GLOBAL The Global Macro Outlook -...

Please refer to page 77 for important disclosures and analyst certification, or on our website

www.macquarie.com/research/disclosures.

GLOBAL

Key forecasts, changes this month

1) Tables for real GDP growth, CPI, interest

rates, currencies and commodity prices

are on pages 9-11. Online access to our

global macro forecasts is available on

request.

2) The cycle rolls: we forecast 2018 and 2019

global real GDP growth (2.7% and 2.6%

respectively) to slow versus 2017 (2.9%)

3) 2018 4Q on 4Q forecast real GDP growth

for the US has been cut to 1.8% from 1.9%

4) 2018 forecast real GDP growth for the

Eurozone has been increased to 1.7%

YoY from 1.6% YoY

Analyst(s) Macquarie Capital Securities (Japan) Limited Peter Eadon-Clarke +81 3 3512 7850 [email protected] Nara Song +81 3 3512 7878 [email protected] Macquarie Capital Markets Canada Ltd. David Doyle, CFA +1 416 848 3663 [email protected] Macquarie Securities (Australia) Limited James McIntyre, CFA +61 2 8232 8930 [email protected] Macquarie Capital Limited Larry Hu, PhD +852 3922 3778 [email protected] Macquarie Equities South Africa (Pty) Ltd Elna Moolman +27 11 583 2570 [email protected] Macquarie Capital (Europe) Limited Matthew Turner +44 20 3037 4340 [email protected] Colin Hamilton +44 20 3037 4061 [email protected]

16 May 2017

The Global Macro Outlook Beyond the cycle The cold bath: With the high-frequency manufacturing sector data rolling over,

page 2, we believe it is time to focus back on two underlying trends: weak labour

force growth in the leading economies and financial repression for decades. We

forecast moderate trend growth and low real and nominal bond yields globally.

The cycle rolls: we forecast 2018 and 2019 global real GDP growth (2.7% and

2.6% respectively) to slow versus 2017 (2.9%).

Labour force growth: The US is better positioned than Europe, Japan and even

China. Nonetheless, even assuming an aggressive rebound in the core working

age (25-54 year old) participation rate, just ~120,000 jobs per month will be

necessary to keep US unemployment stable in 2017. This pace decelerates to

just ~45,000K jobs per month in 2020. The aging demographic profile means

underlying US labour force growth is likely to be just ~0.4% long-term.

For the US, the above combined with recent trends in productivity growth of

~1.0% pa, that demographic forces suggest will continue, leads to our estimate

for US real potential output growth of just 1.4% pa.

Eurozone: private nonfinancial credit growth vs nominal GDP growth

Source: FRB of St. Louis, Datastream, Macquarie Research, May 2017

The private non-financial sector (households, corporates) in the Eurozone is

healing, chart above. This allows policy to shift to fiscal reconstruction.

Financial repression reflects a conscious policy choice to minimise public debt

funding costs that began in Japan and is spreading to Europe. As a result, we

believe the BOJ and ECB have little room to withdraw their monetary policy largesse,

and low real and nominal interest rates will persist. The global real interest rate at

currently around 40bp compares to global real GDP growth of 2.5-3.0% pa, and

advanced economies’ growth of 1.0-1.5% pa.

Short-term business-cycle judgements are more likely to succeed with a deep

awareness of more medium- and longer-term issues. In global macroeconomics,

there are a considerable number of the latter. We examine 24 of them from

page 28; topical issues investigated in our Macq-ro insights reports.

-6

-4

-2

0

2

4

6

8

10

12

14

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(YoY % ) Private nonfinancial credit

Nominal GDP

Macquarie Research The Global Macro Outlook

16 May 2017 2

Beyond the cycle The high-frequency manufacturing sector data are rolling over, below. We are forecasting

global industrial production to rise 2.5% YoY this year, with YoY growth rates moderating as

the year progresses.

Fig 1 Global manufacturing PMIs (>50=expansion) Fig 2 Global PMIs v “hard data”, % YoY

Source: Markit, NBS, ISM, Macquarie Research, May 2017

Cycles oscillate around the trend, and we forecast global real GDP growth to remain

moderate, our ‘long-grinding cycle’ forecast of 2.5 to 3.0% pa growth.

With the ongoing shift to services, trend global industrial production is estimated at 2.25% to

2.75% pa, such that even global industrial production growth of 3.0% is being subjected to a

gravitational pull lower.

We believe investors are about to focus back on underlying, trend issues

1) Labour force growth

One of David Doyle’s key themes has been lower potential growth for the United States, of

around 1.4% pa, with US labour force growth only able to provide 0.4ppt pa of the growth

over the long-term. Combining shifting demographic trends with current participation rates

allows David to compute a measure “breakeven jobs growth”. This is the number of jobs an

economy needs to create in order to keep unemployment from rising. For 2020, for the US,

this is only 45,000 per month: 8 March 2017 Fortress America: Demographics, lower

potential, and the Fed.

Fig 3 The downward trend in breakeven jobs growth is poised to resume

Source: Bureau of Labour Statistics, Macquarie Research, May 2017

46

47

48

49

50

51

52

53

54

55

56

2011 2012 2013 2014 2015 2016 2017

Ind

ex

Global weighted average

BRIC

G4

Increasing rate of expansion

Increasing rate of contraction0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

4.0%

4.5%

5.0%

48

49

50

51

52

53

54

55

2013 2014 2015 2016 2017

Manufacturing

IndustrialProduction

PMI using Markit only

PMI

0

20

40

60

80

100

120

140

160

180

Jan-86 Jan-90 Jan-94 Jan-98 Jan-02 Jan-06 Jan-10 Jan-14 Jan-18 Jan-22

US monthly "breakeven" jobs growth (five year average) (thousands)

Note: This analysis holds constant current (Jan-17) age group participation rates over time and assumes a 4.5%

unemployment rate

projection

Cycles oscillate

around the trend

…even global

industrial

production growth

of 3.0% is being

subjected to a

gravitational pull

lower

We believe US

potential growth is

around 1.4% pa,

with the

contribution from

US labour force

growth being just

0.4ppt pa


16 May 2017 3

We believe the trends have largely gone unnoticed in recent years because of spare capacity

that was created in the economic downturn of 2007-09. But as that slack has nearly

dissipated, particularly in the US, it means that economies are likely to confront the issue of

very weak (if not negative) labour force growth in coming years.

The charts below extend the analysis to Europe, Japan and China. While US labour force

growth will be low (+0.4% per annum), the dynamics are even more severe in other major

economies. Without a jump in age group participation rates, labour forces will shrink through

2030: Japan -0.6% pa, Europe -0.5% pa. and China -0.1% pa.

Fig 4 US breakeven jobs growth has been nearly cut in half since 2010 and is set to fall further ...

Fig 5 … the decline in breakeven jobs in China is poised to become more severe

Source: United Nations, Macquarie Research, May 2017 Source: United Nations, Macquarie Research, May 2017

Fig 6 In Europe, breakeven jobs growth is set to move increasingly into negative territory

Fig 7 … while in Japan it has stabilized (albeit in negative territory)


2) Labour productivity and demographics

There are two major drags on productivity growth from the current age structure in the US, in

our opinion. First, highly experienced workers are retiring and being replaced with younger

inexperienced workers, Fig 9. Please contrast the sharp step-down since 2011 in average

years of experience, Fig 9, with the timing of the step-down in productivity growth, Fig 8.

However, it is not just the exit from the workforce of highly experienced workers, there is also

a mix deterioration amongst those still working. Much of the growth in the workforce is taking

place amongst older workers, who tend to have far lower productivity growth than younger

workers. Please see Fig 10.

113

149

121

110

75

60

41

31

0

20

40

60

80

100

120

140

160

180

1990-95 1995-00 2000-05 2005-10 2010-15 2015-20 2020-25 2025-30

US - monthly breakeven jobs growth (estimate in thousands)

Note: Assumes constant age group participation rates over time (Jan-17 US

rates)

954895

988

647

396

38

-138

-281

-500

-300

-100

100

300

500

700

900

1100

1990-95 1995-00 2000-05 2005-10 2010-15 2015-20 2020-25 2025-30

China - monthly breakeven jobs growth (estimate in thousands)

Note: Assumes constant age US age group participation rates have been used, but have

been upwardly adjusted by 12.5% (the amount that China's 15 & over participation rate exceeds the US 15 & over participation rate)

98

73 73

50

-49

-76

-101-113

-150

-100

-50

0

50

100

150

1990-95 1995-00 2000-05 2005-10 2010-15 2015-20 2020-25 2025-30

Europe- monthly breakeven jobs growth (estimate in thousands)

Note: Assumes constant age group participation rates over time (Europe 2016

rates )

31

16

-1

-19

-33-31

-27

-35-40

-30

-20

-10

0

10

20

30

40

1990-95 1995-00 2000-05 2005-10 2010-15 2015-20 2020-25 2025-30

Japan- monthly breakeven jobs growth (estimate in thousands)

Note: Assumes constant age group participationrates over time (2016 Japan rates)

Without a jump in

participation rates,

labour forces will

shrink through

2030: Japan -0.6%

pa, Europe -0.5% pa

& China -0.1% pa


16 May 2017 4

Fig 8 US non-farm business sector labour productivity, annual % change

Fig 9 US, annual change in average years of experience per worker (3-year rolling average), %

Source: BEA, BLS, Macquarie Research, May 2017 Source: BEA, BLS, Macquarie Research, May 2017

Annual wage gains by age group are an approximation for productivity growth, in our opinion.

Worker wages tend to rise steadily until the mid-40s, before stabilizing and then declining.

Thus, Fig 10 shows a deteriorating mix of worker age groups from a productivity growth

perspective. Rapid productivity growth groups (16-34 and part of the 35-54 age group) are

losing share to the 55+ group.

Demographic headwinds to labour productivity growth are going to persist for a decade.

Fig 10 US labour force, age group shares, %


3) Financial repression for decades

Whilst demographic forecasts are highly reliable for at least 10 years, policy forecasts are

subject to the shifting demands of societies. In Japan, it was only after the private sector

balance sheet recession had ended that the government began to withdraw its fiscal support

for the economy. There are four principal routes to fiscal reconstruction:

1) Strong nominal GDP growth generating strong growth in tax revenues

2) Increasing tax rates

3) Cutting entitlement benefits

4) Minimising public debt expense through financial repression

0

1

2

3

4

1995 2000 2005 2010 2015

US - nonfarm business sector labor productivit y (annual % change)

avg:1995-2010 = 2.5%

avg: 2011-2016 = 0.5%

0.0%

0.2%

0.4%

0.6%

0.8%

1.0%

1.2%

1.4%

1.6%

1989 1992 1995 1998 2001 2004 2007 2010 2013 2016 2019 2022

United States - annual change in average years experience per worker (3 year rolling average)

projection

10%

15%

20%

25%

30%

35%

40%

45%

50%

55%

1953 1963 1973 1983 1993 2003 2013 2023

35-54 yrs

16-34 yrs

55+ yrs

Age group shares of US labour force

lowest productivity growth group, a high

share of the workforce

compared to past

highest productrivity growth group, a low

share of the workforce

compared to the past

A deteriorating mix

of worker age

groups from a

productivity growth

perspective


16 May 2017 5

We do not expect option 1) to be available, given our long grinding cycle thesis, demographic

headwinds and moderate trend global growth. In this environment increasing tax rates, option

2), is likely to lead to a recession; the Japanese experience after its consumption tax rate

increase of April 2014.

In aging societies with slow growth, cutting entitlements, option 3), is a high political risk.

To us, option 4) is the natural choice. An implicit tax on accumulated household savings is

somewhat obscured due to financial intermediation. Further, it tends to be a hidden tax on the

relatively well-off, the elderly who are drawing on their public entitlement benefits.

Financial repression is the policy distortion of markets

Please see Fig 11. The regulatory controls of 1953-79 were dismantled over the subsequent

decades. The current period of financial repression is being achieved principally by monetary

policy, in our opinion.

Fig 11 The US experience since 1953. The return of financial repression

Note: Economic theory has nominal bond yields broadly equal to nominal GDP growth. This was the 1980-2011 experience, the blue column above. Financial repression is the policy distortion of markets as occurred over 1953-79, and, in our opinion, since 2012. Please see page 20 of the 24 April 2017 Macq-ro insights: Financial repression for decades for the Reinhart & Sbrancia historical data

Source: Bloomberg, Macquarie Research, May 2017

On a global scale: A country’s nominal bond yield can be split into a local inflation

compensation element and a common global real interest rate. The latter, in globally

integrated capital markets, is subject to spill-over influences from any of the major central

banks. This is how financial repression is able to show up in the US bond yield in Fig 11.

We believe Japan is prioritizing fiscal reconstruction through financial repression, a multi-

decade program. In our opinion, the BOJ has little room to withdraw its monetary policy

largesse. We believe the Eurozone is moving in Japan’s direction.

The global real interest rate at currently around 40bp compares to global real GDP growth of

2.5-3.0% pa, and advanced economies’ growth of 1.0-1.5% pa.

Financial repression is a headwind to real GDP growth. It involves a transfer from savers

(the accumulated savings of the household sector) to debtors (principally the government). In

Japan, the behavioural response has been an increase in the household savings ratio and

weak consumption growth.

Investment implications

A low real and nominal interest rate environment due to financial repression leads to an

ongoing shortage of assets with stable, secure running yield.

Possibilities include infrastructure assets, investment properties, and a basket of MNC’s

equities with high dividend yields.

-27%

5%

-26%

-40%

-35%

-30%

-25%

-20%

-15%

-10%

-5%

0%

5%

10%

1953-79 (Fin'l repression) 1980-2011 2012-present

Period average - US 10 year bond yield as share of trend US nominal GDP growth

Periods of financial repression have 10 year sovereign yields

below trend (5 year average) in nominal GDP growth

The regulatory

controls of 1953-79

were dismantled

over the subsequent

decades. The

current period of

financial repression

is being achieved

principally by

monetary policy

A country’s nominal

bond yield can be

split into a local

inflation

compensation

element and a

common global real

interest rate. The

latter, in globally

integrated capital

markets, is subject

to spill-over

influences from any

of the major central

banks


16 May 2017 6

The long grinding cycle Global real GDP growth is forecast to remain in ‘the long grinding cycle’ of 2.5-3.0% pa, chart

below. Our 2017-19 global real GDP growth forecasts are 2.9%, 2.7% and 2.6%, respectively.

Fig 12 Global real GDP growth: Macquarie’s long grinding cycle forecast

Note: The 16-Total is the IMF’s 10-Advanced and 6 EM economies. Forecasts are Macquarie where available, alternatively the IMF (see pages 73 and 74). The country weights use market exchange rates, not PPP

Source: IMF, Macquarie Research, May 2017

Global real GDP growth over 1970-2011 was 3.0% pa (3.6% pa using PPP weights). At 2.5-

3.0% pa, we believe the pace of the current expansion will continue to prove to be structurally

lower than in previous decades, as a high global private investment to GDP ratio, fiscal

reconstruction, demographic factors, low TFP growth and sub-optimal global policy-making are

likely to remain as headwinds in the years ahead.

Potential real GDP growth rates are an important anchor to growth forecasting.

Cycles around the trend

Whilst the US Federal Reserve and their policies are regarded as the fulcrum of global capital

markets, the commodity complex provides a critical spyglass on global business cycle

developments. The following two charts come from last month’s 18 April 2017 The Global

Macro Outlook: The view from the commodity pits. We believe the cycle is turning.

Fig 13 Global steel output: Absolute YoY gains remain strong

Fig 14 Chinese steel output growth has partially gone into increased inventories

Note: in February, China was +8.3% YoY, ex-China +7.3% YoY. Please note the greater breadth of the 2016 recovery versus the 2013-14 recovery. Source: worldsteel, Macquarie Research, May 2017 Source: NBS, China Customs, Macquarie Research, May 2017

2.67 2.61 2.89 2.92 2.68 2.88 2.70 2.59 2.60

0.0

1.0

2.0

3.0

4.0

5.0

2012 2013 2014 2015 2016 2017 2018 2019 2020

16-Total Average 1980-2011, 3.0% p.a The long grinding cycle, 2.5% p.a to 3.0% p.a

Average 1980-2011, 3.0% p.a

The long grinding cycle, 2.5% p.a to 3.0% p.a

(Global real GDP growth)

-150

-100

-50

0

50

100

150

Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17

Mt

an

nu

alis

ed

YoY change in crude steel output

World ex-China China

-15%

-10%

-5%

0%

5%

10%

15%

20%

25%

Jan-11 Jan-12 Jan-13 Jan-14 Jan-15 Jan-16 Jan-17

YoY change in Chinese steel apparent and "real" demand

"Real" demand (i.e after stock changes)

Apparent Consumption

At around 2.5-3.0%

pa, we believe the

pace of the current

expansion will

continue to prove to

be structurally lower

than in previous

decades


16 May 2017 7

For broad, GDP-wide judgements, we recommend the OECD Leading indicator as the best

lead indicator of global growth momentum. It is designed to forecast advanced economies’

real GDP growth six months into the future. Please see the 8 March 2017 A Global Macro

Deep Dive: monthly advance #10 for more analysis.

Fig 15 OECD LI, from January 2000 to latest

Note: latest data, March 0.45% YoY (February 0.41% YoY; January 0.32% YoY)

Source: OECD, Datastream, Macquarie Research, May 2017

World export growth has picked up moderately, from -0.8% YoY in January 2016 to +3.9%

YoY in November 2016. Please see the 27 March 2017 A Global Macro Deep Dive: Global

trade in goods for more.

Fig 16 shows how both global industrial production and global export volumes have moved up

together since the start of 2016. In Fig 17, we’ve expressed them as a ratio. Fig 17 shows

how global exports, after having grown faster than global industrial production from 1991-

2008, have subsequently grown moderately less rapidly than global industrial production.

Fig 16 World export volumes and industrial production, YoY % 3mma

Source: CPB, Macquarie Research, May 2017

Fig 17 World export volume divided by World IP, since 1991,monthly


-6

-4

-2

0

2

4

6(%)

OECD LI YoY

0

1

2

3

4

5

01/2013 07/2013 01/2014 07/2014 01/2015 07/2015 01/2016 07/2016 01/2017

(YoY%) World export volumesWorld IP

55

65

75

85

95

105

115

1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015 2017

(Jan 2010=100)

World export volume / World IP

Global industrial

production and

global export

volumes have

moved up together

since the

start of 2016

Global exports, after

having grown faster

than global

industrial

production from

1991-2008, have

subsequently grown

moderately less

rapidly than global

industrial

production

We believe the

OECD Leading

indicator is the best

lead indicator of

global growth

momentum


16 May 2017 8

US trade policies

could lead to a

global growth

shock. We judge

this to be a risk

scenario with a high

probability, 40-50%.

A probability above

50% would need to

become our

base case

The prime risk: An activist US trade policy

A Trump administration in the US brings policy uncertainties which, from the perspective of

global growth, relate primarily to trade policy, tax reform and infrastructure spending.

We believe that President Trump, wearied by the implications of the US being the ‘consumer

of last resort’, wants to rebalance the US economy, and bring factories back to the US.

This implies that President Trump probably focusses more on the trade balance than the

current account which includes the services balance. Fig 18 contrasts the trade balance

positions of Factory Asia and the US. In line with other advanced economies, the US has a

growing surplus on its services balance.

The trade surplus of Factory Asia is now materially bigger than in the years leading to the

Global Financial Crisis (GFC). We believe that this ‘savings surplus’ was one of the main

drivers of the decline in global real interest rates over 2002-06, a contributor to the debt

build-up in advanced economies’ private sectors prior to the GFC.

Ten years later this global ‘fault line’ still exists. The reasons why the global banking system is

not continuing to recycle the imbalances into rapid credit growth are explained in the 15

March 2017 Fault lines and broken pipes.

Fig 18 Trade account balances: Factory Asia in surplus, the US in deficit

Note: Factory Asia is the aggregate of Japan, China, Korea, Taiwan, HK, and the ASEAN-5

Source: IMF, Datastream , Macquarie Research, May 2017

Candidate Trump advocated an activist trade policy, and President Trump is attempting to

implement this, in our opinion. Fig 19 lists our reports on this subject.

These policies could lead to a global growth shock. We judge this to be a risk scenario with

a high probability, 40-50%. A probability above 50% would need to become our base case.

Fig 19 An activist US trade policy: Macquarie reports

1 March 2017 Factory Asia at risk: the numbers

14 February 2017 The Global Macro outlook: Policy shifts in the US

8 February 2017 The US-Japan relationship

31 January 2017 An activist US trade policy, a.k.a protectionism (PowerPoint)

25 January 2017 Global slump scenarios, and the EM economies that concern us the most

19 January 2017 Fortress America: Buy America! Trade policy is great again

9 January 2017 EM economies & US policy risks

Source: Macquarie Research, May 2017

-1200

-800

-400

0

400

800

1200 (USbn$)

Factory Asia

United States

The trade surplus of

Factory Asia is now

materially bigger

than in the years

leading to the

Global Financial

Crisis


16 May 2017 9

Forecasts and revisions Fig 20 & Fig 21 present our principal real GDP forecasts and revisions.

For 2017, we are beneath consensus on the US, Canada, Japan and Australia

We are above consensus in our 2017 forecasts for the Eurozone and NZ

Fig 20 Macquarie’s real GDP forecasts

Calendar Year YoY (%) 4Q on 4Q (%) 2016 2017 2018 2019 2020 2016 2017 2018 2019 2020

US 1.6 2.1 2.0 1.6 1.5 2.0 2.0 1.8 1.6 1.4 Eurozone 1.8 1.8 1.7 1.6 1.6 1.8 1.8 1.6 1.6 1.5 Japan 1.0 0.9 0.7 0.8 0.4 1.6 0.9 0.7 0.8 0.4 UK 1.8 1.7 1.4 1.6 1.7 1.8 1.7 1.4 1.6 1.7 Canada 1.4 2.0 1.3 1.2 1.1 1.9 1.6 1.3 1.1 1.1 Australia 2.5 2.3 2.8 3.0 3.0 2.4 2.6 2.9 3.0 3.1 New Zealand 3.1 3.0 2.6 2.1 2.4 2.7 3.2 2.3 2.1 2.5

China 6.8 6.5 5.6 5.4 5.8 6.8 6.5 5.6 5.4 5.8 S. Korea 2.9 2.5 2.6 2.5 2.4 2.3 2.5 2.5 2.5 2.4 Taiwan 1.5 2.0 2.3 2.2 2.1 2.8 2.0 2.3 2.2 2.1 Hong Kong 1.9 1.5 2.0 2.4 2.4 3.1 1.5 2.0 2.4 2.4 Indonesia 5.0 5.2 5.1 5.0 4.9 4.9 5.2 5.1 5.0 4.9 Malaysia 4.2 4.5 4.5 4.4 4.3 4.5 4.5 4.5 4.4 4.3 Singapore 2.0 2.0 2.3 2.2 2.1 2.9 2.0 2.3 2.2 2.1 Philippines 6.8 6.1 6.3 6.0 5.8 6.7 6.1 6.3 6.0 5.8 Thailand 3.2 3.3 3.2 3.1 3.0 3.0 3.3 3.1 3.1 3.0 India 7.4 6.9 7.7 7.5 7.5 7.0 7.5 7.5 7.5 7.5

South Africa 0.3 1.2 1.3 2.5 3.5 0.2 1.3 1.7 2.7 3.5


Fig 21 Macquarie’s real GDP forecasts: revisions, and versus consensus

2017 YoY (%) 2018 YoY (%) Previous

Macquarie forecast (*)

Current Macquarie

Forecast Consensus Spread (2) versus (3)

Previous Macquarie forecast (*)

Current Macquarie

Forecast Consensus Spread (6) versus (7)

(1) (2) (3) (4) (5) (6) (7) (8)

US (**) 2.2 2.0 2.2 -0.2 1.9 1.8 2.3 -0.5 Eurozone 1.7 1.8 1.7 0.1 1.6 1.7 1.5 0.2 Japan 0.8 0.9 1.3 -0.4 0.7 0.7 1.0 -0.3 UK 1.7 1.7 1.7 0.0 1.3 1.4 1.3 0.1 Canada (**) 2.0 1.6 2.3 -0.9 1.3 1.3 2.0 -0.7 Australia 2.3 2.3 2.6 -0.3 2.8 2.8 2.8 0.0 New Zealand 3.0 3.0 2.9 0.1 2.6 2.6 2.9 -0.3

China 6.5 6.5 6.5 0.0 5.6 5.6 6.2 -0.6 S. Korea 2.5 2.5 2.5 0.0 2.6 2.6 2.5 0.1 Taiwan 2.0 2.0 2.0 0.0 2.3 2.3 2.0 0.3 Hong Kong 1.5 1.5 2.1 -0.6 2.0 2.0 2.1 -0.1 Indonesia 5.2 5.2 5.2 0.0 5.2 5.1 5.4 -0.3 Malaysia 4.5 4.5 4.4 0.1 5.1 4.5 4.4 0.1 Singapore 2.0 2.0 2.2 -0.2 2.6 2.3 2.2 0.1 Philippines 6.1 6.1 6.4 -0.3 6.3 6.3 6.3 0.0 Thailand 3.3 3.3 3.3 0.0 3.2 3.2 3.3 -0.1 India (***) 6.9 6.9 6.8 0.1 7.7 7.7 7.5 0.2

South Africa 1.2 1.2 1.1 0.1 1.3 1.3 1.7 -0.4

Note: (*) April 2017. Calendar year numbers for all countries bar the US and Canada. Data for countries marked with a ** are 4Q on 4Q. Data for India, marked with a ***, is for fiscal year to FY3/17 and FY3/18, and is based on the GDP-at-market-prices series. Consensus numbers for calendar year countries are from Consensus Economics, otherwise the numbers are from Bloomberg.

Source: Consensus Economics, Bloomberg, Macquarie Research, May 2017

For 2017, we are

beneath consensus

on the US, Canada,

Japan and Australia

We are above

consensus in our

2017 forecasts for

the Eurozone and

NZ


16 May 2017 10

We forecast the US

10-year bond yield

to have a quarter-

end cycle high of

only 2.45%

In line with the continuation of moderate real and nominal global real GDP growth, The Long

Grinding Cycle, our interest rate forecasts are commensurately subdued. Please note that we

are forecasting the US 10-year bond yield to have a quarter-end cycle-high of only 2.45%.

Fig 22 Macquarie’s interest rate forecasts

Year-end Policy or cash rate (*) (%) 10-year bond yield (%) 2016 2017 2018 2019 2020 2016 2017 2018 2019 2020

US 0.50 1.25 1.50 1.50 1.50 2.44 2.45 2.40 2.30 2.30 Eurozone 0.00 0.00 0.00 0.25 0.50 0.20 0.75 1.50 1.65 1.75 Japan -0.06 0.00 0.00 0.00 0.00 0.04 0.00 0.10 0.20 0.20 UK 0.25 0.25 0.50 0.75 1.25 1.25 1.75 1.75 2.25 2.50 Canada 0.50 0.50 0.50 0.50 0.75 1.62 1.50 1.50 1.50 1.50 Australia 1.50 1.25 1.25 2.00 3.00 2.76 2.60 2.80 2.90 3.20 New Zealand 1.75 1.75 1.75 2.75 3.50 3.36 3.20 3.10 3.10 3.20

China 4.35 4.35 4.35 4.35 4.35 S. Korea 1.25 1.50 1.50 1.75 2.00 Taiwan 1.38 1.76 2.26 2.76 3.13 Indonesia 4.75 4.75 4.75 4.75 4.75 Malaysia 3.00 2.50 2.50 3.00 3.00 Singapore 0.88 1.80 2.00 2.00 2.00 Philippines 3.00 3.25 3.25 3.25 3.25 Thailand 1.50 1.50 1.50 1.50 1.50 India 6.25 6.25 6.00 6.00 6.00

South Africa 7.00 7.00 6.75 6.75 6.75

Note: (*) Policy or cash rate. US: Fed Funds rate. Eurozone: EMU Refi Rate. Japan: overnight call rate. UK: Repo rate. Canada: Cash rate. Australia: Cash rate. New Zealand: Official cash rate. China: 1-year working capital. South Korea: Overnight call rate. Taiwan: Official discount rate. HK: discount window base. Indonesia: 1-month SBI rate. Malaysia: Overnight policy rate. Singapore: 3-month interbank rate. Philippines: Reverse repo rate. Thailand: 14-day repo rate. India: Repo rate. South Africa: Repo rate.


We are forecasting calendar year 2017 CPI of 2.5% YoY in the US, 1.6% YoY in the Eurozone,

and 2.5% YoY in China: so moderate inflation, not deflation. In 2018, the US and Eurozone

inflation forecasts are 2.4% YoY and 1.4% YoY, respectively, China 2.5% YoY.

After a period of broad US$ strength in 2015, we believe cross-rates are being driven by more

country-specific factors. Whilst relative monetary policy stances will remain important,

resulting capital flows now have to exceed mounting current account surpluses in Japan and

the Eurozone (partially reflecting the falls in oil and other resource prices).

