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EAGLEs BBVA Emerging and Growth Leading Economies Economic Outlook Annual Report 2015
Transcript of Presentación de PowerPoint - BBVA Research · 2015 58% 2025 64% Emerging countries GDP share (% of...
EAGLEs BBVA
Emerging and Growth Leading Economies Economic Outlook
Annual
Report
2015
• Update of forecasts for the 2014-2024
horizon
• The role of EAGLEs and Nest in the global
economy
• Update of middle classes projections
• Inequality concerns
• Balance of risks
Index
1
2
3
4
5
6
7
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
Short-term headwinds for emerging economies but long-term gap remains relative to developed markets
Source: BBVA Research, IMF
Emerging
World
Developed
Previous
New
3
Real GDP growth (% YoY) Emerging economies lost momentum in
2014, but they will recover its growth’s
pace in the long run, maintaining the gap
with the developed world.
We expect emerging countries to
grow 5.5% YoY in 2024 from 4.2%
yoy in 2014.
Developed economies will grow
2.2% YoY in 2024 from 1.8% YoY in
2014.
As a whole, the world economy will
grow 4.3% YoY in 2024 from 3.2%
YoY in 2014.
0
10
20
30
40
50
60
70
80
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
Previous
New
The recent update of Purchasing Power Parities (PPPs) lifts further the share of the emerging world in
world’s GDP
Source: BBVA Research, IMF
Emerging
4
Developed
50-50% reached in 2007-08 and not in 2012-13
2024f 64%
2024f 32%
2007 50%
2015 58%
2025 64%
Emerging countries GDP share (% of total world GDP PPP)
1980 44%
The IMF updated its WEO database at the end of 2014 including a new set of PPPs computed in the 2011 round by the International Comparison Program (ICP),
which imply significant revisions to those estimated in 2005. In particular, among emerging economies the PPP-adjusted GDP levels increased substantially for
African and Asian countries and to a lesser extent in Latin America and Europe, while the figures remained almost unchanged in developed economies. See the
annex for further information.
GDP share (% of total world GDP PPP)
The new set of PPPs considered by the IMF
has supposed a substantial increase in PPP-
adjusted GDP levels for most of the emerging
economies, while the figures remained almost
unchanged in developed economies. Then, with
the PPP revision, emerging economies
reached developed countries in terms of
GDP share 5 years before than previously
considered.
Western Europe 6.1%
Africa 6.5%
Eastern Europe
5.9%
Latin America
6.3%
North America
10.6%
Middle East 5.0%
Japan
1.0%
Oceania
0.8%
Asia exJapan 57.8%
Global growth will be concentrated in the Asia-Pacific region, which
will account for 76.5% of the increase in GDP between 2014 and 2024. 5
1980 2014
2045
Regional contribution to world growth in the next ten years (%)
World Center of Gravity
Source: BBVA Research, IMF and Quah D., 2011, “The Global Economy’s Shifting Centre of Gravity”.
Shifting the economic centre of gravity from the Atlantic to the Pacific area
The role of
EAGLEs & Nest in the global economy
BBVA EAGLEs: a reminder of the methodology
Labor Capital
Technology Institutions
7
Emerging Economies
Developed Economies Current
GDP level
GDP level In 10 years
BBVA Research & IMF forecasts
Growth
rate (10 years)
=
Current size
(“initial size matters”)
Potential Growth
(“long run dynamics”) Final size
X
Step 1: Estimating GDP level in the next decade
Step 2: Calculating incremental GDP
- = Current GDP level
Incremental GDP
GDP level In 10 years
See the annex for further information.
BBVA EAGLEs and Nest 2015 membership
EAGLEs threshold
Nest threshold
Nest (16)
EAGLEs (14)
Rest of emerging economies
G6 average Incremental GDP 2014-24 = USD 475bn
Non-G7 DMs >USD100bn Incremental GDP 2014-24 = USD 168bn
China, India, Indonesia, Russia,
Mexico, Nigeria, Saudi Arabia,
Brazil, Turkey, Philippines, Pakistan,
Iraq, Bangladesh, Thailand
Malaysia, Egypt, Colombia, Vietnam, Poland, UAE,
Iran, Myanmar, Kazakhstan, Qatar, Algeria,
Peru, Argentina, South Africa, Chile, Sri lanka
Rest of emerging economies
8 See the annex for further information.
EAGLEs Nest Other Countries
BBVA EAGLEs and Nest 2015 membership are balanced across the globe
9
Emerging markets will account for 78% of global growth between 2014 and 2024,
with EAGLEs contributing up to 62%, the Nest group 9% and other emerging countries
another 7%.
