APPLICATION OF VECTOR AUTOREGRESSION MODEL FOR LITHUANIAN INFLATION

Ana Cuvak, Zilvinas Kalinauskas

Abstract


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


Keywords


inflation, HCPI; vector autoregression model; stationary

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Print ISSN: 1822-6515
Online ISSN: 2029-9338