1 political economy of the natural resource curse rick van der ploeg oxcarre, university of oxford
TRANSCRIPT
1
POLITICAL ECONOMY OF THE NATURAL RESOURCE CURSE
Rick van der PloegOxCarre, University of
Oxford
2
OVERVIEW OF TALK
Historical and case-study evidence of resource curse
Four explanations of resource curse Cross-country and panel evidence Focus on role of volatility and financial development Sustainable management of natural resources,
Hartwick rule and genuine saving Policy proposals Summing up
3
POOR DESPITE NATURAL RESOURCE WEALTH Nigeria: oil revenues per capita increased from $33
in 1965 to $325 in 2000 but income per capita stagnated at about $1100 since its independence in 1960. Between 1970 and 2000 those on less than $1/day increased from 26 to almost 70%. Top 2% had as much as bottom 17 % in 1970 but staggering bottom 55% in 2000. Declining TFP growth: -1.2% per year. Only a third of capacity is utilized. Successive military dictatorships have plundered oil wealth.
Hopefully, the future will be brighter.
4
GDP / capita1970
GDP / capita2005
CorruptionRank/141
% less than$1 / day
Gini Law andOrder
Congo 221 85 1 63.0 0.99
Nigeria 358 373 11 70.8 43.7 2.03
Indonesia 515 849 136 7.5 34.3 2.69
Botswana 1,611 3,311 101 23.5 56.6 4.47
Russian F 1,962 2,004 28 2.0 39.9 3.47
Venezuela 5,442 4,530 57 8.3 44.1 3.62
Libya 4,815 6,905 89 3.26
Norway 24,895 38,075 133 0 25.8 6.00
Source: World Bank Development Indicators 2006 (2000 US $) andInternational Country Risk Guide, The PRS Group Inc.
5
DISAPPOINTING PERFORMANCE DESPITE NATURAL RESOURCES 17th century Spain despite gold/silver from New
World. Resource Holland did much better. Negative growth rates during past decades: e.g.,
Venezuela, Iran,Libya, Kuwait, Quatar. Decline in OPEC GDP/ capita during last few
decades while other countries enjoyed growth. Gold boom in 70’s did not help South Africa much
(Stokke, 2005). Dutch economy and the Slochteren natural gas
reserves led to unsustainable welfare state.
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JapanUnited States
India
Switzerland
Italy
Korea, Rep.
United KingdomSpain
TurkeyFrance
Mexico
PakistanAustria
Burkina Faso
Hungary
IsraelGreece
Niger
Jordan
Portugal
ArgentinaMali
Burundi
Hong Kong, China
SwedenBrazil
BeninChad
Malta
Finland
Taiwan, China
Cambodia
Egypt, Arab Rep.
Paraguay
Norway
Colombia
Uruguay
Australia
Central African Republic
CanadaBelgium
Indonesia
Madagascar
Congo, Rep.
Tunisia
Panama
Denmark
Thailand
Congo, Dem. Rep.
PhilippinesGuatemala
Chile
Nigeria
Ecuador
Bolivia
Morocco
Sao Tome and Principe
Sudan
Peru
Netherlands
Ireland
SenegalEl Salvador
Togo
Ghana
CameroonNew Zealand
Costa Rica
Sri Lanka
Malawi
Algeria
Nicaragua
Honduras
Venezuela, RB
Solomon Islands
Cote d'Ivoire
Fiji
Malaysia
MauritaniaSuriname
Gabon
Saudi ArabiaGuyana
Trinidad and Tobago
Zambia
Libya
Kuwait
Liberia
Singapore
-50
5A
ve
rag
e y
ea
rly r
ea
l G
DP
per
cap
ita g
row
th 1
970
-20
04
0 20 40 60 80Natural Resources exports in percent of GDP, 1970
Figure: Growth and Natural Resources AbundanceData source: World Development Indicators, 2006
NEGATIVE PARTIAL CORRELATION BETWEENECONOMIC GROWTH AND RESOURCEABUNDANCE (not for food or agriculture exports)
Source: World Bank Development Indicators 2006
7
POSITIVE EXPERIENCES Botswana: 40% of GDP stems from diamonds but has second
highest education/GNP and highest growth rates since 1965. GDP/capita is ten times that of Nigeria. Still, inequality is high as it was during the colonial period.
Norway had huge growth in oil exports since 1971 and third largest exporter after Saudi-Arabia, but has fared fairly well.
United Arab Emirates also turned curse into blessing by investing in modernizing infrastructure and investing in welfare state and free access to education.
Mineral abundance US mid 19th to mid 20th century explains much of subsequent growth: driven by learning, IRTS and US government claimed no ultimate title to mineral rights (Habbakuk, 1962; David and Wright, 1977; Wright and Czelusta, 2004). Also, Germany and UK late 19th century.
Lessons: avoid corruption, diversify, education, and exploit complementarities linkages of manufacturing with resource sector.
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RESOURCE ABUNDANCE ASSOCIATED WITH (Gylfason and Zoega, 2002): Crowding out of non-resource exports and
foreign direct investment. Less openness. Elicits corruption and extreme rent seeking. Crowds out foreign capital, social capital,
human capital and financial capital. Erodes legal system. Bigger Gini index of inequality. Less school enrolment and expected years of
schooling (Botwana exception). Delays development of financial institutions. Armed conflicts and civil wars.
9
Japan
United States
India
Switzerland
Italy
Korea, Rep.
United Kingdom
Spain
Turkey
France
Mexico
Pakistan
Austria
Burkina Faso
HungaryIsraelGreece
Niger
Jordan
Portugal
Argentina
Mali
Hong Kong, China
Sweden
Brazil
Malta
Finland
Taiwan, China
Egypt, Arab Rep.
Paraguay
Norway
Colombia
Uruguay
Australia
Canada
Belgium
Indonesia
Madagascar
Congo, Rep.
Tunisia
Panama
Denmark
Thailand
Congo, Dem. Rep.
