Opportunities for modelling inflation processes in Lithuania
Articles
Ana Čuvak
Vilniaus Gedimino technikos universitetas
Žilvinas Kalinauskas
Vilniaus Gedimino technikos universitetas
Published 2009-12-20
https://doi.org/10.15388/LMR.2009.32
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Keywords

inflation
HCPI
vector autoregression model
stationary

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.

Abstract

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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