Preprint Article Version 1 This version is not peer-reviewed

Determinants of Sustainable Economic Growth in Angola: A Case Study on Agriculture

Version 1 : Received: 19 October 2024 / Approved: 21 October 2024 / Online: 21 October 2024 (17:15:31 CEST)

How to cite: Caetano Joao, M. Determinants of Sustainable Economic Growth in Angola: A Case Study on Agriculture. Preprints 2024, 2024101628. https://doi.org/10.20944/preprints202410.1628.v1 Caetano Joao, M. Determinants of Sustainable Economic Growth in Angola: A Case Study on Agriculture. Preprints 2024, 2024101628. https://doi.org/10.20944/preprints202410.1628.v1

Abstract

Angola has an enormous agricultural potential, but the challenge remains how the country can transform potential into real growth. This study is designed to analyze the impact of the agricultural sector on economic growth in Angola and suggest recommendations for a better policy framework of the agricultural sector for a structural growth of the economy. Annual time-series data from 1993 to 2022 were used. The ARDL and EC model were applied to analyze both long and short-term relationships, as well as different statistical and econometric tests were used to examine the significance of the input data and model results, including various diagnostic tests and the Granger causality test. The study findings show stronger evidence of a long-run relationship between the dependent and independent variables than in the short run. Short run results show to be statistically insignificant. Agricultural value added shows the best reaction in all lags involved, indicating that economic growth would, caeteris paribus, respond positively to improvement in agricultural performance in Angola, although delayed by 3 years. Agricultural value-added development would improve both the contribution of agricultural employment and agricultural exports towards economic growth, as well contribute to a better rural development in Angola.

Keywords

Economic growth; agriculture; ARDL model; Angola

Subject

Business, Economics and Management, Econometrics and Statistics

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