Philippines
Guatemala
Chile
Nigeria
Ecuador
Bolivia
Morocco
Sudan
Peru
Netherlands
Ireland
Senegal
El Salvador
Togo
Ghana
New Zealand
Costa Rica
Sri LankaMalawi
Algeria
Nicaragua
Honduras
Venezuela, RB
Cote d'Ivoire
Malaysia
Suriname
Gabon
Saudi ArabiaGuyana
Trinidad and TobagoZambia
Libya
Kuwait
Liberia
Singapore
02
46
Ant
i-Cor
rupt
ion
Inde
x 19
84-2
005
0 20 40 60 80Natural Resources exports in percent of GDP, 1970
Figure: Corruption and Natural Resource AbundanceData source: ICRG(PRS Group) & World Development Indicators, 2006
CORRUPTION AND RESOURCE ABUNDANCE
10
JapanUnited States
India
Switzerland
ItalyKorea, Rep.
United Kingdom
Spain
Turkey
France
Mexico
Pakistan
Austria
Burkina Faso
Hungary
Israel
Greece
Niger
Jordan
Portugal
Argentina
Mali
Hong Kong, China
Sweden
BrazilMalta
Finland
Taiwan, China
Egypt, Arab Rep.
Paraguay
Norway
Colombia
Uruguay
AustraliaCanadaBelgium
IndonesiaMadagascar
Congo, Rep.
Tunisia
Panama
Denmark
Thailand
Congo, Dem. Rep.
Philippines
Guatemala
Chile
Nigeria
Ecuador
Bolivia
Morocco
Sudan
Peru
Netherlands
Ireland
Senegal
El Salvador
Togo
Ghana
New Zealand
Costa RicaSri Lanka
Malawi
Algeria
Nicaragua
Honduras
Venezuela, RB
Cote d'Ivoire
Malaysia
Suriname
Gabon
Saudi Arabia
Guyana
Trinidad and Tobago
Zambia
Libya
Kuwait
Liberia
Singapore
01
23
4B
ure
aucr
atic
Qua
lity
Inde
x 1
97
0-2
00
5
0 20 40 60 80Natural Resources exports in percent of GDP, 1970
Figure: Bureaucracy and Natural Resource AbundanceData source: ICRG(PRS Group) & World Development Indicators, 2006
BUREAUCRATIC QUALITY AND RESOURCE ABUNDANCE
11
Japan
United States
India
Switzerland
Italy
Korea, Rep.
United Kingdom
Spain
Turkey
France
Mexico
Pakistan
Austria
Burkina Faso
Hungary
IsraelGreece
Niger
Jordan
Portugal
Argentina
Mali
Hong Kong, China
Sweden
Brazil
Malta
Finland
Taiwan, China
Egypt, Arab Rep.
Paraguay
Norway
Colombia
Uruguay
AustraliaCanada
Belgium
Indonesia
Madagascar
Congo, Rep.
Tunisia
Panama
Denmark
Thailand
Congo, Dem. Rep.
Philippines
Guatemala
Chile
Nigeria
Ecuador
Bolivia
Morocco
SudanPeru
Netherlands
Ireland
Senegal
El Salvador
Togo
Ghana
New Zealand
Costa Rica
Sri Lanka
Malawi
Algeria
Nicaragua
Honduras
Venezuela, RB
Cote d'Ivoire
Malaysia
Suriname
Gabon
Saudi Arabia
Guyana
Trinidad and Tobago
Zambia
Libya
Kuwait
Liberia
Singapore
12
34
56
Rule
of L
aw
Ind
ex
19
84
-20
05
0 20 40 60 80Natural Resources exports in percent of GDP, 1970
Figure: Rule of Law and Natural Resource AbundanceData source: ICRG(PRS Group) & World Development Indicators, 2006
RULE OF LAW AND RESOURCE ABUNDANCE
12
Japan
United States
India
Switzerland
Italy
Korea, Rep.
United KingdomSpain
Turkey
France
MexicoPakistan
Austria
Burkina Faso
Hungary
Israel
Greece
Niger
Jordan
Portugal
Argentina
Mali
Hong Kong, China
Sweden
Brazil
Malta
FinlandTaiwan, China
Egypt, Arab Rep.
Paraguay
Norway
Colombia
Uruguay
Australia
CanadaBelgium
Indonesia
Madagascar
Congo, Rep.
Tunisia
Panama
Denmark
Thailand
Congo, Dem. Rep.
Philippines
Guatemala
Chile
NigeriaEcuador
Bolivia
Morocco
Sudan
Peru
Netherlands
Ireland
Senegal
El Salvador
Togo
GhanaNew Zealand
Costa Rica
Sri LankaMalawi
Algeria
NicaraguaHonduras
Venezuela, RB
Cote d'Ivoire
Malaysia
Suriname
Gabon
Saudi Arabia
Guyana
Trinidad and Tobago
Zambia
Libya Kuwait
Liberia
Singapore
56
78
91
0G
ove
rmen
t st
abili
ty In
de
x 1
98
4-2
00
5
0 20 40 60 80Natural Resources exports in percent of GDP, 1970
Figure: Goverment stability and Natural Resource AbundanceData source: ICRG(PRS Group) & World Development Indicators, 2006
GOVERNMENT STABILITY AND RESOURCE ABUNDANCE
13
Japan
United States
India
Switzerland
ItalyKorea, Rep.
United KingdomSpain
Turkey
France
MexicoPakistan
Austria
Burkina Faso
Hungary
Israel
Greece
Niger
Jordan
Portugal
ArgentinaMali
Burundi
Hong Kong, China
Sweden
Brazil
Benin
Chad
Malta
Finland
Cambodia
Egypt, Arab Rep.
Paraguay
Norway
Colombia
Uruguay
Australia
Central African Republic
Canada
Belgium
Indonesia
MadagascarCongo, Rep.
Tunisia
Panama
Denmark
Thailand
Congo, Dem. Rep.
Philippines
Guatemala
Chile
Nigeria
Ecuador
Bolivia
Morocco
Sao Tome and Principe
Sudan
Peru
Netherlands
Ireland
Senegal
El Salvador
Togo
Ghana
Cameroon
New Zealand
Costa RicaSri Lanka
Malawi
Algeria
Barbados
NicaraguaHondurasVenezuela, RB
Solomon Islands
Cote d'IvoireFiji
Malaysia
MauritaniaSuriname
Gabon
Saudi Arabia
Guyana
Trinidad and Tobago
Zambia
Libya
Kuwait
Liberia
Singapore
05
01
001
50D
ome
stic
Cre
dit
to P
riva
te S
ect
or
% G
DP
19
70-2
004
0 20 40 60 80Natural Resources exports in % of GDP, 1970
Figure: Financial Development and Natural Resource AbundanceData source: World Development Indicators, 2006
DOMESTIC CREDIT ANDRESOURCE ABUNDANCE
14
Japan
United States
India
SwitzerlandItaly
Korea, Rep.
