The Analysis of the Factor Affecting the Indonesian Shrimps Export to Japan During 1982-2003 (Based on the simultaneous model between demand and supply)
Abstract
Andhy Setiyawan widodo (2006), "The Analysis of The Factors Affecting
the Indonesian Shrimps Export to Japan During 1982 - 2003 (Based on the
simultaneous model between demand and supply)". Economics Faculty,
Economic Departement, International Program, Islamic University of Indonesia,
Yogyakarta.
Industrialization failed in pushing economic growth rather than agriculture
sector. Based on this, it is important to change the industrialization sector to
agriculture sector as a top priority considering that Indonesia is still a country that
produces raw materials and half finished products. Shrimp is the higher level of
export contribution in agricultural export rather than others agricultural products.
Even though fishery included in agricultural sector, its can beat coffee as major
export agriculture.
In this research the writer appeared export shrimps to Japan as the main
research because recently the export of shrimps has an important role supporting
the economic growth. Japan as the main market for Indonesian shrimps export
used as the research subject. The export of Indonesian shrimps to Japan increased
year by year. In this research the writer want to know what factors that affect to
the demand and supply of Indonesian shrimps export to Japan. Factors that
include in this research are: price of shrimps, Japan GDP, exchange rate between
countries, labor and land. This research will use time series data at 1982 - 2003 to
find the regression result.
Based on the research, from the F test we can see that all variables
simultaneously affect to the demand and supply of Indonesian shrimps export to
Japan. For the demand R-squared value is 0. 628190. It means that the variation of
the dependent variable can be explained by the independent variables about 0.
628190 or 62.8190%, while the rest 37.181% are explained by factors outside the
model. For the supply R-squared value is 0. 281653. It means that the variation of
the dependent variable can be explained by the independent variables about 0.
281653 or 28.1653 %, while the rest 71.8347% are explained by factors outside
the model.
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