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GTAP Resources: Resource Display

GTAP Resource #2047

"Vector Autoregressive Modeling of Agricultural Commodity Trade: The Case of Africa’s Exports to the United States"
by Odularu, Gbadebo Olusegun Abidemi


Abstract
It is pertinent to note that trade in agricultural commodities still dominates the export scene of the African economies. Moreover, the agricultural sector constitutes a significant part of the whole economy and employs a considerable proportion of the labour force. Furthermore, increasing agricultural exports is an intermediate step toward restoring external balance of payments equilibrium, a central component of most economic structural adjustment programmes (ESAP) initiated in the 1980s and 1990s. Against this backdrop, the major objective of this research is to increase our understanding of the specification and estimation of agricultural commodity trade models as well as to provide veritable tools for trade policy analysis. More specifically, the study aims at building a set of dynamic, theory-based econometric models which are able to capture both short-run and long-run effects of income and price changes, and which can be used for prediction and policy simulation under alternative assumed conditions

In this study, the methodology to be adopted will be a relatively unrestricted, data determined, econometric modeling approach based on the vector autoregressive process, which is very popular for modeling multiple time series. Further, econometric models will be constructed for SSA‘s agricultural exports to the United States (U.S). In an attempt to provide a broad-based commodity coverage, this study will also explore whether the chosen modeling approach is able to capture the essentials of the behavioural relationships underlying the SSA-US trade flow.


Resource Details (Export Citation) GTAP Keywords
Category: 2006 Conference Paper
Status: Published
By/In: Presented at the 9th Annual Conference on Global Economic Analysis, Addis Ababa, Ethiopia
Date: 2006
Version:
Created: Odularu, G. (5/1/2006)
Updated: Batta, G. (1/17/2013)
Visits: 1,767
No keywords have been specified.


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