We are currently running a probit model based on the determination of the probability of blue collar workers applying for unemployment benefits using Mccalls 1995 data set as a restricted model using the following variables:
bluecol: dummy, 1 if blue collar worker
stateur: state unemployment rate (in %)
statemb: state maximum benefit level
state: state of residence code
age: age in years
age2: age squared
tenure: years of tenure in job lost
slack: dummy, 1 if job lost due to slack work
abol: dummy, 1 if job lost because position abolished
seasonal: dummy, 1 if job lost becasue seasonal job ended
nwhite: dummy, 1 if nonwhite
school12: dummy, 1 if more than 12 years of school
male: dummy, 1 if male
smsa: dummy, 1 if live is smsa
married: dummy, 1 if married
dkids: dummy, 1 if kids
dykids: dummy, 1 if young kids (0-5 yrs)
yrdispl: year of job displacement (1982=1,..., 1991=10)
rr: replacement rate
rr2: rr squared
head: dummy, 1 if head of household
y: dummy, 1 if applied for (and received) UI benefits
Our issue is because the model is restrictive, our binary dependant variable; blue collar worker is restricted to the value = 1 meaning yes, they are a blue collar worker
Stata reads this as an omitted variable when estimated using probit and provides us with the code r (2000) which states "outcome does not vary; remember:
0 = negative outcome,
all other nonmissing values = positive outcome"
does anyone have any techniques to combat this issue? any help would be great and very much appreciated.
bluecol: dummy, 1 if blue collar worker
stateur: state unemployment rate (in %)
statemb: state maximum benefit level
state: state of residence code
age: age in years
age2: age squared
tenure: years of tenure in job lost
slack: dummy, 1 if job lost due to slack work
abol: dummy, 1 if job lost because position abolished
seasonal: dummy, 1 if job lost becasue seasonal job ended
nwhite: dummy, 1 if nonwhite
school12: dummy, 1 if more than 12 years of school
male: dummy, 1 if male
smsa: dummy, 1 if live is smsa
married: dummy, 1 if married
dkids: dummy, 1 if kids
dykids: dummy, 1 if young kids (0-5 yrs)
yrdispl: year of job displacement (1982=1,..., 1991=10)
rr: replacement rate
rr2: rr squared
head: dummy, 1 if head of household
y: dummy, 1 if applied for (and received) UI benefits
Our issue is because the model is restrictive, our binary dependant variable; blue collar worker is restricted to the value = 1 meaning yes, they are a blue collar worker
Stata reads this as an omitted variable when estimated using probit and provides us with the code r (2000) which states "outcome does not vary; remember:
0 = negative outcome,
all other nonmissing values = positive outcome"
does anyone have any techniques to combat this issue? any help would be great and very much appreciated.