Fig 23 Macquarie’s CPI and currency forecasts

Year end CPI (%, YoY) Currency versus US$ (Year-end) 2016 2017 2018 2019 2020 2016 2017 2018 2019 2020

US 1.3 2.5 2.4 2.4 2.4 Eurozone 0.2 1.6 1.4 1.6 1.5 1.05 1.07 1.09 1.12 1.15 Japan -0.1 0.3 0.5 0.9 1.3 117.1 110.0 108.0 106.0 104.0 UK 0.7 2.7 2.2 1.7 1.8 1.24 1.30 1.37 1.43 1.45 Canada 1.5 1.5 2.0 2.0 2.0 1.34 1.49 1.49 1.45 1.41 Australia 1.3 2.1 1.7 2.5 2.0 0.72 0.74 0.74 0.74 0.75 New Zealand 0.6 1.8 1.5 1.9 2.0 0.70 0.68 0.67 0.67 0.65

China 2.2 2.5 2.5 2.5 2.5 6.95 6.90 6.50 6.00 6.00 S. Korea 1.0 1.8 1.6 1.8 2.0 1,208 1,150 1,150 1,150 1,100 Taiwan 1.4 1.2 1.5 1.5 1.5 32.23 33.00 35.00 36.00 36.00 Hong Kong 2.4 1.6 2.2 2.2 2.4 7.75 7.80 7.80 7.80 7.80 Indonesia 3.5 4.2 4.3 4.3 4.3 13,436 13,700 13,500 13,500 13,500 Malaysia 2.1 2.8 2.6 2.5 2.5 4.49 4.50 4.40 4.30 4.20 Singapore -0.5 1.0 1.4 1.5 1.5 1.45 1.46 1.44 1.42 1.40 Philippines 1.8 2.8 3.3 3.0 3.0 49.71 52.00 52.00 51.00 50.00 Thailand 0.2 1.7 2.0 2.0 2.0 35.78 36.20 36.00 36.00 35.80 India 5.0 4.5 5.1 5.0 5.0 67.81 67.13 68.65 70.03 70.73

South Africa 6.3 5.4 5.1 5.3 5.3 13.70 14.00 14.30 14.66 15.01

Note: The currency forecasts are presented in the most common format. Normally, this is per US$, but exceptions where it is US$ per other currency include the Euro, Sterling, Australia and NZ dollars.


We are not

forecasting deflation

Whilst relative

monetary policy

stances will remain

important, resulting

capital flows now

have to exceed

mounting current

account surpluses

in Japan and the

Eurozone


16 May 2017 11

The latest Macquarie commodity team commodity price forecasts are below.

Commentary follows the table. The next page looks at oil, with comments on other

commodities on the subsequent pages.

Fig 24 Macquarie’s commodity price forecasts

2015 2016 2017 2017 2017 2017 2017 2018 2019 2020 2021 2022 LT

Unit CY CY Q1 Q2 Q3 Q4 CY CY CY CY CY CY $2017

Base Metals

Copper $/tonne 5,503 4,863 5,832 6,100 5,800 5,600 5,833 5,500 5,750 6,088 6,425 6,425 5,900

Aluminium $/tonne 1,663 1,604 1,851 1,850 1,900 2,050 1,913 1,806 1,588 1,513 1,550 1,650 1,350

Zinc $/tonne 1,932 2,092 2,780 2,850 2,950 3,100 2,920 3,100 2,600 2,325 2,188 2,188 2,300

Nickel $/tonne 11,836 9,599 10,271 9,000 8,750 9,500 9,380 10,500 11,500 12,000 13,000 13,500 13,000

Lead $/tonne 1,786 1,871 2,278 2,400 2,500 2,600 2,445 2,525 2,103 1,945 1,928 1,928 1,950

Tin $/tonne 16,077 17,991 20,028 21,500 20,500 20,200 20,557 21,375 23,000 21,000 20,500 20,500 18,000

Steel and Raw Materials

Iron ore - 62% Fe $/t CFR # 56 58 86 65 50 50 63 47 50 55 60 60 60

Hard coking coal $/t FOB 102 114 285 175 150 140 188 128 130 135 140 140 115

Steel - World Export HRC

$/tonne 370 382 523 500 450 450 481 380 390 400 400 415 380

Energy

Crude Oil - Brent $/barrel 51 47 55 56 59 59 57 56 61 69 71 72 64

Crude Oil - WTI $/barrel 48 46 52 54 57 57 55 53 57 64 66 67 60

Henry Hub Gas $/MMBTU 3 2 3 3 4 4 3 3 3 3 3 3 3

Thermal coal - Aus Spot $/t FOB 59 66 81 75 70 73 75 67 63 60 58 58 48

Uranium $/lb 37 26 24 22 23 25 23 25 27 30 33 33 33

Lithium carbonate $/t CFR China

5,190 8,406 10,200 10,500 9,500 8,000 9,550 7,500 7,000 6,750 6,750 6,750 6,000

Precious Metals

Gold $/oz 1,160 1,248 1,219 1,175 1,250 1,325 1,242 1,381 1,375 1,400 1,388 1,425 1,250

Silver $/oz 16 17 17 17 19 21 18 21 22 22 23 23 18

Platinum $/oz 1,053 986 979 950 1,025 1,075 1,007 1,181 1,306 1,325 1,300 1,300 1,400

Palladium $/oz 692 612 765 700 650 650 691 756 825 819 763 713 800

Agriculture

MacPI 1997-2000=100

149 146 155 154 155 156 155

Potash $/t FOB 303 245 214 230 230 220 224 230 240 250 250 316 280

Urea $/t FOB 273 199 240 230 220 220 228 220 220 230 240 268 230

Ammonia $/t FOB 385 234 308 250 250 230 260 225 230 230 245 277 230

Natural Rubber USc/kg 152 161 213 149 151 152 166 154 157 161 165 169 150

Others

Alumina $/t FOB 301 254 340 290 290 345 316 318 288 270 275 275 240

Manganese ore $/mtu CIF 2.9 4.6 5.6 5.5 4.8 4.0 5.0 3.8 4.0 4.0 4.0 4.2 3.0

Ferrochrome (EU contract)

c/lb 107 96 165 154 125 125 142 144 140 130 133 133 110


Whilst the US Federal Reserve and their policies are regarded as the fulcrum of global capital

markets, the commodity complex provides a useful spyglass on global developments.

Based on a simple up/down ratio, 2016 was another challenging year of trying to align supply

with sluggish demand growth.

Fig 25 Macquarie commodity price forecasts, YoY simple up/down ratio

2016 2017 2018 2019 2020 2021 2022

YoY, number of forecasts up 11 22 12 16 13 13 9 YoY, number of forecasts down 15 4 12 7 8 7 1 YoY, number of forecasts unchanged 5 0 1 2 4 6 16



16 May 2017 12

2017 is largely in

balance, based on

our forecasts

Oil The oil supply and demand modelling undertaken by Vikas Dwivedi indicates crude remains on a path to structural rebalance this year.

Fig 26 Global S/D balances, ’000 bpd, tight in 2017, oversupply in 2018

Source: IEA, Macquarie Research, May 2017

Oil demand continues to rise with global real GDP growth, below.

Fig 27 Oil demand remains highly correlated to global growth

Source: World Bank, BP Statistical, Macquarie Research, May 2017

Our house oil price forecasts are presented below and in Fig 28. Please see the 2 February

2017 Longer days, shorter years: Lowering oil price forecast on supply by Vikas Dwivedi for

more explanation. We expect a tighter supply-demand balance in 2017, before surpluses

return in 2018 and 2019.

Fig 28 Macquarie’s commodity price forecasts

2015 2016 1Q17 2Q17 3Q17 4Q17 2017 2018 2019 2020 2021 2022

Long Term (2017 US$)

Crude Oil - Brent $/barrel 51 47 55 56 59 59 57 56 61 69 71 72 64 Crude Oil - WTI $/barrel 48 46 52 54 57 57 55 53 57 64 66 67 60


Continued demand

growth


16 May 2017 13

Commodities The cracks in China-led commodity markets which had started to form last month have been

propagating, with ferrous markets leading many commodities lower. What China giveth,

China can taketh away. That is not to say demand is weak. Indeed the global industrial

recovery is holding up well. However, the end to restock through the industrial chain is pulling

pricing back towards normality.

In commodity cycles, demand leads and supply reacts, with a lag. And the factor which

facilitates this process is price. 2017 looks to be providing another classic example of this

simple commodity rule, one we have seen played out again and again. Those commodities

which traded out the cost curve in 2016 are seeing the strongest positive supply reaction, and

those which have consistently traded into the cost curve a supply decline in the main.

As we have noted before, in modern times this reaction perhaps occurs quicker. This is a

function of where commodity markets were 5-10 years ago, with stronger market conditions

needing every available commodity unit to be attracted in to balance the books. This brought

about the new breed of lower quality cyclical supply, which flexes in and out of markets based

on a short term operating horizon. Of course, much of this supply came from Chinese assets,

most notably in process capacity but also in mining. It is fair to say we were underwhelmed

by the response seen to rising prices last year from this source, with a lack of confidence and

more stringent environmental constraints acting as key headwinds. However, these certainly

seem to have been overcome with supply now ramping up just as the demand cycle turns,

particularly in zinc and alumina.

Of course, such broad-based declines as we have seen in commodity markets create some

opportunities. And in oil, we do view the recent sell-off as a buying opportunity. The global oil

market still appears on track for 3Q and 4Q17 deficits of 450 and 1,000 K BPD, respectively.

We expect consistent crude and product draws to take place over the summer. Crude draws

will be driven by 4 million BPD of returning crude unit capacity by August, primarily in Asia

and Europe. Record high crude runs in the US will also support crude draws this summer.

Our 2018–2019 concern is driven by the potential for easy production growth.

Fig 29 There is increasing evidence that latest supply is reacting to price – the example of Chinese alumina

Fig 30 After five consecutive falls, the headline JFY coal settlement marks a sharp recovery in the price

Source: NBS, Macquarie Research, May 2017 Source: IHS, Macquarie Research, May 2017

Even gold wasn’t immune to the sell-off, though the reasons were somewhat different as Fed

rate expectations firmed. The price is however being held up by weaker supply, offsetting

solid but less punchy investment demand. Physical offtake is slowly improving, although

central banks remain a concern. We expect gold price upside in H2.

Meanwhile, just as stainless steel benefitted from the industrial restock, so it has suffered

most as the cycle has turned. We see Q2 2017 stainless production falling 7% YoY in China

as mills adjust production to weaker demand. With plenty of ore supply (particularly now the

Filipino threat has been removed) and ramping Indonesian NPI the nickel market is more

than well supplied, plus the industry cost structure is lower for the foreseeable future. We

have lowered our nickel forecast by 14% for the current year and 7-10% for future years.

43%

35%

11%

26%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

50%

Shanxi Shandong Henan Total

kt

YoY change in Q1 alumina output, key Chinese provinces

0

20

40

60

80

100

120

140

FY

00

FY

01

FY

02

FY

03

FY

04

FY

05

FY

06

FY

07

FY

08

FY

09

FY

10

FY

11

FY

12

FY

13

FY

14

FY

15

FY

16

FY

17

US$/t FOB

JFY thermal coal contract settlement history (basis 6,322kcal GAR FOB Australia)

What China giveth,

China can taketh

away

The global oil

market still appears

on track for 3Q and

4Q17 deficits of 450

and 1,000 K BPD,

respectively


16 May 2017 14

If there is one common theme in commodity markets over the past year, it is that if the

Chinese government wants something they will probably get it. And this month, they have

become increasingly serious on aluminium. In the light of major regulatory changes

designed to constrain aluminium production capacity, we find that our 2017 global balance

has tipped into a substantial deficit of 1.2Mt. While we still expect some softening during the

present quarter on a major increase in Chinese Q1 output, we limit our downside view to

$1,800-1,900/t (from $1,650-1,800/t previously), and see upside from there in the second half

to $1,900-2,100/t as the market looks towards and absorbs Chinese capacity cuts due to

winter pollution-curbing measures, and potentially “illegal capacity” cuts after the government

inspection teams report back in October. Our aluminium bearishness, based on abundant

bauxite availability and a surfeit of process capacity, is therefore being checked until we see

the market become oversupplied further out from 2019.

After a large shift lower, iron ore prices have found a degree of stability around $60/t for

62%Fe material. However, iron ore is certainly in a displacement cycle. Meanwhile, the

58%Fe CFR China assessment currently sits at ~$45.6/t. In our view, after the recent steel

price falls, Chinese mills are now becoming increasingly focused on maintaining profitability

rather than driving productivity after the likely record crude steel production in April has

struggled to be accommodated by downstream demand, where the restock cycle has ended.

At current 58% levels, however, we will already be displacing some seaborne tonnage from

the market. We would expect a further closing of this gap into mid-year, as 62% material

drops in order to curb the resurgence in Chinese domestic capacity.

For metals and bulk commodities, the key thing to watch over the coming couple of months is

Chinese construction activity. Currently, while steel hot rolled coil margins in China are

negative as downstream sectors struggle to accommodate excess supply, rebar margins are

strong while long product inventory held by the traders is drawing down fast. This points to

still-robust construction activity. However, with MoM sales prices now limited, and only Tier 3

cities (most of which have high inventory) seeing strong sales, we expect signs of weakness

to come through in new starts and fixed asset investment in real estate. Should this start to

pressure the steel rebar margin, we would expect to see further downside in iron ore. We

reiterate our view that 62%Fe iron ore prices will average $50/t for the H2 2017.

The strength in spot thermal coal prices looks to be over, with Chinese prices heading

rapidly back into the NDRC’s favoured market range, and international prices following.

Demand conditions have been decent, but with Chinese domestic tonnes running flat out and

a strong international supply response from Colombia, the US and Indonesia, the thermal

coal market seems amply supplied at present. All eyes are thus back on China again to

reinvigorate domestic mine closures, but in our view this will be carefully controlled to prevent

bottlenecks of the like seen in 2016. Against this backdrop, the $84.97/t FOB Australia JFY

benchmark agreed between Glencore and Tohoku Electric should be viewed as a very

healthy price for producers to lock in for a twelve-month period.

Fig 31 Positions of key mined/extracted commodities in the fundamental cycle – arrow shows 2-year progression


Strong Demand Push Demand destruction Market back in balance Strong supply grow th High stocks Stocks Draw ing Supply constraint

or deficit market Capex accelerating Capex peaking Stocks building Strong supply reaction Limited new supply Capex lagging

Price Acceleration Price peaking Prices falling Severe price decline Prices stablise at low level Prices stable Pricing to encourage supply

Manganese

Lead

UraniumThermal Coal

Met Coal

Iron Ore

Aluminium

Zinc

Copper

Nickel

Chrome

Palladium

Gold

Potash

Platinum

Tin

Oil

US Natural Gas

Silver

Bauxite

LNG

Diamonds

Nitrogen

Steel

Alumina

Lithium

If the Chinese

government wants

something they will

probably get it


16 May 2017 15

United States Underlying economic activity (final domestic demand, which excludes the pace of inventory

building and net exports) continued to grow at an above trend pace, according to the advance

estimate of 1Q growth, which came in at an annualized pace of ~1.5%. The year-on-year

growth rate (~2.5%) also printed firmer than the expansion’s average.

Despite firm activity readings at the start of the year, our conviction continues to grow in the

theme of even lower potential output growth and our long-run estimate of just 1.4%. This was

first highlighted when we made significant revisions to our forecasts in March (Fortress

America: Demographics, lower potential and the Fed) and has since been pushed slightly

lower. We estimate real GDP growth (4Q on 4Q) will come in around 2.0% this year, before

decelerating to 1.8% in 2018, 1.6% in 2019 and 1.4% in 2020 and beyond.

This outlook is driven by our belief that labour force supply will prove to be a major constraint

on growth due to an aging population. Corroborating this view was an excerpt from the most

recent Beige Book, which continued to highlight that worker shortages were manifesting in

increased labour costs, and for the first time reported that these developments were

“restraining growth”.

Aside from this structural call on the US economy, which calls for lower potential output

growth, recent data has also confirmed the decelerating trend that we expect to see going

forward. American consumers, usually a positive contributor to economic growth, took a

breather in 1Q. In fact, consumption was a growth headwind at the beginning of the year.

While we do not expect this trend will continue, the American consumer will likely be the only

saving grace as we move ahead. We do however expect the positive impact from

consumption will be somewhat offset by a more modest growth contribution from areas that

provided a boost in 1Q - energy investment and residential investment.

Indeed, the BEA’s detailed tables suggest energy investment grew ~50% QoQ in 1Q17, its

fastest pace on record going back several decades (and by a wide margin) Fig 32. While

likely continuing to grow, we estimate that the pace of gains seen in energy investment are to

moderate substantially from here, translating to less of a contribution to overall nominal GDP.

As a consequence, industrial growth indicators are likely to moderate in coming months,

presenting yet another headwind for growth momentum. Our full analysis of the advance

estimate for 1Q can be found here: Past the peak: Growth Momentum to fade.

In the context of an economy that is advancing past its peak, we continue to believe the

FOMC will engage in a shorter and sharper rate hike cycle, anticipating two more hikes in

2017 and one hike in 2018, before the upper end of the fed funds target reaches our new

forecasted equilibrium level of 1.75%.

Fig 32 BEA detailed estimates suggest a record quarter for energy investment growth

Source: BEA, Macquarie Research, May 2017

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

60%

1960 1966 1972 1978 1984 1990 1996 2002 2008 2014

QoQ % change in nominal energy & mining investment

We have lowered

our growth

forecasts due to

labour supply

constraints

We anticipate three

Fed rate hikes in

2017 and just 1 in

2018


16 May 2017 16

China China’s economic growth in April started showing some signs of slowdown. That said, 1Q17

may also mark the peak of the ongoing cyclical recovery.

Economy has passed the cyclical peak: Overall, China’s economic data in 1Q17 are quite

strong. GDP growth accelerated to 6.9% from 6.8% in 4Q16. More importantly, nominal GDP

growth rose to 11.8% yoy, the fastest pace since 1Q12. Industrial production in March also

exceeded the consensus, rising to 7.6% yoy from 6.0% in Jan-Feb. Despite the strong data,

the A-share pulled back over the past few weeks, as investors fear that good data could

prompt policy-makers to be more aggressive in tightening regulations.

Regulatory risks a huge overhang: Most equity investors we talked to recently cared much

more about the financial regulation than the real economy. Indeed, the growth rate of the

balance sheet for China’s banking system peaked at 15.8% yoy last Nov, then decelerated to

13.7% this March, the slowest pace since June 2015. We are talking about the world’s largest

banking system, so the deceleration is meaningful. Investors asked us whether the tightening

could lead to a credit crunch, or cause a recession. In our view, the likelihood of the above

two scenarios is very low. After all, the PBoC now has enough liquidity tools to prevent a

credit crunch like the one in June 2013. Moreover, even a liquidity shock like that one has

almost no real impact. That said, we remain cautious for now regarding the financial market,

as regulations are weighing on risk appetite and pushing up interest rates. Both are negative

to risky assets.

Real estate is also cooling down: The property sector has been the biggest positive

surprise so far this year. The booming property market over the past year has lowered the

inventory for developers and also boosted their confidence. That said, in March, property

sales in floor space rose 15% yoy, down from 25% in Jan-Feb. It’s set to fall further in the

coming months, given tighter purchase restrictions and mortgage availability. In 1Q17,

mortgage as % of new loans dropped to 35%, down from 60% in 2H16. Moreover, more and

more cities have seen rising mortgage rates recently, because banks are not only facing

higher funding costs these days but are also under the window guidance to cap the growth of

mortgage loans.

Reflation turned into disinflation: April inflation data showed that CPI inflation edged up to

1.2% yoy in April from 0.9% in March, while PPI inflation moderated to 6.4% yoy from 7.6%.

Falling commodity prices and inventory destocking have reinforced each other since late

March. April data such as PMI, trade and inflation all send the same message: the Chinese

economy has passed its peak in 1Q17. For the next month, CPI might rise to around 1.5%

yoy while PPI could drop below 6%. Lower inflation not only means slower earnings growth in

2Q17, but also reduces the incentive for accumulating inventory.

Fig 33 Industrial profits could have peaked in 1Q17 along with PPI inflation

Source: CEIC, Macquarie Research, May 2017

-8

-6

-4

-2

0

2

4

6

8

10

-10

-5

0

510

15

2025

30

35

40

Ap

r-11

Oct-

11

Ap

r-12

Oct-

12

Ap

r-13

Oct-

13

Ap

r-14

Oct-

14

Ap

r-15

Oct-

15

Ap

r-16

Oct-

16

Ap

r-17

Industrial profits PPI (RHS)

%, yoy %, yoy

Economy has passed

the peak

Financial regulation

becomes the market

focus

The reflation has

peaked


16 May 2017 17

The impacts of lower PPI: The cyclical recovery in China over the past 16 months is driven

by 3Rs: reflation, restocking and real estate. 1Q17 will likely be the peak of this reflation

cycle. Most importantly, lower PPI in April is not only due to the base effect, as the sequential

growth of PPI also dropped into negative territory for the first time this year. It has two impacts

on the economy. First, the nominal GDP growth was 11.8% yoy in 1Q17, the fastest pace

over the past five years. It would moderate from 2Q17. Other data such as corporate earnings

and trade growth would also slow down, as evidenced by incoming trade data for April.

Second, inflation and inventory stocking has turned from a positive feedback loop to a

negative one. PPI inflation could fall to around zero toward the year-end.

External demand resilient but likely to moderate: China’s export growth came in weaker

than consensus, up 8.0% yoy in April. It’s that not exciting but still fine. We expect it to slow

further in the months ahead. For the full year, we expect exports growth of around 5% vs

down 8% in 2016. Import growth slowed to 11.9% yoy in April, mainly due to weaker domestic

demand and lower inflation. The global recovery is real and the recent news from the US and

Eurozone are overall positive. But the growth momentum for external demand seems to be

past the peak. In April, 'Export orders' in the NBS PMI moderated after rising to the new high

since April 2012. In Caixin PMI, 'Export orders' in April dropped to the lowest point in this

year. Global PMIs in April also suggest that the manufacturing recovery is slowing. We still

see 2017 as a solid year but with growth rates moderating from current levels. Therefore,

China’s export growth would remain as the bright spot in the months ahead, but it may also

have peaked in 1Q17 along with PPI inflation, earning growth and nominal GDP growth.

Capital outflows continued to improve: While the economic growth started turning around,

FX reserves data increased for three consecutive months, rising by US$20bn to US$3.03tn.

Other than a positive valuation effect, the improvement is mainly due to two factors. First, the

tight capital controls, which could be eased later this year. Second, it’s also helped by the soft

US$, which has pretty much erased all the gains from the Trump trade since last Nov. So far

this year, the USDCNY has been extremely stable. But the RMB could see more appreciation

pressure in 2H17 unless policy-makers loosen the current capital controls.

Policy outlook - Tight for now: As we discussed above, the economy has just passed the

peak and is at the early stage of a cyclical slowdown. But it's far from a recession and the

demand in the economy is still OK. For instance, cement doesn’t have inventory issue so it

reflects the end-user demand better than steel. In the past few weeks, cement prices still rose

even though steel prices slumped. Therefore, this moment remains as the window for policy-

makers to tighten financial regulation. Like last Dec, they are stress-testing the interbank

market but without any intention to kill it. But it’s still tough for most markets: equity, bond,

commodities and housing. Bond yields are not driven by inflation but by regulatory risks.

Lower risk appetite could even weigh on the RMB as well. But given the current trend, the

slowdown would start testing the 6.5% growth bottom line in 2H17, when policy-makers would

have to shift their focus back to growth.

Fig 34 Rising bond yields on tighter financial regulation

Source: CEIC, Macquarie Research, May 2017

2.5

3.0

3.5

4.0

4.5

5.0

May-1

3

Au

g-1

3

Nov-1

3

Feb-1

4

May-1

4

Au

g-1

4

Nov-1

4

Feb-1

5

May-1

5

Au

g-1

5

Nov-1

5

Feb-1

6

May-1

6

Au

g-1

6

Nov-1

6

Feb-1

7

May-1

7

10y treasury yield%

Exports slowed

down but still a

bright spot

FX reserves

increased for three

consecutive months

Policy still focus on

risks not growth


16 May 2017 18

Eurozone The victory of Emmanuel Macron in the French presidential election was not a surprise, but

for financial markets it was still a relief, especially as the size of his win over far-right

challenger Marine Le Pen beat expectations, even if turnout was lower and abstentions

higher than normal.

There are three potential benefits from his victory. The first, and most certain, is the relief that

we do not have a Le Pen presidency, which economically we think would have been bad for

France, and bad for the Eurozone, despite her rather confused euro-scepticism. A relief rally

began after Macron won the first round two weeks earlier, taking the euro briefly rally to a six-

month high of over €1.10.

The next, and more speculative, benefit is what it means for France. Macron’s economic

policy programme, a mix of lower direct taxes, reform of labour/social security laws, plus

higher investment and defence spending, should be positive but implementation will be hard.

June’s legislative elections present an immediate hurdle. A recent poll (see Fig 35) projected

his En Marche! party could form a workable majority, but naturally there is a huge amount of

uncertainty given the party is new and the electoral system requires alliances.

The third, and the most speculative of all, is the longer-run European dimension. Macron has

expressed a desire for a more unified Eurozone policymaking, with a Finance Ministry and

larger shared budget. These are not new ideas and will run into severe opposition within

Germany. But confidence in the Eurozone’s future is the missing piece of the jigsaw to full

European economic recovery, and something needs to be done.

For now the Eurozone economic recovery continues, though not as strongly as the survey

data has suggested. GDP growth in 1Q came in at 0.46% QoQ. This is faster than in the UK

(0.30%) or the US (0.17%), but 1Q composite PMI, the most widely watched forward

indicator, had hinted at 0.63%, 0.17% higher. The 1Q growth rate was also slightly slower

than in 4Q, despite the PMI being nearly 2 points higher.

We should not always expect the PMI and GDP to move in line - in fact the average ‘miss’

over the last five years has been 0.14%. After all the PMI does not include key sectors such

as construction, government or retail - and the latter was weak in 1Q. Furthermore it is still

possible the official data could be revised higher - as was the case in 4Q - though historically

there isn’t any reason to expect it will be higher.

What we do find is that GDP growth tends to be stronger in the quarter after a quarter in

which the PMI has outperformed the official data. This, and Macron, both add to reasons to

believe our expectation of a slowdown to 0.3% was too much. We revise that to 0.4%, and

this pushes our full-year forecast to 1.8% this year, from 1.7%.

Fig 35 French legislative election, poll forecast seats Fig 36 Eurozone 1Q GDP growth good…not PMI good

Source: Opinion Way, Macquarie Research, May 2017 Source: Markit, Eurostat, Macquarie Research, May 2017

0

50

100

150

200

250

300

350

Far left Left En Marche Right Far right

2012 2017 projected

Majority

0

GDP growth in line

with our forecast

but below survey

data


16 May 2017 19

United Kingdom Britain is in the thick of another election campaign, after the Prime Minister changed her mind

on not calling an early election and gained Parliamentary approval for a vote on 8 June. The

result does not seem in doubt: opinion polls show May’s Conservative Party far ahead of its

challengers, with 49% of the vote, up from 38% last time, with the main opposition party,

Labour, at 28%, down from 31%, the centrist Liberal Democrats taking 10%, up from 8%, and

Ukip, the populist right-wing party, falling to 6% from 13%.It is this latter collapse that has

really helped the Conservative Party, and seat projections suggest they will get a majority of

190 (see Fig 37), up from 12 and the largest since, and almost as large as, Tony Blair’s in his

1997 landslide. What does May want to do with this overwhelming victory? That is not clear,

with policy pronouncements thin on the ground. There is a view that the flexibility afforded by

a large majority will allow her to compromise on Brexit, say by extending the required

transition period as the UK leaves, and deal with structural problems facing the government

budget and economy - the main parliamentary rebellion she faced was early this year on

raising taxes on the self-employed. But her courting of Ukip voters, to the point of accusing

the EU of interfering in the election, suggests the former might be wishful thinking, and on the

latter in general we are wary of governments with large majorities.

The health of the economy has taken a back seat temporarily, despite the flash 1Q GDP

growth report in late April showing the economy slowed to 0.3% growth, down from 0.7% in

4Q. As was widely predicted the sectors that were most badly hit were consumer-facing ones,

a sharp turnaround from 4Q. Retail and ‘distribution’, which includes shops, hotels and

restaurants is 14% of the economy but provided more than a third of the growth in 4Q, rising

2% QoQ. In 1Q, however, it shrank by 0.5% QoQ. This swing reduced GDP growth by nearly

0.4% points.

It is hard to see this as a crisis. Averaged over 4Q and 1Q growth has been 0.5%, in line with

the trend. In 1Q YoY growth actually accelerated, as 1Q 2016 saw just 0.15% growth. And

the first estimate of growth is based on limited information, and could yet be revised higher.