BBVA EAGLEs and Nest 2015 membership: significant impact of new estimates
Revision of PPP-adj. 2014 USD GDP (USD bn)
Source: BBVA Research, IMF
10
-300
-200
-100
0
100
200
300
400
500
600
700
S.A
rabia
Nig
eri
a
Thaila
nd
Pakis
tan
Phili
p.
Bangl.
Iraq
UA
E
Myanm
ar
Kaza
k.
Alg
eri
a
Sri
Lanka
New EAGLEs New Nest
Revision required to become an EAGLEs
Revision required to become a Nest
Final Revision by the IMF
Final Revision by the IMF
Saudi Arabia would have become an EAGLE in 2014 regardless of the PPP revision.
Thailand, Bangladesh and Iraq also became EAGLEs members in 2014, but they rank
at the bottom very close to the EAGLEs threshold.
Evolution of EAGLEs and Nest membership over time
Eagles Nest Other Countries
2015 2013
2011
11
New PPP projections have significantly increase the EAGLEs group in 2014,
while the Nest group’s size remains almost unchanged.
Contribution to world growth 2014-24
Curr
ent
size
(2
01
4)
PPP-adj. 2014 USD GDP (USD trn) % of world growth
Change
2014-2
024
NB: *EAGLEs ex China, India and Indonesia
Source: BBVA Research, IMF
12
14.6 28% 7.7
15% 7.4 14%
5.1 10% 4.7; 9% 3.7; 7% 3.6; 7% 2.9: 6% 2.2; 4%
20
15
10
5
0
5
10
15
Chin
a
EA
GLEs-
11
*
India US
Nest
Oth
er
EM
s
Non-G
7 D
Ms
G6
Indonesi
a
China and India will lead global growth contributing 28% and 14% respectively
between 2014 and 2024. Their rapid growth is behind the boom of the middle
classes in the emerging world.
PPP-adj. 2014 USD GDP (USD bn)
Change
2014-2
024
C
urr
ent
size
(2
01
4)
Source: BBVA Research, IMF
13
938 937 887 814 787 752 749 646 590 556 542 537 528 526 496 491
5000
4500
4000
3500
3000
2500
2000
1500
1000
500
0
500
1000
Russ
ia
Mexic
o
Nig
eri
a
Kore
a
S.A
rabia
Bra
zil
Turk
ey
Germ
any
UK
Phili
ppin
es
Pakis
tan
Taiw
an
Japan
Iraq
Bangla
desh
Thaila
nd
Russia, Mexico and Nigeria will contribute more than any developed country. Saudi
Arabia, Brazil and Turkey will add more to the increase of world GDP than Germany
and UK.
Contribution to world growth 2014-24
Curr
ent
size
(2
01
4)
Change
2014-2
024
Source: BBVA Research, IMF
14
PPP-adj. 2014 USD GDP (USD bn)
461 444 440 419 400 391 387 370 354 315 289 271 269 254 239 239 233 207 199 196 194
2700
2400
2100
1800
1500
1200
900
600
300
0
300
600M
ala
ysi
a
Fra
nce
Egypt
Spain
Colo
mbia
Vie
tnam
Pola
nd
Aust
ralia
Canada
UA
E
Italy
Iran
Myanm
ar
Kaza
khst
an
Qata
r
Alg
eri
a
Peru
Arg
entina
S.A
fric
a
Chile
Sri
Lanka
Malaysia ranks at the top of the Nest group. Egypt, Colombia, Vietnam and
Poland show contributions to global growth comparable to those from large
developed economies.
Contribution to world growth 2014-24
Update of
Middle Classes projections
The Emerging Middle Classes revolution will accelerate
Emerging countries’ middle classes (1980-2025)
(millions)
NB: Based on PPP-adjusted 2010 USD; Poor and Low Income (<USD5,000), Low
Middle Class (USD5,000-15,000), Medium Middle Class (USD15,000-25,000), High
Middle Class (USD25,000-40,000), Affluent (>USD40,000).
Source: BBVA Research, UN, WB, IMF
16 See “Flourishing middle classes in the emerging world to keep driving reductions in global inequality“, BBVA Research. See the annex for further information.
