The resource curse hypothesis relies on the resource-rich countries tendency to grow slower than resource-poor countries. Focusing on forest issues, this paper extends the resource curse hypothesis to environmental degradation: how do forest endowment and forest harvesting affect deforestation? Our empirical results show that countries with important forest cover and forestry sectors seem to deforest more than others, which supports the hypothesis of an environmental resource curse. Moreover, countries implied in important timber certification processes have lower deforestation levels.resource curse, tropical forest, deforestation

Olivier Damette

Philippe Delacote

English

Research Papers in Economics

L Laboratoire d’E Economie F Forestière  
 
The environmental resource curse hypothesis:
the forest case 
Olivier DAMETTE
Philippe DELACOTE
Septembre 2009
Document de travail
n° 2009-04
LEF – AgroParisTech/INRA – 14, rue Girardet – CS 4216 – F-54042 Nancy cedex
￿ 00 33 (0)3 83 39 68 66– ￿ ￿ ￿ ￿ 00 33 (0)3 83 37 06 45 – ￿ ￿ ￿ ￿ lef@nancy-engref.inra.fr
http://www.nancy.inra.fr/lef The environmental resource curse hypothesis:
the forest case
*
Olivier DAMETTE 
1,2
Philippe DELACOTE 
3,4
Septembre 2009
Document de travail du LEF n°2009-04
Résumé
L'hypothèse de malédiction environnemental des ressources: le cas des forêts
L'hypothèse de malédiction des ressources repose sur la tendance des pays riches en ressource à avoir une
croissance inférieure aux pays moins dotés. En se focalisant sur la thématique forestière, cet article étend
l'hypothèse de malédiction des ressources à la dégradation environnementale: quels sont les effets des dotations
et de l'exploitation forestières sur la déforestation?
Nos résultats empiriques montrent que les pays avec de larges couverts forestiers et des secteurs forestiers
importants on tendance à connaître plus de déforestation que les autres, ce qui supporte l'hypothèse d'un
malédiction environnementale des ressources. A l'inverse, les pays qui s'appuient davantage sur la certification
de leur forêt connaissent de moindre niveaux de déforestation.
Mots clés : malédiction des ressources, forêt tropicale, déforestation.
Abstract
The resource curse hypothesis relies on the resource-rich countries tendency to grow slower than resource-poor
countries. Focusing on forest issues, this paper extends the resource curse hypothesis to environmental
degradation: how do forest endowment and forest harvesting affect deforestation? 
Our empirical results show that countries with important forest cover and forestry sectors seem to deforest more
than others, which supports the hypothesis of an environmental resource curse. Moreover, countries implied in
important timber certification processes have lower deforestation levels.
Key words : resource curse, tropical forest, deforestation.
Classification JEL : C21, O13, Q33.
* Acknowledgement: this paper has been presented at the CEA annual conférence (Toronto, Canada, May 2009).
We thank the participants for useful comments. 
1 Université Paris 12
2 Beta, BETA-CNRS, Université de Nancy, Faculté de Droit Economie et Gestion, F-54000 Nancy, France
3 INRA, UMR 356 Economie Forestière, F-54000 Nancy, France
Corresponding author: philippe.delacote@eui.eu
4 AgroParisTech, Engref,  Laboratoire d'Economie Forestière, F-54000 
11 Introduction
A well documented paradox in the economic development literature is the tendency of
resource-rich countries to grow slower than countries with less natural resources. Researchers
(Leite et al., 2002; Mehlun et al., 2006a, 2006b; Papyrakis et al., 2004; Sachs and Warner,
1997, 1999) usually focus on growth to describe a resource curse. Bulte et al. (2005) ﬁnd ev-
idence of the resource curse for several human development indicators. However, important
resource endowments may also have an impact on the environment. Important dotations may
be related to poor institutions and policy making. Poorly developed institutions may lead in
turn to unsustainable environmental management. Among diﬀerent environmental concerns,
deforestation is interesting to analyze. Indeed forests constitute both an environmental indi-
cator and an exploitable natural resource. Thus we investigate for an environmental resource
curse for deforestation: do forest-rich countries tend to deforest more than others?
We test for an environmental resource curse, using two diﬀerent forest indicators: a
forest endowment indicator and a forest harvesting indicator. Controlling for corruption and
institutional development, we ﬁnd some evidence of an environmental resource curse for both
variables. Conversely, countries with large certiﬁed timber assessment tend to deforest less
than others.
Section 2 surveys the institutional explanation of the resource curse, and mentions the
potential for an environmental resource curse. Section 3 investigates empirically the existence
of a resource curse for deforestation, and section 4 concludes.
2 Institutions, the resource curse and deforestation
Among the potential transmission channels of the resource curse identiﬁed in the literature
(Papyrakis and Gerlagh, 2004; Sachs and Warner, 1999), institutional quality and rent-
seeking is potentially the most important and relevant cause.
