ECOLEC-03765; No of Pages 10
Ecological Economics xxx (2010) xxx–xxx
Contents lists available at ScienceDirect
Ecological Economics
j o u r n a l h o m e p a g e : w w w. e l s e v i e r. c o m / l o c a t e / e c o l e c o n
The impact of culture and ecology on cooperation in a common-pool
resource experiment
Sebastian Prediger a,⁎, Björn Vollan b, Markus Frölich c,d,e
a
University of Marburg, Department of Business Administration and Economics, Institute for Co-operation in Developing Countries (ICDC), Am Plan 2, D-35032 Marburg, Germany
University of Mannheim, Department of Economics, Chair of Econometrics, L7,3-5, D-68131 Mannheim, Germany
University of Mannheim, Germany
d
IZA Bonn, Germany
e
ZEW Mannheim, Germany
b
c
a r t i c l e
i n f o
Article history:
Received 15 January 2010
Received in revised form 8 July 2010
Accepted 8 August 2010
Available online xxxx
JEL classification:
C35
C93
D70
Q24
Q57
Keywords:
Common-pool resource experiment
Southern Africa
Payoffs to cooperation
Historical/political background
a b s t r a c t
Context affects decision-making in many ways. In this paper we explore differences in cooperation behaviour
between communal farmers in Namibia and South Africa, who share the same ethnic origin but have had
different historical and ecological constraints. We report on a series of field experiments based on a commonpool resource model. Our experimental design is framed according to the grazing situation in semi-arid
rangelands. Dependent on the behaviour in previous rounds, participants are facing different states of
resource availability with varying need to cooperate, coordinate and to be patient. While only 4% of the
grazing areas in South Africa remain in good quality, Namibians achieve a level of 42%. We analyse the
different experimental states and find that Namibians behave in all states more cooperatively. We argue that
the large difference between the two regions is due to a combination of different historical developments and
ecological preconditions: Namibian resource users have a longer experience in cooperative resource
management and intact traditional norms. Moreover, the real-life payoffs to cooperation are higher in
Namibia stemming from ecological factors.
© 2010 Elsevier B.V. All rights reserved.
1. Introduction
In our study area, the communal lands of Berseba (Namibia) and
Namaqualand (South Africa), the majority of residents depend on
livestock production at subsistence level. The sustainable management of the rangelands is thus essential to poverty reduction and
development of local livelihoods. Residents in both study areas share a
common origin from the Nama culture and used to share the same
traditions. Grazing areas are managed commonly and are characterized by rivalry in consumption and costly exclusion of other users.
Because there are no de facto formal institutions regulating grazing in
our study areas, norms of cooperation and trust are crucial to manage
grazing resources in a sustainable way.
Economic experiments on the sustainable management of commonpool resources (CPR) have been carried out since the beginning of the
1990s in the laboratory (Casari and Plott, 2003; Ostrom et al., 1994) and
also later in the field (Cardenas et al., 2000; Velez et al., 2009). In field
⁎ Corresponding author. Tel.: +49 163 5673429.
E-mail address: [email protected] (S. Prediger).
studies performed with real life CPR users, extraction rates were found
to deviate substantially from the Nash equilibrium. Yet, with more
realistic settings, e.g. the possibility to communicate or to punish,
resource users were able to escape the social dilemma of overuse over
long periods of time (Ostrom, 2006). At the same time, economists
developed theories on social preferences (e.g. Bolton and Ockenfels,
2000; Fehr and Schmidt, 1999) which have in common that individual's
utility partly depends on other people's welfare. However, theoretical
research in economics almost universally ignores cultural differences
(Cason et al., 2002; Henrich, 2000), despite recent studies across diverse
societies (Henrich et al., 2005; Herrmann et al., 2008) provide strong
evidence that economic behaviour varies greatly among individuals
who grew up in different places, thus suggesting that individual
economic decision-making is affected by socialisation and cultural
background.
The experiments presented here are based on a “within culture
between countries” design. They are framed as a task to collectively
manage grazing around the village and address the problem of land
degradation on the communal lands of Berseba (Namibia) and
Namaqualand (South Africa). Our experimental design reflects typical
ecological features of our study area and is framed according to the
0921-8009/$ – see front matter © 2010 Elsevier B.V. All rights reserved.
doi:10.1016/j.ecolecon.2010.08.017
Please cite this article as: Prediger, S., et al., The impact of culture and ecology on cooperation in a common-pool resource experiment, Ecol.
Econ. (2010), doi:10.1016/j.ecolecon.2010.08.017
2
S. Prediger et al. / Ecological Economics xxx (2010) xxx–xxx
State-and-Transition model for semi-arid rangelands. With this more
realistic framework regarding the decision situation, we investigate
how real-life resource users collectively organize the management of
rangelands in different ecological states. Our subjects are rural
villagers who originally share the Nama ethnic group as common
ancestors but have experienced different historical and societal
developments and, moreover, have to cope with different ecological
environments. In many case studies of CPR management it has been
found that attributes of the users, their governance system, the
resource system, and the resource units matter for successful selfgovernance (Ostrom, 1990, 2007). Based on these frameworks we
derive hypotheses for our study region to test whether the same effect
of enhanced cooperation observed in case studies (mainly due to
restriction in people's choice sets) can also be captured in an economic
behavioural experiment.
We hypothesize that Namibians have intact traditional norms and
a longer history of cooperative grazing management which may
favour cooperative behaviour in a social-dilemma experiment. In RSA,
on the other hand, frequent and long-term interferences by external
powers led to internal conflicts and a high incidence of corruption,
which may have created obstacles to cooperation. Evidence for this
claim comes from prior field experiments, anthropological and
historical research. In our experiments, we find that the Namibian
Nama play much more cooperatively than their relatives from South
Africa.
Our experiments were initially developed by Cardenas et al.
(2008) and are presented in this volume by Castillo et al. (this
volume). They find that participants in Thailand and Colombia (both
fishermen and students) behave very similarly to our sample of South
Africans. Since the Thai and Colombians have not experienced
political problems similar to South Africa, we believe that some
additional factors may drive the exceptionally successful resource
management in Namibia. Thus, our main task is to explain the
“outlier” that happened in Namibia where people acted extremely
carefully in order to avoid degradation of their grazing areas. In
addition to the different historical development, we present ecological evidence that the ecosystem in Namibia is more sensitive to
overgrazing and more likely to become irreversibly degraded.
Consequently, the payoffs to engage in cooperation in order to
prevent degradation are higher in Namibia than in RSA. Therefore, we
further hypothesize, similar to Henrich et al. (2005), that resource
users who have higher benefits from cooperation in real life also
behave more cooperatively in the experiment.
