Transcript 2. Global savings: from “glut” to deficit?

Trends for the world
economy in 2012 and
investment flows into
BRIC countries
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. The World Economy
2012: New Cycle Means
New Risks?
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. The World Economy 2012: New Cycle Means New Risks?
 Developed economies for a year stand on the
brink of new economic cycle
 But the progress falters under the burden of
government and financial sector problems,
provoking risk aversion for investors
 Most likely, the cycle will proceed as new, and
these problems will stay unresolved, bound to
turn up later
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1. The World Economy 2012: New Cycle Means New Risks?
1.1. Industrial production,
01/01/2000=100
1.2. Unemployment rate, %
120
11
115
10
110
9
105
100
8
95
7
90
6
85
5
US
Source: IMF International financial statistics
EA
US
EA
окт.11
апр.11
июл.11
янв.11
окт.10
июл.10
апр.10
янв.10
окт.09
июл.09
апр.09
янв.09
окт.08
июл.08
апр.08
янв.08
окт.07
июл.07
апр.07
окт.11
апр.11
июл.11
янв.11
окт.10
апр.10
Japan
июл.10
янв.10
окт.09
июл.09
апр.09
янв.09
окт.08
июл.08
апр.08
окт.07
янв.08
3
июл.07
70
апр.07
4
янв.07
75
янв.07
80
Japan
Source: IMF International financial statistics
While unsure, the recovery in developed countries is slowly
proceeding, the US heading headfirst and both Japan and EA lagging
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1. The World Economy 2012: New Cycle Means New Risks?
1.6. Total money base of largest developed countries, US$ tn
20
3
15
2
10
1
5
0
0
US
EA
Japan
2011
4
2010
25
2009
5
2008
30
2007
6
growth rate % (right axis)
Source: IMF
The money central banks issued most likely would stay even as the
credit multiplier increases
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1. The World Economy 2012: New Cycle Means New Risks?
1.3. EA MB and M3 growth rates, % yoy
1.4. MB and M2 growth rates, % yoy
35
35
30
30
25
25
20
20
15
15
10
10
5
5
0
0
Source: ECB
USM2
Денежная база зоны евро
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
М3 зоны евро
2000
-5
-5
USMB
Source: Fed
So far, the multiplier stays very low, though some increase in US is
visible
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1. The World Economy 2012: New Cycle Means New Risks?

Corporate debt ratios for both US and EA are at 10-15year lows

Trade balance stabilization and strong personal
consumption in the US in 2011 suggest grounds for new
growth cycle

Rates of growth in China won’t skyrocket as the
government finishes deflating bubble, there are
problems with shifting to consumption-based growth,
but “low” still means 8+% for China (and not to forget
expected US growth)
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1. The World Economy 2012: New Cycle Means New Risks?
1.6. EBITDA for main US industries, 2000 prices, 31/03/00=100
150
350
140
300
130
250
120
110
200
100
150
90
80
100
70
50
60
Durable goods production
Manufacturing
2009
2008
2007
2006
2005
2004
2003
2002
2001
0
2000
50
Mining (right axis)
Source: US Census Bureau
EBITDA for US has recovered, for EA lags behind but not totally subdued
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. The World Economy 2012: New Cycle Means New Risks?
1.7. US corporate debt, 2000 prices, 31/03/00=100
120
350
300
110
250
200
100
150
100
90
50
Durable goods production
Manufacturing
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
0
2000
80
Mining (right axis)
Source : US Census Bureau
…as the debt levels grow steadily…
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. The World Economy 2012: New Cycle Means New Risks?
1.8. Debt to EBITDA, main US industries
7.0
6.0
5.0
4.0
3.0
2.0
Durable goods production
Mining
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
1.0
Manufacturing
Source : US Census Bureau
Debt/EBITDA stays at 2000 lows.
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. The World Economy 2012: New Cycle Means New Risks?
1.10. Profit/Sales in US industries
30
31
25
20
15
10
5
0
-5
-21
Durable goods production
Mining
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
-10
Manufacturing
Source : US Census Bureau
While profitability is already at expansion phase levels….
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. The World Economy 2012: New Cycle Means New Risks?
