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Commit 43a07d08 authored by Reinhold Kainhofer's avatar Reinhold Kainhofer
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Restructuring the data files

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R/Tables/AVOe_R.xlsx deleted 100644 → 0
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R/Tables/Overview_Tables.ods deleted 100644 → 0
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R/ValuationTables_Austria_Annuities.R deleted 100644 → 0
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# frame_files = lapply(sys.frames(), function(x) x$ofile)
# frame_files = Filter(Negate(is.null), frame_files)
# PATH <- dirname(frame_files[[length(frame_files)]])
# rm(frame_files)
# setwd(dirname(PATH))
# setwd("R")
library("openxlsx")
###############################################################################
### RR67 Rententafel für Männer, 3%
###############################################################################
rr67.data=openxlsx::read.xlsx("Tables/AVOe_R.xlsx",
sheet="OeVM59-61 RR67", startRow = 3, colNames = TRUE);
rr67=valuationTable.period(
name="ÖVM 59/61 RR67", ages=rr67.data$Alter, deathProbs=rr67.data$qx
);
# rm(rr67.data);
###############################################################################
### EROM/EROF 85 and G 1985 (period and age-shifted generation)
###############################################################################
eromf.data=openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet="EROM-F Basistafeln", startRow = 3)
erom85.male=valuationTable.period(
name="EROM 85, male", ages=eromf.data$Alter, deathProbs=eromf.data$EROM.85
);
erom85.female=valuationTable.period(
name="EROF 85, female", ages=eromf.data$Alter, deathProbs=eromf.data$EROF.85
);
EROM.G1950.male=valuationTable.period(
name="EROM G 1950 Basistafel, male",
ages=eromf.data$Alter,
deathProbs=eromf.data$EROM.G1950,
baseYear=1950
);
EROF.G1950.female=valuationTable.period(
name="EROF G 1950 Basistafel, female",
ages=eromf.data$Alter,
deathProbs=eromf.data$EROF.G1950,
baseYear=1950
);
eromf.data.av=openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet="EROM-F G AV", startRow = 3, rowNames = TRUE, colNames = TRUE)
EROM.G1950.male.av=valuationTable.ageShift(
name="EROM G 1950 mit Altersverschiebung, male",
ages=eromf.data$Alter,
deathProbs=eromf.data$EROM.G1950,
ageShifts=eromf.data.av["Shift.M"],
baseYear=1950
);
EROF.G1950.female.av=valuationTable.ageShift(
name="EROF G 1950 mit Altersverschiebung, female",
ages=eromf.data$Alter,
deathProbs=eromf.data$EROF.G1950,
ageShifts=eromf.data.av["Shift.F"],
baseYear=1950
);
###############################################################################
# AVÖ 1996R exact (Male, Female), 1st-order only
###############################################################################
AVOe1996R.exakt.data=openxlsx::read.xlsx("Tables/AVOe_R.xlsx",
sheet="AVOe 1996R exakt", startRow = 3, cols=c(1:6, 8:12));
AVOe1996R.exakt.data
AVOe1996R.trend.switching=function(year) {
if (year<=1971) {
15/(1991-year)
} else if (1971<year && year<1981) {
1+(year-1981)^2/(year-1991)/20
} else if (1981<=year && year<=2000) {
1
} else if (2000<year && year<2010) {
1-(year-2000)^2/(year-1991)/20
} else if (year>=2010) {
14/(year-1991)
}
}
AVÖ1996R.male=valuationTable.trendProjection(
name="AVÖ 1996R male",
ages=AVOe1996R.exakt.data$age, baseYear=1991,
deathProbs=AVOe1996R.exakt.data$qx1991 * AVOe1996R.exakt.data$factorM,
trend=AVOe1996R.exakt.data$trendM.long,
trend2=AVOe1996R.exakt.data$trendM.short,
dampingFunction=AVOe1996R.trend.switching
);
AVÖ1996R.female=valuationTable.trendProjection(
name="AVÖ 1996R female",
ages=AVOe1996R.exakt.data$age, baseYear=1991,
deathProbs=AVOe1996R.exakt.data$qy1991 * AVOe1996R.exakt.data$factorF,
trend=AVOe1996R.exakt.data$trendF.long,
trend2=AVOe1996R.exakt.data$trendF.short,
dampingFunction=AVOe1996R.trend.switching
);
AVÖ1996R.male.group=valuationTable.trendProjection(
name="AVÖ 1996R male, group",
ages=AVOe1996R.exakt.data$age, baseYear=1991,
deathProbs=AVOe1996R.exakt.data$qx1991 * AVOe1996R.exakt.data$factorMG,
trend=AVOe1996R.exakt.data$trendM.long,
trend2=AVOe1996R.exakt.data$trendM.short,
dampingFunction=AVOe1996R.trend.switching
);
AVÖ1996R.female.group=valuationTable.trendProjection(
name="AVÖ 1996R female, group",
ages=AVOe1996R.exakt.data$age, baseYear=1991,
deathProbs=AVOe1996R.exakt.data$qy1991 * AVOe1996R.exakt.data$factorFG,
trend=AVOe1996R.exakt.data$trendF.long,
trend2=AVOe1996R.exakt.data$trendF.short,
dampingFunction=AVOe1996R.trend.switching
);
###############################################################################
# AVÖ 2005R exact (Male, Female, unisex)
# gender-specific tables also have 2nd-order tables, unisex only 1st-order table
###############################################################################
AVOe2005R.exakt.data=openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet="AVOe 2005R", startRow = 3, cols=c(1:7, 9:14, 16:18));
AVOe2005R.trend.damping=function(t) {
100*atan(t/100)
}
AVOe2005R_gen=function(nm, probs, trend) {
with(
AVOe2005R.exakt.data,
valuationTable.trendProjection(
name=nm,
ages=age, baseYear=2001,
deathProbs=AVOe2005R.exakt.data[[probs]], trend=AVOe2005R.exakt.data[[trend]],
dampingFunction=AVOe2005R.trend.damping
)
)
}
AVOe2005R.male =AVOe2005R_gen("AVÖ 2005R male (exact), loaded", "qx2001", "trendM");
AVOe2005R.female=AVOe2005R_gen("AVÖ 2005R female (exact), loaded", "qy2001", "trendF");
AVOe2005R.unisex=AVOe2005R_gen("AVÖ 2005R unisex (exact), loaded", "qu2001", "trendU");
AVOe2005R.male.unloaded =AVOe2005R_gen("AVÖ 2005R male (exact), unloaded", "qx2001.2Ord", "trendM.2Ord");
AVOe2005R.female.unloaded=AVOe2005R_gen("AVÖ 2005R female (exact), unloaded", "qy2001.2Ord", "trendF.2Ord");
AVOe2005R.male.group =AVOe2005R_gen("AVÖ 2005R male group (exact), loaded", "qx2001G", "trendM");
AVOe2005R.female.group=AVOe2005R_gen("AVÖ 2005R female group (exact), loaded", "qy2001G", "trendF");
AVOe2005R.unisex.group=AVOe2005R_gen("AVÖ 2005R unisex group (exact), loaded", "qu2001G", "trendU");
AVOe2005R.male.nodamping = undampenTrend(AVOe2005R.male);
AVOe2005R.female.nodamping = undampenTrend(AVOe2005R.female);
AVOe2005R.unisex.nodamping = undampenTrend(AVOe2005R.unisex);
AVOe2005R.male.nodamping.unloaded = undampenTrend(AVOe2005R.male.unloaded);
AVOe2005R.female.nodamping.unloaded = undampenTrend(AVOe2005R.female.unloaded);
AVOe2005R.male.nodamping.group = undampenTrend(AVOe2005R.male.group);
AVOe2005R.female.nodamping.group = undampenTrend(AVOe2005R.female.group);
AVOe2005R.unisex.nodamping.group = undampenTrend(AVOe2005R.unisex.group);
###############################################################################
#AVÖ 2005R with age-shifting (Male, Female, unisex), 1st-order only
###############################################################################
AVOe2005R.av.base = openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet="AVOe 2005R AV Basistafel", startRow = 3, rowNames = FALSE);
AVOe2005R.av.verschiebung = openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet="AVOe 2005R AV Verschiebung", startRow = 3, rowNames = TRUE);
AVOe2005R_gen.av=function(nm, probs, shft) {
valuationTable.ageShift(
name=nm,
ages=AVOe2005R.av.base$age,
deathProbs=AVOe2005R.av.base[[probs]],
ageShifts=na.omit(AVOe2005R.av.verschiebung[shft])
)
}
AVOe2005R.male.av =AVOe2005R_gen.av("AVÖ 2005R male (age-shifted), loaded", "qx1965", "shiftM");
AVOe2005R.female.av=AVOe2005R_gen.av("AVÖ 2005R female (age-shifted), loaded", "qy1965", "shiftF");
AVOe2005R.unisex.av=AVOe2005R_gen.av("AVÖ 2005R unisex (age-shifted), loaded", "qu1972", "shiftU");
AVOe2005R.male.group.av =AVOe2005R_gen.av("AVÖ 2005R male group (age-shifted), loaded", "qx1965G", "shiftMG");
AVOe2005R.female.group.av=AVOe2005R_gen.av("AVÖ 2005R female group (age-shifted), loaded", "qy1965G", "shiftFG");
AVOe2005R.unisex.group.av=AVOe2005R_gen.av("AVÖ 2005R unisex group (age-shifted), loaded", "qu1972G", "shiftUG");
###############################################################################
# options("scipen" = 3, "digits"=10)
# t=AVOe2005R.unisex;
# deathProbabilities(t, YOB=1981)
# plotValuationTables(mort.AT.census.1869.male, mort.AT.census.1869.female, mort.AT.census.2011.male, mort.AT.census.2011.female, AVOe2005R.male, AVOe2005R.female, YOB=1972,title="Vergleich österreichische Sterbetafeln, YOB=1972 (bei Generationentafeln)")
#
# plotValuationTables(mort.AT.census.2001.male, AVOe2005R.male, YOB=1972, title="Vergleich österreichische Sterbetafeln")
plotValuationTables(getCohortTable(AVOe2005R.male, YOB=1972), getCohortTable(AVOe2005R.male, YOB=2016), title="Vergleich österreichische Sterbetafeln")
data/Austria_Annuities_AVOe1996R.csv 0 → 100644
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AVÖ 1996R Generationentafeln,,,,,,,,,,
,Männer,,,,,Frauen,,,,
age,qx1991,trendM long,trendM short,factorMG,factorM,qy1991,trendF long,trendF short,factorFG,factorF
0,0.0084686,0.045780839322034,0.062792362,0.8,0.8,0.0067104,0.049763218294738,0.049763218294738,0.8,0.8
1,0.0005477,0.0455624991333896,0.046734646,0.8,0.8,0.0005155,0.0463588998451518,0.0463588998451518,0.8,0.8