Natural resources are usually considered as easily appropriable, so that there are large in-
centives for rent-seeking activities, such as bribes or lobbying. This ”voracity eﬀect”(Mehlun
et al., 2006) constitutes a diversion of labor and capital from more productive activities. As
an extreme case, natural resource appropriation may be a source of conﬂicts or political
2violence. Most papers conclude that institutional background is an important vector of the
resource curse: administrations with low levels of corruption reduce the incentive for rent-
seeking activities and thus decrease the importance of this transmission channel. Therefore,
countries with well-developed institutions could even turn a curse into a blessing (Mehlun et
al., 2006; Arezki and Van der Ploeg, 2007).
However poor institutions may be a consequence of resource wealth (Leite and Weidmann,
2002). Indeed natural resources represent for governments ”easy money” that may lead to
sloth in the development of institutional quality and economic policies. Then low quality
institutions lead to bad economic management, poor decision making, bad or low investment
decisions, unsustainable management of the resource and thus jeopardize long term growth.
Overall, large resource endowments may inﬂuence institutional quality (Hall and Jone, 1999),
which in turn reduces growth and threatens long-term development. Overall, corruption
and rent-seeking activities seem to be key transmission factors of the potentially negative
inﬂuence that natural resource dotations may have on growth and development.
Deforestation and the environmental resource curse hypothesis: Those two factors
also have a strong inﬂuence on environmental quality 1 and especially deforestation. Indeed,
corruption and rent-seeking activities are frequently cited factors of forest over-exploitation
in developing countries (Amacher, 2006; Delacote, 2008). More generally, poor institutional
quality is likely to induce poor policy making, which generates unsustainable forest man-
agement. Overall, many empirical analysis ﬁnd that better institutions reduce deforestation
(Arcand et al., 2008; Culas, 2006; Nguyen Van and Azomahou, 2006). It is therefore crucial
to control for institutional quality when testing for an environmental resource curse.
We test two kinds of environmental resource curse. First, we consider forest dotations.
Deforestation is perceived cheaper for a country with large forest dotations. The implicit idea
is that the net beneﬁt (or cost) of deforesting is decreasing (increasing) in forest scarcity2. Net
beneﬁt of deforestation contents the beneﬁt of agricultural expansion and the environmental
costs of reducing the forest cover. Thus we expect a positive impact of forest dotations on
deforestation. Second, we consider forest harvesting. Deforestation is related to changes in
1see Lopez and Mitra (2000).
2Rudy et al. (2005) and Ewers (2006) give some evidence of this forest transition hypothesis.
3the land use, while sustainable forest harvesting implies no switch in the land use. Thus,
if forest harvesting is sustainable, it should have no impact on deforestation. Conversely,
if forest harvesting is not sustainable, it would tend to increase deforestation. Finally, we
consider certiﬁed (FSC) forest areas, to control for sustainable forest harvesting. We expect
here a negative link between FSC forest areas and deforestation.
3 Is there a resource curse for deforestation?
3.1 Data and regressions
We carry out an econometric analysis using cross-country regression. We regress our defor-
estation proxy (Deforestation) on a vector of natural resource endowments (Resource) and
a vector of other potential explanatory variables (H):
Deforestation
i = β0 + β1Resource
i + β2H
i
j + u
i (1)
Subscript i refers to the country and j the explanatory variable. Our deforestation
indicator is the forest cover change for the period 1990-2005:
Deforestation
i ≡
ForestCoveri
90 − ForestCoveri
05
ForestCoveri
90
We test for two types of environmental resource curse. First, the impact of forest dotations
is estimated. Our ﬁrst control variable is a relative forest endowment indicator i.e. the
proportion of land area covered by forests (Forest Cover; FAO; 1990). Indeed, as mentioned
earlier, the perceived value of standing forests is likely to be smaller for countries with large
forest endowment. Thus, a country with an important forest cover is likely to deforest more
than a country with small forest cover.
Second, we consider the impact of forest harvesting, using industrial roundwood produc-
tion divided by GDP, which is a proxy for the share of GDP provided by the forestry sector
(Forest Sector; FAO; 1985). This proxy is somehow tricky, but the FAO (Food Agricultural
Organization) only provides roundwood production data in volumes. As discussed before,
sustainable forest harvesting should have no or small impact on the forest cover, while un-
4sustainable forest exploitation should increase deforestation. Indeed, the FAO deﬁnition of
the forest cover is: Land spanning more than 0.5 hectares with trees higher than 5 meters
and a canopy cover of more than 10 percent. Forest exploitation leads to deforestation only
