Main Article Content
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.
Central Statistical Agency (CSA). Report of the 2005. Federal Democratic Republic of Ethiopia, Addis Ababa. Central Statistical Authority (2001). Statistical Abstract; 2005.
Hilbe JM. Logistic regression models. Chapman & Hall, London; 2009.
MoFED. National Economic Accounts Directorate. Ministry of Finance and Economic Development, Addis Ababa; 2010.
Bahata YT, Willemse BJ, Grove B. The role of agriculture in welfare, income distribution and economic development of the Free State Province of South Africa: A CGE approach, Agrekon: Agricultural Economics Research, Policy and Practice in Southern Africa. 2014;53(1):46-74.
Geda A, Tafere K. The galloping inflation in Ethiopia: A cautionary tale for aspiring ‘Developmental States’ in Africa. Agricultural Economics Research, Policy and Practice in Southern Africa. 2015;53(1):46-74.
Gemechu B, Temesgen A, Temesgen D. Regression models to identify the determinants of inflation in Ethiopia: The case of Illu Abba Bor Zone, Ethiopia. International Journal of Multidisciplinary Research and Studies. 2019;1(2):2640-7272.
Sahoo K, Sethi N. Investigating the impact of agriculture and industrial sector on economic growth of India. OIDA International Journal of Sustainable Development. 2012;05(05):11-22.
John M, Worku S, Paulos Z. Impact of soaring food prices in Ethiopia. International Food Policy Research Institute (IFPRI). 2017;8(2).
Gemechu Bekana. Analyzing the share of agriculture and industrial sectors in the economic growth of Ethiopia: An ordinary least squares (OLS) application. International Journal of Information, Business and Management. 2018;10(4): 2076-9202.
Hair JF, Black W, Babin BJ, Anderson RE. Multivariate data analysis, 7th Edition, Prentice Hall; 2009. Hosmer DW, Lemeshow S. Applied Logistic Regression, 2nd Ed.; 2004.
Jema H, Fekadu G. Determinates of the recent soaring food inflation in Ethiopia. Universal Journal of Education and General Studies. 2017;12(1):00545–00552.
Khan MS, Senhadji AS. Threshold effects in the relationship between inflation and economic growth. IMF Staff Papers. 2013;48(1):1-21.
Lutkepohl H. Introduction to multiple time series analysis. Springer-Verlag, Berlin; 2005.
Dickey DA, Fuller WA. Distribution of estimators of autoregressive time series with a unit root. Journal of the American Statistical Association. 1979;74:427- 31.
Dickey DA, Fuller WA. Likelihood ratio statistics for autoregressive time series with a unit root. Econometrica. 1981;49(4):1057-72.
Philips PCB. Understanding spurious regression in econometrics. Journal of Economics. 1987;33:311-340.
Johansen P. Statistical analysis of cointegration vectors. Journal of Economic Dynamics and Control. 1988;12:231- 254.
Johansen S, Juselius K. Identification of the long-run and the short-run structure. An application to the ISLM model. Journal of Econometrics; 1990.
Schultz TW. Transforming traditional agriculture. American Journal of Agricultural Economics. 1988;70(1):198-200.