2,0.0004539,0.0445589383626771,0.046695544,0.8,0.8,0.0004117,0.045568312499516,0.045568312499516,0.8,0.8
3,0.0003739,0.0429663572317243,0.046656442,0.8,0.8,0.0003175,0.044453791013854,0.044453791013854,0.8,0.8
4,0.0003086,0.0410116158440628,0.046617341,0.8,0.8,0.0002377,0.0431260876112459,0.0431260876112459,0.8,0.8
5,0.0002571,0.0389562493886482,0.046578239,0.8,0.8,0.0001803,0.0417058756205811,0.0417058756205811,0.8,0.8
6,0.0002165,0.0371009184621877,0.046539137,0.8,0.8,0.0001413,0.0403248573727864,0.0403248573727864,0.8,0.8
7,0.0001897,0.0357903018243682,0.046500036,0.8,0.8,0.0001183,0.0391269753222444,0.0391269753222444,0.8,0.8
8,0.0001677,0.035418452426267,0.046460934,0.8,0.8,0.0001066,0.0382697173174771,0.0382697173174771,0.8,0.8
9,0.0001532,0.0354636812851688,0.046421832,0.8,0.8,0.0001012,0.0375563071959882,0.0375563071959882,0.8,0.8
10,0.0001495,0.0350190955,0.04638273,0.8,0.8,0.0000992,0.03667394928,0.0369984,0.8,0.8
11,0.0001565,0.0339619677534714,0.046343629,0.8,0.8,0.0001005,0.0356215813061646,0.036432,0.8,0.8
12,0.0001716,0.0321995390445823,0.046304527,0.8,0.8,0.000107,0.0344046249791861,0.0359904,0.8,0.8
13,0.0001979,0.0296723266432079,0.046265425,0.8,0.8,0.0001205,0.0330356125475103,0.035616,0.8,0.8
14,0.000262,0.026357509630484,0.045430811,0.8,0.8,0.0001495,0.0315648,0.0353285088,0.8,0.8
15,0.0003961,0.0222722741962857,0.043005172,0.8,0.8,0.000207,0.0301152,0.0350799264,0.8,0.8
16,0.0006237,0.01928,0.038988508,0.8,0.8,0.0002816,0.0290592,0.034831344,0.8,0.8
17,0.0009624,0.01751,0.03474,0.8,0.8,0.0003294,0.02808,0.0345827616,0.8,0.8
18,0.0013468,0.01673,0.0319,0.8,0.8,0.0003751,0.0274848,0.0343341792,0.8,0.8
19,0.0015062,0.01634,0.03063,0.8,0.8,0.0004028,0.0271584,0.0340855968,0.8,0.8
20,0.0014673,0.016,0.03006854,0.8,0.8,0.0004047,0.02680536,0.0338370144,0.8,0.8
21,0.0013739,0.01591546,0.02988563,0.8,0.8,0.0003893,0.0265969632,0.033588432,0.8,0.8
22,0.0012821,0.01582696,0.02970619,0.8,0.8,0.0003696,0.0263868576,0.033341616,0.8,0.8
23,0.0012317,0.01573457,0.02952998,0.8,0.8,0.0003553,0.0261750336,0.0330964608,0.8,0.8
24,0.0012004,0.01563835,0.02935677,0.8,0.8,0.0003446,0.0259614912,0.0328528608,0.8,0.8
25,0.0011736,0.01553836,0.02918632,0.8,0.8,0.0003383,0.0257462016,0.0326107008,0.8,0.8
26,0.001159,0.01543467,0.02901841,0.8,0.8,0.0003501,0.0255291552,0.0323698752,0.8,0.8
27,0.0011614,0.01532733,0.0288528,0.8,0.8,0.0003747,0.0253103616,0.0321302688,0.8,0.8
28,0.0011766,0.01521642,0.02868925,0.8,0.8,0.0004077,0.025089792,0.0318917664,0.8,0.8
29,0.0012047,0.015102,0.02852754,0.8,0.8,0.0004413,0.0248674368,0.031654272,0.8,0.8
30,0.0012464,0.01498413,0.02836743,0.8,0.8,0.0004719,0.0246433056,0.0314176704,0.8,0.8
31,0.0013043,0.01486287,0.02820869,0.8,0.8,0.0005098,0.02441736,0.031181856,0.8,0.8
32,0.0013837,0.01473829,0.02805109,0.8,0.8,0.0005565,0.0241896096,0.030946704,0.8,0.8
33,0.0014691,0.01461044,0.02789439,0.8,0.8,0.0006056,0.0239600352,0.030712128,0.8,0.8
34,0.0015485,0.01447941,0.02773836,0.8,0.8,0.000655,0.0237286272,0.0304779936,0.8,0.8
35,0.0016246,0.01434524,0.02758277,0.8,0.8,0.0007127,0.023495376,0.0302442144,0.8,0.8
36,0.0017037,0.014208,0.02742738,0.8,0.8,0.0007879,0.023260272,0.0300106656,0.8,0.8
37,0.0017987,0.01406776,0.02727197,0.8,0.8,0.0008761,0.0230233056,0.029777232,0.8,0.8
38,0.001941,0.01392457,0.0271163,0.8,0.8,0.0009748,0.0227844576,0.0295438272,0.8,0.8
39,0.0021488,0.01377851,0.02696014,0.8,0.8,0.0010854,0.0225437376,0.0293103168,0.8,0.8
40,0.0024129,0.01362963,0.02680325,0.8,0.8,0.0012084,0.0223011168,0.0290766048,0.8,0.8
41,0.0027102,0.013478,0.0266454,0.8,0.8,0.0013513,0.0220565856,0.028842576,0.8,0.8
42,0.003018,0.01332368,0.02648636,0.8,0.8,0.0015136,0.021810144,0.0286081344,0.8,0.8
43,0.0033313,0.01316674,0.0263259,0.8,0.8,0.0016826,0.0215617824,0.0283731456,0.8,0.8
44,0.0036547,0.01300724,0.02616378,0.8,0.8,0.0018489,0.021311472,0.0281375232,0.8,0.8
45,0.0039948,0.01284524,0.02599978,0.8,0.8,0.0020112,0.0210592224,0.0279011424,0.8,0.8
46,0.0043519,0.0126808,0.02583365,0.8,0.8,0.0021721,0.0208050144,0.0276638976,0.8,0.8
47,0.0047251,0.012514,0.02566517,0.8,0.8,0.0023381,0.0205488384,0.0274256832,0.8,0.8
48,0.0051126,0.01234489,0.0254941,0.8,0.8,0.0025167,0.0202906848,0.027186384,0.8,0.8
49,0.005521,0.01217353,0.02532021,0.8,0.8,0.0027108,0.020030544,0.0269458944,0.8,0.8
50,0.0059701,0.012,0.02514327,0.8,0.8,0.0029238,0.0197684064,0.0267041088,0.8,0.8
51,0.0064826,0.01182435,0.02496304,0.78,0.78,0.0031576,0.0195042528,0.0264609024,0.78,0.78
52,0.0070816,0.01164665,0.0247793,0.76,0.76,0.0034169,0.0192380832,0.0262161792,0.76,0.76
53,0.0077817,0.01146695,0.0245918,0.74,0.74,0.0037033,0.0189698784,0.025969824,0.74,0.74
54,0.0085851,0.01128533,0.02440032,0.72,0.72,0.0040175,0.0186996384,0.0257217312,0.72,0.72
55,0.0094913,0.01110185,0.02420463,0.7,0.7,0.0043607,0.018427344,0.0254717856,0.7,0.7
56,0.0104969,0.01091657,0.02400449,0.68,0.68,0.0047324,0.0181529952,0.0252198816,0.68,0.68
57,0.0115953,0.01072956,0.02379966,0.67,0.66,0.0051322,0.0178765728,0.024965904,0.67,0.66
58,0.0127831,0.01054087,0.02358992,0.67,0.64,0.0055619,0.0175980672,0.0247097472,0.67,0.64
59,0.0140661,0.01035057,0.02337503,0.67,0.62,0.0060314,0.0173174592,0.0244513056,0.67,0.62
60,0.0154529,0.01015873,0.02315477,0.67,0.6,0.0065642,0.0170347584,0.024190464,0.67,0.6
61,0.0169422,0.00996541,0.02292889,0.67567911,0.606497636946269,0.0071846,0.0167499456,0.0239271168,0.67018259,0.601563894964179
62,0.0185334,0.00977067,0.02269716,0.68138971,0.613047339086567,0.0079052,0.0164630112,0.0236611488,0.67058979,0.603330634943284
63,0.0202352,0.00957457,0.02245936,0.68713219,0.619649655519403,0.0087342,0.016173936,0.0233924544,0.67122483,0.605304540725373
64,0.0220656,0.00937719,0.02221525,0.69290692,0.626305120525373,0.009681,0.0158827104,0.0231209184,0.67209093,0.607489951056716
65,0.0240385,0.00917857,0.02196459,0.69871429,0.633014289597015,0.0107563,0.015589344,0.0228464352,0.67319131,0.609891231597015
66,0.0261662,0.00897879,0.02170716,0.70455467,0.639777703325373,0.0119709,0.015293808,0.0225688992,0.67452918,0.612512765838806
67,0.0284651,0.00877792,0.02144272,0.71042844,0.646595914495522,0.0133398,0.0149960928,0.0222881952,0.67610778,0.615358991408955
68,0.0309598,0.008576,0.02117104,0.716336,0.653469497313433,0.0148837,0.0146961888,0.0220042176,0.67793031,0.618434336525373
69,0.0336572,0.00837311,0.02089188,0.72227771,0.660398992755224,0.0166275,0.014394096,0.0217168512,0.68,0.62174328358209
70,0.0365059,0.00816931,0.02060502,0.72825397,0.667384981462687,0.018601,0.0140897952,0.0214259904,0.68232007,0.62529033280597
71,0.0395594,0.00796467,0.02031021,0.73426514,0.674428010680597,0.0208415,0.0137832672,0.02113152,0.68489374,0.629080011337313
72,0.0429954,0.00775924,0.02000724,0.74031162,0.681528667486567,0.0233941,0.0134745216,0.0208333344,0.68772422,0.633116864023881
73,0.0470208,0.00755309,0.01969586,0.74639378,0.688687514620896,0.026311,0.0131635392,0.020531328,0.69081475,0.637405490223881
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111,0.6742548,0.00018814,0.000925,1,1,0.6668048,0.0003897024,0.0061862688,1,1
112,0.6962566,0.00018814,0.000925,1,1,0.6902582,0.0003897024,0.0061862688,1,1
113,1,0,0,1,1,1,0,0,1,1
data/Austria_Annuities_AVOe2005R.csv 0 → 100644
+ 125
− 0
View file @ 43a07d08
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data/Austria_Annuities_AVOe2005R_AVBasis.csv 0 → 100644
+ 124
− 0
View file @ 43a07d08
"Rententafel AVÖ 2005-R mit Altersverschiebung, Basistafel",,,,,,
,,,,,,
age,qx1965,qx1965G,qy1965,qy1965G,qu1972,qu1972G
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data/Austria_Annuities_AVOe2005R_AVShifts.csv 0 → 100644
+ 121
− 0
View file @ 43a07d08
"Rententafel AVÖ 2005-R mit AV, Verschiebung",,,,,,
,,,,,,
YOB,shiftM,shiftMG,shiftF,shiftFG,shiftU,shiftUG
1905,4,4,5,5,,
1906,4,4,5,5,,
1907,4,4,5,5,,
1908,4,4,5,5,,
1909,4,4,5,5,,
1910,4,4,5,5,,
1911,4,4,5,5,,
1912,4,4,5,5,,
1913,4,4,5,5,,
1914,4,4,5,5,,
1915,4,4,5,5,,
1916,4,4,5,5,,
1917,4,4,5,5,,
1918,4,4,5,5,,
1919,4,4,5,5,,
1920,4,4,5,5,,
1921,4,4,5,5,,
1922,4,4,4,5,,
1923,4,4,4,5,,
1924,4,4,4,5,,
1925,4,4,4,4,,
1926,4,4,4,4,,
1927,4,4,4,4,,
1928,4,4,4,4,,
1929,4,4,4,4,,
1930,4,4,4,4,5,5
1931,4,4,4,4,5,5
1932,4,4,4,4,4,5
1933,4,4,4,4,4,5
1934,4,4,4,4,4,5
1935,4,4,4,4,4,4
1936,4,4,3,4,4,4
1937,4,4,3,4,4,4
1938,3,4,3,3,4,4
1939,3,4,3,3,4,4
1940,3,4,3,3,4,4
1941,3,3,3,3,4,4
1942,3,3,3,3,4,4
1943,3,3,3,3,4,4
1944,3,3,3,3,4,4
1945,3,3,3,3,4,4
1946,3,3,2,2,3,4
1947,2,3,2,2,3,4
1948,2,2,2,2,3,3
1949,2,2,2,2,3,3
1950,2,2,2,2,3,3
1951,2,2,2,2,3,3
1952,2,2,2,2,3,3
1953,2,2,1,2,3,3
1954,1,2,1,1,2,3
1955,1,1,1,1,2,2
1956,1,1,1,1,2,2
1957,1,1,1,1,2,2
1958,1,1,1,1,2,2
1959,1,1,1,1,2,2
1960,1,1,1,1,2,2
1961,1,1,0,0,1,2
1962,0,0,0,0,1,1
1963,0,0,0,0,1,1
1964,0,0,0,0,1,1
1965,0,0,0,0,1,1
1966,0,0,0,0,1,1
1967,0,0,0,0,1,1
1968,0,0,0,0,1,1
1969,0,-1,0,0,0,0
1970,-1,-1,-1,-1,0,0
1971,-1,-1,-1,-1,0,0
1972,-1,-1,-1,-1,0,0
1973,-1,-1,-1,-1,0,0
1974,-1,-1,-1,-1,0,0
1975,-1,-1,-1,-1,0,0
1976,-1,-1,-1,-1,0,-1
1977,-1,-1,-1,-1,-1,-1
1978,-1,-2,-1,-1,-1,-1
1979,-2,-2,-1,-1,-1,-1
1980,-2,-2,-1,-2,-1,-1
1981,-2,-2,-2,-2,-1,-1
1982,-2,-2,-2,-2,-1,-1
