876305010 2.667472e+01 4.065530e+01 #> 35 7.4318376300 1.7905172492 30.9784476453 2.105322e+01 3.174649e+01 #> 40 5.2620681370 -2.6361050610 17.8294359966 1.398769e+01 2.039907e+01 #> 45 1.6409798784 -2.1235510680 10.5680414394 5.242261e+00 1.236784e+01 #> 50 3.5528032225 5.0697335208 12.9059761124 5.190501e+00 8.201545e+00 #> 55 4.5669024604 7.3126011011 13.7574122211 1.127484e+01 6.618932e+00 #> 60 5.7964848148 6.4725021367 14.7392106038 9.973541e+00 6.324542e+00 #> 65 4.3823473498 4.4122945905 12.4941899906 4.003111e+00 5.912938e+00 #> 70 2.3424884610 1.4118350206 7.0917545044 -4.958813e-01 3.587037e+00 #> 75 0.4223807796 -0.4160797352 2.1344354343 -2.976618e+00 1.602920e+00 #> 80 -0.2237692930 -0.6727819681 -0.5508956693 -1.992855e+00 6.527169e-01 #> 85 -0.0013472520 -0.0013649720 0.0005310532 -2.288892e-03 6.637464e-04 #> 90 -0.0014153765 -0.0008447875 0.0005782918 -1.248544e-03 2.421791e-04 #> 95 -0.0011599514 0.0005239992 0.0013807440 1.016482e-05 4.658246e-05 #> 100 -0.0002663077 0.0002379727 0.0001025889 -1.467865e-04 -4.672003e-04 #> 2000 2005 2010 2015 2020 #> 0 5.521348e+01 5.181794e+01 3.464569e+01 4.546868e+01 4.391070e+01 #> 5 4.171498e+01 4.644763e+01 3.038654e+01 1.432799e+01 1.389523e+01 #> 10 5.658804e+01 5.122663e+01 6.537600e+01 3.792246e+01 3.678382e+01 #> 15 6.557516e+01 8.495273e+01 1.259713e+02 8.882648e+01 8.614305e+01 #> 20 5.133396e+01 1.003256e+02 8.339817e+01 1.120286e+02 1.086440e+02 #> 25 4.769132e+01 7.864393e+01 3.765750e+01 9.649354e+01 9.359811e+01 #> 30 5.441186e+01 6.361715e+01 4.964878e+01 7.043648e+01 6.832703e+01 #> 35 5.038857e+01 5.144900e+01 3.572532e+01 4.823902e+01 4.679176e+01 #> 40 3.538553e+01 3.904144e+01 1.766614e+01 3.227328e+01 3.130150e+01 #> 45 2.187529e+01 2.825565e+01 1.226915e+01 2.142061e+01 2.076887e+01 #> 50 9.953746e+00 1.595878e+01 2.736801e+01 1.418917e+01 1.375317e+01 #> 55 8.024718e+00 1.171475e+01 2.523316e+01 9.404806e+00 9.113674e+00 #> 60 1.095858e+01 9.441914e+00 2.309601e+01 6.246623e+00 6.051291e+00 #> 65 4.157159e+00 4.963837e+00 1.761464e+01 4.165787e+00 4.032837e+00 #> 70 1.879553e+00 2.032313e+00 2.029089e+00 2.804870e+00 2.709220e+00 #> 75 3.633292e+00 7.856819e+00 2.269679e-01 1.921612e+00 1.849407e+00 #> 80 2.648544e+00 6.637323e+00 -1.231256e+00 7.883184e-01 7.562531e-01 #> 85 4.033675e-05 7.105796e-05 -1.498956e-04 9.007669e-04 4.340415e-04 #> 90 1.617833e-04 5.104875e-05 -2.514495e-03 6.246262e-04 5.782513e-05 #> 95 7.570578e-04 -4.775804e-04 -2.347887e-03 1.876386e-03 -8.238661e-04 #> 100 4.257843e-04 1.591630e-04 -5.068183e-05 -3.603256e-04 -1.501552e-04 #> 2025 2030 2035 2040 2045 #> 0 4.533636e+01 4.725714e+01 4.723415e+01 4.729110e+01 4.739403e+01 #> 5 1.435297e+01 1.495834e+01 1.495057e+01 1.497529e+01 1.501112e+01 #> 10 3.798272e+01 3.958804e+01 3.957368e+01 3.963905e+01 3.973308e+01 #> 15 8.893813e+01 9.269935e+01 9.266739e+01 9.281208e+01 9.302437e+01 #> 20 1.121642e+02 1.169091e+02 1.168658e+02 1.170394e+02 1.173074e+02 #> 25 9.662625e+01 1.007130e+02 1.006725e+02 1.008273e+02 1.010516e+02 #> 30 7.054235e+01 7.351530e+01 7.348607e+01 7.360189e+01 7.375815e+01 #> 35 4.831215e+01 5.033959e+01 5.031996e+01 5.039165e+01 5.050329e+01 #> 40 3.231319e+01 3.367316e+01 3.365320e+01 3.370409e+01 3.377327e+01 #> 45 2.144079e+01 2.234327e+01 2.232287e+01 2.236153e+01 2.239942e+01 #> 50 1.419322e+01 1.478717e+01 1.477057e+01 1.479497e+01 1.482056e+01 #> 55 9.393798e+00 9.787974e+00 9.772460e+00 9.787043e+00 9.800488e+00 #> 60 6.235955e+00 6.491396e+00 6.475070e+00 6.483358e+00 6.492494e+00 #> 65 4.154458e+00 4.317637e+00 4.305202e+00 4.308499e+00 4.313789e+00 #> 70 2.783655e+00 2.892001e+00 2.881492e+00 2.878664e+00 2.878182e+00 #> 75 1.892981e+00 1.963852e+00 1.953794e+00 1.949436e+00 1.943300e+00 #> 80 7.721803e-01 8.009601e-01 7.934284e-01 7.943901e-01 7.884978e-01 #> 85 7.786621e-04 5.130995e-04 -6.648082e-04 -1.703315e-03 2.604560e-04 #> 90 5.174199e-04 -7.749870e-04 -5.907210e-05 -6.034064e-04 1.089173e-03 #> 95 9.482005e-05 -6.681631e-04 -2.483761e-03 1.989245e-03 1.637868e-04 #> 100 6.132923e-05 -2.312750e-04 2.308560e-04 -1.040497e-04 4.127133e-05# Net migration for females using the cohort even flow method mig_res$mig_f#> 1950 1955 1960 1965 1970 1975 #> 0 171.72131816 173.14456142 131.77820968 125.77017105 124.6968682 95.9520589 #> 5 69.20081450 69.28238640 46.84641331 48.75618851 50.9922442 35.2853877 #> 10 29.46477771 26.96618336 18.44416874 33.10558630 42.4374326 34.9937120 #> 15 27.29600628 27.13733711 23.95068047 49.19164496 57.8183162 52.7039012 #> 20 41.33304378 45.22976783 31.44274248 66.24574140 72.9147253 44.9214309 #> 25 48.61860483 53.07861527 29.28367497 55.88984313 60.2716586 29.9682458 #> 30 46.88561716 51.38378241 26.73500957 33.95470778 35.8411804 21.9525937 #> 35 36.86298992 34.86859624 19.36135344 18.75110168 24.4968027 16.3825468 #> 40 24.51040044 19.45753274 10.77528557 13.81136654 20.1137017 16.2070083 #> 45 16.56535817 17.57029029 11.05335164 15.11774766 22.1790338 15.5127441 #> 50 12.26265055 16.29327790 12.64429657 18.59839574 21.9134313 20.3315864 #> 55 11.30080079 13.92818445 15.23128103 26.10027153 22.9939702 26.3244627 #> 60 18.40400698 20.13441348 24.01142703 33.27825496 33.6423294 34.6656953 #> 65 29.00224834 31.55144157 32.65724529 36.93668833 36.6712748 40.9309041 #> 70 27.17509206 28.94143981 31.42783859 36.27914530 37.7960682 44.4445436 #> 75 23.83314481 26.11712003 31.07521196 39.00073414 39.9437017 46.6140330 #> 80 19.13202079 22.82358621 27.36889447 33.37685139 35.5223684 