The document discusses the "resource curse" theory that countries with large endowments of natural resources like oil tend to have lower long-term economic growth. It notes that recent literature argues this is due to the negative effect of natural resources on institutions. It then summarizes several formal models that show how resource wealth can shift efforts from productive activities to rent-seeking, and how weak institutions exacerbate this effect. The document also reviews the empirical evidence on the relationship between natural resources, economic growth, and institutional quality.

1. The “Oil Curse” and Institutions: A Brief Survey
by
Michael Alexeev

2. 2
NATURAL RESOURCE CURSE CLAIM:
LARGE ENDOWMENT OF OIL AND MINREALS
REDUCES LONG-TERM GROWTH RATES
MAIN TRANSMISSION MECHANISM STRESSED IN
RECENT LITERATURE:
DELETERIOUS EFFECT OF NATURAL RESOURCES ON
INSTITUTIONS, INCL. FORM OF GOVERNMENT
MAIN CULPRIT: “POINT-SOURCE” RESOURCES
SUCH AS OIL

3. 3
BASIC LOGIC OF THE NATURAL RESOURCE CURSE:
NATURAL RESOURCES GENERATE RENTS
MORE RENT  MORE EFFORTS TO OBTAIN THAT RENT
(I.E., RENT-SEEKING EFFORTS)  LESS EFFORT IS
DEVOTED TO NON-RENT-SEEKING ACTIVITIES
IF THE LATTER PRODUCE POSITIVE EXTERNALITIES,
ECONOMIC GROWTH DECLINES.

4. 4
AN EXAMPLE OF A FORMAL MODEL: MEHLUM ET AL. (EJ, 2006)
Mehlum, Halvor, Karl Moene, and Ragnar Torvik, “Institutions and the Resource Curse,” Economic Journal 116:508:1–20.
Mehlum et al.’s model sketch: There is a fixed number of entrepreneurs in the economy,
𝑁𝑁 = 𝑛𝑛𝑃𝑃 + 𝑛𝑛𝐺𝐺, 𝑛𝑛𝑃𝑃 = 𝛼𝛼𝛼𝛼, with each choosing between being a “producer” or a
“grabber.” Total rent = 𝑅𝑅. Grabber’s payoff = 𝜋𝜋𝐺𝐺 = 𝑠𝑠𝑠𝑠/𝑁𝑁; producer gets 𝜆𝜆𝜆𝜆𝜆𝜆/𝑁𝑁 of
rent, where 𝜆𝜆ϵ[0,1] is “institutional quality” (i.e., grabbers get ≥ rent than producers) and
𝜕𝜕𝜕𝜕
𝜕𝜕𝑛𝑛𝐺𝐺
< 0.
Two production technologies: “modern” (IRS with fixed costs, low MC, positive profit)
and “fringe” (no fixed costs, high MC, zero profit). Labor = 𝐿𝐿, 𝑤𝑤 = 1.
Producer’s production profit, 𝜋𝜋(𝑛𝑛𝑃𝑃), increases in 𝑛𝑛𝑃𝑃 (b/c total income and demand ↑).
Producer’s total profit is 𝜋𝜋𝑃𝑃 = 𝜋𝜋(𝑛𝑛𝑃𝑃) + 𝜆𝜆𝜆𝜆𝐺𝐺.
If 𝜆𝜆 is low and 𝑅𝑅 is high, there are grabbers in equilibrium where 𝜋𝜋𝑃𝑃 = 𝜋𝜋𝐺𝐺 implying that
𝜋𝜋𝑃𝑃(1 − 𝜆𝜆) = 𝜋𝜋(𝑛𝑛𝑃𝑃), and total income, 𝑌𝑌 =
𝑁𝑁𝑁𝑁( 𝑛𝑛𝑃𝑃)
1−𝜆𝜆
+ 𝐿𝐿 → 𝑅𝑅 ↑ implies that 𝑛𝑛𝐺𝐺 ↑ and 𝑛𝑛𝑃𝑃 ↓
→ 𝑌𝑌 ↓ , i.e., there is “resource curse.” It occurs because 𝑅𝑅 ↑ shifts some producers into
rent grabbing and reduces the positive externality generated by producers. Here the
conclusion is that only countries with weak institutions (low 𝜆𝜆) suffer from a resource
curse.