United Kingdom
Spain
Turkey
FranceMexico
Pakistan
Austria
Burkina Faso
Hungary
Israel
Greece
Niger
Jordan
Portugal
Argentina
Mali
Hong Kong, China
SwedenBrazil
Malta
Finland
Taiwan, China
Egypt, Arab Rep.
Paraguay
Norway
Colombia
Uruguay
Australia
Canada
Belgium
Indonesia
Madagascar
Congo, Rep.Tunisia
Panama
Denmark
Thailand
Congo, Dem. Rep.
Philippines
Guatemala
Chile
Nigeria
Ecuador
Bolivia
Morocco
Sudan
Peru
Netherlands
Ireland
Senegal
El Salvador
Togo
Ghana
New Zealand
Costa Rica
Sri Lanka
Malawi
Algeria
Nicaragua
Honduras
Venezuela, RB
Cote d'Ivoire
Malaysia
SurinameGabon
Saudi Arabia
Guyana
Trinidad and Tobago
Zambia
Libya Kuwait
Liberia
Singapore
68
10
12
Ext
ern
al C
on
flict
198
4-2
00
5
0 20 40 60 80Natural Resources exports in percent of GDP, 1970
Figure: External Conflict and Natural Resource AbundanceData source: ICRG(PRS Group) & World Development Indicators, 2006
Japan
United States
India
Switzerland
Italy
Korea, Rep.
United Kingdom
Spain
Turkey
France
Pakistan
Mexico
Afghanistan
Austria
Burkina Faso
Hungary
Israel
Greece
Niger
Jordan
Portugal
Mali
Argentina
Burundi
Hong Kong, China
Benin
Brazil
Sweden
Chad
MaltaFinland
Taiwan, China
Cambodia
Egypt, Arab Rep.
Paraguay
Norway
Colombia
Uruguay
Australia
Central African Republic
Canada
Belgium
Congo, Dem. Rep.
Indonesia
Congo, Rep.
Madagascar
Tunisia
Denmark
Thailand
Panama
Philippines
Guatemala
Chile
Nigeria
Ecuador
Bolivia
Morocco
Sao Tome and Principe
Sudan
Peru
Netherlands
Ireland
Senegal
El Salvador
Togo
Ghana
Cameroon
New ZealandCosta Rica
Sri Lanka
Malawi
Algeria
Barbados
NicaraguaHonduras
Venezuela, RB
Solomon Islands
Cote d'Ivoire
Fiji
Malaysia
Mauritania
Suriname
Gabon
Saudi ArabiaGuyana
Trinidad and Tobago
Zambia
Libya
Kuwait
Liberia
Singapore
40
50
60
70
80
90
Life e
xp
ecta
ncy 1
97
0-2
00
4
0 1 2 3 4Logarithm of Natural Resources exports in percent of GDP, 1970
Figure: Life expectancy and Natural Resource AbundanceData source: World Development Indicators, 2006
EXTERNAL CONFLICT AND RESOURCEABUNDANCE
LIFE EXPECTANCYAND RESOURCEABUNDANCE
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FOUR EXPLANATIONS OF RESOURCE CURSE I. Old Dutch disease stories II. Volatility III. Bad policies IV. Rent seeking, corruption and conflict
16
I. OLD EXPLANATIONS OF RESOURCE CURSE Windfall gain in demand for resources from abroad
induces an appreciation of the real exchange rate. The non-resource export sectors go in decline. The sheltered sector gets a boost as labour and other
factors move from traded to sheltered sectors. Easy to extend to Heckser-Ohlin and factor use in
resource sector (Corden and Neary, EJ, 1982; Corden, OEP, 1984)
Or to nominal wage rigidity in Dornbusch-style models of the open economy (Eastwood and Venables, EJ, 1982; Buiter and Purvis, 1983)
17
Is there a Dutch Disease? ‘It seems ungrateful to talk of a disease’ (The
Economist). Dutch Disease? Decline of exposed sectors may just be the
efficient response to the resource boom. However, if there is learning by doing in the
non-resource export sectors, there may well be a loss in output and welfare (van Wijnbergen, EJ, 1984; Krugman, JDE, 1987). A lower growth rate may well result (Sachs and Warner, 1997).
18
Worsening of competitiveness P G(LN) = H F(1 LN) with H HT /HN is LM
locus, which slopes upwards in P-LN space Higher natural resource exports Q E boosts P
and induces more than proportionate income in national income Y
Boost to output and consumption of NT-sector Consumption of T-goods rises despite
contraction of T-sector (supplied through imports paid for by resource revenues)
19
Dynamic effects of a resource boom: AAAB On impact resource boom leads to real
appreciation (higher P), decline of exposed sector and boom of sheltered sector
As relative productivity of labour in T-sector gradually falls, the real exchange rate depreciates (falling P) so labour shifts back from sheltered to exposed sectors
In the long run there must be real depreciation
20
Relative price ofnon-traded goods
Fraction of labour in non-traded sector
LM
LMA
A
NTGME
NTGME
NTGME
A
B
Natural resource abundance reduces competitiveness
Higher resource exports shifts A to A, so induces appreciation of real exchange rate. With passing of time relative productivity of traded relative to that of non-traded sector declines if e. of s. between traded and non-traded goods is less than unity. This shifts equilibrium from A to A and eventually all the way to B. In the long run there is a real depreciation and allocation of labour returned to original level.
21
Extraction of natural resources requires labour and capital
Resource movement as well as spending effects of resource boom. Labour is drawn both out NT and T to resource sectors.
Within context of Heckscher-Ohlin the Rybczynski theorem implies output of K-intensive non-resource sector expands.
If T-sector is K-intensive, resource boom induces pro-industrialisation if spending effect is not too large.
22
II. VOLATILITY & RESOURCE CURSE ‘What commodity price lack in trend, they make up for
in variance’ (Deaton, JEcPersp, 1999). Resource rich economies are extremely vulnerable to
the high volatility of resource prices, especially as supply is fairly inelastic.
