1

Social Learning through Economic Games in the Field

Adriana Bernal (*)

Juan-Camilo Cárdenas (*)

Laia Domenech (**)

Ruth Meinzen-Dick (**)

Paula J. Sarmiento (*)

(*) Facultad de Economia - Universidad de Los Andes

(**) IFPRI, Washington

PLEASE DO NOT CITE WITHOUT PERMISSION

Abstract:

Economic experiments have traditionally been used as a tool for measuring human

behavior in different contexts of social interaction. However, little has been discussed so

far on the role of experiments as tools for learning and social change. We conducted a

series of educational interventions in two municipal aqueducts in Guasca, Colombia

using an irrigation collective action game where five people must decide over

contributions to produce water and on the allocation of the resource over an irrigation

system. We used this setting as a pedagogical tool for understanding the effects of

learning over a series of repetitions of these experiments to explore changes in the

behaviors and attitudes of rural households in the sample. We ran two waves of games a

few months apart with most of the same sample of 200 participants. In one of these

aqueducts we held workshops with the community to provide feedback on the results of

the games. In both waves of the experiments we find a powerful effect of face-to-face

communication to improve both group efficiency in the provision of water and fairness

in its distribution. A rotation scheme did not seem to have an important effect in these

two dimensions. Our results suggest that there are processes of learning from one wave

to the next that could provide valuable lessons about the possibilities and difficulties

that collective action faces within communities. In particular we find that the workshop

for discussing the results may have an effect on creating a better climate for the next

wave of games, particularly with respect to average contributions and fair allocation

across players. A combination of the experiments and the workshop increased

individual cooperation levels, while also inducing upstream players to restrain

themselves in extracting water, allowing players downstream to acquire more of the

resource.

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1. Introduction

Economic experiments have traditionally been used to understand the determinants of

human behavior. These were initially performed under controlled laboratory conditions,

frequently using computers and college students (Ostrom et al. 1994) but they are

increasingly performed in the field to test hypotheses under conditions closer to reality

(Cardenas, 2000; Cardenas and Ostrom, 2004; Werthmann et al. 2010). As a result of

their field experience, some authors started to call attention to the effect that some of

these field experiments may have on people’s attitudes and behavior (Cardenas and

Carpenter, 2005; Carter, 2008; Hill and Viceisza, 2012; Salcedo Du Bois 2014).

In common pool resource (CPR) experiments, players make decisions about the natural

resources they depend on, which makes them reflect on their everyday choices. Players

mainly have to decide whether to appropriate from a common-pool resource for their

direct private gains or let the common-pool resource generate an interest to the whole

group (Ostrom and Gardner, 1993). By playing several rounds of the same game, players

can see the results of their own actions. As a result, CPR experiments can help explain

difficult concepts about resource dynamics and depletion as well as raise awareness

about the benefits of community cooperation and sustainable natural resource

management. Ultimately, they can help change attitudes and practices.

Common pool resources (CPR) such as fisheries, groundwater basins, irrigation systems

or forests are used by many individuals. CPRs face two main dilemmas: the provision

dilemma involving the need for inputs such as labor or cash to manage and maintain the

shared natural resource and the allocation dilemma involving the distribution of the

resource among users (Ostrom and Gardner, 1993). In water management, common

dilemmas often involve asymmetric relationships or positions among participants

(Janssen, Anderies and Cardenas, 2011). In surface irrigation schemes and gravity-fed

water supply systems, head-enders and tail-enders often have a differentiated access to

water. Users may also have different influence in coordination and maintenance

decisions depending on their position in the system. In many rural areas, users

contribute their time or cash to build and maintain the system and agree on a series of

rules and regulations to ensure the sustainable use of the resource (Gleitsmann et al.

2007; Meinzen-Dick et al. 2002). In such a context, collective action can become

essential to ensure water provision, equitable water distribution and quality for all.

Collective action has proven successful in avoiding the tragedy of the commons and

ensuring long-lasting socio-ecological systems (Ostrom, 1990). However, sometimes

cooperation and coordination mechanisms do not emerge spontaneously or cannot be

sustained over time. In that case, external support might be needed to stimulate

collective action. Several natural resource programs, mostly led by NGOs, have tried to

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stimulate collective action by using participatory approaches, education and the

redesign of institutions (Bruns and Bruns, 2004). However, these approaches are not

always effective and create dependencies on external cooperation.

In this paper, we explore whether experimental games can provide an additional tool for

strengthening collective action, by examining changes in experimental behavior when

water users have the opportunity of participating again, months after, in a series of field

experimental games involving dilemmas of water provision and appropriation under

different institutional treatments. In particular we analyze how the dimensions of social

efficiency and fairness are affected when players have had a previous experience with

the game within the same context. Our analysis will provide lights into the discussion

about using games as a social learning platform.

In the next section we survey the rather scarce literature on experiments where the

participants have returned to the lab with more experience in the particular game they

are playing. We then proceed to explore the more general literature on learning

processes from games and repetition exercises with a summary through a simple

framework to suggest the potential positive effects of learning through games on socially

desirable outcomes. With these in mind in the following section we provide a quick

overview the field setting in which we implemented such strategy of repeating in two

different waves a set of experimental games for 200 villagers in two aqueducts. The

subsequent section describes the experimental design and the particular game we used,

followed by a description of the data patterns found from these experiments and an

analysis of the data. The paper concludes with lessons learned.

2. Economic experiments and learning: past experience

The hypothesis that CRP experiments can be used as a pedagogical tool to strengthen

collective action was partially explored for first time in Cardenas and Carpenter (2005).