if the cover decreases to less than 10%. An environmental resource curse would therefore
come from unsustainable forest exploitation.
Our ﬁrst control variable concerns sustainable harvest. Indeed, we consider the size
of FSC certiﬁed forest area (Certified; UNEP; 2005). A country relaying on sustainable
harvesting is likely to experience lower levels of deforestation. The second type of control
variables approximates institutional quality. We use the IRIS corruption index (Corruption;
IRIS; 1982). We expect a negative impact of corruption (positive impact of the index) on
the forest cover: rent-seeking behaviors and poor institutions to appropriate forest resources
are likely to increase deforestation. Third, we consider the annual growth rate of GDP as a
potential explanatory variable (Growth; Penn World Tables; 1970-90)3. Finally, an indirect
resource curse is estimated using the share of primary products exports in National GNP
(PrimaryExports; World Data; 1970), which is the usual indicator of resource dotations
in the resource curse literature. An indirect environmental resource curse would come from
road creation and bad environmental management due to poor institutions.
In line with Papyrakis and Gerlagh (2004), we estimate the model of equation (1) by
using Ordinary Least Squares (OLS) estimator and by increasing gradually the set of vari-
ables H to evaluate our theoretical background. Nevertheless, we need to control for some
econometric concerns. In line with the ”‘GDP convergence”’ literature, we can indeed expect
some endogeneity problems facing reverse causality between the deforestation rate and two
regressors: Forest Cover and Forest Sector. At ﬁrst, endogeneity is controlled through the
Hausman test (1978). Because the residuals are not signiﬁcant at 10%, there is no evidence
of endogeneity (in sense of simultaneity) in our regressions. However, those results should be
interpreted cautiously because the inability of the Hausman test to identify endogeneity is
likely to reﬂect the small sample size (N = 40 in this case). Thus we also estimate equation
(1) excluding Certification, in order to increase our sample size (N = 70). At second, we
choose variables refereing either to the beginning of the considered period (1990) or before
3We voluntarily ignore the Environmental Kuznets Curve hypothesis here, as it is largely covered in the
literature (Arcand et al., 2008; Culas, 2006).
5that period (we use Forest Cover in 1985). In addition, we control for heteroskedasticity
concerns, normalizing roundwood production and certiﬁed forest area to GDP, and perform-
ing regressions using White-Heteroskedasticity-Consistent Standard Errors and Covariance.
Multicolinearity is ruled out through the Variance Inﬂation Factor (VIF) index. Finally we
test for the robustness of our regressions using some speciﬁcation test like the Ramsey’s RE-
SET test (1969). Besides, the addition of other possible determinants of the deforestation
(Primary Export for instance) does not change the signiﬁcance of our variables of interest of
our ﬁndings. Our coeﬃcients of interest are quite stable.
3.2 Main results and conclusion
1) Countries with relatively important forest cover have deforested more over the consid-
ered period than countries with small forest cover. Deforestation is thus perceived cheaper
for a country with large forest endowments, conﬁrming the forest transition hypothesis.
2) We ﬁnd some evidence of an environmental forest resource curse: countries relying
heavily on forest harvesting have deforested more than countries with small forestry sectors.
Moreover the estimated tendency is robust when controlling for corruption. This result gives
the alarming insight that forest exploitation is mainly unsustainable worldwide, indepen-
dently of institutional factors.
3) Deforestation appears signiﬁcantly more important in countries with poorer institu-
tions. Unsurprisingly, corruption, rent-seeking behaviors and poor political management
facilitate resource appropriation, limits law enforcement and thus favors land appropriation
and unsustainable forest use.
4) Countries relying on more on sustainable harvesting (through FSC certiﬁcation) de-
forest less than the others. It thus appears that certiﬁcation is quite representative of better
environmental management, and could be taken into account in the context of global warm-
ing mitigation.
5) We do not ﬁnd evidence of an indirect environmental resource curse. The coeﬃcient
related to natural exports is no signiﬁcant at 10% and is consequently ruled out the ﬁnal
model. In addition, the growth signiﬁcantly (at 10%) dampens the deforestation rate.
6Table 1: Deforestation regression as in Equation (1)
Deforestation
Forest Cover 0.35 0.31
(3.89) (3.24)
Forest Sector 0.13 0.18
(3.52) (2.69)
Certiﬁed -0.11 -
(-2.67) (-)
Corruption† -3.02 -3.07
(-4.03) (-3.09)
Growth -1.25 -2.82
(-1.58) (-1.84)
Adjusted R2 0.50 0.40
N 40 70
t-statistics are in parentheses.
All variable are signiﬁcant at 1% level of signiﬁcance, except Growth (10%).
PrimaryExports and the constant are not signiﬁcant at 10% and dropped from the main model.
†Corruption index: low score means high corruption
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9