Particularly bad as many resource rich economies are not much diversified: specialised in resources and small sheltered sector. In fact, they specialise away from non-resource traded goods which causes even more volatility and interest rate rises! Traded sector shrinks until it vanishes (Hausmann & Rigobon, 2002).
Volatility also bad for growth, investment, income distribution, poverty and educational attainment (Ramey & Ramey, Aizenman & Marion, Flug et al)
23
24
Declining natural resource dependence in the global economy .2
.4.6
.81
Ratio o
f V
alu
es o
f P
rim
ary
Com
modity E
xport
sto
Tota
l E
xport
s
1970 1980 1990 2000 2010
Sub-Saharan Africa Latin America & Carib.Middle East & North Africa East Asia & PacificWestern Europe & North America South Asia
Source: World Bank Development Indicators, 2005, World Bank
25
III. RESOURCES ENCOURAGES UNSUSTAINABLE POLICIES Erosion of critical faculties of politicians. Netherlands in the seventies dressed up the welfare
state and governments since 1989 have been trying to have a sustainable welfare state.
Induces excessive borrowing (Manzano and Rigobon, 2002) & invest in ‘prestige’ projects.
Loose sight of growth-promoting policies and value-for-money management.
State-led industrialisation through import substitution and heavy subsidies for manufacturing.
26
IV. RESOURCES RENT SEEKING, CORRUPTION & CONFLICT Allocation of talent: countries with many rent seekers and
lawyers grow more slowly than countries with lots of engineers (Murphy et al, JPE, 1989; AER, 1993)
Voracity effect: drag on economic growth (Tornell and Lane, 1999). Applies theory of common pool.
Corruption, political instability, bureaucratic inefficiency, assassinations and conflict also hamper economic growth (Mauro, 1995; Leite and Weidmann, 1999). Bad effects of resource growth mainly operates via worsening of institutions, rule of law, etc.
Increases civil strife and wars, especially in sub-Saharan Africa thru’ weakening of state or finance of rebels (Collier and Hoeffler, 2004; Ross, 2004). War lord competition (Skaperdas, 2004). Distinguish between grievance and greed (Ollson and Fors, 2004).
Especially bad for point-based rather than diffuse resources.
27
Key: A resource bonanza shifts equilibrium from A to A if there are strong institutions, which means higher profits and more entrepreneurs. In case of weak institutions the equilibrium shifts from A to A, so profits decline and number of rent seekers increases.
RENT GRABBING VERSUS PRODUCERFRIENDLY INSTITUTIONS (Mehlum, Moene and Torvik, EJ, 2005)
28
CROSS-COUNTRY EVIDENCE FOR RESOURCE CURSE Sachs and Warner (1997) Mehlum, Moene and Torvik (2005) Boschini et al (2003) Arezki and van der Ploeg (2007)
29
EFFECTS OF RESOURCE ABUNDANCE ANDINSTITUTIONAL QUALITY ON ECONOMIC GROWTH
Annual growth in real GDP per capita
Sachs and Warner (1997a)
Based on data inSachs and Warner(1997b)
Mehlum, Moene andTorvik (2005a)
Initial income -1.76 (8.56) -1.28 (6.65) -1.26 (6.70)
Openness 1.33 (3.35) 1.45 (3.36) 1.66 (3.87)
Resource abundance
-10.57 (7.01)-6.69 (5.43)
-14.34 (4.21)
Rule of law 0.36 (3.54) - -
Institutional quality - 0.6 (0.64) -1.3 (1.13)
Investments 1.02 (3.45) 0.15 (6.73) 0.16 (7.15)
Interaction term - - 15.40 (2.40)
Number of countries
7187
87
Adjusted R2 0.720.69
0.71
30
GDP growth (1) (2) (3) (4)
Initial log GDP 0.048 -0.051 -0.560 -0.407
(1.09) (0.44) (4.75)** (3.03)**
Openness 2.410 1.985 1.511 1.403
(5.56)** (3.35)** (3.25)** (3.09)**
Natural Resources over GDP 0.009 0.009 -0.023 -0.092
(0.69) (0.66) (2.04)* (2.78)**
Institution 0.098 0.150 0.031
(0.99) (1.95) (0.34)
GFCF over GDP 0.188 0.192
(6.67)** (7.01)**
Interaction 0.007
(2.21)*
Observations 74 69 69 69
R-squared 0.64 0.65 0.80 0.81
Source:World Bank DevelopmentIndicators 2006International Country Risk Guide, PRS Group plc.Sachs and Warner (1997)
CROSS-COUNTRY EVIDENCE
Only countries with poor institutionssuffer from resource curse
Implies = 0.32, = 0.0046 and half-time 15 years
31
Marginal effects of different types of natural resources on growth for
different levels of institutional quality
Primary exports share
of GDP
Ores and metals
exports as share of GDP
Mineral production as share of GNP
Prod of gold, silver and
diamonds as share of GDP
Worst institutions
0.548 0.946 1.127 1.145
Average institutions
0.378 0.425 0.304 0.279
Average + one s.d. institutions
0.288 1.152 1.062 1.183
Best institutions
0.228 1.629 1.560 1.776
Source: Boschini, et. al. (2003)
32
VOLATILITY, FINANCIAL DEVELOPMENT AND THE NATURAL RESOURCE CURSE
Based on work with Steven Poelhekke
33
Motivation
Output volatility seems to matter for growth. (e.g., Ramey & Ramey, AER, 1995)
What explains volatility? Or its absence?
Why do so many resource rich countries stay poor?
Is the resource curse cast in stone?
Can volatility explain the curse?
