Transcript Why the Rich May Favor Poor Protection of Property Rights

Development Based on Commodity Revenues:
Theory and Russian Evidence
Konstantin Sonin,
New Economic School
February 18, 2011
Leontieff Center, St. Petersburg
1
Road map
 Basic tradeoff:
– fantastic growth in Aze, Kaz, Rus, Tkm since 1999
– volatility and a looming long run “resource curse”
Economic Growth in Resource Rich Countries
– theoretical arguments and empirical evidence.
Policy Goals and Policy Tools
– development strategy for resource-rich countries
Diversification Policies in Resource Rich Countries
– actual policy response of countries to resource riches
Assessment
– How successful were they?
Konstantin Sonin / New Economic School
February 18, 2011
2
Commodity boom underpinned growth...
Impressive growth records in oil and gas producing
countries in the region
– Turkmenistan, Azerbaijan, Kazakhstan, Russia
 In particular in nominal (US dollar) terms
Cumulative Nominal US$ GDP Growth, 1999–2008
Cumulative Real GDP Growth, 1999–2008
(In per cent, vertical axis)
(In per cent, vertical axis)
1,200
350
Turkmenistan
300
Azerbaijan
250
Turkmenistan
800
150
Growth
200
Growth
Azerbaijan
1,000
Kazakhstan
Russia
100
600
Kazakhstan
Russia
400
200
50
0
0
0
5,000
10,000
15,000
GDP per capita in 1998 at PPP
Sources: International Monetary Fund, EBRD, and authors' calculations.
Konstantin Sonin / New Economic School
20,000
0
5,000
10,000
15,000
20,000
GDP per capita in 1998 at PPP
Sources: International Monetary Fund, EBRD, and authors' calculations, based on
2007 data for Turkmenistan.
February 18, 2011
3
… but at the expense of great risks
large growth corrections during crisis: macro volatility
Potential “resource curse” affecting long run growth
Average Real GDP Growth in Selected Oil-Rich Countries, 1981–2000
(In per cent, annualized, vertical axis)
12
10
8
Growth
6
4
NO
AE
Non-oil sample trend line
QA
2
KW Oil sample trend line
0
SA
-2
LY
-4
0
5 000
10 000 15 000 20 000 25 000 30 000 35 000 40 000 45 000 50 000
GDP per capita in 1980 at PPP, US$
Sources: IMF, Energy Information Administration, and EBRD calculations. Trend lines are fitted based
on regressions for a broad sample of 138 countries. Oil-rich countries are defined as countries where
oil production valued at international prices exceeded 10 per cent of GDP in 1980. These countries are
marked with large circles.
Konstantin Sonin / New Economic School
February 18, 2011
4
Commodity rents and development
Commodity rents may be a blessing
– developing countries fail to catch up because of an
underdevelopment trap (fixed costs to investment;
externalities across sectors): “big push” needed
– commodity export revenues could finance such big push
 Commodity rents might be a curse
– depress long-run growth by causing macroeconomics
distortions and excess volatility
– have a negative effect on political institutions
Konstantin Sonin / New Economic School
February 18, 2011
5
Commodity rents and investment
Reliance on commodity exports
– leads to high terms-of-trade volatility
– discourages investment, especially if financial systems
are not sufficiently developed
– affects human capital (uncertain returns)
Dutch disease
– underinvestment in high learning by doing technologies
(manufacturing), or technologies that are otherwise
particularly beneficial for long run growth
Konstantin Sonin / New Economic School
February 18, 2011
6
Macro lessons learned
 in macro, little resembled petrostates of late 70s
 fiscal conservatism (up until 2008)
– budget control
– debt repayment
– stabilization funds, despite huge political pressure
 mild political pressure on Central Bank (up until
2008)
 control of ‘white elephants’ (up until 2007)
– lesson “unlearned” by 2010
Konstantin Sonin / New Economic School
February 18, 2011
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“Resource curse 2.0”: Institutions
 Commodity resources discourage investment in good institutions
– good institutions limit rent seeking
– flexibility to “seek” rents is more valuable to politicians in resource-rich
environment
 “Institutional Trap”
– if institutions are bad to start with in a resource-rich economy, they are not
likely to improve
 Interactions with inequality
– when the same amount of rents is appropriated by fewer members of the elite,
rent-seeking strategy becomes even more attractive
– in resource rich environment, inequality and poor institutions are mutually
reinforcing
– high inequality is bad for growth (particularly with imperfect capital markets.