Apart from the historical–political and ecological context differences, our subjects share very similar characteristics: They have a
common ancestry, speak the same language, and have the same
livelihoods (mainly livestock husbandry) and a similar sociodemographic composition. We thus believe that the most relevant
differences between our Namibian and South African sample in our
analysis are the different historical developments and the resource
characteristics that simultaneously led to a different behaviour in
Namibia as highlighted by co-evolutionary theories of institutional
change (see cf. van den Bergh and Stagl, 2003). In order to test our
historical–ecological hypothesis, we analyse individuals' propensity
to cooperate in different resource scenarios, which require different
degrees of cooperation, coordination and patience among resource
users.
Berseba
Keetmanshoop
Karasburg
Warmbad
Namibia
South Africa
Note: The experiments were conducted in the communal lands of Berseba in
Namibia (rectangle with red frame) and in the Leliefontein reserve in the Namaqualand
in South Africa (rectangle with green frame).
Fig. 1. Map of the study site.
section we outline the different ecological circumstances and
historical developments of our study areas, as we think that both
could have an influence on cooperative behaviour in our experiments.
2.1. The Historical and Societal Context
2. Predictions Based on the Historical and Ecological Background
of the Study Area
Originally, the Nama people of our study areas were semi-nomadic
livestock herders who shared the same cultural norms and traditions.
Oral traditions of the Nama as well as archaeological findings suggest
that the Nama divided at the mouth of the Orange River around
2000 years ago: the “great Namaqua” moved northwards into
southern Namibia, while the “little Namaqua” migrated into the
south and settled in the Namaqualand in RSA (Boonzaier et al., 2000).
The Nama people of Namibia and RSA experienced very different
historical developments in the last three centuries.
In South Africa, since the beginning of the colonial expansion into
the Namaqualand in the early 18th century, the European settlers
rapidly began to appropriate huge parts of the Nama territories. The
substantial dispossession of land and the denial of migratory movements of their herds by the colonial administration replaced the
traditional lifestyle of bartering and pastoralism among the Nama in
RSA and gradually undermined their society and cultural identity
(Boonzaier et al., 2000).1 Due to apartheid in Namaqualand people
were displaced and resettled. The strong western influence (e.g. the
imposition of western farming practices) and external interventions
that the people in Namaqualand have been and are still facing can also
Our experiments were carried out in two different regions that
during apartheid were either former homelands or so called “coloured
reserves” where the non-white population lived: In the communal
lands of Berseba in southern Namibia (once called “Namaland”) and in
the Leliefontein reserve in the Namaqualand in RSA (Fig. 1). In this
1
A further example for the erosion of cultural identity is the adoption of the
Afrikaans language around 1800. The loss of Nama identity culminated in the denial of
their ancestry in the late 20th century, when Nama people recognized themselves as
“coloured” people and rejected the name Nama because of their marginal status in
apartheid South Africa, where the Nama were publicly recognized as “primitive” or
“backward”.
Please cite this article as: Prediger, S., et al., The impact of culture and ecology on cooperation in a common-pool resource experiment, Ecol.
Econ. (2010), doi:10.1016/j.ecolecon.2010.08.017
S. Prediger et al. / Ecological Economics xxx (2010) xxx–xxx
be exemplified by the joint attempt of the apartheid administration
and the local management board in 1984 to privatize the communal
land into individualized, exclusive “economic units” (May and Lahiff,
2007). The establishment of “economic units” worsened the skewed
distribution of access to land and wealth and fuelled the divide among
the inhabitants of the communal areas, because the majority of them
lost access to grazing land. Although the broad majority of the
population successfully opposed the privatization, as the Supreme
Court eventually overruled the system of “economic units” in 1988,
the local dispute “has left a legacy of factional division and bitterness”
within the communal areas (Cousins, 1996:11). Internal tensions
among the inhabitants of our study area in Namaqualand seem to
have continued during the ongoing land reform process since
independence in 1994. The redistribution of former white-owned
land especially abets affluent members of the communities and has
led to “widespread discontent among those unable to access this land”
(May and Lahiff, 2007: 778).
In Namibia, the first Europeans arrived much later, mostly at the
end of the 19th century after Germany became the colonial power in
1884. During the following three decades, the German colonial power
broke local resistance and almost completely appropriated the Namas'
ancestral land. Only the Nama tribe in our Namibian study area in
Berseba could preserve large parts of their territory and retained their
local institutions largely intact throughout colonial and apartheid
regime (Kössler, 2001).2 As such the communal land of Berseba was
still managed by captaincy and, despite some interference from
colonial and apartheid regimes into internal affairs, the Berseba
community could maintain self-governance until independence in
1990. In contrast to the Namaqualand, people in Namibia did not
suffer from widespread corruption, and attempts to privatize the
commons have never been made. In the last 10 years, communitybased projects like the formation of local water point associations or
conservancies were initiated in the Berseba constituency in Namibia,
showing that the communities there are capable of self-organization.
In the Namaqualand, on the other hand, many community projects
failed due to internal envy and mismanagement (Vollan, 2008).
Moreover, in prior experiments conducted in our study areas it has
been found that the Nama in Namibia exert significantly higher trust
towards their community members than the Namaqualanders
(Vollan, 2008). Given the signs for stronger community cohesion
and norms of trust in Namibia, we assume them to be more
cooperative in our grazing experiments.
Nowadays, both areas lack behind the development of their
countries and the vast majority still live on livestock production based
on subsistence. A lack of formal employment and the neglect of the
physical and social infrastructure during apartheid are important
reasons for the widespread poverty in the communal lands. Moreover,
in both areas inhabitants face similar social (e.g. HIV), economic (high
unemployment, lack of entrepreneurship) and ecological challenges
(resource degradation).
2.2. The Ecological Background
Though both study areas are semi-arid, there are substantial
ecological differences between them. While the communal lands of
Berseba in Namibia lie within the Nama Karoo biome, our study area
in Namaqualand (RSA) is situated in the Succulent Karoo biome. The
Succulent Karoo is recognized as one of the world's most endangered
biodiversity hotspot: In contrast to most other semi-arid biomes,
2
The colonial administration granted exclusive rights to the Berseba clan since they
stayed aloof from the Nama Uprising against the German colonial power in 1804–
1807. For example, anthropological research shows that the people maintained
traditional norms of generalized reciprocity (Klocke-Daffa, 1999). Moreover, the
Namibian Nama still speak their indigenous language.