There has been a dramatic
reshaping of global income
distribution since 2000 led by
an unprecedented reduction in
poverty rates as well as by the
rapidly growing middle classes
in the emerging economies.
This will continue in the coming
years.
We expect emerging countries
to increase their share of the
global medium-high middle
classes and affluent segments
from 24% in 2000 to 67% by
2025.
0
1000
2000
3000
4000
5000
6000
7000
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
Affluent High Middle ClassMedium Middle Class Low Middle ClassPoor and Low Income
Forecasts Middle classes
revolution
Flourishing middle classes in the emerging world are reducing global inequality
Global GINI index (1980-2025f)
NB: The GINI index is calculated with percentile GDP per capita including data for 90
countries covering over 90% of the world population.
Source: BBVA Research, UN, WB, IMF
17 See “Flourishing middle classes in the emerging world to keep driving reductions in global inequality“, BBVA Research. See the annex for further information.
The expansion of the middle
classes has contributed to a
rapid decline in global
inequality, which will reduce
further even assuming no
changes in domestic income
distributions.
0.50
0.55
0.60
0.65
0.70
1980
1982
1984
1986
1988
1990
1992
1994
1996
1998
2000
2002
2004
2006
2008
2010
2012
2014
2016
2018
2020
2022
2024
Forecasts
However, levels of GINI index
will remain high on cross-
country standards, with a GINI
index similar to those recorded
today in Africa and Latin America.
Asia leads the reshaping of global income distribution…
Change of population (mn) by GDP per capita and region (2000 to 2025f)
Source: BBVA Research, UN, WB, IMF
18
Emerging Asia is the largest
contributor to this reshaping of the
world’s income distribution with a new
middle class of 2658 mln living there
The share of the wealthier segments
is on the rise in Africa, Latin America
and Emerging Europe
Medium-high middle classes and
affluent segments will increase from
24% in 2000 to 67% in 2025 in
Emerging Countries 131
1,001 659
165 -6
-2,000
-1,500
-1,000
-500
0
500
1,000
1,500
2,000
2,500
3,000
Developed EmergingAsia
Africa Latam EmergingEurope
Affluent High Middle ClassMedium Middle Class Low Middle ClassPoor and Low Income TOTAL
…leading creation of the Middle Classes with pro-poor growth. Latam growth has been more
inclusive
19
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
20
12
20
14
20
16
20
18
20
20
20
22
20
24
Forecasts
Africa
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
20
12
20
14
20
16
20
18
20
20
20
22
20
24
Forecasts
Emerging Asia
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04
20
06
20
08
20
10
20
12
20
14
20
16
20
18
20
20
20
22
20
24
Affluent High Middle Class
Medium Middle Class Low Middle Class
Poor and Low Income
Forecasts
Latin America
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
198
01
98
21
98
41
98
61
98
81
99
01
99
21
99
41
99
61
99
82
00
02
00
22
00
42
00
62
00
82
01
02
01
22
01
42
01
62
01
82
02
02
02
22
02
4
Affluent High Middle ClassMedium Middle Class Low Middle ClassPoor and Low Income
Forecasts
Emerging Europe
Income transition drives significant changes in consumption expenditure
20
40
56
24 27 37
17
10
15
20
25
30
35
40
45
50
55
60
1980 1990 2000 2010
Discretionary Semi-necessities Necessities
49
32 18
27
28
32
24 41
50
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Low income Middle income High income
Discretionary Semi-necessities Necessities
Consumption basket according to GDP per capita
(average CPI weights by broad group) (c.2012) Consumption basket in Korea
(% CPI weight by broad group) (1980-2010)
Source: BBVA Research, Haver, IMF Source: BBVA Research, Haver
As countries develop from low income to
middle and high income levels, the relative
demand for basic products declines
substantially, while the opposite happens with
discretionary products.
Korea is a good example of this. The country has
developed extraordinarily rapidly, increasing its
GDP per capita five-fold between 1980 and 2010
and transitioning from low to high income levels.