as poor with entrepreneurial skills have no access to capital)
Konstantin Sonin / New Economic School
February 18, 2011
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“Resource curse 2.0”: Evidence
Oil revenues have adverse impact :
– on property rights (Guriev, Kolotilin, and Sonin, JLEO,
2011)
– on corporate governance (Durnev and Guriev, 2009)
– on media freedom (Egorov, Guriev, and Sonin, 2009)
– on democracy (Ross, 2001, 2009)
– on regulation and reforms to improve business climate
in non-resource sectors (Amin and Djankov, 2009)
– on political stability and likelihood of civil unrest (Ross,
2006)
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February 18, 2011
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Diversification
10
Why diversification
 lowers vulnerability to external shocks
 reduces relative size of resource rents and creates
incentives to improve institutions (commitment
device)
Konstantin Sonin / New Economic School
February 18, 2011
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Diversification Tools: Public Investment
“Vertical” policies: preferential treatment of
specific non-resource industries
– difficult to get right, especially in absence of good
institutions
– crowd out private investment
“Horizontal” policies: investment in education,
infrastructure
– more likely to complement private investment
– again, less efficient in weak institutional environment
Konstantin Sonin / New Economic School
February 18, 2011
12
Diversification Tools: Macro Policies
Sovereign wealth funds
– prevent (in short-run) appreciation of currency or hikes
in inflation, preserve (in short-run) competitiveness
– smooth government expenditures over time
– commitment device to prevent government’s procyclical spending
– could be used to finance development policies
Taxation of resource exports
– per se cannot play a significant role in redirecting
investment in an open economy (capital just flows to
other countries, not to “right sectors”)
Konstantin Sonin / New Economic School
February 18, 2011
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Diversification Tools: Financial Development
 helps to smooth effects of resource price volatility
 benefits non-resource sectors, which are more
dependent on external finance (cf. Rajan-Zingales)
– works as a horizontal industrial policy
 helps to match entrepreneurial ideas and funding
 may help reduce (effects of) inequality
 instruments:
– improved regulation of banks and securities markets
– deposit insurance
– effective court systems
Konstantin Sonin / New Economic School
February 18, 2011
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Diversification Tools: Fighting Inequality
 makes it easier to reform institutions in resource rich environments
 instruments:
– in developing countries typically implemented through government spending
rather than taxation
– ideally, through structural policies: labour mobility and education
Gini Coefficients in Selected Commodity Exporters
(In per cent, vertical axis)
60
50
Commodity exporter sample trend line
GINI Coefficient
40
30
Other countries trend line
20
10
0
0
10 000
20 000
30 000
40 000
50 000
60 000
70 000
80 000
GDP per capita in 1980 at PPP, US$
Sources: UN WIDER, IMF, WTO and EBRD calculations. Higher values of Gini coefficient correspond
to higher income inequality. Trend lines are fitted based on regressions for a broad sample of
countries, where Gini coefficients are available for 2002–06, taking the latest observation available.
Commodity exporters are defined as countries where mining and fuel exports accounted for more than
half of total merchandize exports. These countries are marked with large circles.
Konstantin Sonin / New Economic School
February 18, 2011
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Examples of Substantial Progress
Diversification away from oil and gas is challenging,
but there are examples of substantial progress
– Chile: competitive agriculture and fishing (wine, salmon
farming)
– Malaysia: high-tech manufacturing integrated into South
Asian and World production chains
– Indonesia: medium-to-high-tech manufacturing,
agriculture
– Mexico: high-tech manufacturing based primarily on FDI
by US firms
Konstantin Sonin / New Economic School
February 18, 2011
16
Transition Countries
 Russia and Kazakhstan made diversification
cornerstone of development agenda
Public investment increased in all countries over
commodity boom period
– 3% to 4.5% of GDP in Russia;
– 3% to 6% of GDP in Kazakhstan;
– 2% to 10% of GDP in Azerbaijan.
