oecd business and finance scoreboard 2017...the 2017 edition of the oecd business and finance...

SCOREBOARD2017

OECD Business and Finance

OECD Business and Finance Scoreboard 2017

This work is published under the responsibility of the Secretary-General of the OECD. The opinions expressed and arguments employed herein do not necessarily reflect the official views of OECD member countries. This document and any map included herein are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. The statistical data for Israel are supplied by and under the responsibility of the relevant Israeli authorities. The use of such data by the OECD is without prejudice to the status of the Golan Heights, East Jerusalem and Israeli settlements in the West Bank under the terms of international law. © OECD 2017

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Foreword

Since the 1980s, the global economic landscape has been reshaped by growing trade, mounting investment flows and the increased participation of emerging markets. Coupled with these developments is a more recent discussion about possible links to the widening productivity gap between firms, the growing presence of state-owned enterprises and a greater reliance on non-bank financing. The 2017 edition of the OECD Business and Finance Outlook focuses on ways to enhance “fairness”, in the sense of strengthening global governance, to ensure a level playing field in trade, investment and corporate behaviour. The Scoreboard complements the Outlook by providing additional granular information on global developments in the corporate sector and financial markets. The Scoreboard includes data and analysis for both OECD countries and, to an increasing extent, for non-OECD economies. It focuses on developments relating to:

• Publicly listed companies, using a dataset of 11 000 large listed companies

• Market-based financing, using data from almost 340 000 individual public equity and corporate bond transactions

• Foreign direct investment activity, applying state-of-the-art methodology developed by the OECD

• Pension funds, building on original data provided by national authorities

• The banking sector, providing a set of accounting and market-based indicators The Scoreboard makes use of data that is collected directly by the OECD as well as calculations that are based on information available in external databases. A detailed description of the methodology for data collection and analysis is provided in the annex.

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Table of contents

Foreword .................................................................................................................................... 3 Acronyms and abbreviations ..................................................................................................... 8 Continued divergence in productivity levels ............................................................................. 9 Global trends in investment opportunities ............................................................................... 10 Global trends in key corporate finance data ............................................................................ 12 Financials is the largest sector in many global benchmarks .................................................... 14 Superstar companies ................................................................................................................ 16 The rise of SOEs: fairness in doing business globally and excess capacities .......................... 18 Corporate bond market continues to grow ............................................................................... 20 Longer maturities for large issuances ...................................................................................... 21 Continued slowdown in non-financial company IPOs ............................................................ 22 Public equity financing for growth companies remains weak ................................................. 23 Financial companies’ use of secondary public equity markets has fallen dramatically .......... 24 The use of corporate bond markets in different sectors ........................................................... 25 Change in industry composition of public equity financing in emerging markets .................. 27 Deteriorating corporate bond rating quality ............................................................................. 29 Global trends in foreign direct investment (FDI) flows ........................................................... 30 Inflow of equity capital showed continued strength in 2016 ................................................... 31 FDI flows in and from resident Special Purpose Entities (SPEs) ............................................ 33 Shifting view of the origin of FDI: FDI statistics by ultimate investing country .................... 36 Round-tripping ......................................................................................................................... 38 OECD returns on investment continued to decline in 2016 .................................................... 39 Regulatory Restrictions to Foreign Direct Investment (FDI) .................................................. 42 Distance-to-default has fallen .................................................................................................. 44 Downsizing in banking sector following the 2008 financial crisis .......................................... 45 Systematic risk in the banking sector ...................................................................................... 47 Openness of banking systems .................................................................................................. 49 Saving-investment correlation ................................................................................................. 51 Exchange rate valuation measure ............................................................................................ 52 OECD pension fund assets grew faster than GDP in 2016 ...................................................... 54 Pension funds exhibited positive real investment rates of return in most markets in 2016 ..... 55 Pension funds are more exposed to equities in 2016 .............................................................. 57 ANNEX: Methodology for data collection and analysis ......................................................... 58

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Figures

Figure 1. Productivity measures for listed non-financial companies .......................................... 9 Figure 2. Dividends and buybacks, cost of equity, cost of capital, leverage and profit

margin .......................................................................................................................... 10 Figure 3. Key financial data for listed non-financial companies .............................................. 12 Figure 4. Share of market capitalisation of economic sectors for selected equity

benchmarks .................................................................................................................. 14 Figure 5A. Market shares, cash, ROE minus cost of capital, leverage and profit

margin for top 10% superstar companies versus the other 90% .................................. 16 Figure 5B. Key corporate finance data for top 10% superstar companies versus other

90% and tax profit optimisation................................................................................... 17 Figure 6. Return on equity minus the cost of capital, leverage and profit margin for

private non-financial companies versus SOEs in advanced and emerging economies .................................................................................................................... 18

Figure 7. Outstanding stock of investment grade and non-investment grade corporate bonds ............................................................................................................................ 20

Figure 8. Global trends in average maturities for corporate bonds........................................... 21 Figure 9. Slowdown in non-financial company initial public offerings (IPOs) ....................... 22 Figure 10. Growth company IPOs in the United States, Europe and Japan ............................. 23 Figure 11. Secondary public offerings...................................................................................... 24 Figure 12. Distribution of non-financial corporate bond issuance among sectors ................... 25 Figure 13. Changing industry composition of public equity market financing in

emerging economies .................................................................................................... 27 Figure 14. Corporate bond rating index .................................................................................... 29 Figure 15. Foreign direct investment inflows by region ........................................................... 30 Figure 16. FDI inflows by instrument ...................................................................................... 31 Figure 17. OECD Resident Special Purpose Entities (SPEs) investment ................................. 33 Figure 18. Inward FDI positions by major ultimate versus immediate investors ..................... 36 Figure 19. Foreign direct investment round-tripping ............................................................... 38 Figure 20. OECD rates of return on inward and outward foreign direct investment ................ 39 Figure 21. OECD FDI Regulatory Restrictiveness Index......................................................... 42 Figure 22. Distance-to-default (DTD) of large listed banks ..................................................... 44 Figure 23. Total assets of large listed banks as percentage of world GDP ............................... 45 Figure 24. Bank beta indicator for large listed banks ............................................................... 47 Figure 25. Deviations from covered interest parity (CIP) on domestic forward (DF)

and non-deliverable forward (NDF) markets ............................................................... 49 Figure 26. Saving-investment correlation ................................................................................. 51 Figure 27. Five-year rolling real exchange rate valuation by country ...................................... 52 Figure 28. Pension funds' annual real net rates of investment return in selected

OECD countries ........................................................................................................... 55

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Tables

Table 1. Average value added and net sales data for listed companies ................................... 9 Table 2. Average dividends and buybacks, cost of equity, cost of capital, leverage

and profit margin ........................................................................................................ 11 Table 3. Key financial data for non-financial listed companies .............................................. 13 Table 4. Share of market capitalisation of economic sectors for selected equity

benchmarks ................................................................................................................. 15 Table 5A. Net sales, EBITDA, total assets and market capitalisation for top 10%

superstar companies versus other 90% ....................................................................... 16 Table 5B. Key corporate finance data for top 10% superstar companies versus other

90% ............................................................................................................................. 17 Table 6. Return on equity minus the cost of capital, leverage and profit margin for

private non-financial companies versus SOEs in advanced and emerging economies ................................................................................................................... 19

Table 7. Outstanding stock of corporate bonds ....................................................................... 20 Table 8. Average maturities for corporate bonds .................................................................... 21 Table 9. Initial public offerings ............................................................................................... 22 Table 10. Growth non-financial company IPOs ...................................................................... 23 Table 11. Secondary public offerings ...................................................................................... 24 Table 12A. Distribution of advanced economy companies’ corporate bond issuance

among sectors ............................................................................................................. 25 Table 12B. Distribution of emerging market companies’ corporate bond issuance

among sectors ............................................................................................................. 26 Table 13A. Distribution of public equity financing among different sectors by

companies from advanced economies ........................................................................ 27 Table 13B. Distribution of public equity financing among different sectors by

companies from emerging markets ............................................................................. 28 Table 14. Distribution of corporate bond issuance among rating categories ........................... 29 Table 15A. FDI inflows by selected regions ........................................................................... 30 Table 15B. FDI outflows by selected regions ......................................................................... 30 Table 16A. FDI inflows by instrument for selected regions.................................................... 31 Table 16B. FDI outflows by instrument for selected regions .................................................. 32 Table 17A. FDI outflows for countries with SPEs .................................................................. 34 Table 17B. FDI inflows for countries with SPEs .................................................................... 35 Table 18. Inward FDI positions by immediate (IMD) versus ultimate (ULT)

investing country for selected OECD countries ......................................................... 37 Table 19. Foreign direct investment round-tripping for selected OECD countries ................. 38 Table 20A. Rates of return on inward foreign direct investment of OECD countries ............. 40 Table 20B. Rates of return on outward foreign direct investment of OECD countries ........... 41 Table 21. OECD FDI Regulatory Restrictiveness Index per sector ........................................ 43 Table 22. Average distance-to-default (DTD) of large listed banks ........................................ 44 Table 23. Total assets (harmonised IFRS) in USD billion of large listed banks by

region or size .............................................................................................................. 46

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Table 24A. Average beta calculated using MSCI regional equity indices for large listed banks ................................................................................................................. 48

Table 24B. Average beta calculated using MSCI global equity index for large listed banks ........................................................................................................................... 48

Table 25A. Deviations from covered interest parity (CIP) on domestic forward (DF) markets ........................................................................................................................ 50

Table 25B. Deviations from covered interest parity (CIP) on non-deliverable forward (NDF) markets ............................................................................................................ 50

Table 26. Saving-investment correlation by region ................................................................. 51 Table 27. Five-year rolling real exchange rate valuation by country ...................................... 53 Table 28. Pension fund investments ........................................................................................ 54 Table 29. Pension funds' annual real net rates of investment return in selected OECD

countries ...................................................................................................................... 56 Table 30. Pension fund asset allocation in selected asset classes in selected OECD

countries ...................................................................................................................... 57

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Acronyms and abbreviations

BRICS Brazil, Russia, India, People’s Republic of China (China), and South Africa

BRIICS Brazil, Russia, India, Indonesia, China, and South Africa

CAPEX Company capital expenditure

CIP Covered interest parity

COD Cost of debt

COE Cost of equity

COK Cost of capital

DF Domestic forward

DTD Distance-to-default

EBITDA Earnings before interest, taxes, depreciation and amortisation

EME Emerging market economy

FDI Foreign direct investment

GARCH Generalized Auto Regressive Conditional Heteroskedasticity

GICS Global Industry Classification Standard

G-SIB Global Systemically Important Bank

IMD Immediate investing country

IG Investment grade

IPO Initial public offering

M&A Mergers and acquisitions

MSCI Morgan Stanley Composite Index

NDF Non-deliverable forward

OECD Organisation for Economic Co-operation and Development

R&D Research and development

REIT Real estate investment trusts

ROE

ROI

Return on equity

Return on investment

SPEs Special purpose entities

SPO Secondary public offering (follow-on offering)

ULT Ultimate investing country

9

Figure 1. Productivity measures for listed non-financial companies, 2002–2016

Table 1. Average value added and net sales data for listed companies, 2005–2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Value added per capita Advanced economies 0.15 0.14 0.14 0.14 0.14 0.14 0.15 0.14 0.15 0.15 0.14 0.14 Emerging markets 0.04 0.05 0.06 0.06 0.05 0.06 0.06 0.06 0.06 0.05 0.05 0.05 OECD 0.15 0.14 0.15 0.15 0.14 0.15 0.16 0.15 0.15 0.15 0.14 0.14 United States 0.21 0.21 0.21 0.22 0.21 0.23 0.23 0.23 0.22 0.23 0.21 0.22 Euro area 0.10 0.10 0.12 0.12 0.11 0.11 0.12 0.11 0.12 0.11 0.10 0.10 Japan 0.09 0.07 0.07 0.07 0.07 0.08 0.08 0.08 0.07 0.07 0.07 0.07

Net sales per capita Advanced economies 0.31 0.32 0.35 0.36 0.33 0.36 0.38 0.38 0.37 0.35 0.32 0.32 Emerging markets 0.13 0.16 0.18 0.20 0.18 0.21 0.25 0.24 0.25 0.23 0.21 0.21 OECD 0.32 0.33 0.36 0.37 0.34 0.36 0.39 0.39 0.38 0.35 0.33 0.32 United States 0.32 0.33 0.35 0.36 0.34 0.36 0.39 0.39 0.36 0.37 0.35 0.36 Euro area 0.30 0.32 0.36 0.39 0.33 0.35 0.38 0.36 0.40 0.34 0.30 0.28 Japan 0.42 0.40 0.42 0.44 0.42 0.47 0.50 0.49 0.42 0.39 0.39 0.40

Notes: All data are expressed in current US dollar billion per one thousand employees. Value added: sum of personnel expenses and EBITDA (i.e. income before interest, taxes, depreciation and amortisation). Net sales: total operating revenues less various adjustments to gross sales.

Source: Bloomberg, OECD calculations. See Annex for details.

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Continued divergence in productivity levels

Productivity measured both as company value-added (wages plus EBITDA) per employee and net sales per employee has stagnated and declined following the 2008 financial crisis. While net sales per employee in emerging economies, as a result of their increased participation in global value chains, has caught up with levels in advanced economies, this has not enabled a similar catch up with respect to productivity measured as value added per employee.

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Figure 2. Dividends and buybacks, cost of equity, cost of capital, leverage and profit margin, 2002–2016


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Advanced: Leverage Emerging: LeverageAdvanced: Profit margin (RHS) Emerging: Profit margin (RHS)

Global trends in investment opportunities

In emerging markets, both the return on equity (ROE) minus the cost-of-equity (COE) and the ROE minus cost-of-capital (COK) are declining. Even the ROE minus COK has been negative since 2011. In addition, emerging markets exhibit a continuous decline in profit margins since 2003, becoming weaker than profit margins of companies in advanced economies since 2013. This is consistent with other evidence that these economies exhibit excess capacity in important sectors resulting from overinvestment. With a decrease in investment opportunities, dividends and buybacks have returned to levels immediately before the 2008 financial crisis. Debt financing is still greater in advanced economies but emerging economies are catching up.

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Table 2. Average dividends and buybacks, cost of equity, cost of capital, leverage and profit margin, 2005–2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

ROE minus COE (%) Advanced economies 8.30 8.60 8.30 2.10 2.10 5.30 4.20 2.70 3.60 4.30 0.60 1.50 Emerging markets 3.10 3.50 3.00 -0.40 -0.30 0.90 0.20 -2.20 -3.50 -4.00 -5.40 -4.70 OECD 8.50 8.90 8.60 2.50 2.30 5.50 4.60 3.10 4.00 4.60 1.00 1.90 United States 9.10 9.40 8.70 2.60 4.60 7.00 7.10 5.40 7.00 7.10 3.40 4.30 Euro area 11.50 10.60 11.30 5.40 1.70 6.10 4.30 2.40 2.50 4.00 0.80 1.60 Japan 5.80 5.50 4.40 -3.70 -0.20 2.10 0.00 1.00 1.30 3.60 1.70 2.70

ROE minus COK (%) Advanced economies 9.36 9.55 9.58 5.24 4.53 7.86 7.59 6.39 6.76 8.06 4.69 5.67 Emerging markets 4.80 6.17 6.21 3.88 2.87 4.13 4.45 2.75 1.50 1.25 0.40 0.94 OECD 9.45 9.73 9.70 5.38 4.59 7.93 7.81 6.60 6.90 8.10 4.74 5.78 United States 9.51 9.62 9.41 5.45 6.48 9.21 10.40 9.01 10.29 11.01 7.93 8.64 Euro area 12.36 11.06 11.54 7.83 4.08 8.46 7.30 6.24 5.48 7.64 4.64 5.73 Japan 7.16 6.98 6.10 -1.18 1.78 4.12 2.55 3.67 3.62 6.02 3.66 5.42

Dividends & buybacks (% of net sales) Advanced economies 3.23 3.65 4.03 3.55 2.06 2.59 3.23 3.03 2.84 3.23 3.71 3.57 Emerging markets 1.75 2.07 1.37 1.72 1.35 1.16 2.39 2.33 2.55 1.84 1.48 1.24 OECD 3.20 3.62 4.05 3.50 2.05 2.57 3.20 3.03 2.83 3.23 3.72 3.55 United States 4.23 4.73 5.64 4.26 2.81 3.59 4.40 4.38 4.50 5.22 5.68 5.34 Euro area 2.36 2.78 3.15 3.74 2.61 2.04 2.56 2.00 1.77 1.52 2.04 2.14 Japan 0.96 1.18 1.56 1.72 0.65 0.87 1.19 1.23 1.00 1.28 1.54 1.74

Leverage (%) Advanced economies 36.11 36.18 37.71 40.03 39.17 36.80 37.37 37.92 38.03 39.08 40.31 41.19 Emerging markets 26.91 26.48 27.11 29.77 31.34 30.79 31.72 32.90 34.31 36.69 37.24 35.91 OECD 36.41 36.39 38.10 40.46 39.63 37.27 37.83 38.38 38.56 39.68 40.89 41.52 United States 37.34 37.37 39.28 42.76 40.07 38.58 39.33 40.69 40.23 42.64 45.05 46.27 Euro area 41.14 41.63 43.75 43.95 46.18 42.36 42.33 42.93 41.44 41.03 40.82 41.43 Japan 35.82 34.17 34.40 37.55 37.05 36.10 35.96 34.15 36.61 35.66 34.05 34.01

Profit margin (%) Advanced economies 10.29 10.55 10.57 8.92 7.90 9.80 9.16 8.15 8.95 9.00 8.52 8.81 Emerging markets 15.34 15.39 14.84 12.62 11.90 12.55 11.70 9.74 9.24 8.63 8.00 8.51 OECD 10.29 10.57 10.56 8.96 7.91 9.80 9.23 8.20 9.02 9.06 8.57 8.84 United States 10.84 11.18 11.08 9.83 8.64 10.82 10.59 9.75 11.40 11.06 10.57 10.50 Euro area 10.00 9.95 10.50 9.12 7.52 9.29 8.41 7.33 6.91 7.08 6.60 7.38 Japan 6.93 6.90 6.80 3.86 4.29 6.04 4.96 5.08 5.14 5.85 6.13 6.63

Notes: ROE (return on equity): ratio of net income to common equity. COE (cost of equity): sum of dividend and buyback yield and underlying trend in EPS growth. COK (cost of capital): weighted average (by the share of equity and debt in total assets, respectively) sum of cost of equity and cost of debt. Dividend and buybacks ratio is expressed in percent of net sales. Leverage: ratio of long-term debt to the sum of long-term debt plus equity. Profit margin: ratio of operating income to total revenues.


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Figure 3. Key financial data for listed non-financial companies, 2002–2016

Source: Bloomberg, Thomson Reuters, OECD calculations. See Annex for details.

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Global trends in key corporate finance data

Companies in emerging economies invest much more as a percentage of net sales than companies in advanced economies. However, advanced economies exhibit higher levels of free cashflow than emerging economies and are benefitting from efficacy of three corporate strategies that boost their productivity: higher research and development (R&D), higher international sales and more mergers and acquisitions (M&A) activities to rationalise business models. These higher M&A and R&D activities in advanced economies are reflected in the share of intangible assets in total assets, which is much weaker in emerging economies.

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Table 3. Key financial data for non-financial listed companies, 2005–2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Capital expenditure (% of net sales) Advanced economies 6.37 6.75 6.90 7.03 6.43 6.17 6.55 6.93 6.91 6.99 7.02 6.72 Emerging markets 11.67 11.90 12.94 12.97 12.57 11.31 10.84 10.69 10.43 9.65 9.82 9.36 OECD 6.30 6.69 6.83 6.98 6.35 6.07 6.46 6.87 6.86 6.94 6.94 6.64 United States 5.61 6.36 6.49 6.57 5.68 5.68 6.27 6.89 6.77 7.16 7.14 6.67 Euro area 6.71 7.02 7.17 7.35 7.11 6.58 6.36 6.30 6.21 6.11 6.63 6.62 Japan 5.85 5.58 5.71 5.94 5.05 4.59 4.87 5.30 5.71 5.76 5.67 5.82

Free cashflow (% of net sales) Advanced economies 5.05 4.77 4.67 3.38 5.84 5.46 4.15 3.85 4.03 4.04 4.61 5.16 Emerging markets 4.43 4.02 2.42 0.48 2.51 1.85 0.10 0.71 1.18 1.96 2.83 3.12 OECD 5.02 4.76 4.68 3.33 5.92 5.53 4.18 3.87 4.02 4.21 4.78 5.37 United States 6.02 5.35 5.53 4.67 6.60 6.39 6.15 5.43 5.99 5.51 6.17 6.75 Euro area 4.81 4.37 4.46 2.55 5.17 4.59 3.28 3.36 3.21 3.42 3.63 3.89 Japan 2.39 2.71 2.50 0.61 5.34 4.52 2.00 2.14 1.80 2.47 2.88 3.66

R&D expenditure (% of net sales) Advanced economies 3.26 3.22 3.22 3.19 3.54 3.34 3.31 3.42 3.17 3.35 3.71 3.93 Emerging markets 0.61 0.62 0.64 0.71 0.85 0.81 0.88 1.00 1.02 1.12 1.42 1.51 OECD 3.25 3.21 3.21 3.18 3.54 3.34 3.30 3.42 3.17 3.36 3.73 3.95 United States 4.02 4.27 4.12 3.97 4.68 4.51 4.56 4.83 4.66 4.92 5.58 5.96 Euro area 2.72 2.46 2.59 2.51 2.85 2.60 2.49 2.51 2.33 2.57 2.84 3.03 Japan 3.07 2.92 2.91 3.22 3.26 3.06 3.06 3.06 2.91 2.74 2.80 2.90

International sales (% of net sales) Advanced economies 48.60 44.87 47.03 50.51 50.73 52.37 52.97 55.24 53.44 58.61 56.78 54.97 Emerging markets 37.37 34.56 37.50 43.06 37.81 35.51 37.89 36.13 36.28 38.60 41.26 38.13 OECD 48.50 44.70 46.73 50.38 50.51 52.08 52.44 54.27 52.68 57.84 55.92 54.20 United States 38.87 38.59 40.14 42.90 41.47 42.67 44.89 44.39 42.27 43.98 42.07 40.75 Euro area 60.74 52.14 55.33 57.21 60.59 67.37 61.22 66.89 60.33 75.33 74.65 72.52 Japan 37.64 34.83 36.92 41.09 43.65 33.12 41.46 44.77 54.24 52.74 49.40 48.70

M&A deal value (% of net sales) Advanced economies 3.95 5.50 6.37 4.98 3.61 4.38 4.17 3.53 3.34 4.60 5.51 5.83 Emerging markets 7.40 4.25 8.07 4.20 4.56 4.17 2.97 3.07 3.65 4.34 4.62 4.64 OECD 3.94 5.46 6.36 5.06 3.70 4.42 4.28 3.63 3.39 4.61 5.61 5.93 United States 4.62 7.71 7.89 6.36 4.55 5.44 4.74 4.90 4.62 5.13 6.86 7.30 Euro area 3.70 4.46 5.36 4.85 3.64 3.24 3.12 2.02 2.25 5.13 7.51 7.41 Japan 1.84 3.01 2.12 2.42 2.02 2.13 2.28 2.12 2.68 2.55 2.35 2.98

Intangible assets (% of total assets) Advanced economies 16.09 16.40 16.86 18.89 18.12 18.60 18.67 18.60 19.32 20.13 20.29 20.86 Emerging markets 5.40 6.05 6.73 8.93 7.45 7.71 8.35 8.04 7.77 8.23 9.18 8.88 OECD 16.27 16.57 17.07 19.19 18.36 18.94 19.06 19.00 19.82 21.15 21.33 21.97 United States 20.20 23.18 23.44 23.22 23.82 24.27 24.85 24.48 25.08 25.34 26.75 27.51 Euro area 19.32 17.70 18.71 21.70 21.73 24.12 23.25 22.68 22.49 25.18 24.24 25.05 Japan 3.06 2.90 3.20 4.34 4.91 4.42 4.87 5.98 6.97 7.78 6.99 7.23

Notes: Capital expenditure: amount the company spent on purchases of tangible fixed assets. Free cash flow: operating cash flow minus capital expenditures. R&D expenditure: operating expense related to the research and development of a company's products or services. International sales: Sales generated from operations in foreign countries. M&A deal value: declared amount effectively paid by the acquirer for the target. Intangible assets: other assets not having a physical existence. The value of these assets lies in their expected future return.

