Pemodelan Time Series Multivariat secara Automatis
Abstract: This research aims
at establishing model of multivariate time series by means of econometric
instruments. Four instruments in use are vector auto regressive (VAR),
structural vector auto regressive (SVAR), vector error correction model (VECM),
and structural vector error correction (SVEC). VAR and VECM are employed to
estimate and construct models and, subsequently, predict the future values of
an object. SVAR and SVEC serve to analyze innovative structures of a model. VAR
and SVAR can be implemented only to stationary data whilst VECM and SVEC can be
applied to non-stationary inputs. The identification and estimation of the
model in this research are specifically designed by R software. Based on this
software, all the aforestated models are conclusively able to identify dynamic
relationship of endogenous variabel in a model well.
Penulis: Siana Halim, Arif
Chandra
Kode Jurnal: jptindustridd110097