Public spending on education:
– 2.9 to 4% of GDP in Russia;
– 3.3 to 4.2% of GDP in Kazakhstan
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February 18, 2011
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Policies: Financial Development
Credit to the Private Sector (in per cent of GDP)
Kazakhstan
Russia
70
70
60
60
Retail
50
50
40
40
30
30
20
20
10
0
Jan-00
Retail
10
Corporate
Jan-02
Jan-04
Jan-06
Corporate
0
Jan-00
Jan-08
Sources: Central Bank of Kazakhstan and EBRD.
Jan-02
Jan-04
Jan-06
Jan-08
Sources: Central Bank of Russia and EBRD.
Other Transition Countries Average
Azerbaijan
25
50
20
40
15
30
Retail
Retail
20
10
Corporate
10
5
Corporate
0
Mar-05
0
Mar-06
Mar-07
Mar-08
Sources: Central Bank of Azerbaijan and EBRD.
Mar-09
Dec-99
Dec-01
Dec-03
Dec-05
Dec-07
Sources: EBRD Banking Survey, simple average.
 Despite fast GDP growth (e.g., 8-fold in Russia in US$ nominal terms
between 1998 and 2008) credit-to-GDP ratios have been growing
rapidly
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February 18, 2011
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Policies: Financial development
Loans-to-Deposits Ratio
Growth of Credit to the
(in per cent)
(year on year, in p
200
120
Azerbaijan
190
Kazakhstan
180
100
170
160
150
80
Russia
Ukraine
140
60
130
120
40
110
100
20
Other transition
countries (av.)
90
80
Dec-99
Apr-01
Aug-02
Jan-04
May-05
Oct-06
Feb-08
Sources: Central Banks of Russia, Azerbaijan, Kazakhstan, EBRD Banking Survey and
EBRD calculations. Simple average for other transition countries.
0
Jan-01
Jan-02
Jan-03
Jan-04
Ja
Sources: Central Banks of Russia, Ukraine, Kazak
 Rapid growth made possible due to entry of foreign banks
– Especially in Kazakhstan
 Loan-to-deposit ratios have been very high, well above regional
average
Konstantin Sonin / New Economic School
February 18, 2011
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Policies: Financial Development
Number of Financial Sector Transition indicator Upgrades
(2000–08)
8
Banking
7
NBFI
6
5
4
3
2
1
Nil
0
Russia
Other transition
countries (av.)
Kazakhstan
Azerbaijan
Turkmenistan
Source: EBRD, based on transition indicators for banking sector and non-bank financial institutions.
 financial sector growth was facilitated by number of structural
reforms
– deposit insurance, credit bureaus, interest rates disclosure, revisions to
legislation on collateral and bankruptcies
 non-bank finance has also been growing, albeit at a lower pace
 only in Russia reforms outpaced the non-oil-rich transition country
average
Konstantin Sonin / New Economic School
February 18, 2011
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Policies: Sovereign wealth funds
Sovereign Wealth Fund Assets
(In per cent of GDP, selected countries)
300
250
200
150
100
50
Kiribati
UAE
Brunei
Kuwait
Saudi Arabia
Norway
Bahrain
Libya
Qatar
Algeria
Kazakhstan
Azerbaijan
Oman
Russia
Malaysia
Nigeria
Australia
Iran
Venezuela
0
Sources: SWF Institute and World Bank. Data for 2008 or latest estimate available.
Azerbaijan set up State Oil Fund in 1999
Kazakhstan established National Fund in 2000
– Peaked at 30% of GDP (the largest in relative terms)
Russia: Stabilization Fund in 2004, subdivided into Reserve
Fund and National Wealth Fund in 2008
Konstantin Sonin / New Economic School
February 18, 2011
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Assessment
22
Assessment: Diversification
Share of Higher-Value-Added Manufacturing in Exports
(In per cent, selected countries)
Share of Higher-Value-Added Manufacturing in Exports
(In per cent, selected countries)
80
20
70
15
60
50
10
40
30
5
20
10
0
Source: UNIDO.