1983,-2,-2,-2,-2,-1,-1
1984,-2,-2,-2,-2,-1,-1
1985,-2,-2,-2,-2,-2,-2
1986,-2,-2,-2,-2,-2,-2
1987,-2,-2,-2,-2,-2,-2
1988,-2,-3,-2,-2,-2,-2
1989,-2,-3,-2,-2,-2,-2
1990,-3,-3,-2,-2,-2,-2
1991,-3,-3,-2,-2,-2,-2
1992,-3,-3,-2,-3,-2,-2
1993,-3,-3,-2,-3,-2,-2
1994,-3,-3,-3,-3,-2,-3
1995,-3,-3,-3,-3,-3,-3
1996,-3,-3,-3,-3,-3,-3
1997,-3,-3,-3,-3,-3,-3
1998,-3,-3,-3,-3,-3,-3
1999,-3,-3,-3,-3,-3,-3
2000,-3,-4,-3,-3,-3,-3
2001,-3,-4,-3,-3,-3,-3
2002,-3,-4,-3,-3,-3,-3
2003,-4,-4,-3,-3,-3,-3
2004,-4,-4,-3,-3,-3,-4
2005,-4,-4,-3,-3,-3,-4
2006,-4,-4,-3,-3,-4,-4
2007,-4,-4,-3,-3,-4,-4
2008,-4,-4,-3,-4,-4,-4
2009,-4,-4,-3,-4,-4,-4
2010,-4,-4,-3,-4,-4,-4
2011,-4,-4,-4,-4,-4,-4
2012,-4,-4,-4,-4,-4,-4
2013,-4,-4,-4,-4,-4,-4
2014,-4,-4,-4,-4,-4,-4
2015,-4,-5,-4,-4,-4,-5
2016,-4,-5,-4,-4,-4,-5
2017,-4,-5,-4,-4,-4,-5
2018,-4,-5,-4,-4,-5,-5
2019,-4,-5,-4,-4,-5,-5
2020,-4,-5,-4,-4,-5,-5
2021,,,,,-5,-5
2022,,,,,-5,-5
data/Austria_Annuities_EROMF.csv 0 → 100644
+ 104
− 0
View file @ 43a07d08
EROM/F 85 und G 1950,,,,
,,,,
Alter,EROM 85,EROF 85,EROM G1950,EROF G1950
0,0.001555,0.001161,0.056385,0.049623
1,0.000104,0.000076,0.003974,0.003965
2,0.000066,0.000044,0.001922,0.002197
3,0.000064,0.000044,0.001448,0.001571
4,0.000061,0.000043,0.001102,0.001123
5,0.000059,0.000046,0.000855,0.000811
6,0.000062,0.000052,0.000683,0.000607
7,0.000067,0.000052,0.000568,0.000472
8,0.000069,0.000041,0.000489,0.000388
9,0.000058,0.000035,0.000445,0.000346
10,0.000051,0.000034,0.000417,0.000327
11,0.000047,0.000036,0.000402,0.000318
12,0.000054,0.00004,0.000414,0.000329
13,0.000075,0.000049,0.000457,0.000357
14,0.00012,0.000074,0.000533,0.00041
15,0.000288,0.000126,0.0007,0.000488
16,0.000707,0.000176,0.000959,0.000561
17,0.001192,0.000178,0.001226,0.000599
18,0.001506,0.000163,0.001445,0.000613
19,0.001426,0.000144,0.001544,0.000614
20,0.001201,0.000123,0.001546,0.0006
21,0.001014,0.000109,0.001493,0.00058
22,0.000905,0.000103,0.001429,0.000567
23,0.000841,0.000101,0.00137,0.000559
24,0.000804,0.000101,0.00132,0.000548
25,0.000771,0.000099,0.001286,0.000538
26,0.000751,0.000102,0.00127,0.000531
27,0.000738,0.000107,0.00126,0.000529
28,0.000727,0.000116,0.00125,0.000533
29,0.00072,0.000126,0.001243,0.000537
30,0.000717,0.00014,0.001242,0.000549
31,0.000724,0.000167,0.001244,0.000581
32,0.00074,0.000212,0.001254,0.000634
33,0.000777,0.000271,0.001282,0.0007
34,0.000837,0.000332,0.001333,0.000767
35,0.000923,0.000388,0.001414,0.00083
36,0.001035,0.000429,0.001522,0.000883
37,0.001172,0.000455,0.001653,0.000923
38,0.001328,0.000469,0.001802,0.000951
39,0.001488,0.000484,0.00196,0.000978
40,0.001664,0.000513,0.00214,0.001019
41,0.001874,0.000562,0.002347,0.001079
42,0.002125,0.000636,0.002586,0.001164
43,0.002415,0.000731,0.002862,0.00127
44,0.002722,0.000843,0.003163,0.001395
45,0.00302,0.000955,0.00348,0.001522
46,0.003322,0.001066,0.003817,0.00165
47,0.00363,0.00117,0.004172,0.001773
48,0.003954,0.001276,0.004546,0.001897
49,0.004303,0.001389,0.004943,0.002027
50,0.004675,0.001517,0.00536,0.002168
51,0.005077,0.001662,0.005802,0.002321
52,0.005513,0.001823,0.006271,0.002492
53,0.005974,0.002017,0.006861,0.002682
54,0.006453,0.002227,0.007266,0.002895
55,0.006935,0.00245,0.007774,0.003122
56,0.00751,0.002733,0.008357,0.003407
57,0.008153,0.003025,0.008995,0.003696
58,0.00883,0.003319,0.009664,0.003985
59,0.009523,0.00363,0.010349,0.004293
60,0.010214,0.003952,0.011035,0.004612
61,0.010931,0.004296,0.01174,0.004952
62,0.011766,0.004669,0.012548,0.005311
63,0.01278,0.005045,0.013518,0.005664
64,0.014024,0.005436,0.014703,0.00602
65,0.015509,0.005885,0.016114,0.006423
66,0.017316,0.006454,0.017827,0.00693
67,0.0195,0.007056,0.019899,0.00755
68,0.02226,0.008007,0.02253,0.008296
69,0.024924,0.009034,0.025065,0.009194
70,0.027873,0.010291,0.027873,0.010291
71,0.030984,0.012087,0.030828,0.011889
72,0.034618,0.014084,0.034296,0.013646
73,0.039138,0.016299,0.038646,0.015574
74,0.04403,0.01895,0.043369,0.017882
75,0.049069,0.021999,0.048214,0.020522
76,0.054402,0.025426,0.053334,0.023466
77,0.060066,0.029369,0.058767,0.026845
78,0.065698,0.033989,0.064104,0.030818
79,0.070961,0.039334,0.068857,0.035439
80,0.077578,0.045567,0.075003,0.04088
81,0.08515,0.052855,0.082123,0.047332
82,0.092985,0.061274,0.089452,0.05489
83,0.100797,0.070806,0.096662,0.063557
84,0.108483,0.081295,0.103614,0.073208
85,0.116472,0.092534,0.110674,0.083629
86,0.125489,0.103852,0.118831,0.094214
87,0.135064,0.115687,0.127367,0.105352
88,0.145196,0.128148,0.136349,0.117174
89,0.155959,0.141245,0.14587,0.129704
90,0.167458,0.154955,0.156053,0.142921
91,0.179812,0.169251,0.167005,0.156701
92,0.193049,0.183961,0.178783,0.171138
93,0.207073,0.198844,0.19125,0.185625
94,0.221648,0.213664,0.204103,0.199948
95,0.236393,0.228073,0.216848,0.213628
96,0.249382,0.243347,0.227565,0.227733
97,0.261807,0.257983,0.237257,0.240739
98,0.273532,0.271884,0.24572,0.252414
99,0.284475,0.284874,0.252829,0.26264
100,1,1,1,1
data/Austria_Annuities_EROMF_AV.csv 0 → 100644
+ 54
− 0
View file @ 43a07d08
EROM/F G 1950 AV,,
,,
YOB,Shift M,Shift F
1920,1,2
1921,1,2
1922,1,2
1923,1,2
1924,1,2
1925,1,2
1926,1,2
1927,1,2
1928,1,2
1929,1,2
1930,1,2
1931,1,2
1932,1,2
1933,1,2
1934,1,2
1935,1,1
1936,1,1
1937,1,1
1938,1,1
1939,1,1
1940,1,1
1941,0,1
1942,0,1
1943,0,1
1944,0,1
1945,0,0
1946,0,0
1947,0,0
1948,0,0
1949,0,0
1950,0,0
1951,0,0
1952,0,0
1953,0,0
1954,0,0
1955,0,0
1956,0,-1
1957,0,-1
1958,0,-1
1959,0,-1
1960,-1,-1
1961,-1,-1
1962,-1,-1
1963,-1,-1
1964,-1,-1
1965,-1,-1
1966,-1,-1
1967,-1,-1
1968,-1,-2
1969,-1,-2
1970,-1,-2
data/Austria_Annuities_RR67.csv 0 → 100644
+ 103
− 0
View file @ 43a07d08
Sterbetafel ÖV 1959/61 Männer - RR67,
,
Alter,qx
0,0
1,0
2,0
3,0
4,0
5,0
6,0
7,0
8,0
9,0
10,0
11,0.00018
12,0.00018
13,0.00018
14,0.00018
15,0.00018
16,0.00018
17,0.00018
18,0.00018
19,0.00018
20,0.00018
21,0.00018
22,0.00018
23,0.00018
24,0.00018
25,0.00018
26,0.00054
27,0.00135
28,0.00072
29,0.00135
30,0.00135
31,0.00036
32,0.00108
33,0.00018
34,0.00109
35,0.00109
36,0.00118
37,0.00009
38,0.00118
39,0.00109
40,0.00118
41,0.00118
42,0.00128
43,0.00137
44,0.00146
45,0.00174
46,0.00183
47,0.0022
48,0.00239
49,0.00277
50,0.00315
51,0.00371
52,0.00438
53,0.00515
54,0.00602
55,0.00928
56,0.00812
57,0.00925
58,0.0106
59,0.01464
60,0.01366
61,0.01547
62,0.01746
63,0.02216
64,0.02159
65,0.02403
66,0.02955
67,0.02907
68,0.03504
69,0.03496
70,0.04171
71,0.04167
72,0.0457
73,0.05357
74,0.0546
75,0.06377
76,0.06568
77,0.07588
78,0.07909
79,0.09091
80,0.09519
81,0.10893
82,0.11837
83,0.12513
84,0.14148
85,0.15083
86,0.16914
87,0.18315
88,0.19531
89,0.21359
90,0.22593
91,0.24561
92,0.26216
93,0.27507
94,0.3004
95,0.31638
96,0.33058
97,0.35802
98,0.38462
99,1
data/Austria_Census_Female.csv 0 → 100644
+ 117
− 0
View file @ 43a07d08
Census-Mortality Tables Austrian Females,,,,,,,,,,,,,
Source: Statistik Austria. Alexander Hanika,,,,,,,,,,,,,
,,,,,,,,,,,,,
x,1868/71,1879/82,1889/92,1899/1902,1909/12,1930/33,1949/51,1959/61,1970/72,1980/82,1990/92,2000/02,2010/12
0,0.250079,0.228973,0.227292,0.193085,0.171577,0.09245,0.05838,0.03275,0.02221,0.011066,0.0067104,0.0037607,0.00315084679007483
1,0.065939,0.068601,0.06288,0.048788,0.03834,0.01307,0.00494,0.0024,0.00152,0.000834,0.0005155,0.0003266,0.000192018169121108
2,0.032547,0.035385,0.028086,0.021157,0.015533,0.00598,0.0029,0.00134,0.00094,0.000488,0.0004117,0.0002108,0.000153216363390695
3,0.020914,0.025331,0.018255,0.013599,0.009669,0.0042,0.00217,0.00092,0.00063,0.000413,0.0003175,0.0001318,0.000119276498535962
4,0.018679,0.021452,0.014977,0.009565,0.007471,0.00381,0.00161,0.00075,0.00049,0.000349,0.0002377,0.0000997,0.0000941594039056861
5,0.010797,0.014053,0.009872,0.007163,0.005955,0.00343,0.00119,0.00062,0.00041,0.000302,0.0001803,0.0000858,0.0000799712218996731
6,0.009808,0.012476,0.008759,0.006602,0.004822,0.00299,0.0009,0.00051,0.0004,0.000273,0.0001413,0.0000851,0.0000724099375899447
7,0.007791,0.009985,0.006881,0.005388,0.004229,0.00265,0.00071,0.00042,0.00036,0.000239,0.0001183,0.00009,0.000068729035037648
8,0.007104,0.008813,0.006224,0.004369,0.003515,0.00231,0.00061,0.00036,0.00029,0.000198,0.0001066,0.0000926,0.0000687922571228714
9,0.00584,0.00584,0.00584,0.00584,0.00584,0.00584,0.00584,0.00584,0.00584,0.000178,0.0001012,0.0000934,0.0000703647570474122
10,0.004904,0.006154,0.004488,0.00373,0.002913,0.00175,0.00056,0.0003,0.00026,0.000175,0.0000992,0.0000962,0.0000728690707671526
11,0.004478,0.005547,0.00452,0.003405,0.002911,0.0016,0.00056,0.00029,0.00026,0.000179,0.0001005,0.0001015,0.0000784469743615419
12,0.004294,0.005264,0.00455,0.003384,0.00299,0.00151,0.0006,0.0003,0.00032,0.000194,0.000107,0.0001097,0.000088109729718312
13,0.004327,0.005217,0.004756,0.0035,0.003172,0.0015,0.00066,0.00035,0.00035,0.000225,0.0001205,0.0001293,0.000102893130564081
14,0.004593,0.005381,0.005098,0.003743,0.003428,0.00165,0.00074,0.0004,0.00038,0.000287,0.0001495,0.0001669,0.000123370583919784
15,0.005022,0.00567,0.005489,0.004067,0.003735,0.00194,0.00083,0.00046,0.00048,0.000387,0.000207,0.0002082,0.000147785364895035
16,0.005521,0.006028,0.005874,0.004438,0.004075,0.00221,0.00093,0.00051,0.00058,0.000478,0.0002816,0.0002483,0.00017278537971716