Nevertheless there are three reasons to think this is the start of a more pronounced

slowdown. First, most revisions to ONS data in recent years have been lower, a trend we

think hasn’t been widely noticed. An update of manufacturing and construction data for March

has already reduced the 0.30% to 0.29%, for example. Second, the ONS’s monthly

estimates, and admittedly the March ones are no more than that, suggest momentum going

into 2Q was very weak - even 0.2% MoM growth sequentially in April - June would mean QoQ

growth of only 0.3%. And third, the driver of weaker consumption, higher prices, has some

way to run yet. But we do not see a hard landing. PMI data, which correctly called the 1Q

slowdown, turned up in April, and the global upswing and devaluation should help exporters

and exporting sectors. We stick to our full-year forecast of 1.8%.

Fig 37 The governing Conservatives set for huge majority - 190 on latest polls

Fig 38 …as economy shows signs of slowing (% change QoQ, growth by sector)

Source: Electoralcalculus.com, Macquarie Research, May 2017 Source: ONS, Macquarie Research, May 2017

0

100

200

300

400

500

600

700

2015 2017 forecast

Consv Labour Lib Dems SNP Others

Majority

An election

called…but to what

end is unclear

Economy slowing

but no sign of a

slump


16 May 2017 20

Japan We are expecting the global industrial recovery and moderate export growth to support

growth over the coming year, but strong domestic growth remains elusive. The impact of

financial repression on savings is leading households to be subdued consumers. For more,

please see the 5 January 2017 Japan’s debt-deleveraging marathon. Only reform would jolt

the economy onto a higher growth trajectory, in our opinion.

The needed reform is more flexible labour markets. We believe Japan has a reservoir of

underemployed regular workers now aged 44-54 years old, who were hired over 1985-95

when growth was expected to continue at 4% pa. Companies are unable to fire these

employees, even if they wanted to, under Japanese employment law. With an effective

excess of workers, companies have no incentive to invest in them; hence Japan’s weak

service sector productivity, and absence of significant wage increases

Fig 39 Excess workers in Japan’s service sector

Source: Company data, Macquarie Research, May 2017

Monetary policy: We believe the BOJ is now essentially subordinate to fiscal reconstruction,

working to minimize the government’s interest expense through a policy of financial

repression, (fiscal dominance). The BOJ’s new arrangement to target the 10-year JGB yield

“around zero” makes this more explicit. Please see the 24 April 2017 Financial repression

for decades and the 27 November 2016 Financial repression & valuation. The BOJ’s FY3/18

real GDP growth forecast of 1.3% assumes a big boost from the government’s headline

¥28.1tr supplementary budget. We are much more cautious.

We believe Japan is keen to sign a bilateral trade agreement with the US. In the

meantime, we believe Japan will have to endure a protracted period of US pressure aiming to

increase the value of the Yen versus the US$.

Fig 40 Japan: key macroeconomic forecasts

CY11 CY12 CY13 CY14 CY15 CY16 CY17E CY18E CY19E

GDP (YoY, %) -0.5 1.7 1.4 0.0 0.6 0.8 0.9 0.7 0.8

CPI (YoY, %) -0.4 -0.5 0.1 2.2 0.6 -0.3 0.3 0.5 0.9

Overnight call rate (*) 0.1 0.1 0.1 0.1 0.0 -0.1 0.0 0.0 0.0

10-year JGB (*) 1.0 0.8 0.7 0.3 0.3 0.0 0.0 0.1 0.2

¥/$ (*) 76.9 86.8 105.4 119.8 120.4 117.1 110.0 108.0 106.0

Note: CPI is the headline CPI ex fresh foods. (*): per period end, Macquarie forecasts. (**) The consumption tax rate increase to 10% from 8% is now scheduled for October 2019


We believe the BOJ

is now essentially

subordinate to fiscal

reconstruction,

working to minimize

the government’s

interest expense

through a policy of

financial repression

We believe Japan

has a reservoir of

underemployed

regular workers now

aged 44-54 years

old, who were hired

over 1985-95 when

growth was

expected to

continue at 4% pa


16 May 2017 21

Canada The Canadian economy faces a number of intensifying storm clouds. For one, cracks in

housing have surfaced over the past month with troubles experienced by alternative lender

Home Capital Group, raising the likelihood for potential credit tightening, and ultimately

having adverse consequences for housing activity levels. Adding to these concerns is the

uncertainty around the impact that the Ontario provincial government’s new measures aimed

at curbing speculation will have on the province’s housing market.

The sturdiness of Canada’s trade relationship with the US is also under question following the

Trump administration’s recent announcement to impose countervailing duties on Canadian

softwood lumber imports. Furthermore, ongoing scrutiny by the administration of Canada’s

protected dairy sector may be a signal of more to come. We provide a more thorough

overview of this trade relationship in America First and a Divergent Canada. Lastly, the price

of crude oil has also declined by ~15% YTD, consistent with our team’s forecast for subdued

global growth momentum through year end, presenting further headwinds for Canada’s

energy sector.

These developments have only strengthened our view, which has remained unrelentingly

bearish on Canada since early 2013, and pose escalating downside risks to our well below

baseline forecasts of real GDP growth. Our 2017-19 (4Q on 4Q) real GDP forecasts are

1.6%, 1.3%, 1.1% (cons. 2.3%, 2.0%, 1.9%). Despite this, we are removing our call for a

2017 rate cut. Counter to consensus (which is for a hike in 1Q18), we see the BoC on hold

until 2020 and potentially longer. Our end-cycle estimates for the Overnight rate (1.0%) and

the Canada 10 year (1.5%) are unchanged.

The removal of our call for a cut by the BoC comes after yet another downgraded to its

estimate of real potential output growth (1.4%). Revisions to this estimate began in 2012

(when real potential output growth was estimated at 2.1%) and have since continued on a

steady downtrend. The continued embrace of lower potential output makes rate cuts less

likely due to the low bar that is being set for the economy.

We have altered our call on the CADUSD for end-17 and now estimate a level of $0.67

(USDCAD = $1.49), (prev $0.65, USDCAD = $1.54) as we reduce our expectations for the

two-year sovereign yield differential. While many have pointed to this weakness in the

currency as hope for a revival in non-energy exports, we believe that the window for this long

awaited reorientation of growth has closed. Indeed, despite a ~30% decline in the loonie,

there is no evidence of a resurgence in non-energy export volumes (Fig 41). As such, our

conviction continues to grow in the theme that prolonged weakness is the best Canada can

hope for.

Fig 41 Despite currency weakness, non-energy exports have been broadly weak

Source: Statistics Canada, Macquarie Research, May 2017

8.6%

0.1%

-0.1% -0.7% -1.9% -3.1% -3.5%-5.1% -5.8% -6.3%

-11.9%

-3.4%

-20%

-15%

-10%

-5%

0%

5%

10%

15%March 2017 (3mma) on March 2016 (3mma) - export volume % change by category

Our end-17 estimate

of USDCAD has

been revised lower

to $1.49

Prolonged

weakness is the

best Canada can

hope for


16 May 2017 22

Australia The major development over the past month in Australia has been the release of the federal

government’s 2017/18 budget (see: Aussie Macro Moment – Budget 2017/18 – The fiscal fix).

Whilst striking a much more ‘middle ground’ tone, the budget provides little in the way of

additional macro policy support for the economy. There are small reductions in the near-term

drag on the economy from budget repair, but these are offset in following years with a sharper

contraction. Over the next 4 years the fiscal impulse has shifted from an annual 0.5ppt of

GDP drag on GDP up to 0.6ppts.

Where the budget does offer some support for the economy is in the suite of infrastructure

announcements. But the ‘fiscal fix’ is more one around confidence, than concrete measures.

The funding envelope for infrastructure has not materially shifted, but there is greater clarity

around the government’s intentions – which could anchor business and consumer confidence

around the economy’s growth prospects. There remains a residual risk that measures on the

revenue side (a new levy on large banks, and increased Medicare levy from July 2019) could

dent sentiment.

We have not changed our outlook for the economy based on the budget, and neither has the

RBA, which published its updated growth and inflation outlook a week prior (see: Aussie

Macro Moment – RBA Board – Holding it together and Aussie Macro Moment – RBA

Statement on Monetary Policy). The RBA’s Statement and outlook were relatively upbeat,

citing the improved global backdrop, rather than a domestic boost to from fiscal policy.

Domestic conditions remain a challenge for the RBA’s inflation outlook, particularly the labour

market. Australia’s 1Q17 CPI outcome (see: Aussie Macro Moment – CPI 1Q17 – Done and

dusted?) saw headline inflation return to within the RBA’s 2-3% target band. However, unlike

in other economies, and especially the US, Australia’s reflation is not driven by underlying

economic conditions. Rather, the pickup in headline inflation has narrow (driven by petrol and

tobacco prices) and non-market (tobacco price rises are regulatory, not supply-demand)

sources. Outside of these areas, and electricity price rises, there is very little shift in

Australia’s low-flation outcomes.

Australia’s inflation divergence relative to the US has its roots in divergent labour market

conditions. Headline employment growth surged in Australia in March (see: Aussie Macro

Moment – Labour force: March madness!) but other labour market metrics, such as the

unemployment rate and hours worked, remained subdued. Underlying labour market

weakness is likely to continue to weigh on Australian wages growth, and inflation outcomes,

and ultimately drive a divergence in policy over the next 12-18 months.

Fig 42 Australia’s reflation is driven by petrol prices and regulatory imposts, with inflation pressures outside of these factors remaining subdued.

Source: ABS, Macquarie Research, May 2017

0

1

2

3

4

5

0

1

2

3

4

5

Jun-06 Jun-08 Jun-10 Jun-12 Jun-14 Jun-16

Australia: CPI - Petrol price impact(annual % change)

%%

CPI ex-Petrol

HeadlineCPI inflation

CPI ex-Petrol& tobacco

Australia’s fiscal

policy stance has

shifted in rhetoric,

more than it has in $

terms. Improved

business and

consumer

confidence is a key

channel for a

domestic boost.


16 May 2017 23

New Zealand New Zealand’s inflation and employment growth both surprised on the upside over the course

of the last month. However, the larger surprise was the dovish tone of commentary from the

RBNZ in the May Monetary Policy Statement (MPS).

Headline inflation in New Zealand bounced to 2.2%YoY, which was stronger than the RBNZ

had been anticipating. However, much of the headline bounce was due to higher fuel and

food prices – temporary factors which the RBNZ later acknowledged in the MPS as

temporary, and likely to lead to headline inflation volatility over the year ahead.

In addition to firm headline inflation, New Zealand’s 1Q17 labour market outcome also beat

expectations, with stronger than expected jobs growth (employment is +5.7%YoY) and a sub-

5% unemployment rate (4.9%). However, despite signs of further labour market tightening,

wage inflation remains subdued on account of rising participation and continued strong net

migration flows.

Lastly, house price inflation has moderated further, with the RBNZ citing tighter lending

conditions and loan-to-value ration restrictions as partial explanations. Although broad-based,

the slowing in appreciation has been more pronounced in Auckland, where the RBNZ notes

the annual pace of growth has moderated from 16% in April 2016 to 8.3% in March 2017.

Firmer inflation and tighter labour market headline measures had driven expectations that the

RBNZ may be prepared to bring forward the projected timing of policy normalisation in their

OCR outlook profile. However, not only did the RBNZ’s forecast track remain unchanged, but

the RBNZ noted that monetary policy will remain accomodative for a “considerable period”.

Such a move probably reflects a concern around unwanted NZ$ strength should markets shift

towards a more aggressive policy expectation profile.

The NZ$ has weakened slightly, but remains broadly in line with our current forecast

trajectory. We remain of the view that further NZ$ weakness, to US$0.67, is likely over the

next 12-18 months as the RBNZ’s policy normalisation profile lags in relation to tightening

elsewhere.

Fig 43 The RBNZ has signalled rates will not be rising any time soon, despite a bounce in headline inflation, tight labour market, and softer NZ$.

Source: RBNZ, Macquarie Research, May 2017

1

2

3

4

5

6

7

8

9

1

2

3

4

5

6

7

8

9

Jun-00 Jun-03 Jun-06 Jun-09 Jun-12 Jun-15 Jun-18

New Zealand: Overnight cash rate(%, RBNZ forecasts)% %

RBNZforecasts

Dec-15

Nov-16

Dec-14

May-17

Stronger inflation

and a tight labour

market have not

swayed the RBNZ,

which remains

concerned about

NZ$ strength.


16 May 2017 24

South Africa Ahead of the ANC ruling party’s five-yearly policy and elective conferences later this year,

economic forecast risk will remain high and weighs on private sector investment, employment

and economic growth. We still expect a modest rebound in GDP growth, to around 1.2% in

2017 from 0.3% in 2016, largely driven by a post-drought agricultural sector recovery,

although there could also be some relief to consumers from moderating inflation amid

relatively steady nominal wage increases (see Consumer outlook - Debt & spending power

dynamics across income groups). Our 2017 growth forecast is in line with the consensus

expectation, but we are more bearish than consensus about 2018 growth (1.3% vs 1.6%).

Any significant policy shocks would be a downside risk to our forecasts. The biggest concern

in this regard is the growing support from a significant faction of the ANC for a change in the

constitution to allow expropriation of property without compensation. Our base case view is

that, in the short to medium term, land reform will be accelerated within the existing legislative

framework, without the mooted constitutional change that would threaten property rights. But

unless land reform and redistribution is far more successful than it has been thus far, and

unless economic growth accelerates meaningfully to support faster employment growth, the

risk of populist policies will rise further.

Despite the heightened political risks and possible further sovereign credit rating downgrades,

the rand continues to be supported by foreigners’ bond purchases amid a much narrower

current account deficit. This trend has room to continue given SA’s relatively attractive bond

yields in a global context, especially in light of strong portfolio (especially bond) inflows into

emerging markets1 and foreigners’ estimated holdings of SA bonds still being below previous

record levels (see Fig 44). Economic growth, rather than the currency, will thus bear the brunt

of the political uncertainty and sovereign credit ratings slippage for now. We expect SA to

ultimately end with a mixture of investment and junk credit ratings2, unless there is a

significant departure from the basic policy framework, such as the aforementioned threat to

property rights that would firmly move all ratings to junk. Our base case view implies that SA

should remain in indices such as the World Government Bond Index (WGBI).

The relatively resilient rand alongside receding food inflation should pull inflation back into the

3-6% target, but the SARB is unlikely to cut interest rates this year given the event risk to the

rand related to the ANC’s year-end elective conference (in addition to the general currency

risks). There might be some room to ease monetary policy slightly in 2018 in the context of

below-potential economic growth, ongoing fiscal consolidation, contained inflation

expectations and relatively steady wage settlements, provided that the inflation forecasts

remain below 5.5% on a sustained basis.

Fig 44 Foreigners’ net bond and equity purchases (cumulative) Fig 45 GDP growth composition

Source: Inet-Bridge, Macquarie Research, May 2017 Source: SARB, Macquarie Research, May 2017

1 According to the IIF (IIF Capital Flows Tracker: The Good, the Bad and the Ugly, 1 May 2017), the 3 months to April 2017 recorded the strongest 3-month portfolio inflows into emerging markets since 2014. 2 Current ratings: Fitch BB+ foreign and local currency ratings, Moody’s Baa2 foreign and local currency ratings, and S&P BB+ foreign currency and BBB- local currency ratings. All bar Fitch’s ratings are on negative outlook.

-100000

-50000

0

50000

100000

150000

-50000

0

50000

100000

150000

200000

250000

300000

350000

400000

Jan-00 Jan-02 Jan-04 Jan-06 Jan-08 Jan-10 Jan-12 Jan-14 Jan-16

ZARmnZARmn

Equities Bonds (RHS)

-4

-2

0

2

4

6

2009 2010 2011 2012 2013 2014 2015 2016 2017E

%

Households Government GFCF Inventories

Residual Net exports GDP

We still expect a

modest rebound in

GDP growth, to

around 1.2% in 2017

from 0.3% in 2016,

largely driven by a

post-drought

agricultural sector

recovery


16 May 2017 25

India Reported real GDP growth understated the impact of the slowdown in the economy on

a cash squeeze, in our view: Considering GDP in India is measured using formal sector

economic indicators, we were mindful of the fact that the reported growth numbers will not

reflect the extent of the slowdown in the economy on account of demonetisation, especially in

the informal sector. Accordingly, growth measured on a real GVA (gross value added) basis

stood at 6.6% YoY in the Dec-16 quarter compared with 6.7% YoY in the Sept-16 quarter, not

showing any significant slowdown in economic activity post the cash squeeze seen since

8th November on account of demonetisation. This does not seem to reconcile with other high-

frequency data that we track, including auto sales, cement despatches, power demand, etc,

amongst others that pointed towards slowing economic activity post demonetisation. There

are indications on the ground that consumer discretionary spending was impacted adversely

on a cash squeeze in the short term, even though it is now recovering on remonetisation.

Small & medium enterprises and the rural economy, in which cash transactions are quite

prevalent, have been at a disadvantage. The supply chain disruptions and adverse impact on

productivity also resulted in delaying the recovery in the investment cycle. We believe there

are certain asset classes that are likely to see a long-lasting impact, including real estate/land

sales, jewellery, etc, as the unorganised segment shrinks.

Growth to bounce back in FY18: As the cash situation eases, we expect growth on a GDP-

at-market-prices basis to bounce back from an estimated 6.8% YoY in FY17 to 7.5% in FY18.

On a GVA basis, we expect growth to recover by 80bp, to 7.4% in FY18 from the 6.6%

estimated in FY17. Indeed, we expect growth in FY18 to be largely supported by higher

consumption demand on remonetisation, a lower cost of capital, higher wages & salaries on

state pay commission awards and increased government spending, especially in rural areas.

However, the investment cycle recovery led by private corporate capex is likely to be pushed

forward to FY19. The low capacity utilisation, slow corporate deleveraging and banks’ asset

quality concerns continue to be laggards. Export growth is likely to stabilise in FY18 on

improved global growth prospects.

Challenges for FY18 include:

a) Upside risks to inflation emanating from pent-up consumption demand, rising rural

wages, higher minimum support prices for agricultural produce and gradual narrowing of

the output gap. We believe India’s rate-cut cycle is mostly over now, and any scope for

further monetary easing will be largely data-dependent.

b) Complexity and lag in GST implementation in the initial phase. We expect the

government to implement GST by Jul-17.

c) Global factors including movement in global commodity prices (especially oil) and

uncertainties regarding the direction of US macroeconomic policies.

Fig 46 Real GDP growth Fig 47 CPI inflation forecasts

Source: Inet-Bridge, Macquarie Research, May 2017 Source: SARB, Macquarie Research, May 2017

5.5%

6.5%

7.2%

7.9%

6.8%

7.5%

0%

1%

2%

3%

4%

5%

6%

7%

8%

9%

FY13 FY14 FY15 FY16 FY17E FY18E

YoY%

0%

2%

4%

6%

8%

10%

12%

Mar-12 Jan-13 Nov-13 Sep-14 Jul-15 May-16 Mar-17 Jan-18

YoY%, 3MMAProjected path of CPI inflation

RBI's inflation target (4% +/-2%)

We believe the

upside risk to

inflation clearly

persists in FY18

We expect growth

on a GDP-at-market-

prices basis to

bounce back from

an estimated 6.8%

YoY in FY17 to 7.5%

in FY18


16 May 2017 26

ASEAN Real GDP growth has been fading across ASEAN since 2012, Fig 48, as the region looks for

a new growth engine, and unwinds the credit excesses of the past.

Fig 48 Real GDP growth for ASEAN-5 (weighted by GDP in current US$), 2000 to 2020. 2016-20 are Macquarie forecasts

Note: Please see Fig 176 and Fig 177 for the underlying data. The horizontal dashed line above is 5% pa real GDP growth. The ADB estimates 4.9% pa over 2011-20 and 4.2% pa over 2021-30, whilst the Economic Complexity Project forecasts 4.3% pa. 5% pa is therefore a potential future ‘lid’.

Source: IMF, World Bank, Macquarie Research, May 2017

A subdued external environment and restrained credit expansion is suggestive of real GDP

growth modestly beneath potential, which we estimate at around 4.5% to 5.0% pa for the

ASEAN-5, Fig 48, and the room for monetary policy to have an easing bias, despite the US

Fed’s being in a slow and cautious rate rising cycle.

For EM economies generally, ongoing credit cycle and real property price adjustments temper

the industrial cyclical relief, as does expected weak inward FDI. Please see the 7 November

2016 EM growth struggles & the US Fed and the 5 December 2016 Eastern Europe, ASEAN

& India for more.

We believe Thailand is representative of the challenges facing ASEAN.

Thai manufacturing and total payroll job growth hit an all-time-low in 2016 with weak private

investment growth, contraction in manufacturing loans and rising new NPL formation. The

manufacturing sector is very important for the Thai exports, the job market (41.6% of total

payroll jobs) and the banking system (21% of system loans).

Fig 49 Thailand total exports: flat to down since 2012

Source: BOT, Macquarie Research, May 2017

0

2

4

6

8

10

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

(%)

ASEAN

-20%-16%-12%-8%-4%0%4%8%12%16%20%24%28%

0

50

100

150

200

250

US$ bn

Export (US$ bn) Growth (% YoY)

Drift

Real GDP growth

has been fading

across ASEAN

since 2012, as the

region looks for a

new growth engine,

and unwinds the

credit excesses of

the past

We believe Thailand

is representative of

the challenges

facing ASEAN


16 May 2017 27

The structural weakness of manufacturing has resulted in payroll job growth that has

remained weak, with all-time-low payroll job growth, continued low new hiring in the

manufacturing sector which employs the most payroll jobs, and rising unemployment benefit

claims. One consequence has been moderate Thai private consumption growth, Fig 50.

Fig 50 Thailand private consumption

Source: BOT, Macquarie Research, May 2017

A notable weakness is manufacturing investment. 4Q 2016 private investment (nominal term)

grew only 0.4% YoY being one of the lowest contributions to GDP, at 17.8%. FDI in 2016 hit a

near record low, with only the 2011 major flood year being lower, Fig 51. Thai overseas FDI

was strong, Fig 52, which implies that the better investment opportunities for both Thai and

foreign companies are elsewhere.

Weak private investment and FDI implies that the competitive position of Thailand

manufacturing is still deteriorating.

Fig 51 Foreign direct investment Fig 52 Thai overseas FDI

Source: BOT, Macquarie Research, May 2017 Source: BOT, Macquarie Research, May 2017

Another area of weakness lies in the banking system, which continues to face a sub-par loan

growth. The weak loan growth in 2016 could be attributed to the loan contraction in

manufacturing (-1.4% YoY), the sector that accounts for 21% of total system loan.

Both NPL ratio and new NPL formation from the manufacturing sector remain on a rising

trend which is the key reason behind the loan contraction, in our opinion.

We believe that to support GDP growth, government spending will remain the key factor.

-4%

-2%

0%

2%

4%

6%

8%

10%

12%

0

1

2

3

4

5

6

7

8

Bt trn

PCFE % YoY

8,634 8,562

6,411

14,747

2,474

12,899

15,936

4,975

9,004

3,286

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

18,000

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

US$m

FDI

1,5472,340

5,996

8,1317,176

14,261

12,121

5,7424,991

13,307

0

2,000

4,000

6,000

8,000

10,000

12,000

14,000

16,000

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

US$m

TDI

Moderate Thai

private consumption

growth

Weak private

investment and FDI

implies that the

competitive position

of Thailand

manufacturing is

still deteriorating


16 May 2017 28

Macq-ro insights Short-term business-cycle judgements are more likely to succeed with a deep awareness of

more medium- and longer-term issues. In global macroeconomics, there are a considerable

number of the latter. The following pages provide ‘executive summaries’ on:

Fig 53 Medium- and longer-term global macro issues

1) Global policy coordination 9) Financial repression for decades 17) FDI, following the smart money

2) Global services 10) Housing, globally, a good news story 18) Local factors determine core inflation

3) Innovation clusters/’brain belts’ 11) Global banking’s broken pipes 19) Income shares: from labour to capital

4) The private sector’s appetite for credit 12) Global liquidity & EM credit cycles 20) The corporate savings “glut”

5) Global trade in goods 13) Chinese corporate debt 21) Global income distribution

6) Global trade in services 14) Oil & sovereign defaults 22) Demographic Tectonics

7) Fading fiscal policy tailwinds 15) What’s next for EM economies? 23) Demographics & productivity growth

8) Big government’s impact on growth 16) Global private investment indicators 24) The long grinding cycle continues

Note. Macquarie Research, May 2017

Our Macq-ro insights series have been tackling these with an emphasis on quality data,

presented in numerous tables and charts.

Fig 54 Macq-ro insights 2017 publications

Date Title Topic Pages Data banks

5-Jan Japan’s debt-deleveraging marathon Debt structures are limiting growth - globally 32 BOJ

9-Jan EM economies & US policy risks Protectionism, infrastructure spending and capital flows 13 UNCTAD, World Bank, IMF

11-Jan Following the new smart money MNC political networks and FDUI flows 25 UNCTAD

25-Jan Global slump scenarios and the EM economies that concern us the most

Risks in the US, Eurozone and China, and the vulnerability of EM commodity-exporters

64 Latin America and Net Oil Exporters data build

8-Feb The US-Japan relationship Prospects for a bi-lateral trade agreement 60

1-Mar Factory Asia: the numbers East Asia’s integrated export supply chain & Trump 43 Tariff import volume sensitivities

15-Mar Fault lines and broken pipes Global imbalances and global financial system problems 25 Target2 balances

24-Apr Financial repression for decades A conscious policy choice to minimise public debt funding costs that began in Japan and is spreading to Europe

31 Global real interest rates, inflation-linked bonds


Fig 55 Macq-ro insights 2H 2016 publications

Date Title Topic Pages Data banks

18 July Fiscal winds of change Global fiscal policy tailwinds fade significantly from 2017 30 IMF, World Bank fiscal sustainability databases

22 July Residential investment, globally A good news story: around 4% of global GDP and will grow between 3.5% and 4.0% pa through 2020

58 Residential investment/GDP ratios, BIS price indices

26 July Financial Repression for decades A conscious policy choice to minimise public debt funding costs that began in Japan and is spreading to Europe

21 Global real interest rates, inflation-linked bonds

11 Aug. The Great Divergence: Inflation and Policy

Core inflation is determined by local factors, such that policy divergence is expected to persist

28 Model-based monetary policy rules

26-Aug Timing the exit from unconventional monetary policies: The ECB & BOJ

Using the US experience as a roadmap, but the analysis is complicated by relative fiscal reconstruction priorities

24

7-Nov EM growth struggles & the US Fed A negative reaction, but short-lived and muted to the next Fed Funds hike, but a new growth engine remain elusive

50 UNCTAD FDI, Conference Board productivity statistics

9-Nov Trump and the long durable expansion Post US election analysis for the US and overseas 16

5-Dec Eastern Europe, ASEAN & India Seeking opportunities through contrasts 32 Eastern Europe data build

6-Dec The US economy, oil, and overheating Oil price scenarios, including a US$80 risk case 31

14-Dec The OECED LI: monthly advance #8 The global recovery is maturing, but not yet late cycle 25 OECD LI


Medium- and longer-

term issues


16 May 2017 29

Global policy coordination Over 2016-18, national perspectives are expected to dominate:

1) The US, having achieved domestic balance, will slowly raise policy interest rates

2) The Eurozone will nurture the revival of its private sector

3) China will focus on the quality of its growth

Consumption is the key to global growth forecasts. At the global level, we are expecting

investment to be a mild headwind (pages 54-59), whilst fiscal spending is shifting to a mild

headwind. Trade growth is expected to remain modest and, therefore, we do not expect it to

be a material catalyst of efficiency gains. This leaves consumption, including residential

investment which we believe will be a pocket of strength.

We expect the G7/G20 forums to shift focus from fiscal stimulus to boosting consumption.

Seeking a high-frequency indicator for global consumption, Fig 56 presents the OECD US

and Eurozone consumer confidence monthly series along with the Oxford Economics global

real private consumption series (quarterly data, 4Q ma).

Consumer confidence in both the US and the Eurozone remain at high levels. The benefit to

household real incomes from plunging oil prices is still positive, though at a diminishing rate.

Retail sales data in advanced economies is reassuring, Fig 57.

Fig 56 Global real private consumption is growing around 2.5% pa, consumer confidence indices for the US and the Eurozone, 2006-4Q16

Source: OECD, Oxford Economics, Macquarie Research, May 2017

Fig 57 Retail sales volumes (3m % YoY)

Source: Datastream, Macquarie Research, May 2017

Within consumption, services are becoming ever more important. For example, 67% of US

personal consumption expenditures are now services, with goods just 33%.

-2.0

-1.0

0.0

1.0

2.0

3.0

4.0

5.0

94

95

96

97

98

99

100

101

102

2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(%) US - Consumer Confindence [LHS] Eurozone - Consumer Confidence [LHS]World - Consumption [RHS]

(%)

-10

-8

-6

-4

-2

0

2

4

6

8 (%)

UK US Japan Eurozone

We expect the

G7/G20 forums to

shift focus from

fiscal stimulus to

boosting

consumption

Consumption

growth has softened

over the last six

months


16 May 2017 30

We expect services

will form a greater

share of consumer

spending and total

output in the

years ahead

Global services The service sector has been understudied due to its relative stability. This is despite the

increasing role it is playing in the global economy as its share of output has grown steadily.