34
The Facts1. Volatile countries have lower growth (Figure 1)
Equatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial GuineaEquatorial Guinea
IraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraqIraq
LiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberiaLiberia
United Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab EmiratesUnited Arab Emirates
-50
510
Ave
rage
Yea
rly
GD
P/C
apita
Gro
wth
(197
0-20
03, %
)
0 10 20 30Standard Deviation of Yearly GDP/Capita Growth
(1970-2003, %)
Fitted Values (slope = -.247 (.049); Adj. R2=.14)
35
The Facts: s.d. real GDP growth (Table 1)2. Developing countries are more volatile
Sub-Saharan Africa: 6.52Western Europe: 2.33 Middle East/North Africa: 8.12! North America: 1.90
2. Countries with poorly developed financial systems are more volatile1th Q (<16.2%): 6.40 4th Q (>52.9%): 4.40
3. Remote (distance from waterway) countries are more volatile1th Q (<49km): 6.52 4th Q (>359km): 8.12
36
The Facts (Figure 2)5. Resource dependent countries are more volatile
Bahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, TheBahamas, The
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010
20
30
Sta
ndard
Devi
atio
n o
f Y
earl
yG
DP
/Capita
Gro
wth
(1970-2
003, %
)
0 20 40 60 80 100Average Resource Share of GDP
(1970-2003, %)
Fitted Values (slope =.149 (.016); Adj. R2=.44)
37
The literature
Ramey & Ramey, AER, 1995: volatility affects growth Koren, Tenreyro, QJE, 2007: volatility falls with
development as countries diversify away from highly volatile sectors and improve macro-policy.
Blattman, Hwang, Williamson, JDE, 2007: resource exporters have volatile terms of trade, less
FDI, less growth (1870-1939) Sachs & Warner, 1997: windfall resource revenue ->
RER appreciation -> decline in non-resource exports -> less learning by doing and lower
TFP growth
38
Key questions
1. Does volatility affect growth negatively?
2. Does resource dependence explain output volatility?
3. A new explanation for the resource curse?
4. Do financial development and openness mitigate any adverse effects?
ML to simultaneously explain volatility of unanticipated output shocks and its effect on growth.
39
How can volatility hamper growth? Aghion at. al., CEPR 2006: RER volatility with credit
constraints stunts innovation
nominal exchange rate volatility: liquidity shock Here: shock = exogenous World commodity price
(Cashin et. al., IMF, 2002)cash = profits + resource income
- nominal wage stickiness
40
Results: If F(z) is concave so that E[F(·)] F(E[·]),
then more volatility in natural resource revenues or in nominal exchange rate lowers innovation and growth, unless financial development is very large.
High and stable resource revenues and also a stable nominal exchange rate ease constraints and boost growth.
41
If F(z) is concave so that E[F(·)] F(E[·]), more volatility lowers innovation and growth unless financial development is very large. Figure 3:
42
Other links between output volatility and growth Higher volatility means more uncertainty-induced errors and thus
less irreversible investment and lower growth (Bernanke, QJE, 1983; Pindyck, 1991; Aizenman and Marion, RIE, 1991)
Especially if it is costly to switch factors of production(Bertola, JME, 1994; Dixit and Rob, JET, 1994)
Or: higher volatility leads to more precautionary saving and thus more investment and growth (Mirman, Etrica, 1971)
Higher variance commands investments with higher return and thus higher growth (Black, 1987)
Net effect of volatility on growth can in theory be negative or positive, so needs to be settled empirically
43
Data
Heston, Summers, Aten, Penn World Tables 6.2 Human capital: Barro & Lee (average schooling
years in population age 25+) Resources: World Development Indicators (export
revenue as % GDP) Openness: Sachs & Warner dummy (Wacziarg,
Welch, 2003) Financial development: WDI (domestic credit to
private sector) Distance to coast/river: Center for International
Development (km)
44
Evidence: volatility and growth (Table 2) Dependent Variable yearly GDP growth per capita 1970-2003
(constant 2000 international dollars, PWT 6.2) Mean equation (1) (4) (5: Rents)
Average investment share of GDP 1970-2003 0.108*** (0.012) Investment share of GDP 1970 0.005 (0.013) 0.023 (0.014) Average population growth rate 1970-2003 -0.472*** (0.118) -0.654*** (0.204) -0.730*** (0.220) log per capita GDP 1970 -0.012*** (0.001) -0.016*** (0.003) -0.013*** (0.002) Human capital 1970 0.001* (0.000) 0.001** (0.001) -0.000 (0.001) Volatility (σi) -0.110** (0.049) -0.324** (0.135) -0.410*** (0.138) Point-source resources 1970 -0.054 (0.038) Point-source rent share 1970 -0.198** (0.087) Diffuse resources 1970 0.012 (0.023) 0.052*** (0.017) Financial development 1970 0.001 (0.005) -0.004 (0.006) Sachs Warner updated openness dummy 70 0.007 (0.004) 0.006** (0.003) Point based resources * openness 70 0.040 (0.066) Point-source rent share * openness 70 0.212*** (0.065) Point-source resources * Fin. Dev. 70 0.327* (0.181) Point-source rent share * Fin. Dev. 70 0.714** (0.335) Constant 0.110*** (0.011) 0.167*** (0.020) 0.143*** (0.018) 1st Lag Error (ε) 0.252*** (0.018) 0.229*** (0.018) 2nd Lag Error (ε) -0.006 (0.020) 0.003 (0.020)
45
Evidence: underlying determinants of volatilityDependent Variable yearly GDP growth per capita 1970-2003
Mean equation (6a) (7a: Rents) Investment share of GDP 1970 -0.005 (0.015) 0.022 (0.015)
Average population growth rate 1970-2003 -0.740*** (0.155) -0.897*** (0.158) log per capita GDP 1970 -0.021*** (0.002) -0.019*** (0.003)
Human capital 1970 0.003*** (0.001) 0.002* (0.001) Volatility (σi) -1.572*** (0.372) -1.627*** (0.431)
Point-source resources 1970 0.088*** (0.024) Point-source rent share 1970 -0.089 (0.109) Financial development 1970 -0.025*** (0.008) -0.035*** (0.009)
Sachs Warner updated openness dummy 70 -0.009 (0.007) -0.013* (0.008) Point-source rent share * Fin. Dev. 70 0.788** (0.308) Point-source rent share * openness 70 0.233*** (0.083)
Constant 0.265*** (0.031) 0.259*** (0.033) 1st Lag Error (ε) 0.227*** (0.017) 0.222*** (0.018)
Variance equation Point based resources 1970 1.551*** (0.205) Point based rent share 1970 2.452*** (0.624)
Diffuse resources 1970 0.862** (0.359) 0.215 (0.354) Financial development 1970 -1.333*** (0.089) -1.424*** (0.092)
Sachs Warner updated openness dummy 70 -0.693*** (0.048) -0.720*** (0.048) Distance to nearest navigable river or coast 0.001*** (0.000) 0.001*** (0.000)
Constant -6.073*** (0.064) -5.953*** (0.065) Observations 2084 1980
Log likelihood 3726.2 3571.2
46
Evidence: volatility and growth (Table 2..)