2000
2005
Source: UNIDO.
2000
Germany
Malaysia
Mexico
Czech Rep.
Slovak Rep.
Poland
Georgia
Romania
Indonesia
Macedonia
Australia
Norway
Russia
Macedonia
Australia
Norway
Russia
Albania
Saudi Arabia
Qatar
Chile
Kuwait
Venezuela
Nigeria
0
2005
 measures of structure of output / exports are distorted by oil price
effects
– directly (valuation)
– indirectly (short-term incentives to produce and export)
 Even Norway, Malaysia lost positions in UNIDO “Industrial
Competitiveness” indices during the boom
 compare oil / output structure at similar points in oil price cycle?
Konstantin Sonin / New Economic School
February 18, 2011
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Diversification in Russia: Comparison
Russia: Structure of Merchandize Exports
(In per cent)
Russia: Structure of Gross Domestic Product
(In per cent, based on quarterly data)
100
90
10.3
100
7.9
10.7
90
80
80
70
70
60
44.0
49.9
60
68.3
69.0
50
75.4
50
40
40
30
30
50.5
49.8
45.1
20
20
10
43.5
18.5
17.9
3.0
0
2005q1
Agriculture
10
14.2
2.5
2.4
2008q1
Manufacturing
2009q1
Other
Extraction
Sources: Rosstat and EBRD calculations. Excluding net taxes.
Agriculture includes fishing. "Other" include services, and
construction.
0
5.9
5.1
6.2
Dec04-Apr05
Dec07-Apr08
Dec08-Apr09
Higher-value-added manufacturing
Other
Crude oil and gas
Sources: Rosstat and EBRD calculations. Higher value added
manufacturing goods include machinery, equipment, and vehicles.
Other goods include refines oil and petrochemicals.
 Comparable periods in terms of average oil price:
– Dec04-Apr05 and Dec08-Apr09
 No evidence of diversification, there may be slight decline in
manufacturing
Konstantin Sonin / New Economic School
February 18, 2011
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No diversification of Russian GDP in 2002-2008
100%
90%
Communal utilities, social services
Healthcare
Education
Governance and defense
Real estate
Finance
Transport/Telecom
Hotels/Restaurants
Trade
Construction
Electricity, gas, water, incl.distribution
Manufacturing
Mining
Fishing
Agriculture
80%
70%
60%
50%
40%
30%
20%
10%
0%
2002
2003
2004
Konstantin Sonin / New Economic School
2005
2006
2007
2008
February 18, 2011
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Structure of exports: Russia and Kazakhstan
Russia: Structure of Merchandize Exports
Kazakhstan: Structure of Merchandize Exports
(In per cent)
(In per cent)
100
90
80
100
Oil US$ 28
(2008 prices)
Oil US$ 30
(2008 prices)
90
80
70
70
60
60
50
50
40
40
30
30
20
20
10
10
0
1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
High-tech manufactures
Other manufactures
Agriculture
Sources: WTO and authors' calculations.
Mining and fuels
Oil US$ 28
(2008 prices)
Oil US$ 30
(2008 prices)
0
1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
High-tech manufactures
Other manufactures
Agriculture
Mining and fuels
Sources: WTO and authors' calculations.
 exports structure suggests growing oil dependence in Kazakhstan and
Azerbaijan
– Partly reflects successful exploration, largely led by international firms (PSAs)
 in Russia structure of exports was similar at similar points in the oil
price cycle
Konstantin Sonin / New Economic School
February 18, 2011
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Structure of exports: Azerbaidzhan and non-oil countries
Azerbaijan: Structure of Merchandize Exports
Other Transition Countries:Structure of Merchandize Exports
(In per cent)
(In per cent)
100
90
80
100
Oil US$ 28
(2008 prices)
Oil US$ 30
(2008 prices)
90
80
70
70
60
60
50
50
40
40
30
30
20
20
10
10
Oil US$ 28
(2008 prices)
0
1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007
0
1996
High-tech manufactures
High-tech manufactures
Other manufactures
Agriculture
Sources: WTO and authors' calculations.
