Opportunities for modelling inflation processes in Lithuania
Ana Čuvak
Vilniaus Gedimino technikos universitetas
Žilvinas Kalinauskas
Vilniaus Gedimino technikos universitetas
Published 2009-12-20


vector autoregression model

How to Cite

Čuvak A. and Kalinauskas Žilvinas (2009) “Opportunities for modelling inflation processes in Lithuania”, Lietuvos matematikos rinkinys, 50(proc. LMS), pp. 178–183. doi: 10.15388/LMR.2009.32.


Inflation is a constant and consistent increase in the general price level in the country, due to which the purchasing power of a national currency unit decreases. In practice, the measures of inflation are various price indices, such as a consumer price index (CPI), producer price index (PPI), or gross domestic product deflator. However, inflation is usually defined as a change in the HCPI over a year. Time series models, linear regression models and a vector autoregression model (VAR) can be used to model and forecast inflation processes. This paper examines Lithuanian consumer price inflation using a modern stationary time series and econometric theory. The vector autoregression model is proposed for inflation modelling. Theoretical aspects of model estimation are reviewed: time series stationarity, model identification, parameter estimation, model usage and forecasts. The stationarity of the HCPI index and exogenous variables are analyzed using the Augmented Dickey–Fuller (ADF) test. A vector autoregression model of Lithuanian inflation processes is investigated and proposed for inflation modelling. The obtained model is used for forecasting purposes and shows a fairly high degree of accuracy of the  inflation forecast in the coming 12-month period.

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