1.9. US household debt service ratios, % of income
14.0
13.5
13.0
12.5
12.0
11.5
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
11.0
Source: Fed
…household DSR stays pretty low
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. The World Economy 2012: New Cycle Means New Risks?
1.10. Delinquent credit in US banks, % of assets
10
9
8
7
6
5
4
3
2
1
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Total
business loans
consumer loans
loans secured by real estate
Source: Fed
And the wall of delinquencies is basically overcome
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. The World Economy 2012: New Cycle Means New Risks?
1.11. Loan to deposit ratio
1.10
1.05
1.00
0.95
0.90
0.85
US
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
0.80
EA
Source: Fed, ECB
At the same time, credit activity at US and EA banks
is clearly subdued
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1. The World Economy 2012: New Cycle Means New Risks?
1.12. Credit portfolio as a share of total assets
0.75
0.70
0.65
0.60
0.55
US
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
2000
0.50
EA
Source: Fed, ECB
Liquid assets are preferred to credits as risk aversion is
strong
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. The World Economy 2012: New Cycle Means New Risks?
1.13. Capacity utilization vs unemployment, %
Source: Fed, ECB
Jul-11
Jan-11
Jul-10
Jan-10
Jul-09
Jan-09
Jul-08
Jan-08
Jul-07
Jan-07
Jul-06
12
Jan-06
60
Jul-05
10
Jan-05
65
Jul-04
8
Jan-04
70
Jul-03
6
Jan-03
75
Jul-02
4
Jan-02
80
Jul-01
2
Jan-01
85
Jul-00
0
Jan-00
90
US Capacity utilization
Euro area capacity utilization survey (quarterly, intrapolated)
US Unemployment SA inverted, right axis
EU-27 unemployment inverted, right axis
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1. The World Economy 2012: New Cycle Means New Risks?
1.14. Baltic Dry and Harpex indices
Baltic Dry
0
Jan-12
Oct-11
Jul-11
Apr-11
Jan-11
Oct-10
Jul-10
Apr-10
Jan-10
Oct-09
Jul-09
Apr-06
Jan-06
0
Apr-09
250
Jan-09
100
Oct-08
500
Jul-08
200
Apr-08
750
Jan-08
300
Oct-07
1000
Jul-07
400
Apr-07
1250
Jan-07
500
Oct-06
1500
Jul-06
600
HARPEX (container costs, right axis)
While dry bulk costs were untouched by the slowdown of
2011, container costs were sharply down
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1. The World Economy 2012: New Cycle Means New Risks?
1.15. Main economic forecasts for 2012
GDP yoy, %
UN
IMF
WB
2011
World (PPP)
3.6
3.3
3.4
3.8
US
1.5
1.8
2.2
1.7
EA
0.4
-0.5
-0.3
1.6
Japan
2.0
1.7
1.9
-0.9
China
8.7
8.2
8.4
9.2
India
7.7
7.0
6.5
7.5
Brazil
2.7
3.0
3.4
2.9
Russia
3.9
3.3
3.5
4.1
Oil, $/b
100.0
99.1
98.2
104.2
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2. Global savings: from
“glut” to deficit?
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
 Three arguments for less saving in the long-term:
 world population ageing, esp. in developed countries,
increases retired-to-workers ratio;
 losses the pension savings took after the financial crisis
of 2008 and probable sovereign debt crises of 2008-2011
 forgone investment gains, e.g. negative real rates as a
consequence of ZIRP+QE in reserve currencies
 One argument for less money going to emerging
markets:
 developed world needs more money to refinance
growing public debt and restart new credit cycle
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
2.1. Retired-to-working ratio, world, %
25
20
15
10
2030
2025
2020
2015
2010
5
Мир
World population ageing, esp. in developed
countries, increases retired-to-workers ratio
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
2.2. Global liquid financial asset structure, %
2006
2010
$ tn
%
$ tn
%
Equity market cap
55
30.7
54
25.6
Sovereign debt
28
15.6
41
19.4
Financial institutions debt
35
19.6
42
19.9
Nonfinancial institutions debt
7
3.9
10
4.7
Securitised credit
14
7.8
15
7.1
Nonsecuritised credit
40
22.3
49
23.2
Total
179
100.0
211
100.0
Source: MGI.