42.3677161 #> 85 8.57065143 10.90765432 13.64065673 18.13800515 22.8559186 29.5426976 #> 90 3.41815884 3.91939256 5.21967120 7.05826177 9.5714802 14.1771134 #> 95 1.25221623 1.63514702 1.86297785 2.89364187 3.9438894 6.8026913 #> 100 0.03766896 0.04934962 0.06275325 0.08664575 0.1430509 0.2940806 #> 1980 1985 1990 1995 2000 2005 #> 0 84.4975756 106.1761668 94.7745340 93.0428964 82.3545273 75.8669558 #> 5 28.5730084 45.3124335 45.7159530 40.0648036 47.8985128 47.2331783 #> 10 26.9396863 42.5369562 48.6845584 45.5573823 55.1597026 50.3105897 #> 15 41.1581199 58.1083629 53.9313215 55.2936585 71.1989878 84.0183980 #> 20 38.5564169 63.2154839 51.5985008 52.8430913 74.7031986 110.1303313 #> 25 27.7977659 61.6234186 47.4051198 51.6083434 71.4428640 107.6456040 #> 30 22.2422255 55.0624099 43.8731207 54.8247021 69.7022819 92.0023679 #> 35 15.4282339 44.6721699 39.2611120 49.8762677 64.3662482 69.9977501 #> 40 13.9022608 33.5791503 34.0132172 40.9028124 52.7987748 58.8675964 #> 45 15.1324013 23.1657203 29.0358476 32.6897767 40.0602448 48.9595289 #> 50 23.6430427 24.3027282 29.5679655 27.3167444 37.4326840 40.0787725 #> 55 30.2152519 30.0197155 33.9584308 28.2084960 40.0225780 43.3773939 #> 60 36.7180278 41.0735925 37.3701400 34.8975556 42.8133296 46.4391888 #> 65 43.1354913 49.2244096 44.6705493 45.3497331 46.9441002 47.7359675 #> 70 48.3036273 55.1229691 52.8406941 59.9426380 61.0737010 59.9554207 #> 75 50.7362876 58.3363476 59.9609448 72.1377381 82.0927869 87.8106758 #> 80 47.5944714 53.1999714 61.2981433 71.6760979 84.6800893 100.6440966 #> 85 36.3664993 40.6306969 47.4201296 53.3764469 60.9562720 76.3506288 #> 90 19.0369669 21.3787584 24.5943500 26.1127004 30.5702757 37.8712336 #> 95 10.2343876 11.7002979 13.3059286 13.1155117 14.6560891 19.6212289 #> 100 0.5528349 0.7229901 0.8275142 0.6994879 0.6407134 0.8698355 #> 2010 2015 2020 2025 2030 #> 0 63.536304 65.7260833 4.433063e+01 4.575479e+01 4.767406e+01 #> 5 36.364455 18.8075067 1.428867e+01 1.475587e+01 1.537836e+01 #> 10 61.269592 44.1589114 4.042136e+01 4.173772e+01 4.350211e+01 #> 15 122.497446 99.0230306 9.315949e+01 9.618904e+01 1.002545e+02 #> 20 116.841872 122.2617185 1.139634e+02 1.176635e+02 1.226309e+02 #> 25 91.599610 104.4228958 9.476476e+01 9.783964e+01 1.019700e+02 #> 30 83.556553 77.2882500 6.666796e+01 6.883477e+01 7.174004e+01 #> 35 59.226427 55.5069429 4.397429e+01 4.539983e+01 4.731691e+01 #> 40 38.779598 40.5871463 2.832219e+01 2.923507e+01 3.047038e+01 #> 45 31.279570 32.1673624 1.808882e+01 1.867232e+01 1.945852e+01 #> 50 42.163635 31.2312923 1.152124e+01 1.189181e+01 1.239102e+01 #> 55 42.973366 36.1762133 7.334320e+00 7.567618e+00 7.883037e+00 #> 60 46.928486 44.5379457 4.679762e+00 4.821689e+00 5.024070e+00 #> 65 57.430282 