5. 5
ANOTHER STANDARD ARGUMENT FOR THE
DELETERIOUS EFFECT OF NATURAL RESOURCES ON
INSTITUTIONS:
NATURAL RESOURCE WEALTH MEANS THAT THE
GOVERNMENT DOES NOT NEED MUCH TAX REVENUE
AND HAS NO INTEREST IN MAINTAINING GOOD
PRODUCTIVE INSTITUTIONS.

6. 6
THE “ANTI-CURSE” ARGUMENT IS THAT NATURAL
RESOURCES BRING IN THE POSSIBILITY FOR THE
GOVERNMENT TO IMPROVE ITS FUNCTIONS WITHOUT
TAXING PEOPLE AND BUSINESSES TOO MUCH.
THIS IS PARTICULARLY IMPORTANT IN POOR
COUNTRIES THAT MAY NOT EVEN HAVE THE
ADMINISTRATIVE CAPACITY TO TAX  A COUNTRY,
PARTICULARLY A RELATIVELY POOR COUNTRY, CAN
IMPROVE ITS INSTITUTIONS WITHOUT HAMPERING THE
GROWTH OF THE PRIVATE SECTOR.

7. 7
OTHER STORIES:
DUTCH DISEASE
CIVIL CONFLICT
AUTOCRACY

8. 8
MAIN EARLY EMPIRICAL PAPERS ON THE OIL CURSE:
Sachs and Warner (1995, 2001) claims:
“… a statistically significant, inverse, and robust association between natural
resource intensity and growth over the past twenty years.”
“[e]mpirical support for the curse of natural resources is not bulletproof, but it is
quite strong”
Sala-i-Martin and Subramanian (2003)
“[s]ome natural resources – oil and minerals in particular – exert a negative and
non-linear impact on growth via their deleterious impact on institutional
quality.”

9. 9
Gylfason, T., and G. Zoega (2002a, b):
“[e]conomic growth is inversely related to natural resource dependence…”
M. Ross (2001):
“…oil and mineral wealth tends to make states less democratic”
Isham, et al. (2003)
Leite and Weidmann (1999)
and many others

10. 10
REGRESSIONS OF INSTITUTIONAL QUALITY (RULE OF LAW,
CORRUPTION, ETC.) ON NATURAL RESOURCE ENDOWMENT
𝑰𝑰𝑰𝑰𝒊𝒊,𝒕𝒕 = 𝝁𝝁𝟎𝟎 + � 𝝁𝝁𝒊𝒊
𝒊𝒊
𝑿𝑿𝒊𝒊 + 𝝑𝝑𝟏𝟏 𝒀𝒀𝒊𝒊,𝒕𝒕−𝟐𝟐𝟐𝟐 + 𝝑𝝑𝟐𝟐 𝑵𝑵𝒊𝒊 + 𝝎𝝎𝒊𝒊
WHERE
𝑰𝑰𝑰𝑰𝒊𝒊,𝒕𝒕 -- INSTITUTIONAL QUALITY;
𝑵𝑵𝒊𝒊 -- NATURAL RESOURCE ABUNDANCE OR A MEASURE OF RENTS;
𝒀𝒀𝒊𝒊,𝒕𝒕−𝟐𝟐𝟐𝟐 -- “INITIAL” GDP PER CAPITA;
𝑿𝑿𝒊𝒊 -- CONTROLS

11. 11
PROBLEMATIC ISSUES:
- “INITIAL GDP” AS A CONTROL VARIABLE
- MEASURES OF NATURAL RESOURCES (GDP SHARES
VS. PER CAPITA; EXPORTS/GDP; INCLUSION OF
RENTS )
- ENDOGENEITIES (BOTH DUE TO POTENTIAL
REVERSE CAUSALITY AND OMITTED VARIABLES)

