utilall: Calculate utility of total consumption and bequest (FAST...
In sstoeckl/pensionfinanceLi: Optimal Pension Decisions in Liechtenstein

Description Usage Arguments Value Examples

Expected Utility for total cash-flows is calculated here and used for optimization

utilall(
  ret_age,
  tw3,
  c,
  c2,
  nu2,
  nu3,
  ra,
  delta,
  alpha,
  beta,
  c_age,
  gender,
  gender_mortalityTable2,
  w0,
  CF,
  li,
  lg,
  c1,
  s1,
  s2,
  s3,
  rho2,
  rho3,
  ret,
  retr,
  SPFretsel,
  psi,
  verbose = FALSE,
  warnings = TRUE
)

`ret_age`	Decision Variable: retirement age, can be set anywhere between 60 and 70 (default: 65)
`tw3`	Decision Variable: third pillar portfolio allocation (given either as vector or as matrix with entries) for all years. HERE: Choose only allocation to stocks, bonds and real estate, cash will be determined as fraction missing to sum up to one
`c`	Decision Variable: fraction of income that is consumed while still working (current assumption: constant)
`c2`	Decision Variable: second pillar savings as fraction of gross income (still missing: health, a-fonds-perdu payments)
`nu2`	Decision Variable: fraction of second pillar savings that is converted to life-long pension
`nu3`	Decision Variable: fraction of third pillar savings that is converted to life-long pension
`ra`	Given variable: Risk Aversion of Agent
`delta`	Given Variable: Time Preference
`alpha`	parameter to choose fraction of wealth NOT consumed during retirement but kept for investment (and subsequent consumption) - see file 'Consumption_3p.ods'
`beta`	Given variable: Relative Weight of bequest utility
`c_age`	Given variable: the investor's current age (assuming birthday is calculation-day)
`gender`	Given variable: gender, 0=male and 1=female
`gender_mortalityTable2`	Given variable: Combined MortalityTable with columns for both gender 0=male and 1=female, e.g. 'baseTable(AVOe2005R.male)'
`w0`	Given variable: time c_age wealth that is not disposable, assumption: still available at retirement (no growth or decline), alternatively: expected wealth (that is not disposable) at retirement, stays the same over time
`CF`	Given Variables: income shocks, such as inheritance (not currrently imlemented)
`li`	Given variable: gross labor income at time 0 (in the last year before birthday)
`lg`	Given variable: labor growth rate (in real terms, constant)
`c1`	Given variable: first pillar savings as fraction of gross income
`s1`	Given variable: vector consisting of two components: c(number of contribution years at age=c_age,historical average yearly income until c_age)
`s2`	Given variable: savings in second pillar as of t=0
`s3`	Given variable: liquid wealth - invested in the third pillar (current assumption: no tax advantage for third pillar)
`rho2`	Given variable: conversion factor in second pillar for regular retirement age
`rho3`	Given variable: conversion factor in third pillar for regular retirement age
`ret`	Given variable: investment return scenarios (nominal)
`retr`	Given variable: investment return scenarios (real)
`psi`	Given variable: spread to take a loan/leverage for third pillar savings
`verbose`	optional: show additional information while calculating utility (default: FALSE)
`warnings`	optional: should warnings be given? (default=TRUE)

Expected utility

data(ret); data(retr); data(SPFret)
MortalityTables::mortalityTables.load("Austria_Annuities")
.load_parameters(gend=0,type=1)
SPFretsel <- .SPFretch(SPFret,c_age=c_age,ret_age=ret_age)

utilall_ex <- utilall(ret_age=ret_age,c_age=c_age,
                tw3=c(.25,.25,.25),
                c=cc,c2=c2,nu2=nu2,nu3=nu3,ra=ra,delta=delta,alpha=aalpha,
                beta=bbeta,gender=gender,
                gender_mortalityTable2=cbind(MortalityTables::baseTable(AVOe2005R.male),
                MortalityTables::baseTable(AVOe2005R.female)),
                w0=w0,CF=NULL,li=li,lg=lg,c1=c1,s1=s1,s2=s2,s3=s3,
                rho2=rho2,rho3=rho3,ret=ret,retr=retr,SPFretsel=SPFretsel,psi=psi)

.load_parameters(gend=1,type=2)
SPFretsel <- .SPFretch(SPFret,c_age=c_age,ret_age=ret_age)
utilall_ex2 <- utilall(ret_age=ret_age,c_age=c_age,
                tw3=c(.25,.25,.25),
                c=cc,c2=c2,nu2=nu2,nu3=nu3,ra=ra,delta=delta,alpha=aalpha,
                beta=bbeta,gender=gender,
                gender_mortalityTable2=cbind(MortalityTables::baseTable(AVOe2005R.male),
                MortalityTables::baseTable(AVOe2005R.female)),
                w0=w0,CF=NULL,li=li,lg=lg,c1=c1,s1=s1,s2=s2,s3=s3,
                rho2=rho2,rho3=rho3,ret=ret,retr=retr,SPFretsel=SPFretsel,psi=psi)