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Abstract
In this paper we model five Lithuanian HICP subcomponents in a medium scale Bayesian VAR framework. We deal with the parameter proliferation problem by setting the appropriate amount of shrinkage determined in the out-of-sample forecasting exercise. The main body of the paper consists of displaying the model’s performance in two applications: forecasting and analysis of inflation determinants. We find the model’s forecasts to be competitive against the univariate statistical models, particularly in the cases of predicting processed food and energy goods inflation. What is more, exercises based on conditional forecasting show that these two indices make the best use of accurate conditional information in terms of improving predicting accuracy. In the decomposition of the drivers of HICP components, we demonstrate that both, domestic and foreign factors can be prevalent inflation determinants in certain time periods. We also find some evidence on employees’ bargaining power playing a role in determining the Lithuanian consumer price inflation.
JEL Codes: C32, C53, E37.
The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.
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Working Paper Series
Working papers disseminate economic research relevant not only to the tasks and functions of the Bank of Lithuania and of the European System of Central Banks but also appealing more broadly to the academic community in economics and finance. They present, discuss and analyse the results of original and academically rigorous theoretical and/or empirical research. Working papers constitute the basis for publications in leading academic journals, making contributions to the existing literature in the fields of economics and finance. They encourage collaboration between the researchers of the Bank of Lithuania and other central banks, Lithuanian and foreign universities and research institutes.
Papers are only available in English.
No 56
2018-12-28
Slicing up inflation: analysis and forecasting of Lithuanian inflation components
No 46
2017-09-20
No 41
2017-03-02
No 35
2016-11-02