A heteroskedasticity-consistent covariance matrix and direct test for heteroskedasticity.

A simple test for heteroskedasticity and random coeﬃcient variation.

Can the natural resource curse be turned into a blessing? the role of trade policies and institutions. IMF Working Papers 07/55, International Monetary Fund.

Corruption, pollution, and the kuznets environment curve.

Corruption: A challenge for economists interested in forest policy design.

Deforestation and the environmental kuznets curve: An institutional perspective.

Deforestation and the real exchange rate.

Does mother nature corrupt? Natural resources, corruption and economic growth,

Forest transitions: towards a global understanding of land use change. Global Environmental Change,

Institutions and the resource curse.

Interaction eﬀects between economics development and forest cover determine deforestation rates. Global Environmental Change,

Natural resource abundance and economic growth.

Nonlinearities and heterogeneity in environmental quality: An empirical analysis of deforestation.

Resource intensity, institutions and development.

Speciﬁcation tests in econometrics.

Systemic corruption, scale eﬀects and forest harvesting. Working Paper,

Techniques for testing the constancy of regression relationships over time.

Test for speciﬁcation errors in classical linear least squares regression analysis.

Testing for multiplicative heteroskedasticity.

The big push, natural resource booms and growth.

The resource curse hypothesis and its transmission channels.

Why do some countries produce so much more output than others.

The environmental resource curse hypothesis: the forest case

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The environmental resource curse hypothesis: the forest case

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