Over the past quarter century, ~1 billion new jobs have been created globally; ~75% of these

have been in services. This has caused services employment to rise from ~34% of the global

total in 1991 to ~46% in 2016, a gain of half a percentage point per year. Output data tells a

similar story, with the services share of GDP having risen steadily in both developed and

emerging markets over the past four decades, Fig 58.

Fig 58 Services as a share of GDP, 1970-2014: a secular shift to services

Source: United Nations, Macquarie Research, May 2017

These trends are likely to persist. Growth in per-capita incomes (particularly in EMs),

demographics (aging populations), and firmer relative trends in services inflation all suggest

services will form a greater share of consumer spending and total output in the years ahead.

Fig 59 Services become more important with a higher GDP per capita

Source: IMF, UN, Macquarie Research, May 2017

Country 1970 1975 1980 1985 1990 1995 2000 2005 2010 2014

change

1970 to

2014

change

1995 to

2014

Australia 53.8 57.1 56.9 60.0 66.3 67.8 70.2 69.1 69.0 70.1 16.4 2.3

Canada 59.4 58.7 58.3 61.4 65.8 66.4 64.5 65.8 70.8 69.9 10.5 3.5

France 59.9 62.9 65.2 67.9 69.6 72.7 74.3 76.6 78.6 78.9 19.0 6.1

Germany 48.9 55.2 56.8 59.0 61.1 66.0 68.0 69.8 69.1 69.0 20.1 2.9

Italy 53.4 55.4 57.4 62.4 65.6 67.6 70.0 71.9 73.7 74.3 21.0 6.7

Japan 49.8 54.6 58.1 59.4 59.6 65.2 67.3 70.6 71.3 72.0 22.2 6.8

Republic of Korea 41.2 40.9 46.3 49.5 51.6 54.6 57.5 59.4 59.3 59.4 18.2 4.8

Spain 47.8 49.4 55.0 59.4 60.5 65.1 65.1 66.5 71.4 75.1 27.3 9.9

United Kingdom 58.5 61.6 60.1 62.6 67.0 68.5 72.0 76.0 78.5 78.4 19.9 9.9

United States 65.5 66.5 67.2 70.0 72.6 74.5 76.3 77.5 78.8 78.4 12.9 3.9

DM average (level) 53.8 56.2 58.1 61.2 64.0 66.8 68.5 70.3 72.0 72.5 18.7 5.7

Argentina 48.1 47.0 55.1 56.1 59.1 68.3 69.2 56.9 60.9 63.0 14.8 -5.3

Brazil 52.6 48.9 49.2 46.7 52.9 68.5 67.7 65.9 67.8 71.0 18.4 2.5

China 24.7 22.2 21.8 29.0 32.0 33.3 39.5 40.9 43.7 47.7 23.0 14.3

India 32.5 34.4 33.9 35.9 36.6 39.1 44.2 46.4 48.2 53.0 20.5 13.8

Indonesia 40.1 40.9 37.7 47.1 47.9 47.6 42.9 44.8 41.8 43.3 3.3 -4.2

Mexico 54.1 53.5 49.5 46.8 53.0 57.9 57.1 58.1 58.3 59.0 4.9 1.1

Russian Federation 32.5 53.5 54.0 57.0 61.4 59.1 26.6 5.6

Saudi Arabia 36.8 27.3 27.8 55.2 45.7 45.5 41.5 35.0 39.2 40.6 3.7 -5.0

South Africa 54.4 51.0 45.7 51.5 55.4 61.3 64.8 67.1 67.2 68.0 13.6 6.8

Turkey 41.0 43.4 49.5 51.0 47.8 50.0 59.4 61.4 64.2 64.9 23.9 14.9

EM average 42.7 41.0 41.1 46.6 46.3 52.5 54.0 53.3 55.3 57.0 15.3 4.5

Emerging markets

Services share of GDP

Developed markets

$-

$10

$20

$30

$40

$50

$60

$70

40 45 50 55 60 65 70 75 80 85

GD

P p

er cap

ita (th

ou

san

ds) U

S$

Services share of output (%)

AUS

CAN

DEU

USA

GBR

FRA

ITAJPN

KOR

BRA

ZAF

TUR

ARG

MEX

RUS

IND

CHN

IDN

SAU

line of best fit

GDP per capita vs. services share of output (2014)

ESP

Over the past

quarter century,

~1 billion new jobs

have been created

globally; ~75% of

these have been in

services


16 May 2017 31

The rising importance of services has played a key role in our view that the current expansion

should continue to be characterized by structurally lower growth rates, but also by incredible

persistency and resiliency. We see five major implications:

1) Reduced volatility in economic growth

Services output is much less volatile than industrial output leading to more stable

employment trends. This also means that the business cycle will be less cyclical

supporting longer expansions and limiting the severity of downturns.

2) Central bank policy divergence and less inflation variability

The rise of services means that inflation prospects are going to be increasingly driven by

domestic forces, such as wage growth, and less by external factors such as commodity

prices and exchange rates. As a result, divergent domestic outlooks are likely to enable

desynchronized central bank policy.

Fig 60 US services inflation has shown far more stability relative to goods

Fig 61 ... and has been stronger on average with lower variation

Source: BEA, Macquarie Research, May 2017 Source: Bloomberg, Macquarie Research, May 2017

Fig 62 Euro area services inflation has shown greater stability than goods...

Fig 63 ...and a similar story in China, with services more stable and stronger than goods

Source: Bloomberg, Macquarie Research, May 2017 Source: Bloomberg, Macquarie Research, May 2017

-5%

-3%

-1%

1%

3%

5%

1991 1994 1997 2000 2003 2006 2009 2012 2015

US PCE price index YoY % change

services

goods

0.0%

0.5%

1.0%

1.5%

2.0%

2.5%

3.0%

3.5%

Average STDEV

Services

PCE price inflation descriptive statistics: 1991 to 2015

GoodsServices

Goods

-3

-2

-1

0

1

2

3

4

5

6

7

1991 1994 1997 2000 2003 2006 2009 2012 2015

services

goods

Euro area CPI price index YoY % change

-4

-2

0

2

4

6

8

10

12

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

goods

services

China CPI price index YoY % change

The current

expansion should

continue to be

characterized by

structurally lower

growth rates, but

also by incredible

persistency and

resiliency


16 May 2017 32

3) Increased trade in services

Trade in services has been rising rapidly worldwide, but a steep run-up in commodity

prices between 1998 and 2014 led to disproportionate gains in the trade of goods,

particularly from EM exports. Going forward, our expectation for a flatter commodity price

environment means that services exports are likely to make up a greater share of overall

export growth and rise in importance worldwide. Please see page 38.

4) Relative investment in IT and intellectual property

Service economies, which tend to be centred on knowledge-based industries, are increasingly

investing in IT and intellectual property relative to other investment areas. This shift is likely

to influence growth globally, as these forms of investment tend to be less trade-dependent

and contribute the majority of the economic benefit to the domestic economy.

Fig 64 Intellectual property products have risen to one-third of non-commodity US business investment

Fig 65 ...and the biggest increases have come from the R&D and software components

Source: BEA, Macquarie Research, May 2017 Source: BEA, Macquarie Research, May 2017

5) Lower productivity growth and real rates

The services sector has historically had lower productivity levels and growth rates than the

goods/manufacturing sector. A greater share of services employment and output will act as

a drag on productivity growth as a higher share of output will come from areas with lower

productivity growth.

In the years ahead, EMs are likely to continue to experience the strongest output gains as

productivity growth rates tend to be highest when countries undergo urbanization. This allows

workers with very low marginal productivity in the agricultural sector to be redeployed into

higher productivity employment in either the industrial/goods or service sector.

0%

10%

20%

30%

40%

50%

60%

70%

80%

1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009 2014

all other non-resi

investment

intellectual property

products

information processing

equipment

Share of US nonresidential private investment (ex mining and oil & gas)

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

20%

1959 1964 1969 1974 1979 1984 1989 1994 1999 2004 2009 2014

Share of US nonresidential private investment excl mining and oil & gas

Software

R&D

Enetertainment, literary, and

artistic orginals


16 May 2017 33

Innovation clusters, ‘Brain belts’ After a week visiting the Southern California brain belt, bringing to life the book by Antoine

van Agtmael and Fred Bakker: The Smartest Places on Earth (2016), we are optimistic about

a new global growth engine.

The catalyst for the above book was the insight that “Making things cheap to gain an edge

over high-cost Western companies just wasn’t cutting it anymore. The days of the low-cost

advantage were essentially over”. This led to an understanding that cheap is giving way to

smart, where high value-added products are being created in collaborative environments,

in ‘brain belts’. The latter, to quote Antoine van Agtmael and Fred Bakker are:

Research facilities with deep, specialist knowledge; educational institutions; government

support for basic research; appealing work and living environments; capital; and, most

important, the atmosphere of trust and the freedom of thinking that stimulates unorthodox

ideas and accepts failure as a necessary part of innovation—different from the hierarchical,

regimented thinking so prevalent in many Asian and MIST economies.

MIST stands for Mexico, Indonesia, South Korea and Turkey.

In addition to the brain belts listed in Fig 66, Antoine van Agtmael and Fred Bakker identified

many others in their book, but virtually all were in North America and Europe.

Fig 66 ‘Brain belts’: The Smartest Places on Earth

Country Region Name/place Focus Universities, research institutes, hospitals

United States: Well-known

California West Silicon Valley IT, bioscience, electric car, next gen bendable and wearable electronic devices

Stanford, University of California, Caltech

Massachusetts East Cambridge (and Route 128) Bioscience, robotics MIT, Harvard

Texas South Austin (Silicon Hills) Computers, new materials, bioscience University of Texas

Focus of the book

North Carolina South-East Durham-Raleigh-Chapel Hill (Research Triangle Park)

Bioscience, new materials, energy (LED) Duke, UNC, NC State

New York East Albany (Hudson Tech Valley) Semiconductors SUNY, RPI

Ohio Midwest Akron New materials, polymers University of Akron, Kent State

Minnesota Midwest Minneapolis-St. Paul Medical devices/bioscience University of Minnesota

Oregon West Portland (Silicon Forest) Bioscience OHSU

Northern Europe: in book

Netherlands Eindhoven (High Tech Campus)

Semiconductors. New materials Technical University

Sweden Lund-Malmo (Ideon) Life science, new materials Lund University

Finland Oulu (Technopolis) Medical instruments, wireless Oulu University

Germany Dresden (Silicon Saxony) Semiconductors Max Planck

Switzerland Zurich Life science Technical University

Note: from the book by Antoine van Agtmael and Fred Bakker: The Smartest Places on Earth (2016)

Source: Antoine van Agtmael and Fred Bakker above, Macquarie Research, May 2017

Beyond expensive, multidisciplinary, complex new product development, these innovation

clusters are also undertaking manufacturing, highly automated, custom runs, using 3-D

printers, produced in close proximity to the customer.

From an employment perspective, Antoine van Agtmael and Fred Bakker are optimistic, citing

Enrico Moretti’s book The New Geography of Jobs (2013).

For each new urban high-tech job there are five additional jobs created, three for

professionals and two for lower-wage non-professionals.

Cheap is giving way

to smart, where high

value-added

products are being

created in

collaborative

environments, in

‘brain belts’

For each new urban

high-tech job there

are five additional

jobs created


16 May 2017 34

The private sector’s appetite for credit Debt is not inherently a problem. Intermediated by the financial system, it is the main way that

savers earn returns. Savers, to be sustainably paid, however, require debt to be deployed into

debt-serviceable activities. We regard private sector non-financial credit growth broadly in line

with nominal GDP growth to be healthy.

The revival of private sector credit demand is a prerequisite for the successful withdrawal of

extraordinary central bank support for the economy.

In the case of Japan, the excess of credit growth over nominal GDP growth over the 1980s

‘bubble’ was followed by a protracted period of balance sheet adjustment (credit growth

beneath nominal GDP growth, Fig 67. We believe Japan endured a vicious cycle of policy

and regulatory mistakes, which US policy avoided after the Global Financial Crisis, Fig 71.

Fig 67 Japan: private non-financial credit growth vs nominal GDP growth

Fig 68 US private sector non-financial credit is growing faster than GDP for the first time since 2008

Source: FRB of St Louis, Datastream, Macquarie Research, May 2017 Source: FRB of St. Louis, Macquarie Securities, May 2017

Nevertheless, even in the US it took four years between the year private sector credit growth

turned positive (2011) until it exceeded nominal GDP growth (2015).

The Eurozone is behind the US because of the 2011-13 fiscal squeeze, Fig 69, such that

private sector credit growth double-dipped and has only gone positive again in 2015, four

years behind the US (2011), Fig 70.

Fig 69 The fiscal impulse: the Eurozone’s 2011-13 fiscal squeeze

Fig 70 Euro Area: private nonfinancial credit growth vs Nominal GDP growth

Note: Year-over-year change in the cyclically adjusted net lending (+) or net borrowing (-) of general government, adjusted based on potential GDP, excessive deficit procedure. Forecasts for 2015-17 from the European Commission. Source: EC Annual Macroeconomic Database, Macquarie Research, May 2017 Source: FRB of St Louis, Datastream, Macquarie Research, May 2017

-12

-9

-6

-3

0

3

6

1992 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013 2015

(YoY % change) Private nonfinancial creditNominal GDP

latest

-4

-2

0

2

4

6

8

10

12

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

(YoY% ) Private nonfinancial credit

Nominal GDP

latest

-2

-1

0

1

2

2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

(% of potential GDP)

YoY change in cyclically adjusted budget balance

-6

-4

-2

0

2

4

6

8

10

12

14(YoY % ) Private nonfinancial credit

Nominal GDP

The case of Japan

The US

The Eurozone


16 May 2017 35

The BIS Financial cycle

Claudio Borio in his December 2012 BIS working paper: The financial cycle and

macroeconomics: What have we learnt? (http://www.bis.org/publ/work395.pdf) detailed the

existence of financial cycles: “Arguably, the most parsimonious description of the financial

cycle is in terms of credit and property prices (Drehmann et al (2012)). These variables tend

to co-vary rather closely with each other, especially at low frequencies, confirming the

importance of credit in the financing of construction and the purchase of property.”

Like business cycles, financial cycles are not mechanistic, but do appear as patterns in the

data. One problem is that whilst business cycles average 3-4 years, financial cycles average

16. Averages are just that, so let's say 16 years plus or minus 5. A lot depends on how policy

responds in the business cycle downturns prior to the financial cycle's peak/bust. On average

there will be three prior business cycle downturns, and if policy aggressively counteracts them

then moral hazard/credit leverage builds. We believe the private sectors of the major

economies/blocs are at very different stages in this ‘financial cycle’, below. The credit cycle

in EM economies is examined on page 45.

Fig 71 BIS-defined 16-year private sector ‘financial cycle’


Fig 72 presents the last 35 years of financial history in one chart. The rise and fall in the ratio

of private non-financial credit/GDP has coincided with major events. China is included to put

the relentless rise in its private non-financial credit/GDP ratio into context. China’s corporate

debt issue is examined on page 49.

Fig 72 Private non-financial credit as a % of GDP: significant peaks*

Note: (*) 1) 1990 saw the start of Japan’s lost decade 2) 1995 was Mexico’s peso crisis 3) 1997 saw Thailand kick-off the Asian crisis 4) 2008 was the USA’s subprime crisis 5) 2011 was the start of the Euro crisis that included Spain

Source: The Economist, BIS, Macquarie Research, May 2017

0

50

100

150

200

250(% of GDP)

Japan US Spain Mexico Thailand China

Like business

cycles, financial

cycles are not

mechanistic, but do

appear as patterns

in the data

We believe the

private sectors of

the major

economies/blocs

are at very different

stages in this

“financial cycle”


16 May 2017 36

Global trade in goods The 1980-2008 6% pa global world trade volume growth average has stepped down, in our

opinion, to a new trend growth rate of 2-3% pa, Fig 73.

Fig 73 World Merchandise Trade, from 1992 to latest, rolling 3 months, YoY


This reflects:

1) The maturing of a 50-year containerization trend.

2) The completion of the integration of China into global supply chains post its

December 2001 WTO entry.

3) The move by MNCs to regionalize production to dampen exchange rate risk.

4) The transition of China’s investment and credit-driven growth model into an import

substitution stage for intermediate and capital goods, especially by those companies

that perceive their cost of capital to be very low.

The late 2014/early 2015 air pocket in emerging market economies’ import growth, along with

the trend decline in its growth rate, is shown in Fig 74, red line, which uses rolling three-month

average YoY data.

Fig 74 EM & Advanced economies import volumes


One consequence of the above is the muted response relative to history of the trade account

to exchange rate movements. This probably results in greater currency volatility.

In the case of EM currency depreciations, the consequence is likely to be more import volume

compression than export volume expansion.

For the identification of global trade trends, we recommend the comprehensive database of

the CPB Netherlands Bureau for Economic Policy Analysis. Data for both volume and price/

unit values is available geographically on a monthly basis. Importantly, the data is seasonally

adjusted. Their website is here: http://www.cpb.nl/en and their key summary table is Fig 75.

-25

-20

-15

-10

-5

0

5

10

15

20

1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

World Merchandise Trade, YoY

(%)

-5

0

5

10

15

20

25

2010 2011 2012 2013 2014 2015 2016 2017

Advanced EM

(per 12 month % change)

LAST 3 MONTHS ON YEAR AGO

Please note the late

2014/early 2015 air

pocket in emerging

market economies’

import growth,

along with the trend

decline in its

growth rate


16 May 2017 37

For those interested in going deeper into last year’s developments in China, the May 2016

IMF working paper by Joong Shik Kang and Wei Liao: Chinese imports, What’s behind the

slowdown? provides a comprehensive analysis of recent trends in Chinese trade.

Fig 75 World merchandise trade (% changes) – latest month February 2017

YoY QoQ momentum (note #1) MoM

Volumes (s.a) 2014 2015 2016 2016q2 2016q3 2016q4 2017m01 2017m02 2016m12 2017m01 2017m02

World trade 2.7 2.0 1.3 -0.3 0.6 1.4 2.7 2.7 0.8 1.0 -0.6

World imports 2.6 1.9 1.4 -0.2 0.8 1.1 2.5 2.8 0.6 2.2 -1.2

Advanced economies 3.2 3.6 1.9 -0.2 0.6 -0.2 0.5 0.5 0.1 0.8 -1.4 US 5.1 6.2 0.7 -0.7 0.5 2.0 3.4 3.3 1.6 2.0 -2.5 Japan 2.2 0.2 -0.1 -1.1 0.0 0.3 1.6 0.6 0.5 2.4 -5.2 Eurozone 2.7 3.6 2.4 -0.7 0.8 0.5 0.5 0.0 -1.2 0.4 0.0 Other advanced economies 2.6 2.2 2.9 1.9 0.7 -4.1 -3.1 -1.5 1.3 -0.4 -1.7

Emerging economies 1.7 -0.4 0.6 -0.4 1.0 2.9 5.4 6.1 1.2 4.3 -0.8 Asia 3.2 -0.1 2.2 0.3 1.5 4.4 6.7 6.7 0.5 5.8 -1.2 Central & Eastern Europe -10.9 -23.1 10.2 -0.3 0.5 0.0 4.4 8.4 1.2 10.6 -2.3 Latin America 3.1 -1.3 -2.8 -2.3 1.9 0.4 2.9 4.5 5.6 -2.3 1.6 Africa & Middle East -0.1 10.4 -7.5 -2.1 -2.5 -1.8 1.1 2.9 0.8 0.1 -0.7

World exports 2.7 2.2 1.3 -0.4 0.4 1.8 3.0 2.6 1.0 -0.3 0.0

Advanced economies 2.1 1.8 0.9 -0.1 0.7 1.5 1.8 1.8 1.4 -1.1 0.4 US 3.2 -1.1 0.0 0.4 3.8 -1.1 0.0 2.3 3.6 0.3 0.1 Japan 1.8 2.7 1.8 0.7 0.9 2.5 2.4 2.9 0.0 0.0 4.6 Eurozone 1.9 2.2 1.8 0.4 0.1 1.1 0.9 0.4 -0.1 -1.4 0.9 Other advanced economies 2.0 2.8 -0.7 -2.1 -0.3 4.1 5.2 4.4 4.0 -1.9 -2.2

Emerging economies 3.5 2.7 1.7 -0.6 0.0 2.2 4.4 3.5 0.4 0.6 -0.6 Asia 4.2 1.4 0.8 -0.6 -0.5 2.6 4.3 3.1 0.5 0.0 -0.9 Central & Eastern Europe -0.5 0.1 3.1 0.8 0.4 3.1 5.6 4.8 0.3 1.6 0.3 Latin America 4.8 9.2 3.8 -4.0 0.3 1.8 8.3 8.8 -0.4 6.9 0.2 Africa & Middle East 1.6 4.5 3.2 2.2 2.0 0.0 0.1 -1.3 0.5 -3.4 0.1

Prices/unit values US$ (s.a.)

World trade -1.6 -13.5 -5.1 2.5 0.1 0.1 0.1 1.0 0.6 0.9 0.8

World imports -1.4 -13.2 -5.1 2.5 -0.1 0.2 0.4 1.4 0.3 1.4 1.0

Advanced economies -1.1 -14.0 -4.5 2.5 -0.3 -0.7 -0.5 0.4 -0.1 1.4 0.5 US -1.1 -10.2 -3.3 1.8 0.8 0.6 0.7 1.0 0.4 0.6 0.4 Japan -4.7 -20.3 -6.2 2.5 6.1 -1.3 -3.0 -2.5 -4.5 2.1 3.7 Eurozone -1.5 -17.4 -2.7 3.0 -0.1 -0.9 -1.1 0.0 -0.1 2.1 -0.4 Other advanced economies 1.0 -9.1 -8.5 2.1 -3.8 -1.5 0.1 1.5 0.6 0.6 1.5

Emerging economies -1.8 -12.1 -6.0 2.5 0.1 1.5 1.5 2.6 0.9 1.3 1.6 Asia -2.4 -12.9 -6.6 3.1 0.4 0.8 0.7 2.5 1.5 0.7 2.7 Central & Eastern Europe -2.8 -14.8 -11.3 -5.2 -1.8 -0.6 4.4 9.2 -2.0 19.9 -3.9 Latin America -3.0 -9.2 -5.3 1.7 -0.6 1.8 1.9 1.5 -0.1 0.9 -0.7 Africa & Middle East 2.7 -11.4 -0.5 3.2 1.0 5.4 4.6 2.4 0.1 -0.1 -0.3

World exports -1.7 -13.7 -5.1 2.4 0.3 0.0 -0.3 0.6 0.9 0.4 0.7

Advanced economies -0.9 -12.8 -3.0 2.5 0.0 -1.1 -1.3 -0.8 -0.6 0.9 0.1 US -0.5 -6.3 -3.2 1.3 0.6 0.3 0.7 0.8 0.4 0.2 0.3 Japan -5.2 -11.9 1.0 3.2 4.4 -2.9 -5.2 -5.2 -5.1 0.9 1.7 Eurozone 0.0 -15.2 -1.3 2.6 -0.3 -1.7 -2.3 -1.6 -1.2 1.2 0.0 Other advanced economies -1.6 -12.7 -8.1 2.9 -1.6 0.0 1.2 1.9 1.6 0.6 -0.1

Emerging economies -2.7 -14.7 -7.5 2.4 0.7 1.5 0.9 2.2 2.6 -0.1 1.3 Asia -0.8 -6.9 -5.2 1.5 0.2 0.1 -0.6 0.6 0.8 0.1 2.1 Central & Eastern Europe -5.4 -32.0 -19.5 1.8 3.2 4.7 8.9 10.2 4.8 8.0 -3.6 Latin America -6.0 -19.3 -5.9 5.0 1.5 2.4 0.5 -0.2 3.0 -5.3 1.8 Africa & Middle East -6.7 -37.9 -16.9 8.1 3.4 8.4 7.8 12.4 14.8 0.3 -1.3

World prices/unit values in US$

Fuels (HWWI) -6.8 -44.1 -14.6 28.9 3.6 12.0 10.4 14.0 14.4 0.9 0.1 Primary commodities ex fuels -9.2 -22.8 -0.8 10.2 1.3 6.4 10.1 10.5 2.2 2.9 3.2

Notes: (#1): average of the three months up to the report month over average of the preceding three months



16 May 2017 38

Global trade in services The share of global trade in services has been flat for close to 20 years, Fig 76, as much of

the delta in global trade growth has come from EM goods.

The result of this development is that services have become far less trade-intensive relative

to goods. To provide some context, the average dollar value of world exports per employee

in the goods sector is ~$11,000, nearly 3x the same figure for the services sector, Fig 66.

This represents a significant increase from just ~2x in 1991.

Fig 76 Flat global services export share, 1982-2015 Fig 77 A higher trade intensity in goods

Source: WTO, Macquarie Research, May 2017 Source: WTO, Macquarie Research, May 2017

Partially fuelled by a boom in commodity prices from 1998 to 2014, global trade growth has

been increasingly driven by EMs, where exports are more concentrated in goods. We believe

this contributed to outsized gains in the exports of goods.

Prior to 1998, growth in services exports for both EMs and DMs outpaced the growth in goods

(Fig 78) whereas after 1998 EM goods exports outperformed (Fig 79).

Fig 78 Services trade outperformed from 86 to 98 … Fig 79 Underperformed during the commodity boom

Source: WTO, Macquarie Research, May 2017 Source: WTO, Macquarie Research, May 2017

Going forward, it may be many years before there is another commodity boom. As a result,

global trade growth is likely to come increasingly from services.

Policymakers are already showing signs of awareness on this front. Recent trade

agreements, such as the Trans-Pacific Partnership, have chapters dedicated specifically to

liberalizing the trade in services and removing barriers.

5%

10%

15%

20%

25%

30%

1982 1987 1992 1997 2002 2007 2012

Share of exports that are services (USD basis)

G20-DM

G20-EM

world

$-

$2,000

$4,000

$6,000

$8,000

$10,000

$12,000

1991 1994 1997 2000 2003 2006 2009 2012

goods

services

World exports (USD basis) per employee

0

1

2

3

4

5

1982 1984 1986 1988 1990 1992 1994 1996 1998

Export growth - G20 countries (1982= 1.00)

EM services

DM services

DM goods

EM goods

1982 = 1.00

During flat commodity price period EM service

exports outperformed

0

1

2

3

4

5

6

7

8

1998 2000 2002 2004 2006 2008 2010 2012 2014

DM goods

Export growth - G20 countries (1998 = 1.00)

EM goods

EM services

DM services

1998 = 1.00

During commodity boom EM goods

exports outperformed

The share of global

trade in services

has been flat for

close to 20 years

Going forwards,

global trade growth

is likely to come

increasingly from

services


16 May 2017 39

Global fiscal policy

has now reached an

inflexion point, as it

is forecast to

become a

significantly weaker

cyclical tailwind,

with aggregate

budget balances

forecast to improve

modestly (by around

0.5% of GDP each in

2017 and 2018)

Those countries with

larger budget

deficits (horizontal

scale) are forecast,

on average, to see

the biggest

improvements

(reduction in the

budget deficit) 2017

versus 2016

(vertical scale)

Fading fiscal policy tailwinds In the immediate aftermath of the global financial crisis (GFC), global fiscal policy was very

expansionary, with global budget deficits widening by nearly 2% of GDP in 2008 and a further

5% of GDP in 2009, Fig 80. Aggregate revenue weakness was accommodated and spending

was increased. However, the fiscal expansion was tempered from 2010, when global budget

balances improved by 1% of GDP (each) in 2010 and 2011, as economies began reloading

their fiscal arsenal.

This continued, albeit less aggressively, in 2012-13, with an average improvement of 0.7%

of GDP per year. From 2014-16, however, aggregate fiscal budget balances deteriorated

modestly (on average by 0.2% of GDP per year), as the global economic recovery became

less sure-footed and put pressure on developing economy tax revenues in particular. Global

fiscal policy has now reached an inflexion point again, as it is forecast to become a

significantly weaker cyclical tailwind, with aggregate budget balances forecast to improve

modestly (by around 0.5% of GDP each in 2017 and 2018).

Fig 80 Advanced versus developing countries: primary budget balances


Fig 81 Budget balance 2016 and change to 2017


-6.00

-5.00

-4.00

-3.00

-2.00

-1.00

0.00

1.00

2.00

3.00

% of GDP, YoY change

Advanced weighted Developing economies (weighted)

Philippines

Hungary

Mauritius

Thailand

Indonesia SingaporeIsrael Chile

Brazil SAUSNZ

IndiaChinaNigeria

Croatia

MalaysiaMexico

TurkeyCanada

Ireland

Japan Australia

ArgentinaUK

EgyptRussia

Swaziland

Namibia

-0.5

0.0

0.5

1.0

1.5

2.0

-12 -10 -8 -6 -4 -2 0 2

2017 - 2016 (% of GDP)

(2016, % of GDP)

Fiscal headwind that fades

Fiscal tailwind that intensifies

Fiscal tailwind that fades


16 May 2017 40

Big government’s impact on growth The role of the government, and its impact on economic development and real GDP growth is

a vast area of academic study, with many ongoing controversies. Government has a vital role

to play, providing the conditions for markets to operate (national and domestic security,

regulatory oversight of institutions providing the rule of law etc.) and the provision of ‘public

goods’ that the market is incapable of providing. Alternatively, the presence of the

government creates opportunities to extract ‘economic rents’ by creating market distortions

through the use of political access.