12. 12
ALEXEEV AND CONRAD FIRST SHOW THAT PER CAPITA GDP
IS STRONGLY POSITIVELY CORRELATED WITH NATURAL
RESPURCE ENDOWMENT:
𝒀𝒀𝒊𝒊,𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐 = β𝟎𝟎
+ � 𝜷𝜷𝒊𝒊
𝒊𝒊
𝑿𝑿𝒊𝒊 + γ 𝑵𝑵𝒊𝒊 + ε𝒊𝒊

13. 13
Table 1. Effect of Oil Wealth on PC GDP (Dep. Var.: Log of PC PPP GDP in 2000; Large sample)
Variable 1 2 3 4 5 6
Hydrocarbon
deposits, per capita
.059***
(.016)
.051***
(.010)
Value of oil output,
per capita
.096***
(.023)
.086***
(.015)
Oil/GDP ratio
1.51**
(.693)
1.26***
(.313)
Absolute latitude
.037***
(.005)
.038***
(.005)
.038***
(.005)
Ethnolinguistic
fractionalization
-170
(.232)
-.455*
(.250)
-.436*
(.262)
European population
1.34***
(.202)
1.30***
(.202)
1.43***
(.208)
-.054
(.308)
.097
(.286)
.066
(.322)
Latin America
1.02***
(.155)
.926***
(.154)
1.06***
(.171)
.814***
(.134)
.662***
(.135)
.774***
(.151)
East Asia
1.70***
(.334)
1.67***
(.290)
1.77***
(.269)
.572***
(.195)
.594***
(.172)
.618***
(.213)
Rule of law
(Instrumented)
1.14***
(.150)
1.02***
(.150)
1.09***
(.165)
Observations 111 118 118 111 117 117
Adj. R-squared .739 .725 .708 .862 .869 .844
Notes: *** - significant at 1%; ** - at 2%; * - at 10%;
Instruments for Rule of law: absolute latitude, English language speakers; European language speakers

14. 14
Contrast the above results with the following statement
by Sachs and Warner (2001):
“casual observation suggests that there is virtually no
overlap in the set of countries that have large natural
resource endowments – and the set of countries that have
high levels of GDP.”

15. 15
Table 2. The Effect of Interaction between Institutions and Natural Resources on PC GDP
(large sample; dependent variable: Logarithm of per capita PPP GDP in 2000)
Variable 1 2 3 4 5
Hydrocarbon deposits,
per capita
.056***
(.014)
Value of oil output,
per capita
.101***
(.021)
Oil/GDP ratio
1.14*
(.678)
Mining/GDP ratio
1.64
(1.14)
Mining output,
per capita
.072**
(.028)
Rule of law
(fitted values)
1.14***
(.189)
1.08***
(.202)
1.15***
(.218)
1.13***
(.238)
1.19***
(.236)
(Rule of law)*
Natural resources
-.041***
(.012)
-.065***
(.017)
-.834
(.913)
-1.53
(2.20)
-.053***
(.019)
Observations 111 117 117 117 117
Adj. R-squared .783 .770 .754 .745 .756
Notes: *** - significant at 1% level; ** - significant at 2% level; * - significant at 10% level.

16. 16
THE EFFECT OF MINERAL WEALTH ON INSTITUTIONS
EFFECT OF “INITIAL GDP” AS A CONTROL VARIABLE:
OIL RAISES GDP  IN 1970 KUWAIT HAD MUCH GREATER
PER CAPITA GDP THAN FRANCE, BUT HAD CONSIDERABLY
WORSE INSTITUTIONS THAN FRANCE  CONTROLLING
FOR INITIAL GDP LEADS TO A NEGATIVE COEFFICIENT
FOR OIL

17. 17
COMPARISON OF FRANCE AND KUWAIT IN TERMS OF PER
CAPITA GDP AND INSTITUTIONAL QUALITY
GDP PER
CAPITA
1970
RULE
OF LAW
1998
CONTROL OF
CORRUPTION
1998
GOVERNMENT
EFFECTIVENESS
1998
FRANCE 12,115 1.44
(0.18)
1.75
(0.18)
1.64
(0.23)
KUWAIT 41,357 1.16
(0.24)
1.07
(0.18)
−0.01
(0.31)
Note: standard errors are in parentheses

