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Estimating Distributions of Counterfactuals with an Application ... - UCL

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EFFECTS OF UNCERTAINTY ON COLLEGE CHOICE 389<br />

TABLE 2c<br />

COVARIATES INCLUDED IN OUTCOME, COST AND TEST EQUATIONS<br />

Cost <strong>of</strong> Schooling<br />

Tuition <strong>an</strong>d Foregone Psychic<br />

Earnings Earnings Cost Test Scores<br />

Intercept Yes Yes Yes Yes<br />

Urb<strong>an</strong> Yes Yes Yes Yes<br />

South Yes Yes Yes Yes<br />

Cohort dummies Yes Yes Yes –<br />

Me<strong>an</strong> local unemployment rate Yes Yes – –<br />

Average local wage Yes Yes – –<br />

Local tution – Yes – –<br />

Number <strong>of</strong> siblings – – Yes Yes<br />

Mother’s education – – Yes Yes<br />

Father’s education – – Yes Yes<br />

Broken family – – Yes<br />

Enrolled in school at test date – – Yes<br />

Age in 1980 – – Yes<br />

utility) in the first period (ages 19–29 years) <strong>an</strong>d in the second period (ages 30 to<br />

65 years). Let V 1,s be the period 1 gross utility <strong>of</strong> achieving schooling level s, <strong>an</strong>d<br />

V 2,s be the period 2 gross utility <strong>of</strong> obtaining schooling level s. Using (23), we write<br />

the gross utilities as<br />

V 1,s = ¯δ 1,s + X ′ ¯β 1,s + ᾱ ′ 1,s θ + ¯ε 1,s<br />

V 2,s = ¯δ 2,s + X ′ ¯β 2,s + ᾱ ′ 2,s θ + ¯ε 2,s<br />

These are the outcome equations for the model that we estimate. To see this, notice<br />

that<br />

V 1,s =<br />

=<br />

=<br />

∑A 1<br />

a=19<br />

∑A 1<br />

a=19<br />

∑A 1<br />

a=19<br />

+<br />

ln Y a,s<br />

(1 + ρ) a<br />

δ a,s + X ′ β a,s + α ′ a,s θ + ε a,s + η 1,s × experience a + η 2,s × experience 2 a<br />

(1 + ρ) a<br />

δ a,s + X ′ β a,s + η 1,s × experience a + η 2,s × experience 2 a<br />

(1 + ρ) a<br />

[<br />

A1<br />

∑<br />

a=19<br />

]<br />

α a,s<br />

′<br />

(1 + ρ) a θ +<br />

∑A 1<br />

a=19<br />

= ¯δ 1,s + X ′ ¯β 1,s + ᾱ ′ 1,s θ + ¯ε 1,s<br />

ε a,s<br />

(1 + ρ) a

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