Named for four economists (Barro, Armey, Rahn and Scully), the inverted-U BARS curve

perceives the government first aiding growth, and then, as its presence grows, detracting

from growth on a net basis. The literature concludes that the optimal size of government

spending is between 17% and 40% of GDP, with most estimates being between 20% and

30%. Nonetheless, economists have struggled to conclusively identify a negative relationship

between increased government size and lower rates of economic growth.

We believe that the relationship is between the persistence of large government and lower

rates of economic growth. Rather than using annual pairs, as is most commonly done, we

believe it is necessary to use decade averages. Andreas Bergh & Magnus Henrekson do this

in Fig 82.

Fig 82 Cross-country correlations between growth and government size using averages over decades rather than annual values of growth and government size, OECD, 1970-2005

Note: From the research paper “Government size and implications for economic growth” by Andreas Bergh & Magnus Henrekson, 2010. Government size is measured as tax revenue over GDP. The plots are average growth for the 1970s, 1980s, 1990s and 2000-2005 against average government size in the respective periods

Source: American Enterprise Institute for Public Policy Research above, Macquarie Research, May 2017

For a final perspective, we quote from the European Central Bank (ECB) working paper

number 1399, November 2011 ‘Economic performance and government size’ by Antonio

Afonso & Joan Tovar Jalles, and from their conclusions:

Our results allow us to draw several conclusions regarding the effects on economic growth of

the size of the government: 1) there is a significant negative effect of the size of government

on growth, 2) institutional quality has a significant positive impact on the level of real GDP per

capita, 3) government consumption is consistently detrimental to output growth irrespective of

the country sample considered (OECD, emerging and developing economies); 4) moreover,

the negative effect of government size on GDP per capita is stronger at lower levels of

institutional quality, and the positive effect of institutional quality on GDP per capita is stronger

at smaller levels of government size.

Government has a

role to play

Alternatively, the

presence of the

government creates

opportunities to

extract “economic

rents” by creating

market distortions

The negative effect

of government size

on GDP per capita is

stronger at lower

levels of

institutional quality


16 May 2017 41

Financial repression for decades It would be healthier if real interest rates were broadly in line with real GDP growth.

Please see the 26 July 2016 Macq-ro insights: Financial repression for decades for more.

Real interest rates have also been moving lower progressively, from the 4% level of 1985-97.

Having moved down modestly to 3.5% over 1998 through 2001, there was a substantial slide

over 2002-06 (attributable to the ’saving surplus’ coming out of Asia), and another substantial

slide over 2010-12 (attributable to the imbalances and associated austerity inside the

Eurozone).

Our expectation is for real interest rates to stay low, as explained on the next page.

Fig 83 10-year real bond yields, G7 ex Italy, 1985-2013, quarterly, %

Note: National Bureau of Economic research (NBER) working paper “Measuring the world interest rate” by Mervyn King & David Low (2014) The US enters the sample in 1999 with the first TIPS issue.

Source: NBER above, Macquarie Research, May 2017

The chart above comes from the Mervyn King & David Low National Bureau of Economic

research (NBER) working paper ‘Measuring the world interest rate’. The authors make the

following observation about their methodology:

The ‘real rate’ requires careful definition. For most purposes the relevant concept is an ex

ante rate, which subtracts from the actual nominal rate the expected rate of inflation. Reliable

quantitative measures of inflation expectations are notoriously hard to come by and refer only

to expectations over time horizons too short to be useful for analysing saving and investment.

So in this note we use measures of real rates on government bonds that are issued with

inflation protection.

Such ex-ante measures of real rates are much less volatile than ex post rates when there are

significant and unexpected changes in inflation, as in the 1970s and 1980s, or in equilibrium

real rates, as seen more recently.

The following table provides period averages.

Fig 84 10-year real bond yields, period averages, %

1985-1989 4.27 1990-1994 4.15 1995-1999 3.88 2000-2004 2.86 2005-2009 1.85 2010-2013 0.48

Source: NBER, Macquarie Research, May 2017

Usefully, Mervyn King & David Low also provide a proxy for their G7 ex Italy real 10-year

bond yield, Fig 85. The 2026, 10-year US TIPS yield is currently around 45bp.

-1

0

1

2

3

4

5

6

1985 1987 1989 1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 2013

(%) Weighted real rate Unweighted real rate

We disagree that

record low bond

yields are signalling

a global slump

Rather, we believe

that it is a

conscious policy

choice to minimise

public debt funding

costs that began in

Japan and is

spreading to Europe

Our expectation is

for real interest

rates to stay low


16 May 2017 42

Fig 85 Unweighted 10-year real bond yields, ‘World’, versus the yield on US TIPS, 1985-2013, quarterly, %

Note: There are risks with simply using the US TIPS: 1) it includes expectations of changes in the real exchange rate of the US$, 2) in the case of the US, there is the potential of a safe haven negative risk premium

Source: NBER, Macquarie Research, May 2017

Fig 86 US TIPs yields, %

Source: US Department of the Treasury, FED, Macquarie Research, May 2017

Real interest rates to stay low

In addition to the two major global disequilibria noted above, we believe a third major factor,

financial repression, needs to be incorporated.

We believe fiscal reconstruction (reloading the fiscal policy tool weapon) using the seductive

tool of financial repression, is a conscious policy choice to minimise public debt funding costs

that began in Japan and is spreading to Europe. Budget realities are shown below.

Fig 87 G7 public debt/GDP ratios, %

2007 2016E 2020E

Gross Net Gross Net Gross Net

US 64.0 44.5 108.2 82.2 107.9 83.4 Japan 183.0 80.5 250.4 127.9 254.5 132.2 Germany 63.5 47.9 68.2 45.4 58.9 38.5 UK 42.2 37.1 89.0 80.5 84.3 75.8 France 64.4 57.7 97.2 89.2 95.9 88.0 Italy 99.8 85.9 133.2 113.8 127.5 108.9 Canada 66.8 22.1 92.1 26.9 84.6 19.6

G7 80.9 52.0 121.7 84.3 120.2 83.7 Euro area 64.9 44.9 91.7 67.4 86.2 63.7

Note. 2016 and 2020 estimates IMF. Source: IMF, Macquarie Research, May 2017

-2

-1

0

1

2

3

4

5

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

(yield, %)Treasury inflation protected securities - 5 year

Treasury inflation protected securities - 7 year



Treasury inflation protected securities - long term

In addition to the

two major global

disequilibria noted

above, we believe a

third major factor,

financial repression,

needs to be

incorporated


16 May 2017 43

We disagree that record low bond yields are signalling a global slump. Rather, we believe that

it is a conscious policy choice to minimise public debt funding costs that began in Japan and

is spreading to Europe. The principal driver of record low bond yields since 2009 has evolved

from a private sector balance sheet recession (completed in the US and Japan; ongoing, but

progressing in the Eurozone) to fiscal reconstruction (reloading the fiscal policy tool weapon)

using the seductive tool of financial repression. Japan illustrates well the pressures being

faced by policymakers.

Japan’s public debt to GDP ratio built over the 24 years 1990-2014 from around 65% to

240%. Only in 2006 and 2007 did the ratio decline. Japan’s public debt to GDP has far

exceeded the previous high in 1945, Fig 88.

Please note, however, that Japan’s public debt ratio has stabilised over the last few years.

Fig 88 Japan’s gross government debt, as a percentage of GDP

Source: IMF, Datastream, Macquarie Research, May 2017

Japan’s considerable progress over the last three years towards stabilizing its public debt to

GDP ratio can be illustrated by using the formula for the primary budget balance necessary

for stabilization: (Bond yields minus nominal GDP growth) x (Public debt/GDP)

In 2012, Japan needed a primary budget surplus of 2.4% (1% minus 0% times 2.4). Today,

thanks to the consequences of financial recession, Japan only needs a primary budget deficit

of 2.4% (zero minus 1% times 2.4) to stabilize the public debt to GDP ratio.

That’s a 4.8% of GDP swing. There is no ‘free lunch’, however.

An implicit tax on savers resulting in weak consumption

Savings behaviour is not mechanical, but the hypothesis that households smooth their

consumption by saving for retirement seems to work well in practice. Reducing the returns

on savings leads to higher required savings. The implicit tax on savings leads to weak

consumption. If consumption stagnates, companies do not invest and do not raise wages.

Achieving fiscal reconstruction with financial repression, in the context of very high (around

250% of GDP) household financial assets, has led Japan into a low growth trap.

Fig 89 Household saving rate, 1990 to latest

Source: Datastream, Macquarie Research, May 2017

0

50

100

150

200

250

1875 1885 1895 1905 1915 1925 1935 1945 1955 1965 1975 1985 1995 2005 2015

Gross government debt(as % of GDP)

Gross government debt (as % of GDP)

Bubble bursts

1936 Takahashi assassinated for trying to rein in military expenditures

(%)

1927 Takahashi first appointed Finance Minister

1936 Takahashi assassinated for trying to rein in military expenditures

-5

0

5

10

15

20

1990 1992 1995 1997 2000 2002 2005 2007 2010 2012 2015

Housholds saving rate(%, seasonally adjusted, 6m average)

Japan’s public debt

ratio has stabilised

If consumption

stagnates,

companies do not

invest and do not

raise wages

The principal driver

of record low bond

yields since 2009

has evolved to fiscal

reconstruction

(reloading the fiscal

policy tool weapon)

using the seductive

tool of financial

repression


16 May 2017 44

Housing, globally, a good news story Private sector credit growth needs to revive for central banks to end their extraordinary

support. A recovery in home loan demand could be the key driver. Home loans are on

average ~40% of total loans.

A good news story: We believe residential investment is around 4% of global GDP and will

grow between 3.5% and 4.0% pa through 2020. The latter is supported by recovery in many

advanced economies, whilst financial deepening and the upgrading of the housing stock

underpin growth in EM economies. There are exceptions.

Housing is a lead indicator and an important driver of the business cycle, as well as being

intertwined with credit growth and financial stability. Nonetheless, there is a paucity of globally

consistent data.

Fig 90 10-Advanced economies residential investment to GDP ratio

Note: 10-Advanced economies are US, Japan, Germany, France, Italy, Spain, UK, Australia, Canada, and South Korea. Source: IMF, National sources, Oxford Economics, Macquarie Research, May 2017

The 22 July 2016 Macq-ro insights: Residential investment, globally looked at residential

investment data and residential price trends across 23 countries. The key observations are

summarized below.

Fig 91 Key residential investment observations

Country

USA 10% pa real growth through 2019 would only return residential investment/GDP to the post-1970 average level

Germany & France

Germany has been recovering since 2010, whilst France is still at cyclical lows. We believe a mild recovery is beginning

Japan The Affluent Elderly is supporting renovation and reform, with the upgrading of the housing stock a major government priority

China Due to lower mortgage rates and aggressive policy relaxation, 2016 will be remembered as a year of a property up-cycle like 2013. From a long-term perspective, we believe China’s housing demand has peaked


Fig 92 Residential investment to GDP ratio for Germany and France

Source: Oxford Economics, Macquarie Research, May 2017

3.5

4.0

4.5

5.0

5.5

6.0

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

10-Total

4.0

6.0

8.0

10.0 (%) Germany residential investment - % share of GDP

France residential investment - % share of GDP

Residential

investment is

around 4% of global

GDP and will grow

3.5-4.0% pa through

2020

Recovery in many

advanced

economies...

Financial deepening

and the upgrading

of the housing stock

underpin growth in

EM economies

We looked at

residential

investment data and

residential price

trends across 23

countries


16 May 2017 45

Global banking’s broken pipes Imbalances, disequilibria lead to financial flows, with global intermediation by banks having

been associated with four major boom-bust cycles since 1980 (Latin America in the early

1980s, Japan in the late 1980s, Asia ex Japan in the late 1990s and US & Europe in the late

2000s). The 15 March 2017 Fault lines and broken pipes has more. Thus, we believe the

three major global disequilibria are interconnected:

1) The current surplus of Factory Asia; the current account deficit of the US

2) The imbalances inside the Euro (the first chart below is a proxy for this)

3) The cross-country funding ratio, Fig 94 and Fig 95: ongoing financial sector

deleveraging is driving dysfunction in the interbank lending market and the FX swap

market – these are the broken pipes.

Fig 93 Euro Target2 balances

Note: aggregate 1 consists of Germany, Luxembourg, Netherlands and Finland and aggregate 2 consists of Greece, Ireland, Italy, Portugal and Spain.

Source: Euro crisis monitor, Based on data of the ECB's Statistical Data Warehouse, Macquarie Research, May 2017

The main actors extending US$-denominated foreign claims (loans) are not US banks, the

blue shading in Fig 94, left-hand chart. With global trade and financial transactions (outside

intra-Eurozone Euro activity) being largely US$-denominated, this implies most cross-border

activity globally is being conducted with the assistance of non-US banks.

Fig 94 US$-denominated foreign positions of banks: the ‘Euro-dollar’ market

Notes: (1) Latest data at end-June 2016. (2) “Non-US banks’ US$-denominated foreign claims” and Non-US banks’ US$-denominated foreign liabilities” are calculated as US$-denominated foreign claims and liabilities of all reporting countries after excluding those of US banks, respectively. (3) “Non-US banks’ cross-currency funding ratio” is calculated as “Non-US banks’ US$-denominated foreign claims” less “Non-US banks’ US$-denominated foreign liabilities,” divided by “Non-US banks’ US$-denominated foreign claims.”

Source: BOJ, BIS, Macquarie Research, May 2017

-1200

-700

-200

300

800

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017

Aggregate 1

Aggregate 2

(bn €)

A funding gap,

usually filled

through FX-swaps


16 May 2017 46

When non-US banks extend credit, they need to find dollar funding. Since 2000, there has

always been a funding gap between their US$ assets (claims, loans) and liabilities (Fig 94

left- and right-hand charts) which is usually filled through FX-swaps. Please note:

1) The non-US banks cross-currency funding ratio has been trending up since 2000

2) The funding ratio declines sharply during financial crises – this occurs through the

sudden reduction of claims/loans, acting as an accelerant during the crisis

3) It is important that the FX-swap market functions smoothly (please see the next

page)

Beneath the surface, there have been notable shifts by bank nationality, Fig 95. Most

European banks began to shrink their balance sheets from 2008 (UK banks from 2012),

whilst US banks kept expanding until 2014. Japanese banks continue to expand.

Fig 95 Foreign claims by bank nationality, US$ trillions

Notes: (1) Latest data as at end-June 2016. (2) Euro area claims for German and French banks are excluded

Source: BOJ, BIS, Macquarie Research, May 2017

Unfortunately, the FX swap market is not working smoothly. Fragmentation of the Eurozone’s

financial system along national borders, in combination with regulatory requirements for

banks to reduce their balance sheet leverage ratios, has led to contraction of liquidity in the

money markets. Fig 96 is the US$ 3-month average cross-country basis swap for five leading

currencies in basis points.

Fig 96 US$ 3-month cross-currency basis swap – EUR / JPY/ GBP / CHF / CAD


-60

-50

-40

-30

-20

-10

0

3 mns cross-currency basis swap average bp

US banks kept

expanding until

2014

Japanese banks

continue to expand

Unfortunately, the

FX swap market is

not working

smoothly


16 May 2017 47

Global liquidity & EM credit cycles Global liquidity, as defined by the BIS, is the ease of financing by companies in international

markets.

Global liquidity moves in irregular and powerful waves, appearing to be stronger when the

US$ is depreciating, and weaker when the US$ is appreciating, chart below.

Fig 97 Cumulative flows, gross, in US$-denominated cross-border loans outside the US (US$tr): The dark shaded areas indicate depreciations in the US dollar effective exchange rate

Sources: S Avdjiev, C Koch and H S Shin “Exchange rates and foreign borrowing in international currencies” (2015, in progress); BIS effective exchange rate statistics; BIS locational banking statistics by residence. In addition to cross-border bank loans shown above, the BIS include bond issues in their total debt data

Source: BIS as noted above, Macquarie Research, May 2017

Swings in global liquidity are associated with credit booms and subsequent financial

vulnerability in emerging market economies (EMEs). Into the credit-growth contraction phase

across EMEs, we expect 2016 to see some major debt restructurings, but no cascading

cross-border banking crisis.

This will provide opportunities for well-funded MNCs. Please see the 21 January 2016

Macq-ro insights: The corporate savings “glut” & cross-border M&A.

We believe the EM private non-financial credit cycle peaked with the May-June 2013 ‘taper

tantrum’. However, the following three charts on the next page suggest that this could be

optimistic as private sector credit ratios are still increasing in most EMEs.

The distribution of debt by currency and sectors

We believe that within foreign currency denominated debt, private sector debt is more

vulnerable to destabilization than sovereign debt (the government sector), Fig 71. For more

comprehensive tables, please see the 25 January 2016 Macq-ro insights: Global liquidity.

Fig 98 Key debt ratios, % of GDP in 2015

Singapore Malaysia Thailand Indonesia China Brazil S. Korea

External debt1/GDP NA 40 NA 32 10 31 13

US$-denominated corporate debt2/GDP

NA 6 NA 12 8 9 8

Corporate debt2/GDP 82 64 51 23 157 49 105

Notes: (1): all sectors, all currencies, (2): non-financial corporate debt

Source: BIS, Macquarie Research May 2017

Chinese corporate debt is examined in the next section.

Global liquidity, as

defined by the BIS,

is the ease of

financing by

companies in

international

markets

We believe the EM

private non-financial

credit cycle peaked

with the May-June

2013 ‘taper tantrum’


16 May 2017 48

Fig 99 Private non-financial sector credit as a % of GDP: selected EMEs #1

Note: The BIS does not have data for Nigeria

Source: BIS, Macquarie Research, May 2017

Fig 100 Private non-financial sector credit as a % of GDP: selected EMEs #2

Note: The BIS does not have data for Taiwan. Japan and Korea are included as benchmarks


Fig 101 Private non-financial sector credit as a % of GDP: ASEAN

Note: The BIS does not have data for the Philippines and Vietnam


10

25

40

55

70

85

100 (% of GDP)

Turkey Poland Mexico BrazilArgentina Russia Saudi Arabia

0

50

100

150

200

250(% of GDP) Japan China India Korea

0

40

80

120

160

200 (% of GDP) Indonesia Thailand Singapore Malaysia


16 May 2017 49

Chinese corporate debt Please see Fig 72 on page 35 and Fig.98 on page 45 for context. For more details, please

see Larry Hu’s 8 June 2016 China’s debt: Myths and Realities.

It’s popular to argue that China will run into a debt crisis in either local government debt or

corporate debt. By contrast, our long-held view is that China’s debt problem is very different

from many other countries. The risk of a debt crisis is small because policy-makers could

reshuffle debt among different entities: central government, local government, SOEs and

banks. In 2015, China’s total government debt was RMB37tn, of which RMB27tn was owned

by local governments, Fig 102 and 103. Since last year, China has conducted local

government debt swaps, which essentially converts local government debt to sovereign debt.

Banks also share the costs by swapping loans to bonds, which are safe but offer lower yields.

Fig 102 Corporate leverage is high in China

Fig 103 China’s debt breakdown

Source: CEIC, Macquarie Research, May 2017 Source: CEIC, Macquarie Research, May 2017

In 2015, China’s total corporate debt was RMB106tn, or 157% of GDP. While it’s large, over

70% of China’s corporate debt is owned by SOEs. The discussion on debt/equity swap

suggests that it’s possible to transfer the SOE debt burden to governments and banks.

By doing so, the government also lowers the odds for a corporate debt crisis.

Fig 104 Annual new loans vs. interest payments Fig 105 Leverage ratio: SOE vs. private enterprises


In our view, the real risk behind China’s debt is capital misallocation, as the majority of credit

is poured to the less-efficient SOEs and local governments rather than the private sector. The

debt swap for local governments and SOEs could worsen the problem if it is not designed

well, as it could delay the exit of inefficient firms and worsen the soft budget constraints for

SOEs. Such capital misallocation could undermine China’s potential growth in the long run,

causing the country to become stuck in the so-called ‘middle-income trap’.

0

20

40

60

80

100

120

Non-financial corporate Government Households

RMB tn China's debt breakdown

SOE

Private enterprise

Local govt

Central govt

11 13 14 15 17 21 24 32 40 46 5462 70 76

2 3 3 4 5 6 79

1214

18

2125

30

1 2 2 2 23

4

6

89

10

13

15

19

2 2 2 3 45

5

6

7

7

8

9

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11

1 2 2 3 45

6

9

11

13

16

20

24

27

0

20

40

60

80

100

120

140

160

180 SOE debt

Private corporate debt

Household debt

Central governmt debt

Local government debt

RMB tn

5

10

87

89

10

12

2 23

44

56 6

0

2

4

6

8

10

12

14

20

08

20

09

20

10

20

11

20

12

20

13

20

14

20

15

Annual new loans

Loan interest payment

RMB tn

50

52

54

56

58

60

62

64

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

SOE

Private enterprise

% Industrial enterprise: Debt-to-assets ratio

Government debt

Corporate debt

Capital misallocation


16 May 2017 50

Fig 106 Gross fixed capital formation, % of GDP, 1970-2015

Source: CAO, World Bank, Macquarie Research, May 2017

During the Asian Financial Crisis, the average step-down in gross capital formation to GDP,

1996-98, for Malaysia, Thailand, Indonesia and Korea was approximately 14%. The catalyst

was a hard-stop by capital providers, cross-border bank lending. The equivalent today in

China would be a hard-stop of capital provision by the household sector, i.e. bank deposits

leaving the Chinese banking system en masse.

Fig 107 Core debt of the non-financial sectors, as a % of GDP

Level in 2014 Change since end-2007 (1)

Households Corporate Government Total Households Corporate Government Total

Advanced economies (2) 73 81 110 265 -7 1 41 36

Australia 119 77 35 230 11 -4 26 33

Canada 93 104 70 267 15 15 19 49

France 56 124 109 288 10 20 43 72

Germany 54 54 82 191 -7 -1 18 10

Italy 43 78 151 272 5 3 46 53

Japan 66 105 222 393 0 5 72 77

Spain 71 111 110 293 -10 -14 74 50

Sweden 83 165 47 295 18 27 7 52

Switzerland 120 91 34 245 13 15 -4 26

United Kingdom 87 77 107 271 -9 -11 61 41

United States 78 69 92 239 -18 -1 39 21

Eurozone 61 103 106 270 1 4 39 45

Emerging market economies (2) 30 94 44 167 10 35 4 50

Argentina (3) 6 9 43 58 2 -1 -1 -1

Brazil (4) 25 49 64 139 12 18 1 32

China 36 157 41 235 17 58 6 82

Hong Kong SAR 66 217 5 287 14 85 3 103

India 9 50 66 125 -1 8 -8 -1

Indonesia 17 23 25 64 6 8 -8 5

Korea 84 105 38 228 12 14 14 40

Malaysia (3) 69 64 53 186 15 4 13 32

Mexico 15 22 33 70 1 7 13 21

Russia (3) 20 58 18 95 8 16 9 33

Singapore 61 82 99 242 22 24 13 59

South Africa 37 33 55 125 -4 -2 23 17

Thailand 69 51 30 151 25 5 7 37

Turkey 21 33 34 108 9 28 -8 30

Notes: (1): in percentage points of GDP. (2): weighted average of the economies listed based on rolling GDP and PPP exchange rates. (3): breakdown of household and corporate debt is estimated based on bank credit data. Please note that Government debt data is the BIS core debt (credit to the government) at market values except for countries where only nominal values are available.


10

15

20

25

30

35

40

45

50 (% of GDP) Thailand Malaysia Indonesia Korea

The Asian

Financial Crisis


16 May 2017 51

Oil & sovereign defaults The last great collapse in oil and commodity prices from the end of the 1970s led to a

decade-long wave of sovereign defaults, below. The defaults data is available both by creditor

and defaulting country, below.

Fig 108 Sovereign debt default as a share of world public debt and world GDP

Source: CRAG, Macquarie Research, May 2017

Fig 109 Total sovereign debt in default, by creditor

Source: CRAG, Macquarie Research, May 2017

In the 1980s, there was a reluctance to address the fiscal deficits that resulted from less tax

revenues from lower oil and commodity prices. Fifteen countries saw an increase of public

debt to GDP in excess of 40%. With global capital markets up until 1980 consisting largely of

fixed exchange rates and national controls on capital flows, falling exports led to current

account deficits and persistent forex reserves erosion, Fig 110.

Fig 110 Foreign exchange reserves, in US$, the 1980s and now

1980 forex reserves

as a % of GDP Decline in forex reserves,

start 1980 to 1980s low End-2015 reserves

as a % of GDP

Forex reserves to GDP difference:

2015 vs 1980

Nigeria 4.9 -93% 5.9 1.0 South Africa 8.2 -79% 14.4 6.2 Argentina 3.9 -77% 4.4 0.5 Saudi Arabia 10.1 -66% 98.6 88.5 Brazil 5.8 -64% 19.8 14.0 Colombia 9.1 -64% 17.0 7.9 Indonesia 4.9 -38% 12.1 7.3 Malaysia 14.3 -23% 27.7 13.4 Venezuela 10.4 -15% 12.4 2.0

Note: The above does not include an analysis of forward book positions, which is important for sum including Brazil. Source: IMF/Oxford Economics/Haver, Macquarie Research, May 2017

0

1

2

3

4

5

6

71980

1981

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1988

1989

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1991

1992

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2003

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2012

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2014

(%) % of World Public Debt % of Gross World Product

0

100

200

300

400

500 US$bnIMF World Bank Paris Club Other official creditorsPrivate creditors FC Bank Loans FC Bonds LC Debt

Falling exports led

to current account

deficits and

persistent forex

reserves erosion

A decade-long wave

of sovereign

defaults


16 May 2017 52

Whilst this time, greater exchange rate flexibility is absorbing some of the risk related to

capital flight, Fig 111, cross-border capital account flows are enormously more important.

The decade from 2011

For countries with a high export dependency on oil and commodities, the decade from 2011

could evolve as follows:

1) A major fall in export revenues leading to a current account deficit, and the policy

decision to allow the currency to depreciate.

2) The latter could be of the order of 30-50%, chart below, causing a significant

increase in inflation, and the need for nominal local interest rates to increase.

Fig 111 Emerging Market currencies (nominal)

Note: Latest data point: 11 May 2017


3) Initially, there is a reluctance to increase policy interest rates rapidly given concerns

for economic growth, but capital outflows and an increase in sovereign risk spreads

lead to a tightening of monetary policy.

4) The fiscal position deteriorates with a fall in oil- and commodity-related taxes, and the

weakening economy. The initial reluctance to cut public expenditures is reinforced by

the tightening of monetary policy’s negative impact on economic growth, and the

escalating debt service costs.

At this point, fiscal deficits become persistent.

The ratio of public debt to GDP begins to trend higher.

The following formula gives the primary budget balance (excludes interest expense)

necessary for public debt/GDP stabilization:

(Bond yields minus nominal GDP growth) x (Public debt/GDP)

For example, 10% bond yields, nominal GDP growth of 5% and a public debt/GDP ratio of

50% would require a primary budget balance of 2.5% of GDP (a surplus).

As the public debt/GDP ratio rises over time, then the required primary budget balance

becomes bigger, e.g. at 100%, not 50%, the required primary balance would be a surplus of

5% of GDP, not 2.5% of GDP.

The last great collapse in oil and commodity prices from the end of the 1970s led to a

decade-long wave of sovereign defaults.

We believe another wave is coming, involving multiple debt restructurings over

many years.

60

80

100

120

1999 2001 2003 2005 2007 2009 2011 2013 2015

Emerging Market Currencies (nominal)

Fiscal deficits

become persistent


16 May 2017 53

What’s next for EM economies? An extended period of subdued growth: The major six emerging market economies’

aggregate real GDP growth is expected to trend around 4.6% pa 2017-20, some 2.8% pa

less than the 7.4% pa achieved over 2003-11.

Versus the ten advanced economies, the real GDP growth premium was +5.2% pa over

2003-11, falling to an expected +2.9% over 2013-18. Contributions from all three growth

accounting factors (labour supply, capital accumulation, and total factor productivity)

are fading.

Fig 112 Seven headwinds for emerging market economies since 2011

1) The headwind from falling commodity prices since 2011

2) The turn in the EME credit cycle post the 22 May 2013 to 28 June 2013 ‘Taper tantrum’

3) The deceleration in global industrial production growth since early 2014 has led to a fading of the export growth engine

4) The US$, which had been appreciating gradually since mid-2011, rose rapidly from mid-2014 through end-2015

5) Oil prices breaking decisively through US$100 from July 2014

6) Declining import volumes into China since early 2015 partially reflecting import substitution. Whilst not a net negative for EM economies initially, second round effects such as the tightening of policy by countries suffering deteriorating trade balances is a negative.