Source: Bloomberg, Thomson Reuters, OECD calculations. See Annex for details.

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Figure 4. Share of market capitalisation of economic sectors for selected equity benchmarks, 2003-2016

Notes: 2008 and 2009 are excluded (based on the NBER’s classification of the Great Recession, which began in December 2007 and ended in June 2009) to not contaminate average calculations with cyclical downturns. Source: Thomson Reuters, OECD calculations.

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Financials is the largest sector in many global benchmarks

After the 2008 financial crisis, the financial sector still dominates many equity benchmarks. In the S&P 500, non-bank financial institutions (i.e., asset managers, real estate funds, life insurance and non-life insurance companies) account for a greater share of total market capitalisation than banks. In other benchmarks, banks typically outweigh non-bank financial institutions.

15

Table 4. Share of market capitalisation of economic sectors for selected equity benchmarks, 2005-2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

US benchmark: S&P 500 Consumer discretionary 10.5 10.0 9.1 10.8 10.5 10.7 11.1 11.5 12.0 11.6 12.6 11.7 Consumer staples 7.6 7.8 8.8 10.2 9.4 9.2 9.9 9.3 9.1 8.8 9.4 8.6 Energy 7.6 7.7 10.4 11.1 9.5 9.7 10.0 8.9 8.3 6.7 5.1 5.9 Healthcare 10.5 9.3 9.6 12.2 10.2 8.5 9.4 9.3 9.8 10.7 11.4 9.9 Industrials 10.1 9.5 10.4 10.5 9.5 9.8 10.0 9.6 10.1 9.4 9.0 9.5 Information technology 11.6 11.6 13.5 12.6 15.8 14.7 14.6 14.0 13.7 15.8 16.8 16.6 Materials 2.0 2.0 2.3 2.0 2.5 2.8 2.6 2.6 2.4 2.1 1.7 1.8 Telecommunication services 2.4 2.8 2.9 3.1 2.5 2.4 2.5 2.3 1.7 1.8 1.9 2.1 Utilities 2.7 2.8 2.9 3.5 3.0 2.7 3.2 2.8 2.4 2.6 2.3 2.5 Financials 17.5 18.2 15.0 12.0 13.5 14.7 13.4 14.9 15.2 15.3 14.9 15.8 Banks 8.1 8.0 5.8 5.3 5.7 5.7 4.2 5.0 5.1 4.9 4.8 5.3 Non-bank financial institutions 9.4 10.2 9.3 6.7 7.8 9.0 9.2 9.8 10.2 10.3 10.1 10.5

European benchmark: STOXX 600 Consumer discretionary 6.5 5.8 6.2 6.4 5.4 6.2 6.4 6.0 6.6 6.7 7.4 6.8 Consumer staples 9.1 9.2 10.6 11.3 11.5 13.7 15.4 16.5 16.1 16.3 17.6 17.4 Energy 7.7 7.0 8.1 9.0 8.5 8.0 9.2 7.6 6.5 5.3 4.5 5.5 Healthcare 7.1 6.0 5.5 8.2 7.1 6.9 8.6 8.3 8.2 9.1 9.9 9.3 Industrials 7.5 7.7 8.5 8.5 8.7 10.0 9.6 10.1 10.3 9.8 10.1 10.8 Information technology 2.7 2.3 2.4 2.3 2.1 2.3 2.3 2.5 2.6 2.6 2.8 2.8 Materials 4.6 5.6 6.8 6.5 7.8 9.3 9.4 8.6 7.1 6.8 5.5 6.3 Telecommunication services 6.1 4.8 5.2 6.4 5.1 4.7 5.0 4.0 4.0 3.9 4.1 3.7 Utilities 4.4 5.9 7.0 8.7 6.7 5.5 5.1 4.0 3.9 3.9 3.5 3.5 Financials 22.1 22.9 19.8 16.3 18.5 16.7 14.4 16.2 17.4 17.8 17.3 16.9 Banks 15.8 15.9 13.5 10.2 13.1 11.5 9.0 10.1 10.8 10.7 9.8 9.5 Non-bank financial institutions 6.3 7.0 6.3 6.1 5.4 5.2 5.5 6.1 6.5 7.1 7.5 7.4

Japanese benchmark: S&P Topix 150 Consumer discretionary 5.0 5.2 5.0 5.8 6.9 5.9 6.0 6.9 7.7 7.3 8.7 9.4 Consumer staples 21.1 18.7 20.4 23.0 22.4 22.8 22.1 23.0 22.6 23.1 24.1 23.6 Energy 0.8 0.5 0.5 0.5 1.6 0.9 2.0 1.7 1.2 1.0 0.8 0.7 Healthcare 3.7 3.3 3.7 3.9 4.2 4.1 4.5 5.2 5.4 5.1 5.7 6.9 Industrials 14.0 13.7 14.5 16.4 15.4 17.8 19.4 18.7 16.4 17.5 17.6 16.9 Information technology 8.3 6.8 5.6 5.7 7.0 6.7 5.7 5.3 4.4 4.8 4.3 4.3 Materials 5.5 6.1 7.1 6.9 6.2 6.6 6.3 5.2 4.7 4.4 4.9 4.1 Telecommunication services 6.8 4.6 5.3 5.2 6.8 5.9 7.0 6.3 6.0 7.2 6.2 9.9 Utilities 4.2 3.0 4.0 4.0 5.5 4.3 3.0 2.3 1.8 1.7 1.6 1.4 Financials 15.4 19.1 16.9 14.3 12.0 12.5 12.0 12.7 14.9 13.9 13.0 11.4 Banks 7.2 10.4 8.4 7.2 6.4 6.6 6.1 6.8 8.0 7.3 6.6 5.5 Non-bank financial institutions 8.2 8.7 8.5 7.0 5.7 5.9 5.9 5.8 6.9 6.6 6.4 5.9

Australian benchmark: S&P ASX 200 Consumer discretionary 7.3 7.0 6.8 7.1 6.2 6.7 7.2 6.6 7.7 7.8 7.3 7.2 Consumer staples 2.3 1.9 1.9 2.0 1.6 1.5 1.0 1.1 1.0 0.8 0.9 1.2 Energy 3.5 3.0 3.7 4.0 4.5 4.3 3.9 4.2 3.9 3.6 3.0 2.9 Healthcare 1.6 1.4 1.5 2.1 2.0 1.9 2.2 2.3 2.7 2.8 4.0 4.6 Industrials 6.3 6.8 5.7 5.6 3.9 4.6 5.8 5.7 5.8 6.4 6.7 7.0 Information technology 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.4 0.4 Materials 18.1 20.6 23.7 28.7 26.8 28.3 28.6 22.6 17.5 16.5 12.8 12.9 Telecommunication services 5.2 3.1 3.2 3.8 2.8 2.6 2.4 3.1 3.3 3.5 4.1 4.0 Utilities 0.6 1.1 1.3 2.0 1.6 1.6 1.9 1.8 1.6 1.6 1.6 1.7 Financials 27.5 27.5 26.1 22.4 25.3 24.3 23.4 26.3 28.1 28.4 29.6 29.0 Banks 14.4 13.6 13.1 11.7 15.9 15.1 14.8 17.3 19.1 18.3 18.0 17.1 Non-bank financial institutions 13.1 13.8 12.9 10.6 9.3 9.1 8.6 9.0 9.0 10.1 11.7 11.9

Canadian benchmark: S&P TSX 60 Consumer discretionary 6.8 6.1 6.4 7.3 5.7 6.4 6.6 6.2 6.9 7.1 8.0 7.4 Consumer staples 9.0 9.3 10.5 0.6 10.5 12.3 13.6 14.6 14.5 14.5 15.9 15.3 Energy 9.8 8.9 10.3 21.2 10.8 10.4 11.5 9.9 8.5 7.2 5.9 7.5 Healthcare 6.6 5.6 5.1 0.3 6.4 6.1 7.7 7.6 7.8 8.5 9.4 8.5 Industrials 6.2 6.6 6.9 3.6 7.1 7.9 7.6 8.3 8.5 7.8 8.2 8.6 Information technology 2.7 2.2 2.5 4.9 2.0 2.2 2.2 2.0 2.1 2.1 2.4 2.5 Materials 4.6 5.6 6.4 12.4 7.6 9.4 9.5 8.8 6.9 6.7 5.5 6.3 Telecommunication services 6.7 5.3 5.8 4.7 5.4 5.1 5.4 4.5 4.5 4.3 4.6 4.1 Utilities 4.5 6.0 7.0 0.8 6.5 5.2 4.9 3.9 3.9 4.0 3.6 3.7 Financials 21.6 22.2 19.6 22.1 19.0 17.5 15.5 17.2 18.2 18.9 18.2 18.1 Banks 16.8 16.9 14.6 17.0 14.8 13.3 11.1 12.3 12.9 13.0 12.0 11.8 Non-bank financial institutions 4.8 5.3 5.0 5.1 4.2 4.2 4.4 4.9 5.3 5.9 6.2 6.3

Notes: All data are expressed in per cent. Each figure corresponds to the ratio of total market capitalisation of a given economic sector to the total market capitalisation of the benchmark.

Source: Thomson Reuters, OECD calculations.

16

Figure 5A. Market shares, cash, ROE minus cost of capital, leverage and profit margin for top 10% superstar companies versus the other 90%, 2002–2016


Table 5A. Net sales, EBITDA, total assets and market capitalisation for top 10% superstar companies versus other 90%, 2005–2016

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Net Sales

Top 10% 17,232 16,952 20,109 22,629 19,729 22,770 25,847 25,988 27,000 25,815 23,126 22,937 Other 90% 5,050 8,119 9,242 10,281 10,226 11,999 13,453 14,036 13,735 13,528 13,361 13,297

EBITDA

Top 10% 2,921 3,145 3,712 3,907 3,310 4,139 4,589 4,396 4,502 4,204 3,693 3,837 Other 90% 773 1,114 1,273 1,204 1,198 1,607 1,698 1,573 1,565 1,577 1,353 1,567

Total assets

Top 10% 20,849 22,275 26,940 26,570 28,542 31,673 33,413 34,837 35,916 34,986 33,418 35,444 Other 90% 5,716 9,130 11,003 10,835 13,075 14,878 15,726 16,986 16,905 17,234 17,983 18,214

Market capitalisation

Top 10% 19,808 54,435 29,815 16,729 22,722 25,492 23,632 26,111 30,565 31,179 29,269 31,009 Other 90% 35,412 28,420 11,165 6,103 10,324 13,081 11,233 12,768 14,014 15,270 16,480 16,026


6577 75 78

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Superstar companies

Superstar companies – the top 10% companies which are generating the highest amounts of value added in current US dollars – are enjoying huge market shares, wealth being concentrated among the winners. Superstars are more leveraged but exhibit higher profit margins than the other 90% of companies. They excel in running their business efficiently, their ROE minus COK being much higher than the other 90% of companies. These successful companies are pulling ahead of their rivals by building up enormous piles of cash that could provide a powerful defence against competition. Superstar companies are innovative in investing and developing R&D activities. They are internationalised with a decreasing number of employees (following the reversal of the commodity supercycle and high-tech companies – most of them located in Silicon Valley – substituting artificial intelligence for human intelligence). The quest for performance is producing a global bull market in M&A which is reflected in the large amounts of intangible assets hold by such successful companies.

17

Figure 5B. Key corporate finance data for top 10% superstar companies versus other 90% and tax profit optimisation, 2002–2016

Note:Years 2008 and 2009 are excluded (based on the NBER’s classification of the Great Recession, which began in December 2007 and ended in June 2009) to not contaminate average calculations with cyclical downturns.

Source: Bloomberg, International Monetary Fund, World Bank, OECD calculations. See Annex for details.

Table 5B. Key corporate finance data for top 10% superstar companies versus other 90%, 2005–2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Intangible assets (% of total assets)

Top 10% 15.62 17.23 17.38 19.54 18.52 19.22 19.05 18.80 18.94 19.77 20.28 20.73Other 90% 13.22 10.34 10.83 12.01 11.43 10.89 11.52 11.63 12.17 12.71 13.21 13.09

Capital expenditure (% of net sales)

Top 10% 6.89 7.74 7.98 8.25 7.75 7.44 7.84 8.33 8.13 8.15 8.03 7.82 Other 90% 6.90 6.53 7.08 7.18 6.65 6.38 6.45 6.43 6.57 6.32 6.74 6.23

R&D expenditure (% of net sales)

Top 10% 3.25 3.36 3.29 3.09 3.52 3.22 3.17 3.24 3.01 3.20 3.74 3.95 Other 90% 2.37 2.27 2.30 2.56 2.59 2.35 2.28 2.49 2.21 2.28 2.39 2.51

International sales (% of net sales)

Top 10% 48.34 46.56 48.87 52.02 51.53 53.38 53.57 54.61 52.64 57.61 56.47 54.18 Other 90% 46.84 38.37 39.70 44.08 44.64 43.17 44.89 46.47 45.91 50.21 49.74 48.00

ROE minus COK (%) Top 10% 10.98 12.14 12.49 9.94 8.43 11.24 11.65 10.54 10.55 11.19 9.00 9.02 Other 90% 9.03 9.04 8.73 3.15 3.89 7.22 6.58 5.33 4.89 5.50 1.90 4.29

Leverage (%) Top 10% 35.25 35.22 37.03 39.19 38.78 36.57 36.76 37.40 37.54 39.60 41.23 42.28 Other 90% 33.87 33.81 33.56 36.20 35.38 33.52 35.02 35.73 36.57 36.41 36.73 35.74

Profit margin (%) Top 10% 11.11 12.17 12.12 10.85 9.60 11.26 10.87 9.87 10.33 10.07 9.62 9.84 Other 90% 9.78 8.92 8.98 6.47 6.39 8.42 7.29 5.86 6.43 6.78 6.38 6.87

M&A deal value (% of World GDP)

Top 10% 9.66 9.20 9.58 8.63 9.71 10.28 9.29 9.22 8.04 9.08 8.74 8.57 Other 90% 2.37 2.27 2.30 2.56 2.59 2.35 2.28 2.49 2.21 2.28 2.39 2.51

Cash (% of World GDP)

Top 10% 3.11 2.73 2.94 2.92 3.72 3.75 3.39 3.41 3.22 3.06 3.14 3.29 Other 90% 1.02 1.59 1.64 1.57 2.19 2.42 2.26 2.37 2.03 1.99 2.25 2.37

Notes: In table 5A; all data are expressed in current US dollar billion. In table 5B; all data are expressed in per cent. Companies are separated in two groups: top 10% companies which are generating the highest amounts of value added in current US dollar and the other 90% of companies.

Source: Bloomberg, Thomson Reuters Datastream, International Monetary Fund, World Bank, OECD calculations. See Annex for details.

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Other tax havensCaribbean tax havensForeign assets of top 10% non-financial companies (RHS)

Foreign assets (% of World GDP)

15.1 11.7 3.4 2.6 7.1 6.7

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18

Figure 6. Return on equity minus the cost of capital, leverage and profit margin for private non-financial companies versus SOEs in advanced and emerging economies, 2002–2016

Note: State-owned companies are defined as 20% or higher state ownership. Source: Bloomberg, Factset, OECD calculations.

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The rise of SOEs: fairness in doing business globally and excess capacities

The return on equity (ROE) is higher on average for both state-owned enterprises (SOEs) and private firms in advanced economies. Within emerging markets, returns minus the cost of capital (COK) are lower overall than in advanced economies due to lower margins and a higher average COK and SOEs normally perform worse than private companies. Chinese companies are a large part of this sample, and their response to the crisis, by increasing investment and production, appears to have exacerbated excess capacity pressures on price margins. In advanced economies, profit margins have moved down since 2005 and debt levels have been reasonably stable. The impression that emerging economies are contributing to excess capacity is consistent with fairly continuous falling profit margins since the beginning of the 2000s. In contrast, leverage has increased for emerging SOEs after 2008. This reflects a strong credit expansion and state-directed capital expenditure in some emerging economies to mitigate the effects of the financial crisis

19

Table 6. Return on equity minus the cost of capital, leverage and profit margin for private non-financial companies versus SOEs in advanced and emerging economies, 2005–2016

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Advanced economies

ROE minus COK SOEs 10.52 9.87 10.29 7.83 4.75 7.13 8.17 7.63 5.28 5.12 2.32 3.60 Non-SOEs 9.35 9.54 9.49 5.08 4.52 7.95 7.59 6.27 6.86 8.25 4.86 5.80

Leverage SOEs 37.38 38.12 47.95 38.56 41.21 39.01 38.59 40.02 39.98 41.83 41.51 45.45 Non-SOEs 36.02 36.04 36.85 40.13 39.02 36.64 37.29 37.77 37.88 38.88 40.23 40.92

Profit margin SOEs 14.89 14.38 14.41 13.01 11.89 12.53 12.37 10.24 8.85 8.18 8.79 9.33 Non-SOEs 10.07 10.36 10.38 8.71 7.69 9.67 8.99 8.04 8.96 9.05 8.51 8.78

Emerging markets

ROE minus COK SOEs 3.59 5.77 3.96 4.16 2.00 4.54 5.41 2.95 1.42 0.68 -0.64 -0.87 Non-SOEs 5.13 6.27 7.09 3.74 3.20 4.08 4.12 2.64 1.56 1.48 0.92 1.64

Leverage SOEs 24.45 22.91 23.88 25.44 27.31 28.20 29.04 29.60 32.70 36.73 37.32 36.88 Non-SOEs 27.79 27.74 28.26 31.39 32.79 31.72 32.76 34.27 35.02 36.67 37.20 35.50

Profit margin SOEs 14.79 14.52 13.74 12.54 10.86 11.30 11.32 9.73 8.49 7.82 7.30 7.44 Non-SOEs 15.52 15.69 15.23 12.64 12.29 13.05 11.85 9.75 9.56 8.97 8.31 8.95

Notes: All data are expressed in per cent. State owned companies are defined as 20% or higher state ownership. ROE (return on equity): ratio of net income to common equity. COK (cost of capital): weighted average (by the share of equity and debt in total assets, respectively) sum of cost of equity and cost of debt. COE is the sum of dividend and buyback yield and underlying trend in EPS growth. Leverage: ratio of long-term debt to the sum of long-term debt plus equity. Profit margin: ratio of operating income to total revenues. Source: Bloomberg, Factset, OECD calculations.