As a result of many years of field experience with experimental games, the authors noted

that experiments provided participants with useful metaphors for their daily lives. They

analyzed the learning effect of experimental games in three villages of Colombia by

conducting two rounds of experiments, several months apart. One or two days after the

first experiments, a workshop was held in each community to discuss the strategies that

participants followed during the games as well as other relevant issues related to the

management of common pool resources. The role of the workshop in providing

cooperation mechanisms and promoting pro-social behavior was believed to be high.

The results suggested that both new and experienced participants cooperated more in

the second round, although Cardenas and Carpenter (2005) acknowledge that a more-

systematic follow-up approach was needed to obtain more conclusive results.

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Similarly, Salcedo Du Bois (2014) conducted a series of lab and field CPR experiments

with students and groundwater users in Mexico. The farmers that participated in the

games expressed their gratitude to the researchers for having explained in “simple

terms” the groundwater problems they face. The games also prompted a spontaneous

discussion about groundwater depletion and strategies to improve the management of

the resource. Due to these anecdotal observations, the author concludes that CPR

experiments can play an important pedagogical role in the field.

Economic experiments have also been used in the classroom with pedagogical goals. The

educational benefits of using experiments in the classroom are explored to some extent

in Ball et al. (2006), Dickie (2006), Ehrhardt (2008), Burguillo (2010) and Frank (1997).

Ball et al. (2006) assessed the effectiveness of using the Wireless Interactive Teaching

System (WITS) in economics classes. As part of the WITS activities, students played

standard economic games. Experimental class students obtained on average 3.2 points

more than control class students. The experiments had a greater impact on groups that

usually have more difficulties learning economics, such as women and freshmen. The

main explanation for these positive results was that students and teachers enjoyed the

experimental classes more and as a result, they were more engaged with the materials

and the discussions. Frank (1997) compared the results of a group of students who

participated in a simple classroom experiment about the use of common pool resources

with the results of a control group of students. The students participating in the

experiment obtained higher grades than the control students in a test about the “tragedy

of the commons”. In his study, Burguillo (2010) used game theory tournaments to

support competition-based learning (CnBL). The results of the study also suggest that

the combination of game theory with other learning techniques provides strong

motivation to students and increases learning performance.

Learning processes within the same game have also been a matter of study. Within the

non-cooperative game theory literature, several studies analyze how people learn to

play economic experiments when they play the game repeatedly (Erev and Roth, 1998;

Fudenberg and Levine, 1998; Camerer et al. 2001). In contrast, the learning mechanisms

in cooperative game theory have been less explored and thus, literature is scarce on the

topic. Two main theories try to describe players learning behavior. In reinforcement

learning, learning is guided by the payoffs obtained from the previous chosen strategy,

while in belief learning players choose their strategies based on what they believe

others are likely to do. Camerer and Ho (1999) argue that reinforcement and belief

learning are actually related because they are both special kinds of reinforcement rules.

Test-retest procedures can be useful to explore the learning effects of experimental

games. Test-retest reliability procedures involve repeating the exercise at different

times and measuring the variation of a particular observation under similar conditions.

They have been used in the past to establish the validity of stated preference surveys

and the stability of preferences in choice experiments and willingness to pay surveys

(Bliem et al. 2012; Mørkbak and Olsen, 2014; Czajkowski, 2014). Czajkowski (2014)

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asked the same questions about conservation measures in a Czech forest twice in the

initial survey and one more time six months after the first survey. Preferences did not

appear to be stable. The within-sample differences in preference estimates for

individuals were greater than the between sample differences which suggests that

people learned their true preference by repetition or that they became bored and made

random choices in the second round of questions. In contrast, Mørkbak and Olsen

(2014) found that preferences in a choice experiment remained stable for a marketed

good within a time lag of two weeks, even when economic incentives were given.

With respect to learning and experience in experimental games that involve social

dilemmas, there is a track of studies where researchers compared the behavior of

inexperienced to experienced subjects in laboratory settings. Many of these studies are

based on competitive markets (Smith et.al 1998; Dufwenberg et.al, 2005; Hussam et.al.

2008). A branch of this research has focused on exploring whether experienced subjects

would be able to reduce the risks and likelihoods of bubbles and crashes in financial

markets, with still controversy and a lack of consensus. List (2004) also explored to

what extent experienced vs inexperienced subjects differ in terms of confirming the

neoclassical predictions of behavior to what prospect theory has as an alternative,

arguing that an intense market experience would make individuals approach the

neoclassical prediction better.

Closer to our question, lab experiments on voluntary public goods provision have

reported that experienced subjects tend to show lower levels of contributions compared

to first-time participants (Ledyard 1995). Zelmer (2003) confirms this result in her

meta-analysis from a large sample of public goods games in the laboratory literature.

Unfortunately, the experimental literature on this particular subject is rather silent

when it comes to bringing the lab to the field. Most likely because of the logistic costs to

recruit participants in the field, there are no studies that systematically explore what

happens when “experienced” subjects make decisions again in a context of social

dilemmas such as common-pool resources or public goods provision1.

3. Framework: The pedagogical power of games

The scarce literature on the analysis of behavior in a field-lab controlled economic

experiment where the participants return to the same game led us to explore from other

perspectives what can we learn from the more general literature on learning,

particularly when it comes to learning through games.

