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Groningen Growth and Development Centre (GGDC) 25th anniversary | 28-30 June 2017

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Over the years, OECD work on productivity and globalisation has closely mirrored the work of the GGDC on these issues, reflecting considerable cooperation over the past 25 years. Dirk Pilat, Deputy Director of the OECD Directorate for Science, Technology and Innovation, presented OECD work on productivity and Global value chains - an overview and cooperation with the GGDC.

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Groningen Growth and Development Centre (GGDC) 25th anniversary | 28-30 June 2017

  1. 1. OECD WORK ON PRODUCTIVITY AND GLOBAL VALUE CHAINS – LESSONS LEARNED AND NEW DIRECTIONS Dirk Pilat, Paul Schreyer, Colin Webb and Norihiko Yamano, OECD GGDC Anniversary Conference, Groningen, 28 June 2017
  2. 2. Outline 2 1. Some background 2. Productivity – data, methods and analysis 3. GVCs – data, methods and analysis 4. Conclusions
  3. 3. – OECD – currently 35 member countries, but close engagement with over 100 countries – Productivity was already a key focus of the OECD’s predecessor, the OEEC, e.g.: • European Productivity Agency from 1953 to 1960 • Studies inspiring GGDC work, e.g. Paige and Bombach (1959) – Globalisation also a natural focus – GVCs only later – Regular focus on both productivity and globalisation as drivers of growth. Three aspects to the work: 1. Methodology 2. Data 3. Analysis and policy recommendations 1. Background – the OECD 3
  4. 4. Initially, little interaction between productivity analysis & national accounts and large gaps in the national accounts framework, e.g.: – no recognition of capital services, and no breakdown in the price and volume of capital services; – the use of index number formulas with a fixed base year – an asset boundary largely confined to tangible or physical capital. 2. Productivity - methodology 4
  5. 5. Convergence through: 1. SNA revisions, especially 1993 (e.g. index numbers, software as intangible asset) 2. OECD Productivity Manual (2001) 3. Extensive debate on ICT and productivity and impacts on measurement in 1990s (e.g. hedonic prices and OECD Handbook by Jack Triplett) 4. Blueprint for US accounts (Jorgenson and Landefeld, 2005) and 2008 SNA revision (e.g. R&D) 5. EUKLEMS project – dialogue on measurement 6. OECD Manual on Capital Measurement and Handbook on Capital Measures of IPR 7. Expert group on Supply-Use Tables 8. Natural resources and capital 2. Productivity - methodology 5
  6. 6. At first, mainly analysis at aggregate level: – But inconsistencies in data and gaps, e.g. in hours worked and capital – OECD Productivity Database since 2003 STAN database developed as of 1990, first released in 1992 Also, growing number of policy indicators, e.g. product market regulation, labour markets, trade, FDI, etc. 2. Productivity – data and the STAN database, … 6
  7. 7. … enabling the 2017 OECD Compendium of Productivity Indicators 7 www.oecd.org/std/productivity-stats
  8. 8. Beyond aggregates and sectoral data: • Administrative data, such as patent data. • Private sources of micro data, notably the ORBIS database developed by Bureau Van Dijk, e.g. in Future of Productivity (OECD, 2015a). • Official micro data from statistical offices that are used in OECD analysis through the use of software routines that are applied by national statistical agencies to generate new and policy-relevant micro-aggregated indicators, e.g. in MultiProd project. 2. Productivity analysis – a growing use of micro data 8
  9. 9. 2. Productivity – breaking down growth differences 9 -5 0 5 10 TUR IRL KOR POL SWE DEU JPN OECD USA CAN GBR AUS EU28 FRA BEL NLD FIN ESP ITA 2009-2015 2001-2007 Growth in GDP per capita -5 0 5 10 2009-2015 2001-2007 = Growth in GDP per hour worked -5 0 5 10 2009-2015 2001-2007 + Growth in hours worked per capita Contributions to growth in GDP per capita (% change at annual rate) OECD (2017), OECD Compendium of Productivity Indicators 2017, OECD Publishing, Paris. http://dx.doi.org/10.1787/pdtvy-2017-en
  10. 10. 2. Productivity – looking beyond the aggregate growth rate (with Orbis) 10 The productivity gap between the globally most productive firms and other firms has widened Note: “Frontier firms” is the average labour productivity (value added per worker) of the 100 or 5% globally most productive firms in each two-digit industry. “Non-frontier firms” is the average of all firms, except the 5% globally most productive firms. Source: OECD preliminary results based on Andrews, D., C. Criscuolo and P. Gal (2016), “Mind the Gap: Productivity Divergence between the Global Frontier and Laggard Firms”, OECD Productivity Working Papers, Orbis database of Bureau van Dijk.
