AAU-ETD AAU-ETD
 

Addis Ababa University Libraries Electronic Thesis and Dissertations: AAU-ETD! >
Faculty of Science >
Thesis - Statistics >

Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/3413

Title: MULTIVARIATE TIME SERIES ANALYSIS OF INFLATION: THE CASE OF ETHIOPIA
Authors: Seifu, Neda
Advisors: Butte Gotu(Dr.)
Keywords: Inflation
Vector autoregressive
co-integration
Vector Error correction model and forecasting
Copyright: Jun-2011
Date Added: 18-Jul-2012
Publisher: Addis Ababa University
Abstract: Inflation refers to a situation in which the economy’s overall price level is rising. The inflation rate is the percentage change in the price level from the previous period. The measures of inflation are various price indices, such as a consumer price index (CPI), producer price index (PPI), or GDP deflator. However, inflation is usually defined as a change in the CPI over a year. The aim of this study is to fit a time series model for CPI and its components which can be used to forecast the rate of inflation in Ethiopia. The data used are monthly observations from January 2000 to December 2010 of the Consumer Price Index (CPI), Food Price Index (FPI) and Non-food Price Index (NFPI). The vector autoregressive (VAR) model is employed for modeling. The cointegration relations among the price indices were identified by applying Johansen’s cointegration tests, while potential causal relations were examined by employing Granger’s causality tests. Moreover, the short run interactions among the variables were determined through the application of impulse response analysis and variance decomposition. The results of the research imply the existence of short term adjustments and long-term dynamics in the CPI, FPI and NFPI. Unit root test reveals that all the series are non stationary at level and stationary at first difference. The result of Johansen test indicates the existence of one cointegration relation between the variables. The final result shows that a Vector Error Correction (VEC) model of lag two with one cointegration equations best fits the data. The forecasting accuracy of this model was checked using RMSE, MAE, MAPE and Theil-U statistics. Finally, using the fitted model out-of-sample forecasts were produced for Ethiopian inflation rate.
Description: A Thesis submitted to the School of Graduate Studies of Addis Ababa University in partial fulfillment of the requirements for the Degree of Master of Science in Statistics.
URI: http://hdl.handle.net/123456789/3413
Appears in:Thesis - Statistics

Files in This Item:

File Description SizeFormat
Seifu Neda.PDF535.14 kBAdobe PDFView/Open

Items in the AAUL Digital Library are protected by copyright, with all rights reserved, unless otherwise indicated.

 

  Last updated: May 2010. Copyright © Addis Ababa University Libraries - Feedback