57.9859587 2.994345e+00 3.080767e+00 3.211853e+00 #> 70 66.529195 72.8098599 1.925118e+00 1.981168e+00 2.059526e+00 #> 75 81.908880 86.2100493 1.251706e+00 1.283795e+00 1.332189e+00 #> 80 96.146695 95.5267726 4.973036e-01 5.053310e-01 5.244282e-01 #> 85 86.396271 84.8470594 1.139063e-03 -1.900901e-03 -1.787040e-03 #> 90 46.461630 48.6423262 -5.916063e-04 -2.214464e-04 2.219107e-04 #> 95 22.183238 25.5167066 -1.122828e-03 1.857040e-03 3.723792e-04 #> 100 0.919266 0.8355002 -3.823113e-06 -6.037463e-04 1.228691e-05 #> 2035 2040 2045 #> 0 4.766587e+01 4.773854e+01 4.785075e+01 #> 5 1.537671e+01 1.539557e+01 1.543288e+01 #> 10 4.348980e+01 4.355698e+01 4.365529e+01 #> 15 1.002246e+02 1.003781e+02 1.006076e+02 #> 20 1.225980e+02 1.227812e+02 1.230660e+02 #> 25 1.019459e+02 1.020974e+02 1.023309e+02 #> 30 7.172074e+01 7.182816e+01 7.199256e+01 #> 35 4.730032e+01 4.736846e+01 4.747491e+01 #> 40 3.046052e+01 3.049816e+01 3.056507e+01 #> 45 1.945084e+01 1.947030e+01 1.951809e+01 #> 50 1.238686e+01 1.239838e+01 1.242642e+01 #> 55 7.881202e+00 7.886047e+00 7.901435e+00 #> 60 5.018025e+00 5.019264e+00 5.030757e+00 #> 65 3.203963e+00 3.204237e+00 3.210327e+00 #> 70 2.054404e+00 2.054788e+00 2.053114e+00 #> 75 1.326888e+00 1.326015e+00 1.327060e+00 #> 80 5.245498e-01 5.223082e-01 5.222588e-01 #> 85 1.098362e-03 3.448556e-03 -3.048916e-03 #> 90 1.682787e-04 3.117486e-03 -1.084673e-03 #> 95 1.301420e-03 3.330889e-03 -7.856163e-04 #> 100 -5.497503e-04 -2.754639e-04 -2.854814e-05################ time even flow method ##################### # We reuse the same data from before # Either use the generic mig_resid with the 'time' method # For five year age groups mig_res <- mig_resid( pop_m_mat = pop_m_mat_five, pop_f_mat = pop_f_mat_five, sr_m_mat = sr_m_mat_five, sr_f_mat = sr_f_mat_five, asfr_mat = asfr_mat_five, srb_vec = srb_vec_five, ages = ages_five, ages_asfr = ages_asfr_five, # With the time method method = "time" )#> Using time residual migration method# For single ages mig_res <- mig_resid( pop_m_mat = pop_m_mat_single, pop_f_mat = pop_f_mat_single, sr_m_mat = sr_m_mat_single, sr_f_mat = sr_f_mat_single, asfr_mat = asfr_mat_single, srb_vec = srb_vec_single, ages = ages_single, ages_asfr = ages_asfr_single, # With the stock method method = "stock" )#> Using stock residual migration method# Or directly the mid_resid_time function # (works for both five and single year ages) mig_res <- mig_resid_time( pop_m_mat = pop_m_mat_five, pop_f_mat = pop_f_mat_five, sr_m_mat = sr_m_mat_five, sr_f_mat = sr_f_mat_five, asfr_mat = asfr_mat_five, srb_vec = srb_vec_five, ages = ages_five, ages_asfr = ages_asfr_five ) # Net migration for males using the time even flow method mig_res$mig_m#> 1950 1955 1960 1965 1970 #> 0 3.57986456 