  11. 11. In some sectors, the productivity divergence is more marked ICT services Non-ICT services Note: Excluding the financial sector -0.2 0.0 0.2 0.4 0.6 0.8 1.0 Frontier firms Laggards Top 10% Top 2% -0.2 0.0 0.2 0.4 0.6 0.8 1.0 Frontier firms Laggards Top 10% Top 2% Source: Andrews, D., Criscuolo C., and Gal P. N., “The Best versus the Rest: The Global Productivity Slowdown, Divergence across Firms and the Role of Public Policy”, OECD Productivity Working Papers, 2016-05, OECD Publishing, Paris. The divergence in multi-factor productivity growth
  12. 12. 2. But is the problem about succeeding at the top or dragging at the bottom... or both? Bottom decile 4th-6th decile Top decile Source: OECD Multiprod project, preliminary results, May 2016, see: http://www.oecd.org/sti/ind/multiprod.htm Canada manufacturing sector Canada non-financial business services -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 2000 2002 2004 2006 2008 2010 2012 -0.1 0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 2000 2002 2004 2006 2008 2010 2012 Denmark manufacturing sector Denmark non-financial business services -0.4 -0.3 -0.2 -0.1 0 0.1 2000 2002 2004 2006 2008 2010 2012 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5 2000 2002 2004 2006 2008 2010 2012
  13. 13. 13 Productivity Divergence is more marked at the bottom of the distribution Year fixed effects of a regression of dispersion in log(LP_VA) and in log(MFP_Wooldridge), Within country-sector pairs Source: OECD Multiprod project, preliminary results, October 2016, see: http://www.oecd.org/sti/ind/multiprod.htm
  14. 14. Compare year fixed effects for divergence at: • Top (90-50 wage ratio) • Bottom (50-10 wage ratio) of wage distribution. Results: – Divergence more pronounced for the bottom half of the wage distribution. Wage dispersion also comes mostly from the bottom of the distribution Source: OECD Multiprod project, preliminary results, October 2016, see: http://www.oecd.org/sti/ind/multiprod.htm
  15. 15. 2. Productivity – the Global Forum on Productivity 15 • 2017 Annual Conference of the Global Forum on Productivity (26-27 June), Budapest – “Openness, global value chains, and productivity-enhancing policies” • Opening speeches from OECD Secretary General Angel Gurría and Hungarian Minister of National Economy, Mihály Varga • Themes to include productivity benefits from openness and GVCs; MNEs, knowledge spillovers and upgrading; digital transformation, GVCs and productivity… http://oe.cd/GFP2017.
  16. 16. 2. Productivity – the OECD’s work today 16 • Productivity has become a central part of the OECD’s agenda: – Part of overall OECD narrative on inclusive and sustainable growth – Focus on understanding and ultimately addressing the slowdown in productivity growth – Important links to other challenges, e.g. environmental sustainability and inequality • More demand-driven: – Strong interest from governments – Establishment of Global Forum on Productivity • Stronger foundation in (cross-country) microdata, to complement analysis based on aggregate and structural data – many new insights emerging
  17. 17. Genesis of IO work at OECD Early 1990s Structural change and impact of embodied R&D on productivity Data Requirements: - Business R&D expenditure by industry - Output, value added and employment by industry - Bilateral trade by industry - Harmonised national Input-Output tables Birth of the STAN family of databases … 3. The origins of GVC and IO analysis 17
  18. 18. - 10 countries - 5 benchmark years from ≈ 1970 to 1990 - 36 industries – ISIC Rev.2 (SNA68) - Current and constant prices - Investment matrices. - Data still available on request … OECD’s first I-O publication - 1995 18
  19. 19. IO revisited Early 2000s - 24 countries - benchmark year ≈ 1995 - 36 industries – ISIC Rev.3 (SNA93) - Current prices Ahmad, N. and A. Wyckoff (2003), "Carbon Dioxide Emissions Embodied in International Trade of Goods", STI Working Paper, No. 2003/15, DOI: http://dx.doi.org/10.1787/421482436815 Phase 2 Embodied CO2 - Part 1 19
  20. 20. consolidation of IO work 2006 - 2009 - 40+ countries (most OECD, G20) - Years ≈ 1995, 2000 and 2005 - 48 industries – ISIC Rev.3 (SNA93) - Current prices Nakano, S., et al. (2009), "The Measurement of CO2 Embodiments in International Trade: Evidence from the Harmonised Input-Output and Bilateral Trade Database", OECD STI Working Papers, No. 2009/03, DOI: http://dx.doi.org/10.1787/227026518048 Phase 2 Embodied CO2 - Part 2 20
