Opportunities for modelling inflation processes in Lithuania
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...
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Vilnius University Press
2009-12-01
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doaj-b520634629c44568a56ac57bd0cb82dc2020-11-25T03:32:56ZengVilnius University PressLietuvos Matematikos Rinkinys0132-28182335-898X2009-12-0150proc. LMS10.15388/LMR.2009.32Opportunities for modelling inflation processes in LithuaniaAna Čuvak0Žilvinas Kalinauskas 1Vilniaus Gedimino technikos universitetasVilniaus Gedimino technikos universitetas 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. https://www.journals.vu.lt/LMR/article/view/17924inflationHCPIvector autoregression modelstationary |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ana Čuvak Žilvinas Kalinauskas |
spellingShingle |
Ana Čuvak Žilvinas Kalinauskas Opportunities for modelling inflation processes in Lithuania Lietuvos Matematikos Rinkinys inflation HCPI vector autoregression model stationary |
author_facet |
Ana Čuvak Žilvinas Kalinauskas |
author_sort |
Ana Čuvak |
title |
Opportunities for modelling inflation processes in Lithuania |
title_short |
Opportunities for modelling inflation processes in Lithuania |
title_full |
Opportunities for modelling inflation processes in Lithuania |
title_fullStr |
Opportunities for modelling inflation processes in Lithuania |
title_full_unstemmed |
Opportunities for modelling inflation processes in Lithuania |
title_sort |
opportunities for modelling inflation processes in lithuania |
publisher |
Vilnius University Press |
series |
Lietuvos Matematikos Rinkinys |
issn |
0132-2818 2335-898X |
publishDate |
2009-12-01 |
description |
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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topic |
inflation HCPI vector autoregression model stationary |
url |
https://www.journals.vu.lt/LMR/article/view/17924 |
work_keys_str_mv |
AT anacuvak opportunitiesformodellinginflationprocessesinlithuania AT zilvinaskalinauskas opportunitiesformodellinginflationprocessesinlithuania |
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1724565820705603584 |