There are numerous learning theories and different definitions of learning in the

literature, some focusing on individual and some focusing on group learning (Armitage

1 An exception is reported in Carpenter and Cardenas (2005)

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et al. 2008; Keen and Mahanty, 2006). We will adopt here the definition of Knowles,

Holton and Swanson (2012) which defines learning as “the act or process by which

behavioral change, knowledge, skills, and attitudes are acquired”. According to Keen and

Mahanty (2006) effective learning should be iterative, reflective, and contextual, and

combine direct experience and abstract conceptualization following a learning circle.

Games can stimulate problem-solving skills and generation of new knowledge, especially

when they are engaging and interactive (Shute et al. 2011). Shute et al. (2011) describes

the main features of a good educational game: i) there is a problem to be solved which

may create conflict or challenge; ii) rules are established; iii) goals or outcomes are to be

achieved; iv) implicit or explicit feedback is provided; v) interaction with the

environment is sought and vi) a storyline is provided. Field experiments can provide all

these elements for a relevant learning experience, especially when communication

among the players is allowed and when a debriefing at the end of the session is

provided.

Contemporary learning theory argues that people primarily learn through direct

experience of the consequences of their own actions (Bandura, 1971). In cooperative

game theory a small number of players need to make cooperation and competition

decisions both independently and collectively. Games are also sometimes embedded in a

relevant socioecological context (framing) which can help reproduce real life situations

and make players think about their everyday decisions and the consequences of such

decisions. CPR experiments generally consist of several rounds where similar decisions

need to be made. Accordingly, players can change their behavior depending on their

experience in the previous round of the game. Thus, experimental games can become a

good platform to learn through direct experience and interaction.

Most of the recent literature about games and learning is about the use of digital or

computer games for learning, which goes hand in hand with the success of the

gamification phenomenon. Kapp (2012) defines gamification as “using game-based

mechanics, aesthetics and game thinking to engage people, motivate action, promote

learning, and solve problems”. Deterding (2011) adds that gamification involves using

game design elements in non-game contexts including educational and learning

contexts, and marketing and business contexts. Typical examples of gamification are the

accumulation of flyer miles to redeem prizes and the summer library reading programs

(Nicholson, 2012).

A review study about the effects of gamification concluded that the majority of 24

reviewed studies reported positive effects and benefits of gamification, but some of the

studies concluded that the positive effects of gamification may not be long-term, and

instead they could be attributed to a novelty effect (Hamari et al. 2014).

According to the conceptualization presented by Hamari et al. (2014), gamification can

be seen to have three main parts: 1) motivational affordance 2) the resulting

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psychological outcomes, and 3) the further behavioral outcomes. These three elements

can also be useful to analyze the learning effects of CPR experiments (Figuree 1). The

extrinsic (private) motivational affordance would be the accumulation of the maximum

number of tokens to be later exchanged for monetary incentives. Competition between

players arises in that case and if no one cooperates a Nash equilibrium that leads to the

tragedy of the commons occurs. However, profit maximization is rarely the only

motivation (Anderies et al. 2011). The intrinsic (public) motivational affordance

involves the contribution for the sustainable maintenance of a public or common good

that benefits all. In that case, cooperation between players arises and if everybody fully

cooperates, players can achieve the social optimum, with higher material rewards than if

everyone followed the selfish strategy in the game. Through this experience, players

may change their mental models or psychological outcomes as well as their attitudes

which may result in further behavioral changes in relation to natural resource

management. Some catalysts (such as new rules introduced in the game) may also help

in this learning process.

Figure 1. Learning effects of CPR experimental games

Source: adapted from Hamari et al. (2014)

When all these changes take place at the group level, social learning processes may

emerge. Social learning is a group process that involves the joint development of shared

meanings and values which are all essential for creating joint action or collective action

(Pahl-Wostl et al. 2007). In other words, social learning implies learning together to

manage together (Ridder et al. 2005). A series of capacities that need to be created

among actors to build up social learning for resource management are described in Pahl-

Wostl and Hare (2004) and include: shared problem identification; awareness of each

other’s goals and perspectives; understanding of the actors’ interdependence;

understanding of the complexity of the management system; learning to work together;

trust; the creation of informal as well as formal relationships.” A priori, experimental

SOCIAL LEARNING

PSYCHOLOGICAL

OUTCOMES

BEHAVIORAL

OUTCOMES

MOTIVATIONAL

AFFORDANCE

Competition Cooperation

experie

nce

COLLECTIVE

ACTION

Catalysts

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games have the basic elements to support the development of all these capabilities.

Given the reported pedagogical power of games and interactive decision-making

platforms educators and psychologists are increasingly looking at this as relevant tools

to promote changes in mental models and social practices. However, according to Van

Eck (2008) there is lack of good research on games and learning. Repeating the games

with the same players after a short period of time may allow studying more in detail the

learning processes associated with gamification. Drawing on a field experiment in the

rural areas of Colombia, we will test whether CPR games can be a good platform to

influence the dynamics of social learning for water resources management.

Within our research project we envision two levels in the learning process. One where

we study the impact of experience in the field-lab game and have the opportunity of

playing again under the same circumstances. The other when we evaluate whether such

participation in the games changes the attitudes and behavior, outside of the field-lab, in

their daily lives with respect to water use and conservation. This paper focuses on the

first as data for the second level is still in the making.

In this first level we explore how participants behave when first encountering the social

dilemma of our game that involves getting a group of individuals to contribute to a

common-pool that produces water, and then decide how to allocate such resource

among themselves. We then evaluate if these same people behave differently in a second

wave of the same games, months later.

