2020Journal of Scientific Research and ReportsOpen access

Analysis of Inflation Rates in Ethiopia Using Vector Autoregressive Models

Gemechu Bekana Fufa

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Abstract

This study aims to analyze the inflation rates by using Vector Autoregressive models. Vector Autoregressive (VAR) Models, Testing Stationary: Unit root test, Estimating the Order of the VAR, Cointegration Analysis (testing of cointegration), and Vector Error Correction (VEC) Models were used in this study for data analysis. Comparisons were made between food price index and nonfood price index using descriptive analysis. The findings of the study suggest that the percentage of food price index in higher than nonfood price index. The results also 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 nonstationary 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 equation best fits the data. To contain inflation rates, therefore, the policy interventions aimed at tackling the current situation of inflation rates need to take into account the priorities of the government as the effect of policy instruments and means of solutions.

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What this paper is about

This study aims to analyze the inflation rates by using Vector Autoregressive models. Vector Autoregressive (VAR) Models, Testing Stationary: Unit root test, Estimating the Order of the VAR, Cointegration Analysis (testing of cointegration), and Vector Error Correction (VEC) Models were used in this study for data analysis. Comparisons were made between food price index and nonfood price index using descriptive analysis. The findings of the study suggest that the percentage of food price index in higher than nonfood price index. The results also 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 nonstationary 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 equation best fits the data. To contain inflation rates, therefore, the policy interventions aimed at tackling the current situation of inflation rates need to take into account the priorities of the government as the effect of policy instruments and means of solutions.

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Available abstract

This study aims to analyze the inflation rates by using Vector Autoregressive models. Vector Autoregressive (VAR) Models, Testing Stationary: Unit root test, Estimating the Order of the VAR, Cointegration Analysis (testing of cointegration), and Vector Error Correction (VEC) Models were used in this study for data analysis. Comparisons were made between food price index and nonfood price index using descriptive analysis. The findings of the study suggest that the percentage of food price index in higher than nonfood price index. The results also 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 nonstationary 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 equation best fits the data. To contain inflation rates, therefore, the policy interventions aimed at tackling the current situation of inflation rates need to take into account the priorities of the government as the effect of policy instruments and means of solutions.

Key concepts: Cointegration, Autoregressive model, Econometrics, Unit root, Error correction model, Inflation (cosmology), Economics, Consumer price index (South Africa)

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