17,0.006025,0.006404,0.006215,0.004823,0.00444,0.00248,0.00104,0.00055,0.00061,0.000511,0.0003294,0.0002988,0.00019323207203506
18,0.006507,0.006762,0.006504,0.005192,0.004812,0.00276,0.00114,0.00059,0.00061,0.000518,0.0003751,0.0003345,0.000209189893718415
19,0.00695,0.007095,0.006765,0.005529,0.005176,0.00312,0.00124,0.00062,0.00061,0.000513,0.0004028,0.000338,0.000225729587416606
20,0.007367,0.007398,0.007027,0.005837,0.005512,0.00326,0.00133,0.00065,0.00059,0.000498,0.0004047,0.0003234,0.000241013742318063
21,0.007761,0.007675,0.007298,0.006118,0.005797,0.00336,0.0014,0.00068,0.0006,0.000485,0.0003893,0.0003082,0.000250390348885728
22,0.008106,0.007932,0.007576,0.006374,0.006029,0.0034,0.00146,0.0007,0.0006,0.000484,0.0003696,0.0002973,0.000252026946125503
23,0.008382,0.00818,0.007845,0.006621,0.006213,0.00354,0.00152,0.00071,0.0006,0.000491,0.0003553,0.0002831,0.000248050860207978
24,0.008604,0.008422,0.008072,0.006862,0.006366,0.00363,0.00156,0.00071,0.0006,0.000498,0.0003446,0.0002698,0.000244034105207991
25,0.008762,0.008664,0.008253,0.007095,0.006499,0.00362,0.00162,0.00073,0.0006,0.000505,0.0003383,0.0002695,0.000243913624074764
26,0.008888,0.008909,0.008403,0.007323,0.006627,0.00356,0.00166,0.00076,0.00061,0.000518,0.0003501,0.0002799,0.000247876736285943
27,0.009032,0.009142,0.008553,0.007545,0.006749,0.0036,0.0017,0.0008,0.00063,0.000536,0.0003747,0.0002906,0.000254497609083566
28,0.009191,0.009354,0.008735,0.007756,0.006868,0.00374,0.00173,0.00085,0.00065,0.000562,0.0004077,0.0003004,0.000262337129229031
29,0.009357,0.009538,0.008968,0.00796,0.006992,0.00393,0.00176,0.00092,0.00067,0.000589,0.0004413,0.0003092,0.000271590228578445
30,0.009548,0.009703,0.009233,0.008169,0.007127,0.00396,0.0018,0.00098,0.00071,0.000624,0.0004719,0.0003225,0.000283175146631143
31,0.009768,0.009875,0.009504,0.008378,0.007278,0.00398,0.00184,0.00106,0.00076,0.000684,0.0005098,0.0003531,0.00029830078004775
32,0.010017,0.010076,0.009763,0.008578,0.007447,0.004,0.00188,0.00112,0.00083,0.000768,0.0005565,0.0003966,0.000316232515317261
33,0.010342,0.010308,0.009992,0.008765,0.007632,0.00403,0.00192,0.00119,0.00091,0.000867,0.0006056,0.000451,0.000336746652698102
34,0.01073,0.010553,0.010196,0.008932,0.007823,0.00413,0.00199,0.00127,0.001,0.000968,0.000655,0.0005,0.000363174110084129
35,0.011131,0.010784,0.010386,0.009084,0.008019,0.00442,0.00209,0.00136,0.0011,0.001065,0.0007127,0.0005394,0.00039475431608024
36,0.011508,0.010979,0.010572,0.009237,0.008217,0.00474,0.00223,0.00147,0.00121,0.001155,0.0007879,0.000585,0.000430384646355252
37,0.011822,0.011133,0.010751,0.009399,0.008414,0.00484,0.0024,0.00159,0.00132,0.001235,0.0008761,0.0006533,0.000468281595420265
38,0.012031,0.01127,0.010929,0.009567,0.008607,0.00485,0.00259,0.00174,0.00144,0.001306,0.0009748,0.0007412,0.000509520671248531
39,0.012156,0.011407,0.011114,0.009737,0.008795,0.00487,0.00279,0.00189,0.00157,0.00138,0.0010854,0.0008412,0.000557354785106964
40,0.012251,0.011551,0.011314,0.009904,0.008969,0.00514,0.00299,0.00206,0.00172,0.001472,0.0012084,0.0009502,0.000616969061717308
41,0.012347,0.011705,0.011536,0.01007,0.009132,0.00538,0.00319,0.00223,0.00189,0.001589,0.0013513,0.0010633,0.000693863273653744
42,0.012481,0.011869,0.011777,0.010251,0.009294,0.00554,0.00339,0.00241,0.00208,0.001736,0.0015136,0.0011789,0.000788184271090969
43,0.012681,0.012055,0.012026,0.010466,0.009474,0.00598,0.0036,0.00258,0.00228,0.00191,0.0016826,0.0012999,0.000898503487345335
44,0.012952,0.012297,0.012278,0.010731,0.009698,0.00646,0.00384,0.00276,0.0025,0.002109,0.0018489,0.0014259,0.001022288576879
45,0.013291,0.012636,0.012547,0.011059,0.009995,0.00706,0.00414,0.00297,0.00275,0.002324,0.0020112,0.001565,0.00115724255592473
46,0.01371,0.013086,0.012861,0.011455,0.01038,0.00749,0.00449,0.00323,0.00302,0.002552,0.0021721,0.0017304,0.00130173494817301
47,0.014214,0.013649,0.013255,0.011932,0.010854,0.00795,0.00488,0.00353,0.00332,0.002786,0.0023381,0.0019207,0.0014559125201251
48,0.014818,0.014316,0.013765,0.012503,0.011415,0.00812,0.0053,0.00386,0.00364,0.003032,0.0025167,0.0021238,0.00161882663211953
49,0.015553,0.015053,0.014409,0.013181,0.012054,0.00871,0.00576,0.00423,0.00399,0.003297,0.0027108,0.0023362,0.00178993824416907
50,0.016455,0.015833,0.015177,0.01397,0.012771,0.0094,0.00623,0.00462,0.00435,0.003581,0.0029238,0.0025657,0.00196937308928953
51,0.017531,0.016658,0.016057,0.014863,0.013577,0.01016,0.0067,0.00505,0.00472,0.003883,0.0031576,0.0028073,0.00215927578904445
52,0.018769,0.01755,0.017031,0.015843,0.01448,0.01062,0.00717,0.00553,0.00507,0.004207,0.0034169,0.0030534,0.00236201832168177
53,0.020133,0.018549,0.018087,0.016904,0.015483,0.01115,0.00768,0.00595,0.0054,0.004565,0.0037033,0.0032958,0.00258257870864176
54,0.021569,0.01972,0.019254,0.018049,0.016587,0.01218,0.00826,0.00644,0.00576,0.004967,0.0040175,0.0035351,0.00282674288099027
55,0.023061,0.02113,0.020588,0.019305,0.017791,0.01315,0.00894,0.00701,0.0062,0.005415,0.0043607,0.0037768,0.00310218819367269
56,0.024651,0.022804,0.022144,0.020706,0.019107,0.01449,0.00968,0.00765,0.00677,0.005942,0.0047324,0.0040245,0.00341206272528798
57,0.02643,0.02473,0.023992,0.022282,0.020573,0.01583,0.01046,0.00835,0.00744,0.006489,0.0051322,0.0042739,0.00375470733104562
58,0.028521,0.026891,0.026193,0.024074,0.022234,0.01695,0.01135,0.00909,0.00819,0.007076,0.0055619,0.0045302,0.00413233376028644
59,0.031053,0.029255,0.028769,0.026107,0.024137,0.0183,0.01241,0.00992,0.00905,0.007738,0.0060314,0.0048119,0.0045463708993423
60,0.034115,0.03181,0.031706,0.028398,0.026314,0.01991,0.01372,0.01089,0.01004,0.008496,0.0065642,0.0051423,0.00499340572840824
61,0.037649,0.034566,0.034939,0.030992,0.028765,0.02207,0.01526,0.01204,0.01119,0.009355,0.0071846,0.005533,0.00546279919555108
62,0.04154,0.037539,0.038355,0.033911,0.031457,0.02381,0.01696,0.01333,0.01246,0.010294,0.0079052,0.0059968,0.00594904929729518
63,0.045655,0.040714,0.041839,0.037146,0.034376,0.02607,0.01887,0.01471,0.0138,0.011306,0.0087342,0.0065535,0.00645263954126601
64,0.049881,0.044087,0.045325,0.040699,0.037516,0.02886,0.02106,0.01627,0.01533,0.012423,0.009681,0.007213,0.00697579779624276
65,0.05411,0.04766,0.048856,0.044565,0.040916,0.03239,0.02357,0.01812,0.01712,0.013701,0.0107563,0.007982,0.00752055171955155
66,0.058558,0.051505,0.052574,0.048687,0.044655,0.03592,0.02634,0.02036,0.01927,0.015184,0.0119709,0.008879,0.00809368770883296
67,0.06352,0.055755,0.056699,0.053098,0.048829,0.03959,0.02935,0.02291,0.02172,0.016882,0.0133398,0.0099125,0.00871223695433519
68,0.069206,0.060605,0.06148,0.057891,0.053501,0.04297,0.03265,0.02573,0.02442,0.018828,0.0148837,0.0110837,0.00940158464074007
69,0.075862,0.066241,0.067115,0.063143,0.058686,0.047,0.03637,0.02889,0.02744,0.021093,0.0166275,0.012407,0.0101909301313094
70,0.083546,0.0728,0.07372,0.068975,0.064359,0.05122,0.04058,0.03248,0.03086,0.023751,0.018601,0.0139145,0.0111139981673978
71,0.091947,0.080287,0.081254,0.075521,0.070486,0.05682,0.04517,0.03659,0.03477,0.027074,0.0208415,0.0156392,0.0122097876096495
72,0.100765,0.088489,0.089556,0.082761,0.077039,0.06421,0.05007,0.04109,0.03904,0.030682,0.0233941,0.0176233,0.0135237279748655
73,0.109945,0.097137,0.098294,0.090586,0.084016,0.07104,0.05546,0.04595,0.04362,0.034651,0.026311,0.0199112,0.0151067724567435
74,0.119383,0.105943,0.107193,0.098912,0.091502,0.07908,0.06153,0.05132,0.04869,0.039249,0.0296518,0.0225557,0.0170149901705156
75,0.128923,0.11472,0.116036,0.107624,0.099605,0.08597,0.06845,0.05736,0.05443,0.044495,0.0334821,0.0256061,0.0193094958193007
76,0.138906,0.123403,0.124896,0.11654,0.108313,0.09367,0.07627,0.06424,0.06103,0.050389,0.0378743,0.0291105,0.0220561458435687
77,0.149681,0.132504,0.134146,0.125661,0.117677,0.10181,0.08488,0.07194,0.06843,0.057009,0.0429098,0.0331236,0.0253247965493915
78,0.161507,0.142688,0.144497,0.135159,0.127755,0.11029,0.09419,0.08035,0.07652,0.06445,0.0486813,0.0377085,0.0291894241767978
79,0.174899,0.154506,0.156656,0.14525,0.138521,0.12185,0.10412,0.08951,0.08537,0.072705,0.055294,0.0429438,0.033727621833522
80,0.190122,0.168328,0.171023,0.15628,0.150015,0.13156,0.11459,0.09939,0.09506,0.081854,0.0628663,0.0489131,0.0390195056292805
81,0.206748,0.183784,0.187472,0.168596,0.162227,0.14435,0.12552,0.11003,0.10568,0.091965,0.0715314,0.0557097,0.0451460161311372
82,0.223945,0.19971,0.204935,0.182137,0.174999,0.15959,0.13696,0.1214,0.11852,0.103075,0.0814414,0.0634426,0.0521874839283418
83,0.240956,0.214886,0.221688,0.196254,0.188162,0.17653,0.14901,0.13349,0.13159,0.115177,0.0927706,0.0722388,0.0602220671414176
84,0.256561,0.228525,0.233556,0.210049,0.201685,0.18736,0.1615,0.14646,0.14489,0.128059,0.1057192,0.0822385,0.0693235884112821
85,0.269637,0.239857,0.240417,0.222569,0.215554,0.20212,0.17456,0.16027,0.15842,0.141622,0.1195473,0.0936,0.0795591892530993
86,0.278798,0.250129,0.246873,0.234271,0.22879,0.21861,0.18821,0.17528,0.17218,0.15584,0.1333896,0.106504,0.0909871698328793
87,0.284376,0.262272,0.259156,0.244958,0.24165,0.23369,0.20247,0.19174,0.18617,0.170705,0.1474734,0.1204218,0.103654135689782
88,0.286855,0.277479,0.285071,0.256439,0.255164,0.24581,0.21738,0.20865,0.2004,0.186321,0.1620554,0.1353127,0.117591969606498