20

Figure 7. Outstanding stock of investment grade and non-investment grade corporate bonds, 2005–2016

Outstanding stock Share of emerging markets

Table 7. Outstanding stock of corporate bonds, 2005–2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

World 11.4 12.8 14.2 14.7 15.6 16.5 17.3 18.6 19.8 21.3 22.6 23.9 Non-financial 4.8 5.1 5.5 5.8 6.8 7.5 8.0 9.0 9.8 10.7 11.5 12.4 Financial 6.6 7.7 8.7 8.9 8.8 9.0 9.3 9.7 10.0 10.6 11.0 11.5 Investment grade 10.3 11.6 12.9 13.5 14.2 14.9 15.6 16.6 17.5 18.8 19.8 21.0 Non-investment grade 1.1 1.2 1.3 1.2 1.3 1.6 1.7 2.0 2.3 2.6 2.7 2.9 Advanced economies 10.8 12.1 13.3 13.7 14.3 14.8 15.3 16.2 16.9 17.8 18.6 19.3 Non-financial 4.5 4.8 5.1 5.3 6.0 6.5 6.9 7.7 8.3 8.8 9.4 9.9 Financial 6.3 7.3 8.3 8.4 8.2 8.3 8.4 8.6 8.7 9.0 9.2 9.4 Investment grade 9.9 11.0 12.2 12.7 13.1 13.5 13.8 14.5 14.9 15.6 16.3 16.9 Non-investment grade 1.0 1.1 1.1 1.1 1.2 1.4 1.5 1.7 2.0 2.2 2.3 2.5 Emerging markets 0.5 0.7 0.9 1.0 1.3 1.6 2.0 2.4 2.9 3.5 3.9 4.6 Non-financial 0.3 0.3 0.4 0.5 0.7 0.9 1.1 1.3 1.6 1.9 2.1 2.4 Financial 0.2 0.4 0.5 0.5 0.6 0.7 0.9 1.1 1.3 1.6 1.8 2.1 Investment grade 0.4 0.6 0.7 0.8 1.1 1.4 1.8 2.1 2.5 3.1 3.6 4.2 Non-investment grade 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.4 0.4 0.4 United States 4.5 4.9 5.4 5.4 5.5 5.6 5.7 6.0 6.4 6.9 7.5 8.0 Non-financial 2.6 2.7 2.9 2.9 3.1 3.4 3.6 3.9 4.2 4.6 5.1 5.5 Financial 1.9 2.2 2.5 2.5 2.3 2.2 2.1 2.1 2.2 2.3 2.4 2.5 Investment grade 3.7 4.0 4.5 4.6 4.6 4.6 4.6 4.7 5.0 5.4 5.9 6.4 Non-investment grade 0.8 0.9 0.9 0.8 0.9 1.0 1.1 1.3 1.4 1.5 1.5 1.6 European Union 4.6 5.3 5.8 6.0 6.3 6.4 6.6 6.8 6.9 7.0 7.0 7.0 Non-financial 1.1 1.2 1.3 1.4 1.8 1.9 2.0 2.3 2.4 2.5 2.6 2.7 Financial 3.5 4.1 4.5 4.6 4.5 4.5 4.6 4.6 4.5 4.5 4.4 4.3 Investment grade 4.5 5.1 5.7 5.9 6.1 6.2 6.3 6.5 6.5 6.5 6.4 6.3 Non-investment grade 0.1 0.1 0.1 0.1 0.2 0.2 0.3 0.3 0.4 0.6 0.6 0.7 OECD 10.8 12.1 13.3 13.7 14.2 14.8 15.3 16.2 16.9 17.8 18.6 19.2 Non-financial 4.5 4.8 5.1 5.3 6.1 6.6 7.0 7.7 8.3 8.9 9.5 10.0 Financial 6.3 7.3 8.2 8.4 8.2 8.2 8.3 8.5 8.6 8.9 9.1 9.2 Investment grade 9.8 11.0 12.1 12.6 13.1 13.5 13.8 14.5 14.9 15.6 16.2 16.8 Non-investment grade 1.0 1.1 1.1 1.1 1.1 1.4 1.5 1.7 2.0 2.2 2.4 2.5

Note: All data are expressed in current US dollar trillion.

Source: Thomson Reuters, Bloomberg, OECD calculations. See Annex for details.

Corporate bond market continues to grow

The gobal value of outstanding corporate bonds continued to increase during 2016, reaching USD 23.9 trillion. This means that the global value of outstanding corporate bonds has doubled since 2005. Since 2008, the main driver has been growth in non-financial company issuance in advanced economies. During the same period, the stock of corporate bonds in emerging markets has more than tripled for both financial and non-financial companies. The growing share of corporate bonds from emerging markets is mainly explained by a rapid increase in investment grade bonds.

21

Figure 8. Global trends in average maturities for corporate bonds, 2005–2016

Table 8. Average maturities for corporate bonds, 2005–2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

World 6.5 6.8 6.8 6.2 6.5 6.8 6.7 7.2 7.3 6.3 6.3 6.5 Non-financial 9.1 9.5 9.7 7.8 7.5 7.9 7.9 8.8 8.0 7.1 7.4 7.0 Financial 5.5 5.8 5.7 5.3 5.5 6.1 5.9 5.9 6.6 5.6 5.5 6.0 Investment grade 6.4 6.7 6.7 6.1 6.4 6.7 6.6 7.2 7.3 6.3 6.3 6.5 Non-investment grade 8.3 8.4 8.7 7.4 7.3 7.8 7.5 7.6 7.6 7.4 7.7 7.4 Advanced economies 6.6 6.9 7.0 6.1 6.5 6.9 7.0 7.7 8.1 7.3 7.7 8.1 Non-financial 9.2 9.7 10.1 8.0 7.9 8.4 8.4 9.3 9.1 8.7 9.8 9.6 Financial 5.6 5.8 5.9 5.1 5.2 6.0 6.1 6.3 7.1 6.0 6.3 6.8 Investment grade 6.5 6.8 6.9 6.1 6.4 6.8 7.0 7.8 8.2 7.2 7.7 8.1 Non-investment grade 8.6 9.0 9.2 7.7 7.3 7.9 7.6 7.6 7.7 7.5 7.8 7.8 Emerging markets 5.8 6.2 5.9 6.5 6.4 6.5 5.4 5.7 5.3 4.4 3.9 4.1 Non-financial 8.6 8.1 8.2 6.7 6.1 6.1 6.0 6.9 5.4 4.2 3.9 3.9 Financial 4.6 5.5 4.9 6.3 6.7 6.8 5.1 5.1 5.1 4.7 3.9 4.3 Investment grade 5.7 6.2 5.8 6.5 6.3 6.4 5.4 5.6 5.2 4.3 3.8 4.1 Non-investment grade 7.0 6.3 7.1 6.1 7.6 7.1 7.0 7.6 6.9 6.6 7.0 5.9 United States 8.3 8.4 9.5 8.8 9.3 9.6 10.2 10.8 10.8 10.5 11.1 11.8 Non-financial 11.3 11.7 12.4 10.9 9.9 10.8 11.5 11.8 11.8 12.0 12.4 13.1 Financial 6.2 6.5 7.7 6.5 7.7 7.9 8.3 8.3 9.0 7.8 8.7 9.5 Investment grade 8.2 8.3 9.5 8.9 9.9 10.3 11.0 12.0 11.9 11.5 11.8 12.5 Non-investment grade 8.7 9.4 9.7 8.1 7.4 8.0 7.7 8.0 8.0 7.6 8.0 8.3 European Union 6.0 6.5 6.2 5.8 6.0 6.6 6.4 6.6 7.0 6.7 7.4 7.9 Non-financial 8.2 10.2 10.7 8.0 8.0 8.5 7.7 8.6 7.9 8.0 8.6 8.6 Financial 5.7 5.7 5.5 5.3 4.9 6.1 6.0 5.7 6.6 6.2 6.8 7.6 Investment grade 6.0 6.4 6.2 5.8 6.0 6.5 6.3 6.6 6.9 6.7 7.3 8.0 Non-investment grade 7.7 8.0 7.5 5.5 6.7 6.9 6.8 6.5 7.6 7.5 7.9 6.9 OECD 6.8 7.1 7.2 6.3 6.6 6.9 7.2 7.9 8.3 7.4 7.8 8.1 Non-financial 9.6 10.3 10.4 8.6 8.1 8.8 8.8 9.7 9.5 9.1 9.9 9.9 Financial 5.6 5.9 6.0 5.2 5.2 5.9 6.2 6.3 7.1 6.0 6.3 6.8 Investment grade 6.6 7.0 7.1 6.3 6.5 6.8 7.1 7.9 8.3 7.3 7.8 8.2 Non-investment grade 8.7 9.0 9.4 7.7 7.3 7.9 7.6 7.7 7.8 7.6 7.9 7.9

Note: Average maturities are expressed in number of years and represent simple averages.

Source: Thomson Reuters, OECD calculations. See Annex for details.

Longer maturities for large issuances

Since 2005, simple average maturities have shown little change in the length of corporate bond maturities. However, when maturities are weighted by the value of bond issues, the average length of maturities has increased by about one year in the last decade. Since the financial crisis, the gap between simple and weighted maturities has been widening, indicating the increasing importance of larger bond issues.

22

Figure 9. Slowdown in non-financial company initial public offerings (IPOs), 2014–2016

Table 9. Initial public offerings, 2005–2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

World 186 282 330 105 121 294 156 104 140 228 174 120 Non-financial 151 210 255 74 100 207 140 94 113 187 131 90 Financial 35 72 75 31 21 87 16 10 26 41 44 30 Advanced economies 122 151 148 46 38 132 73 60 93 143 116 65 Non-financial 107 128 129 22 31 83 65 55 81 114 90 57 Financial 15 24 20 24 6 49 9 4 12 29 26 8 Emerging markets 64 131 181 59 83 162 83 44 47 85 58 55 Non-financial 44 82 126 52 69 124 76 39 33 73 41 33 Financial 19 49 55 8 15 39 7 6 14 12 18 22 United States 38 39 35 29 17 37 28 35 47 47 25 12 Non-financial 32 32 33 7 15 33 26 33 43 31 20 11 Financial 6 6 2 22 2 4 2 2 4 16 4 1 European Union 54 70 81 11 7 26 20 9 25 55 58 30 Non-financial 49 58 71 10 5 23 14 6 20 43 44 24 Financial 5 12 10 1 2 4 6 3 5 12 14 6 OECD 124 147 144 50 33 109 70 61 94 141 114 60 Non-financial 107 123 121 25 28 80 62 56 83 111 88 52 Financial 16 24 23 24 6 29 8 5 11 29 26 8

Note: All data are expressed in 2016 US dollar billion.


Continued slowdown in non-financial company IPOs

The volume of initial public offerings (IPOs) in both advanced and emerging markets has decreased from the strong level of growth in 2014. In most markets, 2016 also saw a decline from the 2015 IPO level. In the United States, the value of IPOs in 2016 was back to 2008-2009 levels amidst increased global policy uncertainty.

23

Figure 10. Growth company IPOs in the United States, Europe and Japan, 1994–2016

Table 10. Growth non-financial company IPOs, 2005-2016

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 World Issues with size < USD 50 M 12,561 14,028 14,865 5,679 3,609 7,111 7,501 5,269 5,481 8,437 10,436 10,740 Issues with size < USD 100 M 21,205 24,677 29,402 10,466 9,770 24,677 20,582 15,373 12,802 22,768 25,323 20,970 Advanced economies Issues with size < USD 50 M 9,560 9,549 8,469 2,307 1,989 3,960 4,199 2,459 3,904 5,001 5,588 4,870 Issues with size < USD 100 M 16,352 16,871 17,878 3,682 3,337 8,426 7,514 6,109 9,036 12,676 11,410 8,734 Emerging markets Issues with size < USD 50 M 3,001 4,479 6,396 3,372 1,620 3,151 3,302 2,811 1,577 3,436 4,818 5,870 Issues with size < USD 100 M 4,853 7,806 11,524 6,784 6,433 16,251 13,068 9,265 3,766 10,093 13,884 12,236 United States Issues with size < USD 50 M 882 1,027 638 95 7 212 328 205 520 624 516 380 Issues with size < USD 100 M 3,307 3,427 3,844 373 558 2,687 1,511 2,528 3,365 4,895 2,964 1,815 European Union Issues with size < USD 50 M 2,581 3,550 3,074 564 153 1,144 981 740 855 1,267 1,420 1,325 Issues with size < USD 100 M 4,567 5,806 6,404 897 358 1,795 1,834 1,268 1,565 3,106 2,929 2,046 OECD Issues with size < USD 50 M 8,712 9,463 8,540 2,031 1,564 3,626 3,809 2,201 3,336 4,357 4,747 3,877 Issues with size < USD 100 M 14,989 16,320 17,114 3,067 2,701 8,109 7,072 5,867 7,984 12,127 9,978 7,337

Note: All data are expressed in 2016 US dollar million.


Public equity financing for growth companies remains weak

The OECD Business and Finance Outlook 2016 demonstrated that equity capital is of particular importance for innovative investment and productivity growth. It was shown that rising debt-to-equity ratios after the financial crisis were associated with weaker productivity growth. However, the longer term decline in growth company IPOs in the United States, Europe and Japan continued in 2016, both in terms of the value of equity capital raised and the number of companies using public equity markets.

24

Figure 11. Secondary public offerings, 2015 and 2016

Table 11. Secondary public offerings, 2005–2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

World 428 468 604 650 959 741 507 518 577 608 701 550 Non-financial 311 331 448 294 483 469 317 323 439 469 524 483 Financial 117 137 156 356 476 273 189 195 138 139 177 66 Advanced economies 358 388 422 522 801 426 323 347 409 423 466 314 Non-financial 266 280 335 201 387 249 213 223 319 318 352 280 Financial 92 108 87 322 415 178 111 125 91 106 114 34 Emerging markets 70 80 182 128 158 315 183 170 167 185 234 236 Non-financial 45 50 112 93 97 220 105 100 120 152 172 204 Financial 25 30 69 35 61 95 79 70 47 33 63 32 United States 88 95 90 167 223 151 90 136 133 118 147 118 Non-financial 70 81 80 58 75 57 61 72 125 105 127 111 Financial 18 15 10 110 148 94 29 64 8 13 20 7 European Union 150 144 165 225 326 128 126 100 166 179 145 90 Non-financial 105 79 115 69 143 76 63 65 93 108 98 68 Financial 45 65 49 156 183 53 63 35 73 70 47 22 OECD 341 365 377 512 771 407 314 321 410 395 413 303 Non-financial 252 257 292 190 359 229 204 210 314 294 314 267 Financial 89 109 85 322 412 178 111 111 96 101 99 36

Note: All data are expressed in 2016 US dollar billion.


Financial companies’ use of secondary public equity markets has fallen dramatically

Following the sharp drop in bank lending after the 2008 financial crisis companies that were already listed raised a record amount of equity capital through secondary public offerings in 2008 and 2009. The market for secondary public equity offerings remained strong in 2016. Compared to 2008-2009, however, when financial companies raised most of the money, almost 90% of all equity raised in 2016 went to non-financial companies. In 2016, total proceeds of issues by financial companies from advanced economies was, in real terms, at the lowest level since 2000.

25

Figure 12. Distribution of non-financial corporate bond issuance among sectors, 2014–2016

Table 12A. Distribution of advanced economy companies’ corporate bond issuance among sectors, 2005–2016

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Consumer Products and Services

Volume 29 54 34 31 55 53 52 83 66 76 79 73 Share 1% 2% 1% 1% 2% 2% 2% 3% 2% 2% 3% 2%

Consumer Staples Volume 36 43 68 91 104 80 75 114 108 78 116 126 Share 1% 1% 2% 3% 4% 3% 3% 4% 4% 3% 4% 4%

Energy and Power Volume 132 176 237 259 410 279 257 351 330 343 315 298 Share 5% 5% 7% 10% 15% 10% 10% 12% 12% 11% 10% 10%

Financials Volume 2,083 2,555 2,428 1,831 1,366 1,615 1,493 1,534 1,412 1,706 1,563 1,580 Share 78% 75% 73% 70% 50% 60% 58% 52% 50% 55% 52% 53%

Healthcare Volume 31 42 77 36 125 75 84 105 85 144 188 169 Share 1% 1% 2% 1% 5% 3% 3% 4% 3% 5% 6% 6%

High Technology Volume 28 54 45 52 65 67 78 70 104 100 149 139 Share 1% 2% 1% 2% 2% 2% 3% 2% 4% 3% 5% 5%

Industrials Volume 108 129 121 86 191 170 177 214 212 200 199 207 Share 4% 4% 4% 3% 7% 6% 7% 7% 7% 6% 7% 7%

Materials Volume 49 82 76 67 134 114 106 164 113 105 81 89 Share 2% 2% 2% 3% 5% 4% 4% 6% 4% 3% 3% 3%

Media and Entertainment Volume 45 74 44 34 83 83 65 101 78 91 81 74 Share 2% 2% 1% 1% 3% 3% 2% 3% 3% 3% 3% 2%

Real Estate Volume 40 48 41 12 26 43 41 65 77 85 75 77 Share 1% 1% 1% 0% 1% 2% 2% 2% 3% 3% 2% 3%

Retail Volume 33 40 65 40 53 56 54 66 73 73 69 58 Share 1% 1% 2% 2% 2% 2% 2% 2% 3% 2% 2% 2%

Telecommunications Volume 70 110 79 84 133 77 101 105 181 121 92 97 Share 3% 3% 2% 3% 5% 3% 4% 4% 6% 4% 3% 3%

Note: Volume data are expressed in 2016 US dollar billion. Source: Thomson Reuters, OECD calculations. See Annex for details.

The use of corporate bond markets in different sectors

Despite a significant decline in their dominance since 2009, financial sector companies are by far the largest single users of corporate bond markets, both in advanced and emerging markets. Among non-financial companies, the shares of energy, power and industrials sectors are significant, in particular for emerging markets. In advanced economies, corporate bonds are also used as a means of finance in the relatively large high-technology and healthcare sectors.

26

Table 12B. Distribution of emerging market companies’ corporate bond issuance among sectors, 2005–2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Consumer Products and Services Volume 17 8 5 10 4 6 11 4 7 14 17 22 Share 9% 3% 2% 4% 1% 1% 2% 1% 1% 1% 2% 2%



Financials Volume 111 189 193 102 194 235 255 335 272 483 404 501 Share 57% 64% 58% 46% 41% 47% 49% 53% 40% 48% 44% 43%









Note: Volume data are expressed in 2016 US dollar billion.


27

Figure 13. Changing industry composition of public equity market financing in emerging economies, 2011–2016

Table 13A. Distribution of public equity financing among different sectors by companies from advanced economies, 2005–2016


Volume 21 32 23 6 13 13 10 11 29 33 36 16 Share 4% 6% 4% 1% 2% 2% 2% 3% 6% 6% 6% 4%














Change in industry composition of public equity financing in emerging markets

The share of public equity in emerging markets raised by high-technology and healthcare firms more than doubled during 2014-2016, compared to the previous three year period. This means that the share of all public equity going to the high-technology and healthcare industries during this period was about the same in advanced and emerging markets, about 19% .

28

Table 13B. Distribution of public equity financing among different sectors by companies from emerging markets, 2005–2016


Volume 2 2 6 1 5 9 13 3 6 9 8 17 Share 1% 1% 2% 1% 2% 2% 5% 2% 3% 3% 3% 6%














29

Figure 14. Corporate bond rating index, 2001–2016

Table 14. Distribution of corporate bond issuance among rating categories, as a percentage of total, 2005–2016

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 A-grade investment 82.8% 81.5% 81.8% 87.6% 70.9% 64.6% 67.5% 58.0% 52.6% 55.6% 58.4% 57.3% B-grade investment 10.2% 10.8% 10.4% 9.6% 18.8% 17.9% 17.4% 24.7% 27.4% 25.5% 26.5% 28.9% B-grade non-investment 6.5% 7.1% 6.5% 2.6% 10.0% 16.2% 14.0% 15.9% 18.3% 17.5% 14.2% 13.3% C-grade non-investment 0.5% 0.6% 1.3% 0.1% 0.3% 1.2% 1.1% 1.4% 1.7% 1.4% 0.9% 0.5%

Notes: There are eleven non-investment grade categories: five from C, C to CCC+; and six from B, B- to BB+. There are ten investment grade categories: three from B, BBB- to BBB+; and seven from A, A- to AAA. The index is weighted as one for C, two for CC and rising to twenty one for AAA. A fall in the index indicates declining quality. Index is based on value weighted 6-month moving averages.

Source: Thomson Reuters, Bloomberg, OECD calculations. See Annex for details.

Deteriorating corporate bond rating quality

The overall corporate bond rating quality index declined more than one-notch during 2016, except for Japan. This means that for the United States, advanced European and emerging markets, the index remains well below the pre-2008 level. The corporate bond rating quality index, constructed by assigning the value 1 to the lowest credit quality rating and 21 to the highest credit quality rating, tracks rating quality trends since 2001. The decline in overall corporate bond rating quality in the United States and emerging markets started immediately after the global financial crisis, while the decline in Europe is associated with the eurozone crisis of 2011.

30

Figure 15. Foreign direct investment inflows by region, 2005-2016

Table 15A. FDI inflows by selected regions, 2005-2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p

World 991 1 458 2 020 1 580 1 180 1 489 1 709 1 530 1 579 1 438 1 868 1 774 European Union 458 526 828 317 378 358 425 336 336 241 478 582 United States 113 243 221 310 150 206 236 204 206 176 353 396 China 104 124 156 172 131 244 280 241 291 268 242 171 Other countries 316 564 815 781 521 681 768 748 747 752 794 625

Addenda items: OECD 621 956 1 319 846 674 717 875 727 776 614 1 032 1 092 G20 619 871 1 142 1 032 691 907 1 059 874 999 838 984 1 193 Advanced economies 647 1 000 1 383 866 705 815 939 826 830 730 1 231 1 110 Emerging markets 344 458 636 714 476 674 770 703 749 708 637 664

Table 15B. FDI outflows by selected regions, 2005-2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p

World 853 1 378 2 179 1 726 1 090 1 387 1 533 1 255 1 344 1 265 1 608 1 476 European Union 556 664 1 217 752 348 460 482 300 340 188 531 476 United States 36 245 414 329 310 301 419 339 324 312 322 318 China 14 24 17 57 44 58 48 65 73 123 174 217 Other countries 247 445 530 587 388 569 584 551 608 641 581 465

Addenda items: OECD 728 1 149 1 897 1 414 871 1 029 1 214 925 981 784 1 206 1 096 G20 403 805 1 397 1 190 780 856 1 037 819 849 778 831 898 Advanced economies 774 1 216 2 004 1 485 934 1 149 1 288 1 019 1 069 930 1 311 1 239 Emerging markets 79 162 174 241 156 239 246 236 275 335 297 238

Notes: All data are expressed in US dollar billion. p: preliminary data; Data are updated as of April 2017. Source: OECD Foreign Direct Investment statistics database and IMF Balance of Payments database. See Annex for details.

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

0

500

1 000

1 500

2 000

2 500

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p

EU United States China Other countries Global flows as a share of GDP

Global trends in foreign direct investment (FDI) flows

Global FDI inflows stagnated following the financial crisis but picked up in 2015. In 2016, FDI inflows fell 5%, equal to 2.4% of global GDP, but remained above the average level observed in 2009-2014. The slow growth between 2008 and 2014 was largely due to weak FDI flows to the EU and, to a lesser extent, to the United States; both these regions experienced an increase in inflows in 2015 and 2016. In contrast, FDI inflows to China, which increased following the financial crisis, dropped by 30% in 2016 to their lowest level since 2009.