3
including the Nama Karoo in Namibia, annual rainfall is predictable
and prolonged droughts are very rare (Cowling et al., 1999). These
unique ecological features are responsible for the enormous plant
diversity of the Namaqualand and make the ecosystem relatively
robust. In the Nama Karoo in Namibia, on the other hand, rainfall is
erratic and highly variable, ranging between 50 and 290 mm per
annum (Kuiper and Meadows, 2002). Moreover, severe droughts are a
common occurrence in the Berseba area (Namibia) and in turn make
the ecosystem of the Nama Karoo more fragile and responsive to
grazing.
In both study areas, many parts of the communal land have
switched into a different ecological state. Overstocking is doubtless a
major driver of these changes. However, indicators of theses
ecological changes differ remarkably between Namibia and RSA. In
our Namibian study area (Nama Karoo), a sequence of long-term
satellite images indicates that the change from commercial farm
status to communal land has led to an increase in bare soil from 6.3%
in 1970 to 11% in 1998 while it remained the same on a neighbouring
government farm where stocking rates were significantly lower
(Kuiper and Meadows, 2002). In addition to more bare patches, the
ecological change in Namibia is characterized by less perennial
grasses, lower species diversity and the abundance of “desert” species
(Hoffmann and Zeller, 2005). In the Namaqualand in RSA (Succulent
Karoo), on the other hand, heavy grazing did not lead to bare soils but
to an increased density and recruitment of the unpalatable shrub
Galenia africana (Todd and Hoffman, 1999) and a compositional shift
towards smaller species.
Thus, changes in the Succulent Karoo ecosystem in Namaqualand
(RSA) occur slowly and more gradually, due to the predictable rainfall
and the high plant diversity. But gradual changes, like a compositional
shift towards smaller species, are not as visible as bare soils and thus
only observable to scientists and people with good knowledge of
indigenous plants.3 Yet, if changes in the resource system are not as
easily observed and indicators (e.g. loss of certain species) to learn the
resource dynamics are more difficult to recognize, a common
understanding of the need for sustainable management is less likely
to occur. On the other hand, the occurrence of bare soil patches in
Namibia is easily observable to farmers and an unambiguous indicator
of degradation. Bare patches yield no future income and are
irreversibly destroyed in most cases (Visser et al., 2004). Thus, the
payoffs to cooperation (from preventing degradation) are higher in
Namibia than in RSA. Due to the higher payoffs to cooperation in real
life, we hypothesize that Namibians manage the rangelands (at least
in our experimental set-up) more successfully.
3. Experimental Design
Our grazing experiments are based on the protocol of the fishery
experiments of Cardenas et al. (2008) but translated to rangelands.
The fishery experiments were conducted in Thailand and Colombia
and their results are presented by Castillo et al. (this volume). We
adopted their design as it reflects the inter-temporal dynamics of
grazing in semi-arid rangelands and has features of path dependency
of previous use, spatial variability and non-linearity of payoffs. The
most important feature for our study area is the (temporary) resource
degradation when a certain threshold has been exceeded. The Stateand-Transition model, developed by ecologists to evaluate rangeland
dynamics in semi-arid regions, asserts that ecosystems are moving
towards different stable states but that changes from higher to lower
states and vice versa occur due to a combination of major events, such
as droughts or little rainfall and high grazing pressure (Westoby et al.,
3
Research of ethno-botanists supports this claim, as they report that knowledge of
plants is rapidly disappearing in the Namaqualand (Boonzaier et al., 2000).
Please cite this article as: Prediger, S., et al., The impact of culture and ecology on cooperation in a common-pool resource experiment, Ecol.
Econ. (2010), doi:10.1016/j.ecolecon.2010.08.017
4
S. Prediger et al. / Ecological Economics xxx (2010) xxx–xxx
• L2L2: both areas are in bad condition and each needs two rounds to
recover.
Table 1
Payoff table.
Grazing
quality
Grazing intensity
0
1
2
High
Low
0
0
7
2
8
3
Note: This table is based on Cardenas et al. (2008).
1989). The ecological states of rangelands differ with respect to
resource availability and species composition: The lower the state, the
less grazing is available. Our experimental design allows us to
accommodate the heterogeneity of resource availability and thus to
analyse subjects' propensity to cooperate in different ecological states.
An experimental session consists of 5 participants and lasts for 10
rounds. The composition of groups remained unchanged throughout
the session (fixed matching) and participants did not know the actual
number of rounds in advance. In each round, similar to a grazing
season, each participant decides whether to graze on area A or B, and
she chooses either a low or a high stocking rate (intensity 1 or 2,
respectively). Alternatively, she may choose to not graze at all
(=intensity 0). According to the payoff table below (Table 1), returns
to grazing do not only depend on individual intensities but also on the
grazing quality, which can be good or bad.4 For example, an intensity
of 1 gives seven tokens when the chosen grazing land is in good
condition, but only two tokens in case the grazing quality is low.5 The
aggregate group intensity on an area (i.e. the sum of the grazing
intensities of all five group members on that area) in round t
determines the grazing condition in the next round t + 1. If the
aggregate group intensity exceeds the carrying capacity of 4 in round
t, the grazing area switches to bad condition in round t + 1. (Since the
maximum intensity each player can choose is 2, the aggregate
intensity ranges between 0 and 10, for each area.) A grazing area of
bad quality recovers to good quality if for two successive rounds the
group grazing intensity is less or equal to 1 (in each round). This
captures the observation for semi-arid rangelands that transitions are
possible in both directions, but that changes from a lower to a higher
ecological state require a substantial reduction of stocking rates for a
relatively long time period (Visser et al., 2004). The design implies
that a grazing area can either be in good condition (H) or in bad
condition with two more rounds needed to recover (L2) or in bad
condition with one more round needed to recover (L1, i.e. this area
already has recovered one round). If the aggregate group intensity on
an L1 area is larger than 1, the area switches back to L2.
With two separate grazing areas, there are thus 6 possible
ecological states a group might be facing:
• HH: both areas are in good condition.
• HL1: one area is in good condition; the other area is in bad condition
but already has recovered one round.
• HL2: one area is in good condition; the other area is in bad condition
and needs two rounds to recover.
• L1L1: both areas are in bad condition and each needs one more round
to recover.
• L1L2: one area is in bad condition and needs one more round to
recover, the other area is also in bad condition but requires two
rounds to recover.
