Description Usage Arguments Value Examples
Estimate and/or decompose a Simultaneous Equation Model into its recursive and Interdependent sub-systems
1 2 | causal_decompose(data, eq.system, resid.est = "noDfCor", instruments,
sigma.in = NULL)
|
data |
the data frame containing the data |
eq.system |
the system of equations (a list of formula objects, e.g. as in pkg |
resid.est |
the estimation methods for the residual covariance matrix (as in |
instruments |
the intruments used to estimate the model via 3-SLS (as in |
sigma.in |
the Σ matrix, if the user wants to simulate a particular structure at stochastic level. Overrides 3SLS estimation if specified. |
A list with components
eq.system
: the system of equations given as input
Gamma
: the 3-SLS estimate of Γ'
C
: the matrix highlighting the interdependent mechanisms at deterministic level.
Psi1
: the matrix highlighting the interdependent mechanisms at stochastic level.
Psi0
: the matrix highlighting the causal mechanisms.
A
: the 3-SLS estimate of A
Sigma
: the 3-SLS estimate of Sigma
systemfit
: the output from the systemfit
function used to
estimate the model
all.graph
: the path diagram of the model, using the package igraph
dec.graph
: the path diagram of the decomposed model, with color
coding for each vertex
type.out
: the type of analysis performed, either 'simulation' or 'empirical'
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | 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
causal_decompose(data = macroIT,
eq.system = eq.system,
resid.est = "noDfCor",
instruments = instruments,
sigma.in = NULL)
|
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