Abstract
Monthly data on price indices of consumer goods and services as well as groups of some goods and the principal monetary indices in Lithuania are considered in this paper using methods of mathematical statistics. The main goal of this work is to construct mathematical models of the consumer price (ePI) index, fit for short-term prediction. Statistical dependency between prices and monetary indicators is investigated in the paper. Trends and seasonal components are estimated. Random fluctuations are described using autoregression models. Regressive models of prices and monetary indicators as regressors are constructed. Errors of indicator prediction using the proposed models are estimated. An expert analysis of the state of the national economy is made, taking into account changes in price, production, and unemployment indicators. Due to data inaccuracy and frequent recalculation of indicators, only a qualitative analysis was made without applying mathematical means.
Highlights
Data on price indices of consumer goods and services as well as groups of some goods and the principal monetary indices in Lithuania are considered in this paper using methods of mathematical statistics
In recent years specific attention has been paid to changes in prices of consumer goods and services in Lithuania
Taking into account the research carried out by using Lithuanian economic data from the years 1993-1995, we can assert that, in recent years, there has been a strong dependency between consumer prices and monetary indicators as well as income indicators in Lithuania
Summary
The following indicators are considered in the paper: 1) Consumer goods and services price index (CPI); 2) Food, alcoholic beverages and tobacco price index (FPI); 3) Clothing and footwear price index (CFPI); 4) Rent, fuel, and power price index (RPI); 5) Transport and communication price index (TPI); 6) MoneyM1; 7) MoneyM2; 8) Currency outside banks (COl); 9) Average monthly gross wages and salaries (AWSI). Pother(t) denotes the price index of consumer goods and services not contained by groups [2-5], and q(.) denotes the respective weight coefficients whose sum equals 1. These weights are determined by household surveys (and are specified no more than once a year).
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