Mining and fuels
1997
1998 1999
Oil US$ 30
(2008 prices)
2000
2001
2002
Other manufactures
2003
2004 2005
Agriculture
2006
2007
Mining and fuels
Sources: WTO and authors' calculations, based on weighted average of AM, BG,
BY, CZ, EE, GE, HU, KG, LV, LT, MK, MD, MN, PL, RO, SK, SI, TR, UA.
 in other transition countries share of manufacturing exports has
been increasing on average
Konstantin Sonin / New Economic School
February 18, 2011
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Commodity Dependence and Crisis Impact
Commodity Dependence and Crisis Impact
(Deviation of 2009 growth forecast from the 1999–2008 average growth)
10
Qatar
5
Yemen
(Deviation of 2009 growth forecast from the 1999–2008 average growth)
0
-2
Deviation (in percentage points)
Deviation (in percentage points)
Assessment: Impact of Crisis
0
-5
-10
-15
Russia
-20
Angola
Latvia
-25
Moldova
-4
Kyrgyz
Mongolia
-6
-8
Kaz
-10
Armenia
-12
Azerbaijan
-14
Ukraine
Russia
-16
-18
Latvia
-20
0
20
40
60
80
100
Share of fuel and commodities in merchandize exports
Sources: WTO, International Monetary Fund, and authors' calculations, based on
World Economic Outlook April 2009 forecasts, 129 countries.
0
20
40
60
80
100
Share of fuel and commodities in merchandize exports
Sources: WTO, EBRD, and authors' calculations, based on May 2009 EBRD
forecasts.
 no clear link between commodity dependence and severity of the
crisis on average (in terms of macro impact on growth)
– indirect measure: deviation of 2009 forecast from the 1999-2008 average
growth
– if anything, the effect of commodity wealth is positive
 all countries in the region drew on their fiscal and monetary reserves
to finance sizable fiscal and monetary stimulus packages
Konstantin Sonin / New Economic School
February 18, 2011
28
Assessment: Financial Development
Table 2. Determinants of Impact of Global Crisis on Growth
 Financial development
Model
supported real sector, but also Method
Dependent variable
exacerbated commodity cycleAverage growth, 1999–2008
(per cent a year)
– very high leverage
GDP per capita
Log, PPP
– rapid consumer credit growth Oil rents
per cent of GDP)
– credit growth averaging 50%+, (In
Share of commodities
up to 115%, put strain on bankin merchandize exports
Private sector credit-to-GDP
risk management and on
Loan-to-deposit ratio
supervisors
A
B
C
D
E
OLS
Difference between 2009 growth forecast and 1999 –2008 av.
–1.067
(0.164)***
–1.031
(0.174)***
–1.144
(0.189)***
–1.036
(0.138)***
–1.108
(0.149)***
–3.225
(0.520)***
–2.799
(0.435)***
–3.302
(0.521)***
–2.454
(0.329)***
–2.338
(0.206)***
0.073
(0.025)***
0.036
(0.021)*
0.030
(0.018)*
0.017
(0.009)*
0.016
(0.007)**
0.072
(0.024)***
0.028
(0.013)**
0.023
(0.008)***
0.025
(0.008)***
–0.018
(0.008)**
–0.018
(0.008)**
–0.019
(0.008)**
0.046
–0.053
0.028
 Overall, some cross-country Quality of institutions, index (0.129)
(0.115)
(0.126)
of higher-value-added
0.005
0.014
0.007
evidence that while financial Share
manuf and food in exports
(0.017)
(0.021)
(0.016)
28.690
23.909
28.199
22.451
20.920
development softened the Constant
(4.873)*** (4.449)*** (4.943)*** (2.711)*** (2.193)***
0.64
0.63
0.61
0.62
0.58
impact of crisis, excessively R
Number of observations
101
101
101
135
135
high loan-to-deposit ratios Notes: Robust standard errors in parentheses. Values significant at the 10% level
are marked with *; at the 5% level, with **; at the 1% level, with ***.