Losses the pension savings took after the financial crisis
of 2008 and probable sovereign debt crises of 2008-2011
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
“What incentive does a US bank have to extend
maturity to a two- or three-year term when
Treasury rates at that level of the curve are below
the 25 basis points available to them overnight
from the Fed?
What incentive does PIMCO or banks have to
buy five-year Treasuries at 75bp when the
maximum upside capital gain is 2 per cent of par
and the downside substantially more?”
- Bill Gross, PIMCO
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
 As more and more sovereign debt in developed
countries needs refinancing, emerging markets will
experience outflow of capital sourced in developed
markets, i.e. “home bias” for the debt will strengthen
 This means governments should concentrate on
stimulating the potential of internal savings rather
than seeking overseas financing, especially financing
for the emerging markets
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
2.3. Financing needs of
developed countries in 2012,
$ bn
США*
США*
471
Япония*
359
2.4. Financing needs of
developed countries in 2012,
% GDP
30
Япония*
601
Франция
59
Франция
Италия
Италия
538
Германия
21
24
Германия
389
Великобритания
11
Великобритания
383
324
Испания
15
Испания
Португалия
54
Португалия
Греция
51
Греция
Ирландия
22
17
Ирландия
32
0
21
100
200
300
500
400
*10 млрд. долл
600
14
0
5
10
15
20
25
30
35
40
45
50
55
60
*10 млрд. долл
Source: IMF, Fiscal Monitor 2011
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
2.5. Saving and investment avg. 2006-2010, % GDP
Gross national saving
Gross fixed capital
formation
Brazil
19.3
18.1
Russia
28.0
20.6
India
34.2
31.7
China
52.0
41.9
Compare to:
EU
21.3
20.4
Not all BRIC countries have internal resources for
investment, thus more investment in infrastructure may
mean less investment elsewhere
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
 Can FDI help? Various studies (based on Danning,
Akamatsu etc.) suggest FDI are the source of quality
governance and tech transfer, not so much a
financing tool
 In 2006-2010, average yearly FDI inflow into BRIC
countries was less than 3% GDP or less than 10% of
investment
 Two differing approaches to attracting the funds to
long-term investment (including infrastructure) are
widespread (e.g. Walsh, Park and Yu 2011), socalled centralized and decentralized
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
 Centralized is either government investment or its
advanced version, directed loan-based:
 used in China with public banks+PBC, in Brazil with
BNDES (esp.after PAC)+pensions
 Centralized form reqs:
 healthy budget (little evidence of investment in
infrastructure to create short-term budget gains
 concentrated banking system
 + creating off-budget development institutions not tied by
system-wide banking regulations
 some insulation from external shocks as banking system
becomes somewhat distorted and vulnerable as it takes
on infrastructure risk
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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2. Global savings: from “glut” to deficit?
 Decentralized is based on a mature market for long-term
debt and equity instruments
 Increasingly used in China (highway SPV), much less for
Brazil, in the debt part – basic for Chile and Korea
 Decentralized long-term financing reqs:
 Large long-term internal funds (i.e. fully-funded pension
scheme or the like) Institutional environment for long-term
open market financing

(i.e. market-makers + risk management regulatory practices)
 Institutional environment for long-term open market
financing

(i.e. market-makers + risk management regulatory practices)
 Framework for private involvement (PPP, concessions etc.)
