Asymmetric Error Correction Model R
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...) Arguments y dependent or left-side variable for the long-run regression. x independent or right-side variable for the long-run regression. lag number of lags for variables on the right vector error correction model in r side. split a logical value (default of TRUE) of whether the right-hand variables error correction model stata should be split into positive and negative parts. model a choice of three models: linear, tar , or mtar error correction model eviews cointegration. thresh a threshold value; this is only required when the model is specified as 'tar' or 'mtar.' ... additional arguments to be passed. Details There are two specficiations of an asymmetric error correction model interpretation ECM. The first one is how to calculate the error correction terms. One way is through linear two-step Engle Granger approach, as specificied by model="linear". The other two ways are threshold cointegration by either 'tar' or 'mtar' with a threshold value. The second specification is related to the possible asymmetric price transmission in the lagged price variables, as specified in split = TRUE.
Vector Error Correction Model Tutorial
Note that the linear cointegration specification is a special case of the threshold cointegration. A model with model="linear" is the same as a model with model="tar", thresh = 0. Value Return a list object of class "ecm" and "ecmAsyFit" with the following components: y dependend variable x independent variable lag number of lags split logical value of whether the right-hand variables are split model model choice IndVar data frame of the right-hand variables used in the ECM name.x name of the independent variable name.y name of the dependent variable ecm.y ECM regression for the dependent variable ecm.x ECM regression for the independent variable data all the data combined for the ECM thresh thresh value for TAR and MTAR model Author(s) Changyou Sun (csun@cfr.msstate.edu) References Enders, W., and C.W.J. Granger. 1998. Unit-root tests and asymmetric adjustment with an example using the term structure of interest rates. Journal of Business & Economic Statistics 16(3):304-311. See Also print.ecm; summary.ecm; ecmDiag; and ecmAsyTest. Examples data(daVi); data(daCh) t.mtar <- -0.451 aem <- ecmAsyFit(y=daVi, x=daCh, lag=4, model="mtar", split=TRUE, thresh=t.mtar) aem summary(aem) ecmDiag(aem, 3) (tes <- ecmAsyTest(aem)$out) [Package apt version 1.1 Index]
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