4. The Guasca setting

The site for our field work is the rural surrounding of Guasca, a town about two hours

north-east from Bogotá, the capitol of Colombia. This is an important agricultural town

from the Cundinamarca Department, producing cut-flowers to export, as well as milk,

strawberries, potatoes and carrots for the domestic market. This town has increasingly

seen an interest by developers in expanding the offer of high end housing projects for

families from Bogota. With rising water demand, the collective action processes for the

conservation of the watershed that supply this resource for the aqueducts and

agricultural irrigation become even more critical.

Political division in Guasca is based on urban and rural areas. The town’s total area is

346 km2, of which 8.8 km2 (2.54% of total area) represents urban areas, formed by 8

neighborhoods. The rural area is defined by 14 rural districts or “veredas”. In terms of

water management this urban/rural division remains, with an urban aqueduct that

provides water for all 8 neighborhoods, while a total of 22 rural aqueducts are

distributed among the 14 rural districts.

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The urban aqueduct provides 100% coverage for the urban area of Guasca, with

approximately 1.500 users. This aqueduct takes water from two different sources and

later treats it in a treatment plant owned by the company.Each rural aqueduct provides

water for 1 to 4 different rural districts. Small rural aqueducts cover less than 20

households from the same rural district, with no water treatment. Large rural aqueducts

cover more than 200 households from different rural districts and provide some water

treatment, ranging from only filtration and sedimentation treatments to the inclusion of

a chemical treatment.

No irrigation districts have been established in Guasca, and while some ditches exist in

each rural district, large drought periods and waste water practices from the users in the

upper side of each ditch make difficult the use of these ditches for agricultural purposes.

As a result, most households are familiar with the challenges associated to having a

vertical flow of water in watersheds. Taking water from the aqueducts to supply

irrigation is also a common practice, even though in many cases this practice is illegal.

Two rural aqueducts with similar socioeconomic and environmental conditions were

selected for our analysis: Mariano Ospina and Pastor Ospina y Flores. Both take their

water sources from the same area in the upper watershed and distribute to a similar size

area and number of water users, offering a sufficient number of participants in each

location.

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Figure 2. Guasca map

5. Our experimental design: The water irrigation game.

Based on Cardenas et.al. (2011) and Janssen et.al. (2012), we implemented an irrigation

game where five players (A,B,C,D,E) make two decisions for the provision and

appropriation, respectively, of water resources. From an initial endowment of 10 tokens,

each player must decide simultaneously how many of her tokens to keep for a private

profit, and how many to invest in a fund that produces water for the group.

0: Centro Urbano

1: Santuario

2: Flores

3: Santa Ba rbara

4: Pastor Ospina

5: Floresta

6: San Jose 7: San Isidro

8: Mariano Ospina

9: Santa Lucí a

10: El Salitre 11: Santa Isabel de Potosí 12: La Trinidad

13: Santa Ana

14: Concepcio n

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Figure 3. Water production function and allocation along the irrigation system

The water produced will be later extracted by the five players for a profit as well. Figure

2., bottom panel, shows the production function of water from investment. At least 6

tokens must be invested by the group to obtain a positive amount of water. The

maximum amount of water for the group (100 units) can be obtained if the group

invests between 46-50 tokens. However, tokens kept privately by the players can be

exchanged for money as well. Once the decisions to invest, made simultaneously, are

collected, the experimenter announces the total investment and therefore the amount of

water produced for the group. The experimenter will then proceed to player A in the

sequence (See Figure 2, top panel) and asks her to decide how much of the available

water she wants to keep for her own gain and how much water to leave for the rest of

players downstream. With the available water after player A, the experimenter goes to

player B and asks the same question, which will in turn define the water available for C

and so on. All contributions and extraction decisions were to be kept private during and

after the conclusion of the experimental session and kept confidential by the

experimenter.

At the end of the round each player´s earnings would be composed of the tokens kept

(not invested in the group fund) plus the water tokens extracted. Both tokens kept and

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tokens extracted were converted to cash earnings that were paid in private and

confidentially at the end of each session. The average earnings for these participants

were around $15 USD. Each session took around 3 hours from each participant between

registration, instructions, experiment, payments and exit survey. This amount of cash

would more than compensate the opportunity cost of time for these villagers as average

minimum wage was $13 USD per day.

We invited five neighbors from the same aqueduct to participate in an entire session

made of 15 rounds in the following sequence:

Stage 1 (rounds 1-5): Players randomly assigned to positions in the ABCDE

sequence. They keep these same positions over the five rounds.

Stage 2 (rounds 6-10): Players randomly reassigned to new positions in the

ABCDE sequence for round 6 and then rotate through the rest of the positions

over rounds 7-10 in a sequential manner (e.g. a player in position C in round 6

will move to position D in round 7, then to position E (t=8), then A(t=9), then

B(t=10).

Stage 3 (rounds 11-15): Players randomly reassigned to new positions in the

ABCDE sequence. They keep these same positions over the rounds 11 to 15, but

in each round are allowed to have a face-to-face conversation regarding any

aspect of the game.

We visited the two aqueducts and invited as many as possible to participate by signing

up to different possible dates and times in groups of five. We randomly selected 100

participants (one per household) from each aqueduct, for a total of 200 participants for

the experimental games, in 40 sessions in the first wave of the study, conducted between

September and December of 2013. The two selected aqueducts were randomly assigned

to a games-only treatment in Mariano Ospina and a games+workshop treatment in Pstor

Ospina y Flores (table 1). In the latter, after concluding all 20 sessions for that aqueduct

we invited their members to participate in a workshop where the results of the games

were presented and discussed with the community to test whether workshops with

communities facilitate individual understanding of the game and raising awareness

about water conservation and cooperation. We also ran an individual survey for all

particpants to collect data on socioeconomic characteristics, the actual status and

changes in water supply, the effect and perception on climate variation, water use

practices, collective action perception on each community.