18. 18
ALEXEEV AND CONRAD’S APPROACH:
FIRST, ESTIMATE 𝒀𝒀�:
𝒀𝒀𝒊𝒊,𝟏𝟏𝟏𝟏𝟏𝟏𝟏𝟏 = β𝟎𝟎
+ � 𝜷𝜷𝒊𝒊
𝒊𝒊
𝑿𝑿𝒊𝒊 + 𝒖𝒖𝒊𝒊 → 𝒀𝒀� = 𝒃𝒃𝟎𝟎 + � 𝒃𝒃𝒊𝒊
𝒊𝒊
𝑿𝑿𝒊𝒊
WHERE 𝑿𝑿𝒊𝒊 ARE ABSOLUTE LATITUDE, EUROPE, LATIN AMERICA, EAST
ASIA
𝒀𝒀� = 𝟔𝟔. 𝟖𝟖 + 𝟎𝟎. 𝟎𝟎𝟎𝟎 × 𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨𝑨 + 𝟏𝟏. 𝟏𝟏𝟏𝟏 × 𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬 + 𝟎𝟎. 𝟖𝟖𝟖𝟖 × 𝑳𝑳𝑳𝑳𝑳𝑳𝑳𝑳𝑳𝑳 + 𝟎𝟎. 𝟒𝟒𝟒𝟒 × 𝑬𝑬𝑬𝑬𝑬𝑬𝑬𝑬
Adj. 𝑅𝑅2
= 0.55; No. obs. = 118
NOTE THAT 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶(𝑁𝑁𝑖𝑖 , 𝑌𝑌𝑖𝑖 ) >> 𝐶𝐶𝐶𝐶𝐶𝐶𝐶𝐶(𝑁𝑁𝑖𝑖 , 𝑌𝑌�) ≈ 0

19. 19
THEN, CONTRAST
𝑰𝑰𝑰𝑰𝒊𝒊,𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐 = 𝝁𝝁𝟎𝟎 + � 𝝁𝝁𝒊𝒊
𝒊𝒊
𝑿𝑿𝒊𝒊 + 𝝑𝝑𝟏𝟏 𝒀𝒀𝒊𝒊,𝟏𝟏𝟏𝟏𝟏𝟏𝟏𝟏 + 𝝑𝝑𝟐𝟐 𝑵𝑵𝒊𝒊 + 𝝎𝝎𝒊𝒊
AND
𝑰𝑰𝑰𝑰𝒊𝒊,𝟐𝟐𝟐𝟐𝟐𝟐𝟐𝟐 = 𝝁𝝁𝟎𝟎 + � 𝝁𝝁𝒊𝒊
𝒊𝒊
𝑿𝑿𝒊𝒊 + 𝝑𝝑𝟏𝟏 𝒀𝒀� + 𝝑𝝑𝟐𝟐 𝑵𝑵𝒊𝒊 + 𝝎𝝎𝒊𝒊

20. 20
Table 3. The Effect of Oil Wealth on the Rule of Law (ethnic and linguistic controls only; large sample)
(Dependent variable: Rule of law index for year 2000)
Variable 1 2 3 4 5 6
Hydrocarbon
deposits,
per capita
-.042**
(.017)
-.005
(.017)
Value of oil
output, per capita
-.068**
(.026)
-.012
(.027)
Oil/GDP ratio
-1.33**
(.536)
.003
(.666)
GDP 1970, per
capita
.570***
(.090)
.552***
(.091)
.569***
(.103)
GDP 1970, per
capita, fitted
.508***
(.173)
.466***
(.169)
.473***
(.160)
Observations 112 112 118 118 118 118
Adj. R-squared .717 .623 .710 .617 .712 .616
Notes: robust standard errors are in parentheses; *** - significant at 1% level; ** - significant at 2%
level; * - significant at 10% level