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3. The case of Russia –
a path to decentralized
financing model
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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3. The case of Russia
 Relatively low (20+% GDP) gross fixed capital
formation rate for an emerging economy
 Significant difference between gross savings and
investment
 Banking system has very small share of long-term
deposits, almost all are callable
 Bond market has plenty of long-term bonds, but most
long-term have embedded call after 2 years, making
them lower-medium-term instead
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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3. The case of Russia
 Currently, the model is highly centralized:
 main infrastructure investment is budget-sourced
 development institution (VEB) is the primary nonbudget financing source
 almost no long-term debt market
 most pension savings are locked into low-yield
government bonds
 Banking system is deconcentrated (CR4=45 but
CR20=65 etc.) and syndication is underdeveloped
 rates are unstable due to exchange-rate targeting
policy
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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3. The case of Russia
 Thus, the way to decentralized system is unlocking
pension savings and the funds dispersed inside banking
system
 The market for long-term lending needs to be created:
 VEB (DI) should co-finance market-makers both for
the long-term bond market and standardised
syndicated loan market
 The industry standards (lex mercatoria) need to be
developed:
 Self-regulating organizations (like LMA/ LSTA
APLMA), debt covenants, law issues – starting with
the market makers
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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3. The case of Russia
 Once there is liquidity in long-term bond and credit
syndication secondary markets (e.g. via credit
mutuals) – money managers (including VEB) may be
allowed to use pension savings to ramp up the
markets for syndication and long-term bonds
 The experience is based on case studies of financial
market developments by EBRD (in CEE), KfW (in
Germany), BNDES (in Brazil), NAFIN (in Mexico)
 We estimate doubling of credit syndication market to
$25 bn a year in 3 years, at the cost of $15 bn (0.2%
GDP a year) in credits, LT bond stimulus is
comparable
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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Conclusions
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
34
Conclusions
 The economy in 2012 looks to the upside and ZIRP is
on the side of long-term international investment in
emerging markets
 However, the long-term prospects are gloomy:
 the global savings glut could turn into deficit
 developed markets will need more long-term
funds to fix sovereign debt problems than today,
ergo home bias for the debt markets
 Thus, perspectives of international capital going into
the infrastructure are not impressive
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
35
Conclusions
 However important, FDI flows and international
financing are insufficient to finance long-term
investment in developing countries
 Thus, developing countries should finance long-term
development, including infrastructure, out of internal
sources
 The potential for increase in investment is present
almost in all BRIC countries
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
36
Conclusions
 Most investment in long-term investment projects in
BRIC is centralized via development institutions,
government funds or pet banking systems
 pension savings are utilized in China and Brazil,
much less in India and Russia
 elements of decentralized model are present in all
BRIC countries, but all of them lack a complete
set of elements
 the decentralized model is an infrastructure in
itself, and thus is a long-term prospect to build
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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International workshop
“Long-term S&T forecast”
Macroeconomic background for S&T forecast
IRU-HSE, 2011
Москва 2007
ЦМАКП
1. Why «economy-centric»?
General government expenditures*
27.9
26.5
30.0
28.1
25
25.6
26.3
25.0
25.9 26.1 26.2 25.9 26.1 26.1
25.5 25.5
24.6
23.2
20
25.1 24.9
24.5
23.9
24.2 23.9
23.7 23.5
23.2
22.3 22.2
21.7
25.0
22.7 22.4
22.2 21.9
16.5
20.0
15
12.6
10
8.3
15.0
6.2
6.8
5.5
5.3
4.6
3.9
5
6.0
4.6
5.0
4.7
5.3
4.3
3.7
5.0
4.2
4.1
4.7
4.7
4.2
4.7
4.8
5.1
10.0
2030
2029
2028
2027
2026
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
2005
2004
2003
2002
2001
0
5.0
-5
-3.9
-7.8
growth rate
% GDP (right scale)
-10
0.0
* Non-interest gen.gov-t expenditures minus pension and capital expenditures of the budget
39
1. Why «economy-centric»?
1.3. The need for clear priorities
Расходы на R&D expenditures 2009
(PPP USD bn)
160
R&D expenditure per researcher 2009
(‘000 PPP USD)
300
140
398.2
120
100
80
250
200
60
40
150
20
20
00
20
09
us
si
a
50
R&D workforce 2009
(‘000 work years)
20
00
20
09
us
si
a
R
R
us
si
a
hi
n
a*
in
Br
ita
at
C
d
la
n
G
re
Fi
n
e
re
a*
Ko
nc
*
pa
n
Fr
a
700
Ja
U
SA
*
G
er
m
an
y
Sw
ed
en
0
It a
ly
us
si
a
R
100
R
a*
in
hi
n
C
d
rit
a
G
re
at
B
Fi
n
la
n
ea
*
e
or
nc
K
Fr
a
Ja
pa
n
*
It a
ly
n
ed
e
S
w
m
an
y
G
er
U
S
A
*
0
500
400
1412.6
1592.4
600
* - 2008 R&D expenditure data.