31

Figure 16. FDI inflows by instrument, as a share of global GDP, 2005-2016

Notes: p: preliminary data; Data are updated as of April 2017. Source: OECD Foreign Direct Investment statistics database and IMF Balance of Payments and World Economic Outlook databases.

Table 16A. FDI inflows by instrument for selected regions, 2005-2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p

Equity capital World 566 764 1 117 1 060 695 788 805 702 677 658 1 206 1 162 European Union 330 341 545 378 254 265 204 190 105 168 364 488 OECD 385 529 812 706 453 454 411 363 340 300 755 806 G20 372 457 703 692 415 482 523 451 514 382 611 778 Advanced economies 383 541 816 689 450 461 397 388 329 344 877 906 Emerging markets 183 223 301 371 245 328 408 313 349 314 329 256

Reinvestment of earnings World 302 448 588 385 336 583 582 602 604 616 561 495 European Union 78 131 191 39 33 110 84 91 110 123 131 157 OECD 165 264 337 145 129 253 254 269 267 299 272 288 G20 180 250 295 219 164 340 345 323 343 355 300 246 Advanced economies 184 294 384 179 167 311 319 327 337 360 340 333 Emerging markets 118 154 203 206 168 272 263 275 267 256 220 162

Debt World 123 246 315 135 150 117 322 226 298 164 102 117 European Union 49 55 91 -100 91 -17 136 55 120 -50 -17 -63 OECD 71 163 170 -5 91 10 210 95 170 15 5 -3 G20 67 163 143 122 112 85 191 100 143 101 73 168 Advanced economies 80 165 183 -2 88 43 222 111 165 26 14 -17 Emerging markets 42 81 132 136 62 74 100 115 133 138 88 134

0.0%

1.0%

2.0%

3.0%

4.0%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p

Equity Reinvestment of earnings Debt

Inflow of equity capital showed continued strength in 2016

The increase in FDI during 2015 and 2016 was largely due to a reported increase in the inflow of equity. In 2015, the reported inflow of equity capital more than doubled from the previous year and, while falling slightly, continued to show strength in 2016. Intercompany debt increased slightly, while reinvested earnings declined by 12% in 2016.

32

Table 16B. FDI outflows by instrument for selected regions, 2005-2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p Equity capital World 479 746 1 131 959 561 658 704 654 560 451 769 715 European Union 316 446 645 471 277 269 309 231 122 76 417 409 OECD 420 636 994 818 439 479 541 440 337 195 649 590 G20 223 418 689 619 337 403 432 367 383 229 319 390 Advanced economies 429 642 1 030 822 457 492 544 447 342 250 667 588 Emerging markets 50 104 102 137 104 166 161 207 217 201 102 127

Reinvestment of earnings World 289 606 732 485 462 703 691 599 679 754 660 683 European Union 176 253 353 120 95 162 162 120 117 87 72 110 OECD 243 544 654 383 381 549 555 506 515 557 496 516 G20 170 439 525 413 354 508 555 493 507 541 471 502 Advanced economies 268 576 697 428 437 628 642 570 594 633 571 589 Emerging markets 21 30 35 56 25 75 49 29 84 121 89 94

Debt World 85 26 316 282 67 27 138 3 106 61 179 78 European Union 64 -35 220 161 -24 30 11 -52 101 25 41 -43 OECD 66 -32 250 212 51 1 117 -21 129 33 61 -10 G20 11 -52 184 158 89 -55 50 -41 -41 8 41 7 Advanced economies 77 -2 278 234 41 29 102 2 132 49 74 8 Emerging markets 8 27 37 48 26 -2 36 1 -27 12 105 69

Notes: All data are expressed in US dollar billion. p: preliminary data; For OECD countries who did not report FDI aggregates by instrument to the OECD, instruments were estimated using data on instruments available from the IMF BOP database; or by using instrument shares observed in non-revised data for historical years. Missing instruments for 2016 were estimated by using instrument shares observed in 2015. Instruments for non-OECD G20 countries and advanced economies were gathered from national source websites and from the IMF. Missing instruments for those countries were estimated by distributing total FDI equally among instruments or by applying the average instrument shares observed in previous periods. Instruments for the rest of the world were estimated by applying instrument shares observed on data available in the IMF BOP database for the rest of the world. 2016 data were estimated by applying the same instrument shares as observed in 2015. Data are updated as of April 2017. Source: OECD Foreign Direct Investment statistics database and IMF Balance of Payments database.

33

Figure 17. OECD Resident Special Purpose Entities (SPEs) investment, 2005-2016

As a share of total OECD inflows and outflows

Notes: OECD resident SPEs include SPEs from Austria, Denmark, Hungary, Luxembourg, Netherlands, Poland and Portugal. Information on resident SPEs for Estonia is confidential. The information is available separately for Belgium, Chile, Iceland, Korea, Norway, Spain, Sweden, Switzerland and the United Kingdom but was not included in this chart due to limited historical availability of information on SPEs. Source: OECD Foreign Direct Investment statistics database.

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p

SPEs inflows SPEs outflows

FDI flows in and from resident Special Purpose Entities (SPEs)

SPEs are entities whose function is to facilitate the internal financing of multinational enterprises but have little or no physical presence in an economy. Excluding such entities from FDI statistics provides a better measure of the real economic impact of FDI flows. FDI flows to and from SPEs are significant for certain countries and are much more volatile than FDI flows into non-SPE, or operating, affiliates. Flows to and from SPEs, which started to decline in 2014, turned negative during 2016, indicating disinvestments to and from SPEs resident in these economies last year.

34

Table 17A. FDI outflows for countries with SPEs, 2005-2016

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016P Data including SPEs Austria 78 074 11 228 66 753 28 532 12 355 -14 065 32 532 20 492 6 704 -2 586 12 504 -33 159 Belgium 32 640 50 713 80 141 17 256 1 048 -8 313 46 413 33 834 29 480 -2 700 30 361 18 263 Chile 2 183 2 171 2 573 8 041 6 212 10 534 13 617 17 041 8 127 12 573 12 139 6 165 Denmark 17 444 7 172 17 091 11 832 2 440 -1 407 9 598 -13 017 6 948 5 759 7 865 15 162 Estonia 662 1 017 1 684 1 140 1 375 167 -1 455 1 054 505 -159 323 479 Hungary 12 656 19 084 67 478 70 686 4 498 -41 146 21 436 12 358 -2 747 5 189 -30 578 -27 464 Iceland 460 -295 -29 -1 191 Korea 31 488 19 994 12 376 Luxembourg 124 541 114 537 266 000 135 227 227 058 205 556 374 294 369 305 360 341 189 962 618 931 49 625 Netherlands 248 511 461 992 205 473 364 080 385 931 210 620 388 351 257 720 468 440 87 576 134 508 126 419 Norway 6 213 32 939 Poland 2 864 7 660 3 490 3 437 3 657 6 148 3 677 -2 660 -1 346 4 598 1 928 6 953 Portugal 1 643 6 214 5 262 1 163 -367 -9 783 13 447 -8 208 -1 205 -517 5 686 1 582 Spain 12 821 36 326 44 497 41 776 Sweden 27 716 26 691 38 845 30 335 26 205 20 364 29 912 28 977 30 279 9 162 14 946 22 866 Switzerland 50 994 75 862 51 036 45 312 26 428 85 718 48 098 43 572 38 568 -1 058 104 016 40 111 United Kingdom c c -90 552 Data excluding SPEs Austria 11 139 12 317 36 077 28 851 11 038 9 548 22 004 13 060 15 598 -665 10 002 -1 757 Belgium 27 727 -2 212 34 724 21 731 Chile 6 487 10 226 12 470 17 252 8 382 13 918 12 188 6 198 Denmark 13 108 14 408 13 049 15 362 3 690 1 368 11 278 7 349 7 162 6 722 11 192 14 598 Estonia c c c c c c c c c c c c Hungary 2 171 4 346 4 300 2 638 1 852 1 173 4 713 11 717 1 887 3 780 -15 980 -8 823 Iceland 7 084 5 495 10 105 -4 250 2 248 -2 368 18 -3 205 460 -257 -31 -1 199 Korea 31 488 19 994 12 376 Luxembourg 9 034 7 183 73 363 11 737 6 709 20 842 9 052 2 771 20 226 7 633 50 458 31 633 Netherlands 105 999 72 534 55 691 68 345 26 267 68 363 34 818 6 174 69 692 63 606 138 042 173 585 Norway 6 734 32 025 Poland 1 347 3 857 1 682 1 858 1 807 6 149 1 028 2 905 -451 4 701 3 172 6 434 Portugal 2 634 4 435 5 457 722 814 -9 956 13 917 -8 095 -192 -88 4 934 1 401 Spain 11 060 33 297 41 326 Sweden c 9 338 c c Switzerland 91 490 United Kingdom c c c SPEs Austria 66 936 -1 089 30 676 -319 1 317 -23 613 10 529 7 432 -8 894 -1 921 2 501 -31 402 Belgium 1 752 -488 -4 364 -3 468 Chile -274 308 1 147 -212 -256 -1 345 -48 -33 Denmark 4 336 -7 235 4 042 -3 530 -1 250 -2 775 -1 680 -20 366 -214 -963 -3 326 565 Estonia c c c c c c c c c c c c Hungary 10 484 14 739 63 178 68 049 2 646 -42 319 16 723 641 -4 633 1 409 -14 598 -18 641 Iceland 0 -37 2 8 Korea 0 0 0 Luxembourg 115 507 107 354 192 637 123 490 220 349 184 714 365 241 366 533 340 115 182 329 568 473 17 992 Netherlands 142 512 389 458 149 782 295 735 359 664 142 257 353 533 251 546 398 748 23 970 -3 534 -47 166 Norway -521 914 Poland 1 516 3 803 1 808 1 579 1 850 -1 2 649 -5 565 -895 -103 -1 244 519 Portugal -991 1 779 -194 441 -1 181 174 -470 -113 -1 013 -430 752 181 Spain 1 760 3 029 3 170 Sweden c -176 c c Switzerland 12 526 United Kingdom 20 732 -160 711 c Notes: All data are expressed in USD millions. | : breaks in series c: Confidential data p: Preliminary data; Data are updated as of April 2017. Information on resident SPEs for Estonia is confidential. This information is not yet available separately for Canada, Ireland and Mexico. The information is available separately for Austria, Belgium (from 2013), Chile (from 2009), Denmark, Hungary, Iceland (from 2013), Korea (from 2013), Luxembourg, the Netherlands, Norway (from 2013), Poland, Portugal, Spain (from 2013), Sweden (from 2013), Switzerland (from 2013) and the United Kingdom (from 2013). Resident SPEs are not present or not significant in Australia, the Czech Republic, Finland, France, Germany, Greece, Israel, Italy, Japan, New Zealand, the Slovak Republic, Slovenia, Turkey, and the United States. Source: OECD Foreign Direct Investment statistics database.

35

Table 17B. FDI inflows for countries with SPEs, 2005-2016

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016P Data including SPEs Austria 77 903 5 557 56 753 7 143 11 139 -21 694 17 182 7 371 -3 765 32 5 597 -32 033 Belgium 34 351 58 926 93 448 -13 830 60 966 43 233 78 329 6 518 25 188 -8 917 21 281 33 094 Chile 6 984 7 298 12 534 15 150 12 946 17 227 17 739 27 046 19 331 23 784 15 866 11 266 Denmark 13 451 1 589 10 908 -4 198 -401 -12 559 9 590 -18 358 635 2 157 2 561 1 064 Estonia 2 798 1 335 2 312 1 826 1 840 1 509 1 006 1 566 750 604 130 870 Hungary 20 300 19 597 70 003 72 408 5 170 -37 264 23 628 15 050 -2 687 9 041 -27 915 -23 695 Iceland 412 439 670 -476 Korea 6 083 -917 3 076 Luxembourg 116 107 128 557 191 162 105 765 204 341 222 023 412 774 410 089 498 870 129 469 410 185 37 892 Netherlands 189 851 313 143 334 444 282 344 339 086 135 774 349 932 259 371 381 217 131 746 127 070 66 405 Norway -5 916 19 504 Poland 9 723 18 379 21 663 13 857 11 892 12 799 18 290 7 130 2 734 17 509 11 819 11 873 Portugal 3 462 10 600 2 876 3 542 1 611 2 424 7 435 8 860 2 701 2 977 6 935 6 062 Spain 37 429 25 656 11 911 18 653 Sweden 11 627 27 552 28 849 36 855 10 095 141 12 946 16 349 4 125 4 032 6 206 19 596 Switzerland -949 43 740 32 445 15 205 28 945 28 750 25 857 28 969 646 8 070 70 406 -17 392 United Kingdom 47 141 45 831 35 312 Data excluding SPEs Austria 10 778 4 888 25 492 7 254 9 397 2 728 10 820 4 003 5 813 4 803 3 647 -6 011 Belgium -16 430 -2 597 48 282 41 999 Chile 12 625 15 864 17 880 27 029 19 391 23 855 15 765 11 170 Denmark 8 614 9 161 7 233 -668 1 428 -9 179 11 457 644 1 045 3 197 4 094 974 Estonia c c c c c c c c c c c c Hungary 7 711 6 817 3 952 6 314 1 998 2 195 6 315 14 427 3 404 7 752 -14 811 -5 314 Iceland 3 076 3 858 6 822 919 79 245 1 107 1 025 397 447 709 -484 Korea 6 053 3 382 2 805 Luxembourg 5 976 31 802 -28 266 11 194 20 667 35 661 13 302 4 423 10 479 -10 535 16 003 26 849 Netherlands 39 077 13 901 119 733 5 751 38 748 -7 185 24 391 20 121 51 094 53 310 68 765 91 911 Norway -5 366 20 184 Poland 8 207 14 576 19 855 12 279 10 043 12 800 15 953 12 441 3 626 17 612 13 063 11 354 Portugal 4 360 7 227 3 086 2 099 1 282 1 507 5 997 8 951 2 443 3 034 8 864 6 029 Spain 28 398 24 050 9 947 Sweden c 5 419 4 797 c Switzerland 55 684 United Kingdom c 36 729 c SPEs Austria 67 126 669 31 261 -111 1 742 -24 423 6 363 3 369 -9 578 -4 771 1 950 -26 021 Belgium 41 618 -6 321 -27 001 -8 905 Chile 320 1 363 -141 17 -61 -71 101 95 Denmark 4 836 -7 572 3 675 -3 530 -1 829 -3 380 -1 867 -19 002 -409 -1 040 -1 533 90 Estonia c c c c c c c c c c c c Hungary 12 589 12 780 66 052 66 093 3 172 -39 458 17 313 623 -6 091 1 289 -13 104 -18 381 Iceland 15 -8 -38 8 Korea 30 -4 299 271 Luxembourg 110 132 96 754 219 428 94 570 183 675 186 362 399 473 405 666 488 391 140 004 394 182 11 043 Netherlands 150 774 299 242 214 710 276 592 300 338 142 959 325 541 239 251 330 123 78 436 58 305 -25 506 Norway -550 -681 Poland 1 516 3 803 1 808 1 579 1 850 -1 2 337 -5 311 -892 -103 -1 244 519 Portugal -898 3 372 -210 1 443 329 917 1 438 -91 259 -57 -1 929 33 Spain 9 031 1 607 1 963 Sweden c -1 387 1 409 c Switzerland 14 722 United Kingdom c 9 103 c Notes: All data are expressed in USD millions. | : breaks in series c: Confidential data p: Preliminary data; Data are updated as of April 2017. Information on resident SPEs for Estonia is confidential. This information is not yet available separately for Canada, Ireland and Mexico. The information is available separately for Austria, Belgium (from 2013), Chile (from 2009), Denmark, Hungary, Iceland (from 2013), Korea (from 2013), Luxembourg, the Netherlands, Norway (from 2013), Poland, Portugal, Spain (from 2013), Sweden (from 2013), Switzerland (from 2013) and the United Kingdom (from 2013). Resident SPEs are not present or not significant in Australia, the Czech Republic, Finland, France, Germany, Greece, Israel, Italy, Japan, New Zealand, the Slovak Republic, Slovenia, Turkey, and the United States. Source: OECD Foreign Direct Investment statistics database.

36

Figure 18. Inward FDI positions by major ultimate versus immediate investors, atend 2015

As a share of total positions for the reporting countries

Notes: For 11 OECD countries which report FDI by Ultimate investing country and FDI by Immediate partner country to the OECD: Austria, Czech Republic, Estonia, France, Hungary, Germany, Iceland, Italy, Poland, Switzerland and the United States. Finland reports inward FDI by ultimate investing country to the OECD but the data are excluded from the analysis because inward FDI by the immediate counterparty is not publishable. Data for Austria, Estonia, Hungary, Iceland and Poland exclude resident SPEs. Data for France, Germany and Hungary correspond to FDI positions at-end 2014. Source: OECD Foreign Direct Investment statistics database.

0%

2%

4%

6%

8%

10%

12%

14%

16%

UnitedKingdom

United States Germany Japan France Canada Netherlands Switzerland LuxembourgMajor investing country

Ultimate investing country Immediate investing country

Shifting view of the origin of FDI: FDI statistics by ultimate investing country

Standard FDI statistics are presented according to the immediate investing country but when presented according to the ultimate investor, they indicate the direct investors’ country. The direct investor ultimately controls the investment and, thus, bears the risks and reaps the rewards of the investment. FDI statistics according to ultimate investor also reveal substantial differences in the distribution of inward positions by investing country.The United States, Germany, and the United Kingdom are generally found to be more important investors than standard FDI statistics indicate while Luxembourg, the Netherlands, and Switzerland are generally found to be much less important. This suggests that investors from the United States, Germany, and the United Kingdom - as well as other countries - hold their investments in other countries indirectly through Luxembourg, the Netherlands and Switzerland.

37

Table 18. Inward FDI positions by immediate (IMD) versus ultimate (ULT) investing country for selected OECD countries, at end 2015 or latest available year

Inward FDI positions from: Of which:

WO

RL

D

Uni

ted

Kin

gdom

Uni

ted

Stat

es

Ger

man

y

Japa

n

Fran

ce

Can

ada

Net

herl

ands

Switz

erla

nd

Lux

embo

urg

Austria* IMD 164 2 2 42 1 3 0 28 9 16 ULT 164 5 14 44 3 3 2 5 8 3

Czech Republic IMD 112 4 2 15 1 7 0 25 5 14 ULT 112 5 9 27 3 7 0 6 3 3

Estonia* IMD 19 0.4 0.4 0.3 0.0 0.2 0.1 0.0 0.3 0.6 ULT 19 0.4 0.7 0.6 0.1 0.3 0.1 0.5 0.2 0.4

France IMD 681 73 78 64 15 0 3 100 58 142 ULT 681 81 139 81 16 31 2 39 63 79

Germany IMD 850 86 67 0 24 64 1 183 69 169 ULT 850 116 188 67 37 58 7 56 65 63

Hungary* IMD 99 4 2 23 1 3 1 15 2 12 ULT 99 4 18 26 2 5 0 2 2 1

Iceland* IMD 8 0 -3 0 0 0 0 2 1 6 ULT 8 1 5 0 0 0 0 0 0 0

Italy IMD 337 39 8 24 3 59 0 68 18 70 ULT 337 30 31 24 7 52 1 16 20 28

Poland* IMD 183 10 5 30 1 20 0 33 5 21 ULT 183 11 20 35 4 20 2 6 4 2

Switzerland IMD 878 38 99 25 6 41 0 199 0 204 ULT 878 32 310 33 12 44 38 66 0 26

United States IMD 3 134 484 0 255 411 234 269 283 258 328 ULT 3 134 569 77 319 414 251 342 137 144 15 Notes: All data are expressed in US dollar billion. For 11 OECD countries which report FDI by ultimate investing country and FDI by mmediate investing country to the OECD: Austria, Czech Republic, Estonia, France, Germany, Hungary, Iceland, Italy, Poland, Switzerland and the United States. Finland reports inward FDI by ultimate investing country to the OECD but the data is excluded from the analysis given that inward FDI by the immediate counterparty is not publishable. Data for France, Germany and Hungary correspond to FDI positions at-end 2014. * Data exclude resident Special Purpose Entities (SPEs). Source: OECD Foreign Direct Investment statistics database.

38

Figure 19. Foreign direct investment round-tripping, at-end 2015

As a share of total positions for the reporting countries

Notes: For 11 OECD countries which report round-tripping information to the OECD: Austria, Czech Republic, Estonia, Finland, France, Hungary, Germany, Iceland, Italy, Poland and the United States. Switzerland reports inward FDI by Ultimate investing country to the OECD but the data are excluded from the analysis because round-tripping information is confidential. Data for Austria, Estonia, Hungary, Iceland and Poland exclude resident SPEs. Data for France, Germany and Hungary correspond to FDI positions at-end 2014. Source: OECD Foreign Direct Investment statistics database.

Table 19. Foreign direct investment round-tripping for selected OECD countries, at-end 2015

Reporting country Total inward FDI positions In USD billion Round-tripping - In USD billion Round-tripping - As a share of total

inward FDI positions Austria* 164 3 2% Czech Republic 112 7 6% Estonia* 19 1 7% Finland 81 7 8% France 681 31 5% Germany 850 67 8% Hungary* 99 1 1% Iceland* 8 0 1% Italy 337 35 11% Poland* 183 9 5% United States 3134 77 2% Notes: For 11 OECD countries which report round-tripping information to the OECD: Austria, Czech Republic, Estonia, Finland, France, Hungary, Germany, Iceland, Italy, Poland and the United States. Switzerland reports inward FDI by Ultimate investing country to the OECD but the data are excluded from the analysis because round-tripping information is confidential. Data for France, Germany and Hungary correspond to FDI positions at-end 2014. * Data exclude resident Special Purpose Entities (SPEs) Source: OECD Foreign Direct Investment statistics database.