7) The start of a US Fed Funds policy interest rate up-cycle since December 2015, which puts upward pressure on nominal local rates in fixed/semi-fixed exchange rate regimes

Note: Remembering the good times: The 2009-11 commodity price boom, a weak US$ facilitating access to global capital markets and strong credit growth had enabled rapid growth to persist across the EM economies. However, over the past five years, conditions have become progressively tougher


Emerging market economies (EME) have been battered by seven negatives since 2011, table

above. Whilst some of these are abating, two new headwinds worry us: falling property values

with the credit down-cycle, and declining FDI inflows as the elevated global investment-to-GDP

ratio adjusts.

These are headwinds for consumption and investment, respectively.

Fig 113 Real residential property prices, YoY growth

Note: Housing price movements are deflated by the CPI. Aggregates are weighted by GDP in current US$. Advanced consists of 10 advanced countries (US, Japan, Germany, France, Italy, Spain, UK, Aust, Canada and South Korea) and emerging consists of 6 emerging countries (Brazil, Mexico, Russia, Turkey, India and China). 16-Total is the sum of advanced and emerging countries. ASEAN consists of 5 ASEAN countries (Indonesia, Malaysia, Singapore, Philippines and Thailand).

Source: BIS, IMF, Macquarie Research, May 2017

-12

-9

-6

-3

0

3

6

9

12

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016

(%) Advanced Emerging 16-Total ASEAN

Two new headwinds

worry us:

1) Falling

property

values with

the credit

down-cycle

2) Declining FDI

inflows as the

elevated global

investment-to-GDP

ratio adjusts

These are

headwinds for

consumption and

investment,

respectively


16 May 2017 54

Global private investment indicators This is a six-page section, as we believe that there is widespread misunderstanding about the

existing elevated level of global private investment. Given the relative volatility of private

investment, this implies that it is the major downside risk to global growth.

Lead indicators of capital expenditure

We are unaware of any composite global machinery order indicators. We present indicators

for the US, China, Germany and Japan. The overall impression is one of softness.

We believe Germany is the key series to follow, Fig 116, below (bottom), for the reasons

shown in Fig 114 and Fig 115.

On the basis of exports as a percentage of that country’s GDP, Germany is the most exposed

to emerging markets, at roughly 11.0%, Fig 114. Japan has the highest exports to GDP ratio

to China but emerging markets in total are just 7%. The US is approximately 5%.

Fig 114 Emerging Market export exposures Fig 115 Germany: Goods exports to China

Source: Oxford Economics/Haver Analytics, Macquarie Research, May 2017

Source: Oxford Economics/Haver Analytics, Macquarie Research, May 2017

Fig 116 shows trends in Germany, which are currently a little beneath zero.

Fig 116 Germany VDMA plant & machinery orders, 1999 to latest

Source: VDMA, Bloomberg, Macquarie Research, May 2017

Fig 117 is the well-known US non-defence capital goods orders (excluding aircraft). The case

for excluding aircraft orders relates to both the lumpiness of orders historically and the long

lag between order receipt and the start of work on such orders.

Energy and other commodity-related capital expenditures are expected to stay weak, but the

fall is almost complete, in our opinion.

-40%

-30%

-20%

-10%

0%

10%

20%

30%Germany Plant&Machinery Orders(YoY%, 3mma)

The overall

impression is one of

softness


16 May 2017 55

Fig 117 US non-defence capital goods orders (excluding aircraft), 2000 to latest

Source: US Census Bureau, Macquarie Research, May 2017

Japanese machinery orders are broadly stable to soft; Fig 118 and Fig 119.

For Larry Hu’s recent insights on the China business cycle, please see his Macro Monday

reports from which Fig 120 and Fig 121 come.

Fig 118 Japanese machinery orders: total (¥tr) Fig 119 ...and by geography (¥tr)

Source: CAO, Macquarie Research, May 2017 Source: CAO, Macquarie Research, May 2017

Fig 120 Chinese fiscal spending Fig 121 Chinese fixed asset investment


-30

-25

-20

-15

-10

-5

0

5

10

15

20 (YoY%, 3mma) Non-defence capital goods orders, ex aircraft

1.2

1.4

1.6

1.8

2.0

2.2

2.4

2.6

2.8

3.0

04/0

5

10/0

5

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6

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6

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7

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10/1

6

(¥tr)Machinery orders (total, SA)

0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

1.6

04/0

5

11/0

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5

05/1

6

12/1

6

Domestic Overseas

(¥tr)


16 May 2017 56

The following charts from the IMF include residential investment; 2015-16 are IMF forecasts

Please note that at the global level, private investment is already at elevated levels.

Fig 122 World investment (US$tr) Fig 123 World investment (% of current GDP)

Source: IMF WEO database, Macquarie Research, May 2017 Source: IMF WEO database, Macquarie Research, May 2017

Fig 124 Advanced economies’ investment (US$ tr)

Fig 125 Advanced economies’ investment (% of current GDP)


Fig 126 US investment (US$tr) Fig 127 US investment (% of current GDP)


0

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(US$tr) World investment

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16

(%)World investment, % of GDP

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(US$tr) Advanced economies, investment

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(%) Advanced economies, investment, % of GDP

0.0

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(US$tr) US's investment

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(%GDP) US's investment, % of GDP


16 May 2017 57

Anxiety normally revolves around China, which is the difference between a currently strong

level of world investment activity, Fig 123, and the depressing picture presented in Fig 125.

As Fig 126 and Fig 127 show, the IMF has positive 2015-16 growth forecasts for the US.

Fig 128 World investment by economic groups

Fig 129 World investment by economic groups (% of current GDP)


Fig 130 Emerging & developing economies’ investment (US$tr)

Fig 131 Emerging & developing economies’ investment (% of current GDP)


Fig 132 China’s investment (US$tr) Fig 133 China’s investment, % of GDP


0

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(US$tr) Emerging and developing economies investment

Advanced economies, investment

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35

1980

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(%) Advanced economies, investment, % of GDP

Emerging and developing economies investment, % of GDP

0

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(US$tr) Emerging and developing economies investment

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(%)

Emerging and developing economies investment, % of GDP

0.0

1.0

2.0

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6.0

1980

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(US$tr) China's investment

25

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(%GDP) China's investment, % of GDP


16 May 2017 58

Whilst China is still growing in absolute terms (Fig 132, previous page), a slow rebalancing of

the economy is underway (Fig 133). EM ex China has been stagnant, 2011-15, Fig 134.

Fig 134 Emerging and developing economies ex China investment

Fig 135 Emerging and developing economies ex China investment, % of GDP


Fig 136 India’s investment Fig 137 India’s investment, % of GDP


Fig 138 Brazil’s investment Fig 139 Brazil’s investment, % of GDP


0.0

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5.0

6.0

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(US$tr) Emerging and developing economies ex China

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(%)

Emerging and developing economies ex China, % of GDP

0.0

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(US$tr) India's investment

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(%GDP) India's investment, % of GDP

0.0

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(US$tr) Brazil's investment

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(%GDP) Brazil's investment, % of GDP


16 May 2017 59

Fig 140 Russia’s investment Fig 141 Russia’s investment, % of GDP


Fig 142 Indonesia’s investment Fig 143 Indonesia’s investment, % of GDP

Source: IMF WEO database, Macquarie Research, April 2017 Source: IMF WEO database, Macquarie Research, May 2017

Fig 144 Investment by World ex China

Fig 145 Investment by World ex China, % of GDP


0.0

0.1

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1980

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(US$tr) Russia's investment

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2018

2020

(%GDP) Russia's investment, % of GDP

0.00

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0.35

1980

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(US$tr) Indonesia's investment

0

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(%GDP) Indonesia's investment, % of GDP

0

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198

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(US$tr)

Investmet by World ex China

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198

0

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(% GDP)

Investment by World ex China, % of GDP


16 May 2017 60

FDI, following the smart money Gross capital flows to EM economies are likely to remain under pressure during the US Fed’s

tightening cycle. Macquarie forecasts the latter to last into 2019. Contracting since 1Q 2015,

the blue portion in Fig 146, is a proxy for the global liquidity cycle. The red portion is FDI, and

we expect a 40% shrinkage in total global FDI flows from the 2015 high through 2018.

Fig 146 Emerging Market economies: Gross capital flows

Note: Other investment includes cross-border bank lending and international debt issues

Source: Oxford Economics, Haver Analytics, Macquarie Research, May 2017

The 11 January 2017 Macq-ro insights: following the new smart money identified four key FDI

trends that are expected to persist over the next three years:

1) A 40% shrinkage of inward FDI from the 2015 high. UNCTAD estimates that 2016

saw a 10-15% decline

2) Relative strength in flows to advanced economies versus EM economies

3) Pronounced strength in flows to India versus China, reflecting absolute growth and

material YoY declines respectively

4) Pronounced weakness in FDI flows to commodity-exporting economies

Fig 147 FDI flows, total and greenfield only for the US and China, US$bn

Note: Inward FDI data is Oxford Economics and the greenfield data series is from UNCTAD.

Source: UNCTAD, Oxford Economics, Macquarie Research, May 2017

-2%

0%

2%

4%

6%

8%

10%

1995 1998 2001 2004 2007 2010 2013 2016

Portfolio investmentOther investmentDirect investment

% of combined GDP

0

50

100

150

200

250

300

350

400 US Inward FDI China Inward FDI

US Greenfield China Greenfield(in bnUS$)

The new smart

money is

disengaging from

China


16 May 2017 61

Local factors determine core inflation One popular perspective holds a global view of inflation – that global slack determines local

inflation. However, there is significant evidence that local conditions drive underlying inflation.

For example, Fig 148 shows that divergence in CPI-services for the US and the Eurozone.

Of personal consumption expenditures in advanced economies, three-quarters is on services.

Fig 148 A dramatic divergence between the US and Euro area services inflation


We believe Fig 149 explains the confusion. Currently, the average pair-wise correlation on

core inflation measures is near zero, and near 40-year lows. At the same time, the average

pair-wise correlation on headline inflation measures is as elevated today as during the first oil

shock of the early 1970s. From late 2014 until February 2016 oil prices plunged 80%.

Fig 149 International synchronisation of inflation (headline and core)

Notes: From Bank of England Governor, Mark Carney’s speech at the 2015 Jackson Hole symposium: Inflation in a globalised world. Average pair-wise rolling (15 years) correlation of seasonally-adjusted quarterly headline and core inflation. Source: OECD, Global Financial Data, DataStream, National sources, and Bank Staff calculation

Source: BoE, Macquarie Research, May 2017

We believe that core inflation is driven locally, through the influence of local output gaps and

the slack in the local labour market.

The US: The services CPI for the US, shown in Fig 148, reflects the acceleration in US wage

growth, following six years of employment growth above labour force growth, and the

unemployment rate approaching full employment.

The Eurozone: Conversely, the tightening of fiscal policy in the Eurozone over 2011-13 and

a second credit crunch there during 2011-12 leaves the Eurozone approximately four years

behind the US in the business cycle.

0%

1%

2%

3%

4%

5%

1998 2000 2002 2004 2006 2008 2010 2012 2014 2016

1998-2011 correl = +0.47 2012-16 correl = -0.55

Services CPI

US

Euro area

We believe that core

inflation is driven

locally, through the

influence of local

output gaps and the

slack in the local

labour market

Of personal

consumption

expenditures in

advanced

economies, three-

quarters is on

services


16 May 2017 62

Income shares: from labour to capital To the benefit of capital, there has been a 5% decline in the labour share globally since 1980,

Fig 150.

We believe the main driver has been technology, facilitated by globalisation with MNCs as the

main agents of change. As a consequence, MNCs have been the major beneficiaries.

Fig 150 Declining global labour share: 0.65 means 65%

Note: Loukas Karabarbounis & Brent Neiman, The global decline of the labour share, June 2013. “The figure shows year fixed effects from a regression of corporate and overall labour shares that also include country fixed effects to account for entry and exit during the sample. The regressions are weighted by corporate gross value added and GDP measured in U.S. dollars at market exchange rates. We normalize the fixed effects to equal the level of the global labour share in our dataset in 1975”

Source The global decline of the labour share above, Macquarie Research, May 2017

MNCs are a global macro dimension needing attention. The last 30 years have seen the

emergence of global oligopolistic competition. Following waves of M&A activity, the top MNCs

now dominate their global markets, entrenching their position by undertaking the vast proportion

of R&D in their industries. The result is the control of leading technologies and brands.

We believe one consequence of global oligopolistic competition is to limit the diffusion of new

techniques and labour productivity growth across the economy.

Fig 151 Labour productivity growth: the issue of diffusion

Note: Each line shows the average labour productivity (value added per worker). The “Top 5%” and “Top 100” are the globally most productive firms in each two-digit industry. “Non-frontier firms” is the average of all firms, excluding the Top 5%. Included industries are manufacturing and business services, excluding the financial sector. The coverage of firms in the dataset varies across the 24 countries in the sample and is restricted to firms with at least 20 employees. Source: OECD preliminary results based on Andrews, D., C. Criscuolo and P. Gal (2016), “Mind the Gap: Productivity Divergence between the Global Frontier and Laggard Firms”, OECD Productivity Working Papers, forthcoming; Orbis data of Bureau van Dijk Source: OECD, Macquarie Research, May 2017

We believe one

consequence of

global oligopolistic

competition is to

limit diffusion of

new techniques,

labour productivity

growth across the

economy

The last 30 years

have seen the

emergence of global

oligopolistic

competition

We believe the main

driver has been

technology,

facilitated by

globalisation with

MNCs as the main

agents of change

There has been a

5% decline in the

labour share

globally since 1980


16 May 2017 63

The corporate savings ‘glut’ Savings-Investment balances, net lending/borrowing by sector, the net acquisition of financial

assets (NAFA) are terms used interchangeably in the literature.

The corporate sector in most advanced economies is running a savings-investment surplus.

We believe this is an unintended by-product of the monetary policy response to credit bubble/

busts that transfers income from the household sector to the corporate sector: the lowering of

policy interest rates to near zero and the flattening of the yield curve.

The corporate sector in Japan is a representative example. Japan’s data go back to 1994,

just far enough to capture the swing from net investing (borrowing) to net saving (lending),

below. Looking at the numbers:

The ¥35.4tr swing over 1994-2013 from annual net borrowing (-¥2.0bn) to net lending

(¥33.4bn, pale red highlights) compares to reduced interest payments of ¥28.6tr (from

¥32.2bn to ¥3.6bn, blue highlights).

We’ve also highlighted (in orange) how the surplus of gross fixed capital formation over

consumption of fixed capital has shrunk from ¥11.9tr in 1994 to ¥2.0tr in 2013.

In turn, this narrowing of ¥9.9tr reflects a gradual upward drift in the consumption of fixed

capital charge (¥2.7tr) and a marked fall in gross fixed capital formation (¥7.2tr).

Dividend payments increased from ¥4.6tr in 1994 to ¥15.1tr in 2013, for an increase over the

period of ¥10.5tr.

So rather than paying interest, non-financial corporations have paid down net debt.

Rather than growing their fixed capital base, non-financial corporations have paid out

dividends.

Fig 152 Non-financial corporations’ flow of funds (¥tr), 1994 to latest available (2014)

CY 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

Gross fixed capital formation 72.9 74.5 75.6 81.1 74.7 70.6 74.2 71.0 64.6 65.3 66.3

Consumption of fixed capital 61.0 59.5 60.2 63.3 64.9 64.0 63.7 63.6 63.3 61.8 61.8 changes in inventories -1.4 1.6 2.2 2.5 1.4 -3.5 -0.5 -0.1 -1.9 -0.4 1.7 purchases of land, net -7.7 3.9 -3.1 0.5 -0.2 -0.3 9.3 5.7 -4.9 3.7 -1.8 Net lending/net borrowing -2.0 -13.7 -2.5 -8.3 22.3 9.3 3.4 3.8 28.4 21.5 29.8 Net saving -3.7 1.7 6.7 8.3 5.2 11.7 17.3 13.2 19.7 24.0 31.4 Net capital transfers 4.5 5.0 5.2 4.3 28.1 0.4 5.6 3.7 3.3 4.3 2.7 Interest payable 32.2 28.8 23.8 21.9 17.3 13.9 12.1 9.4 7.0 6.3 5.3 Dividends

4.6 5.1 5.2 5.2 5.0 5.6 4.8 5.3 7.1 6.8 9.3

CY

Gross fixed capital formation 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 Consumption of fixed capital 66.3 69.2 73.4 76.9 74.8 62.2 61.2 62.6 64.8 65.3 66.3 changes in inventories 61.8 62.2 64.4 66.5 68.6 67.7 65.0 63.4 62.8 61.8 61.8 purchases of land, net 1.7 0.5 -0.5 1.7 2.9 -5.2 1.1 -1.7 -0.9 -0.4 1.7 Net lending/net borrowing -1.8 -8.7 -0.1 5.1 3.8 5.3 -0.6 5.8 0.2 3.7 -1.8 29.8 32.0 17.7 13.1 12.5 29.9 39.3 27.4 33.5 21.5 29.8 Net saving Net capital transfers 31.4 28.0 24.0 28.1 23.3 22.1 33.0 27.2 31.6 24.0 31.4 2.7 2.8 2.1 2.1 2.1 2.5 3.0 3.5 3.3 4.3 2.7 Interest payable Dividends 5.3 4.6 4.9 5.8 5.1 4.8 4.7 4.2 3.7 6.3 5.3

Source: CAO, ESRI, CEIC, Datastream, Macquarie Research May 2017

The corporate savings ‘glut’: variations by geography

Fig 153 presents the US data. In the case of the US, below, the weakness of investment post

the TMT Bubble (1998-2001) led to a small corporate surplus over the years 2002-05. The

post Global Financial Cycle corporate Saving-Investment surpluses, however, have been

much more substantial, 2-3% versus 1%. The corporate surplus calculation used in Fig 153 is

net of both dividend payments and share buy-back activity.

The corporate

sector in most

advanced

economies is

running a savings-

investment surplus

… an unintended

by-product of the

monetary policy

response to credit

bubble/busts that

transfers income

from the household

sector to the

corporate sector

The US


16 May 2017 64

Fig 153 Net lending of US non-financial corporations

Note: Savings (the blue line) is calculated as the undistributed profits of non-financial corporations, that is after-tax profits less dividends to shareholders. Investment (the red line) represents spending by non-financial companies on capital formation. Any excess of savings over investment represents net lending to the rest of the economy, the black bars at the bottom of the charts. More precisely:

Source: Gruber, Joseph W., and Steven B. Kamin (2015). The Corporate Saving Glut in the Aftermath of the Global Financial Crisis International Finance Discussion Papers 1150, Macquarie Research, May 2017

Japan is as has been indicated earlier: A rapid growth in gross saving since the 1987-1991

bubble-bust, and a trend decline in gross investment. The trend decline in investment in

Japan began a decade earlier in Japan than in the USA (1991 versus 2001). The post-GFC

corporate Saving-Investment surplus has averaged 5%.

Germany has seen similar trends, a trend increase in gross savings, a trend decrease in

gross investment, but the latter could be described two ways: either as a very mild downtrend

since 1991, or broadly sideways until the Global Financial Crisis, and then a step-decline

thereafter. However, the German corporate sector surplus is less than 1%.

The trends are far from uniform. Canada has seen a trend improvement in gross savings,

but gross investment has been broadly stable. The UK does not appear to have experienced

a trend improvement in gross savings, but a trend decline in gross investment has occurred.

Both Canada and UK do have corporate sector surpluses, of 1-2%.

However, since 1990, the corporate sectors in both France and Italy have had persistent

deficits of 2-3%. As a consequence, a weighted average of the corporate Saving-Investment

balances for the three euro-zone majors of Germany, France and Italy is mildly negative.

We believe the above is facilitating global cross-border M&A, which in 2015 was 40% above

its previous high of 2007. We expect 2016 to be another year of intense cross-border M&A,

with the trend towards global oligopolistic competition amongst MNCs continuing.

Fig 154 Total & cross-border M&A, 2007 to latest

Total M&A (US$bn) Cross-border M&A (US$bn) % of cross-border M&A to

total M&A Global Japan Global Japan Global Japan

2007 2391.6 111.7 1050.3 52.4 43.9 46.9 2008 1398.9 138.2 569.4 87.1 40.7 63.1 2009 1033.3 85.2 286.5 38.4 27.7 45.1 2010 1369.9 82.0 551.6 51.7 40.3 63.0 2011 1465.8 139.1 556.2 94.5 37.9 67.9 2012 1405.4 123.5 598.8 89.6 42.6 72.5 2013 1489.5 78.1 468.0 62.1 31.4 79.6 2014 2400.9 71.9 1203.5 58.3 50.1 81.2 2015 3429.4 127.3 1368.9 102.8 39.9 80.7

2016 2880.5 143.5 1270.7 115.3 44.1 80.4

Note: Data for Japan from RECOF. Cross-border for Japan is both In-Out and Out-In.

Source: FactSet, RECOF, Macquarie Research, May 2017

Japan

Germany

Canada, U.K.

France and Italy

We expect 2016 to

be another year of

intense cross-

border M&A


16 May 2017 65

Global income distribution Income gains have varied markedly over the 20 years since 1988, Fig 155. The relative winners

have been ‘the top 1%’ and the one-fifth of the world’s population in the 40th to 60th percentile

range. In nine out of ten cases, the latter live in the emerging Asia economies of China, India,

Thailand, Vietnam and Indonesia, and are around the median income earners in their countries.

Whilst they are often referred to in the media as the “emerging global middle class” they are still

economically below the lower middle class of the rich nations, as commonly understood.

Fig 155 Relative gain in real per capita income by global income level, 1988-2008

Note: World Bank Economic Review, Lakner, Christoph & Branko Milanovic, 2015, Global income distribution: From the fall of the Berlin Wall to the great Recession. The following notes come from the book Global inequality by Branko Milanovic:

This graph shows relative (percentage) gain in household per capita income (measured in 2005 international dollars) between 1988 and 2008 at different points of the global income distribution (ranging from the poorest five percentiles, 0 to 5, to the richest global percentile, at 100). Real income gains were greatest around the 50th percentile of the global income distribution (the median; at point A) and among the richest (the top 1%; at point C). They were lowest among people who were around the 80th percentile globally (point B), most of whom are in the lower middle class of the rich world

Source: World Bank above, Macquarie Securities, May 2017

The relative losers are the lower middle class of the rich nations, who cluster around the 80th

percentile, point B above. As a consequence estimates of global income distribution have

shown declined inequality, but increased inequality in advanced economies such as the US.

Please note that US inequality is currently much lower than global inequality.

Fig 156 Global and US inequality, 1820-2011

Note: This graph shows global and US income inequalities (calculated across world and US citizens, respectively). In the recent period, global inequality is decreasing while US inequality is going up.

Sources: Milanovic Branko: Global inequality, page 124, with the 2003, 2008 and 2013 estimates and the 2035 forecast for global inequality from the paper The future of worldwide income distribution, April 2015, by Tomas Hellebrandt and Paolo Mauro

Source: Various as noted above, Macquarie Research, May 2017

0

10

20

30

40

50

60

70

80

90

100

0 10 20 30 40 50 60 70 80 90 100

Cum

ulat

ive

gain

in re

al i

ncom

e (in

%)

Ventile/percentile of global income distribution

A

B

C

30

35

40

45

50

55

60

65

70

75

1800 1850 1900 1950 2000 2050

US inequality Global (B-M series) Global (L-M series) Global (H-M series)

The relative winners

have been ‘the top

1%’ and the one-fifth

of the world’s

population in the

40th to 60th

percentile range

The relative losers

are the lower middle

class of the rich

nations, who cluster

around the 80th

percentile

As a consequence

estimates of global

income distribution

have shown

declined inequality,

but increased

inequality in

advanced

economies such as

the US

Please note that US

inequality is

currently much

lower than global

inequality


16 May 2017 66

Demographic Tectonics

Fig 157 Key Demographic Tectonic reports so far have included:

a) China – A V-shaped age profile

b) ASEAN – The rise of ASEAN affluence

c) Japan – Aging Japan it’s wonderful (the Affluent Elderly)

d) India – The young and restless

e) Global consumption – Global implications for the apparel & footwear industries


To take the example of the Affluent Elderly, for those that have prepared well for retirement,

this demographic cluster has both the cash-flow and the time to be a prime consumer. One

example is Japan. The Affluent Elderly are approximately 20% of Japan’s population, and

30% of annual consumption. Their total income in 2015, US$1tr, makes them equal to about

half the size of Italian GDP, and unlike Italy, Japan’s Affluent Elderly is still a growth story.

Fig 158 Japan’s Affluent Elderly: a massive market that will continue to grow

Persons, by household head age and income bracket (millions) 2005 2015 2025 2025 vs 2015

65+ with income $50,000 to $120,000 13.3 18.4 20.0 +1.6

65+ with income $120,001 plus 3.0 5.0 5.7 +0.7

Affluent Elderly households’ total 16.3 23.4 25.7 +2.3

Affluent Elderly households’ total

household income (US$ billions) 629 1,022 1,223 +201

Note: The total income of the above affluent elderly in 2015 at US$1tr makes them equal to about half the size of Italian GDP. Source: Global Demographics Ltd, Macquarie Research, May 2017

This group are consumers of premium services and goods: a) luxury brands, b) increased

quality of living through the progressive upgrading in the unit size of dwellings and the overall

building and furnishing standards; and c) increased wellness & health expenditures –

increased expenditures on wellbeing, covering everything from skin care and nutritional

supplements through to medical expenses.

The global labour supply

This is a demographic headwind.

Fig 159 Global changes in working age populations (2025 less 2015)

Note: To calculate working age population we have used the definition of 15-64 years for economies including Africa, Central & South America, Developing Asia, India, North Africa & Middle East and South Asia. For the rest, we have used the definition of 15-74 years to calculate working age population, as the life expectancy in these countries is higher.

Source: Global Demographics, Macquarie Research, May 2017

100

5344 39 35

2814

1 0

-1 -5

-29

-60

-20

20

60

100

140

Ind

ia

No

rth

Afr

ica

& M

idd

le E

as

t

Afr

ica

Develo

pin

g A

sia

So

uth

Asia

Ce

ntr

al

& S

outh

Am

erica

No

rth

Am

eri

ca

We

ste

rn E

uro

pe

Ru

ss

ia

Easte

rn E

uro

pe

Aff

lue

nt

As

ia

Ch

ina

Persons mn

Affluent Elderly

demographic

opportunities


16 May 2017 67

The world’s working age population is now growing quite modestly, Fig 159. An extra 260m

over a decade on 4.6bn is approximately 0.5% pa. Please note the divergence in working age

populations, 2025 versus 2015, for India and China.

Fig 160 shows the impact of labour retirement ages.

Fig 161 shows the ongoing fade in growth of the working population in EM economies.

Fig 160 Global population & labour supply Fig 161 Annual growth in the working population

Note: from the December 2015, Bank of England staff working paper No. 571, Secular drivers of the global real interest rate by Lukasz Rachel and Thomas D Smith. Black lines shows growth in the global working aged 20 to retirement. Retirement ages are calculated using OECD data on average effective retirement ages. Over the future, global retirement ages are assumed to grow by one and a half years every decade to keep pace with expected rises in longevity

Source: UN population projections, OECD, Macquarie Research, May 2017

Source: Oxford Economics, Macquarie Research, May 2017

The US labour supply

One of David Doyle’s key themes has been lower potential growth for the United States, of

around 1.4 pa, with US labour force growth only able to provide 0.4% pa of that over the long-

term. Combining shifting demographic trends with current participation rates allows David to

compute a measure “breakeven jobs growth”. This is the number of jobs an economy needs

to create in order to keep unemployment from rising. For 2020, for the US, this is only 45,000

per month: 8 March 2017 Fortress America: Demographics, lower potential, and the Fed.

Fig 162 The downward trend in breakeven jobs growth is poised to resume


0

20

40

60

80

100

120

140

160

180

Jan-86 Jan-90 Jan-94 Jan-98 Jan-02 Jan-06 Jan-10 Jan-14 Jan-18 Jan-22

US monthly "breakeven" jobs growth (five year average) (thousands)

Note: This analysis holds constant current (Jan-17) age group participation rates over time and assumes a 4.5%

unemployment rate

projection

US potential growth

of around 1.4 pa,

with US labour force

growth only able to

provide 0.4% pa of

that over the long-

term


16 May 2017 68

The charts below extend the analysis to Europe, Japan and China.

We believe the trends have largely gone unnoticed in recent years because of spare capacity

that was created in the economic downturn of 2007-9. But as that slack has nearly dissipated,

particularly in the US, it means that economies are likely to confront the issue of very weak (if

not negative) labour force growth in coming years.

While US labour force growth will be low (+0.4% per annum), the dynamics are even more

severe in other major economies.

