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Economic production

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The authors wish to thank the World Bank for financial support and accesses to information sources. For many helpful comments and suggestions, the authors are also grateful to Nicholas Treich and other conferees at the European Society for Benefit-Cost Analysis first annual meeting at the Toulouse School of Economics, November 2019; Bryan Land and other participants at a World Bank stakeholder meeting in Sydney Australia, November 2018; Jonathan Wiener, of Duke University; Steve Grimsley, a Senior Geophysical Advisor, previously of Hess Corporation; and Chris Colton, founder of Hexis Energy Trading, LLC. Carl Brown-Grimm and Shu-Chuan Chiu provided essential research assistance. Notwithstanding this excellent input, the authors bear exclusive responsibility for the findings, judgements, and conclusions in this article.

Cost-Benefit Analysis --- Deep Sea Mining --- Energy --- Environmental Management --- Extractive Industries --- Fundamental Uncertainty --- Industry --- International Seabed Authority --- Mining --- Mining and Extractive Industry (Non-Energy) --- Mining Lease --- Natural Resource Management --- Oceans --- Seabed Mining --- Water Resources

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In this paper we review a number of analytical methods and issues related to identifying and estimating the source of productivity growth. The two major methods used in measuring productivity growth -- index number and econometric estimation approach -- are briefly discussed. Substantive issues such as the contribution of R&D capital and R&D spillovers, infrastructure capital, allocative distortions, nature of the market structure and technological advancement on productivity growth at various levels of aggregation are examined. The attributes of the static and dynamic factor demand models used to estimate the contribution of different inputs to productivity growth are described and the evaluation of the production process changes in response to exogenous factors and their impact on productivity growth are discussed. Econometric issues and data considerations for proper estimation of the underlying structural models are noted briefly as well.