mvprobit

[chiara.mussida]

Dear Statusers,
I’m writing for a question on the package mvprobit.
I’m estimating a mvprobit for 5 search actions (outcomes) for the unemployed to see the effect of individual characteristics and structural variables effectiveness on such actions. The output I got so far is in the attached pdf . First there is some descriptive stuff for the outcomes and covariates (the labels of the variables are in Italia, buti t does not matter for my issue). Second, there is the mvprobit estimation with 5 equations (Y1,…Y5, 1 equation for each unemployment job search action):

Y1 (0,1) =f(x)
Y2 (0,1) =f(x)
Y3 (0,1) =f(x)
Y4 (0,1) =f(x)
Y5 (0,1) =f(x)

Marginal effects on each outcome are obtained using posterior simulation (10000 as number of simulated coefficient vectors from the posterior distribution of the estimated model parameters) and are not shown in the pdf for the sake of brevity.

I’m interested in calculating the marginal effects for combinations of outcome (joint marginal effect, to see the joint effect of search actions, as some unemployed use combinations of actions) such as:

pr(Y1=1, Y2=1, Y3=1, Y4=1, Y5=1)
pr(Y1=0, Y2=1, Y3=1, Y4=1, Y5=1)
pr(Y1=0, Y2=0, Y3=1, Y4=1, Y5=1)
….
pr(Y1=1, Y2=0, Y3=1, Y4=1, Y5=1)
……
….
pr(Y1=0, Y2=0, Y3=0, Y4=0, Y5=1)

we won’t have the case of no search actions:
pr(Y1=0, Y2=0, Y3=0, Y4=0, Y5=0)

I read in the Stata manual, your help file and SJ article that it is easy to calculate these marginal effects for M = 3, but I was not able to find a way to calculate them for M > 3, that is my case, with 5 equations.
Do you have some suggestions on this?

Thank you very much in advance,
Chiara

[John Mullahy]

Chiara: With your estimated parameters one approach is to use the Mata functions mvnormal(...) or mvnormalderiv(...) to compute the marginal effects. Stephen Jenkins may have other (=better) suggestions.

[Stephen Jenkins]

John is probably right! The Mata functions he cites were not available when I programmed mvprobit