89,0.286844,0.298226,0.325255,0.27079,0.271466,0.25996,0.23296,0.22603,0.21486,0.202713,0.1773108,0.1517418,0.132815238244346
90,0.28972,0.306885,0.291388,0.277883,0.283701,0.27942,0.24925,0.24388,0.22955,0.219895,0.1935492,0.1698118,0.149318696224486
91,,,,,,0.30021,0.26627,0.26223,0.24447,0.23787,0.2110395,0.1895022,0.16707527949112
92,,,,,,0.30811,0.28406,0.28108,0.25962,0.256563,0.2299318,0.2108727,0.186034692558165
93,,,,,,0.3116,0.30266,0.30045,0.27501,0.275859,0.2501231,0.2338888,0.206122548851386
94,,,,,,0.32117,0.32209,0.32035,0.29062,0.295637,0.2714322,0.2583034,0.227240276570904
95,,,,,,0.35801,0.34241,0.34081,0.30647,0.315727,0.2935812,0.2836835,0.249265952492919
96,,,,,,0.39828,0.36364,0.36182,0.32255,0.335996,0.3162299,0.3095368,0.272056114190465
97,,,,,,0.415,0.38583,0.38341,0.33886,0.356369,0.3391737,0.3357864,0.295448461910108
98,,,,,,0.434,0.40902,0.4056,0.3554,0.37678,0.3623051,0.3624251,0.319265280434416
99,,,,,,0.455,0.43326,0.42839,0.37218,0.397213,0.3855587,0.3893823,0.343317560442081
100,,,,,,0.479,0.4586,0.45182,0.38918,1,1,0.4165604,1
101,,,,,,,,,,,,0.4438524,
102,,,,,,,,,,,,0.4711769,
103,,,,,,,,,,,,0.4985037,
104,,,,,,,,,,,,0.5258296,
105,,,,,,,,,,,,0.5531587,
106,,,,,,,,,,,,0.580489,
107,,,,,,,,,,,,0.6078194,
108,,,,,,,,,,,,0.6351498,
109,,,,,,,,,,,,0.66248,
110,,,,,,,,,,,,0.6898099,
111,,,,,,,,,,,,0.7171393,
112,,,,,,,,,,,,0.744468,
data/Austria_Census_Male.csv 0 → 100644
+ 117
− 0
View file @ 43a07d08
Census-Mortality Tables Austrian Males,,,,,,,,,,,,,
Source: Statistik Austria. Alexander Hanika,,,,,,,,,,,,,
,,,,,,,,,,,,,
x,1868/71,1879/82,1889/92,1899/1902,1909/12,1930/33,1949/51,1959/61,1970/72,1980/82,1990/92,2000/02,2010/12
0,0.297731,0.274107,0.26678,0.230381,0.205894,0.1154,0.07518,0.04207,0.0293,0.015329,0.0084686,0.005343,0.00394905716260243
1,0.068279,0.070981,0.066802,0.049499,0.038888,0.014,0.0056,0.0028,0.00171,0.001088,0.0005477,0.0003452,0.000268187201429239
2,0.033583,0.037701,0.029168,0.020716,0.01563,0.00637,0.00283,0.00156,0.00108,0.000609,0.0004539,0.0002639,0.000213916794000993
3,0.022415,0.026774,0.019087,0.013365,0.0099,0.00444,0.00222,0.00115,0.00079,0.000524,0.0003739,0.0001984,0.00016542160363432
4,0.019419,0.022588,0.016738,0.009748,0.007152,0.00403,0.00175,0.00097,0.00071,0.000451,0.0003086,0.0001512,0.000124328897954087
5,0.010429,0.014015,0.009422,0.007376,0.005718,0.00341,0.0014,0.00085,0.00064,0.000392,0.0002571,0.0001295,0.0000914455713648781
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63,0.048862,0.044851,0.044341,0.042434,0.042321,0.03446,0.02988,0.03011,0.02856,0.0233,0.0202352,0.0143678,0.0131839431733137
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79,0.170718,0.166417,0.166923,0.154566,0.146625,0.13511,0.11957,0.11433,0.11678,0.107795,0.0850452,0.0682233,0.0540783137118937
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91,,,,,,0.33292,0.29491,0.2838,0.2683,0.264435,0.2390753,0.2221826,0.200088269846977
92,,,,,,0.33672,0.31397,0.30179,0.28273,0.281777,0.2583662,0.2440479,0.219345334689177
93,,,,,,0.35505,0.33386,0.32055,0.29737,0.29994,0.2788847,0.2672621,0.239596707006356
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95,,,,,,0.39,0.37626,0.36052,0.32731,0.338075,0.3222411,0.3162331,0.282747906996984
96,,,,,,0.4125,0.39886,0.38181,0.3426,0.357614,0.3444248,0.3414812,0.305440646120197
97,,,,,,0.435,0.42243,0.404,0.35811,0.377275,0.3665705,0.3670574,0.328716241821161
98,,,,,,0.46,0.44703,0.42715,0.37383,0.39699,0.3886051,0.3928725,0.352438339954358
99,,,,,,0.485,0.4727,0.45129,0.38978,0.416711,0.4105795,0.4188563,0.376461610299673
100,,,,,,0.51,0.49948,0.47647,0.40593,1,1,0.4449421,1
101,,,,,,,,,,,,0.4710857,
102,,,,,,,,,,,,0.4972566,
103,,,,,,,,,,,,0.5234342,
104,,,,,,,,,,,,0.5496121,
105,,,,,,,,,,,,0.57579,
106,,,,,,,,,,,,0.6019685,
107,,,,,,,,,,,,0.628148,
108,,,,,,,,,,,,0.6543293,
109,,,,,,,,,,,,0.6805127,
110,,,,,,,,,,,,0.706699,
111,,,,,,,,,,,,0.7328886,
112,,,,,,,,,,,,0.7590821,
data/ValuationTables_Austria_Annuities.R 0 → 100644
+ 199
− 0
View file @ 43a07d08
stopifnot(require(methods), require(utils), require(ValuationTables)) # ValuationTable classes; new; Excel reader
###############################################################################
### RR67 Rententafel für Männer, 3%
###############################################################################
rr67.data = utils::read.csv("Tables/Austria_Annuities_RR67.csv", skip=2)
rr67 = ValuationTables::valuationTable_period(
name = "ÖVM 59/61 RR67", ages = rr67.data$Alter, deathProbs = rr67.data$qx
);
rm(rr67.data);
###############################################################################
### EROM/EROF 85 and G 1985 (period and age-shifted generation)
###############################################################################
# eromf.data = openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet = "EROM-F Basistafeln", startRow = 3)
eromf.data = utils::read.csv("Tables/Austria_Annuities_EROMF.csv", skip=2)
erom85.male = new("valuationTable_period",
name = "EROM 85, male", ages = eromf.data$Alter, deathProbs = eromf.data$EROM.85
);
erom85.female = new("valuationTable_period",
name = "EROF 85, female", ages = eromf.data$Alter, deathProbs = eromf.data$EROF.85
);
EROM.G1950.male = new("valuationTable_period",
name = "EROM G 1950 Basistafel, male",
ages = eromf.data$Alter,
deathProbs = eromf.data$EROM.G1950,
baseYear = 1950
);
EROF.G1950.female = new("valuationTable_period",
name = "EROF G 1950 Basistafel, female",
ages = eromf.data$Alter,
deathProbs = eromf.data$EROF.G1950,
baseYear = 1950
);
# eromf.data.av = openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet = "EROM-F G AV", startRow = 3, rowNames = TRUE, colNames = TRUE)
eromf.data.av = utils::read.csv("Tables/Austria_Annuities_EROMF_AV.csv", skip=2)
EROM.G1950.male.av = valuationTable_ageShift(
name = "EROM G 1950 mit Altersverschiebung, male",
ages = eromf.data$Alter,
deathProbs = eromf.data$EROM.G1950,
ageShifts = eromf.data.av["Shift.M"],
baseYear = 1950
);
EROF.G1950.female.av = valuationTable_ageShift(
name = "EROF G 1950 mit Altersverschiebung, female",
ages = eromf.data$Alter,
deathProbs = eromf.data$EROF.G1950,
ageShifts = eromf.data.av["Shift.F"],
baseYear = 1950
);
rm(eromf.data, eromf.data.av)
###############################################################################
# AVÖ 1996R exact (Male, Female), 1st-order only
###############################################################################
# AVOe1996R.exakt.data = openxlsx::read.xlsx("Tables/AVOe_R.xlsx",
# sheet = "AVOe 1996R exakt", startRow = 3, cols = c(1:6, 8:12));
AVOe1996R.exakt.data = utils::read.csv("Tables/Austria_Annuities_AVOe1996R.csv", skip=2)
AVOe1996R.trend.switching = function(year) {
if (year <= 1971) {
15/(1991-year)
} else if (1971 < year && year < 1981) {
1+(year-1981)^2/(year-1991)/20
} else if (1981 <= year && year <= 2000) {
1
} else if (2000 < year && year < 2010) {
1-(year-2000)^2/(year-1991)/20
} else if (year >= 2010) {
14/(year-1991)
}
}
AVÖ1996R.male = new("valuationTable_trendProjection",
name = "AVÖ 1996R male",
ages = AVOe1996R.exakt.data$age, baseYear = 1991,
deathProbs = AVOe1996R.exakt.data$qx1991 * AVOe1996R.exakt.data$factorM,
trend = AVOe1996R.exakt.data$trendM.long,
trend2 = AVOe1996R.exakt.data$trendM.short,
dampingFunction = AVOe1996R.trend.switching
);
AVÖ1996R.female = new("valuationTable_trendProjection",
name = "AVÖ 1996R female",
ages = AVOe1996R.exakt.data$age, baseYear = 1991,
deathProbs = AVOe1996R.exakt.data$qy1991 * AVOe1996R.exakt.data$factorF,
trend = AVOe1996R.exakt.data$trendF.long,
trend2 = AVOe1996R.exakt.data$trendF.short,
dampingFunction = AVOe1996R.trend.switching
);
AVÖ1996R.male.group = new("valuationTable_trendProjection",
name = "AVÖ 1996R male, group",
ages = AVOe1996R.exakt.data$age, baseYear = 1991,
deathProbs = AVOe1996R.exakt.data$qx1991 * AVOe1996R.exakt.data$factorMG,
trend = AVOe1996R.exakt.data$trendM.long,
trend2 = AVOe1996R.exakt.data$trendM.short,
dampingFunction = AVOe1996R.trend.switching
);
AVÖ1996R.female.group = new("valuationTable_trendProjection",
name = "AVÖ 1996R female, group",
ages = AVOe1996R.exakt.data$age, baseYear = 1991,
deathProbs = AVOe1996R.exakt.data$qy1991 * AVOe1996R.exakt.data$factorFG,
trend = AVOe1996R.exakt.data$trendF.long,
trend2 = AVOe1996R.exakt.data$trendF.short,
dampingFunction = AVOe1996R.trend.switching
);
rm(AVOe1996R.exakt.data)
###############################################################################
# AVÖ 2005R exact (Male, Female, unisex)
# gender-specific tables also have 2nd-order tables, unisex only 1st-order table
###############################################################################
# AVOe2005R.exakt.data = openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet = "AVOe 2005R", startRow = 3, cols = c(1:7, 9:14, 16:18));
AVOe2005R.exakt.data = utils::read.csv("Tables/Austria_Annuities_AVOe2005R.csv", skip = 2);
AVOe2005R.trend.damping = function(t) {
100*atan(t/100)
}
AVOe2005R_gen = function(nm, probs, trend) {
with(
AVOe2005R.exakt.data,
new("valuationTable_trendProjection",