We would expect the degradation of one grazing area immediately
after the initial round, leading to a situation with one good area and
one bad area (HL2) in the beginning of period 2. (Because if all subjects
apply an intensity of 2, then in one of the two grazing areas the
maximum carrying capacity of 4 will be exceeded automatically. On
the other hand, it is impossible that the carrying capacity is exceeded
in both areas.) In the next round all players will choose the remaining
location in good quality, resulting in a situation where both grazing
areas are bad (L1L2) at the beginning of round 3. In that situation, both
pastures yield the same return, but one grazing area (L1) will require
only one more round to recover. Therefore, all players would spare the
L1 area and choose an intensity of 2 on the L2 area. Consequently, in
period 4 (and 6, 8 and 10), participants will face the same situation as
in period 2, with one good grazing area and one bad area (HL2), and
will choose again the area which yields the highest return. Therefore,
individual payoff-maximizing behaviour can lead to a rotation system,
where each second round one location will be in good condition. In a
sequence of ten rounds, the resulting group return is 300 tokens. On
the other hand, if subjects do not distinguish between L1 and L2 at the
beginning of round 3, or if they are myopic, they are likely to get stuck
in a situation where both grazing areas are degraded for the
remaining eight rounds. Then, the group return will be at maximum
200 tokens at the end of round 10. Yet, if participants fully coordinated
their actions, a group return of 382 tokens would be possible.
Altogether we conducted 24 experimental sessions, 12 in the
Namaqualand (RSA) and in the Berseba area (Namibia), respectively.
In both study areas, formal employment opportunities are rare and for
most households keeping livestock on subsistence basis is an
important part of their livelihood (Kuiper and Meadows, 2002).
Information on socio-demographic characteristics of our participants
is presented in the supplementary material. The instructions of the
experiments were presented orally (in Afrikaans) by the same
experimenter in all 24 sessions. During the experiments, communication was impossible.
4. Results
First, we examine the results without distinguishing between
different levels of resource availability. Judged solely by the average
group earnings after round 10, the results for Namibia (201 tokens)
and RSA (191) are very close to the Nash-equilibrium of 200 tokens
(which was predicted for the case where subjects do not distinguish
between L1 and L2). However, group revenues vary substantially
among the groups, ranging from a minimum of 139 (164) tokens up to
279 (249) in Namibia (RSA).6 Furthermore, subjects did not behave as
selfishly as predicted: The maximum intensity of 2 units was applied
in only 38.5% of all cases, and in about 21% of all cases the intensity
zero was chosen. In none of the sessions we observed the presumed
‘rotational pattern’ where subjects would have one good pasture to
graze on each second round and which would have evolved if subjects
followed a payoff-maximizing behaviour but differentiated between
low quality areas that need one respectively two rounds to recover. If
faced with asymmetric resource conditions (i.e. the scenarios HL2, HL1
and L1L2), a substantial fraction of subjects did not choose the grazing
area one might have expected. In the scenarios HL1 and HL2, for
example, a fraction of 22% decided to graze on the low quality pasture
and not, as predicted, on the good pasture, implying that the bad
4
The payoff table is the same for both locations.
The tokens were converted to South African Rand (ZAR) or Namibian Dollar
(NAD), respectively. Both currencies are accepted means of payment in Namibia and
are pegged at a 1:1 exchange ratio. One token was worth ZAR/NAD 0.25. The average
exchange rate was 7.153 ZAR/$ at that time.
5
6
On average, individuals earned 39 tokens (≈ZAR 10) until round ten, ranging from
20 to 68 tokens. In addition to these earnings, everybody received a showing-up fee of
ZAR 10.
Please cite this article as: Prediger, S., et al., The impact of culture and ecology on cooperation in a common-pool resource experiment, Ecol.
Econ. (2010), doi:10.1016/j.ecolecon.2010.08.017
S. Prediger et al. / Ecological Economics xxx (2010) xxx–xxx
5
% pastures in good condition
100
80
RSA
60
NAM
40
20
0
1
2
3
4
5
6
7
8
9
10
Notes : The continuous red (green) line with squares (triangles) indicates the percentage of good condition
grazing areas in Namibia (South Africa) over the course of the game. The red and green dashed lines represent
the 95%-confidence intervals.
Fig. 2. Comparison of average stock levels between countries.
pastures did not rest and thus could not recover. As shown in Fig. 2,
substantial differences between Namibia and RSA are visible when we
examine the evolution during the 10 rounds. Fig. 2 shows the average
resource availability, measured by the number of grazing areas in
good condition per round in per cent, in Namibia and RSA. South
Africans had difficulties in both, maintaining high resource availability
as well as in recovering from low stock levels. At the latest after four
rounds, all South African groups were trapped in a situation where
both locations were in bad condition. Only 4% of grazing areas were in
good quality at the end of round 10 (line with triangles). A very
similar situation is observed by Castillo et al. (this volume) in the
fishery games for Colombia and Thailand. Furthermore, none of the
groups in RSA ever recovered to the initial situation of having two
good pastures. On the contrary, Namibians were remarkably successful in resource management by sustaining 42% of pastures in good
quality after round 10. Moreover, half of all groups could manage to
regain full resource availability (HH) when faced with degradation the
first time and needed on average only 3.16 rounds to recover. In
general we find the Namibian groups to be more successful, as they
achieved grazing improvements in 48% of all possible cases, compared
to 27% in RSA. Examples for grazing improvements include switches
from L1L2 to HL2 or from L2L2 to L1L2.
turn our focus on area choices made by the individuals if confronted
with the scenario HL2.
The covariates we use in all regression analyses are classified into
three different groups of variables: socio-demographic, collective
action and group variables.7 Since we expect intensity and area
choices to depend on some village morality we include an index
measure of surveyed trust and dummies for subjects' self-assessment
about their influence within the community and voluntary community work. We further control for the exogenous variable “round
number”, since cooperation might increase or decrease over time.
The first column of Table 2 displays the marginal effects on the
probability of applying intensity two in the scenario where grazing is
abundantly available, i.e. where either both pastures are in good
condition (HH), or one grazing area is in good and the other one in bad
condition, but needs only one more round to recover (HL1). Both
resource scenarios are quite similar in that subjects can face high
resource availability in one pasture for the next two successive
rounds.8 To avoid degradation, the only cooperative strategy is to
apply a maximum intensity of one unit.9 We find Namibians to be
significantly more likely to choose either no intensity or an intensity
4.1. Cooperation Under Four Different Ecological Conditions
Fig. 2 revealed a substantial difference between Namibia and RSA.
The rapid destruction of both grazing areas as well as the relatively
low incidence of grazing improvements suggests that South Africans
behave less cooperatively than their ancient relatives from Namibia.
