The energy-bias of North-South technology spillovers - a global, bilateral, bisectoral trade analysis


Hübler, Michael ; Glas, Alexander


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URL: https://ub-madoc.bib.uni-mannheim.de/33782
URN: urn:nbn:de:bsz:180-madoc-337822
Document Type: Working paper
Year of publication: 2013
The title of a journal, publication series: ZEW Discussion Papers
Volume: 13-031
Place of publication: Mannheim
Publication language: English
Institution: Sonstige Einrichtungen > Zentrum für Europ. Wirtschaftsforschung (ZEW)
MADOC publication series: Veröffentlichungen des ZEW (Zentrum für Europäische Wirtschaftsforschung) > ZEW Discussion Papers
Subject: 330 Economics
Classification: JEL: C23 , F18 , F21 , O13 , O33 , O47 , Q43,
Keywords (English): Energy intensity , labor intensity , trade , technology diffusion , convergence , developing countries
Abstract: We examine variations in the South-North ratios (emerging vs. industrialized countries) of energy and labor intensities driven by imports. We use the novel World Input-Output Database (WIOD) that provides bilateral and bisectoral data for 40 countries and 35 sectors for 1995-2009. We find South-North convergence of energy and labor intensities, an energy bias of import-driven convergence and no robust difference between imports of intermediate and investment goods. Accordingly, trade helps emerging economies follow a ’green growth’ path, and trade-related policies can enhance this path. However, the effects are economically small and require a long time horizon to become effective. Trade-related policies can become much more effective in selected countries and sectors: China attenuates labor intensity via imports of intermediate goods above average. Brazil reduces energy intensity via imports of intermediate and investment goods above average. Production of machinery as an importing sector in emerging countries can immoderately benefit from trade-related reductions in factor intensities. Electrical equipment as a traded good particularly decreases energy intensity. Machinery particularly dilutes labor intensity. Our main results are statistically highly significant and robust across specifications.

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