exacerbated it
2
Konstantin Sonin / New Economic School
February 18, 2011
29
Institutions Matter
30
Assessment: Institutions
 To look at diversification,
compare export structures in
1991–92 and 2001–03 (oil at
US$ 30-31 in 2008 prices)
 Use share of food and highervalue-added manufacturing in
exports (WTO data)
– Technologically distanced from oil
and gas
– Bulk of developed countries’
exports (from 70% in Germany to
30% in Australia, but less than
10% in Rus, Kaz, Aze)
Konstantin Sonin / New Economic School
Table 3. Determinants of Export Structure
Model
A
B
C
D
E
Method
OLS
Dependent variable
Share of hva manufacturing and food in exports, 2001 –03
Exports structure in 1991–92
0.784
(0.061)***
0.806
(0.059)***
0.803
(0.058)***
0.815
(0.073)***
0.756
(0.067)***
GDP per capita
Log, PPP
1.779
(0.935)*
–2.874
(1.769)
–2.472
(1.818)
–3.664
(2.057)
–5.608
(2.094)**
Oil rents
(In per cent of GDP)
–0.230
(0.114)**
0.013
(0.127)
–0.051
(0.150)
0.027
(0.151)
0.159
(0.144)
1.074
(0.620)*
3.779
(0.943)***
1.130
(0.484)**
0.009
(0.041)
0.012
(0.093)
–0.045
(0.103)
Oil rents * SWF dummy
Quality of institutions, index
1.222
(0.549)**
Private sector credit-to-GDP
(period average)
Constant
R2
Number of observations
–5.487
(7.724)
30.282
(14.615)**
26.709
(14.824)*
0.72
0.75
0.76
0.79
0.79
96
89
86
43
25
39.716
51.026
(16.101)** (18.151)**
Notes: Robust standard errors in parentheses. Values significant at the 10% level are marked
with *; at the 5% level, with **; at the 1% level, with ***. In Column D only countries with
the value of index of institutions below the median are included. In Column E only countries
where commodities accounted for more than 40 per cent of merchandize exports at the start
of the period are included.
February 18, 2011
31
Assessment: Institutions
 export structures are generally “sticky” (correlation is 0.85)
 oil rents suppress diversification, but this effect becomes
insignificant when quality of institutions is included
 quality of institutions is statistically and economically significant
 one standard deviation improvement in the quality of institutions is
associated with a 4 to 6 p.p. increase in share of higher-value-added
manufacturing and food in merchandize exports
– relationship is even stronger in the subsample of countries with weaker
institutions (index below median)
– result holds in a small subsample of countries where commodities accounted
for 40%+ of merchandize exports at the start of the period
 financial development per se or existence of sovereign wealth fund
do not appear to have significant impact
Konstantin Sonin / New Economic School
February 18, 2011
32
Assessment: Institutions
 improving institutions remains a challenge
World Bank Governance Indicators: Overall
World Bank Governance Indicators: Rule of Law
(Higher values correspond to better institutions)
(Higher values correspond to better institutions)
1
0
0.0
-1
-2
-0.5
-3
-4
-1.0
-5
-6
-7
-8
-1.5
-9
-10
1996
1998
AZE
2000
KAZ
2002
2003
RUS
2004
2005
TMN
2006
2007
2008
-2.0
1996
Other trans. countries (av)
1998
AZE
KAZ
World Bank Governance Indicators: Voice and Accountability
0.5
0.0
0.0
-0.5
-0.5
-1.0
-1.0
-1.5
-1.5
-2.0
-2.0
AZE
KAZ
2002
RUS
2003
2004
RUS
2004
TMN
2005
2006
2007
2008
Other trans. countries (av)
(Higher values correspond to better institutions)
0.5
2000
2003
World Bank Governance Indicators: Government Effectiveness
(Higher values correspond to better institutions)
1998
2002
Source: World Bank and Kaufmann et al. (2009).
Source: World Bank and Kaufmann et al. (2009).
-2.5
1996
2000
2005
TMN
Source: World Bank and Kaufmann et al. (2009).
Konstantin Sonin / New Economic School
2006
2007
2008
Other trans. countries (av)
-2.5
1996
AZE
1998
2000
KAZ
2002
RUS
2003
2004
TMN
2005
2006
2007
2008
Other trans. countries (av)
Source: World Bank and Kaufmann et al. (2009).