Inequality
concerns
25
30
35
40
45
50
55
60
6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5
China
India
Indonesia
Philippines
Thailand
Chile
Turkey
Brazil
Peru
Malaysia
Argentina
Mexico
Colombia
Inequality as a by-product of the development process (Kuznets Inverted U curve)
Kuznets curve: income inequality and GDP per capita to relate in the form of an inverted U
GDP per capita (natural logs)
Source: BBVA Research, WIID, IMF
22
GIN
I in
de
x
(1980s-2
000s)
However, the decline in global
inequality has taken place at the
expense of more uneven income
distributions in large Asian
economies and only a slight
smoothing of high inequality in Latin
America.
Unprecedented growth in emerging
economies during the last 15 years
has brought an impressive reduction
of poverty and a boom in the middle
classes.
Note: see “Tackling excessive inequality as a critical ingredient for sustainable development in the emerging world”, BBVA Research.
0
10
20
30
40
50
60
70
6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5
Ancient Modern - Early 00s ALL Polinómica (ALL)
The Kuznets curve seems to hold from a historical perspective
Source: Milanovic, Branko, Lindert, Peter H., and Williamson, Jeffrey G., 2007, “Measuring ancient inequality”, NBER Working Paper No.13550
23
Income per capita (natural logs of PPP-adjusted USD)
GIN
I in
de
x
US
Sweden
Malaysia
Brazil South Africa
China Nigeria
Tanzania
Congo
Holland (1732)
England/Wales (1801-03)
England/Wales (1688)
Holland (1561)
Roman Empire
(14)
Nueva España (1790)
Old Castille (1752)
British India (1947)
Naples (1811)
Brazil (1872) Bihar,
India (1807)
Moghul India (1750)
Byzantium (1000)
The global economy’s development over time shows the inverted-U relationship between
economic development and inequality (Kuznets curve) from the Roman Empire to US and China.
Note: According to Kuznets curve theory, income inequality would be a by-product of growth in early stages of development as urbanisation and the shift to more
productive activities increase the gap with rural areas, and the capital share rises. Thereafter, this upward trend is stabilised and eventually reversed at some point,
following transition to medium-high income levels. See “Tackling excessive inequality as a critical ingredient for sustainable development in the emerging world “, BBVA
Research
Beyond Kuznets curve, redistribution and human capital play key roles
Source: BBVA Research
24
Average by quintile for GINI index Average by development and region
Estimate of GINI index (DIS) and decomposition of non-Kuznets determinants
(average for country groups)
-9 -11 -14
-14 -16 -6
-7 -8
-8 -9
-30
-25
-20
-15
-10
-5
0
5
10
5th 4th 3rd 2nd 1st
Human Capital Redistribution Residue
-15 -16 -11 -9
-14
-8 -7
-8 -6
-9
-30
-25
-20
-15
-10
-5
0
5
10
All EU15 All LAT EUR
DM EM
Human Capital Redistribution Residue
Our cross-country analysis exercise shows that redistribution policies and labour
market dynamics are key determinants in tackling inequality. This relationship appears
more intense in developed countries, which present lower GINI indices.
Source: BBVA Research
Redistribution requires stable and adequate fiscal revenues
25
Source: OECD Source: IMF
GINI index in OECD countries before and after
taxes and transfers (late 00s)
General government revenue (% GDP) (2014)
Hungary
Czech Republic Slovenia
Estonia
US
Turkey
Chile
Korea
Mexico
20
25
30
35
40
45
50
55
20 25 30 35 40 45 50 55
GIN
I aft
er
taxes
and t
ransf
ers
GINI before taxes and transfers
(-)
(+)
0
5
10
15
20
25
30
35
40
45
Nig
eri
aBangla
desh
Iran
Sri
Lanka
Pakis
tan
Indonesi
aPhili
ppin
es
India
Vie
tnam
Peru
Thaila
nd
Mexic
oC
hile
Mala
ysi
aM
yanm
ar
Kaza
khst
an
Egypt
Chin
aC
olo
mbia
S.A
fric
aU
AE
Alg
eri
aTurk
ey
Arg
entina
Russ
iaD
EV
ELO
PED
Pola
nd
Bra
zil
Iraq
Qata
rS.A
rabia
Redistribution policies in developed countries have proved to be effective in reducing
inequality. To use redistribution policies, emerging countries need to increase fiscal revenues,
especially in South-east Asia, Mexico and the Andean countries in Latin America, where fiscal
revenues are around 20% of GDP compared to 40% in G7 economies.
