Precision policies and local content targets in resource-rich developing countries: The case of the oil and gas sector in Mozambique
This paper aims to understand whether and to what extent firm-level data can “precisely” support the definition of Local Content (LC) targets for international oil and gas companies in resource-rich developing countries. The paper addresses this topic with reference to a specific, publicly available...
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Veröffentlicht in: | Resources policy 2022-06, Vol.76, p.102597, Article 102597 |
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Sprache: | eng |
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Zusammenfassung: | This paper aims to understand whether and to what extent firm-level data can “precisely” support the definition of Local Content (LC) targets for international oil and gas companies in resource-rich developing countries. The paper addresses this topic with reference to a specific, publicly available dataset developed by the World Bank Enterprises Survey (ES) Unit and uses the case of Mozambique to demonstrate the informative potential of firm-level data for policy-making. Specifically, we compare the LC estimates obtained using firm-level data with those obtained using sector-level data (input-output tables). Based on this comparison, we demonstrate that firm-level data provide a more accurate representation of the capability of the domestic supply chain to provide inputs to the oil and gas industry, while input-output tables lead to a significant overestimation of LC. Overall, our findings suggest that firm-level data can provide a more precise basis for supporting the design of LC policies and the Enterprise Survey for Mozambique could represent a reference model for data collection to be extended to other resource-rich developing countries to support target definition.
•Setting Local Content (LC) targets is a key issue of LC policies.•LC targets should be defined according to the country’s industrial supply capacity.•Firm-level data represent supply capacity more precisely than sector-level data.•Firm-level data can contribute to address the poor data-poor policy dilemma. |
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ISSN: | 0301-4207 1873-7641 |
DOI: | 10.1016/j.resourpol.2022.102597 |