However, it might be the case that South Africans behave cooperatively too, at least in certain ecological situations, but fail to coordinate
their actions. The resource scenario HL2, for instance, constitutes an
ecological condition where cooperation and coordination is required,
as more than one strategy can result in resource recovery. It is also
possible that South Africans exhibit an intention to cooperate initially,
but are too myopic to regain recovery. This might be the case in the
scenario L2L2, where cooperative behaviour (here applying intensity
zero) ensures recovery only if the players are patient, i.e. if they have a
time horizon of two rounds.
We distinguish among four different resource scenarios a group
might be facing, and first examine individual intensity choices of
Namibians and South Africans in each scenario. In Section 4.2, we then
7
The independent variables married, female, permanent work, farmer, voluntary
community work, Namibia and community involvement are categorical variables. The
reference category for marital status is single, widowed or divorced, and for
employment status is occasional work, pension or unemployed. Age is measured in
years. Education is an ordinal scaled variable with the characteristics “some primary
school” (1.7%), “primary school” (12%), “secondary school” (80%), “technical” (3.4%)
and “university/post-university” (2.6%). Community involvement takes 1 if subjects
answered the question “How much influence do you think people like yourself can
have in making this village a better place to live?” with “a lot”. Voluntary community
work is a categorical variable that takes 1 if subjects were engaged in voluntary work
during the last year. The considered group variables are: The fraction of female
subjects and farmers (ranging from 0 to 1) and the average age of the other group
members. Trust is an index variable ranging from 0 (no trust) and 4 (high trust)
constructed with answers of different statements (see supplementary material).
8
This is also the case in the situation HL1, because we expect that in this situation
one would usually either choose the grazing area H or alternatively zero intensity in
order to let the L1 area rest for one more round. Therefore, in the next period the L1
area has recovered back to high quality.
9
This strategy can still cause degradation if all five players choose the same grazing
area and intensity one. Yet, the probability that all subjects choose the same location is
only 6.25%.
Please cite this article as: Prediger, S., et al., The impact of culture and ecology on cooperation in a common-pool resource experiment, Ecol.
Econ. (2010), doi:10.1016/j.ecolecon.2010.08.017
6
S. Prediger et al. / Ecological Economics xxx (2010) xxx–xxx
Table 2
Marginal effects after ordered probit estimations for individual intensity choices.
Y: individual intensity
Namibia
Socio-demographics
Education
Age
Married
Female
Permanent work
Farmer
Collective action
Voluntary Community work
Trust index
Community involvement
Group variables
Average age
Fraction female
Fraction farmer
Round number
Dummy for HL1
i.e. one grazing area L1
Observations
Chi square
Degrees of freedom
Pseudo R²
Log Likelihood
SE adjusted for clusters
HH and HL1 resource
abundance
L1L2 resource scarcity
(short-term cooperation)
L2L2 resource scarcity
(long-term cooperation)
HL2 spatial resource
availability
−0.419***
(0.068)
−0.265***
(0.102)
−0.304***
(0.089)
−0.429***
(0.069)
0.104
(0.069)
0.005*
(0.003)
−0.076
(0.083)
0.016
(0.075)
−0.079
(0.084)
−0.020
(0.068)
−0.057
(0.053)
0.001
(0.003)
0.125
(0.128)
0.140
(0.119)
−0.189*
(0.108)
0.019
(0.121)
−0.025
(0.040)
−0.001
(0.003)
0.110
(0.095)
0.273***
(0.077)
−0.181*
(0.094)
−0.040
(0.094)
0.054*
(0.030)
0.002
(0.002)
−0.103
(0.067)
−0.027
(0.062)
0.206***
(0.076)
0.028
(0.067)
−0.043
(0.064)
0.019
(0.058)
0.116*
(0.064)
−0.040
(0.096)
−0.071
(0.085)
0.025
(0.099)
−0.291***
(0.066)
−0.102
(0.083)
0.142
(0.097)
−0.082
(0.057)
0.007
(0.053)
0.015
(0.062)
−0.001
(0.004)
−0.019
(0.143)
0.174
(0.145)
0.039***
(0.011)
−0.424***
(0.062)
263
93.71***
15
0.152
−232.4
53
0.003
(0.006)
−0.163
(0.232)
−0.114
(0.220)
0.004
(0.016)
0.001
(0.004)
0.076
(0.189)
−0.128
(0.193)
0.031**
(0.014)
−0.009***
(0.003)
−0.009
(0.118)
0.043
(0.118)
−0.031***
(0.010)
153
23.29***
14
0.0796
−153.4
71
229
75.31***
14
0.105
−209.7
71
273
75.66***
14
0.144
−247.3
93
Notes: Dependent variable is the intensity chosen (each individual, each round), which can be 0, 1 or 2. Ordered probit estimation. The table shows the estimated marginal effects for
the probability of choosing an intensity of 2. Not shown are the marginal effects for the probability of choosing an intensity of 0, nor for 1, nor the marginal effects on the mean
intensity. These omitted results led to similar qualitative conclusions.
***, **, and * indicates statistical significance at the 1%, 5%, and 10% level, respectively. Standard errors (shown in parentheses) are adjusted for clusters at the individual level. The
number of observations included in the estimations differ from the actual number of observations in each scenario due to missing values of some covariates.
of 1 and less likely to apply the highest intensity.10 We obtain the
same results if we analyse country differences in intensity choices
unconditionally, i.e. without controlling for further covariates. The
mean intensities in HH and HL1 differ significantly between Namibia
and RSA: Subjects from Namibia apply an average intensity of 1.09
units, compared to 1.63 in RSA (t = 6.04***). Only few South Africans
(6.7%) choose 0 when facing HH or HL1, while two thirds chose 2,
compared to about 31% in Namibia. This explains the fast resource
depletion observed for South Africa in Fig. 2.
The second and third columns of Table 2 show intensity choices
when resources are scarce and profits uncertain. We distinguish
10
In Table 2, we report only the marginal effects for the probability of choosing
intensity two. However, in all four resource scenarios we obtain highly statistically
significant (1% level) coefficients for intensity zero as well. The marginal effects for
intensity zero and one are available as supplementary material. The supplementary
material also contains further univariate and multivariate regression results. For
example, we report results of a regression model for each scenario, where we include
several game history variables (e.g. the cumulated and previous round individual and
relative profit) as further covariates. The strong country effect reported in Table 2
remains highly significant if we take the game history into account. Furthermore, we
perform separate regressions for HH and HL1 and obtain a significant country
difference as well for each scenario.
between two situations where higher future returns can be realized
soonest either in one period (L1L2) or in two periods (L2L2).11 The first
case requires cooperation in the short-run by letting rest the area
which needs only one round to recover (L1). In the latter case,
transition from the current to a better ecological state is possible, but
requires low stocking rates (at maximum one unit in at least one
grazing area) for two consecutive rounds and thus long-term
cooperation and patience among the subjects. In other words, the
benefits from cooperating for only one round are zero in L2L2.