Dependent Variable yearly GDP growth per capita 1970-2003 (constant 2000 international dollars, PWT 6.2)
Mean equation (1) (4) (5: Rents) Average investment share of GDP 1970-2003 0.108*** (0.012) Investment share of GDP 1970 0.005 (0.013) 0.023 (0.014) Average population growth rate 1970-2003 -0.472*** (0.118) -0.654*** (0.204) -0.730*** (0.220) log per capita GDP 1970 -0.012*** (0.001) -0.016*** (0.003) -0.013*** (0.002) Human capital 1970 0.001* (0.000) 0.001** (0.001) -0.000 (0.001) Volatility (σi) -0.110** (0.049) -0.324** (0.135) -0.410*** (0.138) (other controls included)
Variance equation Sub-Saharan Africa 2.588*** (0.154) 2.653*** (0.160) Middle-East & North Africa 1.734*** (0.160) 1.686*** (0.166) Latin America & Caribbean 1.604*** (0.153) 1.571*** (0.158) Eastern Europe & Centra Asia 1.433*** (0.274) 1.357*** (0.272) East Asia & Pacific 1.027*** (0.159) 0.868*** (0.162) South Asia 0.459** (0.194) 0.385* (0.200) Western Europe 0.211 (0.154) 0.274* (0.158) North America Reference region (least volatile) Constant -3.823*** (0.118) -7.804*** (0.149) -7.753*** (0.153) Country dummies in variance eq. yes no no Observations 3448 2186 2014 Log likelihood 5898.5 4012.4 3748.2
47
IV: Endogenous Investment
Unobserved country characteristics may determine the investment share and growth simultaneously (notably institutions)
Growing countries may attract more investment
IVs - ethnolinguistic fractionalization & polarization (Montalvo, Reynal-Querol, JDE & AER 2005) less trust, more corruption, less political rights
(Alesina et al, JEG, 2003)- % pop. in temperate climate
(Gallup et al, 1999; CID)
48
IV: Endogenous Investment (cont.)
Dependent Variable yearly GDP growth per capita 1970-2003
Initial investment share GDP 1970
yearly GDP growth per capita 1970-2003
Mean equation (6a) (6b: 1st stage)† (6c: 2nd stage) Investment share of GDP 1970 -0.005 (0.015) 0.065** (0.029)
Average population growth rate 1970-2003 -0.740*** (0.155) 0.697 (3.436) -0.581*** (0.148) log per capita GDP 1970 -0.021*** (0.002) -0.097*** (0.036) -0.015*** (0.003)
Human capital 1970 0.003*** (0.001) 0.025** (0.010) 0.002* (0.001) Volatility (σi) -1.572*** (0.372) -1.318*** (0.357)
Point-source resources 1970 0.088*** (0.024) 0.899** (0.406) 0.029 (0.034) Financial development 1970 -0.025*** (0.008) 0.174** (0.083) -0.030*** (0.008)
Sachs Warner updated openness dummy 70 -0.009 (0.007) 0.029 (0.036) -0.009 (0.006) Constant 0.265*** (0.031) 0.822*** (0.221) 0.202*** (0.039)
1st Lag Error (ε) 0.227*** (0.017) 0.223*** (0.017) Ethnic Polarization 0.008 (0.057)
% Population in Temperate Climate Zone 0.066 (0.062) Ethnic Fractionalization Index -0.133*** (0.044)
Variance equation Point based resources 1970 1.551*** (0.205) 1.614*** (0.206)
Diffuse resources 1970 0.862** (0.359) 0.900** (0.366) Financial development 1970 -1.333*** (0.089) -1.316*** (0.097)
Sachs Warner updated openness dummy 70 -0.693*** (0.048) -0.679*** (0.048) Distance to nearest navigable river or coast 0.001*** (0.000) 0.001*** (0.000)
Constant -6.073*** (0.064) -6.102*** (0.066) F-stat. on excl. instruments 3.63
Hansen overidentification J-statistic (p-value)
0.127
Observations 2084 2084 2084 R2 . 0.53 .
Log likelihood 3726.2 3728.7 † Robust and clustered standard errors by country.
49
Direct Resource Effect: Curse or blessing? Resource rents: -0.316** Resource rents × financial development: +1.106*** Resource rents × openness: +0.243***
Continuous interactions: size and significance of resource effect on growth depends on initial levels of financial development and openness.
50
Blessing for some-.
50
.51
1.5
Mar
gina
l Eff
ect o
f R
ent S
hare
on
Gro
wth
for A
vera
ge 1
970
Ope
nnes
s
0 .2 .4 .6 .8 1Finiancial Development in 1970
Marginal Effect of Rent Share on Growthfor Average 1970 Openness95% Confidence Interval
51
Direct and Indirect Effect Direct resource effect on growth + indirectly through
volatility (abstracting from interactions)-.
08-.
06-.
04-.
020
.02
Mar
gina
l eff
ect o
n gr
owth
of
poin
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urce
dep
ende
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.01
.02
OE
CD
Asi
an T
.