0%

2%

4%

6%

8%

10%

12%

Austria CzechRepublic

Estonia Finland France Germany Hungary Iceland Italy Poland UnitedStates

Share of total inward FDI position

Round-tripping

Identifying investment flows in terms of the origin of the ultimate investing country (UIC) sheds light on so-called round-tripping. Round-tripping is when funds that have been channelled abroad by resident investors are returned to the domestic economy in the form of FDI. It can be useful to know the portion of round-tripping in total inward FDI since it arguably does not represent a genuine inward FDI. Moreover, a high portion of round-tripping may indicate problems with the country's investment policy regime. For all countries that have reported inward FDI positions by UIC, investors from their own country were among their top ten “foreign” investors. This indicates that round-tripping is quite a widespread phenomenon. The overall importance of round-tripping varies between reporting countries from rather insignificant portions of inward FDI to slightly more than 10%.

39

Figure 20. OECD rates of return on inward and outward foreign direct investment, 2005-2016

Notes: All data are expressed in per cent. p: preliminary data; Data are updated as of April 2017. Rates of return on inward/outward FDI are defined as the ratios between total income on inward/outward FDI and total inward/outward FDI positions. OECD rates of return for 2016 were estimated using FDI positions and income for 2016 when available, on directional basis or asset/liability if the latter was not available. When FDI positions for 2016 were not yet available for selected OECD countries, estimates were used by adding FDI flows for 2016 to FDI positions at-end 2015. Source: OECD Foreign Direct Investment statistics database.

0.0%

1.0%

2.0%

3.0%

4.0%

5.0%

6.0%

7.0%

8.0%

9.0%

10.0%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2 015 2016p

Rate of retun on inward FDI Rate of return on outward FDI

OECD returns on investment continued to decline in 2016

A simple rate of return - total FDI income over total FDI position - can be calculated from FDI statistics for OECD economies. Rates of return can be examined over time as an indication of the profitability of direct investments. Rates of return on both inward and outward FDI for OECD countries fell during the financial crisis, started to recover, but since 2011 have been on a general downward trend. The downturn in commodity prices likely contributed to the drop.

40

Table 20A. Rates of return on inward foreign direct investment of OECD countries, 2005-2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p

OECD countries 7.1 7.1 7.0 6.5 5.0 5.9 6.1 5.0 4.6 5.1 4.4 3.8 Australia 9.4 8.5 8.8 11.2 6.0 7.6 8.2 5.8 6.0 5.3 4.4 4.2 Austria 0.0 7.0 7.3 3.1 4.8 5.5 7.6 6.8 5.1 5.2 7.1 7.6 Belgium 4.7 5.0 4.7 3.7 4.4 3.6 3.2 3.3 3.8 5.5 4.5 4.0 Canada 4.7 4.6 4.0 6.7 3.1 4.1 5.3 5.1 4.8 4.9 4.4 3.2 Chile 15.4 24.8 23.0 17.5 12.7 12.6 11.9 9.2 8.4 6.8 4.6 4.0 Czech Republic 11.0 11.4 13.6 12.1 10.7 12.0 12.5 11.5 11.5 13.2 12.4 13.5 Denmark 9.4 6.5 6.9 5.7 4.3 5.7 5.5 3.8 6.4 5.0 4.6 Estonia 8.5 12.7 14.8 10.8 6.3 10.5 12.6 9.6 8.1 8.9 6.9 7.4 Finland 8.8 8.9 10.8 9.3 3.0 6.2 7.6 6.5 6.2 6.8 5.1 France 7.5 6.1 5.6 4.5 3.2 4.6 2.8 4.5 3.5 3.5 3.0 Germany 5.1 4.0 5.2 1.4 1.8 4.5 4.2 4.7 3.2 4.6 4.0 4.0 Greece 5.8 3.8 4.1 5.3 1.6 -2.5 -7.4 -14.1 -1.3 2.1 3.9 Hungary 8.7 8.1 9.3 9.2 5.8 7.4 9.2 7.2 6.2 9.4 10.6 11.2 Iceland 22.4 17.9 6.2 -5.2 -2.9 1.2 7.8 7.2 -0.6 -0.6 0.4 -1.2 Ireland 24.9 25.2 24.8 23.2 19.4 17.5 20.3 12.6 11.7 11.8 6.7 6.6 Israel Italy 2.6 2.3 1.9 6.5 4.8 5.1 5.9 3.3 2.8 3.2 3.5 2.4 Japan 10.1 10.0 9.8 3.3 2.6 5.3 4.2 6.0 10.8 13.4 12.0 Korea 11.1 8.3 9.4 12.3 8.9 10.4 9.9 6.9 6.9 6.6 5.9 6.1 Latvia 12.6 13.1 11.3 4.8 -12.4 1.2 5.1 7.4 6.8 7.0 7.8 8.0 Luxembourg 4.4 5.6 4.5 Mexico Netherlands 7.0 6.3 6.4 5.3 3.2 5.1 5.3 4.2 4.8 6.1 4.2 4.6 New Zealand 10.6 9.0 9.5 11.7 6.3 8.2 9.0 8.6 9.0 9.5 8.8 7.7 Norway 15.8 16.0 13.6 15.2 7.7 7.9 9.2 8.8 7.9 4.4 5.2 Poland 10.2 10.5 10.5 7.7 8.1 8.2 9.8 7.7 7.9 10.0 9.8 9.9 Portugal 6.8 7.0 5.6 5.9 7.0 10.1 7.2 4.5 2.5 3.1 4.1 Slovak Republic 7.6 7.2 8.0 6.9 5.8 6.2 6.6 4.9 5.7 7.9 8.3 9.0 Slovenia 0.0 8.5 7.4 6.5 5.0 2.8 3.7 2.2 0.0 -0.4 8.6 6.1 Spain 3.7 4.1 3.6 3.3 Sweden 8.8 7.6 7.6 6.4 5.1 6.7 6.1 5.2 5.4 7.4 6.9 Switzerland 17.0 8.9 12.8 9.5 7.3 5.9 5.3 5.5 4.3 9.3 7.6 4.3 Turkey 0.0 1.2 1.4 3.7 2.0 1.5 2.1 1.4 2.4 1.3 2.4 United Kingdom 5.8 7.4 9.1 9.7 7.0 5.8 6.3 5.0 5.3 5.3 5.2 5.4 United States 6.8 7.9 6.1 6.1 4.7 6.4 6.5 4.2 3.5 3.3 2.8 2.3

Notes: All data are expressed in per cent. p: preliminary data; Data are updated as of April 2017. Rates of return on inward/outward FDI are defined as the ratios between total income on inward/outward FDI and total inward/outward FDI positions. Data for Austria, Hungary, Iceland, Luxembourg and the Netherlands exclude resident Special Purpose Entities (SPEs). Rates of return for 2016 for Denmark, Finland, France, Greece, Japan, Luxembourg, Norway, Portugal, Sweden and Turkey are not available as FDI positions at-end 2016 are not yet available. Rates of return for Australia (2016), Japan (2005-2015), Korea (2005-2016), Spain (2016) and Switzerland (2016) are based on asset/liability figures. Rates of return are not available for Israel and Mexico as FDI income is not available. Source: OECD Foreign Direct Investment statistics database

41

Table 20B. Rates of return on outward foreign direct investment of OECD countries, 2005-2016 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p

OECD countries 9.0 8.7 8.2 7.1 5.9 7.2 7.4 6.5 6.2 6.6 5.7 5.1 Australia 5.0 5.0 5.5 8.3 3.2 3.6 4.7 4.4 4.3 4.3 3.5 4.7 Austria 0.0 8.9 9.3 7.2 5.5 6.7 7.6 6.5 5.9 5.3 6.5 6.8 Belgium 4.6 5.3 5.3 3.3 2.5 2.7 1.8 1.8 3.0 3.9 2.7 1.9 Canada 3.3 4.2 4.2 5.2 2.9 3.8 5.0 4.6 3.9 4.3 3.8 3.1 Chile 5.0 4.4 8.7 9.0 6.4 7.3 6.3 4.6 4.5 5.1 3.7 2.5 Czech Republic 14.0 13.6 15.9 31.5 5.5 7.3 9.0 7.8 6.4 8.7 10.0 8.1 Denmark 10.5 8.6 8.1 7.8 5.5 6.5 6.4 4.9 6.6 7.4 7.2 Estonia 15.6 13.2 13.9 11.7 6.4 7.3 11.1 7.3 9.0 9.0 5.2 7.5 Finland 8.6 9.7 10.0 9.3 6.6 8.0 8.0 6.7 5.4 9.3 8.0 France 8.6 7.9 6.9 6.8 5.1 6.6 6.1 6.2 5.9 6.3 5.5 Germany 6.9 6.9 6.4 2.2 4.9 6.0 7.1 6.0 6.0 6.3 5.3 5.3 Greece 4.8 2.5 2.4 2.4 1.9 2.5 0.9 2.6 2.2 9.6 7.6 Hungary 7.7 10.1 8.3 4.2 4.9 4.8 5.0 4.7 3.7 4.3 3.1 4.6 Iceland 9.6 9.6 9.3 -11.6 -5.6 -4.8 7.6 -2.2 3.2 2.0 3.7 5.9 Ireland 7.7 9.0 9.5 8.8 4.3 5.6 6.4 3.4 3.1 2.9 1.0 1.5 Israel Italy 1.7 2.0 2.6 7.5 5.8 5.8 6.5 5.0 4.3 5.4 2.6 2.4 Japan 9.1 9.0 8.0 3.9 5.4 6.9 6.7 5.9 7.7 8.5 7.5 Korea 8.6 5.9 5.4 2.8 2.2 6.2 7.6 7.8 6.5 5.3 3.8 2.9 Latvia 12.9 7.1 7.0 5.1 -8.3 -3.3 6.8 7.4 6.1 6.7 13.1 10.5 Luxembourg 2.5 4.0 2.8 Mexico Netherlands 8.2 8.6 8.3 5.2 3.9 6.1 7.3 6.7 5.6 6.2 4.3 3.8 New Zealand 3.3 3.3 5.6 1.8 1.4 3.7 1.8 3.6 3.1 3.9 2.7 3.7 Norway 12.8 7.1 7.1 6.8 2.4 6.0 4.2 4.7 4.7 8.4 4.8 Poland 2.0 4.7 0.6 4.0 -0.4 2.9 2.9 3.5 0.6 6.7 3.0 3.6 Portugal 6.6 6.2 5.3 6.0 4.4 10.8 7.8 4.8 4.9 2.9 3.4 Slovak Republic 5.2 15.6 11.8 15.6 16.2 14.3 11.0 4.9 5.6 28.8 7.9 7.7 Slovenia 0.0 4.0 4.4 3.4 -1.6 -3.9 -0.7 -5.2 -7.7 -1.3 0.9 0.7 Spain 6.1 6.7 5.9 4.9 Sweden 11.7 11.8 11.9 11.7 7.0 9.2 8.9 8.4 7.9 9.0 7.7 Switzerland 14.2 9.7 7.1 0.9 5.6 6.9 4.5 5.4 5.1 8.3 8.5 4.9 Turkey 0.0 1.5 0.9 1.8 0.8 3.0 0.8 0.3 0.8 0.8 0.6 United Kingdom 11.3 10.2 9.8 8.4 6.6 8.0 9.2 7.5 6.8 6.4 5.6 5.3 United States 12.1 12.3 11.7 12.2 9.5 11.2 11.2 8.8 7.5 7.5 7.0 6.5

Notes: All data are expressed in per cent. p: preliminary data; Data are updated as of April 2017. Rates of return on inward/outward FDI are defined as the ratios between total income on inward/outward FDI and total inward/outward FDI positions. Data for Austria, Hungary, Iceland, Luxembourg and the Netherlands exclude resident Special Purpose Entities (SPEs). Rates of return for 2016 for Denmark, Finland, France, Greece, Japan, Luxembourg, Norway, Portugal, Sweden and Turkey are not available as FDI positions at-end 2016 are not yet available. Rates of return for Australia (2016), Japan (2005-2015), Korea (2005-2016), Spain (2016) and Switzerland (2016) are based on asset/liability figures. Rates of return are not available for Israel and Mexico as FDI income is not available. Source: OECD Foreign Direct Investment statistics database

42

Figure 21. OECD FDI Regulatory Restrictiveness Index: OECD and Non-OECD, 1997-2016

Notes: The OECD FDI Regulatory Restrictiveness Index covers only statutory measures discriminating against foreign investors (e.g. foreign equity limits, screening & approval procedures, restriction on key foreign personnel, and other operational measures). Other important aspects of an investment climate (e.g. the implementation of regulations and state monopolies among other) are not considered. Country coverage expands over time. In 1997, there were 46 economies covered. In 2016, all 35 OECD countries and 28 non-OECD countries were covered, including all G20 members. Data reflect average scores for restrictions as of end-year.

Source: OECD FDI Regulatory Restrictiveness Index database.

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

1997 2003 2006 2010 2011 2012 2013 2014 2015 2016(n=46) (n=47) (n=48) (n=56) (n=56) (n=60) (n=61) (n=61) (n=61) (n=63)

OECD Non-OECD

OECD FDI Regulatory Restrictiveness Index (open=0; closed=1)

Regulatory Restrictions to Foreign Direct Investment (FDI)

Seen from a broad perspective, countries have significantly liberalised restrictions on international investment over time, albeit at a slower pace more recently. Yet, significant variation remains across countries in terms of statutory restrictions on FDI. Many service sectors worldwide remain partly off limits to foreign investors, holding back potential productivity gains. In recent periods, some countries became more sensitive to FDI in primary sectors (notably agriculture, mining and quarrying), tightening the regime for foreign investors in these sectors. But an overall liberalisation trend still stands in most countries. In 2016, some emerging economies undertook relatively extensive FDI liberalisation reforms. The OECD FDI Regulatory Restrictiveness Index gauges the restrictiveness of a country’s FDI rules across 22 economic sectors and across four types of restrictions: foreign equity restrictions; screening or approval mechanisms; restrictions on key foreign employment; and operational restrictions to FDI. Restrictions are scored on a range from 0 (open) to 1 (closed).

43

Table 21. OECD FDI Regulatory Restrictiveness Index per sector, (Open = 0; Closed = 1), 2016

Countries Total Index Primary Manufacturing Electricity Distribution Transport Media Communications

Financial services

Business services

Real estate investment

Australia 0.15 0.14 0.08 0.20 0.08 0.27 0.20 0.40 0.13 0.08 0.40 Austria 0.11 0.15 0.00 1.00 0.00 0.18 0.00 0.00 0.00 0.32 0.20 Belgium 0.04 0.04 0.02 0.02 0.02 0.11 0.02 0.02 0.02 0.25 0.02 Canada 0.17 0.19 0.10 0.10 0.10 0.27 0.71 0.57 0.07 0.10 0.01 Chile 0.06 0.15 0.00 0.00 0.00 0.41 0.19 0.00 0.02 0.01 0.00 Czech Rep. 0.01 0.03 0.00 0.00 0.00 0.08 0.00 0.00 0.01 0.00 0.02 Denmark 0.03 0.06 0.00 0.00 0.00 0.08 0.00 0.00 0.00 0.36 0.05 Estonia 0.02 0.02 0.00 0.00 0.00 0.15 0.00 0.00 0.00 0.00 0.15 Finland 0.02 0.02 0.01 0.08 0.01 0.09 0.01 0.01 0.01 0.05 0.00 France 0.05 0.16 0.00 0.00 0.00 0.15 0.05 0.00 0.05 0.00 0.00 Germany 0.02 0.07 0.00 0.00 0.00 0.20 0.03 0.00 0.01 0.00 0.00 Greece 0.03 0.08 0.00 0.00 0.00 0.15 0.11 0.00 0.02 0.06 0.00 Hungary 0.03 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.01 0.00 0.45 Iceland 0.17 0.24 0.11 0.56 0.11 0.20 0.11 0.11 0.12 0.11 0.24 Ireland 0.04 0.14 0.00 0.00 0.00 0.13 0.00 0.00 0.01 0.00 0.25 Israel 0.12 0.06 0.02 0.77 0.02 0.40 0.26 0.40 0.04 0.02 0.22 Italy 0.05 0.13 0.00 0.00 0.00 0.20 0.36 0.00 0.02 0.00 0.00 Japan 0.05 0.07 0.00 0.03 0.00 0.28 0.20 0.27 0.00 0.00 0.10 Korea 0.14 0.25 0.00 0.42 0.00 0.51 0.56 0.33 0.05 0.00 0.00 Latvia 0.03 0.03 0.01 0.01 0.01 0.08 0.01 0.01 0.01 0.01 0.23 Luxembourg 0.00 0.00 0.00 0.00 0.00 0.08 0.00 0.00 0.00 0.00 0.00 Mexico 0.19 0.32 0.10 0.10 0.18 0.53 0.53 0.10 0.13 0.10 0.17 Netherlands 0.02 0.06 0.00 0.00 0.00 0.08 0.00 0.00 0.00 0.00 0.00 New Zealand 0.24 0.33 0.20 0.20 0.20 0.28 0.20 0.40 0.23 0.20 0.20 Norway 0.09 0.16 0.00 0.00 0.00 0.35 0.13 0.00 0.07 0.31 0.25 Poland 0.07 0.05 0.00 0.00 0.00 0.09 0.30 0.08 0.00 0.00 0.90 Portugal 0.01 0.01 0.00 0.00 0.00 0.08 0.00 0.00 0.02 0.00 0.00 Slovak Rep. 0.05 0.00 0.00 0.00 0.00 0.08 0.00 0.00 0.00 0.00 1.00 Slovenia 0.01 0.00 0.00 0.00 0.00 0.15 0.00 0.00 0.00 0.00 0.01 Spain 0.02 0.01 0.00 0.00 0.00 0.08 0.23 0.00 0.00 0.11 0.00 Sweden 0.06 0.14 0.00 0.00 0.00 0.29 0.20 0.20 0.00 0.05 0.00 Switzerland 0.08 0.00 0.00 0.50 0.00 0.25 0.47 0.00 0.07 0.00 0.40 Turkey 0.06 0.01 0.00 0.00 0.00 0.38 0.20 0.00 0.00 0.13 0.55 UK 0.04 0.14 0.00 0.00 0.00 0.09 0.23 0.00 0.00 0.00 0.00 United States 0.09 0.18 0.00 0.20 0.00 0.55 0.25 0.11 0.04 0.00 0.00 OECD Avg. 0.07 0.10 0.02 0.12 0.02 0.21 0.16 0.09 0.03 0.07 0.17 Argentina 0.03 0.04 0.00 0.00 0.00 0.04 0.50 0.00 0.00 0.00 0.00 Brazil 0.10 0.19 0.03 0.03 0.03 0.28 0.55 0.03 0.11 0.03 0.03 Cambodia 0.05 0.04 0.02 0.01 0.01 0.04 0.44 0.01 0.04 0.07 0.13 China 0.33 0.37 0.12 0.44 0.12 0.54 1.00 0.75 0.49 0.25 0.11 Colombia 0.03 0.04 0.00 0.05 0.00 0.12 0.21 0.00 0.02 0.00 0.00 Costa Rica 0.05 0.10 0.00 0.12 0.00 0.33 0.05 0.00 0.05 0.00 0.03 Egypt 0.06 0.00 0.00 0.00 0.00 0.33 0.00 0.00 0.02 0.10 0.33 India 0.21 0.21 0.04 0.06 0.29 0.09 0.28 0.18 0.28 0.56 1.00 Indonesia 0.32 0.46 0.07 0.11 0.37 0.38 0.80 0.26 0.20 0.58 1.00 Jordan 0.24 0.11 0.05 0.05 0.57 0.56 0.41 0.05 0.18 0.36 0.80 Kazakhstan 0.13 0.22 0.04 0.04 0.04 0.22 0.54 0.39 0.12 0.04 0.04 Kyrgyzstan 0.08 0.06 0.04 0.04 0.04 0.22 0.04 0.04 0.04 0.04 0.24 Lao PDR 0.19 0.17 0.14 0.17 0.35 0.14 0.15 0.12 0.21 0.14 0.13 Lithuania 0.03 0.07 0.01 0.01 0.01 0.28 0.01 0.01 0.01 0.01 0.11 Malaysia 0.21 0.25 0.00 0.50 0.44 0.10 0.65 0.25 0.20 0.09 0.30 Mongolia 0.10 0.13 0.09 0.09 0.09 0.20 0.09 0.09 0.09 0.09 0.09 Morocco 0.07 0.17 0.00 0.00 0.00 0.27 0.03 0.00 0.03 0.40 0.00 Myanmar 0.36 0.34 0.31 0.14 0.24 0.38 0.64 0.11 0.68 0.21 0.38 Peru 0.08 0.05 0.05 0.05 0.05 0.43 0.30 0.05 0.05 0.05 0.00 Philippines 0.40 0.66 0.07 0.50 0.16 0.67 0.96 0.67 0.11 1.00 0.53 Romania 0.01 0.00 0.00 0.00 0.00 0.17 0.00 0.00 0.00 0.00 0.00 Russia 0.19 0.16 0.10 0.03 0.05 0.35 0.48 0.10 0.43 0.18 0.33 Saudi Arabia 0.36 0.61 0.21 0.21 0.23 0.45 0.61 0.30 0.27 0.30 1.00 South Africa 0.06 0.01 0.01 0.01 0.01 0.19 0.30 0.01 0.05 0.26 0.06 Tunisia 0.21 0.21 0.04 0.03 0.63 0.27 0.09 0.20 0.24 0.22 0.20 Ukraine 0.12 0.13 0.08 0.06 0.08 0.34 0.27 0.08 0.08 0.08 0.41 Viet Nam 0.11 0.06 0.03 0.01 0.11 0.50 0.37 0.58 0.04 0.03 0.24

Notes: The OECD FDI Regulatory Restrictiveness Index covers only statutory measures discriminating against foreign investors (e.g. foreign equity limits, screening & approval procedures, restriction on key foreign personnel, and other operational measures). Other important aspects of an investment climate (e.g. the implementation of regulations and state monopolies among other) are not considered. All 35 OECD countries and 28 non-OECD countries were covered, including all G20 members. Data reflect average scores for restrictions as of end-year. Source: OECD FDI Regulatory Restrictiveness Index database, http://www.oecd.org/investment/fdiindex.htm.