Again we find a highly significant country effect: The likelihood of
choosing intensity 2 is 30 and 26.5 percentage points lower for
Namibians under L2L2 and L1L2, respectively. Moreover, Namibians are
significantly more likely to choose zero: 40% of the participants from
Namibia applied zero intensity in L2L2, compared to only about 14% in
RSA. We observe similar choices in L1L2, where about 80% of South
Africans chose either a low or high intensity, while the fraction of
Namibians who grazed with an effort of zero was larger than 55%.
These patterns explain why full recovery has never been reached in
11
The L1L1 scenario provides the prospect of recovery of both pastures in the
following round and thus constitutes a situation requiring short-term cooperation, too.
However, because the situation L1L1 was never observed in any of the experiments in
RSA, we exclude it from the analyses.
Please cite this article as: Prediger, S., et al., The impact of culture and ecology on cooperation in a common-pool resource experiment, Ecol.
Econ. (2010), doi:10.1016/j.ecolecon.2010.08.017
S. Prediger et al. / Ecological Economics xxx (2010) xxx–xxx
RSA. Whereas Namibians cooperate already more successfully if
resources are plentiful, they a fortiori outperform their relatives from
RSA in case of severe resource scarcity. The same conclusion can be
drawn for scenario HL2 (column four of Table 2) where resource
availability varies spatially. Here we obtain a highly significant
country effect as well.
We do not find any demographic characteristics to be significant in
all four scenarios. Only two covariates have a significant impact in
more than one scenario: round number and permanent work. Round
number has a positive effect in HH, HL1 and L2L2, implying that
subjects play more selfishly over time, whereas they play more and
more carefully over time when facing the situation HL2. Permanent
work has a negative impact in L1L2 and L2L2, albeit only weakly
significant. Hence, when resources are scarce, permanently employed
subjects are more willing to cooperate than occasional workers,
pensioners and jobless individuals. When facing HL2, however,
permanently employed workers are more likely to choose intensity
2. Yet, this need not necessarily be an uncooperative strategy as we
discuss in the next subsection.
It is noteworthy that we do not observe qualitative changes of the
covariates in Table 2 if we drop the country dummy. Thus, there is no
evidence that the significant country difference is driven by
differences in socio-demographics. Moreover, the pseudo-R² and
Chi2 values declined substantially, indicating that the country dummy
has high explanatory power for intensity choices.
To examine whether we had problems of multicollinearity, we
regress age and farmer on the remaining covariates of Table 2 using
simple OLS regressions respectively probit estimations if farmer is the
dependent variable. If there was collinearity, we should observe an R²
(respectively pseudo-R²) close to 1. However, because this was not
the case, there is no evidence for multicollinearity. In addition, we also
repeated the regressions of Table 2 after dropping one or two of the
covariates. Dropping these covariates, however, did not make any of
the other covariates statistically significant (as one would have
expected if the reason for their non-significance had been the nearcollinearity with the other covariates).
7
Table 3
Marginal effects after multinomial logit estimation for location choices if HL2.
Y: location choice
HL2
No grazing
Namibia
Socio-demographics
Education
Age
Married
Female
Permanent work
Farmer
Collective action
Voluntary community work
Trust index
Community involvement
Group variables
Average age
Fraction female
Fraction farmer
Previous round
Round number
Bad grazing
Good grazing
0.338***
(0.042)
0.078
(0.054)
−0.416***
(0.060)
0.008
(0.015)
−0.001
(0.001)
0.163***
(0.055)
0.022
(0.049)
−0.074**
(0.031)
−0.009
(0.040)
−0.033
(0.064)
−0.001
(0.002)
−0.039
(0.060)
0.078
(0.059)
0.170*
(0.095)
0.187***
(0.063)
0.025
(0.061)
0.002
(0.002)
−0.124
(0.078)
−0.101*
(0.060)
−0.095
(0.095)
−0.178***
(0.061)
0.055
(0.035)
−0.021
(0.030)
−0.036
(0.043)
−0.024
(0.057)
−0.027
(0.039)
0.031
(0.061)
−0.030
(0.061)
0.049
(0.042)
0.004
(0.071)
0.011***
(0.002)
0.089
(0.107)
−0.035
(0.091)
−0.001
(0.002)
0.073
(0.121)
−0.038
(0.095)
−0.009***
(0.003)
−0.162
(0.143)
0.073
(0.116)
−0.011
(0.008)
−0.010
(0.011)
0.0208***
(0.008)
Notes: Dependent variable is the chosen grazing area: Either H (good grazing), L2 (bad
grazing) or no grazing. The regression includes only those observations where the
group faced the grazing condition HL2, i.e. one grazing area in good and the other in bad
condition L2.
***, **, and * indicate statistical significance at the 1%, 5%, and 10% level respectively.
Standard errors (shown in parentheses) adjusted for 93 clusters at the individual level.
Number of observations: 273, Chi2: 129.1***, degrees of freedom, pseudo-R²: 0.178 and
log-likelihood: −217.5.
4.2. Cooperation Under Spatial Resource Differences
In semi-arid areas, overstocking might occur only in some areas
and is both a coordination problem of moving the animals to the
‘right’ grazing area and a cooperation problem to prevent free-riding.
The scenario HL2 constitutes such an ecological condition which
requires cooperation and coordination. In Table 3 we investigate
whether Namibians and South Africans behave differently when
facing this scenario. Subjects are confronted with three different
alternatives in HL2: No grazing, grazing on bad pasture and grazing on
good pasture. Apart from choosing intensity zero, there are basically
two (long-term) strategies an individual with cooperative intentions
could pursue: One strategy is to try to retain always one high quality
grazing area and leave the bad grazing area for further exploitation. In
this case, one would in most cases choose an intensity of two on the
bad area L2, and only occasionally one would graze on the good area
(hoping that not too many other people choose this area in the same
round to avoid degradation). The other strategy is to use the grazing
areas in a rotation system: One would let the bad area rest for two
rounds to recover and exploits the good area in this time. After the L2
area has recovered after two rounds, one exploits this area and lets the
other area (which presumably had been degraded in the meantime)
rest for two rounds. This leads to a rotation system, where in every
second round both grazing areas are of bad quality. The coordination
problem in this scenario arises from the fact that the subjects do not
know which strategy the other group members will aim for. But both
strategies can only be successful if all group members adhere to the
same strategy.