.04
.05
Mal
awi
RR
. Afr
ica
LL
. Afr
ica
.08
.09
Zam
bia
Volatility of unanticipated output growth, estimated 1970-2003
52
Robustness: Revenue volatility & Policy
Dependent Variable yearly GDP growth per capita 1970-2003 (base line mean equation with point-source
resources, fin. dev., openness) (9b) (9c) (9d)
Variance equation Initial point-source resources 1970 -0.803*** (0.283) -0.586* (0.324) -0.620** (0.299)
Initial diffuse resources 1970 -0.314 (0.555) -1.341** (0.583) 0.007 (0.555) Initial financial development 1970 -0.905*** (0.107) -0.888*** (0.108) -0.800*** (0.114)
Sachs Warner updated openness dummy 1970 -0.532*** (0.057) -0.475*** (0.066) -0.540*** (0.057) Distance to nearest navigable river or coast 0.001*** (0.000) 0.001*** (0.000) 0.000*** (0.000) Point-source export share volatility 70-03 9.361*** (0.464) 15.410*** (1.635)
Diffuse export share volatility 70-03 4.703* (2.429) 2.786 (2.430) Government share volatility 70-03 10.632*** (1.099) 10.365*** (1.225) 9.814*** (1.082)
Agricultural R.M. resource share volatility 70-03 0.699 (2.117) Foods resource share volatility 70-03 12.691*** (3.453)
Ores & metals resource share volatility 70-03 6.517*** (2.255) Fuels resource share volatility 70-03 9.369*** (0.478)
Financial development * point based volatility -33.275*** (8.893) Constant -6.734*** (0.082) -6.815*** (0.086) -6.698*** (0.081)
Observations 2084 2084 2084 Log likelihood 3806.0 3807.5 3810.4
53
Robustness: Economic restrictions IMF’s Annual Report on Exchange Arrangement and Restrictions
yearly GDP growth per capita 1970-2003
Mean equation (11a) Variance equation Investment share of GDP 1970 0.016 (0.019) Initial point-source resources 70 5.680*** (0.343) Average population growth rate ‘70-‘03 -0.770*** (0.202) Initial diffuse resources 70 1.949*** (0.498) log per capita GDP 1970 -0.017*** (0.003) Initial financial development 1970 -1.726*** (0.140) Human capital 1970 0.003*** (0.001) Distance to nearest navigable river or
coast 0.001*** (0.000)
Volatility (σi) -0.557*** (0.188) Ethnic Polarization Initial point-source resources 70 0.085*** (0.032) Multiple Exchange Practices (yes=1) -0.717*** (0.061) Initial diffuse resources 70 -0.009 (0.030) Current Account Restrictions (yes=1) 0.446*** (0.071) Financial development 1970 -0.008 (0.006) Capital Account restrictions (yes=1) -0.442*** (0.126) Current Account Restrictions (yes=1) 0.003 (0.003) Surrender of Export receipts (yes=1) 0.345*** (0.112)
Capital Account restrictions (yes=1) -0.003 (0.004) Cur. Acc. Restrictions * Point
Resources 70 4.485*** (0.945)
Cap. Acc. Restrictions * Point Resources 70
-1.988*** (0.468)
Constant 0.178*** (0.028) Constant -6.573*** (0.112) 1st Lag Error (ε) 0.235*** (0.019) 2nd Lag Error (ε) -0.001 (0.019) Observations 2015 Log likelihood 3595.0
54
Robustness: Ethnic tensions Polarization -> civil war, less investment, likely to
fight over resources yearly GDP growth
per capita 1970-2003
Mean equation (11a) Variance equation Investment share of GDP 1970 -0.005 (0.015) Initial point-source resources 70 -1.143*** (0.329) Average population growth rate 1970-2003 -0.569*** (0.215) Initial diffuse resources 70 0.967** (0.401) log per capita GDP 1970 -0.019*** (0.002) Initial financial development 70 -1.127*** (0.106) Human capital 1970 0.003*** (0.001) Sachs Warner updated
openness dummy 70 -0.507*** (0.058)
Volatility (σi) -0.771*** (0.250) Distance to nearest navigable river or coast
0.001*** (0.000)
Initial point-source resources 70 -0.043 (0.053) Financial development 1970 -0.041 (0.029) Sachs Warner updated openness dummy 70 -0.011* (0.006) Initial point-source resources * openness 70 -0.001 (0.005) Initial point-source resources * Fin. Dev. 70 0.153 (0.096) Ethnic Polarization 0.356 (0.231) Ethnic Polarization 0.178** (0.073) Point-source resources 70
* Ethnic Pololarization 13.914*** (0.779)
Constant 0.211*** (0.025) Constant -6.475*** (0.081) 1st Lag Error (ε) 0.230*** (0.017) Observations 2084 Log likelihood 3795.4
55
Robustness: Panel estimates Dependent Variable yearly GDP growth per capita 1970-2003 yearly GDP growth per capita 1990-2003 Mean equation (13a) (13b) Within (14a) (14b) Within
Investment share of GDP 0.034*** (0.013) 0.000 (0.018) 0.010 (0.017) -0.119*** (0.030) Population growth rate -0.808*** (0.121) -0.217 (0.192) -0.584*** (0.205) -0.218 (0.291) log per capita GDP -0.019*** (0.002) -0.036*** (0.004) -0.011*** (0.004) -0.103*** (0.011) Human capital 0.003*** (0.001) 0.000 (0.002) 0.002* (0.001) -0.003 (0.004) Volatility (σit) -1.440*** (0.482) 0.130 (0.388) -1.903** (0.839) 0.649 (0.500) Point-source resource share 0.157** (0.070) -0.019 (0.024) 0.224* (0.115) 0.188* (0.112) Diffuse resource share 0.062** (0.032) -0.031 (0.032) 0.091 (0.064) -0.037 (0.059) Financial development -0.011** (0.006) 0.001 (0.009) -0.019** (0.008) 0.010 (0.009) Sachs Warner updated openness dummy -0.009 (0.007) 0.008 (0.005) -0.022** (0.011) 0.008 (0.006) Point-source resources*Financial
development. -0.095 (0.091) 0.014 (0.045) -0.157 (0.134) -0.206 (0.177)
Constant 0.245*** (0.030) -0.004 (0.021) 0.183*** (0.044) -0.048** (0.022) 1st Lag Error (ε) 0.266*** (0.016) 0.170*** (0.016) 0.260*** (0.027) -0.203*** (0.031) 2nd Lag Error (ε) 0.027 (0.031) 0.001 (0.024)
Variance equation
Point-source resource share 4.692*** (0.315) -0.097 (0.176) 5.677*** (0.513) -10.771*** (1.748) Diffuse resource share 2.214*** (0.383) -1.632** (0.679) 3.396*** (0.672) -3.563** (1.683) Financial development -0.855*** (0.070) -1.495*** (0.043) -0.812*** (0.086) -1.302*** (0.059) Sachs Warner updated openness dummy -0.598*** (0.055) -0.237*** (0.056) -0.560*** (0.091) 0.126 (0.177) Distance to nearest navigable river or
coast 0.000*** (0.000) - -0.000 (0.000) -
Point-source resources*Financial development.