Education is also crucial to guarantee equality of opportunities… Spending on education will
discriminate between and within countries
26
Public expenditure by educational level (‘000s of PPP-adjusted USD per student) (2006-10 avg)
Source: BBVA Research, WB and IMF
Educational gaps are crucial
determinants to fight inequality.
Large gaps remain between
countries.
Public expenditure on education in
emerging countries is very low
compared with developed standards.
Reducing these gaps will be
important in tackling inequality.
0
1
2
3
4
5
6
7
8
9
10
OEC
D
Pola
nd
Arg
entina
Chile
Mexic
o
Bra
zil
Thaila
nd
Mala
ysi
a
S.A
fric
a
Colo
mbia
Peru
Vie
tnam
Indonesi
a
Phili
ppin
es
India
Bangla
desh
Turk
ey
Russ
ia
Primary Secondary Tertiary
…although it must be accompanied by good infrastructure
27
Quality of overall infrastructure (1-7) (2013-14)
NB: Countries are ranked according to their real PPP-adjusted GDP per capita in 2013
Source: BBVA Research, WEF
Poor quality of infrastructure
harms competitiveness and
may eventually become a
serious bottleneck for further
growth.
The challenges to developing
infrastructure are huge, given
the low fiscal revenues, leading
necessarily to consideration of
alternative financing sources
such as regional banks, private-
public partnerships or portfolio
diversification by global lenders.
1
2
3
4
5
6
7
Bangla
desh
Nig
eri
aPakis
tan
Vie
tnam
India
Phili
ppin
es
Indonesi
aEgypt
Chin
aThaila
nd
Colo
mbia
S.A
fric
aPeru
Bra
zil
Mexic
oTurk
ey
Mala
ysi
aR
uss
iaA
rgentina
Chile
Pola
nd
Italy
Fra
nce
Japan
UK
Germ
any
Canada
US
Low income Middle income Developed
Financial inclusion rather than size is a key factor in tackling income inequality…
Source: BBVA Research
28
Average of GINI index for income groups / regions and financial inclusion conditioned on GDP per capita
25
30
35
40
45
50
Very lowincome
Low Income MediumIncome
High Income25
30
35
40
45
50
55
60
Develop. E.Europe Emg.AsiaL.America Africa
Note: Values above average correspond to residuals of regressions on GDP per capita (level and square values) that are one standard deviation above mean (0).
See García-Herrero A., Martínez Turégano D., 2015, “Financial inclusion, rather than size, is the key to tackling income inequality”
Financial inclusion contributes significantly to more equal income distribution,
having a larger incidence in low and medium-income countries, particularly in
Emerging Asia and Africa.
Average Financial Inclusion
Higher than average Financial Inclusion
Lower than average Financial Inclusion
…and there is still plenty of room for improvement in emerging markets
Countries ordered by the degree of financial inclusion. Source: BBVA Researcha
29
BBVA Research Multidimensional Financial Inclusion Index
Ranking
Note: the degree of financial inclusion is determined by three dimensions: usage, barriers and access. These dimensions are, at the same time, determined
by several demand-side individual level indicators for the cases of usage and barrier, and supply-side country level indicators for access. Weights assigned
to the dimensions are determined endogenously. See Cámara N., Tuesta D., 2014. “Measuring Financial Inclusion: A Multidimensional Index”, BBVA
Research.
Balance of Risks
Geopolitics will dominate Eurasia and Middle East, but more hot spots need to be monitored
31
BBVA World Conflict Heatmap (from 2H 2014 to Mar 2015) (Number of conflicts / Total events)
Ukraine-Russia
Instability in Middle East
A new ceasefire agreement was
reached, but is still very fragile
Fighting continues in Syria and Iraq
and is now spreading to North Africa.
Yemen conflict escalates
Some pressure in Asia
The risk of Social unrest in Hong
Kong and territorial disputes in
South East Asia Sea Source: www.gdelt.org & BBVA Research
79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03 04 05 06 07 08 09 10 11 12 13 14
USA
UK
Norway
Sweden
Austria
Germany
France
Netherlands
Italy
Spain
Belgium
Ireland
Portugal
Greece
Poland
Czech Republic
Hungary
Bulgaria
Romania
Croatia
Turkey
Russia
Ukraine
Georgia
Kazakhstan
Moldova
Azerbaijan
Armenia
Morocco
Algeria
Tunisia
Libya
Egypt
Israel
Jordan
Syria
Iraq
Iran
UAE
Bahrain
Qatar
Oman
Saudi Arabia
Mexico
Brazil
Chile
Colombia
Peru
Argentina
Venezuela
China
Hong Kong
Korea
Thailand
Indonesia
Malaysia
Philippines
India
Pakistan
Afghanistan
LA
TA
MEM
Eu
rop
e &
CIS
Asi
aD
evelo
ped
Mark
ets
N.