February 18, 2011
33
Corruption
World Bank Governance Indicators - Control of corruption
0
0
0
-1
-1
-1
-1
-1
-2
1996
1998
Azerbaijan
2000
Kazakhstan
Konstantin Sonin / New Economic School
2002
2003
Russia
2004
2005
Turkmenistan
2006
2007
2008
Other transition countries (averag
February 18, 2011
34
3
A Russian problem…
IRL
USA
BEL
FRA
ESP
CHL
JPN
PRT ARE
BWA
SVNKWT
EST
URY
ISR
HUNBHR
ZAF
KOR
SVK CZE
GRCITA
CRI MUS
JOR
MYS LVA
LTU
SAU
POL
TUN
TUR
HRV
NAM
SLB
TTO
MDG BFA
BGR
MAR
LSO
SEN
COL
ROM
THA
MRT
PAN
BRA
MLI
LKA
ERI
GHA IND EGY
LBN DZA
SLV
MEX ARG
IRN
JAM
PER
MKD
MNG
GEO
GUY
PHLFJIUKR
SYR
SWZ
GAB
YEM MOZTGO
NIC
ARM
DJI
DOM RUS
HND
NPL GMB
TZA ZMB
ALB CHN
MDA
VNM
RWA
NER ETH
GIN BOL
MWI
BDI
IDNECU
UGA COM
BLR
GTM
SLE
PAK
ZAR
KEN
AZE VENKAZ
KGZ
UZB
PNG
GNB BEN
TJK
CAF
AGO
LAO
KHM
CMR
BGD
PRY
NGA TCD
CIV ZWE
COG
HTI SDN
Russia is 1.04 st.dev.
below the line;
-2
-1
0
1
2
FIN
NZLSGP
DNK
CHE
SWE
NLD
AUT NOR
AUS
GBR
CAN
DEU
-2
-1
0
e( loggdppcppp | X )
coef = .69167874, se = .04034047, t = 17.15
Log GDP per capita, PPP, 2005
Konstantin Sonin / New Economic School
1
2
Same if control for
education, size,
inequality etc…
February 18, 2011
35
Media freedom and Government Effectiveness
CHE
DNK
Replay
NZL
NOR
FIN
CAN NLD
SWE
AUS
GBR
AUTUSA BEL
IRL
FRADEU
ESP
CHL
JPN
ISR CYP
PRT
ARE
MYS
SVN
EST
KOR
BWA
GRC
ZAFCZE
SVK
LTU
MUS
HUN
OMN
ITA
LVA
QAT
BHR
POL
TUN
URY TTO CRI
THA HRV
KWT
NAM
BTNJOR
JAM
BRA BGR
TUR MEX
CHN
PAN
IND
MRT
MAR
YUG
GUY
COL
SEN
MKDROM LSO
GHA
SAU
EGYARM
ARG PHL
SLV
ALB
MLI
LKA
LBN
BEN
VNM
RUS
MNG FJI
TZA
MDG MOZ
IDN
UGA
PER
PAK
DOM
DZA
BOL
BIH BFA
RWAIRN
CUB
GAB
UKR
GMB
HND
NIC
SWZ
CMR
KEN
BGD
DJI
NER
MDA
LBY
KAZAZE
PNG
GEO
ZMB
MWI
KGZ
ECU
NPL
GTM
TMP
ETH
KHM
SYR
YEM
NGA
ERI
TCD
VEN
GIN
TJK
LAO
PRY
UZB
BLR
ZWE
AGO
AFG
SDN ZAR
GNB
TGOCIV
BDI
GNQ
SLE
TKM
COG COM
IRQ
SLB
MMR
CAF
PRK
LBR HTI
SOM
-2
-1
0
1
2
SGP
-.4
-.2
0
e( mf100 | X )
.2
.4
coef = 3.0090516, (robust) se = .23436654, t = 12.84
Egorov, Guriev, and Sonin (2009)
Konstantin Sonin / New Economic School
February 18, 2011
36
Media freedom and Control of Corruption
3
Replay
FIN
NZL
DNK
SWE
AUT
CHE
NOR
NLD
GBR
AUS
CAN
DEU
USA
IRL BEL
ESP
FRA
CHL
ARE
JPN PRT
SVN
BWA
OMN
KWT
ISR CYP EST
BHR BTNQAT
HUN
ITA URY
CRI
GRC
ZAFCZE
JOR
SVK
LTU
MUS
MYS
TUN
LVA
SAU
POL
KOR
HRV
NAM TTO
FJI
BGR
MRT
BFA
MAR
BRA
MDG
PAN
LSO
EGY COL LKA
TUR
ROM MEX
THA
CUB
SLV
MLI
NIC
PER
IND
SEN TMPGHA
RWA
ARG
BEN
DZA
LBN
MNG
DOM
ERI
JAM
MKD BIH YUG PHL SLB GUY
SYR
CHN
IRN
GAB
TZA
SWZ GMB
NPL
GTM
ARM
GNB
DJI
HND
COM
ECU
SLE
RUS
ZMB
ALB
MOZ
VNM YEM
LBY
BDI
CMR KEN GEO
MWI
UGA
BOL PNG
TGO ETH
UKR
IDN NER
BLR
KHM
ZAR
KGZ MDA
VEN
LAO
LBR
PAK
GIN
CIVAGO
UZB
KAZ
CAF PRY
TJK
AZE
TCD
BGD
NGA
SDN
TKM ZWE
AFG
HTI
COG
IRQ
PRK
MMR
GNQ SOM
-2
-1
0
1
2
SGP
-.4
-.2
0
e( mf100 | X )
.2
