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This paper investigates the factor content of imports and exports across 40 countries from 1995 to 2006, highlighting crucial policy implications. It focuses on the contributions of various production factors, including ICT and non-ICT capital, and different skill levels of labor. The study aims to identify benefits from stimulus measures, the evolution of skill content in exports, and overall changes in trade dynamics. Utilizing data from the WORLD KLEMS database and conducting extensive analysis, the authors showcase significant findings, particularly related to the USA and Japan's trade structures.
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The Factor Content of Trade:Global trends since 1995 Abdul A. Erumban Marcel P. Timmer Gaaitzen J. de Vries University of Groningen WIOD conference, Vienna, 26-28 May 2010 This project is funded by the European Commission, Research Directorate General as part of the 7th Framework Programme, Theme 8: Socio-Economic Sciences and Humanities. Grant Agreement no: 225 281
Aim of this paper • Measure the factor content of imports and exports by country • Relevant for many important policy questions: • Who benefits from the stimulus package for car manufacturers in Europe? • Who is adding the ‘brains’ to electronic products, and is this changing over time? • Is a country upgrading the skill-content of its exports? Or which exported products see an increase in the skill-content?
Aim of this paper • Measure the factor content of tradefor • The 40 countries in WIOD • The period 1995-2006 Distinguish production factors: ICT and non-ICT capital, low-, medium-, and high-skilled employment Allow for trade in intermediate inputs Allow for differences in technology across countries (e.g. because of factor price differences)
Related literature • Studies related to the effectiveness of import-substitution policies (e.g. Syrquin and Urata 1986 JDE; Chenery, Robinson, and Syrquin 1986) (as well as for projection and forecasting purposes) • Vertical specialization (Gourevitch 2000 WD; Hummels et al. 2001, JIE) • Factor content of trade, testing Heckscher-Ohlin-Vanek predictions (Dietzenbacher and van der Linden 1995 JRS; Davis and Weinstein 2001 AER; Reimer 2006 JIE; Johnson 2008; Trefler and Zhu 2010 JIE; Johnson and Noguera 2010 JIE; Feenstra and Hong 2007 NBER)
Data (1) • Data requirements to measure the factor content of trade: • By country for the period 1995-2006: • Supply and Use tables • AM, the N x N imported coefficient matrices • AD, the N x N domestic coefficient matrices • Bilateral trade data • WORLD KLEMS database • By country and industry for the period 1995-2006: • Capital compensation by industry • Low-, medium-, and high-skilled employment • PPPs (current version uses exchange rates)
Data (2) • Major data steps: • Obtain and harmonize official Supply and Use tables. • Benchmark SUTs on the national accounts and inter/extrapolate SUTs using the SUTRAS program (Temurshoev and Timmer 2010). • Construction of a KLEMS database for non-EU countries • Construction of global input-output matrix using imported coefficient matrix and bec classification
Methodology (1) • Net output of goods N for country C: yC= xC- AxC(1) where, yC is net output (NC x 1), xC is an (NC x 1) gross output vector, and A is an interregional input-output matrix of dimension (NC x NC) • Trade in goods: tC = yC – dC (2) where tC represents country C’s exports of goods (NC x 1) for intermediate or final use, and dC is demand for final use.
Methodology (2) • Define a total factor input matrix: • B* = B ( I – A)-1 (3) • Where B is a direct factor input matrix (F x NC), I an identity matrix, and B* the total factor input matrix. • The Measured Factor Content of Trade (MFCT) for country C is: • B*tC= B*yC – B*dC (4)
Concluding remarks • USA relatively large exporter of IT capital and high-skilled employment compared to Japan in 1995 • Much further data work is needed (interregional table for 40 WIOD countries, factor content for non-EU countries) • Measure factor content using volumes instead of values • Methodologically advance using price indices • Many applications for policy analysis appear feasible.