7.83804281 -11.708613930 25.81847493 58.42237710 #> 5 99.65372764 99.91545521 56.096782636 20.16120060 11.21457792 #> 10 -40.94162774 -42.78430686 -39.882708344 18.59078430 50.05512859 #> 15 55.48348586 51.36112198 29.686148299 13.09179503 12.81047107 #> 20 -11.79757463 -19.64383338 -33.657655806 67.25140324 90.92287133 #> 25 107.42501258 140.01220683 80.160934509 102.29400345 87.21131258 #> 30 -32.40904222 -43.26549135 -47.553510864 7.44391246 18.67159066 #> 35 106.17661163 121.93971456 66.014834078 46.46533877 29.35435108 #> 40 -51.15631402 -93.89843855 -63.174578114 -27.88927758 5.48775806 #> 45 88.57046150 108.82847303 50.267264262 42.37000677 3.42290940 #> 50 -63.32934115 -93.13047934 -47.057179615 -39.73615654 17.77493878 #> 55 58.46883834 92.26143114 37.785755257 49.95450413 -18.35527636 #> 60 -58.32986589 -84.64085443 -33.370638099 -31.75995974 34.90416044 #> 65 66.83013145 92.79117747 37.313414670 46.77483495 -13.45378292 #> 70 -43.57046784 -62.56497815 -18.527162169 -34.44289291 24.15556419 #> 75 30.01886407 45.21821705 11.378053697 22.72777192 -17.18309176 #> 80 -12.62450034 -21.29332857 -2.130173274 -7.74682943 9.31779578 #> 85 5.60441174 9.70724986 0.986839238 3.68891047 -4.50288791 #> 90 -1.70123799 -3.01062248 -0.313951952 -1.20302297 1.52466156 #> 95 0.31632108 0.55768479 0.061728916 0.23383116 -0.32111739 #> 100 -0.02811154 -0.05411331 -0.005447638 -0.02448547 0.03644719 #> 1975 1980 1985 1990 1995 #> 0 28.96387615 30.01006533 61.232172593 45.58267324 66.8188773 #> 5 19.61458145 -0.11384016 17.798839229 21.81186415 -11.4789958 #> 10 20.20595285 26.10889922 44.850683328 56.74184507 81.8729514 #> 15 48.95919987 36.25809415 62.845864529 59.53667644 31.0999449 #> 20 23.01801705 61.62328797 30.756451497 7.89400063 62.2618417 #> 25 1.62298038 -29.72231189 41.475065426 52.03339643 8.4963877 #> 30 28.94199434 59.82581388 56.757960851 7.07303243 77.6072932 #> 35 -21.87239151 -54.10090181 15.060691363 40.53058132 -1.0157575 #> 40 44.33117340 55.38825229 37.079303424 -3.83519751 51.4366294 #> 45 -45.24366939 -66.76114668 -17.615872177 23.12250876 -20.0512376 #> 50 51.97198921 68.73233751 40.118018493 -21.15026980 38.0260225 #> 55 -43.51296896 -49.55790353 -10.657202225 39.33641676 -22.7965318 #> 60 51.82676172 58.29271858 35.664479258 -11.98652737 33.5229966 #> 65 -35.33901983 -39.41621873 -1.325981088 24.25817390 -18.2014075 #> 70 34.99220822 36.88719713 17.281657343 -18.97573621 25.6182594 #> 75 -23.57247670 -26.76288480 -3.793379475 11.33350586 -16.9839990 #> 80 14.15059062 15.05938901 0.694028281 -14.10486407 13.7584471 #> 85 -7.09942975 -7.76410472 -0.358176585 7.41969081 -7.3510661 #> 90 2.59035597 2.91884576 0.132464878 -2.78840546 2.7397113 #> 95 -0.60437431 -0.71424802 -0.030070852 