Without a jump in age group participation rates, labour forces in will shrink through 2030:

1) Japan (-0.6% p.a.)

2) Europe (-0.5% p.a.)

3) China (-0.1% p.a.)

Fig 163 US breakeven jobs growth has been nearly cut in half since 2010 and is set to fall further ...

Fig 164 … the decline in breakeven jobs in China is poised to become more severe


Fig 165 In Europe, breakeven jobs growth is set to move increasingly into negative territory

Fig 166 … while in Japan it has stabilized (albeit in negative territory)


113

149

121

110

75

60

41

31

0

20

40

60

80

100

120

140

160

180

1990-95 1995-00 2000-05 2005-10 2010-15 2015-20 2020-25 2025-30

US - monthly breakeven jobs growth (estimate in thousands)

Note: Assumes constant age group participation rates over time (Jan-17 US

rates)

954895

988

647

396

38

-138

-281

-500

-300

-100

100

300

500

700

900

1100

1990-95 1995-00 2000-05 2005-10 2010-15 2015-20 2020-25 2025-30

China - monthly breakeven jobs growth (estimate in thousands)

Note: Assumes constant age US age group participation rates have been used, but have

been upwardly adjusted by 12.5% (the amount that China's 15 & over participation rate exceeds the US 15 & over participation rate)

98

73 73

50

-49

-76

-101-113

-150

-100

-50

0

50

100

150

1990-95 1995-00 2000-05 2005-10 2010-15 2015-20 2020-25 2025-30

Europe- monthly breakeven jobs growth (estimate in thousands)

Note: Assumes constant age group participation rates over time (Europe 2016

rates )

31

16

-1

-19

-33-31

-27

-35-40

-30

-20

-10

0

10

20

30

40

1990-95 1995-00 2000-05 2005-10 2010-15 2015-20 2020-25 2025-30

Japan- monthly breakeven jobs growth (estimate in thousands)

Note: Assumes constant age group participationrates over time (2016 Japan rates)

While US labour

force growth will be

low (+0.4% per

annum), the

dynamics are even

more severe in

other major

economies


16 May 2017 69

Demographics and productivity growth For the past 2.5 years we have held the view that the major significant driver of low

productivity growth was demographic forces. This is a topic we addressed in Demographics,

productivity, and wage growth and our conclusion is supported by a broad range of academic

evidence.

An NBER working paper published in 2016 The Effect of population aging on economic

growth, the labour force, and productivity (Maestas et. al) provides further support for our

conclusion. The paper uses variation in the rate of population ageing across US states and

finds that “a 10% increase in the fraction of the population aged 60+ decreases the growth

rate of GDP per capita by 5.5%. Two-thirds of this reduction is due to slower growth in the

labour productivity of workers across the age distribution, while one-third arises from slower

labour force growth”.

The drag on productivity from demographics comes from two channels. First is the aging

channel. Individuals that are 55+ are less likely to improve their productivity, this acts as a

drag on productivity growth when this group is growing as a share of the workforce. Second is

the retirement channel. This means workers with several years of experience are replaced

with those with little to no experience, creating a further productivity drag.

Fig 167 Productivity growth has been very low for the past six years

Source: BLS, Macquarie Research, May 2017

Fig 168 Worker wages tend to rise steadily until the mid-40s, before stabilizing and then declining

Fig 169 Annual wage gains by age group are an approximation for productivity growth

Source: BLS, Macquarie Research, May 2017 Source: BLS, Macquarie Research, May 2017

0

1

2

3

4

1995 2000 2005 2010 2015

US - nonfarm business sector labor productivit y (annual % change)

avg:1995-2010 = 2.5%

avg: 2011-2016 = 0.5%

0

200

400

600

800

1000

16-19 20-24 25-34 35-44 45-54 55-64 65+

Median usual weekly earnings of full-timewage and salary workers (US$)

-2%

-1%

0%

1%

2%

3%

4%

5%

6%

20-24 25-34 35-44 45-54 55-64 65+

Estimated annual wage gains by age group (%)

The drag on

productivity from

demographics

comes from two

channels:

First is the aging

channel: individuals

that are 55+ are less

likely to improve

their productivity,

this acts as a drag

on productivity

growth when this

group is growing as

a share of the

workforce

Second is the

retirement channel:

This means workers

with several years

of experience are

replaced with those

with little to no

experience, creating

a further

productivity drag


16 May 2017 70

The Long Grinding Cycle continues We believe the pace of the current expansion should continue to prove to be structurally

lower than in previous cycles, as fiscal reconstruction, demographic factors, low productivity

growth and sub-optimal global policy making are likely to remain as headwinds.

Fig 170 shows data since 1999, breaking real GDP growth down into contributing parts:

labour, “capital deepening” (labour quality, non-IT capital, IT capital) and total factor

productivity (TFP) growth. Fig 171 provides more detail on TFP.

Fig 170 Contributions of sources of growth to aggregate GDP growth, 1999-2015

GDP Growth Labour Labour Quality Non-IT Capital IT Capital TFP Growth

World

99-06 4.2 0.6 0.2 1.8 0.6 0.9 07-13 3.3 0.2 0.1 2.4 0.5 0.1 2013 3.0 0.3 0.1 2.2 0.4 0.0 2014 3.2 0.6 0.1 2.1 0.3 0.0 2015 2.7 0.6 0.1 2.0 0.3 -0.3

Mature

99-06 3.0 0.3 0.3 1.2 0.7 0.5 07-13 1.1 -0.1 0.1 0.9 0.5 -0.3 2013 1.2 0.1 0.1 0.7 0.4 -0.1 2014 2.0 0.8 0.1 0.8 0.4 -0.1 2015 2.3 0.8 0.1 0.8 0.4 0.1

Emerging

99-06 5.6 0.9 0.1 2.6 0.4 1.6 07-13 5.4 0.6 0.1 3.8 0.4 0.4 2013 4.4 0.5 0.1 3.4 0.3 0.1 2014 4.1 0.4 0.1 3.3 0.3 0.0 2015 3.1 0.4 0.1 3.0 0.3 -0.7

United States

99-06 3.3 0.4 0.2 1.4 0.9 0.5 07-13 1.1 -0.1 0.1 0.8 0.5 -0.2 2013 1.6 0.7 0.1 0.8 0.4 -0.5 2014 2.6 1.1 0.1 0.9 0.4 0.1 2015 2.7 1.2 0.1 0.9 0.4 0.1

Japan

99-06 1.6 -0.4 0.4 0.7 0.7 0.1 07-13 0.6 -0.4 0.1 0.3 0.5 0.1 2013 1.5 0.0 0.1 0.3 0.3 0.7 2014 0.2 0.2 0.1 0.4 0.3 -0.8 2015 1.0 0.2 0.2 0.3 0.3 -0.1

Euro Area

99-06 2.3 0.5 0.2 1.1 0.4 0.1 07-13 0.2 -0.3 0.1 0.6 0.3 -0.7 2013 -0.3 -0.8 0.1 0.3 0.2 -0.2 2014 0.9 0.4 0.1 0.3 0.2 -0.2 2015 1.7 0.7 0.1 0.4 0.3 0.2

China

99-06 8.7 0.5 0.2 5.0 0.8 2.3 07-13 8.3 0.2 0.1 6.3 0.4 1.3 2013 6.2 0.2 0.1 5.5 0.2 0.2 2014 6.0 0.2 0.1 5.3 0.3 0.1 2015 4.1 0.2 0.1 4.8 0.2 -1.3

India

99-06 6.6 1.4 0.1 4.1 0.8 0.1 07-13 7.2 0.1 0.1 4.9 1.5 0.6 2013 6.1 0.5 0.1 3.5 1.2 0.9 2014 6.8 0.7 0.1 3.4 1.0 1.6 2015 7.0 0.8 0.1 3.3 0.9 1.9

Brazil

99-06 2.9 1.1 0.1 1.3 0.2 0.1 07-13 3.7 0.6 0.2 1.9 0.1 0.9 2013 2.7 0.2 0.2 2.0 0.1 0.2 2014 0.1 0.5 0.2 1.6 0.1 -2.2 2015 -3.9 0.1 0.2 0.7 0.0 -5.0

Source: The Conference Board Summary Table, Macquarie Research, May 2017

Fiscal

reconstruction,

demographic factors,

low productivity

growth and sub-

optimal global policy

making are likely to

remain as headwinds

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Fig 171 Growth of total factor productivity (TFP) per annum, %, aggregates weighted by GDP in current US$ shares

Country Name 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Advanced US 0.3 -0.1 0.3 0.4 0.5 0.2 -0.2 -0.2 -0.4 -0.1 0.7 -0.1 0.0 -0.2 0.0 0.0 Japan 0.1 -0.2 0.0 0.0 0.2 0.0 0.0 0.1 -0.1 -0.5 0.6 -0.1 0.1 0.1 -0.1 0.0 Germany 0.1 0.1 0.0 -0.1 0.0 0.1 0.1 0.1 -0.1 -0.4 0.2 0.2 0.0 0.0 0.0 0.0 France 0.1 0.0 0.1 0.0 0.0 0.0 0.1 0.0 -0.1 -0.2 0.1 0.0 -0.1 0.0 -0.1 0.0 Italy 0.1 0.0 -0.1 -0.1 0.0 0.0 0.0 0.0 -0.1 -0.3 0.1 0.0 -0.1 0.0 0.0 0.0 Spain 0.0 0.0 0.0 0.0 -0.1 -0.1 0.0 0.0 -0.1 -0.1 0.0 0.0 0.0 0.0 0.0 0.0 UK 0.1 0.0 0.0 0.1 0.0 0.0 0.1 0.0 -0.2 -0.2 0.0 0.1 -0.1 0.0 0.0 0.0 Australia 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.1 0.0 0.0 0.0 0.0 Canada 0.0 0.0 0.0 0.0 0.0 0.0 0.0 -0.1 -0.1 -0.1 0.0 0.0 0.0 0.0 0.0 0.0 S. Korea 0.0 0.0 0.1 0.0 0.1 0.1 0.1 0.1 0.0 0.0 0.1 0.1 -0.1 0.1 0.0 0.0

10-advanced total 0.8 -0.2 0.4 0.3 0.6 0.3 0.1 -0.1 -1.2 -1.8 1.7 0.0 -0.3 -0.1 -0.1 0.0

Emerging Brazil 0.3 -0.1 0.1 -0.2 0.3 0.1 0.2 0.5 0.2 -0.1 0.5 0.0 -0.1 0.0 -0.3 -0.5 Mexico 0.6 -0.5 -0.6 -0.1 0.1 -0.2 0.2 0.0 -0.3 -0.5 0.0 0.1 0.0 -0.1 0.0 0.0 Russia 0.6 0.4 0.3 0.7 0.7 0.7 0.9 0.9 0.6 -0.7 0.4 0.4 0.3 0.2 0.1 -0.3 Turkey 0.3 -0.4 0.3 0.2 0.3 0.1 0.0 0.0 -0.2 -0.4 0.2 0.1 -0.1 0.0 0.0 0.0 India 0.0 -0.1 0.1 0.0 -0.2 0.2 0.2 0.1 0.0 -0.1 0.3 0.1 0.0 0.1 0.2 0.2 China (Official) 0.8 0.8 0.6 1.3 1.2 1.6 1.6 2.4 1.3 0.4 0.9 1.0 0.3 0.4 0.3 0.8

6-EM Total 2.7 0.2 0.8 2.0 2.4 2.5 3.1 3.7 1.5 -1.4 2.3 1.6 0.4 0.6 0.2 0.1

16-Total 1.0 -0.1 0.4 0.6 0.9 0.6 0.6 0.7 -0.6 -1.7 1.9 0.5 -0.1 0.1 0.0 0.1

Other Indonesia 0.9 0.2 0.9 1.0 0.4 1.0 0.7 -0.2 0.5 0.1 0.7 0.7 0.6 0.5 0.3 0.5 Malaysia 1.1 -0.2 0.6 0.6 0.7 0.7 0.5 0.7 0.2 -0.8 0.2 0.2 0.0 -0.2 0.1 0.0 Singapore 0.8 -1.1 0.5 0.8 1.5 1.1 0.8 0.7 -0.6 -0.5 1.0 0.2 -0.3 -0.1 -0.1 0.2 Philippines 0.8 0.0 0.2 0.1 0.5 0.1 0.4 0.5 0.0 -0.2 0.3 -0.2 0.4 0.3 0.3 0.3 Thailand 0.5 0.4 0.9 1.0 0.6 0.3 0.3 0.4 -0.2 -0.8 0.9 -0.5 0.8 0.3 0.0 0.2

ASEAN 5-Total 4.2 -0.7 3.1 3.4 3.6 3.2 2.7 2.2 -0.1 -2.2 3.1 0.4 1.4 0.7 0.6 1.3

China (alternative) 1.9 1.5 2.8 1.1 1.7 4.8 4.5 4.7 -2.3 0.9 5.2 1.2 -1.1 0.2 0.1 -1.3

Note: estimated as a Tornqvist index

Source: The Conference Board, IMF, Macquarie Research, May 2017

Fig 172 China’s total factor productivity (TFP) per annum, %, 1995-2015, adjusted version

Country 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

China (Alternative) 2.8 1.0 1.7 -5.5 0.4 1.9 1.5 2.8 1.1 1.7 4.8 4.5 4.7 -2.3 0.9 5.2 1.2 -1.1 0.2 0.1 -1.3 China (Official) 5.1 3.8 3.4 1.6 1.4 2.4 2.0 1.7 3.2 3.2 4.3 4.4 6.2 3.0 0.8 2.0 2.1 0.6 0.8 0.6 1.2


The Conference board provides an explanation of the methodological differences between the old and new series here: https://www.conference-board.org/retrievefile.cfm?filename=FAQ-for-China-GDP-vs4_10nov15.pdf&type=subsite. “The Maddison-Wu approach, which the Conference Board has adopted, reconstructs aggregate real GDP growth from the bottom-up, on a sector-by-sector basis. The biggest adjustments are for the industrial sector and the so-called “non-material services” sector, which includes banking & financing, real estate, professional services, education, healthcare, culture & entertainment services, and government services. We argue that the upward bias in the published GDP numbers in China is attributable to two sources: (1) a ‘misreporting effect” which accounts for about two-thirds of the upward bias; and (2) a “price effect” which accounts for the remaining one third. The price effect includes the adjustment for the “non-material services” sector, where the Conference Board has introduced judgemental labour productivity growth estimate of 1% pa 1982-91 and 2% from 1992 onwards – in line with common experience at China’s level of development. In contrast, the official data has 6% pa growth on average.”

Source: The Conference Board, Macquarie Research, May 2017


16 May 2017 72

TFP is the increase in the overall efficiency in production, reflecting innovation and the

adoption of new technologies.

However, TFP growth has been very weak recently. TFP in the US has fallen from 0.9% pa

2000-07 to 0.5% pa 2010-14 to zero pa 2013-14, Fig 173.

Fig 173 Growth of total factor productivity (TFP), per annum, %

2000-07 2010-14 2013-14 2013-14 minus 2000-07

Brazil 0.3 -0.9 -1.6 -1.9 Mexico -0.3 -0.7 -1.7 -1.4 Russia 5.3 2.2 0.4 -4.9 Turkey 0.3 -0.3 -1.9 -2.2 India 1.4 1.3 0.6 -0.8 China – old methodology 4.8 1.1 0.2 -4.6 China – new methodology 2.1 -1.3 -2.4 -4.5

US 0.9 0.5 0.0 -0.9


Source: The Conference Board, IMF, Macquarie Research, May 2017

This decline of 0.9% pa 2013-14 versus 2000-07 has been exceeded by all the major EM

economies with the exception of Turkey (-0.8% pa). Russia and China have seen TFP per

annum declines 2013-14 versus 2000-07 of over 4%. For a more extensive discussion,

please see the 19 April 2016: The Global Macro Outlook – The long grinding cycle,

pages 41-58. Fig 174 provides a decomposition of our global growth expectations.

Fig 174 Global growth and components, per annum, %, 2016-20

Labour supply

growth Capital

deepening TFP Total

Advanced economies 0.2 0.8 0.5 1.5

EM economies 0.8 2.3 1.0 4.0

Global 0.4 1.4 0.7 2.5

Note: Macquarie estimates. Weights used: advanced economies 0.6, EM economies 0.4. Pale red shading: most vulnerable, highest downside risk. Blue shading: most upside risk, in our opinion


Our real GDP growth forecasts by country are shown in Fig 85, which shows the aggregates

out to 2020. The long grinding cycle continues.

Fig 175 Real GDP growth for ten advanced economies and six emerging market economies, in current US$: The long grinding cycle continues

Note: Global real GDP growth (10-Advanced & 6-Emerging) is forecast to be 2.2% in 2016, 2.6% in 2017, and 2.7% in 2018. Macquarie forecasts where available. Please see Fig 176 and Fig 177 for the constituents & weights used. The above uses market exchange rates. Using PPP weights would boost the numbers by about 0.5-0.6% pa

Source: IMF, World Bank, OECD, Macquarie Research, May 2017

-6

-4

-2

0

2

4

6

8

10

12

2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 2020

Advanced Emerging 16-Total(%)

Russia and China

have seen TFP per

annum declines

2013-14 versus

2000-07 of over 4%

The long grinding

cycle continues

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Fig 176 GDP in current US$ for 10-Advanced countries and 6-Emerging market economies. Also for the 5-ASEAN majors

Country Name

2000 % of total

2001 % of total

2002 % of total

2003 % of total

2004 % of total

2005 % of total

2006 % of total

2007 % of total

2008 % of total

2009 % of total

2010 % of total

2011 % of total

2012 % of total

2013 % of total

2014 % of total

2015 % of total

10-advanced countries (GDP in trillion)

US 10.3 38% 10.6 40% 11.0 40% 11.5 37% 12.3 36% 13.1 35% 13.9 35% 14.5 33% 14.7 31% 14.4 32% 15.0 30% 15.5 29% 16.2 29% 16.8 30% 17.3 30% 17.9 32%

Japan 4.7 18% 4.2 16% 4.0 14% 4.3 14% 4.7 13% 4.6 12% 4.4 11% 4.4 10% 4.8 10% 5.0 11% 5.5 11% 5.9 11% 6.0 11% 4.9 9% 4.6 8% 4.1 7%

Germany 1.9 7% 1.9 7% 2.1 7% 2.5 8% 2.8 8% 2.9 8% 3.0 8% 3.4 8% 3.7 8% 3.4 8% 3.4 7% 3.8 7% 3.5 6% 3.7 7% 3.9 7% 3.4 6%

France 1.4 5% 1.4 5% 1.5 5% 1.8 6% 2.1 6% 2.2 6% 2.3 6% 2.7 6% 2.9 6% 2.7 6% 2.6 5% 2.9 5% 2.7 5% 2.8 5% 2.8 5% 2.4 4%

Italy 1.1 4% 1.2 4% 1.3 5% 1.6 5% 1.8 5% 1.9 5% 1.9 5% 2.2 5% 2.4 5% 2.2 5% 2.1 4% 2.3 4% 2.1 4% 2.1 4% 2.1 4% 1.8 3%

Spain 0.6 2% 0.6 2% 0.7 3% 0.9 3% 1.1 3% 1.2 3% 1.3 3% 1.5 3% 1.6 3% 1.5 3% 1.4 3% 1.5 3% 1.4 2% 1.4 2% 1.4 2% 1.2 2%

UK 1.5 6% 1.5 6% 1.7 6% 1.9 6% 2.3 7% 2.4 7% 2.6 7% 3.0 7% 2.8 6% 2.3 5% 2.4 5% 2.6 5% 2.6 5% 2.7 5% 3.0 5% 2.8 5%

Australia 0.4 2% 0.4 1% 0.4 1% 0.5 2% 0.6 2% 0.7 2% 0.7 2% 0.9 2% 1.1 2% 0.9 2% 1.1 2% 1.4 3% 1.5 3% 1.6 3% 1.5 2% 1.3 2%

Canada 0.7 3% 0.7 3% 0.8 3% 0.9 3% 1.0 3% 1.2 3% 1.3 3% 1.5 3% 1.5 3% 1.4 3% 1.6 3% 1.8 3% 1.8 3% 1.8 3% 1.8 3% 1.6 3%

S. Korea 0.6 2% 0.5 2% 0.6 2% 0.7 2% 0.8 2% 0.9 2% 1.0 3% 1.1 3% 1.0 2% 0.9 2% 1.1 2% 1.2 2% 1.2 2% 1.3 2% 1.4 2% 1.4 2%

(Advanced) 23.3 87% 23.1 87% 23.9 86% 26.6 86% 29.4 85% 30.9 84% 32.4 82% 35.0 79% 36.7 77% 34.8 76% 36.3 74% 38.8 71% 39.0 71% 39.1 69% 39.8 68% 38.0 68%

6-emerging market economies (GDP in trillion)

Brazil 0.6 2% 0.6 2% 0.5 2% 0.6 2% 0.7 2% 0.9 2% 1.1 3% 1.4 3% 1.7 3% 1.6 4% 2.1 4% 2.5 5% 2.2 4% 2.2 4% 2.4 4% 1.8 3%

Mexico 0.7 3% 0.7 3% 0.7 3% 0.7 2% 0.8 2% 0.9 2% 1.0 2% 1.0 2% 1.1 2% 0.9 2% 1.1 2% 1.2 2% 1.2 2% 1.3 2% 1.3 2% 1.1 2%

Russia 0.3 1% 0.3 1% 0.3 1% 0.4 1% 0.6 2% 0.8 2% 1.0 2% 1.3 3% 1.7 3% 1.2 3% 1.5 3% 1.9 4% 2.0 4% 2.1 4% 2.0 3% 1.3 2%

Turkey 0.3 1% 0.2 1% 0.2 1% 0.3 1% 0.4 1% 0.5 1% 0.5 1% 0.6 1% 0.7 2% 0.6 1% 0.7 1% 0.8 1% 0.8 1% 0.8 1% 0.8 1% 0.7 1%

India 0.5 2% 0.5 2% 0.5 2% 0.6 2% 0.7 2% 0.8 2% 0.9 2% 1.2 3% 1.2 3% 1.4 3% 1.7 3% 1.8 3% 1.8 3% 1.9 3% 2.0 3% 2.1 4%

China 1.2 4% 1.3 5% 1.5 5% 1.6 5% 1.9 6% 2.3 6% 2.7 7% 3.5 8% 4.5 10% 5.0 11% 5.9 12% 7.3 13% 8.2 15% 9.2 16% 10.4 18% 10.9 19%

(Emerging) 3.5 13% 3.6 13% 3.8 14% 4.3 14% 5.1 15% 6.1 16% 7.2 18% 9.1 21% 10.9 23% 10.7 24% 13.1 26% 15.5 29% 16.3 29% 17.5 31% 18.9 31% 17.9 31%

Total 26.9 26.7 27.7 30.9 34.5 37.0 39.6 44.1 47.5 45.5 49.4 54.3 55.3 56.7 58.7 55.9

5-Asean Countries (GDP in trillion)

Indonesia 0.2 30% 0.2 30% 0.2 33% 0.2 35% 0.3 34% 0.3 34% 0.4 36% 0.4 36% 0.5 37% 0.5 39% 0.8 42% 0.9 43% 0.9 43% 0.9 41% 0.9 40% 0.9 40%

Malaysia 0.1 17% 0.1 17% 0.1 17% 0.1 16% 0.1 16% 0.1 17% 0.2 16% 0.2 16% 0.2 17% 0.2 15% 0.3 14% 0.3 15% 0.3 14% 0.3 14% 0.3 15% 0.3 14%

Singapore 0.1 17% 0.1 17% 0.1 15% 0.1 14% 0.1 15% 0.1 15% 0.1 15% 0.2 15% 0.2 14% 0.2 14% 0.2 13% 0.3 13% 0.3 13% 0.3 13% 0.3 14% 0.3 14%

Philippines 0.1 15% 0.1 14% 0.1 14% 0.1 12% 0.1 12% 0.1 12% 0.1 12% 0.1 12% 0.2 12% 0.2 12% 0.2 11% 0.2 11% 0.3 12% 0.3 12% 0.3 13% 0.3 14%

Thailand 0.1 22% 0.1 22% 0.1 21% 0.2 22% 0.2 22% 0.2 22% 0.2 22% 0.3 21% 0.3 21% 0.3 20% 0.3 19% 0.4 18% 0.4 18% 0.4 19% 0.4 18% 0.4 18%

5-ASEAN 0.6 100 0.5 100 0.6 100 0.7 100 0.8 100 0.8 100 1.0 100 1.2 100 1.4 100 1.4 100 1.8 100 2.1 100 2.2 100 2.2 100 2.2 100 2.1 100

Note: The GDP trillions numbers are to one decimal point, so rounding plays an important part in the ASEAN part of the table


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Fig 177 Real GDP growth (annual %), totals weighted by GDP in current US$ shares, Macquarie where available (shaded in grey)

Country Name 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Advanced US 1.9 -0.1 3.6 2.7 4.0 2.7 3.8 4.5 4.5 4.7 4.1 1.0 1.8 2.8 3.8 3.3 2.7 1.8 -0.3 -2.8 2.5 1.6 2.2 1.7 2.4 2.6 1.6 2.1 2.0 1.6 1.5

Japan 5.6 3.3 0.8 0.2 0.9 1.9 2.6 1.6 -2.0 -0.2 2.3 0.4 0.3 1.7 2.4 1.3 1.7 2.2 -1.0 -5.5 4.7 -0.5 1.7 1.4 0.0 1.2 1.0 0.9 0.7 0.8 0.4 Germany 5.7 5.0 1.5 -1.0 2.5 1.8 0.9 1.9 1.8 1.8 3.2 1.8 0.0 -0.7 0.7 0.9 3.9 3.4 0.8 -5.6 4.0 3.7 0.7 0.6 1.6 1.5 1.7 1.4 1.4 1.3 1.3 France 2.9 1.0 1.6 -0.6 2.3 2.1 1.4 2.3 3.6 3.4 3.9 2.0 1.1 0.8 2.8 1.6 2.4 2.4 0.2 -2.9 2.0 2.1 0.2 0.6 0.6 1.3 1.3 1.3 1.6 1.7 1.8 Italy 2.1 1.5 0.8 -0.9 2.2 2.3 1.3 1.8 1.6 1.6 3.7 1.8 0.2 0.2 1.6 1.0 2.0 1.5 -1.1 -5.5 1.7 0.6 -2.8 -1.7 -0.3 0.8 0.8 0.9 1.1 0.9 0.9 Spain 3.8 2.5 0.9 -1.3 2.3 4.1 2.4 3.9 4.5 4.7 5.1 4.0 2.9 3.2 3.2 3.7 4.2 3.8 1.1 -3.6 0.0 -1.0 -2.6 -1.7 1.4 3.2 3.1 2.2 1.9 1.9 1.8 UK 0.7 -1.1 0.4 2.5 3.9 2.5 2.5 3.1 3.2 3.3 3.7 2.7 2.4 3.5 2.5 3.0 2.5 2.6 -0.6 -4.3 1.9 1.5 1.3 1.9 3.1 2.2 1.8 1.7 1.4 1.6 1.7

Australia 1.5 -1.1 2.7 4.0 4.9 3.0 4.3 4.3 4.6 4.3 3.2 2.5 4.0 3.0 4.1 3.2 2.7 4.5 2.6 1.8 2.3 2.7 3.6 2.0 2.7 2.4 2.5 2.3 2.8 3.0 3.0 Canada 0.2 -2.1 0.9 2.7 4.5 2.7 1.6 4.3 3.9 5.2 5.2 1.8 3.0 1.8 3.1 3.2 2.6 2.1 1.0 -3.0 3.1 3.1 1.7 2.2 2.5 0.9 1.4 2.0 1.3 1.2 1.1 S. Korea 9.8 10.4 6.2 6.8 9.2 9.6 7.6 5.9 -5.5 11.3 8.9 4.5 7.4 2.9 4.9 3.9 5.2 5.5 2.8 0.7 6.5 3.7 2.3 2.9 3.3 2.6 2.9 2.5 2.6 2.5 2.4

10-Total 3.7 1.4 1.6 2.0 2.9 2.5 2.7 2.4 0.0 -3.6 2.9 1.5 1.4 1.2 1.8 2.1 1.6 1.8 1.7 1.5 1.4 Emerging Brazil -4.2 1.0 -0.5 4.7 5.3 4.4 2.2 3.4 0.3 0.5 4.4 1.4 3.1 1.1 5.8 3.2 4.0 6.1 5.1 -0.1 7.5 3.9 1.9 3.0 0.1 -3.8 -3.3 0.5 1.5 2.0 2.0 Mexico 5.2 4.2 3.5 2.3 4.7 -5.8 5.9 7.0 4.7 2.7 5.3 -0.6 0.1 1.4 4.3 3.0 5.0 3.1 1.4 -4.7 5.1 4.0 4.0 1.4 2.2 2.5 2.1 2.3 2.6 2.9 3.0 Russia n/a n/a n/a -8.7 -12.7 -4.1 -3.6 1.4 -5.3 6.4 10.0 5.1 4.7 7.3 7.2 6.4 8.2 8.5 5.2 -7.8 4.5 4.0 3.5 1.3 0.7 -3.7 -0.8 1.1 1.2 1.5 1.5 Turkey 9.3 0.9 6.0 8.0 -5.5 7.2 7.0 7.5 3.1 -3.4 6.8 -5.7 6.2 5.3 9.4 8.4 6.9 4.7 0.7 -4.8 9.2 8.8 2.1 4.2 3.0 4.0 3.3 3.0 3.2 3.3 3.5 India 5.5 1.1 5.5 4.8 6.7 7.6 7.6 4.1 6.2 8.5 4.0 4.9 3.9 7.9 7.8 9.3 9.3 9.8 3.9 8.5 10.3 6.6 5.6 6.6 7.2 7.2 7.4 6.9 7.7 7.5 7.5 China 3.9 9.2 14.3 13.9 13.1 11.0 9.9 9.2 7.8 7.6 8.4 8.3 9.1 10.0 10.1 11.3 12.7 14.2 9.6 9.2 10.6 9.5 7.9 7.8 7.3 6.8 6.8 6.5 5.6 5.4 5.8

6-Total 6.5 3.9 5.3 6.5 7.9 7.8 8.9 9.6 6.2 3.8 8.8 7.1 5.7 5.7 5.2 4.6 4.9 5.1 4.8 4.8 5.0

16-Total 4.1 1.7 2.1 2.7 3.7 3.4 3.8 3.9 1.4 -1.8 4.5 3.1 2.7 2.6 2.9 2.9 2.7 2.9 2.7 2.6 2.6

ASEAN Indonesia 9.0 8.9 6.5 8.0 7.5 8.2 7.8 4.7 -13.1 0.8 5.0 3.6 4.5 4.8 5.0 5.7 5.5 6.3 7.4 4.7 6.4 6.2 6.0 5.6 5.0 4.9 5.0 5.2 5.1 5.0 4.9 Malaysia 9.0 9.5 8.9 9.9 9.2 9.8 10.0 7.3 -7.4 6.1 8.7 0.5 5.4 5.8 6.8 5.0 5.6 6.3 4.8 -1.5 7.5 5.3 5.5 4.7 6.0 5.0 4.2 4.5 4.5 4.4 4.3 Singapore 10.0 6.7 7.1 11.5 10.9 7.0 7.5 8.3 -2.2 6.1 8.9 -1.0 4.2 4.4 9.5 7.5 8.9 9.1 1.8 -0.6 15.2 6.2 3.7 4.7 3.3 1.9 2.0 2.0 2.3 2.2 2.1

Philippines 3.0 -0.6 0.3 2.1 4.4 4.7 5.8 5.2 -0.6 3.1 4.4 2.9 3.6 5.0 6.7 4.8 5.2 6.6 4.2 1.1 7.6 3.7 6.7 7.1 6.2 5.9 6.8 6.1 6.3 6.0 5.8 Thailand 11.6 8.4 9.2 8.7 8.0 8.1 5.7 -2.8 -7.6 4.6 4.5 3.4 6.1 7.2 6.3 4.2 5.0 5.4 1.7 -0.7 7.5 0.8 7.2 2.7 0.8 2.9 3.2 3.3 3.2 3.1 3.0

5-ASEAN 6.1 2.2 4.8 5.5 6.5 5.4 5.9 6.6 4.6 1.5 8.1 4.8 5.9 5.0 4.3 4.3 4.4 4.4 4.4 4.3 4.2

Note: Totals are weighted by the respective year ‘GDP in current US$’ weights from Fig 176. 2016-20 use 2015 weights.