44

Figure 22. Distance-to-default (DTD) of large listed banks, 1999–2016

Table 22. Average distance-to-default (DTD) of large listed banks, 2004–2016 All large banks G-SIBs Other large banks

United States Europe Asia Latin

America United States Europe Asia United

States Europe Asia Latin America

Dec-04 6.72 5.26 2.58 3.04 6.74 5.32 2.33 6.61 4.97 2.87 3.04Jun-05 7.15 6.21 3.49 3.39 7.15 6.34 3.66 7.17 5.57 3.31 3.39 Dec-05 7.60 6.29 3.27 3.03 7.74 6.44 3.18 6.93 5.52 3.36 3.03 Jun-06 7.08 5.12 2.94 2.38 7.10 5.24 2.75 7.01 4.51 3.14 2.38 Dec-06 7.10 5.05 3.50 2.71 6.96 5.18 3.28 7.85 4.39 3.73 2.71 Jun-07 6.86 5.53 3.89 3.54 6.66 5.63 4.23 7.92 5.03 3.59 3.54 Dec-07 3.82 4.08 2.84 3.01 3.81 4.07 2.95 3.92 4.15 2.77 3.01 Jun-08 2.41 2.72 2.22 2.36 2.39 2.69 2.21 2.50 2.95 2.23 2.36 Dec-08 0.71 1.18 1.54 1.19 0.66 1.18 1.61 0.93 1.20 1.50 1.19 Jun-09 0.05 0.61 1.54 1.08 0.03 0.63 1.53 0.15 0.52 1.54 1.08 Dec-09 0.60 1.12 2.30 2.36 0.61 1.18 2.17 0.60 0.88 2.39 2.36 Jun-10 2.68 2.11 3.08 2.79 2.71 2.15 3.17 2.53 1.96 3.02 2.79 Dec-10 3.13 2.37 3.64 3.14 3.15 2.36 4.09 3.01 2.38 3.34 3.14 Jun-11 3.86 3.06 3.90 3.66 3.88 3.12 3.85 3.76 2.81 3.92 3.66 Dec-11 2.29 1.79 4.04 2.79 2.22 1.82 3.85 2.67 1.65 4.17 2.79 Jun-12 2.16 1.65 4.22 2.64 2.06 1.69 4.19 2.65 1.51 4.24 2.64 Dec-12 3.70 2.42 4.96 3.36 3.51 2.44 4.46 4.64 2.36 5.27 3.36 Jun-13 4.56 2.95 4.38 3.78 4.38 2.95 3.69 5.47 2.98 4.79 3.78 Dec-13 5.44 3.68 4.30 3.61 5.25 3.74 3.76 6.36 3.42 4.60 3.61 Jun-14 5.96 4.45 5.08 3.44 5.81 4.54 4.67 6.68 4.05 5.28 3.44 Dec-14 5.98 4.51 4.56 2.67 5.88 4.54 4.31 6.48 4.40 4.68 2.67 Jun-15 5.80 4.11 3.92 2.46 5.73 4.05 3.89 6.08 4.37 3.92 2.46 Dec-15 4.73 3.84 3.29 2.32 4.73 3.77 3.27 4.76 4.11 3.30 2.32 Jun-16 3.63 2.51 3.30 1.95 3.59 2.48 2.98 3.77 2.67 3.44 1.95 Dec-16 4.03 2.51 4.14 2.22 3.96 2.48 3.35 4.35 2.64 4.51 2.22

Notes: All data are reported at period-end. Europe refers to the European Union, Norway and Switzerland. Banks included in the sample are listed in Bloomberg regional banking indices. The horizontal 3-standard-deviation line represents a minimal level of “safety” based on calibration from previous crises. G-SIB stands for Global Systemically Important Bank. Source: Bloomberg, OECD calculations. See Annex for details

0

1

2

3

4

5

6

7

8Std. dev .

United States Europe Asia Latin America

Distance-to-default has fallen

Bank default risk is measured by the distance-to-default (DTD). A bank defaults when DTD moves to 0 and below. During 2016, DTD increased in the United States and Asia and remained largely unchanged in Latin America, which was below Europe. Latin America and Europe both remain below the minimal level of “safety”. Despite modest improvements during 2016, DTD in United States remains well below the pre-crisis level.

45

Figure 23. Total assets of large listed banks as percentage of world GDP, 2005–2016

Notes: The sample includes large global banks over the period 2005-2016. All systemically important banks (G-SIBs) listed by the Financial Stability Board (2016) are included. The six US G-SIBs, the fifty largest US banks by 2015 assets, the fifty-five largest banks in the world ranked by market capitalisation (including European, Japanese and Australian G-SIBs) and eighteen listed domestic systemically important European banks identified by the European Banking Authority. For consistency purposes, financial statements reported under GAAP accounting standards are adjusted to be comparable with IFRS basis. Under GAAP accounting standards, net value of derivatives is reported on the balance sheet instead of gross market value under IFRS accounting standards. The gross market value of derivatives is added to total assets of banks which are reporting the financial statements under GAAP accounting standards. Source: SNL Financials, Bloomberg, International Monetary Fund, OECD calculations.

30

35

40

45

50

55

60

10

15

20

25

30

35

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

% of World GDP% of World GDP

Total assets (harmonised IFRS)

North America Asia Pacific Europe (RHS)

0

1

2

3

4

5

6

15

20

25

30

35

40

45

50

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

% of World GDP% of World GDP

G-SIBs US G-SIBs Non-USOther Large Banks Non-US Other Large Banks US (RHS)Domestic Systemically Important Banks EU (RHS)

Downsizing in banking sector following the 2008 financial crisis

The share of banks’ total assets in world GDP is massively decreasing for large listed European banks and to a lesser extent for large listed US banks. Large listed banks worldwide and domestic systemically important banks in the EU reduced the size of their balance sheet after 2009-2010, except for US large non-G-SIBs banks. However, concerns are rising regarding uneven financial regulations between large and small banks and the increase in high-risk shadow banking activities.

46

Table 23. Total assets (harmonised IFRS) in USD billion of large listed banks by region or size, 2005–2016

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Europe 20,454 26,423 35,114 37,208 34,908 34,836 35,891 34,050 33,487 32,904 28,543 27,313

North America 13,317 15,545 16,674 19,935 19,383 20,046 22,209 22,030 20,793 21,787 20,291 20,850

Asia Pacific - - - 7,275 7,813 8,592 10,701 10,446 9,694 9,384 9,324 9,836

G-SIBs US 10,152 11,959 12,390 15,489 14,611 14,895 16,429 15,825 14,488 15,184 13,609 13,769

G-SIBs Non-US 13,478 18,059 24,114 30,041 26,750 27,245 29,808 27,127 26,410 26,467 23,581 23,109

Other Large Banks US 1,614 1,757 1,908 2,231 2,391 2,422 2,584 2,804 2,866 3,130 3,350 3,593

Other Large Banks Non-US 8,698 10,960 14,309 14,356 15,998 16,659 17,963 18,845 18,373 17,629 16,174 16,148

Domestic Systemically Important Banks in Europe 1,328 1,740 2,192 2,301 2,355 2,254 2,018 1,925 1,838 1,665 1,445 1,379

Notes: The sample includes large global banks over the period 2005-2016. All systemically important banks (G-SIBs) listed by the Financial Stability Board (2016) are included. The six US G-SIBs, the fifty largest US banks by 2015 assets, the fifty-five largest banks in the world ranked by market capitalisation (including European, Japanese and Australian G-SIBs) and eighteen listed domestic systemically important European banks identified by the European Banking Authority. For consistency purposes, financial statements reported under GAAP accounting standards are adjusted to be comparable with IFRS basis. Under GAAP accounting standards, net value of derivatives is reported on the balance sheet instead of gross market value under IFRS accounting standards. The gross market value of derivatives is added to total assets of banks which are reporting the financial statements under GAAP accounting standards. Total assets is expressed in current USD by region or bank size. Source: SNL Financials, Bloomberg, International Monetary Fund, OECD calculations.

47

Figure 24. Bank beta indicator for large listed banks, 1999–2016

Source: Bloomberg, OECD calculations.

0.0

0.5

1.0

1.5

2.0

2.5

3.0Beta

Beta calculated using Regional MSCI Indices

0.0

0.5

1.0

1.5

2.0

2.5

3.0Beta

Beta calculated using Global MSCI Index

United States Europe Asia Latin America

Systematic risk in the banking sector

Beta is defined as the covariance of a firm’s stock returns with the market divided by variance of market returns (calculated here over a rolling window). The beta for a bank stock is a measure of the degree to which its returns co-vary with the market and therefore cannot be eliminated through diversification. Beta is a key input into the calculation of the bank-specific equity risk premium (the product of bank beta and the market equity risk premium). During the 2008 financial crisis, betas of mainly US and European banks peaked-up raising their equity risk premia in a correlated way. Recent beta values of US, European and Latin American banks are higher than pre-crisis values emphasizing the limited effects of regulatory measures implemented after the crisis to mitigate systemic risk. Asian banks exhibit much lower beta values than the other banks with a slump in December 2014. Systemic risk should remain under close scrutiny in particular for US and European banks with increasing beta since December 2015.

48

Table 24A. Average beta calculated using MSCI regional equity indices for large listed banks, 2004–2016 All large banks G-SIBs Other large banks





Table 24B. Average beta calculated using MSCI global equity index for large listed banks, 2004–2016 All large banks G-SIBs Other large banks





Notes: All data are reported at period-end. Europe refers to the European Union, Norway and Switzerland Banks included in the sample are listed in Bloomberg regional banking indices. Beta is defined as the covariance of a bank's stock returns with MSCI benchmark (either related regional or global benchmarks) divided by variance of market returns. It is an indicator of the systemic importance a bank with respect to the economy. G-SIB stands for Global Systemically Important Bank. Source: Bloomberg, OECD calculations.

49

Figure 25. Deviations from covered interest parity (CIP) on domestic forward (DF) and non-deliverable forward (NDF) markets, 2016

Notes: Deviations from CIP is measured as the 1-year average conditional volatility of CIP which is the conditional standard deviation calculated using a GARCH (1,1) model. Along with interest parities, the conditional variance of CIPs might be a measure of dynamic capital mobility. Indeed with greater capital mobility, not only covered differential rates but also the variance would decline over time. CIP is calculated using deliverable and non-deliverable forward rates. The greater the volatility, the more CIP is deviating from the 0 equilibrium. This phenomenon is observed in countries with strong capital control measures. Source: Thomson Reuters, OECD calculations. See Annex for details.

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7GARCH conditional std dev

Domestic forward market

0.71

0

0.5

1

1.5

2

2.5

3

GARCH conditional std devNon-Deliverable forward market

5.10

Openness of banking systems

The measure of the openness of a country’s banking system is based on the persistence of deviations from covered interest parity (CIP). A higher score implies a less open banking system. While the indicator shows that banking systems in emerging economies typically are less open than in advanced economies, many emerging countries have, over time, moved down the restrictiveness index. Countries with non-deliverable forward markets (NDF) are those where controls are so strong that an offshore parallel foreign exchange market emerges to serve investor needs.

50

Table 25A. Deviations from covered interest parity (CIP) on domestic forward (DF) markets, 2006–2016 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

Australia 0.02 0.04 0.20 0.07 0.06 0.06 0.05 0.04 0.04 0.05 0.03 Canada 0.03 0.05 0.15 0.06 0.03 0.02 0.02 0.01 0.01 0.02 0.02 China 0.30 0.64 1.07 0.57 0.44 0.51 0.62 0.57 0.56 0.26 0.22 Czech Republic 0.04 0.05 0.21 0.15 0.06 0.04 0.03 0.03 0.02 0.11 0.11 Denmark 0.03 0.04 0.15 0.05 0.03 0.05 0.03 0.01 0.01 0.05 0.03 Euro area 0.03 0.03 0.13 0.03 0.04 0.05 0.02 0.01 0.01 0.02 0.03 Hong Kong (China) 0.04 0.05 0.09 0.02 0.02 0.02 0.01 0.01 0.01 0.02 0.04 Hungary 0.24 0.30 0.41 0.72 0.34 0.30 0.26 0.18 0.20 0.36 0.18 India 0.20 0.46 0.54 0.18 0.17 0.31 0.18 0.25 0.16 0.11 0.16 Indonesia - 0.24 0.44 0.43 0.13 0.17 0.13 0.14 0.11 0.34 0.21 Israel 0.05 0.06 0.16 0.08 0.06 0.11 0.08 0.04 0.06 0.04 0.06 Japan 0.06 0.06 0.14 0.03 0.03 0.04 0.02 0.01 0.01 0.03 0.04 Korea 0.03 0.17 0.45 0.14 0.09 0.08 0.05 0.06 0.04 0.03 0.04 Malaysia 0.05 0.04 0.15 0.06 0.05 0.06 0.05 0.04 0.06 0.06 0.05 Mexico 0.08 0.06 0.32 0.19 0.11 0.09 0.08 0.07 0.07 0.05 0.12 Morocco 0.21 0.23 0.20 0.23 0.19 0.18 0.14 0.19 0.28 0.25 0.22 New Zealand 0.08 0.08 0.14 0.15 0.11 0.10 0.07 0.07 0.06 0.11 0.11 Norway 0.03 0.04 0.17 0.06 0.04 0.05 0.03 0.02 0.02 0.02 0.02 Pakistan 0.16 0.16 0.65 0.29 0.18 0.32 0.17 0.21 0.29 0.15 0.10 Philippines 0.18 0.22 0.32 0.20 0.59 0.28 0.20 0.18 0.08 0.06 0.08 Poland 0.03 0.04 0.25 0.11 0.08 0.09 0.12 0.06 0.08 0.09 0.14 Russia 0.22 0.23 2.03 1.09 0.19 0.29 0.12 0.09 0.50 0.60 0.25 Saudi Arabia - - - - 0.11 0.08 0.06 0.11 0.19 0.20 0.21 Singapore 0.04 0.07 0.14 0.06 0.02 0.06 0.02 0.01 0.02 0.09 0.06 South Africa 0.06 0.10 0.18 0.16 0.09 0.07 0.09 0.08 0.09 0.10 0.09 Sweden 0.08 0.06 0.13 0.17 0.11 0.11 0.08 0.07 0.06 0.15 0.09 Switzerland 0.05 0.04 0.15 0.03 0.06 0.08 0.04 0.02 0.02 0.07 0.05 Chinese Taipei 0.24 0.46 0.39 0.42 1.07 0.48 0.20 0.25 0.18 0.26 0.26 Thailand 0.93 6.08 2.09 0.57 0.53 0.83 0.72 0.90 0.61 1.10 0.71 Turkey 0.31 0.21 0.39 0.15 0.13 0.17 0.17 0.19 0.18 0.16 0.15 United Kingdom 0.01 0.03 0.14 0.03 0.01 0.06 0.01 0.01 0.01 0.01 0.04 United States 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00

Table 25B. Deviations from covered interest parity (CIP) on non-deliverable forward (NDF) markets, 2006–2016

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 Argentina 0.82 1.32 2.91 2.18 0.89 1.91 2.43 3.22 3.82 8.85 2.31 Brazil 0.50 0.18 0.47 0.30 0.20 0.47 0.18 0.17 0.12 0.17 0.20 Chile 0.37 0.28 0.39 0.65 0.28 0.31 0.28 0.22 0.27 0.25 0.19 China 0.33 0.64 1.10 0.57 0.71 0.73 0.74 0.63 0.73 0.95 0.75 Colombia 0.23 0.42 0.39 0.31 0.45 0.44 0.25 0.15 0.22 0.24 0.23 Egypt 0.07 0.14 0.81 2.58 0.31 1.34 1.31 2.37 1.24 2.26 5.10 India 0.60 1.02 2.10 1.35 1.18 1.20 1.30 1.54 0.93 0.78 0.78 Indonesia 1.11 1.41 3.05 2.92 1.38 2.02 1.54 2.67 1.71 1.68 1.55 Korea 0.66 0.84 3.24 2.45 1.97 1.87 0.98 1.06 1.11 1.55 1.58 Malaysia 0.38 0.64 1.10 1.22 1.05 1.19 0.84 1.08 0.87 1.95 1.88 Peru 0.20 0.19 0.74 0.33 0.25 0.27 0.18 0.28 0.36 0.67 0.26 Philippines 0.64 1.26 2.06 1.68 1.20 1.14 0.74 0.89 0.83 0.86 0.96 Russia 0.46 0.32 1.65 4.62 0.94 1.56 1.72 0.44 1.64 1.20 1.33 Chinese Taipei 0.79 0.62 1.30 1.24 0.97 1.24 0.66 0.77 0.68 1.31 1.19 Source: Thomson Reuters Datastream, OECD calculations. See Annex for details.

51

Figure 26. Saving-investment correlation, 5 years rolling window, 1981–2016

Table 26. Saving-investment correlation by region, 5 years rolling window, 1986–2016

Date range Advanced economies Emerging markets OECD countries BRICS 1986 Q4 0.38 0.20 0.37 0.74 1987 Q4 0.45 0.18 0.43 0.83 1988 Q4 0.45 0.25 0.45 0.86 1989 Q4 0.47 0.25 0.48 0.85 1990 Q4 0.49 0.29 0.50 0.79 1991 Q4 0.52 0.27 0.53 0.75 1992 Q4 0.54 0.35 0.56 0.71 1993 Q4 0.58 0.42 0.60 0.81 1994 Q4 0.61 0.47 0.61 0.85 1995 Q4 0.60 0.52 0.61 0.85 1996 Q4 0.60 0.65 0.60 0.80 1997 Q4 0.58 0.70 0.59 0.78 1998 Q4 0.52 0.70 0.53 0.75 1999 Q4 0.42 0.69 0.44 0.69 2000 Q4 0.28 0.59 0.30 0.61 2001 Q4 0.19 0.57 0.22 0.58 2002 Q4 0.13 0.56 0.17 0.60 2003 Q4 0.11 0.56 0.16 0.64 2004 Q4 0.08 0.53 0.14 0.70 2005 Q4 0.06 0.49 0.12 0.80 2006 Q4 0.02 0.43 0.07 0.85 2007 Q4 0.00 0.38 0.05 0.85 2008 Q4 0.00 0.34 0.04 0.83 2009 Q4 0.06 0.37 0.09 0.82 2010 Q4 0.12 0.42 0.13 0.82 2011 Q4 0.18 0.44 0.19 0.81 2012 Q4 0.22 0.46 0.22 0.80 2013 Q4 0.27 0.51 0.26 0.79 2014 Q4 0.30 0.49 0.28 0.76 2015 Q4 0.33 0.50 0.31 0.75 2016 Q4 0.37 0.56 0.35 0.74

Notes: Saving-investment correlation is measured by the β coefficient associated to the national gross capital formation indicator when regressed on the national gross saving indicator over 5-years rolling sample time period using quarterly data.


-0.1

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1981 Q4 1985 Q2 1988 Q4 1992 Q2 1995 Q4 1999 Q2 2002 Q4 2006 Q2 2009 Q4 2013 Q2 2016 Q4

Advanced economies Emerging economies OECD countries BRICS

Saving-investment correlation

The saving-investment correlations are indicators of the financial openness of an economy. Among the categories of countries presented, the BRICS are the least open economies and have in recent years made no significant efforts in further opening their economies. The financial openness of advanced and OECD economies increased in the 1990s and early 2000s, but has been declining since the 2008 crisis. Other EMEs made progress compared to the BRICS, but their financial openness has also declined since the crisis.

52

Figure 27. Five-year rolling real exchange rate valuation by country, 1990-2015

Notes: Selected countries included in the chart are OECD or G20 Members.

Source: International Monetary Fund, OECD calculations. See Annex for details.

-1.2

-0.7

-0.2

0.3

0.8

1.3

Log of UNDERVAL

Average 1990-2015 Max Min

Exchange rate valuation measure

A purchasing-power-parity (PPP) real exchange rate is compared to fundamentals-based "norm" for where its level should be. Real GDP per capita is used as a general measure of real living standards against which PPP real exchange rates might be compared over the longer term. Higher GDP per capita warrants a higher real exchange rate. Amongst the BRIICS countries, Russia, Indonesia and India have been significantly undervalued on this PPP measure, while China, Brazil and South Africa have on average been much closer to the level justified by fundamentals. Amongst OECD countries, only a few countries appear to have had undervalued currencies (Poland, Hungary and Turkey). Most OECD economies have overvalued currencies (compared to what is justified by GDP per capita).