0.65864048 -0.6134260 #> 100 0.07855023 0.09881163 0.004110768 -0.08173701 0.0688248 #> 2000 2005 2010 2015 2020 2025 #> 0 70.4126299 51.48145831 33.73236083 74.5237684 71.9248264 74.2787331 #> 5 9.2223352 52.52998713 37.20561118 -42.0424248 -40.4151595 -41.7427286 #> 10 78.0107215 29.25548089 13.40764281 66.8830873 64.5071365 66.6372408 #> 15 61.1002538 93.82266121 197.37105948 59.9439586 58.5164254 60.3817971 #> 20 62.1021505 122.80643192 95.77213448 168.3817044 162.9313907 168.2596094 #> 25 20.1148330 61.93362372 -54.90300355 51.4450008 50.2569949 51.8140624 #> 30 88.3718114 68.01002222 164.54991665 114.7947184 111.0135390 114.6788458 #> 35 20.8205517 56.52957864 -75.48650810 0.8280661 1.1274237 1.0935709 #> 40 71.5336598 24.86139074 129.21554946 76.5135937 73.9162539 76.3993357 #> 45 -22.0122498 49.89176029 -111.77480201 -24.5285913 -23.5568882 -24.4557117 #> 50 59.7886258 -11.24947223 142.64920256 58.0869502 56.1548785 58.1644701 #> 55 -56.8405940 36.31951173 -63.55416721 -34.4574904 -33.3626521 -34.7478059 #> 60 84.3838898 -14.13565389 85.10506293 48.0687406 46.6862333 48.5890735 #> 65 -65.7712511 29.32707902 -14.15647172 -35.8655365 -35.0816217 -36.8046551 #> 70 61.6773024 -23.35409488 15.10886419 39.3393827 38.7196217 40.7791816 #> 75 -47.0754634 24.20349394 -7.59220972 -29.9265975 -29.9667998 -32.0866992 #> 80 42.8165215 4.82076390 1.53813111 26.2495781 26.6336803 28.8995750 #> 85 -24.3487769 -2.93691216 -0.96750858 -16.8699992 -17.6523987 -19.6928288 #> 90 9.6710926 1.24605503 0.42211034 7.5546157 8.3531350 9.6521764 #> 95 -2.2748115 -0.31123505 -0.11037382 -1.9541809 -2.2518481 -2.6861664 #> 100 0.2597073 0.03683747 0.01288714 0.2285256 0.2509391 0.3042474 #> 2030 2035 2040 2045 #> 0 77.4459176 77.4204900 77.5188470 77.6983814 #> 5 -43.5429804 -43.5345068 -43.5819780 -43.6922370 #> 10 69.4908108 69.4665111 69.5605646 69.7436785 #> 15 62.8975960 62.8819987 63.0042277 63.1255567 #> 20 175.4243967 175.3598544 175.6067308 176.0358055 #> 25 53.9474549 53.9155099 53.9903843 54.0801592 #> 30 119.5914528 119.5528521 119.7715458 120.0562085 #> 35 1.0225270 1.0072712 0.9519375 0.9121235 #> 40 79.7379684 79.7274719 79.9051533 80.1456864 #> 45 -25.6296697 -25.6871280 -25.7956559 -25.9708380 #> 50 60.7878345 60.8398404 61.0409161 61.3084604 #> 55 -36.4591281 -36.5987410 -36.8176156 -37.0954370 #> 60 50.9769737 51.1657131 51.4807825 51.8403704 #> 65 -38.8691838 -39.2202149 -39.6397621 -40.0819810 #> 70 43.1850851 43.6969678 44.2773104 44.8632888 #> 75 -34.3995882 -35.1814702 -35.9946429 -36.7846096 #> 80 31.3094023 32.3339309 33.3781480 34.3711942 #> 85 -21.7940080 -22.9599143 -24.1187034 -25.2468632 #> 90 10.9779695 11.8694772 12.7578752 13.6605184 #> 95 -3.1357372 -3.4757375 -3.8169784 -4.1788256 #> 