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Fig 178 CPI, YoY, forecasts Macquarie where available (shaded in grey), totals weighted by GDP in current US$ shares

Country Name 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020

Advanced US 5.4 4.2 3.0 3.0 2.6 2.8 2.9 2.3 1.6 2.2 3.4 2.8 1.6 2.3 2.7 3.4 3.2 2.9 3.8 -0.4 1.6 3.2 2.1 1.5 1.6 0.1 1.3 2.5 2.4 2.4 2.4 Japan 3.0 3.3 1.7 1.3 0.7 -0.1 0.1 1.8 0.7 -0.3 -0.7 -0.8 -1.3 0.2 0.0 -0.3 0.2 0.1 1.4 -1.3 -0.7 -0.3 0.0 0.4 2.8 0.8 -0.1 0.3 0.5 0.9 1.3 Germany 5.1 4.4 2.7 1.7 1.4 1.9 0.9 0.6 1.5 2.0 1.4 1.0 1.7 1.5 1.6 2.3 2.6 0.3 1.1 2.1 2.0 1.5 0.8 0.2 1.2 1.5 1.6 1.8 1.9 France 3.4 3.2 2.4 2.1 1.7 1.8 2.0 1.2 0.6 0.5 1.7 1.6 1.9 2.1 2.1 1.7 1.7 1.5 2.8 0.1 1.5 2.1 2.0 0.9 0.6 0.1 1.0 1.1 1.3 1.5 1.7 Italy 6.5 6.3 5.1 4.5 4.0 5.2 4.0 2.0 2.0 1.7 2.5 2.8 2.5 2.7 2.2 2.0 2.1 1.8 3.4 0.8 1.5 2.7 3.0 1.2 0.2 0.2 0.7 1.0 1.1 1.2 1.3 Spain 6.7 5.9 5.9 4.6 4.7 4.7 3.6 2.0 1.8 2.3 3.4 3.6 3.1 3.0 3.0 3.4 3.5 2.8 4.1 -0.3 1.8 3.2 2.4 1.4 -0.2 -0.3 0.9 1.0 1.2 1.4 1.5 UK 7.0 7.5 4.3 2.5 2.0 2.7 2.5 1.8 1.6 1.3 0.8 1.2 1.3 1.4 1.3 2.0 2.3 2.3 3.6 2.2 3.3 4.5 2.8 2.6 1.5 0.0 0.7 2.7 2.2 1.7 1.8 Australia 7.3 3.2 1.0 1.8 1.9 4.6 2.6 0.3 0.9 1.5 4.5 4.4 3.0 2.8 2.3 2.7 3.5 2.3 4.4 1.8 2.8 3.4 1.8 2.4 2.5 1.5 1.3 2.1 1.7 2.5 2.0 Canada 4.8 5.6 1.5 1.8 0.2 2.2 1.6 1.6 1.0 1.7 2.7 2.5 2.3 2.8 1.9 2.2 2.0 2.1 2.4 0.3 1.8 2.9 1.5 0.9 1.9 1.1 1.5 1.5 2.0 2.0 2.0 S. Korea 8.6 9.3 6.3 4.7 6.3 4.5 4.9 4.4 7.5 0.8 2.3 4.1 2.8 3.5 3.6 2.8 2.2 2.5 4.7 2.8 3.0 4.0 2.2 1.3 1.3 0.7 1.0 1.8 1.6 1.8 2.0

10-Total 2.1 2.0 1.3 1.8 2.0 2.3 2.4 2.2 3.2 0.0 1.4 2.5 1.8 1.4 1.5 0.3 1.0 1.9 1.9 2.0 2.0 Emerging Brazil 2948 432.8 951.6 1928 2076 66.0 15.8 6.9 3.2 4.9 7.0 6.8 8.5 14.7 6.6 6.9 4.2 3.6 5.7 4.9 5.0 6.6 5.4 6.2 8.9 8.9 6.3 5.2 5.0 4.8 4.6 Mexico 26.7 22.7 15.5 9.8 7.0 35.0 34.4 20.6 15.9 16.6 9.5 6.4 5.0 4.5 4.7 4.0 3.6 4.0 5.1 5.3 4.2 3.4 4.1 3.8 4.0 2.8 3.0 3.0 3.0 3.0 3.0 Russia 874.6 307.6 197.5 47.7 14.8 27.7 85.7 20.8 21.5 15.8 13.7 10.9 12.7 9.7 9.0 14.1 11.7 6.9 8.4 5.1 6.8 7.8 15.8 8.6 7.3 5.0 4.0 4.0 Turkey 60.3 66.0 70.1 66.1 106.3 88.1 80.3 85.7 84.6 64.9 54.9 54.4 45.0 25.3 10.6 10.1 9.6 8.8 10.4 6.3 8.6 6.5 8.9 7.5 8.9 7.4 7.0 6.5 6.5 6.5 6.5 India 9.0 13.9 11.8 6.4 10.2 10.2 9.0 7.2 13.2 4.7 4.0 3.7 4.4 3.8 3.8 4.2 6.1 6.4 8.4 10.9 12.0 8.9 9.3 10.9 6.7 4.9 5.0 4.5 5.1 5.0 5.0 China 3.1 3.5 6.3 14.6 24.2 16.9 8.3 2.8 -0.8 -1.4 0.3 0.7 -0.8 1.2 3.9 1.8 1.5 4.8 5.9 -0.7 3.3 5.4 2.7 2.6 1.5 1.5 2.2 2.5 2.5 2.5 2.5

6 -Total 9.4 7.9 6.6 6.9 5.7 5.2 4.5 5.6 7.6 3.9 5.5 6.3 4.5 4.8 4.3 8.6 7.9 7.6 7.4 7.2 7.1

16-Total 3.0 2.8 2.0 2.5 2.5 2.8 2.7 2.9 4.2 0.9 2.5 3.6 2.6 2.4 2.4 2.9 3.2 3.7 3.6 3.6 3.7 ASEAN Indonesia 7.8 9.4 7.5 9.7 8.5 9.4 8.0 6.2 58.4 20.5 3.7 11.5 11.9 6.6 6.2 10.5 13.1 6.4 9.8 4.8 5.1 5.4 4.3 6.4 6.5 6.4 3.5 4.2 4.3 4.3 4.3 Malaysia 2.6 4.4 4.8 3.5 3.7 3.5 3.5 2.7 5.3 2.7 1.5 1.4 1.8 1.0 1.5 3.0 3.6 2.0 5.4 0.6 1.7 3.2 1.7 2.1 2.1 2.1 2.1 2.8 2.6 2.5 2.5 Singapore 3.5 3.4 2.3 2.3 3.1 1.7 1.4 2.0 -0.3 0.0 1.4 1.0 -0.4 0.5 1.7 0.4 1.0 2.1 6.5 0.6 2.8 5.3 4.5 2.4 -0.4 -0.5 -0.5 1.0 1.4 1.5 1.5 Philippines 12.7 18.5 8.6 6.9 8.4 6.7 7.5 5.6 9.3 5.9 4.0 5.3 2.7 2.3 4.8 6.5 5.5 2.9 8.3 4.2 3.8 4.6 3.2 3.0 1.4 1.4 1.8 2.8 3.3 3.0 3.0 Thailand 5.9 5.7 4.1 3.3 5.0 5.8 5.8 5.6 8.0 0.3 1.6 1.6 0.7 1.8 2.8 4.5 4.6 2.2 5.5 -0.8 3.3 3.8 3.0 2.2 -0.8 -0.9 0.2 1.7 2.0 2.0 2.0

5-ASEAN 2.5 5.0 4.7 3.2 3.8 5.9 7.1 3.7 7.5 2.4 3.8 4.7 3.6 4.0 2.9 2.8 1.9 2.9 3.1 3.1 3.1

Note: On the above data, for advanced countries the CPI increases at 1.8% pa1999-2020, emerging economies 5.3% and the 16-Total 2.6%. Brazil’s inflation 1990-1994 has been rounded to the nearest percent.

For advanced countries the GDP deflator increases at 1.5% pa1999-2014, emerging economies 6.8% and the 16-Total 2.5%

Source: World Bank, IMF, Macquarie Research, May 2017

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Fig 179 G20 real GDP growth softened over 3Q and 4Q 2015, YoY based on quarterly data

2011 2012 2013 2014 2015 2016

Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4 Q1 Q2 Q3 Q4

G20 4.8 4.4 3.9 3.5 3.5 3.2 3.0 2.7 2.8 3.1 3.4 3.7 3.7 3.4 3.3 3.4 3.4 3.5 3.3 3.1 3.0 3.0 2.9 ..

Argentina 9.1 5.2 5.6 4.3 0.6 -3.6 -1.3 0.2 1.4 5.4 2.8 0.1 -1.2 -2.5 -4.0 -2.4 0.4 3.2 4.1 2.9 0.3 -3.3 -3.5 ..

Australia 1.9 2.5 3.1 3.1 4.5 3.9 3.3 2.9 2.0 2.1 2.0 2.3 3.1 3.0 2.8 2.4 2.5 2.0 2.4 2.6 2.5 3.1 1.9 2.4

Brazil 5.1 4.8 3.6 2.6 1.6 1.0 2.5 2.5 2.5 4.1 2.8 2.6 3.3 -0.3 -0.6 -0.3 -1.9 -2.9 -4.5 -5.8 -5.4 -3.6 -2.9 ..

Canada 3.1 2.8 3.5 3.1 2.4 2.6 1.4 0.7 1.7 2.0 2.6 3.6 2.5 2.9 2.6 2.2 1.9 0.7 0.8 0.4 1.3 1.1 1.4 1.9

China 10.2 9.9 9.4 8.7 8.1 7.6 7.5 8.1 7.9 7.6 7.9 7.7 7.4 7.5 7.1 7.2 7.0 7.0 6.9 6.8 6.7 6.7 6.7 6.8

France 2.8 2.1 1.9 1.6 0.4 0.3 0.2 0.0 0.0 0.9 0.7 0.9 0.9 0.4 0.7 0.6 1.3 1.2 1.1 1.2 1.2 1.1 0.9 1.2

Germany 5.6 3.6 3.3 2.4 1.0 0.9 0.7 0.2 -0.4 0.5 0.7 1.6 2.3 1.3 1.1 1.6 1.1 1.8 1.7 1.3 1.8 1.7 1.7 1.8

India 9.8 8.5 5.3 4.7 4.2 4.3 6.2 5.8 6.1 6.5 6.3 6.9 6.8 7.1 7.4 7.1 7.3 7.5 7.3 7.5 7.9 7.2 7.2 7.2

Indonesia 6.3 6.2 6.2 6.0 6.1 6.1 6.0 5.9 5.7 5.6 5.5 5.4 5.2 5.0 4.9 4.8 4.8 4.8 4.9 5.0 5.0 5.1 5.0 4.9

Italy 2.0 1.5 0.5 -1.1 -2.2 -3.2 -3.2 -2.8 -2.8 -2.1 -1.3 -0.7 0.3 0.3 0.0 0.1 0.4 0.6 0.6 0.9 1.0 0.8 1.0 1.0

Japan 0.7 -0.8 -0.4 0.1 2.7 2.9 0.1 0.3 0.5 1.9 3.0 2.7 2.7 -0.3 -1.0 -0.3 -0.0 1.7 2.1 1.2 0.3 0.9 1.0 1.6

Korea 4.8 3.7 3.4 2.9 2.6 2.4 2.1 2.1 2.2 2.7 3.2 3.5 3.9 3.5 3.3 2.7 2.4 2.2 2.8 3.1 2.8 3.2 2.6 2.3

Mexico 4.2 3.7 4.2 4.2 3.9 4.5 3.3 3.4 3.1 0.7 1.6 1.1 1.1 3.0 2.3 2.7 -2.6 -4.3 -3.5 -3.6 2.3 1.5 2.0 2.4

Russia 3.3 4.2 4.0 4.6 5.3 4.3 3.1 1.8 0.6 1.1 1.2 2.1 0.6 1.1 0.9 0.2 -2.8 -4.5 -3.7 -3.8 -1.2 -0.6 -0.4

Saudi Arabia 10.0 11.2 13.5 5.6 8.5 6.7 4.9 1.7 0.2 1.9 3.7 4.9 6.1 3.6 2.4 2.6 3.2 4.8 4.0 2.0 1.5 1.4 .. ..

South Africa 3.9 3.8 2.9 2.6 2.1 2.4 2.4 2.0 2.0 2.1 2.2 3.0 2.2 1.4 1.6 1.4 2.3 1.6 1.1 0.2 -0.6 0.7 0.7 ..

Turkey 11.5 11.5 11.6 9.9 6.3 4.9 3.7 4.3 7.9 9.8 9.3 7.0 8.2 2.8 4.0 5.7 3.5 7.0 6.5 7.3 4.5 4.2 -1.5 ..

United Kingdom 2.3 1.3 1.2 1.3 1.2 1.0 1.8 1.3 1.5 2.1 1.7 2.4 2.6 3.1 3.1 3.5 2.8 2.4 1.8 1.7 1.6 1.7 2.0 2.0

United States 1.9 1.7 1.2 1.7 2.8 2.5 2.4 1.3 1.3 1.0 1.7 2.7 1.6 2.4 2.9 2.5 3.3 3.0 2.2 1.9 1.6 1.3 1.7 1.9

European Union (28 countries) 2.8 1.8 1.5 0.7 -0.1 -0.4 -0.5 -0.7 -0.6 0.1 0.5 1.2 1.6 1.5 1.6 1.8 2.1 2.2 2.1 2.1 1.8 1.8 1.9 1.9

Euro area (19 countries) 2.8 1.8 1.4 0.5 -0.5 -0.8 -1.0 -1.1 -1.2 -0.4 0.0 0.7 1.3 1.0 1.1 1.3 1.8 2.0 1.9 2.0 1.7 1.6 1.8 1.7

Note: all data from the OECD with the exception of the pale green highlighted numbers which come from National Statistics sources

Aggregates above use PPP weights. Using market exchange rates would reduce the G20 real GDP growth numbers by 0.5-0.6%

“The G7 was established in 1976 as an informal forum of seven major industrial economies: Canada, France, Germany, Italy, Japan, the United Kingdom and the United States of America. It was re-named the G8 after the entry of Russia in 1998. In March 2014, the G7 voted to suspend Russia in response to escalating tensions with Ukraine that led to Russia's annexation of Crimea. However, the suspension is designed to be temporary. Where the G7 seeks agreement on current economic issues based on the interests of those countries, the G20 reflects the wider interests of both industrial and emerging-market economies. The G20 is made up of the finance ministers and central bank governors of 19 countries: Argentina, Australia, Brazil, Canada, China, France, Germany, India, Indonesia, Italy, Japan, Mexico, Russia, Saudi Arabia, South Africa, South Korea, Turkey, the United Kingdom, the United States of America” - plus the EU (Source: the Telegraph newspaper)

Source: OECD, Macquarie Research, May 2017


16 May 2017 77

Important disclosures:

Recommendation definitions

Macquarie - Australia/New Zealand

Outperform – return >3% in excess of benchmark return Neutral – return within 3% of benchmark return Underperform – return >3% below benchmark return Benchmark return is determined by long term nominal GDP growth plus 12 month forward market dividend yield

Macquarie – Asia/Europe Outperform – expected return >+10% Neutral – expected return from -10% to +10% Underperform – expected return <-10%

Macquarie – South Africa Outperform – expected return >+10% Neutral – expected return from -10% to +10% Underperform – expected return <-10%

Macquarie - Canada

Outperform – return >5% in excess of benchmark return Neutral – return within 5% of benchmark return Underperform – return >5% below benchmark return

Macquarie - USA Outperform (Buy) – return >5% in excess of Russell 3000 index return Neutral (Hold) – return within 5% of Russell 3000 index return Underperform (Sell)– return >5% below Russell 3000 index return

Volatility index definition*

This is calculated from the volatility of historical price movements. Very high–highest risk – Stock should be

expected to move up or down 60–100% in a year – investors should be aware this stock is highly speculative. High – stock should be expected to move up or down at least 40–60% in a year – investors should be aware this stock could be speculative. Medium – stock should be expected to move up or down at least 30–40% in a year. Low–medium – stock should be expected to move up or down at least 25–30% in a year. Low – stock should be expected to move up or down at least 15–25% in a year. * Applicable to Asia/Australian/NZ/Canada stocks only

Recommendations – 12 months Note: Quant recommendations may differ from Fundamental Analyst recommendations

Financial definitions

All "Adjusted" data items have had the following adjustments made: Added back: goodwill amortisation, provision for catastrophe reserves, IFRS derivatives & hedging, IFRS impairments & IFRS interest expense Excluded: non recurring items, asset revals, property revals, appraisal value uplift, preference dividends & minority interests EPS = adjusted net profit / efpowa* ROA = adjusted ebit / average total assets ROA Banks/Insurance = adjusted net profit /average total assets ROE = adjusted net profit / average shareholders funds Gross cashflow = adjusted net profit + depreciation *equivalent fully paid ordinary weighted average number of shares All Reported numbers for Australian/NZ listed stocks are modelled under IFRS (International Financial Reporting Standards).

Recommendation proportions – For quarter ending 31 March 2017

AU/NZ Asia RSA USA CA EUR Outperform 47.26% 55.50% 38.46% 45.47% 59.09% 48.21% (for global coverage by Macquarie, 8.20% of stocks followed are investment banking clients)

Neutral 38.01% 29.31% 42.86% 48.77% 37.88% 36.79% (for global coverage by Macquarie, 8.25% of stocks followed are investment banking clients)

Underperform 14.73% 15.19% 18.68% 5.76% 3.03% 15.00% (for global coverage by Macquarie, 8.00% of stocks followed are investment banking clients)

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Keisuke Moriyama (Japan) (813) 3512 7476

Chan Hwang (Korea) (822) 3705 8643

Suresh Ganapathy (India) (9122) 6720 4078

Sameer Bhise (India) (9122) 6720 4099

Gilbert Lopez (Philippines) (632) 857 0892

Ken Ang (Singapore) (65) 6601 0836

Passakorn Linmaneechote (Thailand) (662) 694 7728

Conglomerates

David Ng (China, Hong Kong) (852) 3922 1291

Conrad Werner (Singapore) (65) 6601 0182


Consumer and Gaming

Linda Huang (Asia, China, Hong Kong) (852) 3922 4068

Zibo Chen (China, Hong Kong) (852) 3922 1130

Terence Chang (China, Hong Kong) (852) 3922 3581

Sunny Chow (China, Hong Kong) (852) 3922 3768

Satsuki Kawasaki (Japan) (813) 3512 7870

Kwang Cho (Korea) (822) 3705 4953

KJ Lee (Korea) (822) 3705 9935

Stella Li (Taiwan) (8862) 2734 7514

Amit Sinha (India) (9122) 6720 4085

Fransisca Widjaja (65) 6601 0847 (Indonesia, Singapore)

Karisa Magpayo (Philippines) (632) 857 0899

Chalinee Congmuang (Thailand) (662) 694 7993

Emerging Leaders

Jake Lynch (Asia) (852) 3922 3583

Aditya Suresh (Asia) (852) 3922 1265

Timothy Lam (China, Hong Kong) (852) 3922 1086

Kwang Cho (Korea) (822) 3705 4953

Corinne Jian (Taiwan) (8862) 2734 7522

Marcus Yang (Taiwan) (8862) 2734 7532

Conrad Werner (ASEAN) (65) 6601 0182

Industrials

Janet Lewis (Asia) (813) 3512 7856

Patrick Dai (China) (8621) 2412 9082

Kunio Sakaida (Japan) (813) 3512 7873

William Montgomery (Japan) (813) 3512 7864

James Hong (Korea) (822) 3705 8661

Benson Pan (Taiwan) (8862) 2734 7527

Inderjeetsingh Bhatia (India) (9122) 6720 4087

Justin Chiam (Singapore) (65) 6601 0560

Internet, Media and Software

Wendy Huang (Asia, China) (852) 3922 3378

David Gibson (Asia, Japan) (813) 3512 7880

Hillman Chan (China, Hong Kong) (852) 3922 3716

Soyun Shin (Korea) (822) 3705 8659

Abhishek Bhandari (India) (9122) 6720 4088

Oil, Gas and Petrochemicals

Polina Diyachkina (Asia, Japan) (813) 3512 7886

Aditya Suresh (Asia, China, India) (852) 3922 1265

Anna Park (Korea) (822) 3705 8669

Isaac Chow (Malaysia) (603) 2059 8982

Pharmaceuticals and Healthcare

Abhishek Singhal (India) (9122) 6720 4086

Wei Li (China, Hong Kong) (852) 3922 5494

Property

Tuck Yin Soong (Asia, Singapore) (65) 6601 0838


Raymond Liu (China, Hong Kong) (852) 3922 3629

Wilson Ho (China) (852) 3922 3248

William Montgomery (Japan) (813) 3512 7864


Abhishek Bhandari (India) (9122) 6720 4088

Aiman Mohamad (Malaysia) (603) 2059 8986

Kervin Sisayan (Philippines) (632) 857 0893

Patti Tomaitrichitr (Thailand) (662) 694 7727

Resources / Metals and Mining

Polina Diyachkina (Asia, Japan) (813) 3512 7886

Coria Chow (China) (852) 3922 1181

Anna Park (Korea) (822) 3705 8669

Sumangal Nevatia (India) (9122) 6720 4093

Technology

Damian Thong (Asia, Japan) (813) 3512 7877

George Chang (Japan) (813) 3512 7854

Daniel Kim (Korea) (822) 3705 8641

Allen Chang (Greater China) (852) 3922 1136

Jeffrey Ohlweiler (Greater China) (8862) 2734 7512

Patrick Liao (Greater China) (8862) 2734 7515

Louis Cheng (Greater China) (8862) 2734 7526

Kaylin Tsai (Greater China) (8862) 2734 7523

Telecoms

Soyun Shin (Korea) (822) 3705 8659

Prem Jearajasingam (ASEAN) (603) 2059 8989

Kervin Sisayan (Philippines) (632) 857 0893

Transport & Infrastructure

Janet Lewis (Asia) (852) 3922 5417


Azita Nazrene (ASEAN) (603) 2059 8980

Utilities & Renewables

Patrick Dai (China) (8621) 2412 9082

Candice Chen (China) (8621) 2412 9087

Alan Hon (Hong Kong) (852) 3922 3589


Prem Jearajasingam (Malaysia) (603) 2059 8989

Karisa Magpayo (Philippines) (632) 857 0899

Commodities

Colin Hamilton (Global) (44 20) 3037 4061

Ian Roper (65) 6601 0698

Jim Lennon (44 20) 3037 4271

Lynn Zhao (8621) 2412 9035

Matthew Turner (44 20) 3037 4340

Economics

Peter Eadon-Clarke (Global) (813) 3512 7850

Larry Hu (China, Hong Kong) (852) 3922 3778

Quantitative / CPG

Gurvinder Brar (Global) (44 20) 3037 4036

Woei Chan (Asia) (852) 3922 1421

Danny Deng (Asia) (852) 3922 4646

Per Gullberg (Asia) (852) 3922 1478

Strategy/Country

Viktor Shvets (Asia, Global) (852) 3922 3883

Chetan Seth (Asia) (852) 3922 4769


Peter Eadon-Clarke (Japan) (813) 3512 7850

Chan Hwang (Korea) (822) 3705 8643

Jeffrey Ohlweiler (Taiwan) (8862) 2734 7512


Jayden Vantarakis (Indonesia) (6221) 2598 8310

Anand Pathmakanthan (Malaysia) (603) 2059 8833


Conrad Werner (Singapore) (65) 6601 0182

Passakorn Linmaneechote (Thailand) (662) 694 7728

Find our research at Macquarie: www.macquarieresearch.com/ideas/ Thomson: www.thomson.com/financial Reuters: www.knowledge.reuters.com Bloomberg: MAC GO Factset: http://www.factset.com/home.aspx CapitalIQ www.capitaliq.com Email [email protected] for access

Asia Sales Regional Heads of Sales

Miki Edelman (Global) (1 212) 231 6121

Jeff Evans (Boston) (1 617) 598 2508

Jeffrey Shiu (China, Hong Kong) (852) 3922 2061

Sandeep Bhatia (India) (9122) 6720 4101

Thomas Renz (Geneva) (41 22) 818 7712

Riaz Hyder (Indonesia) (6221) 2598 8486

Nick Cant (Japan) (65) 6601 0210

John Jay Lee (Korea) (822) 3705 9988

Nik Hadi (Malaysia) (603) 2059 8888

Gino C Rojas (Philippines) (632) 857 0861

Regional Heads of Sales cont’d

Paul Colaco (San Francisco) (1 415) 762 5003

Amelia Mehta (Singapore) (65) 6601 0211

Angus Kent (Thailand) (662) 694 7601

Ben Musgrave (UK/Europe) (44 20) 3037 4882

Christina Lee (UK/Europe) (44 20) 3037 4873

Sales Trading

Adam Zaki (Asia) (852) 3922 2002

Stanley Dunda (Indonesia) (6221) 515 1555

Sales Trading cont’d

Suhaida Samsudin (Malaysia) (603) 2059 8888

Michael Santos (Philippines) (632) 857 0813

Chris Reale (New York) (1 212) 231 2555

Marc Rosa (New York) (1 212) 231 2555

Justin Morrison (Singapore) (65) 6601 0288

Daniel Clarke (Taiwan) (8862) 2734 7580

Brendan Rake (Thailand) (662) 694 7707

Mike Keen (UK/Europe) (44 20) 3037 4905

This publication was disseminated on 15 May 2017 at 18:00 UTC.

Date post:	02-Oct-2020
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