[Limdep Nlogit List] scenario analysis in nlogit

[Kristy Wallmo - NOAA Federal]

Hi -
I am estimating a fairly simple RPL in nlogit and am using the simulation
tool to compare different scenarios.  My model looks good, all signs as
expected.  My question is about storing predicted probabilities from
simulations of alternative scenarios.  If I run the code below I can store
the probabilities of the base scenario (probbase) and those of the
alternative scenario (probmax8).  However, if I want to run more than one
scenario comparison by using the & and adding additional scenario(s), is it
possible to also store the probabilities associated with additional
scenario(s)?  I know there is a limit of five scenario comparisons in one
run.  Thanks for any advice.  -- Kristy

*Code*
rplogit; lhs = chosen
; choices = 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,
21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,
41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,
61,62,63,64,65,66,67,68
;
; rhs = pyf1523, pbe1523, cost
; fcn = pbe1523 (n), pyf1523 (n)

; parameters; Halton; pts=50
; pds = cttripto
; prob = probbase
; utility = util
$
WALD ; Labels = b1,b2,b3,b4,b5
    ; Start = b ; Var = varb
    ; Fn1 = -b1/b3
; fn2 = -b2/b3
; K&R
; Pts = 50000  $

*scenario 8.5 MAX  simulation*

rplogit; lhs = chosen
; choices = 1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,
21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,
41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,
61,62,63,64,65,66,67,68
;
; rhs = pyf1523, pbe1523, cost
; fcn = pbe1523 (n), pyf1523 (n)

; parameters; Halton; pts=50
; pds = cttripto
; prob = probmax8
; utility = util

; simulation = *
; scenario:
pbe1523 (1, 2, 3, 4, 5, 10, 11, 12, 13, 14, 15, 16, 20, 21, 22, 23, 24, 25,
26, 30, 31, 32, 33, 34, 42, 43, 44, 65, 66, 67, 68) = [*]1.22/
pbe1523 (6, 7) = [*]1.14/
pbe1523 (8, 9, 17, 18, 19) = [*]1.34/
pbe1523 (27, 28, 29) = [*]1.30/
pbe1523 (35, 36, 45, 46, 47, 48, 59) = [*]1.16/
pbe1523 (37, 38) = [*]1.29/
pbe1523 (39, 40, 41, 49, 50, 51, 52, 61, 62, 63) = [*]1.18/
pbe1523 (53, 54, 55, 56, 57, 58, 64) = [*]1.30/
pbe1523 (60) = [*]1.51/

pyf1523 (1, 2, 3, 4, 65, 66, 67, 68) = [*]1.46/
pyf1523 (5, 6, 7) = [*]1.35/
pyf1523 (8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 23, 24, 25, 26, 29,
30, 31, 32, 33, 34, 42, 49, 50, 51, 52, 53) = [*]1.59/
pyf1523 (20, 21, 22) = [*]1.70/
pyf1523 (27, 28, 37, 38, 39, 40, 41) = [*]1.48/
pyf1523 (35, 36, 46, 47, 48, 58, 59) = [*]1.53/
pyf1523 (43, 44, 45, 54, 55, 56, 57) = [*]1.75/
pyf1523 (60, 61, 62, 63) = [*]1.75/
pyf1523 (64) = [*]2.27$



-- 
Kristy Wallmo, Ph.D.
Economist, Office of Science and Technology
NOAA Fisheries | Department of Commerce
301-257-9653