FORECASTING CONSUMER PRICE INDEX (CPI) USING TIME SERIES MODELS AND MULTI REGRESSION MODELS (ALBANIA CASE STUDY)

Author:

Gjika Dhamo Eralda1,Puka Llukan1,Zaçaj Oriana2

Affiliation:

1. University of Tirana

2. Polytechnic University

Abstract

In this work we analyse the CPI index as the official index to measure inflation in Albania, Harmo-nized Indices of Consumer Prices (HICPs) as the bases for comparative measurement of inflation in European countries and other financial indicators that may affect CPI. This study is an attempt to model CPI based on combination of multiple regression model with time series forecasting models. In the first approach, time series models were used directly on the CPI time series index to obtain the forecast. In the second approach, the time series models (SARIMA, ETS) were used to model and simulate forecast for each subcomponent with significant correlation to CPI and then use the multiple regression model to obtain CPI forecast. The projection of this indicator is important for understand-ing the country's economic and social development. This study helps researchers in the field of time series modeling, economic analysis and investments.

Publisher

VGTU Technika

Reference28 articles.

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2. Box, G. E. P., & Jenkins, G. (1970). Time series analysis, forecasting and control, Holden-Day. San Francisco, CA.

3. Falnita, E., & Sipos C. (2007). A multiple regression model for inflation rate in Romania in the enlarged EU. Munich Personal RePEc Archive, Paper No. 11473, posted 11 November 2008. Retrieved from http://mpra.ub.unimuenchen. de/11473/

4. Fat Codruta, M., & Dezsi, E. (2011). Exhange-rates forecasting: Exponential smoothing techniques and ARIMA models. The Annals of the University of Oradea. Economic Sciences, 499-508, Romania. Retrieved from http://steconomiceuoradea.ro/anale/volume/2011/n1/ 046.pdf

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