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Table 27. Five-year rolling real exchange rate valuation by country, 2005-2015 Country 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Argentina 0.21 0.36 0.32 0.28 0.30 0.26 0.20 0.13 0.09 0.04 0.02 Australia -0.43 -0.49 -0.55 -0.52 -0.49 -0.53 -0.57 -0.61 -0.65 -0.65 -0.61 Brazil 0.25 0.21 0.06 0.01 -0.04 -0.11 -0.16 -0.18 -0.22 -0.20 -0.13 Bulgaria 0.44 0.39 0.34 0.31 0.34 0.32 0.32 0.33 0.33 0.36 0.37 Canada -0.48 -0.50 -0.56 -0.55 -0.49 -0.48 -0.48 -0.47 -0.49 -0.48 -0.45 Chile 0.07 0.03 -0.04 -0.03 0.00 -0.01 0.00 -0.01 -0.06 -0.05 -0.01 China 0.11 0.14 0.15 0.13 0.16 0.16 0.12 0.09 0.07 0.02 -0.02 Croatia -0.09 -0.14 -0.17 -0.19 -0.14 -0.14 -0.11 -0.08 -0.06 -0.02 0.00 Czech Republic -0.04 -0.10 -0.14 -0.16 -0.11 -0.11 -0.08 -0.06 -0.03 0.01 0.04 Denmark -0.73 -0.76 -0.78 -0.78 -0.71 -0.70 -0.67 -0.65 -0.64 -0.61 -0.61 Euro area -0.37 -0.41 -0.44 -0.44 -0.37 -0.36 -0.32 -0.29 -0.28 -0.25 -0.24 Hungary 0.00 -0.06 -0.08 -0.09 -0.01 0.00 0.06 0.10 0.12 0.17 0.19 Iceland -0.91 -0.95 -0.97 -0.87 -0.69 -0.58 -0.48 -0.37 -0.40 -0.42 -0.45 India 0.36 0.37 0.35 0.37 0.44 0.44 0.47 0.50 0.52 0.54 0.56 Indonesia 0.65 0.60 0.58 0.57 0.56 0.51 0.47 0.43 0.43 0.44 0.47 Israel -0.58 -0.53 -0.51 -0.49 -0.43 -0.44 -0.43 -0.43 -0.45 -0.45 -0.47 Japan -0.82 -0.77 -0.69 -0.66 -0.57 -0.57 -0.60 -0.61 -0.54 -0.47 -0.41 Korea -0.38 -0.40 -0.40 -0.35 -0.23 -0.17 -0.10 -0.06 -0.09 -0.10 -0.12 Mexico -0.20 -0.16 -0.14 -0.11 -0.03 0.01 0.07 0.08 0.07 0.07 0.08 New Zealand -0.46 -0.52 -0.55 -0.51 -0.43 -0.42 -0.42 -0.42 -0.49 -0.51 -0.52 Norway -0.53 -0.58 -0.62 -0.63 -0.58 -0.59 -0.60 -0.60 -0.63 -0.61 -0.57 Poland -0.03 -0.04 -0.09 -0.10 -0.03 -0.01 0.04 0.09 0.10 0.14 0.17 Russia 0.68 0.57 0.45 0.35 0.36 0.32 0.29 0.26 0.22 0.26 0.33 Saudi Arabia 0.69 0.66 0.63 0.56 0.59 0.58 0.55 0.51 0.51 0.46 0.45 South Africa 0.01 -0.10 -0.14 -0.09 0.00 0.00 0.01 0.02 0.00 0.05 0.14 Sweden -0.70 -0.73 -0.74 -0.68 -0.59 -0.58 -0.55 -0.54 -0.57 -0.55 -0.54 Switzerland -0.71 -0.72 -0.70 -0.69 -0.62 -0.63 -0.65 -0.67 -0.68 -0.67 -0.68 Turkey 0.13 0.04 -0.06 -0.07 -0.02 0.00 0.04 0.08 0.11 0.14 0.18 United Kingdom -0.76 -0.78 -0.78 -0.71 -0.60 -0.54 -0.47 -0.41 -0.43 -0.43 -0.45

Notes: The overvaluation and undervaluation exchange rate measure is derived from the Rodrik (2008) model. It is an exchange rate measure based on domestic price level adjusted for the Balassa-Samuelson effect. Whenever UNDERVAL exceeds unity, it indicates that the exchange rate is set such that goods produced at home are relatively cheap in US dollar terms: the currency is undervalued. When UNDERVAL is below unity, the currency is overvalued. See Annex for details. Selected countries included in the chart are OECD or G20 Members.

Source: International Monetary Fund, OECD calculations. See Annex for details.

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Table 28. Pension fund investments, 2005 - 2016

As a % of GDP in USD

bn.

% all funded assets

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p 2016p 2016p Australia 77.9 87.0 106.0 93.3 82.1 89.2 92.3 91.0 101.8 109.2 118.3 120.9 1,486 97.4 Austria 4.6 4.8 4.7 4.3 4.9 5.2 4.8 5.1 5.7 5.8 6.1 6.0 22 .. Belgium 4.3 4.1 4.3 3.2 4.0 3.6 4.1 4.5 5.0 5.7 5.8 5.9 26 .. Canada 56.4 61.4 60.7 49.9 58.7 63.1 61.8 65.5 70.7 75.9 83.3 86.0 1,316 53.6 Chile 55.6 57.5 61.0 49.8 62.0 62.6 58.0 60.1 62.2 68.1 69.5 70.1 174 100.0 Czech Republic 3.8 4.2 4.4 4.8 5.5 5.9 6.1 6.7 7.3 7.9 8.2 8.5 16 100.0 Denmark 32.9 31.6 31.6 45.8 41.7 47.9 48.1 48.2 41.1 47.2 43.9 47.3 138 23.1 Estonia 2.6 3.5 4.4 4.5 6.7 7.3 6.8 8.3 9.4 11.2 12.9 14.8 3 89.3 Finland 65.7 69.0 68.1 58.2 73.5 79.1 42.4 45.4 48.4 50.7 49.3 49.1 111 .. France 0.0 0.0 0.1 0.1 0.2 0.2 0.2 0.3 0.4 0.5 0.6 0.6 14 6.0 Germany 4.1 4.2 4.6 4.6 5.3 5.4 5.5 6.1 6.1 6.7 6.7 6.8 224 .. Greece .. .. 0.0 0.0 0.0 0.0 0.0 0.0 0.5 0.6 0.6 0.7 1 .. Hungary 8.3 9.6 10.8 9.5 13.0 14.6 3.8 3.9 3.9 4.0 4.1 4.3 5 73.8 Iceland 114.3 124.9 123.3 107.9 114.8 121.6 126.3 136.2 141.7 145.4 148.0 144.9 31 94.8 Ireland 45.8 47.4 43.9 33.8 42.5 45.2 41.8 45.8 50.8 55.8 41.9 40.0 112 .. Israel 29.5 29.3 30.4 39.6 43.7 45.5 45.9 48.7 50.0 54.1 53.9 55.7 177 .. Italy 2.7 2.9 3.1 3.3 4.0 4.4 4.7 5.4 6.0 6.6 6.8 7.2 126 78.1 Japan 29.7 29.1 27.8 27.6 29.1 28.2 28.7 29.3 29.5 30.7 30.1 29.4 1,355 100.0 Korea 1.6 2.6 2.7 2.8 3.3 3.7 4.1 4.9 6.0 7.3 8.2 9.9 133 37.0 Latvia 0.4 0.4 0.4 0.4 0.7 0.9 0.8 0.9 1.0 1.2 1.4 1.5 0 12.1 Luxembourg 1.1 1.0 1.0 1.0 2.3 2.0 1.9 2.0 2.1 3.0 2.8 2.9 2 .. Mexico 8.8 10.0 9.9 10.0 11.7 12.6 12.7 14.1 14.7 15.5 15.5 15.6 146 93.6 Netherlands 113.6 116.0 126.0 104.9 110.1 120.4 126.9 144.4 148.3 159.3 171.9 181.8 1,335 .. New Zealand 11.4 12.4 11.5 10.4 11.6 14.0 15.4 16.3 18.6 19.8 22.1 23.7 41 100.0 Norway 6.6 6.6 6.8 5.9 7.2 7.5 7.2 7.4 8.1 8.8 9.7 10.2 37 .. Poland 8.7 11.0 11.9 10.9 13.2 15.4 14.6 16.8 18.3 8.8 7.9 8.3 37 91.1 Portugal 12.0 12.7 12.7 11.3 12.5 11.0 7.5 8.6 8.9 10.1 10.1 9.9 19 93.0 Slovak Republic 0.5 2.4 3.6 4.6 6.2 7.2 8.2 9.4 9.7 10.5 10.2 11.2 10 100.0 Slovenia 1.2 1.6 1.8 1.9 2.5 3.0 3.2 3.6 3.9 4.2 4.3 4.2 2 59.6 Spain 7.1 7.3 8.0 7.0 7.9 7.8 7.8 8.3 9.0 9.7 9.7 9.5 112 68.2 Sweden 8.5 8.7 8.1 6.9 7.8 9.0 8.8 10.1 9.2 9.2 8.8 8.6 41 11.9 Switzerland 106.9 108.4 105.6 90.1 102.0 102.5 101.1 107.9 113.5 120.7 122.1 127.9 817 .. Turkey 0.6 0.7 1.2 1.4 2.2 2.2 3.8 3.4 4.2 4.7 4.6 4.7 34 .. United Kingdom 72.1 76.8 73.9 61.9 74.0 82.0 88.7 95.7 98.1 97.9 98.8 95.3 2,274 .. United States 74.2 76.4 77.3 59.0 69.2 73.8 71.0 73.8 82.2 81.9 79.0 81.0 15,040 59.7 OECD total 44.5 45.3 44.3 36.6 41.4 44.3 44.6 46.8 51.0 53.8 54.2 55.3 25,421 ..

Notes: p: preliminary data; ".." not available. OECD total is calculated for each year as the ratio between all pension fund investments and the GDPs (in US dollar) of all reporting OECD countries. See annex for more country-specific details.

Source: OECD Global Pension Statistics; National Bank of Belgium; French Asset Management Association; Bank of Japan; Bank of Korea; Reserve Bank of New Zealand and Willis Towers Watson "Global Pension Assets Study 2017".

OECD pension fund assets grew faster than GDP in 2016

Pension fund assets grew faster than domestic economies in 25 out of the 35 OECD countries in 2016. Pension fund investments exceeded 100% of GDP in 2016 in four countries: Australia, Iceland, the Netherlands and Switzerland. OECD pension fund investments were worth more than USD 25.4 trillion in 2016, peaking at 55.3% of the GDP of the OECD area. The overall assets accumulated for retirement were even larger, as individuals can save in retirement products offered and managed by other institutions than pension funds, such as life insurance companies (e.g. Denmark, France and Sweden).

55

Figure 28. Pension funds' annual real net rates of investment return in selected OECD countries, 2016

Notes: All data are expressed in per cent. The weighted average is calculated using as weights for each country the amount of pension fund investments. See annex for explanations of the calculation method and country-specific details. Source: OECD Global Pension Statistics; Pensions & Investments (Japan).

8.37.8

7.2

4.9 4.84.3 4.0 4.0 3.7

2.8 2.8 2.7 2.7 2.6 2.3 2.3 2.2 1.9 1.9 1.5 1.0 1.0 0.9 0.9 0.5 0.0

-0.4-1.2-2

0

2

4

6

8

10%

Pension funds exhibited positive real investment rates of return in most markets in 2016

Pension funds exhibited positive real investment rates of return (net of investment expenses) in most OECD countries (23 out of the 26 reporting). Pension funds achieved the highest returns in 2016 in Poland (8.3%), followed by Denmark (7.8%) and the Netherlands (7.2%). Real investment rates of return of pension funds were close to 5% in Sweden (4.9%) and Hungary (4.8%). Ten further countries exhibited real returns higher than 2% in 2016, including some of the largest pension markets in terms of assets (i.e. Canada, Japan and the United States). As a result, the OECD weighted average real return was above 2%. By contrast, preliminary estimates suggest that the Czech Republic, Iceland and Mexico did not achieve positive real rates of return on pension fund investments in 2016.

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Table 29. Pension funds' annual real net rates of investment return in selected OECD countries, 2005-2016

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016p

Australia 10.1 8.9 12.9 -11.4 -10.2 5.6 5.3 0.6 10.3 8.9 6.4 1.9 Austria 9.0 3.8 -1.8 -14.4 7.3 3.7 -6.0 5.5 2.9 6.2 1.2 2.8 Belgium 10.3 10.3 7.7 -22.3 13.4 4.4 -4.6 9.2 5.8 10.7 2.6 .. Canada 10.7 10.8 1.0 -16.9 10.3 7.6 1.8 7.9 9.8 7.8 5.1 3.7 Chile 5.0 14.4 4.4 -24.1 22.0 8.3 -6.0 5.1 3.5 8.1 1.5 1.5 Czech Republic 2.7 1.3 -2.0 -1.5 -0.6 0.7 0.5 0.2 0.2 1.2 0.9 -1.2 Denmark 14.7 1.4 -3.3 5.1 1.2 7.1 12.2 5.3 -4.5 16.6 0.8 7.8 Estonia 7.2 2.2 -5.4 -32.4 17.0 3.6 -8.0 5.2 1.6 5.0 2.9 1.0 Finland .. .. .. .. .. .. .. 5.2 6.0 6.2 5.3 4.0 Germany 3.4 3.2 1.0 0.5 3.9 3.6 1.0 2.7 2.8 4.4 3.1 .. Greece .. .. .. 2.3 0.3 -7.8 -5.6 5.0 .. 6.5 4.7 4.3 Hungary 7.6 1.2 -3.9 -21.7 12.8 4.2 .. 7.8 7.0 9.6 3.7 4.8 Iceland 12.0 9.0 0.5 -23.2 0.8 1.2 2.1 6.9 4.8 7.1 7.4 0.0 Ireland .. .. -7.3 -35.7 .. .. .. .. .. .. 4.5 .. Israel 7.1 5.7 3.5 -16.3 20.1 7.0 -4.3 7.8 8.4 5.8 4.3 4.0 Italy 4.8 2.1 0.3 -5.3 5.3 1.2 -2.8 4.0 3.9 5.7 1.7 2.2 Japan .. .. .. .. .. .. .. .. .. .. .. 2.3 Korea 0.6 6.0 0.6 -2.7 -2.2 2.1 0.0 3.3 2.6 2.3 1.5 .. Latvia 1.7 -1.9 -8.9 -19.5 12.2 5.3 -6.5 7.0 3.2 4.9 1.6 0.9 Luxembourg .. 4.9 -2.5 -11.4 6.5 0.7 -2.3 6.0 1.7 8.3 0.6 .. Mexico 4.8 5.6 -0.1 -7.8 7.5 6.6 1.2 9.7 -1.5 4.7 -0.8 -0.4 Netherlands 10.9 6.8 0.6 -17.3 11.5 8.9 4.3 9.5 1.6 15.1 0.9 7.2 New Zealand 4.3 8.8 5.0 -5.5 -9.5 10.5 3.1 1.6 9.5 7.2 .. .. Norway 9.2 7.4 3.1 -10.6 9.7 5.5 -0.1 6.0 7.9 5.1 1.9 2.7 Poland 12.9 13.4 1.5 -17.3 8.9 7.2 -9.1 1.6 2.7 .. -6.1 8.3 Portugal 7.1 7.1 5.5 -13.2 11.6 -3.0 -7.3 5.8 4.9 6.9 2.1 0.5 Slovak Republic .. .. -0.1 -8.9 1.0 0.0 -3.8 0.4 1.1 3.9 0.8 2.6 Slovenia .. .. -1.1 -5.4 4.2 1.8 -1.8 4.5 2.5 6.7 2.4 1.9 Spain .. .. .. -9.9 6.9 -2.2 -2.3 3.7 7.9 8.0 2.0 1.0 Sweden .. .. .. .. .. .. -1.0 7.9 6.7 10.6 2.7 4.9 Switzerland 9.2 5.3 0.2 -13.8 9.9 2.8 0.6 7.5 5.9 7.2 2.1 .. Turkey 22.1 1.4 13.2 0.9 17.6 1.9 -10.4 9.6 -7.6 5.6 -6.1 0.9 United Kingdom 19.8 10.3 0.9 -15.9 13.4 11.2 8.3 9.0 5.4 5.2 4.7 .. United States 1.6 5.7 -1.2 -25.3 9.3 5.8 -3.9 5.2 11.2 3.6 -1.1 2.3

Notes: All data are expressed in per cent. p: preliminary data. ".." not available. See annex for explanations of the calculation method and country-specific details. Source: OECD Global Pension Statistics; Pensions & Investments (Japan).

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Table 30. Pension fund asset allocation in selected asset classes in selected OECD countries, 2005-2016

2005 2016p

Shares Bills and bonds

Cash and deposits Other Shares Bills and

bonds Cash and deposits Other

Australia 48.7 9.3 9.8 32.2 51.1 10.2 16.7 22.1 Austria 37.0 53.2 3.5 6.3 33.5 45.7 8.9 11.9 Belgium 36.3 25.2 9.7 28.8 41.8 43.9 4.4 9.9 Canada 39.7 33.4 4.6 22.4 27.8 35.0 4.5 32.7 Chile 40.0 53.4 0.4 6.3 33.6 65.6 0.3 0.5 Czech Republic 6.1 81.5 8.3 4.1 0.4 90.7 8.3 0.6 Denmark 29.2 56.5 0.8 13.5 17.1 62.2 0.2 20.5 Estonia 37.4 54.6 6.0 2.0 33.8 42.6 23.3 0.3 Finland .. .. .. .. 39.6 35.1 2.7 22.6 Germany 12.0 45.7 3.8 38.5 5.8 50.8 4.0 39.4 Greece .. .. .. .. 9.8 81.5 5.9 2.8 Hungary 8.6 83.0 1.5 6.9 10.2 81.7 5.6 2.5 Iceland 35.2 44.7 3.0 17.1 33.4 50.0 4.9 11.7 Israel 4.2 89.1 1.4 5.2 7.6 70.4 6.3 15.7 Italy 15.7 40.8 4.7 38.9 20.5 49.0 4.2 26.4 Japan 24.3 28.5 5.0 42.1 9.5 32.3 7.5 50.8 Latvia .. .. .. .. 23.1 61.0 11.9 3.9 Luxembourg .. .. .. .. 23.3 66.1 2.7 7.8 Mexico 1.3 96.5 0.0 2.2 17.6 79.8 0.6 2.0 Netherlands 46.2 40.8 2.3 10.7 39.2 44.7 1.8 14.4 Norway 28.9 55.4 4.9 10.9 36.0 56.0 2.3 5.7 Poland 32.0 63.4 4.1 0.4 82.9 8.8 7.3 1.0 Portugal 26.6 50.7 12.5 10.2 19.8 54.8 6.5 18.9 Slovak Republic 8.6 44.3 43.1 4.0 2.6 79.9 12.4 5.1 Slovenia 3.2 82.6 14.1 0.1 1.2 75.7 22.8 0.4 Spain 21.4 63.6 5.0 10.0 13.6 63.9 14.9 7.6 Sweden 34.4 57.7 1.4 6.5 18.3 66.7 2.2 12.8 Switzerland 24.6 37.2 11.5 26.7 29.7 32.7 5.6 32.0 Turkey 11.1 81.1 0.0 7.8 11.9 54.1 8.4 25.7 United Kingdom 47.7 22.7 2.6 27.0 21.7 42.9 4.1 31.3 United States 54.5 31.6 1.3 12.7 44.7 36.8 1.0 17.5

Notes: All data are expressed in per cent of total investment. p: preliminary data. ".." not available. See annex for more methodological notes and country-specific details.

Source: OECD Global Pension Statistics; Australian Bureau of Statistics; Bank of Japan.

Pension funds are more exposed to equities in 2016 than in 2005 in one third of reporting countries

Pension funds have a larger share of their portfolio allocated to equities in 2016 compared to 2005 in 10 of the 27 reporting OECD countries. The largest change occurred in Poland where pension funds held almost 83% of their portfolio in equities in 2016 compared to 32% in 2005, as a result of a pension reform in 2014 preventing open pension funds from investing in treasury bonds and state-backed bonds and requiring a minimum share of the portfolio to be invested in equities instead. Australia is the only other OECD country where investment in equities increased and accounted for more than 50% of pension funds’ portfolio in 2016. Against a backdrop of prolonged low interest rates, defined benefit pension funds in Switzerland also increased their investment in equities (and other assets) while they reduced their exposure to bills and bonds. In most countries, bills and bonds remain, however, the main asset classes in which pension funds invest. In more than half of the reporting countries, pension funds held more than 50% in bills and bonds at the end of 2016, especially in Central and Eastern European countries (e.g. Czech Republic, Hungary, Slovak Republic) and Latin American countries (e.g. Chile, Mexico).

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ANNEX: Methodology for data collection and analysis

Country classification

The Scoreboard follows the IMF country classification, which takes into account multiple criteria, including per capita income level, export diversification, and degree of integration into the global financial system.

Advanced economies (composed of 39 countries): Australia, Austria, Belgium, Canada, Cyprus1, Czech

Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hong Kong (China), Iceland, Ireland, Israel, Italy, Japan, Korea, Latvia, Lithuania, Luxembourg, Macao SAR, Malta, Netherlands, New Zealand, Norway, Portugal, Puerto Rico, San Marino, Singapore, Slovak Republic, Slovenia, Spain, Sweden, Switzerland, Chinese Taipei, United Kingdom, and United States.

Emerging markets and developing economies (composed of 152 countries): Afghanistan, Albania,

Algeria, Angola, Antigua and Barbuda, Argentina, Armenia, Azerbaijan, The Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei Darussalam, Bulgaria, Burkina Faso, Burundi, Cabo Verde, Cambodia, Cameroon, Central African Republic, Chad, Chile, China (People’s Republic of), Colombia, Comoros, Democratic Republic of the Congo, Republic of Congo, Costa Rica, Côte d'Ivoire, Croatia, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Ethiopia, Fiji, FYR Macedonia, Gabon, The Gambia, Georgia, Ghana, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, India, Indonesia, Iran, Iraq, Jamaica, Jordan, Kazakhstan, Kenya, Kiribati, Kosovo, Kuwait, Kyrgyz Republic, Lao P.D.R., Lebanon, Lesotho, Liberia, Libya, Madagascar, Malawi, Malaysia, Maldives, Mali, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nepal, Nicaragua, Niger, Nigeria, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Qatar, Romania, Russia, Rwanda, Samoa, São Tomé and Príncipe, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Solomon Islands, South Africa, South Sudan, Sri Lanka, St. Kitts and Nevis, St. Lucia, St. Vincent and the Grenadines, Sudan, Suriname, Swaziland, Syria, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Tuvalu, Uganda, Ukraine, United Arab Emirates, Uruguay, Uzbekistan, Vanuatu, Venezuela, Viet Nam, Yemen, Zambia, and Zimbabwe.

Non-financial company data and sample description

Company data are based on the Bloomberg World Equity Index (BWEI). The sample includes all companies which have been listed in the BWEI over the period 2002-2016. 10 098 listed companies in 76 countries were selected (i.e. 6 506 in advanced economies and 4 592 in emerging economies according to IMF

1 Footnote by Turkey:

The information in this document with reference to “Cyprus” relates to the southern part of the Island. There is no single authority representing both Turkish and Greek Cypriot people on the Island. Turkey recognizes the Turkish Republic of Northern Cyprus (TRNC). Until a lasting and equitable solution is found within the context of United Nations, Turkey shall preserve its position concerning the “Cyprus” issue.

Footnote by all the European Union Member States of the OECD and the European Union:

The Republic of Cyprus is recognized by all members of the United Nations with the exception of Turkey. The information in this document relates to the area under the effective control of the Government of the Republic of Cyprus.

59

country group classification) operating in 9 GICS industry sectors. Annual consolidated financial statements are collected on an annual basis, at the firm level and in current USD.2 The current primary source of this information is Bloomberg and some data are extracted from Thomson Reuters. All variables are trimmed at the 1st and 99th percentile levels to reduce the effect of outliers.

