fellow programmers. I'm studying a book on numerical solutions for economics (Judd 1998). I'm trying to reproduce a problem from that same book in R so I can use the optim
package to see if I can get similar results.
The problem established by the author is this one: and his results were these.
I have tried to transcribe this problem to R, which resulted in this code chunk:
DisutilityJudd <- function(L){
if(L == 0){
return(0)
}else{
return(0.1)
}
}
AgentUtilityJudd <- function(w, L){
(-exp(-2*w) + 1) - DisutilityJudd(L)
}
reservation.utility.judd <- AgentUtilityJudd(1, 1)
MaxEffortUtility <- function(w1, w2, L = 1){
0.8 * AgentUtilityJudd(w1, L) + 0.2 * AgentUtilityJudd(w2, L)
}
LeastEffortUtility <- function(w1, w2, L = 0){
0.4 * AgentUtilityJudd(w1, L) + 0.6 * AgentUtilityJudd(w2, L)
}
UtilityDifferenceJudd <- function(w1, w2){
MaxEffortUtility(w1, w2) - LeastEffortUtility(w1, w2)
}
PenaltyFunctionJudd <- function(w1, w2, P = 100000){
if(length(w1) == 2){
y <- -1 * (0.8 * (2 - w1[1]) - 0.2 * w1[2] - P *
(pmax(0, -MaxEffortUtility(w1[1], w1[1]) - reservation.utility.judd))^2 -
P * (pmax(0, -UtilityDifferenceJudd(w1[1], w1[1])))^2)
}else{
y <- -1 * (0.8 * (2 - w1) - 0.2 * w2 - P *
(pmax(0, -MaxEffortUtility(w1, w2) - reservation.utility.judd))^2 -
P * (pmax(0, -UtilityDifferenceJudd(w1, w2)))^2)
}
return(y)
}
There were no errors, but the results generated by my code were nowhere near to what I was expecting:
optim(c(1.1, 0.5), PenaltyFunctionJudd)
$par
[1] 1.343909e+49 -2.370681e+51
$value
[1] -4.633849e+50
$counts
function gradient
501 NA
$convergence
[1] 1
$message
NULL
Perhaps there is a problem to my penalty function. I'm assuming that it is due to the pmax
function. Could somebody help me identify it? Thank you, I appreciate your attention.
Edit: a typo.
I believe you meant w1[2]
in when if(length(w1) == 2)
is true.
I have modified your code, without touching how you define the previous function. It is not clear if it the result expected : what does IV(-1) mean, is it the result minus 1 ? a power if 10 ?
PenaltyFunctionJudd <- function(w1, w2, P = 1e5){
if(length(w1) > 1){
w2 <- w1[2]
w1 <- w1[1]
}
# cat("length is 2 \n")
y <- 0.8 * (2 - w1) - 0.2 * w2 - P *
( pmax(0, -MaxEffortUtility(w1, w2) - reservation.utility.judd) )^2 -
P * ( pmax(0, -UtilityDifferenceJudd(w1, w2)) )^2
# cat("pmax1 :", pmax(0, -MaxEffortUtility(w1, w2) - reservation.utility.judd), "\n")
# cat("pmax2 :", pmax(0, -UtilityDifferenceJudd(w1, w2)), "\n")
return(y)
}
optim(c(1.1, 0.5), PenaltyFunctionJudd, control = list(fnscale = -1) )
optim(c(11, 5), PenaltyFunctionJudd, method = "BFGS", control = list(fnscale = -1, maxit = 100) )
You can use cat
or print
to check your values (here I noticed some Inf and 0 the leaded me to notice code error).
Friendly warning : provided you defined correctly the previous function, there is lot of instability in optimisation (problem badly set ? More penalty needed ?). Indeed when running twice or more the algorithm parameters fluctuate a lot...