  21. 21. Global Value Chains: of growing interest 2005 2007 2008
  22. 22. From harmonised IOTs to Inter-Country Input Output (ICIO) system 2009 +++ - Financial Crisis 2008-09 … led to worldwide collapse in international trade and … some head-scratching: why so widespread ? - Calls for new metrics to understand GVCs - Strong advocacy from WTO and other international orgs 1st release of TiVA indicators 16th January 2013. BIG LAUNCH – press conference (OECD SG / WTO DG etc). 40 countries, 18 aggregate industries; 3 years: 2005, 2008, 2009; supporting documentation, dedicated website and A VIDEO Phase 3 of the IO work: The TiVA explosion 22
  23. 23. 23 OECD-WTO TiVA database and GVC synthesis for Ministers
  24. 24. 24
  25. 25. Then expansion 25 January 2013 40 countries 18 industries 3 years May 2013 57 countries 18 industries 5 years October 2015 61 countries 34 industries 7 years December 2016 63 countries 34 industries 17 years Underlying ICIO tables: 6.9 million cells per year
  26. 26. 63 Countries Covering all 35 OECD countries, all EU28, all G20, most ASEAN and APEC economies and selection of South American countries (most recent additions: Colombia, Costa Rica, Croatia, Morocco, Peru and Tunisia) Firm heterogeneity within manufacturing industry : China (exporters and non-exporters) and Mexico (global manufacturing firms) 34 Industries: from including 16 manufacturing sectors and 14 service sectors 17 years: 1995-2011 First set of “nowcasts” now available up to 2014 Latest set of indicators – TiVA 2016 26
  27. 27. Exports require imports 27 Services matter New bilateral trade patterns emerge Country / industry integration into GVCs Some basic messages from the TIVA work 0% 5% 10% 15% 20% 25% USA JPN DEU KOR IND GBR FRA CAN AUS RUS Gross exports Domestic value added embodied in foreign final demand 0% 2% 4% 6% 8% 10% 12% 14% JPN USA KOR DEU AUS TWN SAU RUS BRA HKG Gross imports Foreign value added in domestic final demand 0% 10% 20% 30% 40% 50% TWN SGP KOR MYS THA KHM VNM FIN TUN POL CHN MEX SWE CRI ESP ITA TUR DEU FRA IND PHL CAN GBR CHE HKG CHL NLD ZAF NOR NZL USA JPN AUS ARG RUS IDN BRA COL BRN SAU 2011 2009 2008 0% 20% 40% 60% 80% 100% SAU BRN COL IDN CHL MEX VNM NOR KOR MYS CHN RUS THA ARG ZAF CAN AUS TWN PHL BRA JPN TUN DEU POL TUR FIN ITA KHM USA CRI NZL IND ESP SWE CHE FRA GBR SGP NLD HKG Domestic VA content Foreign VA content SNA service export share 0% 10% 20% 30% 40% 50% 60% Agriculture Mining Foodproducts Textiles&apparel Wood&paper Coke&petroleum Chemicals Rubber&plastics Non-metallic minerals Basicmetals Fabricatedmetals Machinery ICT&electronics Electricalmachinery Motorvehicles Othertransport Othermanufactures Wholesale,retail& hotels Transport& telecoms Finance& insurance Businessservices Otherservices Total FVA share of gross exports, 2011 FVA share of gross exports, 1995
  28. 28. Challenges of constructing ICIO DATA - Compiling and validating maximum official statistics – from various collections (SNA, international trade, industry stats, HH consumption, TSA etc) from numerous sources: e.g. OECD, UNSD, Eurostat and national statistics offices - Filling gaps and dealing with inconsistencies in data: across sources and both within and between countries. - Balancing everything TECHNICAL - Since beginnings, always pushing the limits of IT environment (at least at OECD … )
  29. 29. So much data to process Trade in services Trade in goods ICIO BTDIxE UN Comtrade OECD ITCS EBTSI eBOPS TiS national SUTs/IOTs SNA by activity STAN, UNSD, Eurostat, SNA main aggregates OECD, UNSD, National harmonised SUTs/ IOTs TiVA IND34 VA/PROD IND34 FD CO2 Jobs/GVCs HH Cons - COICOP Tourism Satellite Non-Res direct
  30. 30. Some particular features of ICIO Accounting for firm heterogeneity in manufacturing: Split tables for China (processors, other exporters and non-exporters) and Mexico (“global manufacturers” versus other firms) To measure Domestic VA in exports or final demand, ideally need to isolate exporters from non-exporters in ICIO (different production characteristics). OECD extended-SUTs initiative encouraging other countries to attempt this. www.oecd.org/sti/ind/tiva/eSUTs_TOR.pdf Separation of “direct purchases by non-residents” from cross- border trade: has sparked interest from Tourism policy analysts Allocation of domestic trade and transport margins from manufacturing output to services: emphasises the service content of manufactured exports None of this is easy …
