Description Usage Arguments Value Examples
Testing for Feedback Effects in a Simultaneous Equation Model
1 2 | feedback_ml(data, out.decompose, eq.id, lb = -200, ub = 200,
nrestarts = 10, nsim = 20000, seed.in = 1)
|
data |
the data frame containing the data |
out.decompose |
the decomposition object resulting from |
eq.id |
the equation to be tested for feedback effects |
lb |
lower bound of the parameter space required for |
ub |
upper bound of the parameter space required for |
nrestarts |
number of solver restarts (as in |
nsim |
number of random parameters to generate for every restart of the solver (as in |
seed.in |
seed number for gosolnp routine |
A list with components
rho.est
: a data frame with the maximum likelihood estimate of rho and the
equations with which each element is involved in feedback-like mechanisms
loglik
: the value of the log-likelihood of the model
theta.hessian
: the hessian matrix for the estimated parameters
rho.jacobian
: the Jacobian matrix of ρ with respect to the entire set of parameters
wald
: the resulting Wald test statistic
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | data("macroIT")
eq.system = list(
eq1 = C ~ CP + I + CP_1,
eq2 = I ~ K + CP_1,
eq3 = WP ~ I + GDP + GDP_1,
eq4 = GDP ~ C + I + GDP_1,
eq5 = CP ~ WP + T,
eq6 = K ~ I + K_1)
instruments = ~ T + CP_1 + GDP_1 + K_1
c.dec = causal_decompose(data = macroIT,
eq.system = eq.system,
resid.est = "noDfCor",
instruments = instruments)
feedback_ml(data = macroIT,
out.decompose = c.dec,
eq.id = 5,
lb = -200,
ub = 200,
nrestarts = 10,
nsim = 20000,
seed.in = 1)
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