Afr
ica &
Mid
dle
East
World Protest Intensity Map 1979- Mar 2015 (Number of protests / Total events. Dark Blue: high intensity)
There was some revival of
instability on the EU but less
intensive than during the
early 80´s and it’s softening
now…
EM Europe and CIS countries
are facing increasing social
unrest…
The Arab Spring spread
protests across the Middle
East region. Some countries
remain under tensions…
The Global Awakening has spiked after years of calm
Source: www.gdelt.org & BBVA Research
Portfolio flows to EM adjust as policy normalisation in the West is becoming closer…
33
Update* of cumulated flows to Emerging
Markets
(Official balance of payments data, in USD trn)
0.0
0.2
0.4
0.6
0.8
1.0
2006 2007 2008 2009 2010 2011 2012 2013 2014 2015
Estimation* (3Q14)
Nowcast* (4Q14)
Forecast (1Q15)
(*) Estimation s using BBVA’s DFM/FAVAR Model
Source: BBVA Research. Update 27 Feb. 2015
Phase 1
Phase 2
Phase 3
The monetary policy reactions in
developed economies after the financial
distress and favorable conditions in terms
of economic growth and lower risk premia
triggered supporting global push and
pull factors for flow dynamics across
Ems, leading to strong and sustained
flows into them (phase 2).
However, the announcement of the
normalisation of monetary stimuli, the
recovery of Developed economies and
lower appeal of Ems is triggering a
portfolio rebalancing in favor of DM.
(phase 3).
Ber
nan
ke s
pee
ch
on
tap
erin
g
QE2
34
Emerging Markets flows (Median Emerging Market portfolio flow breakdown as per
BoP, monthly change in %)
Emerging Markets flows’ drivers (Median Emerging Market portfolio flow
decomposition, in % change MoM)
-20
-15
-10
-5
0
5
10
15
20
2008 2009 2010 2011 2012 2013 2014 2015
LocalGlobalEM_BoP
70%
30%
65%
35%
Phase 1-2 Phase 2-3
Phase 2 Phase 3 Phase 4 Phase 1
Phase 3-4
Source: IMF, IFS Data , BBVA Research Source: IMF, IFS Data , BBVA Research
…but still global factors dominate the correction of flows so far. However, some
local strains have emerged
Global Factors dominated the reallocation at the end of 2014 and the beginning of the first quarter of 2015. However, high frequency data reveal that idiosyncratic elements are also emerging.
95%
5%
35
The Fed will dominate and the ECB’s push will only partially compensate
Page 35
Monetary policy in the north and flows in the south (alternative QE, Fed and ECB scenarios) Cumulative response of portfolio flows in USD bn, forecast made at end 2Q14)
(1) Fed and ECB in QE mode
(3) Fed early exit and ECB QE failure
(2) Fed normalisation as expected + ECB QE 1
2
3
Data 3Q14
NowCast 4Q14
NowCast/Fcast 1Q15
EM Flows will continue to be
challenged by Monetary Policy
normalisation by key Central
Banks…
0.60
0.65
0.70
0.75
0.80
0.85
0.90
0.95
1.00
2011 2012 2013 2014 2015 2016 2017
Source: IMF, BBVA Research
… but part of the adjustment
have already been materialised
0
50
100
150
200
250
300
3502000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
2013
2014
Jan-F
eb /
15
Beyond flows adjustments, commodity exporters will have to adapt to lower prices…
Source: BBVA Research, Haver
Commodity prices in 2000 USD (index 100 = 2000)
Metals
-25%
Foodstuffs
-30%
36
Commodity prices, especially the oil price, have experienced a declining
trend since 2011, introducing important challenges and potential risks for
exporting countries.
Energy
-47%
-30-20-10
010203040506070
S.A
rabia
Iraq
Russ
ia
Nig
eri
a
Chin
a
Mexic
o
Bra
zil
Indonesi
a
Thaila
nd
Bangla
d.
Phili
p.