  31. 31. ICIO extensions – Embodied CO2 revisited UNFCCC COP side events (2009, 2015) OECD Green growth indicators CO2 embodied in international trade: http://oe.cd/io-co2. 0 2 4 6 8 10 12 14 16 18 20 0 2 4 6 8 10 12 14 16 18 20 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 GtCO2 CO2 emissions from fuel combustion Consumption-based (OECD) Production-based (OECD) Production-based (non-OECD) Consumption-based (non-OECD) Net-imports of embodied CO2 into OECD countries Net-exports of embodied CO2 of non-OECD countries
  32. 32. ICIO Extensions – Jobs Origin of demand for manufacturing jobs in OECD, 1995-2011 -7 -5 -3 -1 1 3 EU28 NAFTA Southeast and East Asia (Excl. China) Brazil China India Russia Rest of the World Total Source: OECD (2015), OECD Science, Technology and Industry Scoreboard 2015: Innovation for Growth, OECD Publishing, doi: http://dx.doi.org/10.1787/sti_scoreboard-2015-en. Millions of persons, annual changes by region of demand
  33. 33. TiVA / ICIO: Next steps – from 2017 • Always demand for more countries (Africa?!) and more recent years • Recent regional TiVA meeting – March 2017 • New version being developed based on ISIC Rev.4 (NACE Rev.2) and latest SNA 2008 / BPM6 inputs • Nowcasting: for more timely information, improve methods for extrapolating TiVA indicators to provide figures for more recent years (t-1 rather than t-3). • Better accounting for firm heterogeneity – beyond China and Mexico Linking trade, SNA and business statistics? Fruits of extended SUTs project • Developing and extending the statistical infrastructure 33
  34. 34. 4. Conclusions - The OECD and GGDC Useful and important cooperation in many ways • Among the only organisations seeking to develop large structural databases for policy research – a public good • Friendly competition/cooperation useful to improve quality Inspiration of academic research important for the OECD’s work - Pioneers in some areas, new research questions - Active and early users of the data (e.g. STAN and ICIO test-users) Both seeking to fill gap between statistical concepts and analytical needs Common research interests, e.g. ICT and productivity, GVCs
  35. 35. Some differences • OECD agenda, capacity building & priorities determined by: - Numerous OECD Committees and their Working Parties. Many meetings with many Delegates - Key role in G20 and increasing engagement with non-Members at a global scale (and with many seeking membership) • Access to leaders (including via G20 / G7) - high visibility • Links with regional/international orgs (UN, WTO, EU, APEC etc) • Deep working level relations with policy analysts in Ministries – relevancy, but also high level of scrutiny (e.g. TiVA results) • Active engagement with statistical agencies – setting standards (e.g. SNA) • Challenges in managing high level expectations
  36. 36. Concluding remarks  Research on productivity (including microdata) and IO-based analysis of GVCs are now firmly established as major contributors to economic, environmental and social policy making – no longer niche areas. High visibility and interest from policy makers  Increasing numbers of young researchers attracted by the joys of empirical work with large datasets, e.g. microdata and IO.  National statistical offices motivated to improve underlying statistics e.g. consistent bilateral trade, extended SUTs project etc, and provide access to microdata  Regional TiVA initiatives converging towards common approaches to construct global IOTs (APEC-TiVA, EU Figaro, NAFTA-TiVA etc.)
  37. 37. Thank you Contacts: dirk.pilat@oecd.org, paul.schreyer@oecd.org, colin.webb@oecd.org and norihiko.yamano@oecd.org Twitter: @OECDinnovation and @OECD_Stat Internet resources: Productivity database: www.oecd.org/std/productivity-stats STAN: www.oecd.org/sti/stan TiVA: www.oe.cd/tiva Global Forum on Productivity: www.oecd.org/global-forum- productivity Multiprod: www.oecd.org/sti/ind/multiprod.htm

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