21. 21
Table 4. The Effect of Oil and Mineral Wealth on Corruption (Dep. var.: Index of control of corruption, 2000)
Variable 1 2 3 4 5 6 7 8 9 10
Hydrocarbons
,
PC
-.014
(.015)
.014
(.013)
Value of oil
output, PC
-.060**
(.023)
-.008
(.019)
Oil/GDP ratio
-1.12**
(.442)
.111
(.363)
Mining/GDP
ratio
-.554
(1.25)
.814
(.829)
Mining
output,
per capita
-.022
(.027)
.019
(.025)
PC GDP 1970
.498**
*
(.100)
.578**
*
(.088)
.579**
*
(.093)
.517**
*
(.103)
.528**
*
(.099)
PC GDP
1970, fitted
.765**
*
(.167)
.800**
*
(.153)
.804**
*
(.154)
.814**
*
(.155)
.803**
*
(.157)
Observations 110 110 113 113 113 113 113 113 113 113
Adj. 𝑅𝑅2 .732 .756 .738 .740 .734 .740 .720 .743 .721 .742
Notes: *** - significant at 1% level; ** - significant at 2% level; * - significant at 10% level.

22. COMPARISON OF BELARUS, RUSSIA, AND UKRAINE IN TERMS
OF PER CAPITA GDP AND INSTITUTIONAL QUALITY
PPP GDP
per capita,
2012 US$
Rule of
law
2012
Control of
corruption
2012
Government
effectiveness
2012
BELARUS 15,327 −0.92
(0.13)
−0.52
(0.13)
−0.94
(0.22)
RUSSIA 23,589 −0.82
(0.12)
−1.01
(0.12)
−0.43
(0.19)
UKRAINE 7,298 −0.79
(0.12)
−1.03
(0.12)
−0.58
(0.19)

23. 23
A&C CONCLUSIONS:
GIVEN THE DATA AVAILABLE SO FAR, NATURAL
RESOURCES, INCLUDING OIL:
- DO NOT REDUCE LONG-TERM GROWTH RATES
- DO NOT MAKE INSTITUTIONAL QUALITY
SIGNIFICANTLY WORSE
HOWEVER, A&C DID NOT LOOK AT VOICE AND
ACCOUNTABILITY INDEX

24. 24
THE OIL CURSE AND THE ECONOMIES IN TRANSITION
MOST ECONOMIES IN TRANSITION EXPERIENCE A DRASTIC CHANGE IN
INSTITUTIONS AND THUS PRESENT AN OPPORTUNITY TO GET AROUND
THE PROBLEM OF INSTITUTIONAL PERSISTENCE
SIMILAR APPROACH AS DESCRIBED EARLIER BUT WITH A DUMMY
VARIABLE FOR ECONOMIES IN TRANSITION SHOWS THAT IT IS MOSTLY
NOT TRUE.

25. 25
Table 5. Institutional quality regressions (reduced form; OLS)
Dependent variables: Measures of institutional quality for 2005
Variable name
Corr.
control
Corr.
control
Rule of
law
Rule of
law
Voice &
account.
Voice &
account.
(1) (2) (3) (4) (5) (6)
Transition economy -1.11***
(.159)
-1.13***
(.168)
-.968***
(.166)
-.991***
(.176)
-.443**
(.145)
-.449***
(.150)
CIS -.301
(.232)
-.246
(.233)
-.341
(.228)
-.329
(.221)
-.584*
(.319)
-.619*
(.330)
Per capita oil output .013
(.021)
-
.016
(.020)
-.038**
(.017)
-
Transition*PC oil
output
-.035
(.038)
-
-.037
(.040)
-.020
(.046)
-
Resource
depletion/GNI
-
-.036
(.040)
-
-.051
(.042)
-
-.140***
(.040)
Transition*Resource
depletion/GNI
-
.002
(.068)
-
.005
(.067)
-
.032
(.082)
R-squared .604 .665 .573 .647 .579 .626
Observations 162 148 162 148 162 148

