PurposeThe purpose of this paper is to assess the role of agriculture in economic growth and its interactions with other sectors of the Tunisian economy.Design/methodology/approachJohansen's multivariate approach is used to study the cointegration of the different sectors of the Tunisian economy and overcome the problem of spurious regression. Special attention is paid to investigate non‐causality between agriculture and other economic sectors.FindingsEmpirical results suggest that all Tunisian economic sectors cointegrate and tend to move together. In addition, weak exogeneity for the agricultural sector is rejected and this underlines the fact that the agricultural sector should be considered by policymakers in the analysis of intersector growth. However, in the short run, agriculture in Tunisia seems to have a partial role as a driving force in the growth of other non‐agricultural sectors and agricultural growth may be conducive only to the agro‐food industry sub‐sector. In addition, while Tunisia started improving quality of services and restructuring the banking sector to make it “internationally” viable, this paper's statistical results indicate that the agricultural sector does not fully benefit from the development of the commerce and services sector and the presence of credit market constraints continue to hamper growth of agricultural output in Tunisia.Originality/valueAlthough high importance is placed on the agricultural sector, in the context of the Tunisian economy, the issue of agricultural contribution to the economic growth has often been raised by policymakers but rarely examined empirically.
This paper aims to analyse the impact of changes in the monetary policy and the exchange rate on agricultural supply, prices and exports. The methodology used is based on the multivariate cointegration approach. Ten variables are considered: interest and exchange rates, money supply, inflation, agricultural output and input prices, agricultural supply and exports, income and the rate of commercial openness. Sample period covers annual data from 1967 to 2002. Due to the short-sample period, two subsystems are considered. First, long-run relationships are identified in each subsystem. Second, both subsystems are merged in order to calculate the short-run dynamics. Results indicate that changes in macroeconomic variables have an effect on the agricultural sector but the reverse effect does not hold.
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