To examine the financial characteristics of firms, the following financial variables are considered and are defined as follows:

• Value added: sum of personnel expenses and EBITDA (income before interest, taxes, depreciation and amortisation).

• Number of employees: number of people employed by the company, based on the number of full time equivalents. If unavailable, then the number of full time employees is used, excluding part-time employees.

• Net sales: represent gross sales and other operating revenues less discounts, returns and allowances.

• International sales: represent the sales generated from operations in foreign countries. It excludes export sales, excise taxes, windfall profit taxes, value added taxes, general and services taxes.

• Capital expenditure: represent the funds used to acquire fixed assets other than those associated with acquisitions.

• Free cash flow: a measure of financial performance calculated as operating cash flow minus capital expenditures. It represents the cash that a company is able to generate after laying out the money required to maintain or expand its asset base.

• Dividends and buybacks: represent the total cash common dividends paid on the company's common stock during the fiscal year and the repurchase of outstanding common shares by a company.

• Research and development (R&D) expenditure: represents all direct and indirect costs related to the creation and development of new processes, techniques, applications and products with commercial possibilities.

• Intangible assets: represent other assets not having a physical existence. The value of these assets lies in their expected future return. It includes but is not restricted to: goodwill/cost in excess of net assets purchased, patents, copyrights, trademarks, formulae, franchises of no specific duration, capitalized software development costs/computer programs, organizational costs, customer lists, licenses of no specific duration, capitalized advertising cost, mastheads (newspapers), capitalized servicing rights, and purchased servicing rights.

• Cash and near cash items: represent the money available for use in the normal operations of the company. It is the most liquid of all of the company's assets. It includes but is not restricted to: cash on hand, un-deposited checks, cash in banks, checks in transit, cash in escrow, restricted cash, money orders, letters of credit, demand deposits (non-interest bearing), mortgage bond proceeds held in escrow, drafts, post office checking/GIRO accounts, post office savings accounts, central bank deposits, bullion, bullion in transit, cashier checks and credit card sales.

• Foreign assets: total or identifiable assets of foreign operations before adjustments and eliminations.

2 Bloomberg provides the option to collect the information in current USD values. Bloomberg for example, reports items

on the balance sheet using the exchange rate set on the date of publishing; income statements and statements of cash flow items are reported using the average exchange rate for the period. Thomson Reuters on the other hand uses the WMR Spot Rate set on the date of publishing for items on the balance sheet, income statement and statement of cash flows.

60

• Total assets: represent sum of total current assets, long-term receivables, investment in unconsolidated subsidiaries, other investments, net property plant and equipment and other assets.

• Market capitalisation: represents the company’s worth by multiplying the shares outstanding by the price per share.

• Leverage ratio: is defined as total long-term borrowings divided by the sum of long-term borrowing and equity capital. Long-term borrowing includes all interest-bearing financial obligations that are not due within a year. It may also include shares issued by subsidiaries if the group has an obligation to transfer economic benefits in connection with these shares. Equity capital is share capital, plus retained earnings and minus treasury stock.

• Return on equity (ROE): is calculated as the ratio of net income to common equity. Net income is the profit after all expenses have been deducted. Common equity is the amount that all common shareholders have invested in a company.

• Profit margin: is calculated as the ratio of operating income to total revenues (which also corresponds to net sales).

• Cost of equity (COE): sum of dividend yield, buyback yield and underlying trend in earnings per share growth.

• Cost of debt (COD): is the after-tax weighted average cost of debt for the security, calculated using government bonds rates, a debt adjustment factor, the proportions of short and long-term debt to total debt, and the stock’s effective tax rate.

• Cost of capital (COK): is the weighted average (by the share of equity and debt in total assets, respectively) cost of equity and cost of debt.

• Value of completed M&A deals: represents the declared amount effectively paid by the acquirer company for the target company.

Corporate bonds

Primary corporate bond market data are based on original OECD calculations using data obtained from Thomson Reuters ThomsonOne New Issues Database, an international deal-level database on new issues of corporate bonds. The database provides a detailed set of information for each corporate bond issue, including the identity, nationality and sector of the issuer; the type, interest rate structure, maturity date and rating category of the bond, the amount of and use of proceeds obtained from the issue.

Prior to any exclusion, the database covers 273 158 observations in the period from January 2000 to December 2016. From this initial set, the deals that were registered but were not consummated (30 219), sukuk bonds (3 252) convertible bonds (18 189), preferred shares (2 950) and bonds with an original maturity less than 1 year (21 458) or an issue size less than USD 1 million (1 117) have been excluded. After eliminating observations with improper or missing fields (1 836), the dataset covers 194 137 bond issues from 108 countries. When tranches under the same bond package are counted as a single issue, this figure reduces to 165 9914.

Outstanding amounts are calculated based on annual net issuance amounts. Actual call date data obtained from Bloomberg were used on net issuance calculations. Outstanding amount are at current prices.

Given that a significant portion of bonds are issued internationally, it is not possible to assign such issues to a certain country of issue. For this reason, the country breakdown was carried out based on the domicile country of the issuer. Issuance amounts are expressed in 2016 USD adjusted by US CPI.

Rating index

For each bond that has rating information in the corporate bond dataset, developed based on data from Thomson Reuters and Bloomberg, a value of 1 to the lowest credit quality rating (C) and 21 to the highest credit quality rating (AAA for S&P and Fitch and Aaa for Moody’s) is assigned. There are eleven non-

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investment grade categories: five from C, C to CCC+; and six from B, B- to BB+. There are ten investment grade categories: three from B, BBB- to BBB+; and seven from A, A- to AAA. This index is weighted as one for C, two for CC and rising to twenty one for AAA. A fall in the index indicates declining quality.

Public equity

Initial public offering (IPO) and secondary public offering (SPO) data are based on original OECD calculations using data obtained from Thomson Reuters ThomsonOne New Issues Database. Data exclude Real Estate Investment Trusts (REITs), closed-investment funds, over-the-counter (OTC) markets and unit/trust offerings.

The IPOs of companies that were listed in an organised market after the IPO but currently traded in OTC markets are included. SPO covers all share issues of listed companies after an IPO. The country breakdown was carried out based on the domicile country of the issuer. Issuance amounts are expressed in 2016 USD adjusted by US CPI.

Industry classification for corporate bond and public equity data

The data on corporate bonds and public equity follow Thomson Reuters’ industry classification. The main categories and their subcategories are the following:

• Consumer products and services: Educational services, employment services, home furnishings, legal services, travel services, professional services, and others.

• Consumer Staples: Agriculture and livestock, food and beverage, household & personal products, textiles & apparel, tobacco, and others.

• Energy: Oil & gas, petrochemicals, pipelines, power, water and waste management, alternative energy sources, and others.

• Healthcare: Pharmaceuticals, biotechnology, healthcare equipment & supplies, healthcare providers & services, hospitals, and others.

• High technology: Computers & peripherals, e-commerce / B2B, electronics, IT consulting & services, internet software & services, semiconductors, software, and others.

• Industrials: Aerospace & defence, automobiles & components, building/construction & engineering, industrial conglomerates, machinery, transportation & infrastructure and others.

• Materials: Chemicals, construction materials, containers & packaging, metals & mining, paper & forest products, and others.

• Media and entertainment: Broadcasting, cable, publishing, recreation & leisure, advertising and marketing, hotels and lodging, motion pictures & audio visual, casinos & gaming and others.

• Real estate: Non-residential, residential, REITs, real estate management & development, and others.

• Retail: Food & beverage retailing, discount and department store retailing, apparel retailing, computers & electronics retailing, internet and catalog retailing, automotive retailing, home improvement retailing and others.

• Telecommunications: Space & satellite, telecommunications equipment, telecommunications services, wireless, and others.

Distance-to-default

The distance-to-default indicator , is a measure of corporate default. It represents the expected difference between the assets value of the firm relative to the default barrier, after correcting and normalizing for the volatility of the assets. To derive the measure, it is assumed that a bank defaults (or is bankrupt) when the market value of assets equals (or is lower) than the book value of debt ( = ). The formula to calculate

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the distance-to-default is derived from the option pricing model of Black and Scholes (1973) and implicitly assumes that returns distribute normal. The distance-to-default ( − )periods ahead , , formula is as follows:

, = log + , − 2 . ( − )( − )

where: : Market value of bank’s asset at time t, , : Risk-free interest rate, : Book value of the debt at time t, : Volatility of bank’s asset at time t,

: Maturity of the debt.

However, the market value of assets (Vt) and its volatility ( ) have to be estimated. Equity-holders have the residual claim on a firm’s assets and have limited liability. As first realised by Merton (1977), equity can be modelled as a call option on the underlying assets of the bank, with a strike price equal to the total book value of the bank’s debt. Thus, option-pricing theory can be used to derive the market value and volatility of bank’s underlying assets from equity’s market value ( ) and the equity’s volatility ( , ), by solving: = + , ( ) ( 2)( 1) = ,( 1)

where:

1 = log + , + 2 . ( − )( − ) 2 = 1 − ( − )

: Value of bank’s equity, N: The cumulative normal distribution,

: Equity’s volatility.

DTD represents the number of standard deviations away from the default point. A bank defaults (or is bankrupt) when , approaches zero or becomes negative. For the estimations the used data are extracted from Bloomberg. The total annual debt liabilities (i.e., the difference of the annual total assets and annual total equity) is interpolated using a cubic spline to yield daily observations ( ). The volatility of equity ( , )is the standard deviation of daily return multiplied by √252 (i.e., 252 trading days by year). The expiration date of the option ( − ) equals the maturity of the debt and it is assumed to be 1 in accordance with the common practice. The risk free interest rate ( , )is the 12 months interbank rate.

Conditional volatility of covered interest parity

The 1-year average conditional volatility of Covered Interest Parity (CIP) is measured as the conditional standard deviation calculated using a GARCH ( , ) model. If CIP is denoted generically yt, a time-series model that captures the autoregressive structure in both the mean and the variance can be written as: = + +⋯+ + ℎ ~ (0, )

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= + +

Where ∑ is the ARCH term (the squared error term in the previous time period) of q order, generally being news about volatility from the previous period; ∑ is the GARCH term (the conditional variance in the previous time period) of p order. Thus, yt follows an (ℎ) process with a conditional variance equation described by a ( , )process. The GARCH model is implemented via maximum likelihood estimation of the log-likelihood function. The estimated conditional variance will give us an indication of the evolution of capital mobility. In this Scoreboard, (1,1) model is adopted, which is sufficient to capture the dynamics of the conditional variance of yt. The properties of the dataset are examined before the analysis of the empirical results. Augmented Dickey–Fuller and Phillips−Perron (PP) tests are used to check the stationarity of the times series. CIP time series are driven by an (1) process. It is also identified that the estimated coefficients are significant and all the diagnostic statistics are reasonable.

Along with interest parities, the conditional variance of CIPs might be a measure of dynamic capital mobility. With greater capital mobility, not only covered differential rates but also the variance would decline over time. CIP is calculated using deliverable and non-deliverable forward rates. The greater the volatility, the more CIP is deviating from the 0 equilibrium. This phenomenon is observed in countries with strong capital control measures.

The savings investment correlation

The analysis on savings-investment correlation is based on “Integration versus Interdependence and Complexity in Global Trade and Finance in the Post-War Period” (Blundell-Wignall, A., Atkinson, P., Roulet, C., 2013, in 50 Years of Money and Finance: Lessons and Challenges, Edited by M. Balling, Larcier Edition, Chapter 6: 195-228).

Countries which open up to foreign private participation in domestic investment opportunities for technology transfer, synergies in the global supply chain, or resources development reasons will see − correlations decline over time as this opening up occurs. Countries that are not open, or which are excessively selective in their openness, should see higher more stable − correlations.

To explore this proposition, revised and internationally consistent quarterly data for a constant sample of 43 countries’ savings and investment from 1977 are compiled. Panel regressions are run for the OECD countries as a group, advanced economies, emerging economies and BRICS countries. To explore the changing degree of openness, the following empirical model is estimated, where the subscripts i and t denote the country and the period, respectively: , = , + , + ,

where GFCF , is national gross capital formation and , is national gross saving. Both variables are expressed in per cent of national gross domestic product. corresponds to the coefficient of openness. This equation is estimated using ordinary least squares (OLS). From 1977, the panel regressions are run in 5-years rolling sample time period format.

Exchange rate valuation measure

The overvaluation and undervaluation exchange rate measure is derived from the Rodrik (2008)3 model. It is an exchange rate measure based on domestic price level adjusted for the Balassa-Samuelson effect. The advantage of this index is that it is comparable across countries as well as over time. This index is computed in three steps using IMF data including 179 countries over the period 1990-2015. First, exchange rate data are

3 Rodrik, D. (2008), “The Real Exchange Rate and Economic Growth”, Brookings Papers on Economic Activity, Fall.

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extracted from the International Financial Statistics database. Power parity conversion factors ( ) are extracted from IMF World Economic Outlook database. The “real” exchange rate ( ) is calculated as follows: ln , = ln( , , )

Where indexes countries4 and indexes five-year time periods. , and , are expressed as national currency units per US dollar. Values of greater than one indicate that the value of the currency is lower (more depreciated) than indicated by purchasing power parity. However, in practice non-tradable goods are also cheaper in poorer countries (through the Balassa-Samuelson effect), which requires an adjustment. To account for this effect, in the second step, five year averaged is regressed on five year averaged real GDP per capita ( ), taken from IMF World Economic Outlook database. ln , = + ln , + + , (1)

where ft is a fixed effect for time period and t is the error term. This regression yields an estimate of of −0.18 (with a very high statistic of around -12), suggesting a strong and precisely estimated Balassa-Samuelson effect: when incomes rise by 10 percent, the real exchange rate falls (appreciates) by around 1.8 percent. Finally, the undervaluation index ( ) is derived from the difference between the actual real exchange rate and the Balassa-Samuelson-adjusted rate. ln , = ln , − ln ,

where ln , is the predicted value from equation 1. Whenever exceeds unity, it indicates that the exchange rate is set such that goods produced at home are relatively cheap in US dollar terms: the currency is undervalued. When is below unity, the currency is overvalued.

Global trends in FDI Flows

OECD, EU, World, G20 aggregates: FDI outward and inward flows for these aggregates were compiled using directional figures when available. Missing quarterly directional figures were approximated using the ratio between annual asset liability and directional figures; or by distributing annual directional figures equally among the four quarters; or using unrevised historical data. When directional figures were not available and could not be approximated, asset liability figures were used.

Resident SPEs from Austria, Belgium, Chile, Denmark, Hungary, Iceland, Luxembourg, Mexico, the

Netherlands, Norway, Poland, Portugal, Spain and Sweden are excluded. The European Union aggregate corresponds to member country composition of the reporting period:

EU15 for data up to and including 2003, EU25 for data between 2004 and 2006, EU27 for data between 2007 and 2012 and EU28 starting from 2013.

World aggregate: World totals for FDI flows are based on available data at the time of update as reported

to the OECD and IMF. Missing data for countries for Q3 2016 and Q4 2016 were estimated using the overall growth rate observed between, respectively, Q2 2016 and Q3 2016 and Q3 2016 and Q4 2016. Growth rates were calculated from data for OECD countries, for non-OECD G20 countries, and for 50 non-OECD and non-G20 countries in Q3 and 15 non-OECD and non-G20 countries in Q4.

4 Data for euro-area members are not available after 1999. Hence, aggregate data for euro-area are considered in the

regressions instead of individual country data over the period 1980-2015. Missing exchange rate data before 1999 are replaced by data for Germany. PPP conversion factor data are average PPP conversion factors of the 1999 Euro area members. Real gross domestic product per capita is the ratio of the sum of real gross domestic product per capita of Euro-area member states to total population in the euro-area.

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World totals for FDI positions are based on available FDI data at the time of update as reported to OECD and IMF for the year ended or the latest available year.

By definition, inward and outward FDI worldwide should be equal. However, in practice, there are

statistical discrepancies between inward and outward FDI. More information on measurement, methodologies, and analysis of FDI statistics is available at:

http://www.oecd.org/investment/statistics.htm. Pension fund investments

Data for Australia refer to June of each year. Data for 2016 for Belgium come from the National Bank of

Belgium and refer to financial assets of pension funds. Investments of Canada's pension funds for 2016 refer to the end of September 2016. Data on pension funds in Estonia only refer to the mandatory funded pension system. The break in series in 2011 for Finland is due to the exclusion of public buffer funds while they were included before 2011. Data for investments of PERCO (Collective retirement savings plan) in France in 2016 come from the French Asset Management Association and refer to June 2016. Data for Germany only refer to Pensionskassen and Pensionsfonds. There is a break in series in 2013 in Greece, as four new occupational funds were converted in March 2013 from a public redistributing system (PAYG) into a private law capital-accumulating system. The drop in Hungarian pension fund investments in 2011 comes from a pension reform suspending payments to the mandatory funded individual schemes and redirecting all the contributions to the pay-as-you-go public pension schemes, unless workers chose to keep these individual schemes by the end of January 2011. Data for Israel refer to old, new and general pension funds. Data for Japan come from Bank of Japan. The value of pension fund investments in 2016 for Korea comes from Bank of Korea. Data on pension funds for Latvia only refer to open and closed private pension funds. Data for Mexico cover occupational plans (2015 data) and personal plans (2016 data). Data for New Zealand refer to the end of March of each year and come from the website of the Reserve Bank of New Zealand for 2016. For Poland, the drop in pension fund investments in 2014 comes from the reversal of the mandatory funded pension system that led to a transfer of domestic sovereign bonds held by open pension funds into the social security system. Data on pension funds in Slovenia only refer to mutual pension funds under the supervision of the Securities Market Agency. The main part of the Swedish funded pension market is secured via insurance contracts. Data for 2016 for Switzerland are estimates coming from Willis Towers Watson "Global Pension Assets Study 2017".

The share of pension fund investments in the overall funded pension system was calculated using

sometimes 2015 values for some vehicles as in the case of Canada, Hungary, Italy, Korea, Poland, Portugal and Sweden. Pension funds' annual real net rates of investment return

Methods for calculating the average investment rates of return ( ) of pension funds vary greatly from country to country, hindering international comparability of these statistics. With a view to increasing data comparability across countries, the OECD and its Working Party on Private Pensions therefore decided that it would be worth applying the same calculation method for across countries, which would be calculated by the OECD, using variables already collected as part of the Global Pension Statistics’ framework. In order to reach a consensus on the most appropriate formula for the calculation, an electronic discussion group was created, composed of selected country experts.

Drawing on preliminary consultations, the OECD Secretariat proposed five formulas to the electronic

discussion group for comments. A consensus was reached within the group and subsequently endorsed by the OECD Task Force on Pension Statistics on the following formula for the average , in each year t:

= ( + )/2 . 100

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Net investment income comprises income from investments, value re-adjustments on investments and income from realised and unrealised capital gains and losses. It includes rents receivable, interest income, dividends and realised and unrealised capital gains, before tax and after investment expenses.

Real in this Scoreboard have been calculated using this common formula for the average nominal net investment return (ratio between the net investment income at the end of the year and the average level of assets during the year) for all the countries, except for Austria (2011-2012, 2016), Finland (2015-2016), Iceland (2016), Ireland (all years), Israel (all years), Italy (2016), Korea (2010-2015), Slovak Republic (2016), Sweden (all years), Turkey (2011, 2013-2014) and the United States (all years) for which values have been provided by the countries or come from national official publications.

Pension funds' real net investment rates of return of the year are calculated over the period December N-1 - December N for all the other countries, except for Australia ( − ), Canada in 2016 ( 2015 - 2016) and New Zealand ( ℎ − ℎ ).

There is a break in series in 2011 for Finland which is due to the exclusion of public buffer funds which

were included before. Data for Germany only refer to Pensionskassen and Pensionsfonds. There is a break in series in 2013 for Greece coming from the inclusion of four new occupational pension funds which were operating on a pay-as-you-go basis previously. The break in series in 2011 in Hungary relates to the pension reform leading to a decrease in the assets of mandatory pension funds in 2011. Data for Israel refer to new pension funds only. Investment returns for pension funds in Italy are net of taxes. Data for 2016 for Italy only refer to contractual pension funds. Data for Mexico and Turkey refer to personal pension plans only. There is a break in series for Poland in 2014 due to the reversal of the mandatory funded pension system that led to a transfer of domestic sovereign bonds held by open pension funds into the social security system. Pension fund asset allocation

The OECD Global Pension Statistics database provides information about investments in Collective Investment Schemes and the look-through of Collective Investment Schemes' investments in cash and deposits, bills and bonds, shares and other. When the look-through was not provided by the countries, estimates were made assuming that collective investment schemes’ allocation in bills and bonds, shares and other was the same as pension funds' direct investments in these categories. Therefore, pension fund asset allocation data in this Scoreboard include both direct investment in shares, bills and bonds and indirect investment through Collective Investment Schemes. The "Other" category includes cash and deposits, loans, land and buildings, unallocated insurance contracts, hedge funds, private equity funds, structured products, other mutual funds (i.e. not invested in bills and bonds, or shares) and other investments.

Data refer to 2006 (instead of 2005) for the Slovak Republic. Data refer to 2015 (instead of 2016) for

Belgium, Israel, Sweden and Switzerland. Data for 2016 for Canada refer to September 2016. Data for Australia come from the Australian Bureau of Statistics and refer to the end of June of each year.

The breakdown of investments by collective investment schemes into cash and deposits, bills and bonds,

equities and others for 2005 was supposed to be the same as in 2008 for Chile and 2011 for Italy (OECD estimations). Data for Germany refer to Pensionsfonds and Pensionskassen, and are preliminary estimates as the requested breakdown was not available for Pensionsfonds and the breakdown of investments of collective investment schemes has not been approved by external auditors yet for 2016. Data for Japan come from Bank of Japan and exclude claims of pension funds on pension managers. The high value for the “Other” category in Japan is mainly driven by outward investments in securities. Data for Mexico and Turkey refer only to personal pension plans.

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oecd business and finance scoreboard 2017...the 2017 edition of the oecd business and finance...

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