| Abstract: | The objective of this study is investigating the relationship (linkage) between agriculture and
industry in the short and long run time dynamics. To conduct this paper, secondary time series
data from World Bank (WB) Data-Base has taken in which the sample observation covers from
1991 to 2016. Before running the model, to understand the stationary property of time series
data; graphical analysis method, and correlogram and Q statistics approach of stationary test is
carried out. To further check the existence of unit root problem, Augmented Dickey – Fuller
(ADF) and Phillip - Perron (PP) unit root test is done. The result of stationary test implies that,
all variables are co-integrated at the same order, I(1) since all of them are non-stationary at a
level but stationary after first difference.
To investigate the presence of long run long run relationship between variables, Johansen cointegration
test (trace and max statistics) has employed. The result of this co-integration test
shows that, there is at least one co-integrated vector. Hence, VEC is selected to run the model.
The empirical finding reveals there is one-way relationship between agriculture and industry
both in the short and long run dynamics which goes from agriculture to industry. In the short run,
agriculture impact industry positively but in the long run it has a negative causality during the
sample period from 1991 to 2016 |