name = nm,
ages = age, baseYear = 2001,
deathProbs = AVOe2005R.exakt.data[[probs]], trend = AVOe2005R.exakt.data[[trend]],
dampingFunction = AVOe2005R.trend.damping
)
)
}
AVOe2005R.male = AVOe2005R_gen("AVÖ 2005R male (exact), loaded", "qx2001", "trendM");
AVOe2005R.female = AVOe2005R_gen("AVÖ 2005R female (exact), loaded", "qy2001", "trendF");
AVOe2005R.unisex = AVOe2005R_gen("AVÖ 2005R unisex (exact), loaded", "qu2001", "trendU");
AVOe2005R.male.unloaded = AVOe2005R_gen("AVÖ 2005R male (exact), unloaded", "qx2001.2Ord", "trendM.2Ord");
AVOe2005R.female.unloaded = AVOe2005R_gen("AVÖ 2005R female (exact), unloaded", "qy2001.2Ord", "trendF.2Ord");
AVOe2005R.male.group = AVOe2005R_gen("AVÖ 2005R male group (exact), loaded", "qx2001G", "trendM");
AVOe2005R.female.group = AVOe2005R_gen("AVÖ 2005R female group (exact), loaded", "qy2001G", "trendF");
AVOe2005R.unisex.group = AVOe2005R_gen("AVÖ 2005R unisex group (exact), loaded", "qu2001G", "trendU");
AVOe2005R.male.nodamping = undampenTrend(AVOe2005R.male);
AVOe2005R.female.nodamping = undampenTrend(AVOe2005R.female);
AVOe2005R.unisex.nodamping = undampenTrend(AVOe2005R.unisex);
AVOe2005R.male.nodamping.unloaded = undampenTrend(AVOe2005R.male.unloaded);
AVOe2005R.female.nodamping.unloaded = undampenTrend(AVOe2005R.female.unloaded);
AVOe2005R.male.nodamping.group = undampenTrend(AVOe2005R.male.group);
AVOe2005R.female.nodamping.group = undampenTrend(AVOe2005R.female.group);
AVOe2005R.unisex.nodamping.group = undampenTrend(AVOe2005R.unisex.group);
###############################################################################
#AVÖ 2005R with age-shifting (Male, Female, unisex), 1st-order only
###############################################################################
AVOe2005R.av.base = openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet = "AVOe 2005R AV Basistafel", startRow = 3, rowNames = FALSE);
AVOe2005R.av.verschiebung = openxlsx::read.xlsx("Tables/AVOe_R.xlsx", sheet = "AVOe 2005R AV Verschiebung", startRow = 3, rowNames = TRUE);
AVOe2005R_gen.av = function(nm, probs, shft) {
new("valuationTable_ageShift",
name = nm,
ages = AVOe2005R.av.base$age,
deathProbs = AVOe2005R.av.base[[probs]],
ageShifts = na.omit(AVOe2005R.av.verschiebung[shft])
)
}
AVOe2005R.male.av = AVOe2005R_gen.av("AVÖ 2005R male (age-shifted), loaded", "qx1965", "shiftM");
AVOe2005R.female.av = AVOe2005R_gen.av("AVÖ 2005R female (age-shifted), loaded", "qy1965", "shiftF");
AVOe2005R.unisex.av = AVOe2005R_gen.av("AVÖ 2005R unisex (age-shifted), loaded", "qu1972", "shiftU");
AVOe2005R.male.group.av = AVOe2005R_gen.av("AVÖ 2005R male group (age-shifted), loaded", "qx1965G", "shiftMG");
AVOe2005R.female.group.av = AVOe2005R_gen.av("AVÖ 2005R female group (age-shifted), loaded", "qy1965G", "shiftFG");
AVOe2005R.unisex.group.av = AVOe2005R_gen.av("AVÖ 2005R unisex group (age-shifted), loaded", "qu1972G", "shiftUG");
###############################################################################
# options("scipen" = 3, "digits" = 10)
# t = AVOe2005R.unisex;
# deathProbabilities(t, YOB = 1981)
# plotValuationTables(mort.AT.census.1869.male, mort.AT.census.1869.female, mort.AT.census.2011.male, mort.AT.census.2011.female, AVOe2005R.male, AVOe2005R.female, YOB = 1972,title = "Vergleich österreichische Sterbetafeln, YOB = 1972 (bei Generationentafeln)")
#
# plotValuationTables(mort.AT.census.2001.male, AVOe2005R.male, YOB = 1972, title = "Vergleich österreichische Sterbetafeln")
# plotValuationTables(getCohortTable(AVOe2005R.male, YOB = 1972), getCohortTable(AVOe2005R.male, YOB = 2016), title = "Vergleich österreichische Sterbetafeln")
R/ValuationTables_Austria_Census.R → data/ValuationTables_Austria_Census.R
+ 6
− 4
View file @ 43a07d08
...@@ -5,6 +5,8 @@ ...@@ -5,6 +5,8 @@
# setwd(dirname(PATH)) # setwd(dirname(PATH))
library("openxlsx") library("openxlsx")
# library("ggplot2")
library("ValuationTables")
...@@ -20,7 +22,7 @@ a.vz.dataF = openxlsx::read.xlsx("Tables/A_Volkszaehlungen.xlsx", sheet="Austria ...@@ -20,7 +22,7 @@ a.vz.dataF = openxlsx::read.xlsx("Tables/A_Volkszaehlungen.xlsx", sheet="Austria
censtable = function(data, name, qslot, baseYear=1900) { censtable = function(data, name, qslot, baseYear=1900) {
qx=data[names(data)==qslot]; qx=data[names(data)==qslot];
ix=complete.cases(qx); ix=complete.cases(qx);
valuationTable.period(name=name, ages=data$x[ix], deathProbs=qx[ix,], baseYear=baseYear) valuationTable_period(name=name, ages=data$x[ix], deathProbs=qx[ix,], baseYear=baseYear)
} }
mort.AT.census.1869.male = censtable(a.vz.dataM, name="ÖVSt 1868/71 M", baseYear=1869, qslot="1868/71"); mort.AT.census.1869.male = censtable(a.vz.dataM, name="ÖVSt 1868/71 M", baseYear=1869, qslot="1868/71");
...@@ -51,7 +53,7 @@ mort.AT.census.1991.female = censtable(a.vz.dataF, name="ÖVSt 1990/92 F", bas ...@@ -51,7 +53,7 @@ mort.AT.census.1991.female = censtable(a.vz.dataF, name="ÖVSt 1990/92 F", bas
mort.AT.census.2001.female = censtable(a.vz.dataF, name="ÖVSt 2000/02 F", baseYear=2001, qslot="2000/02"); mort.AT.census.2001.female = censtable(a.vz.dataF, name="ÖVSt 2000/02 F", baseYear=2001, qslot="2000/02");
mort.AT.census.2011.female = censtable(a.vz.dataF, name="ÖVSt 2010/2012 F", baseYear=2011, qslot="2010/12"); mort.AT.census.2011.female = censtable(a.vz.dataF, name="ÖVSt 2010/2012 F", baseYear=2011, qslot="2010/12");
mort.AT.census.2001.unisex = valuationTable.mixed(table1=mort.AT.census.2001.male, table2=mort.AT.census.2001.female) mort.AT.census.2001.unisex = valuationTable_mixed(table1=mort.AT.census.2001.male, table2=mort.AT.census.2001.female)
mort.AT.census.ALL.male = makeQxDataFrame( mort.AT.census.ALL.male = makeQxDataFrame(
mort.AT.census.1869.male, mort.AT.census.1869.male,
...@@ -87,5 +89,5 @@ rm(a.vz.dataM, a.vz.dataF, censtable) ...@@ -87,5 +89,5 @@ rm(a.vz.dataM, a.vz.dataF, censtable)
############################################################################### ###############################################################################
plotValuationTables(mort.AT.census.ALL.male, title="Vergleich österreichische Sterbetafeln, Männer", legend.position=c(1,0)) # plotValuationTables(mort.AT.census.ALL.male, title="Vergleich österreichische Sterbetafeln, Männer", legend.position=c(1,0))
plotValuationTables(mort.AT.census.ALL.female, title="Vergleich österreichische Sterbetafeln, Frauen", legend.position=c(1,0)) # plotValuationTables(mort.AT.census.ALL.female, title="Vergleich österreichische Sterbetafeln, Frauen", legend.position=c(1,0))
R/ValuationTables_Germany_Annuities.R → data/ValuationTables_Germany_Annuities.R
+ 29
− 28
View file @ 43a07d08
frame_files = lapply(sys.frames(), function(x) x$ofile) # frame_files = lapply(sys.frames(), function(x) x$ofile)
frame_files = Filter(Negate(is.null), frame_files) # frame_files = Filter(Negate(is.null), frame_files)
PATH <- dirname(frame_files[[length(frame_files)]]) # PATH <- dirname(frame_files[[length(frame_files)]])
rm(frame_files) # rm(frame_files)
#
setwd(dirname(PATH)) # setwd(dirname(PATH))
library("gdata") library("gdata")
library("ValuationTables")
############################################################################### ###############################################################################
...@@ -13,23 +14,23 @@ library("gdata") ...@@ -13,23 +14,23 @@ library("gdata")
############################################################################### ###############################################################################
DAV1994R.exakt.data=read.xls( DAV1994R.exakt.data=read.xls(
"Tafeln/DAV_R.xls", "Tables/DAV_R.xls",
sheet="DAV 1994R", skip=2, #row.names=1, sheet="DAV 1994R", skip=2, #row.names=1,
col.names=c("age", col.names=c("age",
"qx2000", "qy2000", "trendM", "trendF", "qxAVbase1955", "qyAVbase1955", "qx2000", "qy2000", "trendM", "trendF", "qxAVbase1955", "qyAVbase1955",
"", "", "", "", "", "") "", "", "", "", "", "")
); );
DAV1994R.male=valuationTable.trendProjection( DAV1994R.male=valuationTable_trendProjection(
name="DAV 1994R male", name="DAV 1994R male",
ages=DAV1994R.exakt.data$age, baseYear=2000, ages=DAV1994R.exakt.data$age, baseYear=2000,
deathProbs=DAV1994R.exakt.data$qx2000, deathProbs=DAV1994R.exakt.data$qx2000,
trend=DAV1994R.exakt.data$trendM trend=DAV1994R.exakt.data$trendM
); );
DAV1994R.female=valuationTable.trendProjection( DAV1994R.female=valuationTable_trendProjection(
name="DAV 1994R female", name="DAV 1994R female",
ages=DAV1994R.exakt.data$age, baseYear=2000, ages=DAV1994R.exakt.data$age, baseYear=2000,
deathProbs=DAV1994R.exakt.data$qy2000, deathProbs=DAV1994R.exakt.data$qy2000,
trend=DAV1994R.exakt.data$trendF trend=DAV1994R.exakt.data$trendF
); );
...@@ -39,16 +40,16 @@ DAV1994R.female=valuationTable.trendProjection( ...@@ -39,16 +40,16 @@ DAV1994R.female=valuationTable.trendProjection(
############################################################################### ###############################################################################
DAV2004R.data.basistafeln=read.xls( DAV2004R.data.basistafeln=read.xls(
"Tafeln/DAV_2004_R.xls", "Tables/DAV_2004_R.xls",
sheet="Basistafeln", skip=3, #row.names=1, sheet="Basistafeln", skip=3, #row.names=1,