India
Pakis
tan
Turk
ey
Qata
r
Kaza
k.
UA
E
Iran
Mala
ysi
a
Alg
eri
a
Pola
nd
Arg
entina
Vie
tnam
Myanm
ar
Colo
mbia
Chile
S.A
fric
a
Peru
Sri
Lanka
Egypt
EAGLEs Nest
Mining products Agricultural Fuels Non-commodities trade balance Trade balance
Emerging Markets asymmetry in oil dependence…
37
Trade balance (% of GDP) (2013)
Source: BBVA Research, WTO, IMF
Average fuel deficit of 6% of GDP
Oil-producing countries suffer the sharp drop of oil prices, but some other
emerging countries from Asia, such as India and Phillippines, and also
Turkey benefit from cheaper energy.
…explains the different sentiment to the sharp fall in oil prices across countries
38
The world sentiment to the drop in oil prices
Source: BBVA Research and www.gdelt.org
See “Very low energy prices and geopolitical risks”, BBVA Research.
The contribution of the Emerging World to global growth is bound to be even bigger
than we had initially projected, due to recent updates in purchasing power parity
estimates across the globe. In fact, in 2024 they will have an almost two-thirds share of
the global economy.
There are now more countries included in our EAGLEs list. The new additions come
mainly from Asia and the Middle East.
The creation of a new middle class is well underway and this will continue to push
consumption.
A flourishing middle class in emerging markets, fiscal redistribution,
equality of opportunities and financial inclusion will all be instrumental in
reducing income inequality.
Geopolitical risk in Emerging Markets has become one of the main risks of 2015. The
single-polar word is changing towards more multipolar geopolitics. Instability’s spots
appear in several geographies at the same time.
40
Annex
Methodological issues: BBVA EAGLEs and Nest membership definition
The reference variable in our calculations is the incremental GDP, i.e. the increase of real GDP in PPP-adjusted
terms during the following ten years. To compute it, we add growth forecasts to the estimate of PPP-adjusted for the
starting year provided by the IMF. Our approach is therefore a mixture of size and growth.
We update growth forecasts for the following ten years on an annual basis. We use BBVA Research
projections for those countries that we cover in depth, and IMF projections in the latest World Economic Outlook
(and updates) for the remainder. In the latter case, we extend the available forecast horizon by assuming as
constant the growth rate available for the last year.
After updating the growth forecasts we compute the incremental GDP for all countries in the world and then rank
them from largest GDP to smallest, defining membership of BBVA EAGLEs and Nest as follows:
• The BBVA EAGLEs are defined as those emerging economies contributing to world growth more than the
average of the G6 countries in the next ten years.
• The BBVA Nest is formed of those emerging economies contributing to world growth more than the average
of the non-G7 developed economies, which have a PPP-adjusted GDP of over USD100bn but below the EAGLEs
threshold.
42
Methodological issues: new PPP valuations
The IMF updated its WEO database at the
end of 2014, including a new set of
Purchasing Power Parities (PPPs) computed
in the 2011 round by the International
Comparison Program (ICP), which imply
significant revisions to those computed in
2005*.
In particular, among emerging economies the
PPP-adjusted GDP levels have increased
substantially for African and Asian
countries and to a lesser extent in Latin
America and Europe, while the figures have
remained almost unchanged in developed
economies.
Valuation of 2013 GDP in PPP-adjusted terms (% change between previous and new estimates)
Source: BBVA Research, IMF
* A thorough analysis on methodology changes between the 2005 and 2011 rounds is available at Deaton, A., and Aten, B., 2014, “Trying to understand the PPPs
in ICP 2011: why are the results so different?” 43
17
3
31
60
37 35 30
18 18
0
10
20
30
40
50
60
70
Mundo
Desa
rrolla
dos
Em
erg
ente
s
MEN
A
SS A
fric
a
CEI
Asi
a
Lata
m
Euro
pa
Emerging
Methodological issues: population projections
We use PPP-adjusted real GDP per capita measured in 2010 dollars. GDP values and projections correspond to the
October 2014 edition of the IMF/WEO database, while population estimates and forecasts are from the 2012 revision of the
UN World Population Prospects. Regarding income distributions, our starting point is the information available in the
WDI/World Bank, which includes the two top and bottom deciles and all quintiles. As data are not continuous we interpolate
missing data. Projections until 2025 keep distributions constant from the latest observation.