Table 1. Experimental design

Rural Aqueducts Treatment Description # participants

Aqueduct Pastor Ospina y Flores

Treatment-1 Surveys + Economic games + Workshop

100

Aqueduct Mariano Ospina Treatment-2 Surveys + Economic games 100

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Data collection of experiments, attitudes and behavior regarding water was divided in

two stages. During the first stage, September to December 2013, we ran 300 surveys, 40

experimental sessions and 1 workshop2. In he second stage, January to May 2014, we

ran another 40 experimental sessions, 1 workshop and 287 more surveys. As indicated

in Table 2, 85% of these were repeat participants who had experience with this same

game from the first wave. However, the group compositions changed as the recruitment

process would involve assigning people to times and dates that did not match the same

as the other people in their group in the previous wave.

Table 2. Experimental sample

Rural Aqueducts

1st Stage 2nd Stage % Repeating

Parti-cipants

Sur-veys

Ses-sions

Work-shops

Sur-veys

Ses-sions

Work-shops

Pastor Ospina y Flores 100 20 1 100 20 1 85% Mariano Ospina 100 20 0 100 20 0 87% Total 200 40 1 200 40 1 86%

Table 3. Socioeconomic features of the participants

Games only (Mariano Ospina)

Games + workshop (Pastor Ospina)

Primary education completed (%) 43.0 43.0 Female (%) 68.5 69.0 Age (years) 44.2 39.4 Years in community 25.0 30.6 Household members 4.1 4.3 Average income less than COP 800 00 (%) 61.5 62.6 Crop irrigation 6.5 12 Livestock trough 59.0 59.5

6. Data patterns and statistical tests:

In this section we will describe the patterns of the data from the experiments and

explore questions regarding the effect of the positions (ABCDE) on individual behavior;

the effects of the three treatments within a session (fixed position, rotation, group

communication), and the observed change between the first and second wave in terms

of the social and individual learning. We also compare the behavior and outcomes

between the control aqueduct where we ran the games only and the treatment aqueduct

2 The rural aqueduct Santa Barbara in the same town was randomly selected as a control group where no economic games were conducted, but we collected survey data from 100 more households. Because those surveyed households did not participate in the experiments, they are excluded from this paper

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where we had workshops after the games were conducted. We show the overall patterns

and effects of different treatments and waves, complemented with multivariate

regression analysis.

Overall, behavior is quite similar to the reported data with this particular experimental

game (Janssen et.al 2012; Cardenas et.al. 2011). Players contributed about half of their

endowment to the public fund that produces water, with no major difference between

upstream and downstream players. Regarding the allocation of water, we continue to

find that unequal allocation between those upstream capturing most of the water and

those downstream receiving a much lower fraction of the water produced for the group,

even to the point that at some point the last player E fails to recover back his investment.

Also consistent with previous studies using this game, face-to-face communication

achieves two main goals, increase the level of contributions to the level that more water

is produced for the group, and to improve the distribution of the resource so that those

downstream receive more water, increasing their earnings, although the inequality of

those upstream capturing more earnings remains.

Before we discuss the differences between the two waves, let us first describe in more

detail what happened within each wave and across the three stages (fixed location,

rotation, communication) during the 15 rounds of the game. The average contribution

during both waves in the first stage (rounds 1-5) was 5 units; in the second rotation

stage (rounds 6-10) 4.8 units; and in the communication stage (rounds 11-15), 6.9 units.

This is 50%, 48% and 69% of players’ endowment, respectively. Figure 1 clearly shows

the important increase in social efficiency when communication is allowed: average

earnings per person for the last stage increases from 16 units per round per player in

stages one and two to 20 units per round per player in the third communication stage

(Mann-Whitney two-sample test n1=4000, n2=2000, p-value=0.000). These general

patterns are observed in both waves, although the difference between the first and

second stage is more perceptible, as discussed further below. Although contributions

were similar in the first two stages, on average players contributed less in the second

stage rotation rule, which contradicts our initial expectation that experiencing the

different positions in the sequence for extracting water could improve the efficiency at

the group level.

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Figure 4: Average contributions to the public fund

These averages mask the fact that players are located asymmetrically in the watershed

or irrigation system, so their incentives to invest in the public fund are different. The

higher the position of the player in the irrigation system, the higher is the chance to

enjoy returns to his investment. In fact there is substantial inequality of extractions

across participants upstream and downstream, even though downstream participants D

and E contributed on average 50% of their endowment, while upstream participants A

and B contributed just a bit more, 60% of their endowment, as shown in Figure 5. During

the first stage (rounds 1-5) the average appropriation of player A was more than 7 times

than that number for player E illustrating the inequalities generated in this first stage. In

87 of the 200 total rounds in the first stage, players in position E did not extract all the

water left to them, despite being the last players in the watershed. In other words, they

left money on the table which extrapolated to their everyday life could mean that they

kept in mind the importance of the environmental services water provides and the

needs of other users downstream. In the whole game, this behavior happened in 229

rounds out of 600—38% of all rounds in all the games.