col.names=c("age", col.names=c("age",
"qxSel2Ord", "qySel2Ord", "qxAgg2Ord", "qyAgg2Ord", "qxSel2Ord", "qySel2Ord", "qxAgg2Ord", "qyAgg2Ord",
"qxSelBestand", "qySelBestand", "qxAggBestand", "qyAggBestand", "qxSelBestand", "qySelBestand", "qxAggBestand", "qyAggBestand",
"qxSel", "qySel", "qxAgg", "qyAgg") "qxSel", "qySel", "qxAgg", "qyAgg")
); );
DAV2004R.data.trend=read.xls( DAV2004R.data.trend=read.xls(
"Tafeln/DAV_2004_R.xls", "Tafeln/DAV_2004_R.xls",
sheet="Trends", skip=4, header=FALSE, #row.names=1, sheet="Trends", skip=4, header=FALSE, #row.names=1,
col.names=c("age", col.names=c("age",
"trend2Ord.male.start", "trend2Ord.female.start", "trend2Ord.male.start", "trend2Ord.female.start",
"trend2Ord.male.end", "trend2Ord.female.end", "trend2Ord.male.end", "trend2Ord.female.end",
...@@ -57,35 +58,35 @@ DAV2004R.data.trend=read.xls( ...@@ -57,35 +58,35 @@ DAV2004R.data.trend=read.xls(
"trend1Ord.male", "trend1Ord.female") "trend1Ord.male", "trend1Ord.female")
); );
DAV2004R.data.select=read.xls( DAV2004R.data.select=read.xls(
"Tafeln/DAV_2004_R.xls", "Tafeln/DAV_2004_R.xls",
sheet="Selektionsfaktoren", skip=2, header=FALSE, #row.names=1, sheet="Selektionsfaktoren", skip=2, header=FALSE, #row.names=1,
col.names=c("year", "SelectMale", "SelectFemale") col.names=c("year", "SelectMale", "SelectFemale")
); );
DAV2004R.data.av.grundtafeln=read.xls( DAV2004R.data.av.grundtafeln=read.xls(
"Tafeln/DAV_2004_R.xls", "Tafeln/DAV_2004_R.xls",
sheet="Grundtafeln", skip=3, #row.names=1, sheet="Grundtafeln", skip=3, #row.names=1,
col.names=c("age", col.names=c("age",
"qxBestand", "qyBestand", "qxBestand", "qyBestand",
"qxB20", "qyB20", "qxB20", "qyB20",
"qx1Ord", "qy1Ord") "qx1Ord", "qy1Ord")
); );
DAV2004R.data.av=read.xls( DAV2004R.data.av=read.xls(
"Tafeln/DAV_2004_R.xls", "Tafeln/DAV_2004_R.xls",
sheet="Altersverschiebungen", skip=1, row.names=1, sheet="Altersverschiebungen", skip=1, row.names=1,
col.names=c("YOB", "shiftMBestand", "shiftFBestand", col.names=c("YOB", "shiftMBestand", "shiftFBestand",
"shiftMB20", "shiftFB20", "shiftMB20", "shiftFB20",
"shiftM1Ord", "shiftF1Ord") "shiftM1Ord", "shiftF1Ord")
); );
DAV2004R.male=valuationTable.trendProjection( DAV2004R.male=valuationTable_trendProjection(
name="DAV 2004R male", name="DAV 2004R male",
ages=DAV2004R.exakt.data$age, baseYear=2000, ages=DAV2004R.exakt.data$age, baseYear=2000,
deathProbs=DAV2004R.exakt.data$qx2000, deathProbs=DAV2004R.exakt.data$qx2000,
trend=DAV2004R.exakt.data$trendM trend=DAV2004R.exakt.data$trendM
); );
DAV2004R.female=valuationTable.trendProjection( DAV2004R.female=valuationTable_trendProjection(
name="DAV 2004R female", name="DAV 2004R female",
ages=DAV2004R.exakt.data$age, baseYear=2000, ages=DAV2004R.exakt.data$age, baseYear=2000,
deathProbs=DAV2004R.exakt.data $qy2000, deathProbs=DAV2004R.exakt.data $qy2000,
trend=DAV2004R.exakt.data$trendF trend=DAV2004R.exakt.data$trendF
); );
R/ValuationTables_Germany_LifeInsurance.R → data/ValuationTables_Germany_LifeInsurance.R
+ 27
− 26
View file @ 43a07d08
frame_files = lapply(sys.frames(), function(x) x$ofile) # frame_files = lapply(sys.frames(), function(x) x$ofile)
frame_files = Filter(Negate(is.null), frame_files) # frame_files = Filter(Negate(is.null), frame_files)
PATH <- dirname(frame_files[[length(frame_files)]]) # PATH <- dirname(frame_files[[length(frame_files)]])
rm(frame_files) # rm(frame_files)
setwd(dirname(PATH)) # setwd(dirname(PATH))
library("gdata") library("gdata")
library("ValuationTables")
# DAV1994T (Male, Female), 1st-order and general mortality 1986/88 # DAV1994T (Male, Female), 1st-order and general mortality 1986/88
dav1994T.data=read.xls( dav1994T.data=read.xls(
"Tafeln/DAV_T.xls", "Tables/DAV_T.xls",
sheet=1, skip=1, #row.names=1, sheet=1, skip=1, #row.names=1,
col.names=c("age", col.names=c("age",
"", "", "", "",
"qx2", "qxKI", "qx", "qx2", "qxKI", "qx",
"", "", "", "", "", "",
"qy2", "qyKI", "qy" "qy2", "qyKI", "qy"
)); ));
DAV1994T.male=valuationTable.period( DAV1994T.male=valuationTable_period(
name="DAV 1994T male, loaded", name="DAV 1994T male, loaded",
ages=dav1994T.data$age, deathProbs=dav1994T.data$qx) ages=dav1994T.data$age, deathProbs=dav1994T.data$qx)
DAV1994T.male.2Ord=valuationTable.period( DAV1994T.male.2Ord=valuationTable_period(
name="DAV 1994T male, unloaded", name="DAV 1994T male, unloaded",
ages=dav1994T.data$age, deathProbs=dav1994T.data$qx2) ages=dav1994T.data$age, deathProbs=dav1994T.data$qx2)
DAV1994T.female=valuationTable.period( DAV1994T.female=valuationTable_period(
name="DAV 1994T female, loaded", name="DAV 1994T female, loaded",
ages=dav1994T.data$age, deathProbs=dav1994T.data$qy) ages=dav1994T.data$age, deathProbs=dav1994T.data$qy)
DAV1994T.female.2Ord=valuationTable.period( DAV1994T.female.2Ord=valuationTable_period(
name="DAV 1994T female, unloaded", name="DAV 1994T female, unloaded",
ages=dav1994T.data$age, deathProbs=dav1994T.data$qy2) ages=dav1994T.data$age, deathProbs=dav1994T.data$qy2)
...@@ -39,8 +40,8 @@ rm(DAV1994T.data) ...@@ -39,8 +40,8 @@ rm(DAV1994T.data)
###################################################### ######################################################
DAV2008T.data=read.xls( DAV2008T.data=read.xls(
"Tafeln/DAV_T.xls", "Tables/DAV_T.xls",
sheet=2, skip=2, #row.names=1, sheet=2, skip=2, #row.names=1,
col.names=c("age", "", "", "", col.names=c("age", "", "", "",
"qx2", "qx2NR", "qx2R", "qx2", "qx2NR", "qx2R",
"qx1", "qx1NR", "qx1R", "qx1", "qx1NR", "qx1R",
...@@ -50,44 +51,44 @@ DAV2008T.data=read.xls( ...@@ -50,44 +51,44 @@ DAV2008T.data=read.xls(
)); ));
### DAV 2008T Aggregat (smoker+non-smoker combined) ### DAV 2008T Aggregat (smoker+non-smoker combined)
DAV2008T.male=valuationTable.period( DAV2008T.male=valuationTable_period(
name="DAV 2008T male, loaded", name="DAV 2008T male, loaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx1) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx1)
DAV2008T.male.2Ord=valuationTable.period( DAV2008T.male.2Ord=valuationTable_period(
name="DAV 2008T male, unloaded", name="DAV 2008T male, unloaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx2) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx2)
DAV2008T.female=valuationTable.period( DAV2008T.female=valuationTable_period(
name="DAV 2008T female, loaded", name="DAV 2008T female, loaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy1) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy1)
DAV2008T.female.2Ord=valuationTable.period( DAV2008T.female.2Ord=valuationTable_period(
name="DAV 2008T female, unloaded", name="DAV 2008T female, unloaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy2) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy2)
### DAV 2008T Smoker ### DAV 2008T Smoker
DAV2008T.male.smoker=valuationTable.period( DAV2008T.male.smoker=valuationTable_period(
name="DAV 2008T male smoker, loaded", name="DAV 2008T male smoker, loaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx1R) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx1R)
DAV2008T.male.smoker.2Ord=valuationTable.period( DAV2008T.male.smoker.2Ord=valuationTable_period(
name="DAV 2008T male smoker, unloaded", name="DAV 2008T male smoker, unloaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx2R) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx2R)
DAV2008T.female.smoker=valuationTable.period( DAV2008T.female.smoker=valuationTable_period(
name="DAV 2008T female smoker, loaded", name="DAV 2008T female smoker, loaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy1R) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy1R)
DAV2008T.female.smoker.2Ord=valuationTable.period( DAV2008T.female.smoker.2Ord=valuationTable_period(
name="DAV 2008T female smoker, unloaded", name="DAV 2008T female smoker, unloaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy2R) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy2R)
### DAV 2008T Non-Smoker ### DAV 2008T Non-Smoker
DAV2008T.male.nonsmoker=valuationTable.period( DAV2008T.male.nonsmoker=valuationTable_period(
name="DAV 2008T male non-smoker, loaded", name="DAV 2008T male non-smoker, loaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx1NR) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx1NR)
DAV2008T.male.nonsmoker.2Ord=valuationTable.period( DAV2008T.male.nonsmoker.2Ord=valuationTable_period(
name="DAV 2008T male non-smoker, unloaded", name="DAV 2008T male non-smoker, unloaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx2NR) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qx2NR)
DAV2008T.female.nonsmoker=valuationTable.period( DAV2008T.female.nonsmoker=valuationTable_period(
name="DAV 2008T female non-smoker, loaded", name="DAV 2008T female non-smoker, loaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy1NR) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy1NR)
DAV2008T.female.nonsmoker.2Ord=valuationTable.period( DAV2008T.female.nonsmoker.2Ord=valuationTable_period(
name="DAV 2008T female non-smoker, unloaded", name="DAV 2008T female non-smoker, unloaded",
ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy2NR) ages=DAV2008T.data$age, deathProbs=DAV2008T.data$qy2NR)
......
