Analysis of economic growth indicators in ethiopia using
vector autoregressive models
Accepted 7th
September, 2020
Abdi Tesfaye1 and Gemechu Bekana2
1Department of Statistics, College of
Natural and Computational Science, Bule Hora
University, Bule Hora, Ethiopia. 2Assistant Professor of Statistics,
Department of Statistics, College of Natural and
Computational Science, Wollega University,
Nekemte, Ethiopia.
The objective of this study was to carry out an
Analysis of Economic Growth indicators in
Ethiopia using Vector Autoregressive models.
Yearly data set on the variables for the period
of 1988 to 2018 was obtained from the National
Bank of Ethiopia (NBE) and CSA. 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. 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: LRGDP, Lexport,
Limport, inflation and Exchange rate are
co-integrated, which implies that the variables
have long run equilibrium relationship. The
Result of Vector Error Correction Model (VECM)
from term in LRGDP equation is weakly
significant at 5% level and has a negative
value, implying that there exists a long run
relationship running from inflation, Lexport,
Limport and Exchange rate to Real GDP. The final
result shows that a Vector Error Correction (VEC)
model of lag two with one cointegration equation
best fits the data.
This is an open access article
published under the terms of the
Creative Commons Attribution
License, which permits unrestricted use, distribution, and
reproduction in any medium, provided the original work is
properly cited.
Cite this article as:
Tesfaye A, Bekana G (2020). Analysis of economic growth indicators in ethiopia
using vector autoregressive models. Acad. J. Sci. Res.
8(11): 362-371.