26. 26
AS THE ABOVE TABLE SHOWS, OIL ABUNDANCE IS ASSOCIATED WITH
WORSE VALUES OF VOICE AND ACCOUNTABILITY INDEX.
THIS RESULT IS CONSISTENT WITH EGOROV ET AL. (2009) WHO CONSIDER
AUTOCRT’S INCENTIVES WITH RESPECT TO FREE MEDIA.
INTUITION FOR EGOROV ET AL.’S MODEL: FREE MEDIA PROVIDE INFO
ABOUT BUREAUCRAT’S PERFORMANCE, BUT INCREASE THE PROBABILITY
OF AUTOCRAT’S DEMISE.
WHEN TAX REVENUES FROM NON-MINING IS IMPORTANT, THIS TRADEOFF
FAVORS RELATIVELY FREE MEDIA.
HOWEVER, WHEN THE AUTOCRAT COULD GET REVENUES FROM OIL,
PERFORMANCE OF THE REST OF THE ECONOMY IS LESS IMPORTANT AND
THE AUTOCRAT STIFLES THE MEDIA.
EMPIRICAL APPROACH: FIXED EFFETS REGRESSIONS
EMPIRICAL PROBLEMS WITH THE PAPER: “ABSOLUTE” NATURAL
RESOURCE MEASURE (I.E., NOT RELATED TO EITHER POPULATION OR
GDP); CONTROLS FOR PER CAPITA GDP; POTENTIAL ENDOGENEITIES.

27. 27
OIL AND DEMOCRACY
M. ROSS (2014): “The core finding that more oil wealth is associated with less
democracy has been replicated many times, using better data and more
sophisticated methods”
THIS STATEMENT IS CORRECT. HOWEVER, THERE HAVE BEEN SEVERAL
RECENT STUDIES THAT FOUND NO ASSOCIATION (OR POSITIVE ASSOCIATION)
BETWEEN OIL WEALTH AND DEMOCRACY (E.G., HABER AND MENALDO 2010).

28. 28
CITING WRIGHT ET AL. (2014), ROSS CLAIMS THAT THERE MIGHT HAVE BEEN
NO ASSOCIATION PRIOR TO MID-1970s, BUT THERE HAS BEEN A FAIRLY
STRONG RELATIONSHIP SINCE THEN.
HOWEVER, WRIGHT ET AL. SHOWED THAT WHILE HIGH OIL WEALTH EXTENDS
AUTOCRATIC REGIME’S LIFE, DECREASING OIL WEALTH PROMOTES A
TRASITION TO ANOTHER AUTOCRACY RATHER THAN TO DEMOCRACY.
ROSS ALSO EMPHASIZES THE DIFFERENCE BETWEEN SHORT-TERM EFFECTS OF
OIL WEALTH CHANGES AND LONG-TERM EFFECTS, BUT IT IS HARD TO SEE
WHAT LONG-TERM EFFECTS COULD BE FOUND “SINCE MID-1970s”.

29. 29
A NICE PAPER IN THIS LITERATURE IS BRUCKNER ET AL. (2012)
WHO SHOW THAT OIL PRICE SHOCKS (𝜃𝜃 × 𝑂𝑂𝑂𝑂𝑂𝑂 𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂𝑂, where 𝜃𝜃 =
𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 − 𝑖𝑖 𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖𝑖) IMPROVE DEMOCRACY SCORES OF OIL
EXPORTERS (IN A SENSE CONTRADICTING AREZKI AND BRUCKNER
2009) BUT WORSEN DEMOCRACY IN OIL IMPORTERS.
ALTHOUGH THE ECONOMETRICS IN THIS PAPER APPEARS TO BE
SOUND, THIS RESULT IS SUSPECT, BECAUSE ACCORDING TO THE
AUTHORS, DEMOCRACY SCORES REACT TO OIL SHOCKS ONLY
WITHIN A YEAR.
INTERESTINGLY, OIL PRICE SHOCKS HAVE A ROBUST POSITIVE
(NEGATIVE) EFFECT ON GDP OF EXPORTERS (IMPORTERS).

30. 30
USE OF SUB-NATIONAL DATA
ADVANTAGES VS. DISADVANTAGES OF SUB-NATIONAL DATA
RESEARCH HAS BEEN MAINLY ON THE US AND MAINLY ON CORRUPTION
PROBLEMS WITH MEASURING CORRUPTION (CONVICTIONS VS. SURVEY OF
REPORTERS VS. AP INDEX).

