Vector Error Correction Model Input
gen_vec produces the input for the estimation of a vector error correction (VEC) model.
gen_vec( data, p = 2, exogen = NULL, s = 2, r = NULL, const = NULL, trend = NULL, seasonal = NULL, structural = FALSE, iterations = 50000, burnin = 5000 )
data |
a time-series object of endogenous variables. |
p |
an integer vector of the lag order of the series in the (levels) VAR. |
exogen |
an optional time-series object of external regressors. |
s |
an optional integer vector of the lag order of the exogenous variables of the series in the (levels) VAR. |
r |
an integer vector of the cointegration rank. |
const |
a character specifying whether a constant term enters the error correction
term ( |
trend |
a character specifying whether a trend term enters the error correction
term ( |
seasonal |
a character specifying whether seasonal dummies should be included in the error
correction term ( |
structural |
logical indicating whether data should be prepared for the estimation of a structural VAR model. |
iterations |
an integer of MCMC draws excluding burn-in draws (defaults to 50000). |
burnin |
an integer of MCMC draws used to initialize the sampler (defaults to 5000). These draws do not enter the computation of posterior moments, forecasts etc. |
The function produces the variable matrices of vector error correction (VEC) models, which can also include exogenous variables:
Δ y_t = Π w_t + ∑_{i=1}^{p-1} Γ_i Δ y_{t - i} + ∑_{i=0}^{s-1} Υ_i Δ x_{t - i} + C^{UR} d^{UR}_t + u_t,
where Δ y_t is a K \times 1 vector of differenced endogenous variables, w_t is a (K + M + N^{R}) \times 1 vector of cointegration variables, Π is a K \times (K + M + N^{R}) matrix of cointegration parameters, Γ_i is a K \times K coefficient matrix of endogenous variables, Δ x_t is a M \times 1 vector of differenced exogenous regressors, Υ_i is a K \times M coefficient matrix of exogenous regressors, d^{UR}_t is a N \times 1 vector of deterministic terms, and C^{UR} is a K \times N^{UR} coefficient matrix of deterministic terms that do not enter the cointegration term. p is the lag order of endogenous variables and s is the lag order of exogenous variables of the corresponding VAR model. u_t is a K \times 1 error term.
If an integer vector is provided as argument p, s or r, the function will
produce a distinct model for all possible combinations of those specifications.
An object of class 'bvecmodel', which contains the following elements:
data |
A list of data objects, which can be used for posterior simulation. Element
|
model |
A list of model specifications. |
Lütkepohl, H. (2006). New introduction to multiple time series analysis (2nd ed.). Berlin: Springer.
# Load data
data("e6")
# Generate model data
data <- gen_vec(e6, p = 4, const = "unrestricted", season = "unrestricted")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.