We will consider the first of these two strategies as more
cooperative in the sense that choosing the bad area signals a clear
intention that one wants to cooperate and values very highly the
existence and maintenance of one good grazing area. On the other
hand, choosing the good area (as in the rotation strategy) does not
send such a cooperation signal since a fully egoistic player would also
choose the good area. Of course, choosing an intensity of zero signals
an even higher willingness to cooperate.
Since the independent variables do not vary over the alternatives,
we use a multinomial logit regression model. Table 3 presents the
marginal effects for the three alternatives: Intensity zero (i.e. no
grazing), choosing the bad area, choosing the good area. Namibians
are significantly more likely to choose zero intensity and choose also
more frequently the bad area. On the other hand, they rarely choose
the good grazing area, compared to South Africans. These results
suggest that Namibians do not aim for a rotation system, as only a
fraction of 45% graze on the good pasture. Furthermore, if the majority
of Namibians applied a rotation system, we would expect the grazing
situation to be either L1L2 or L2L2 in the subsequent round. But we
observe the opposite: Namibian groups sustain one pasture in good
condition in 76% of all situations after having faced HL2 in the previous
round. Moreover, five out of twelve groups even conserve one good
area for the entire course of the game and consequently never face a
situation where both pastures are degraded. These patterns and the
high fraction of Namibians who abstain from grazing (31%) suggest
Please cite this article as: Prediger, S., et al., The impact of culture and ecology on cooperation in a common-pool resource experiment, Ecol.
Econ. (2010), doi:10.1016/j.ecolecon.2010.08.017
8
S. Prediger et al. / Ecological Economics xxx (2010) xxx–xxx
that Namibians rather aim for the strategy which ensures the
conservation of at least one area in good condition.12
In South Africa, on the other hand, the interpretation of the
behavioural patterns is ambiguous, as individual area choices suggest
a strong preference for either payoff maximization or the rotation
system. 75% of South Africans graze on the good pasture when facing
HL2 (63% of them with intensity two) and only 7% abstain from
grazing. However, there is only one group that successfully applied
the rotation system. All other groups failed: In 5 groups both pastures
were degraded until the end of the game after facing HL2. The other 6
groups achieved once again a situation where one of the grazing areas
was in good condition, but only after getting stuck in L1L2 or L2L2 for
on average 4.6 rounds. Hence, if the intention of the majority of South
Africans is to establish a rotation system, then this attempt failed
because the groups are not able to solve the coordination problem
which arises with the rotation system. A successful rotation system
requires that all group members graze on the good pasture and let the
bad pasture rest, so that the group faces the situation L1L2 in the
subsequent round. In that situation, which was the subsequent
outcome after HL2 in 55% of all cases in RSA, subjects can follow their
dominant strategy without risking recovery of one area since the
heterogeneity of the pastures should automatically coordinate their
actions. However, a substantial fraction of South Africans (18%) does
not use this contrivance of coordination when confronted with L1L2
subsequently after HL2, but graze on L1 and hence make recovery
impossible.13
The analysis of area choices under HL2 revealed two major results:
First, Namibians behave more cooperatively than South Africans, as
about one third of them choose intensity zero, which constitutes the
biggest individual sacrifice and is an unambiguous indication for
cooperative intentions. Second, Namibian groups are more successful
in solving the coordination problem. Most Namibian groups seem to
apply the strategy which aims at maintaining one pasture in good
condition. South African groups, on the other hand, rather aim for
short-run profit maximization or the rotation system. However, the
rotation strategy fails because a substantial fraction of individuals
grazes on the “wrong” area, either already in the situation HL2, or
latest in the situation L1L2. It might be that some subjects interpret the
behaviour of those who graze on the high quality area not as an
attempt to apply a rotation strategy, but rather as pure egoism (which
may indeed be the case). Thus, a problem of the rotation system in our
experimental set-up, where communication is prohibited, might be
that it does not unambiguously signal whether the group members
have cooperative or egoistic motives when choosing the high quality
area.
5. Discussion
Our study investigated subjects’ cooperativeness under various
resource scenarios which aimed to reflect real-life resource patterns
in a semi-arid study area. We found Namibian Nama to be
significantly more successful in managing common-pool resources
(CPR) than the South Africans: They were more cooperative and more
successful in coordinating their actions. In Section 2, we hypothesized
that a combination of different historical developments and higher
payoffs to cooperation in Namibia (stemming from the more fragile
ecological preconditions of the Nama Karoo) may explain the
significant country effect. In order to substantiate the theoretical
argument of our historical–ecological hypothesis, we draw on
12
The same seems to be true for farmers, who choose significantly more likely the
bad grazing area and less likely the good area (Table 3). Moreover, if we include an
interaction term between Namibia and farmer we observe that especially Namibian
farmers prefer to graze on the bad pasture.
13
In 22% of all cases South African groups faced the situation L2L2 immediately after
HL2. That situation is even worse as a contrivance of coordination does not exist.
Ostrom's (2007) framework for successful self-governance and
discuss alternative hypotheses first. In a second step, we relate the
results of our grazing experiments to prior experimental studies.
5.1. Alternative Hypotheses
Ostrom (2007) proposes a framework for successful self-governance
that considers (i) the resource system (e.g. fishery, grazing area), (ii) the
resource units generated by that system (e.g. fish, fodder), (iii) the users
of that system, and (iv) the governance system as main attributes. While
the resource system (pasture) and the resource unit (fodder for small
livestock) belong to ecological factors, the user characteristics and
governance system are influenced by societal and historical aspects.
Although we have made no rigorous assessment of all the 33 proposed
second tier variables, we argue, based on our knowledge of the study
region as well as on secondary data, that southern Namibia and
Namaqualand are more or less identical with respect to many of these
components. Ecological factors like the size of the resource system, the
lack of clear boundaries (no fences but agreed upon boundaries), similar
man-made infrastructure (collectively used water points), the economic
value of the livestock (same market access and similar prices), or the
growth rate of plants are very similar in both regions. Regarding the
governance system and user characteristics we find government and
non-government organisations with similar duties and frequency of
meetings, a comparable common property arrangement, a lack of
monitoring and sanctioning by the users or an external agency and little
experience with entrepreneurship in both regions. Moreover, farmers
use the same “technology” (extensive livestock keeping) for their
livestock production.
One important factor for effective self-governance is that users are
dependent on the CPR for a major portion of their livelihood and plan
to use the resources also in the future. Castillo et al. (this volume)
observe in the fishery games that Colombian and Thai fishermen
behave very similar to our subjects from South Africa. Discussions and
role games with the fishermen revealed that they assume others will
take as much as possible, so that they have no other choice than to fish
(to feed the family). However, there is no reason to assume that
Namibians are less dependent on the resource than South Africans,
and that they therefore had more time to wait and to cooperate in the
experiment. (In our sample, the fraction of subjects whose main cash
income source is farming is even higher in Namibia than in RSA.