01

23

45

67

89

10

Un

its c

ontr

ibute

d

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Round

Data for both aqueducts and waves

Average contributed units to the public fund

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Figure 5. Average contributions and extraction by position (Rounds 1-5)

To further explore the distribution problem, we analyze whether the level of fairness in

the behavior of Player A in round t would affect the subsequent decisions to invest in the

group by players BCDE in round t+1. If the participant located on position A took 20%

(1/5) or less of the common resource in round t=1 -which for us means that A is a fair

player- then the average contributions from all players but A in rounds 2 to 10 is 5.3

units. That average falls to 4.5 units if the share extracted by A is 50% or more (Mann-

Whitney two-sample test n1=252, n2=1008, p-value=0.000), confirming the importance

of behavior by player A in triggering strategies of reciprocal contributions. When

participant A is unfair in round 1, as just defined, the equity in water distribution

measured as the average extraction slope3 over the watershed almost doubled in value

compared to when the participant A took 20% or less of the available water in the first

round. This suggests a retaliation process in the rest of the game due to an unfair share

appropriated by participant A at the beginning of the round (Figure 6).

3 This slope (see Figure 5) describes how unequal is extraction among the five players. A perfectly fair extraction would have a horizontal line. The steeper the slope the more unequal is extraction.

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r E

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A B C D E

Average contribution Average extraction

Data for both aqueducts and waves in rounds 1-5.

Contribution and Extraction

17

Figure 6: Average contribution from players located in positions B, C, D, and E by

fiarness of player A in round 1

Accordingly, the unevenly water distribution leads to lower contributions of the less

favored participants in the water allocation. Whereas extraction diminishes

monotonically as the position lowers in the irrigation system, the same apply to

contributions over the watershed (Figure 5). Recall that although these locations are

assigned randomly, they do not remain unchanged during the game (see experimental

design).

Effect of the stages: fixed sequence, rotation, and face-to-face communication

Average contributions in the second stage (rotation rule) decrease in relation to the first

stage (fixed sequence), from 5 units to 4.8 units (Mann-Whitney two-sample test

n1=2000, n2=2000, p-value=0.040). In comparison to the first stage, players located in B,

C and D positions contributed less in the second stage while player A contributed more.

Likewise, extraction levels decrease for all participants, except for players located on A,

who increase appropriation in the second stage. On the other hand, as previously

mentioned, during the communication rounds there is an increase in the provision and

appropriation levels of all players. The higher appropriation levels are triggered in part

by the higher levels of contribution experienced during those rounds.

In the first stage the participant located farthest downstream (E), contributes on

average more to the public fund than he later extracts from the common resource

(average contribution=4, average extraction=3.2). The same happens during the rotation

stage, but player E’s average extraction drops is even lower (2.4). Hence, upstream

players take advantage of their location and proportionally extract more water than

player E downstream. However, during the communication stage a redistributive

transfer occurs that improves the earnings of player E. During this stage inequalities still

remain but in lower degree.

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Fair A Unfair A

Data for both aqueduct and waves, rounds 2-10 and players not locatedin position A on watershed. Fainess is defined as: if player A took 20%or less from the public fund in round 1, is a fair play. On the contrary, ifhe or she takes 50% or more, is un unfair play

Average contribution from players located on B, C, D and Eby fairness of player A in round 1

18

We constructed an extraction level slope indicator in order to analyze water distribution

patterns in the watershed, calculated as the coefficient estimated from a regression

where the dependent variable is the appropriation level and the only independent

variable is the location on watershed. As expected, the lowest inequality levels are found

in the communication stage. In contrast, the highest inequality levels are found in the

rotation stage.

Figure 7 and 8

We conducted a regression analysis to explore the effect of the different stages and the

experimental location in the provision and appropriation decisions of this asymmetric

common-pool resource game. We controlled for experimental conditions, contextual and

individual characteristics. Provision decisions are measured as the percentage of

individual endowment of 10 units contributed to the production of water, while

appropriation decisions are measured with the indicator fair extraction. This indicator

is defined in equation 1.

(1) 𝐹𝑎𝑖𝑟 𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛𝑖𝑡 =𝑊𝑎𝑡𝑒𝑟 𝑟𝑒𝑐𝑒𝑖𝑣𝑒𝑑𝑖𝑡

𝑁− 𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛𝑖𝑡

(2) 𝐹𝑎𝑖𝑟 𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛 𝑝𝑒𝑟𝑐𝑒𝑛𝑡𝑎𝑔𝑒 𝑝𝑖𝑡 = −𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛𝑖𝑡

𝐹𝑎𝑖𝑟 𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛𝑖𝑡∗ 100

Where N is the number of players who still need to receive water downstream, including

the player taking the decision. For example, for player A, N=5; for player C,N=3. The

subscript 𝑖𝑡 refers to the decision of player 𝑖 in round 𝑡. Another indicator of equity is the

percentage of water extracted as a fraction of what an equal share of the remaining

water would be for that player and those downstream, as shown in equation (2).

We run a fixed-effects model with robust standard errors, where the fixed effects

captured each of the particular 98 groups of five participants. We included socio-

demographic controls such as gender, age, education level, household size and some

dummies such as having a drinking trough and crop irrigation to account for the

heterogeneity of the participants. We also included indicators of community dynamics

such us the number of neighbors stored in the participants cell phone’s memory. As the

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Un

its c

ontr

ibute

d

A B C D E

Base line Rotation rule Comunication rule

Data for both aqueducts and waves

Average contribution by ruleand position on watershed

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15

20

25

30

Wa

ter

Extr

acte

d

A B C D E

Base line Rotation rule Comunication rule

Data for both aqueducts and waves

Average extraction by ruleand position on watershed

19

location for each player changed during the game, we run separate regressions

according to the location assigned randomly in rounds 1 to 5, and then we control for

the change in positions in the second stage. Table 1 and 2 present the regression results

for both provision and appropriation decisions, respectively.

