Pengaruh Volatilitas Nilai Tukar Rupiah Terhadap Permintaan Uang M1 Indonesia, Estimasi Data Non Stasioner

Etty Puji Lestari


This article attempted to estimate the influence of exchange rate volatility of rupiah toward the demand for Indonesian M1 money using non stationary techniques. This analysis is adopted Morimune and Zhao’s study on 1994 in Japan.
These techniques are less dependent Johansen’s maximum likelihood of cointegra¬tion but more depend on the ordinary least squares (OLS) estimation of the equation in¬cluded in the ECM. The dynamic OLS estimation proposed by Phillips and Loretan in 1991 is used to estimate cointegration. Meanwhile, Vector auto regression (VAR) is used to fore¬cast the model which have an interelation time series. Since it desirable to include national income and exchange rate as regressor in the money demand function. To estimate demand function in the short run is used autoregressive distributed lag ECM ADL ECM) which known Hendry type ECM.
The results have found that there are non stationary condition in the time series data in. Meanwhile, the estimation with VAR, DOLS and ADL ECM is suggested that vola¬tility of exchange rate impact to demand for Indonesian M1 money.

Key words:    volatility of exchange rate rupiah, demand for Indonesian M1 money, non statio¬nary estimation.

Full Text:


Economic Journal of Emerging Markets (EJEM) is accredited by the Ministry of Research, Technology and Higher Education of the Republic of Indonesia (RISTEKDIKTI), No. 36a/E/KPT/2016. It is currently indexed in:

Emerging Source Citation Index Clarivate AnalyticsREPEC (Econpapers)EBSCODirectory of Open Access Journals (DOAJ)Cite FactorSinta (Science and Technology Index)IPI (Indonesian Publication Index)OCEC WorldCatHarvard LibraryThe Univesity of ManchesterUniversity of OxfordGoogle ScholarAsean Citation IndexDimensions - Digital Science

  Harvard Library   Google Scholar Indonesian Publication Index (IPI)   WorldCat  Harvard Library  University of Oxford    

 Creative Commons License
Economic Journal of Emerging Markets by is licensed under a Creative Commons Attribution 4.0 International License.