100 0.3588661 0.4034127 0.4472692 0.4953120# Net migration for females using the time even flow method mig_res$mig_f#> 1950 1955 1960 1965 1970 #> 0 226.3458702 229.79272201 180.46526622 174.91745284 180.0865949 #> 5 -21.0374290 -22.28540657 -31.50143500 -36.12133305 -54.2299461 #> 10 99.3415777 97.83858796 74.17190806 95.74522542 135.2772394 #> 15 -59.6809765 -65.39419993 -43.13633166 -23.17129337 -46.8001148 #> 20 128.4354061 140.68621033 107.36582549 146.74972311 188.9421056 #> 25 -31.8378149 -35.02737104 -45.53762715 -5.25186295 -39.1701555 #> 30 129.3780748 141.35666443 100.68019100 87.71909797 130.7375337 #> 35 -38.9436452 -41.71922721 -48.58209382 -33.86767281 -78.2687759 #> 40 96.1969156 82.17618397 74.01404694 55.22193698 123.4478722 #> 45 -54.6355206 -44.39140208 -55.84845122 -21.29545414 -87.4661601 #> 50 78.9618389 76.33323073 81.03814346 47.61263555 138.8417828 #> 55 -52.9859019 -42.06729052 -54.48681576 0.34775936 -100.3924019 #> 60 70.2110143 62.17078749 86.34367902 54.96362841 150.0050752 #> 65 -13.6705663 -2.18847224 -21.04847767 22.41355071 -61.7595508 #> 70 68.3375982 64.28074915 81.42847971 46.82844725 114.8253826 #> 75 -10.3770787 -6.38475405 -12.10171449 27.99107016 -14.8924516 #> 80 43.4733361 46.94240803 59.62805297 46.69267660 69.9571248 #> 85 -1.9687420 1.39813765 -0.03423644 12.94953562 10.0953495 #> 90 5.9489557 5.85004073 8.75937070 8.16573505 13.2737132 #> 95 0.0898606 0.38802533 0.10170185 1.00605627 0.9981967 #> 100 0.0679131 0.06587289 0.11661638 0.08288009 0.1932348 #> 1975 1980 1985 1990 1995 2000 #> 0 140.9175869 130.9811791 152.7782663 137.4260367 140.5404398 115.6156018 #> 5 -47.6765502 -61.7171348 -40.8585367 -39.0325437 -54.6180620 -21.2182395 #> 10 97.6260741 108.3826166 111.6492954 124.6180639 129.9601873 118.9342766 #> 15 -7.8818342 -47.4337354 -12.4509483 -15.6031808 -23.1929547 3.9108808 #> 20 128.6090432 150.7026598 145.3857926 122.1649032 137.3844478 157.7556344 #> 25 -69.0487765 -99.2216052 -25.2362233 -22.1547875 -39.9084905 -20.2548668 #> 30 129.1419899 158.6280625 151.3826146 111.6798611 148.5439952 168.1412151 #> 35 -100.8450048 -128.4887081 -56.8328512 -25.5163741 -37.6094921 -36.7292738 #> 40 137.5336842 159.5245635 140.7046297 96.3026480 126.0717377 162.4750899 #> 45 -108.6421302 -134.1399364 -89.3958210 -30.7009674 -50.4245702 -76.1732663 #> 50 140.6039363 167.8574350 129.9678704 80.9786683 105.2077827 149.5078659 #> 55 -89.8706856 -105.5535968 -72.2499150 -12.6897624 -49.8245648 -71.9891197 #> 60 141.3008408 160.8936779 132.1033687 79.1982021 105.5948969 152.2723407 #> 65 -51.4025974 -66.1123963 -26.1991832 4.4994582 -20.5531042 -58.3050739 #> 70 119.4994680 137.3914275 112.9664642 86.9423211 112.0615845 146.1102282 #> 75 -7.9495626 -13.1711402 