31. 31
PAPYRAKIS AND GERLACH (2007) FIND THAT NATURAL RESOURCES ARE
ASSOCIATED WITH GREATER CORRUPTION.
PROBLEMS: FEW OBSERVATIONS (49); NATURAL RESOURCES ARE DEFINED
TO INCLUDE AGRICULTURE, FORESTRY, FISHING, AND MINING AS A
SHARE OF GSP ON THE SCALE OF 1-10; RESULT HOLDS ONLY WITH NO
CONTROL VARIABLES. CONTROLLING FOR INCOME, STATISTICAL
SIGNIFICANCE DISAPPEARS.

32. 32
Table 6. Correlations among corruption measures (US states)
Convictions
per 1000
people
Legal
corruption
(reporters)
Illegal
corruption
(reporters)
AP
corruption
index
Convictions
per 1000
people
1.0
Legal
corruption
(reporters)
0.1919 1.0
Illegal
corruption
(reporters)
0.1032 0.4800 1.0
AP
corruption
index
0.1218 0.6967 0.6736 1.0

33. 33
ACCORDING TO MY OWN ESTIMATES FOR THE US,
MINING MEASURES (BOTH SHARE AND PER CAPITA)
ARE INDEED ASSOCIATED WITH GREATER CORRUPTION
IN THE US AS MEASURED BY CONVICTIONS, BUT NOT
AS MEASURED BY SURVEY OF REPORTERS.
MOREOVER, EVEN FOR CONVICTIONS, STATISTICAL
SIGNIFICANCE IS REDUCED WHEN WE ADD SOME
CONTROLS.
THE RESULTS FOR RUSSIA ARE AMBIGUOUS
PRESUMABLY BECAUSE CORRUPTION MEASURES FOR
RUSSIA’S REGIONS ARE ALL OVER THE PLACE

34. 34
Table 7. Natural resource abundance and corruption in the US states
Convictions
per 1000
people
Legal
corruption
(reporters)
Illegal
corruption
(reporters)
AP
corruption
index
Log PC
mining
.009*
(.005)
-.097
(.121)
.101
(.103)
-.009
(.017)
Log of
population
.0002
(.0029)
.208**
(.094)
.330***
(.109)
.036***
(.012)
Urban share
(%, 2000)
-.0004*
(.0002)
-.012
(.009)
.011
(.011)
.003**
(.001)
Racial
diversity
.0006
(.0169)
1.97**
(.794)
.309
(.784)
.041
(.086)
BA Degree
(%, 2000)
.0003
(.0007)
-.038
(.037)
-.050
(.033)
-.008***
(.003)
“Moralistic”
nature
-.016***
(.005)
-.380
(.328)
-.481*
(.292)
-.033
(.027)
R-sq .295 .331 .496 .570
Notes: Log per capita GSP doesn’t affect estimates and is typically insignificant; all regressions have a constant; very similar results
obtain for share of mining in GSP

35. 35
RUSSIAN CORRUPTION MEASURES
CARNEGIE CENTER (2004) – HIGHER VALUES REFLECT LESS
CORRUPTION
INDEM FOUNDATION (2002; “INTEGRAL ESTIMATE” AND
“VOLUME”) – HIGHER VALUES IMPLY MORE CORRUPTION
FOM SURVEY (2011) – HIGHER VALUES MEAN MORE CORRUPTION
BRIBE TAX (BEEPS; 2011) – HIGHER VALUES CORRESPOND TO
GREATER CORRUPTION
BRIBE FEQUENCY (BEEPS; 2011) – HIGHER VALUES CORRESPOND
TO BRIBES BEING MORE COMMON

36. 36
Table 8. Correlations among corruption measures (Russia’s regions)
Carnegie
index
(2004)
INDEM
“estimate”
(2002)
INDEM
“volume”
FOM
survey
(2011)
Bribe
tax
(BEEPS
2011)
Bribe
frequency
(BEEPS)
Carnegie
index (2004)
1.0
INDEM
“estimate”
(2002)
0.048 1.0
INDEM
“volume”
-0.362 0.296 1.0
FOM survey
(2011)
-.494 0.430 0.461 1.0
Bribe tax
(BEEPS;
2011)
-.044 -0.424 -0.376 -0.187 1.0
Bribe
frequency
(BEEPS)
-0.100 0.223 0.332 0.220 0.425 1.0