Table 3. Regression results for individual-level data analysis for contribution percentages, relative contribution to the total contributed by the group, share extracted, fair extraction and extraction proportional to contribution. Standard deviations are shown between brackets.

(1) (2) (3) (4) (5) (6) VARIABLES Contribution

percentage Relative

contribution (to group)

Share extracted

Fair extraction

Fair extraction percentage

Extraction proportional

to contribution

Lagged gini4 in contributions

-0.0049 0.1156 -9.6365 -1.0320* -0.1566 (0.0082) (0.0388) (3.5414) (0.1398) (0.5488)

Lagged gini in extractions

-0.0036** 0.1110 -3.0690 -0.5645 -0.3813 (0.0002) (0.0709) (5.1484) (0.3378) (0.1453)

Wave 0.0669*** -0.0086 -0.2201 4.4190 0.8919 0.6038 (0.0007) (0.0055) (0.0373) (1.8727) (0.1490) (0.7334)

Treatment 0.0316 -0.0068 -0.125** 1.9055 0.5144** 0.2923 (0.0503) (0.0099) (0.0054) (0.6178) (0.0395) (0.5042)

(Treatment X Wave)

-0.1728 0.0224 0.4821** -4.096*** -2.1059** -2.7964 (0.0436) (0.0098) (0.0260) (0.0228) (0.0442) (0.9771)

Workshop -0.0439** -0.0181** 0.0123 -0.5766 -0.0001 0.6325 (0.0010) (0.0009) (0.0025) (1.0486) (0.0463) (0.1496)

Round -0.0045 -0.0001 0.0068 0.0450 -0.0325 0.0137 (0.0007) (0.0001) (0.0049) (0.1508) (0.0139) (0.0417)

Stage 2 0.0116 -0.0010 0.0355 -1.8431 -0.1230 0.2832*** (0.0259) (0.0094) (0.0479) (0.8087) (0.1120) (0.0031)

Stage 3 0.1870* -0.0008 -0.0978 1.7812 0.6083* -1.5228 (0.0260) (0.0145) (0.0759) (0.8668) (0.0808) (0.4652)

Treatment * Stage 2

0.0041*** -0.0035*** 0.0107 -0.0426 -0.0173 0.0873 (0.0000) (0.0000) (0.0041) (0.0989) (0.0154) (0.0207)

Treatment * Stage 3

0.1098*** -0.0012 -0.048** 2.0541*** 0.2073* 0.0944 (0.0003) (0.0003) (0.0021) (0.0018) (0.0181) (0.0328)

Location in watershed

-0.0301*** -0.0159** 0.1050 3.0938* 0.2933* -1.0832* (0.0000) (0.0005) (0.0181) (0.4205) (0.0369) (0.1410)

Stage 2 * Location on watershed

-0.0032 0.0012 -0.0154 0.5475* 0.0599* -0.1365 (0.0074) (0.0029) (0.0070) (0.0623) (0.0081) (0.0741)

Stage 3 * Location on watershed

-0.0052 0.0010 0.0238 -0.5800 -0.1056 0.4270** (0.0111) (0.0049) (0.0087) (0.3202) (0.0205) (0.0313)

Initial resource -0.0016** -0.0571

4 A gini coefficient measures inequality in the distribution of a variable among the number of individuals, and ranges from 0 to 1. In our analysis we estimate the gini coefficient for the group of five players in terms of contributions, and of extraction. . A larger gini indicates greater inequality.

20

(0.0001) (0.0101) Relative contribution

-0.0542 -2.1224 (0.0757) (2.1756)

Constant 0.9679* 0.4795** 0.5096** -9.3315 -2.8675** 0.2435 (0.1026) (0.0321) (0.0091) (3.9961) (0.0622) (4.3307)

Observations 5,700 5,320 4,562 4,562 4,562 5,084 R-squared 0.2953 0.1426 0.3925 0.2505 0.4138 0.1739 Session fixed effects and errors clustered by aqueduct

YES YES YES YES YES YES

Socioeconomic and community controls

YES YES YES YES YES YES

Notes: Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

We observe the powerful effect of face-to-face communication, increasing contributions

in the provision stage and increasing extraction levels in the appropriation stage, in all

locations. However, the effectiveness of communication highly depends on the treatment

group (aqueduct), as discussed below. Players located downstream benefit most from

the communication rule, as face-to-face communication is seen to improve equity (see

appendix). In the rotation stage, an important determinant of fair extraction is the

players’ location in the watershed. As expected, players downstream extract less.

Comparing the two aqueducts

There were significant differences in behavior between the two aqueducts during the

first wave. Mariano Ospina (control) players contributed more in the first ten rounds but

the water produced was more unevenly distributed than in Pastor Ospina (workshop

treatment). However, in the last five rounds face-to-face communication seems to be

more effective in Pastor Ospina since the average contribution increased from 4.59 to

7.1 units compared to 5.1 to 6.2 units in Mariano Ospina. The extraction slope in Pastor

Ospina decreased from 4.8 in the first ten rounds to 3.6 in the communication rounds,

while in Mariano Ospina this indicator only falls by 0.5 units. Table 3 shows how the

communication rule in Pastor Ospina increases significantly provision levels and

fairness in extraction, in comparison to Mariano Ospina. In the first wave, the share

extracted was significantly lower in Pastor Ospina while the fair extraction percentage

was higher.