20.1620016 32.1240324 34.2024895 10.3023640 #> 80 77.2260167 86.3128305 76.0691914 81.0085017 99.5705861 145.9411473 #> 85 15.8341860 21.3140279 33.0870227 42.8214335 45.8964765 33.1931354 #> 90 18.7134443 24.2671827 24.5037172 27.0921147 30.0018912 43.7139432 #> 95 2.4071631 4.3137979 5.5552771 6.4911688 5.7190028 4.0726763 #> 100 0.3523143 0.6684041 0.8605413 0.9424119 0.7500321 0.7860324 #> 2005 2010 2015 2020 2025 2030 #> 0 96.8489527 81.787724 108.4964018 72.7929143 75.1377635 78.2999917 #> 5 10.1456148 6.861041 -64.5147999 -41.3212737 -42.6378073 -44.4263380 #> 10 72.0885342 50.154505 96.0526852 67.0220607 69.1777814 72.0812494 #> 15 46.8365412 137.666319 48.8726280 68.9452677 71.2172872 74.2579199 #> 20 169.9719435 164.268004 202.0142957 167.6757076 173.0972445 180.3776182 #> 25 53.8651176 1.674869 36.2921853 51.5879497 53.2730104 55.5402431 #> 30 152.8004253 198.451595 143.1858115 108.2401113 111.7463469 116.4513446 #> 35 9.0499008 -63.722429 -13.1662853 -1.3229319 -1.3567847 -1.4166120 #> 40 109.2538323 165.752322 105.1968799 70.3049707 72.5687612 75.6518060 #> 45 8.0918478 -111.804908 -34.4986470 -25.8589758 -26.7076872 -27.8794694 #> 50 70.6184057 181.907767 92.1907107 53.6822324 55.4537780 57.8631744 #> 55 11.2247424 -82.427027 -24.5262744 -35.1714449 -36.3953427 -38.0578218 #> 60 79.5974807 153.293244 100.4054475 45.7645298 47.3851820 49.5739605 #> 65 16.0694181 -35.018895 2.4904511 -37.1421185 -38.6125234 -40.5402789 #> 70 77.3204513 142.125455 122.5674937 39.8336501 41.5180415 43.7294736 #> 75 64.9764201 17.669656 43.2746269 -33.6428689 -35.3367518 -37.5389842 #> 80 128.3596517 138.115219 126.1406102 30.7027237 32.5078219 34.8617924 #> 85 72.5951224 75.405603 75.9497393 -22.9890882 -24.7183961 -26.9616805 #> 90 41.4996635 58.915419 60.6511414 13.2008917 14.4778586 16.1584514 #> 95 9.2686019 7.492899 10.2366742 -4.6738266 -5.2221854 -5.9617379 #> 100 0.5589578 0.851188 0.2535397 0.7421335 0.8358793 0.9663258 #> 2035 2040 2045 #> 0 78.301291 78.438885 78.632681 #> 5 -44.439072 -44.540444 -44.654494 #> 10 72.097267 72.236517 72.418842 #> 15 74.190986 74.283958 74.427831 #> 20 180.379735 180.672096 181.123362 #> 25 55.469495 55.523010 55.613918 #> 30 116.491593 116.695956 116.994920 #> 35 -1.508978 -1.546569 -1.582514 #> 40 75.729792 75.873104 76.071716 #> 45 -27.992601 -28.100488 -28.203044 #> 50 57.986739 58.142769 58.345844 #> 55 -38.226599 -38.401601 -38.608806 #> 60 49.797401 50.026525 50.314056 #> 65 -40.876810 -41.187768 -41.540384 #> 70 44.186892 44.619462 45.098744 #> 75 -38.197735 -38.810642 -39.481595 #> 80 35.743188 36.582545 37.499323 #> 85 -28.026998 -29.079131 -30.223302 #> 90 17.126684 18.119018 19.185104 #> 95 -6.442425 -6.947161 -7.507029 #> 100 1.053518 1.148182 1.254126