37. 37
Table 8. Natural resource abundance and corruption in Russia’s regions
Carnegie
index
(2004)
INDEM
“estimate”
(2002)
INDEM
“volume”
(2002)
FOM
survey
(2011)
Bribe tax
(BEEPS;
2011)
Bribe
frequency
(BEEPS)
Oil / GRP
(%; 2001) ×
Oil Price
.001
(.002)
-.000
(.001)
-.003**
(.001)
-.010**
(.005)
.003**
(.001)
-.001
(.001)
Log of
population
-.134
(.109)
.022
(.070)
.191**
(.078)
.934
(1.14)
.300
(.225)
.400***
(.100)
Urban share
(%)
.006
(.008)
-.001
(.005)
.001
(.010)
.072
(.084)
-.008
(.015)
.004
(.007)
Student /
population
2.38
(7.84)
3.75
(3.16)
4.17
(4.69)
62.60
(77.27)
-57.03***
(11.50)
-11.02
(.6.78)
Mean Jan
temperature
-0.043***
(.013)
.017*
(.037)
.006
(.010)
.770***
(.140)
-.021
(.030)
-.000
(.011)
Log of dist.
to Moscow
-.314***
(.085)
.033
(.052)
-.036
(.050)
2.64***
(.766)
.148
(.146)
.067
(.080)
R-sq .211 .175 .311 .358 .437 .396
No. Obs. 73 36 36 68 35 35
Notes: Log of per capita GRP is sometimes statistically significant but doesn’t qualitatively affect the estimates of oil abundance
coefficients

38. 38
Table 8. Natural resource abundance and corruption in Russia’s regions
Carnegie
index
(2004)
INDEM
“estimate”
(2002)
INDEM
“volume”
(2002)
FOM
survey
(2011)
Bribe tax
(BEEPS;
2011)
Bribe
frequency
(BEEPS)
Log of PC
Oil (2001) ×
Oil Price
.004
(.026)
.002
(.015)
-.033*
(.017)
-.281
(.208)
.054
(.040)
-.045**
(.018)
Log of
population
-.133
(.106)
-.024
(.070)
.214***
(.076)
1.10
(1.19)
.337
(.241)
.426***
(.098)
Urban share
(%)
.006
(.008)
.001
(.005)
.001
(.009)
.078
(.085)
-.005
(.017)
.001
(.007)
Student /
population
3.11
(7.65)
3.52
(2.72)
3.14
(4.17)
52.55
(81.13)
-48.09***
(12.78)
-12.1**
(5.40)
Mean Jan
temperature
-0.043***
(.013)
.017*
(.009)
.010
(.009)
.797***
(.145)
-.023
(.033)
.000
(.011)
Log of dist.
to Moscow
-.314***
(.085)
.034
(.051)
-.017
(.049)
2.77***
(.812)
.094
(.155)
.099
(.079)
R-sq .209 .175 .310 .347 .379 .453
No. Obs. 73 36 36 68 35 35
Notes: Log of per capita GRP is sometimes statistically significant but doesn’t qualitatively affect the estimates of oil abundance
coefficients

39. 39
CONCLUSIONS
- LARGE ENDOWMENTS OF OIL/MINERALS DO NOT LOWER LONG-TERM
ECONOMIC GROWTH, ALTHOUGH THEY MAY DISTORT THE
RELATIONSHIP BETWEEN GDP AND INSTITUTIONAL QUALITY
- BECAUSE OF THIS DISTORTION, THE NEGATIVE EFFECT OF LARGE
ENDOWMENTS OF “POINT-SOURCE” RESOURCES ON INSTITUTIONS
CLAIMED IN THE LITERATURE IS MOSTLY DUE TO THE USE OF INITIAL
GDP VALUES AS CONTROL VARIABLES
- THERE MIGHT BE A NEGATIVE EFFECT OF OIL ON GOVERNMENT
ACCOUNTABILITY, BUT THIS REQUIRES FURTHER RESEARCH
- EVIDENCE ON THE EFFECT OF OIL ON DEMOCRACY IS
CONTRADICTORY
- REGIONAL DATA FOR RUSSIA AND THE US PRESENT CONTRADICTORY
EVIDENCE ON THE EFFECT OF OIL ON CORRUPTION