Moreover, the fraction of permanent workers, i.e. those who are least
dependent on grazing, is almost the same in both samples) Thus, we
think that Namibians rely at least as much on farming as South
Africans.
Differences between the sites with respect to socio-demographic
characteristics or group composition cannot be the reason for the
huge country difference either, since we control for these in the
regression analyses. In addition, in contrast to most studies carried out
across diverse societies, we could avoid potential language, currency
and experimenter effects which can confound the results and which
have been recognized as the main problems for cross-cultural
comparisons (Roth et al., 1991).
5.2. Comparing the Results with Prior Experiments
The authors had carried out two other experiments: (i) a trust
game and a framed CPR experiment with the same population (Vollan,
2008) and (ii) an unpublished grazing experiment with a different
population. The unpublished grazing experiment was performed nine
months later in other communities to avoid the recruitment of
subjects who had heard about the previous grazing experiment.
The trust games revealed significant lower trust in Namaqualand:
Subjects from Namaqualand sent on average only 20% of their initial
endowment compared to 40% in Namibia. If trust is seen as an
important cooperation enhancing factor, then the results of our
Please cite this article as: Prediger, S., et al., The impact of culture and ecology on cooperation in a common-pool resource experiment, Ecol.
Econ. (2010), doi:10.1016/j.ecolecon.2010.08.017
S. Prediger et al. / Ecological Economics xxx (2010) xxx–xxx
grazing experiment are in line with those from the trust game. The
comparably low level of trust and cooperation among the Namaqualanders may be ascribed to the internal conflicts and the high
incidence of corruption reported in Section 2.1. However, if these
aspects and thus the historical context provided the only impact on
cooperation we should also have observed Namibians playing
significantly more cooperatively in the CPR experiment and the
follow-up grazing game, which were both framed as grazing
management tasks. But the CPR experiment showed no differences
in the open access scenario between the two countries (only in the
adoption of new rules),14 and in the follow-up grazing experiment,
where we eased the coordination problem (we basically changed the
threshold level from 4 to 5 units), the strong country effect was less
apparent. Although Namibians still applied significantly lower
average intensities there (1.14 compared to 1.28 in RSA,
t = 3.29***), both Namibians and South Africans had a good grazing
in 50% of all cases at round 10. This shows that South Africans are able
to coordinate once the threshold level is increased and thus the setup
is much easier (the coordination problem was much less serious
because it was now possible for all players to exert an intensity of 1
without causing a bad grazing situation). However, especially in
situations of resource scarcity, i.e. when both pastures were degraded
and coordination and strong cooperation was required, Namibians
played significantly more successfully and reached resource recovery
faster than South Africans. Thus it seems that the threat of long-term
resource degradation enhances cooperation among Namibians, while
it does not so among South Africans. The high degree of cooperation
and successful coordination among Namibians in situations with
threat of long-term resource scarcity, observed in both grazing
experiments, might be, at least partly, attributed to their specific
ecological knowledge on the fragility of the ecosystem, stemming
from clearer and better observable indicators of degradation in real
life (i.e. bare soil patches). In South Africa, on the other hand, there is a
lack of reliable indicators and the resource dynamics are less
predictable. These might also be features of fishing grounds and
could explain why Thai and Colombian fishermen in the fishery
experiment (Castillo et al., this volume) played similar to South
Africans in the grazing game, i.e. why they got stuck in situations of
resource scarcity. Similarly, this could explain why Vollan (2008) did
not observe a significant country difference in the CPR experiment,
where features of coordination, degradation and resource scarcity
were not incorporated. The influence of participants' specific
ecological knowledge on the fragility of the ecosystem, in particular
the threat of degradation (which is irreversible in real-life), may
matter more in experiments closely framed to real life and which
incorporate the features mentioned above, such as the grazing game.
5.3. Summary
The discussion reveals that (unfortunately) neither the results of
the presented experiment, nor those of previous experiments enable
us to strictly separate the effects of the historical from the ecological
background. Both aspects are captured in the dummy variable for
Namibia. One possibility to disentangle both aspects from each other
would be to conduct a series of experiments in two study sites within
the same district, i.e. where participants sharing the same cultural
background were affected by identical political respectively historical
context, but where the ecosystems are different with respect to
indicators for ecological changes (or vice versa). We leave this for
future research. Nevertheless we think that our study could highlight
some important factors that shape human behaviour.
14
In the CPR experiments, the introduction of a penalty rule led to a crowding out
effect of cooperative behaviour in Namibia compared to the open access situation
(Vollan, 2008). This can only occur when people have already reached a high degree of
morality.
9
Based on Ostrom's framework for successful self-governance, we
believe that the main differences in the attributes of the users and the
governance system are that Namibians have an autonomous management of their resources (including some freedom in designing
operational or collective choice rules whereas the government in RSA
dictates management plans) within a relatively stable population
with intact norms and social capital. These differences have been
derived from historical events and are features that have already been
mentioned as important factors for sustainable local level CPR
management by Ostrom (1990). The main difference in the attributes
of the resource units and the resource system is the lack of reliable and
easily observable indicators of ecological changes in the resource
system in South Africa. In Namibia, on the other hand, the increasing
occurrence of bare soil patches is a clear and easily observable
indicator of degradation for the resource users. This threat of
irreversible degradation can be an important cooperation enhancing
ecological factor in Namibia, because a degraded grazing area with
bare soil becomes useless for many years.
Acknowledgments
This research is part of the BIOTA Southern Africa Project and is
funded by the German Federal Ministry of Education and Research
(Commission number: 01 LC 0024A). We thank J.C. Cardenas, M.A.
Janssen and F. Bousquet, for providing the protocols of their fishery
game. This paper greatly benefited from helpful comments of M.
Anderies, G.W. Harrison, M. Janssen, M. Kirk, E. Ostrom, R. Slonim and
3 anonymous referees. We are also grateful to the comments of our
colleagues S. Gobien, S. Hanafy, D. Roth and S. Vaeth and participants
of the Workshop on Lab and Field Experiments on Diverse Social
Dilemmas, January 11–13, 2009 in Phoenix. Special acknowledgements go to our experimenter Richard S. Isaacks and to all participants
of the experiments for their time and hospitality.
Appendix A. Supplementary data
Supplementary data to this article can be found online at
doi:10.1016/j.ecolecon.2010.08.017.
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