causal_decompose {SIRE} | R Documentation |
Estimation and decomposition of simultaneous equation model
Description
Estimate and/or decompose a Simultaneous Equation Model into its recursive and Interdependent sub-systems
Usage
causal_decompose(data, eq.system, resid.est = "noDfCor", instruments,
sigma.in = NULL)
Arguments
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 |
Value
A list with components
-
eq.system
: the system of equations given as input -
Gamma
: the 3-SLS estimate of\Gamma'
-
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 ofA
-
Sigma
: the 3-SLS estimate ofSigma
-
systemfit
: the output from thesystemfit
function used to estimate the model -
all.graph
: the path diagram of the model, using the packageigraph
-
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'
Examples
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)