Restricted ECM regression
Creates the Restricted Error Correction Model (RECM). This is the conditional RECM, which is the RECM of the underlying ARDL.
recm(object, case)
object |
An object of |
case |
An integer from 1-5 or a character string specifying whether the 'intercept' and/or the 'trend' have to participate in the short-run or the long-run relationship (cointegrating equation) (see section 'Cases' below). |
Note that the statistical significance of 'L(ect, 1)' in a RECM should not be
tested using the corresponding t-statistic (or the p-value) because it
doesn't follow a standard t-distribution. Instead, the
bounds_t_test
should be used.
recm
returns an object of class
c("dynlm", "lm", "recm")
. In addition, attributes 'order', 'data',
'parsed_formula' and 'full_formula' are provided.
The formula of a Restricted ECM conditional to an ARDL(p,q1,...,qk) is:
Δ y_{t} = c_{0} + c_{1}t + ∑_{i=1}^{p-1}ψ_{y,i}Δ y_{t-i} + ∑_{j=1}^{k}∑_{l=1}^{q_{j}-1} ψ_{j,l}Δ x_{j,t-l} + ∑_{j=1}^{k}ω_{j}Δ x_{j,t} + π_{y}ECT_{t} + ε_{t}
c_{0}=c_{1}=0
ECT = y_{t-1} - (∑_{j=1}^{k} θ_{j} x_{j,t-1})
c_{0}=c_{1}=0
ECT = y_{t-1} - (μ + ∑_{j=1}^{k}θ_{j} x_{j,t-1})
c_{1}=0
ECT = y_{t-1} - (∑_{j=1}^{k} θ_{j} x_{j,t-1})
c_{1}=0
ECT = y_{t-1} - (δ(t-1)+ ∑_{j=1}^{k} θ_{j} x_{j,t-1})
ECT = y_{t-1} - (∑_{j=1}^{k} θ_{j} x_{j,t-1})
According to Pesaran et al. (2001), we distinguish the long-run relationship (cointegrating equation) (and thus the bounds-test and the Restricted ECMs) between 5 different cases. These differ in terms of whether the 'intercept' and/or the 'trend' are restricted to participate in the long-run relationship or they are unrestricted and so they participate in the short-run relationship.
No intercept and no trend.
case
inputs: 1 or "n" where "n" stands for none.
Restricted intercept and no trend.
case
inputs: 2 or "rc" where "rc" stands for restricted
constant.
Unrestricted intercept and no trend.
case
inputs: 3 or "uc" where "uc" stands for unrestricted
constant.
Unrestricted intercept and restricted trend.
case
inputs: 4 or "ucrt" where "ucrt" stands for
unrestricted constant and restricted trend.
Unrestricted intercept and unrestricted trend.
case
inputs: 5 or "ucut" where "ucut" stands for
unrestricted constant and unrestricted trend.
Note that you can't restrict (or leave unrestricted) a parameter that doesn't
exist in the input model. For example, you can't compute recm(object,
case=3)
if the object is an ARDL (or UECM) model with no intercept. The same
way, you can't compute bounds_f_test(object, case=5)
if the object is
an ARDL (or UECM) model with no linear trend.
Pesaran, M. H., Shin, Y., & Smith, R. J. (2001). Bounds testing approaches to the analysis of level relationships. Journal of Applied Econometrics, 16(3), 289-326
Kleanthis Natsiopoulos, klnatsio@gmail.com
data(denmark) ## Estimate the RECM, conditional to it's underlying ARDL(3,1,3,2) ----- # Indirectly from an ARDL ardl_3132 <- ardl(LRM ~ LRY + IBO + IDE, data = denmark, order = c(3,1,3,2)) recm_3132 <- recm(ardl_3132, case = 2) # Indirectly from an UECM uecm_3132 <- uecm(ardl_3132) recm_3132_ <- recm(uecm_3132, case = 2) identical(recm_3132, recm_3132_) summary(recm_3132) ## Error Correction Term (ect) & Speed of Adjustment ------------------- # The coefficient of the ect, # shows the Speed of Adjustment towards equilibrium. # Note that this can be also be obtained from an UECM, # through the coefficient of the term L(y, 1) (where y is the dependent variable). tail(recm_3132$coefficients, 1) uecm_3132$coefficients[2]
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