.4
coef = 2.8623033, (robust) se = .26412487, t = 10.84
Egorov, Guriev, and Sonin (2009)
Konstantin Sonin / New Economic School
February 18, 2011
37
Next South Korea?
Income per capita, purchasing power parity.
Source of data and forecast: World Economic Outlook October 2009, IMF.
Russia
Korea 11 years earlier
$25,000
$15,000
$10,000
$5,000
$-
19
92
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
20
10
20
11
20
12
20
13
20
14
GDP per capita, PPP
$20,000
Konstantin Sonin / New Economic School
February 18, 2011
38
Institutions much worse in Russia
Korea, % rank in 1997
Russia, % rank in 2008
Control of corruption
Rule of law
Regulatory quality
Government Effectiveness
Political stability and absence of
violence/terrorism
Voice and Accountability
0
Konstantin Sonin / New Economic School
25
50
75
100
February 18, 2011
39
Conclusion
commodity revenues provide significant opportunities for
financing investment but may also negatively affect growth
– terms of trade volatility has negative impact on investment
– structural shifts in accumulation/allocation of physical/human
capital
– incentives to engage in rent-seeking rather than improve
institutions
diversification may be pursued via variety of strategies
–
–
–
–
direct investment in non-resource sectors
investment in education and infrastructure, fiscal redistribution
financial sector development
sovereign wealth funds
Konstantin Sonin / New Economic School
February 18, 2011
40
Conclusion, ctd
 diversification policies can be successful, but success
crucially depends on institutions
– democracy, media freedom, property rights, corporate
governance, low tolerance for corruption
– improving these institutions is a particularly challenging task in oilrich societies
 post-communist oil-rich countries have done well in terms
of prudent macro policies
 financial sector development
– played an important role in supporting the real sector
– extraordinary financial services boom fuelled by external
borrowing in part amplified the effects of the commodity cycle
Konstantin Sonin / New Economic School
February 18, 2011
41
Sources
 Chapter 4 of the 2009 EBRD Transition Report
– background paper “Development Based on Commodity Revenues”, with Sergei
Guriev and Alexander Plekhanov
 Own work on resource-dependence
– Why Resource-Poor Dictators Allow Freer Media (with Georgy Egorov and
Sergei Guriev), American Political Science Review, November 2009
– Determinants of Nationalizations in the Oil Sector (with Sergei Guriev and
Anton Kolotilin), Journal of Law, Economics, and Organization, 2011
 Sergei Guriev and Ekaterina Zhuravskaya work
– Why Russia is Not South Korea, Journal of International Affairs, 2010
Konstantin Sonin / New Economic School
February 18, 2011
42