-4.138*** (0.953) 0.066 (0.823) -5.926*** (1.498) 21.274*** (2.902)
Constant -6.207*** (0.066) -5.748*** (0.025) -6.288*** (0.105) -6.080*** (0.033) Observations 2346 2476 1005 1075 Log likelihood 4342.4 4492.1 1990.5 2148.6
56
The bottom line for some resource rich countries: counterfactual exerciseResource-Rich Africa versus the Asian Tigers Asian Tigers
Resource-rich Africa
on yearly GDP/capita growth rate
GDP per capita growth 4.04% 0.25% Mean equation
Investment share of GDP 1970 0.065 ** 19.48% 30.42% -0.71% Average population growth rate 1970-2003 -0.581 *** 1.86% 2.75% 0.52%
Initial log per capita GDP 1970 -0.015 *** 7.747 7.129 -0.93% Initial human capital 1970 0.002 * 4.049 1.476 0.51%
Volatility (σi) -1.318 *** 3.45% 6.04% 3.41% Initial point-source resources 1970 0.029 4.32% 13.13% -0.26% Initial financial development 1970 -0.030 *** 26.89% 14.43% -0.37%
Variance equation
Initial point-source resources 1970 1.614 *** 4.32% 13.13% 0.57% Initial diffuse resources 1970 0.900 ** 11.08% 10.52% -0.02%
Initial financial development 1970 -1.316 *** 26.89% 14.43% 0.65% Sachs Warner updated openness dummy 70 -0.679 *** 0.746 0.000 1.85% Distance to nearest navigable river or coast 0.001 *** 90.902 552.571 1.70%
Countries 4 6
Note: Resource-rich African counties are: Algeria, Congo, Rep., Ghana, Malawi, Togo, Zambia. Asian Tigers are: South Korea, Malaysia, Philippines and Thailand.
57
Conclusions on volatility and finance Volatility of unanticipated output growth is
quintessential feature of the natural resource curse!
Positive direct effect of the level of natural resource exports on growth is swamped by negative indirect effect of volatility on growth performance.
Countries with high degrees of financial development can turn resource wealth into blessing and boon for growth.
Point-base impact stronger than diffuse resources.
58
Conclusions on volatility and finance .. High levels of investment rates, human capital
and openness boost growth performance. Countries with low initial GDP per capita catch up, but countries with high population growth rates grow more slowly.
Volatility increases with distance to waterways, volatility of government share, ethnic polarization, current account restrictions & surrender of export receipts.
Volatility decreases with openness, multiple exchange practices, capital account restrictions financial development.
59
GENUINE SAVING AND EXHAUSTIBLE RSOURCE RENTS
Source: World Bank (2006, Figure 3.4)
60
GENUINE SAVING RATESAND GDP GROWTH, 2003
Source: World Bank (2006, Figure 3.6).
61
RESOURCE ABUNDANCE AND CAPITAL ACCUMULATION (HARTWICK RULE)
Source: World Bank (2006, Figure 4.1).
62
HARTWICK RULE IN SMALL OPEN ECONOMY: THE KUWAIT MODEL No resources as factor input into production. Country should save less on its current
account than the marginal Hotelling rents if world resource prices are expected to increase and exploration technology is expected to advance.
It is then better to postpone extraction and borrow and profit from future resource scarcity and innovation.
63
HARTWICK RULE IN GLOBAL ECONOMY? Free trade in oil and goods & PCM & ZLM Capital and resource intensities fixed by world interest
rate & world price of natural resources. With zero technical progress and population growth &
identical technologies, maxi-min egalitarianism can be characterized (cf., Asheim):
Hartwick rule for global economy as a whole. Oil exporters run a deficit: Hotelling rule implies that
they expect capital gains and growing incomes. Oil importers run a surplus to accumulate national
wealth by consuming only a fraction of the MPK to compensate for decreasing return on capital.
64
WHY DO RESOURCE RICH COUNTRIES HAVE NEGATIVE GENUINE SAVING RATES? Anticipation of better times (higher oil prices
in the future, improvements in future extraction technology, etc.)?
Or rapacious rent seeking induced by voracity effect and dynamic common pool problem (building on Tornell and Lane)?
65
POLITICAL HOTELLING AND HARTWICK RULES In homogenous society s(t) = (Hartwick
rule) and genuine saving rate is zero. In fractionalized society with N>1, society
saves more than resource rents but still has negative genuine saving.
With more rival fractions, genuine saving rate is more negative and sustainable level of consumption is lower.
Resource price appreciation exceeds the interest rate and thus depletion is too fast.
66
POLICY PROPOSALS Temporary subsidy/tax relief for non-resource exposed
sectors if learning by doing (van Wijnbergen, QJE). Danger: policy addiction.
Staple trap view suggests gradual dual-track reform by creating a dynamic market sector in early-reform enclaves with post-reform benefits may work with sustained rents from natural resources. Rapid expansion of enclaves can pull the more backward sectors up as well. Big push: works if IRTS in NT-sector (Murphy et al, Sachs & Warner, 1997, JDE).
Put resource revenues into a fund to spread the benefits to future generations by investing in education, infrastructure, etc. Fund also helps to cope with volatile resource prices.
If rapicious rent seeking, better to keep oil in ground rather than deplete it and put the revenues in fund.
67
POLICY PROPOSALS ctd. Use revenues to reduce debt or invest in education & infrastructure with market return.
Privatisation of state-owned oil and mining industries & tendering exploitation rights to private companies. Not clear that this works.
Improve institutions, rule of law, etc. Easier said than done in presence of vested interests.
Exit caused by corruption does not necessarily reduce welfare, so more competition not necessarily good either (Bliss & Di Tella, JPE, 1997).
Distribute revenues as citizen dividends. Government must then make better case for its pet projects, since it has to tax its people: endowment and an information effect (Sandbu, 2004).
Get exploitation companies at the peace negotiation table to secure re-employment of ex-combatants.
68
Transparency is a must
Highest standards of public and corporate accountability, PSR/CSR and transparency: publish what you earn from exports and publish what you do with the revenues.
Exploitation companies should publish their payments to all governments and encourage mandatory disclosure mechanism.
Make debt relief etc. contingent on transparency, free press and anti-corruption efforts – role IMF, World Bank and UNDP. Establish global information office.
Western banks should be punished for allowing tainted money to be deposited.