We group population according to the following five income ranges: 1/ poor and low-income (up to USD5,000), 2/ low
middle class (USD5,000-15,000), 3/ medium middle class (USD15,000-25,000), 4/ high middle class (USD25,000-
40,000), and 5/ affluent (over USD40,000).
The number of countries included has been extended to 90 and the current coverage accounts for over 90% of the world
population:
• Developed economies: United States, Japan, Germany, France, United, Kingdom, Italy, Korea, Spain, Canada,
Australia, Netherlands, Belgium, Greece, Czech Republic, Portugal, Sweden, Austria, Denmark, Finland, Slovak
Republic, Ireland, Slovenia, Estonia and Luxembourg.
• Emerging economies: China, India, Indonesia, Brazil, Pakistan, Nigeria, Bangladesh, Russia, Mexico, Philippines,
Ethiopia, Vietnam, Egypt, Iran, Turkey, DR Congo, Thailand, South Africa, Tanzania, Colombia, Kenya, Ukraine,
Argentina, Algeria, Uganda, Poland, Iraq, Sudan, Morocco, Afghanistan, Venezuela, Peru, Malaysia, Uzbekistan,
Nepal, Mozambique, Ghana, Yemen, Angola, Madagascar, Cameroon, Syria, Sri Lanka, Romania, Côte d'Ivoire,
Niger, Chile, Burkina Faso, Malawi, Paraguay, Mali, Kazakhstan, Guatemala, Ecuador, Cambodia, Zambia,
Zimbabwe, Senegal, Hungary, Bulgaria, Croatia, Panama, Qatar, Uruguay, Lithuania and Latvia.
44
Methodological issues: determinants of inequality
45
To measure inequality, we use the UNU WIDER World Income Inequality Database that provides more than
7,000 observations. Why we focus on it?
• Data availability with a fair geographical and time balance
• High ratio of observations adjusted by household composition
• Much better data quality
• Better approach to inequality among income measures
UNU-WIDER World Income Inequality Database (WIID)
Period of analysis:
Cross-section
Panel data Annual
observations
10-year average for
seven periods
This report has been produced by Emerging Markets Unit, Cross-Country Analysis Team
Chief Economist for Emerging Markets Alicia García-Herrero +852 2582 3281 [email protected]
Chief Economist, Cross-Country Emerging Markets Analysis Álvaro Ortiz Vidal-Abarca +34 630 144 485 [email protected] Gonzalo de Cadenas +34 606 001 949 [email protected]
David Martínez Turégano +34 690 845 429 [email protected]
Alfonso Ugarte Ruiz + 34 91 537 37 35 [email protected] Tomasa Rodrigo +3491 537 8840 [email protected]
46
BBVA Research Group Chief Economist Jorge Sicilia
Emerging Economies: Alicia García-Herrero [email protected]
Cross-Country Emerging Markets Analysis Álvaro Ortiz Vidal-Abarca [email protected]
Asia Stephen Schwartz [email protected]
Mexico Carlos Serrano
Latam Coordination Juan Ruiz
Argentina Gloria Sorensen [email protected]
Chile Jorge Selaive [email protected]
Colombia Juana Téllez [email protected]
Peru Hugo Perea [email protected]
Venezuela Oswaldo López [email protected]
Developed Economies: Rafael Doménech [email protected]
Spain Miguel Cardoso [email protected]
Europe Miguel Jiménez [email protected]
US Nathaniel Karp [email protected]
Global Areas:
Financial Scenarios Sonsoles Castillo [email protected]
Economic Scenarios Julián Cubero [email protected]
Innovation & Processes Oscar de las Peñas [email protected]
Financial Systems & Regulation: Santiago Fernández de Lis [email protected]
Financial Systems Ana Rubio [email protected]
Financial Inclusion David Tuesta [email protected]
Regulation and Public Policies María Abascal [email protected]
Recovery and Resolution Policy José Carlos Pardo [email protected]
Contact details: BBVA Research Paseo Castellana, 81 – 7th floor 28046 Madrid (Spain) Tel. + 34 91 374 60 00 and + 34 91 537 70 00 Fax. +34 91 374 30 25 [email protected] www.bbvaresearch.com
BBVA Research Asia 43/F Two International Finance Centre 8 Finance Street Central Hong Kong Tel: +852 2582 3111 E-mail: [email protected]
47
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