R/ValuationTables_USA_Annuities.R → data/ValuationTables_USA_Annuities.R
+ 33
− 32
View file @ 43a07d08
frame_files = lapply(sys.frames(), function(x) x$ofile) # frame_files = lapply(sys.frames(), function(x) x$ofile)
frame_files = Filter(Negate(is.null), frame_files) # frame_files = Filter(Negate(is.null), frame_files)
PATH <- dirname(frame_files[[length(frame_files)]]) # PATH <- dirname(frame_files[[length(frame_files)]])
rm(frame_files) # rm(frame_files)
setwd(dirname(PATH)) # setwd(dirname(PATH))
library("gdata") library("gdata")
library("ValuationTables")
############################################################################### ###############################################################################
...@@ -12,25 +13,25 @@ library("gdata") ...@@ -12,25 +13,25 @@ library("gdata")
############################################################################### ###############################################################################
USA1971IAM.data=read.xls( USA1971IAM.data=read.xls(
"Tafeln/USA_Annuities.xls", "Tables/USA_Annuities.xls",
sheet="1971 IAM", skip=2, #row.names=1, sheet="1971 IAM", skip=2, #row.names=1,
col.names=c("age","qx", "qy", "B")); col.names=c("age","qx", "qy", "B"));
USA1971IAM.male=valuationTable.period ( USA1971IAM.male=valuationTable_period (
name="USA 1971 IAM, male", name="USA 1971 IAM, male",
ages=USA1971IAM.data$age, ages=USA1971IAM.data$age,
deathProbs=USA1971IAM.data$qx) deathProbs=USA1971IAM.data$qx)
USA1971IAM.female=valuationTable.period ( USA1971IAM.female=valuationTable_period (
name="USA 1971 IAM, female", name="USA 1971 IAM, female",
ages=USA1971IAM.data$age, ages=USA1971IAM.data$age,
deathProbs=USA1971IAM.data$qy) deathProbs=USA1971IAM.data$qy)
USA1971IAM.male.projected=valuationTable.improvementFactors ( USA1971IAM.male.projected=valuationTable_improvementFactors (
name="USA 1971 IAM, male", name="USA 1971 IAM, male",
ages=USA1971IAM.data$age, baseYear=1971, ages=USA1971IAM.data$age, baseYear=1971,
deathProbs=USA1971IAM.data$qx, deathProbs=USA1971IAM.data$qx,
improvement=USA1971IAM.data$B) improvement=USA1971IAM.data$B)
USA1971IAM.female.projected=valuationTable.improvementFactors ( USA1971IAM.female.projected=valuationTable_improvementFactors (
name="USA 1971 IAM, female", name="USA 1971 IAM, female",
ages=USA1971IAM.data$age, baseYear=1971, ages=USA1971IAM.data$age, baseYear=1971,
deathProbs=USA1971IAM.data$qy, deathProbs=USA1971IAM.data$qy,
...@@ -44,24 +45,24 @@ rm(USA1971IAM.data); ...@@ -44,24 +45,24 @@ rm(USA1971IAM.data);
############################################################################### ###############################################################################
USA1983a.data=read.xls( USA1983a.data=read.xls(
"Tafeln/USA_Annuities.xls", "Tables/USA_Annuities.xls",
sheet="1983a - GAM", skip=2, sheet="1983a - GAM", skip=2,
col.names=c("age","qx", "qy", "qxG", "qyG")); col.names=c("age","qx", "qy", "qxG", "qyG"));
USA1983a.male=valuationTable.period ( USA1983a.male=valuationTable_period (
name="USA 1983 Table a, male", name="USA 1983 Table a, male",
ages=USA1983a.data$age, ages=USA1983a.data$age,
deathProbs=USA1983a.data$qx) deathProbs=USA1983a.data$qx)
USA1983a.female=valuationTable.period ( USA1983a.female=valuationTable_period (
name="USA 1983 Table a, female", name="USA 1983 Table a, female",
ages=USA1983a.data$age, ages=USA1983a.data$age,
deathProbs=USA1983a.data$qy) deathProbs=USA1983a.data$qy)
USA1983GAM.male=valuationTable.period ( USA1983GAM.male=valuationTable_period (
name="USA 1983 GAM, male", name="USA 1983 GAM, male",
ages=USA1983a.data$age, ages=USA1983a.data$age,
deathProbs=USA1983a.data$qxG) deathProbs=USA1983a.data$qxG)
USA1983GAM.female=valuationTable.period ( USA1983GAM.female=valuationTable_period (
name="USA 1983 GAM, female", name="USA 1983 GAM, female",
ages=USA1983a.data$age, ages=USA1983a.data$age,
deathProbs=USA1983a.data$qyG) deathProbs=USA1983a.data$qyG)
...@@ -74,25 +75,25 @@ rm(USA1983a.data); ...@@ -74,25 +75,25 @@ rm(USA1983a.data);
############################################################################### ###############################################################################
USA1994GAM.data=read.xls( USA1994GAM.data=read.xls(
"Tafeln/USA_Annuities.xls", "Tables/USA_Annuities.xls",
sheet="1994 GAR", skip=2, sheet="1994 GAR", skip=2,
col.names=c("age","qx", "AAx", "qy", "AAy", "qxBasic", "qyBasic")); col.names=c("age","qx", "AAx", "qy", "AAy", "qxBasic", "qyBasic"));
USA1994GAM.male.basic=valuationTable.period ( USA1994GAM.male.basic=valuationTable_period (
name="USA 1994 GAM basic (unloaded), male", name="USA 1994 GAM basic (unloaded), male",
ages=USA1994GAM.data$age, ages=USA1994GAM.data$age,
deathProbs=USA1994GAM.data$qxBasic) deathProbs=USA1994GAM.data$qxBasic)
USA1994GAM.female.basic=valuationTable.period ( USA1994GAM.female.basic=valuationTable_period (
name="USA 1994 GAM basic (unloaded), female", name="USA 1994 GAM basic (unloaded), female",
ages=USA1994GAM.data$age, ages=USA1994GAM.data$age,
deathProbs=USA1994GAM.data$qyBasic) deathProbs=USA1994GAM.data$qyBasic)
USA1994GAR.male=valuationTable.improvementFactors ( USA1994GAR.male=valuationTable_improvementFactors (
name="USA 1994 GAM, male", name="USA 1994 GAM, male",
ages=USA1994GAM.data$age, ages=USA1994GAM.data$age,
deathProbs=USA1994GAM.data$qx, deathProbs=USA1994GAM.data$qx,
improvement=USA1994GAM.data$AAx) improvement=USA1994GAM.data$AAx)
USA1994GAR.female=valuationTable.improvementFactors ( USA1994GAR.female=valuationTable_improvementFactors (
name="USA 1994 GAM, female", name="USA 1994 GAM, female",
ages=USA1994GAM.data$age, ages=USA1994GAM.data$age,
deathProbs=USA1994GAM.data$qy, deathProbs=USA1994GAM.data$qy,
...@@ -106,24 +107,24 @@ rm(USA1994GAM.data); ...@@ -106,24 +107,24 @@ rm(USA1994GAM.data);
############################################################################### ###############################################################################
USAAnnuity2000.data=read.xls( USAAnnuity2000.data=read.xls(
"Tafeln/USA_Annuities.xls", "Tables/USA_Annuities.xls",
sheet="Annuity 2000", skip=2, #row.names=1, sheet="Annuity 2000", skip=2, #row.names=1,
col.names=c("age","qxBasic", "qyBasic", "qx", "qy")); col.names=c("age","qxBasic", "qyBasic", "qx", "qy"));
USAAnnuity2000.basic.male=valuationTable.period ( USAAnnuity2000.basic.male=valuationTable_period (
name="USA Annuity 2000 basic, male", name="USA Annuity 2000 basic, male",
ages=USAAnnuity2000.data$age, ages=USAAnnuity2000.data$age,
deathProbs=USAAnnuity2000.data$qxBasic) deathProbs=USAAnnuity2000.data$qxBasic)
USAAnnuity2000.basic.female=valuationTable.period ( USAAnnuity2000.basic.female=valuationTable_period (
name="USA Annuity 2000 basic, female", name="USA Annuity 2000 basic, female",
ages=USAAnnuity2000.data$age, ages=USAAnnuity2000.data$age,
deathProbs=USAAnnuity2000.data$qyBasic) deathProbs=USAAnnuity2000.data$qyBasic)
USAAnnuity2000.male.projected=valuationTable.period ( USAAnnuity2000.male.projected=valuationTable_period (
name="USA Annuity 2000, male", name="USA Annuity 2000, male",
ages=USAAnnuity2000.data$age, ages=USAAnnuity2000.data$age,
deathProbs=USAAnnuity2000.data$qx) deathProbs=USAAnnuity2000.data$qx)
USAAnnuity2000.female.projected=valuationTable.period ( USAAnnuity2000.female.projected=valuationTable_period (
name="USA Annuity 2000, female", name="USA Annuity 2000, female",
ages=USAAnnuity2000.data$age, ages=USAAnnuity2000.data$age,
deathProbs=USAAnnuity2000.data$qy) deathProbs=USAAnnuity2000.data$qy)
...@@ -136,25 +137,25 @@ rm(USAAnnuity2000.data); ...@@ -136,25 +137,25 @@ rm(USAAnnuity2000.data);
############################################################################### ###############################################################################
USA2012IAM.data=read.xls( USA2012IAM.data=read.xls(
"Tafeln/USA_Annuities.xls", "Tables/USA_Annuities.xls",
sheet="2012 IAR", skip=3, sheet="2012 IAR", skip=3,
col.names=c("age","qxBasic", "qyBasic", "qx", "qy", "G2x", "G2y", "", "", "")); col.names=c("age","qxBasic", "qyBasic", "qx", "qy", "G2x", "G2y", "", "", ""));
USA2012IAM.male.basic=valuationTable.period ( USA2012IAM.male.basic=valuationTable_period (
name="USA 2012 IAM basic (unloaded), male", name="USA 2012 IAM basic (unloaded), male",
ages=USA2012IAM.data$age, ages=USA2012IAM.data$age,
deathProbs=USA2012IAM.data$qxBasic) deathProbs=USA2012IAM.data$qxBasic)
USA2012IAM.female.basic=valuationTable.period ( USA2012IAM.female.basic=valuationTable_period (
name="USA 2012 IAM basic (unloaded), female", name="USA 2012 IAM basic (unloaded), female",
ages=USA2012IAM.data$age, omega=max(USA2012IAM.data$age,rm.na=TRUE)+1, ages=USA2012IAM.data$age, omega=max(USA2012IAM.data$age,rm.na=TRUE)+1,
deathProbs=USA2012IAM.data$qyBasic) deathProbs=USA2012IAM.data$qyBasic)
USA2012IAM.male=valuationTable.improvementFactors ( USA2012IAM.male=valuationTable_improvementFactors (
name="USA 2012 IAM, male", name="USA 2012 IAM, male",
ages=USA2012IAM.data$age, omega=max(USA2012IAM.data$age,rm.na=TRUE)+1, ages=USA2012IAM.data$age, omega=max(USA2012IAM.data$age,rm.na=TRUE)+1,
deathProbs=USA2012IAM.data$qx, deathProbs=USA2012IAM.data$qx,
improvement=USA2012IAM.data$G2x) improvement=USA2012IAM.data$G2x)
USA2012IAM.female=valuationTable.improvementFactors ( USA2012IAM.female=valuationTable_improvementFactors (
name="USA 2012 IAM, female", name="USA 2012 IAM, female",
ages=USA2012IAM.data$age, omega=max(USA2012IAM.data$age,rm.na=TRUE)+1, ages=USA2012IAM.data$age, omega=max(USA2012IAM.data$age,rm.na=TRUE)+1,
deathProbs=USA2012IAM.data$qy, deathProbs=USA2012IAM.data$qy,
......
src/Tables/Austria_Annuities.xlsx 0 → 100644
+ 0
− 0
View file @ 43a07d08
File added
R/Tables/A_Volkszaehlungen.xlsx → src/Tables/Austria_Census.xlsx
+ 0
− 0
View file @ 43a07d08
File moved
R/Tables/DAV_2004_R.xls → src/Tables/DAV_2004_R.xls
+ 0
− 0
View file @ 43a07d08
File moved
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