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Hello,
I'd like to know how to solve this ECM equation in Gretl:
dy = b[1] + b[2] dx + b[3] ( y(-1) - b[5] x(-1) )
With b[4]=b[3]*b[5],
dy = b[1] + b[2] dx + b[3] y(-1) - b[4] x(-1)
Using OLS we can have coefficient, t-value, and p-value of:
b[1], b[2], b[3], and b[4]
<script>
open data10-5
ols diff(calwage) const diff(uswage) lags(1,calwage) lags(1,uswage)
</script>
How to get coefficient, t-value, and p-value of b[5] itself?
Thank you.
Yuniarto Hadiwibowo
On Sun, 7 Dec 2008, Yuniarto Hadiwibowo wrote:
I'd like to know how to solve this ECM equation in Gretl:
dy = b[1] + b[2] dx + b[3] ( y(-1) - b[5] x(-1) )
With b[4]=b[3]*b[5],
dy = b[1] + b[2] dx + b[3] y(-1) - b[4] x(-1)
Using OLS we can have coefficient, t-value, and p-value of:
b[1], b[2], b[3], and b[4]
<script>
open data10-5
ols diff(calwage) const diff(uswage) lags(1,calwage) lags(1,uswage)
</script>
How to get coefficient, t-value, and p-value of b[5] itself?
It's a nonlinear model; you can use nls.
<script>
open data10-5
diff calwage uswage
lags 1 ; calwage uswage
ols d_calwage const d_uswage calwage_1 uswage_1
scalar b1 = $coeff(const)
scalar b2 = $coeff(d_uswage)
scalar b3 = $coeff(calwage_1)
scalar b5 = 1
nls d_calwage = b1 + b2*d_uswage + b3*(calwage_1 - b5*uswage_1)
deriv b1 = 1
deriv b2 = d_uswage
deriv b3 = calwage_1 - b5*uswage_1
deriv b5 = -b3*uswage_1
end nls
</script>
Allin Cottrell
Thank you very much.
Yuniarto Hadiwibowo
----- Original Message ----
From: Allin Cottrell <cottrell(a)wfu.edu>
To: Gretl list <gretl-users(a)lists.wfu.edu>
Sent: Monday, December 8, 2008 12:43:53 PM
Subject: Re: [Gretl-users] ECM
I'd like to know how to solve this ECM equation in Gretl:
dy = b[1] + b[2] dx + b[3] ( y(-1) - b[5] x(-1) )
How to get coefficient, t-value, and p-value of b[5] itself?
It's a nonlinear model; you can use nls.
<script>
open data10-5
diff calwage uswage
lags 1 ; calwage uswage
ols d_calwage const d_uswage calwage_1 uswage_1
scalar b1 = $coeff(const)
scalar b2 = $coeff(d_uswage)
scalar b3 = $coeff(calwage_1)
scalar b5 = 1
nls d_calwage = b1 + b2*d_uswage + b3*(calwage_1 - b5*uswage_1)
deriv b1 = 1
deriv b2 = d_uswage
deriv b3 = calwage_1 - b5*uswage_1
deriv b5 = -b3*uswage_1
end nls
</script>
Allin Cottrell
On Mon, 8 Dec 2008, Yuniarto Hadiwibowo wrote:
Thank you very much.
You're welcome. By the way, although the answer I gave was the
most direct response to your question, it may not be the best one.
You might be better employing the Johansen ML approach, as in
<script>
open data10-5
coint2 2 calwage uswage
vecm 2 1 calwage uswage
restrict
a[2] = 0
end restrict --verbose
</script>
The "restrict" block tests the hypothesis that the US wage does
not error-correct in response to perturbations to the California
wage, which is implicitly assumed in the single-equation
specification; this hypothsis is rejected at the 5 percent level.
Allin Cottrell
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