300
Upfront “pro rata” R&D financing raise as existing R&D
institutions’ research profiles are conserved would only deepen
dispersion of funding and unlikely to achieve any “quantum leaps”
In research quality.
200
100
d
Fi
n
la
n
n
ed
e
Sw
It a
ly
e
nc
Fr
a
re
a
Ko
in
G
re
at
Br
ita
m
an
y
G
er
20
00
us
si
a
20
09
us
si
a
R
R
SA
U
Ja
pa
n
C
hi
n
a
0
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
40
1. Why «economy-centric»?
Sources of R&D funding 2009 (%)
100%
80%
60%
40%
20%
ed
e
n
d
Sw
la
n
Fi
n
re
a
Ko
a
hi
n
C
in
Br
ita
G
re
at
m
an
y
Fr
an
ce
G
er
pa
n
Ja
SA
U
It a
ly
20
09
us
si
a
R
R
us
si
a
20
00
0%
Foreign
Other internal sources
Private corporations sector
Government
We do not expect significant budget R&D expenditure raises. Therefore, new funding can only come from private sector.
This implies a change in existing research objectives (and research profiles) towards private demand both for applied and, in part,
for fundamental science.
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
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1. Why «economy-centric»?
1000000
100000
10000
1000
Экспорт машин и оборудования, логарифмическая шкала (долл. по ППС)
Economic impact (growth of hi-tech exports) of Russian R&D expenditures is insufficient relative
to other countries
Fmr Fed. Rep. of Germany
China
Korea
Italy
Mexico
Netherlands Canada
Spain
Sw eden
Austria
Czech repuиlic
HungaryPoland
Sw itzerlandBrazil
Finland
Slov akia
Ireland
Denmark
Portugal
India
SAR
Norw ay
Romania
Slov enia
Turkey
Argentina
Australia
Belarus
Ukraine
New Zealand
Estonia
USA
Japan
France
United Kingdom
Russian Federation
Lithuania
Greece
Latv ia
Kazakhstan
Georgia
Azerbaij an
100
Armenia
1000000
100000
Затраты на НИОКР, логарифмическая шкала (долл. по ППС)
10000
1000
100
10
10
ЦМАКП
2. Our research plan
CMASF
Developing
methodology
stage 1 (2011)
Partners
Estimate model inputs
stage 2 (2011)
World economy and geopolitical
forecasts
Tentative forecast
Stage 3 (2012)
Industry
forecasts
Long-term industry development
potential forecasts
Stage 4 (2012)
«Macro-driven» S&T and innovation
forecast
Stage 5 (2013)
Final stage macroeconomic forecast
Stage 6 (2013)
S&T forecasts
Tentative industry forecasts
Updated
S&T
forecasts
World
economic
policies
forecasts
Long-term
cycle S&T
forecasts
Final stage industry forecasts
43
3. Our goals: solutions to labour productivity problem
Payroll (PPP USD.)
3815
4000
3500
3042
2869
3000
2500
1904
2000
1445
1500
1162
925
890
1000
Labour productivity (2011 = 100,
“first-best” scenario)
pay per single worker
"EU-7", 2008 г.
2030
2028
2026
2024
2022
2020
2018
2016
2014
2012
2010
2008
500
235
240
"EU-7": Austria, France, Germany, Italy, Spain, Netherlands, Sweden
220
190
200
180
160
145
140
119
120
100
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
2030
2029
2028
2027
2026
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
100
44
3. Our goals: solutions to energy efficiency problem
Electricity cost (cent/kWh) and mtoe-per-dollar-of-GDP
energy intensity index (2011=100)
100
100
16.9
18
16
14.8
95
14
12.7
91
90
12
10.9
10
85
80
10.2
83
8
7.3
6
4
75
2
71
энергоемкость (максимальный)
electricity prices for all consumers
wholesale electricity price for industry, Germany 2007
2030
2029
2028
2027
2026
2025
2024
2023
2022
2021
2020
2019
2018
2017
2016
2015
2014
2013
2012
0
2011
70
3. Our goals: search for new sources of economic growth
GDP growth components (average growth rates, %,
“baseline no-policy” scenario)
14
13
2.6
3.9
0.5
0.2
5.2
0.4
3.1
0.8
0.1
1.5
2.3
2.5
0.8
1.7
2.0
0.9
1.4
1.3
0.6
2.4
2.4
1.4
-4.6
-2.5
-3.7
-5.2
-5.6
-4
-5
-6
-7
0.9
1.6
-1.1
-3.3
1.0
2.7
-1.6
3.0
-1.9
1.0
1.0
0.8
0.7
0.1
0.5
2.0
1.9
1.8
1.9
1.0
1.0
1.2
0.9
0.9
2.5
2.8
3.0
3.0
-2.6
-2.7
-2.2
1.2
1.0
2.0
0.9
1.0
5.5
3.0
0.1
-0.5
0.0
1.0
0.2
0.9
0.1
0.0
0.6
1.5
1.5
0.9
0.6
1.2
1.8
-0.9
-1.2
-2.6
1.8
0.1
0.6
0.1
0.6
0.1
0.6
1.7
0.1
0.5
1.4
1.5
1.5
1.7
0.9
0.9
0.8
0.9
0.9
2.9
2.7
2.6
2.6
2.5
2.6
-1.2
-1.1
-1.0
-0.9
-1.2
-1.4
-1.4
2030
6.7
0.9
2029
1.2
6.7
2
1
0
-1
-2
-3
1.1
0.5
2028
5.6
2.2
2027
0.4
2026
0.6
2025
3.2
2024
5
4
3
2.1
2022
9
8
7
6
0.4
2021
12
11
10
0.5
-4.9
-6.3
-3.5
-1.5
-8
-9
-10
Private Consumption
Government Consumption
Investment
Export
Import
2023
2020
2019
2018
2017
2016
2015
2014
2013
2012
2011
2010
2009
2008
2007
2006
-11
-12
Inventories+Errors
GDP
3. Our goals: export potential
Exports commodity structure (%)
100
90
80
32 33 32 31 31 31 32 32 32 33 33 33 34 34 34 35 35 35
35 36 36 37 37
70
60
7 5
6
8
8
8
9
9 10 11 11
12 13 13 14 15
16 17
50
17 17 18 18 19
20
62
62 60 61 60 59 59 58 57
56 55 53 52 51 50
50 49
48 47 46 45 44
2026
30 61
2010
40
Export growth potential, forecasts by
industry (2030/2011, times)
10
2030
2028
2024
2022
2020
2018
2016
2014
2012
2008
0
1.0
1.5
2.0
2.5
3.0
3.5
4.0
Производство машин и оборудования
Oil, gas, petroleum products
Machinery&equipment
Other goods
4.0
Производство транспортных средств и оборудования
3.8
3.7
Производство электро- и оптического оборудования
Сельское хозяйство, охота и лесное хозяйство
3.6
Рыболовство и рыбоводство
3.3
Производство пищевых продуктов
3.3
Производство изделий из кожи, обуви
3.0
Текстильное и швейное производство
2.7
Деревообработка
2.6
Производство резиновых и пластмассовых изделий
2.6
Химическое производство
2.4
2.3
Производство стройматериалов
Металлургическое производство и металлоизделий
1.8
Целлюлозно-бумажное производство, полиграфия
1.7
Добыча нетопливно-энергетических полезных ископаемых
Добыча топливно-энергетических полезных ископаемых
4.5
1.7
1.2
Производство нефтепродуктов и ядерных материалов
1.2
Прочие производства
1.2
Center for Macroeconomic Analysis and Short-term Forecasting, Moscow, Russia
47
3. Что мы хотим получить: импортозамещение
Import elasticity to domestic demand components
5.0
8.2
4.3
4.5
4.0
4.0
3.5
3.2
3.2
3.0
3.1
2.5
2.5
2.0
1.7
1.8
1.6
1.5
1.1
1.1
0.90.7
0.7
1.0
0.6 0.7
0.5
0.7
0.4
Consumer imports to private consumption
2027
0.2
2028
2025
2023
2024
2021
2019
2020
2018
2017
2015
2016
2014
2013
2011
2012
2010
2009
2008
2006
2007
2005
2004
2002
2003
2001
0.0
2022
0.4
2026
0.8
Machinery imports to investment
0.5
0.5
0.8
0.7
0.6 0.6
2030
1.0
2029
1.0
1.0