In the second wave, players’ behavior changed in the two aqueducts. In the control

group that did not receive a workshop; contributions to the public fund decreased in

relation to the first wave (Figure 9). By contrast, in Pastor Ospina where a workshop

was conducted after the first wave games, the average contribution increased in

21

comparison to the first wave and was higher than in the control group during the three

stages. In addition, equity in the extraction distribution -measured with the extraction

slope indicator- improved in Pastor Ospina, but worsened in Mariano Ospina.

Figures 9 and 10

We also used the gini coefficient5 in contributions and extrations calculated by round

and group as an additional measure of equity. We observed important differences

between aqueducts within waves. During the first ten rounds of wave 1 the gini in

contributions shows higher equity in Mariano Ospina, but in the last five rounds where

face-to-face communication was allowed, the indicator fell more in Pastor Ospina. In

other words, face-to-face communication was more effective in Pastor Ospina.In Pastor

Ospina the distribution of contributions during the first ten rounds was worse than in

Mariano Ospina and therefore, it was more feasible to improve the distribution of

investments in the water fund through communication. Furthermore, in wave 2 the

equity of contributions in the second wave is always better in Pastor Ospina (Figure 11).

A similar pattern is observed for the gini coefficient of group extractions in each round.

In the first ten rounds of wave 1 the distribution indicator is similar for both aqueducts,

but during the communication stage the extraction distribution improves much more in

Pastor Ospina. In the second wave, the extraction distribution remains more unequal

during the whole game in Mariano Ospina. This suggests that face-to-face

communication was more effective in Pastor Ospina. In wave 2, players’ behavior

changed in a different way in each aqueduct. In the group that received the workshop

the gini coefficient of group extraction reflects more fairness, while in the other group it

reflects more inequity, suggesting that the workshop may have had a positive effect in

the fairness behavior in game, but the games alone may have triggered unfair behavior

(Figure 12).

5 The gini index is a distribution measure widely used in economics to evaluate the distribution of income or consumption among individuals or households. A gini index equal to 1 represents perfect inequality and a gini index equal to 0 represent perfect equality. Thus, lower values are interpreted as a more equitable distribution and upper values are interpreted as a more unequal distribution.

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wave 1 wave 2

Mariano Ospina Pastor ospina

Data for rounds 1-10

Average contribution by aqueduct and waves

0.1

.2.3

.4.5

.6.7

.8.9

1

Wave 1 Wave 2

Mariano Ospina Pastor ospina

Data for rounds 1-10

Average percentage of extraction from the totalleft to each player

22

Figure 11 and 12. Gini coefficients over time for contributions and extraction levels for

both waves (ola 1 and ola 2).

We hypothesize that the differences mentioned above are attributable to the workshop

conducted in Pastor Ospina and Flores., but it is hard to disentangle the effects of the

workshop from pre-existing conditions or features that differ in each aqueduct since the

beginning. In fact, we find a negative effect of the workshop in individual provision

levels and provision levels relative to group (Table 3). Below we investigate these

differences between aqueducts and within waves in more detail.

The effect of returning (wave 1 vs wave 2): “experienced” vs “non-experienced”

players.

As described previously, we returned to the same communities a few months after the

first wave to repeat the games. We will try to answer the following question: did people

learn something during the games that made them play differently? Or did the feedback

make the difference in the learning? Game data show that people played differently in

the second wave. However, these changes depend on the aqueduct and on each of the

games stages.

Between waves 1 and 2, the contribution level increased in the second and third stages

of the game, but in rounds 1 to 5 it remained unchanged. On average, contributions to

the public fund within waves increased a small amount, from 5.5 to 5.7 units (Mann-

Whitney two-sample test n1=3000, n2=3000, p-value=0.022). All players except for

player D increased their contributions in the second wave (Figure 13), but average

extraction remained unchanged within waves. This was due to changes in different

directions depending on the player position in the watershed. Water extraction

increases in every position but in A, and decreases significantly in position A (Figure 14).

These changes in the way water is distributed lead to an improvement in the equity

indicators. The extraction slope went from 5.59 to 4.46 and the gini in extraction from

0.46 to 0.41.

0.1

.2.3

.4.5

.6.7

.8.9

1

Avera

ge g

ini o

n c

ontr

ibution

s b

y r

oun

d b

y g

roup

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Round

ola 1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Round

ola 2

Average gini on contributions by round by group

Mariano Ospina Pastor ospina

0.1

.2.3

.4.5

.6.7

.8.9

1

Avera

ge g

ini o

n e

xtr

actio

ns b

y r

ou

nd

by g

rou

p

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Round

ola 1

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Round

ola 2

Average gini on extractions by round by group

Mariano Ospina Pastor ospina

23

Figures 13 and 14

In wave 1 during the rotation stage, we found no differences in relation to base line

(rounds 1-5), but in wave 2 we found a significant negative effect in terms of equity (a

higher extraction slope). To explore group efficiency and equity behaviors, we

conducted some additional regressions but this time we used group variables. As an

efficiency indicator we used total group contributions and as equity indicator we used

the gini coefficient for group contributions and extractions and the extraction slope

along the watershed. As before, we ran robust standard errors and included socio-

demographic, socio-economic and community dynamics controls.

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wave 1 wave 2

Data for both aqueducts in rounds 1-15.

Contribution

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wave 1 wave 2

Data for both aqueducts in rounds 1-15.

Extraction

24

Table 5. Regression results for group-level data analysis of group contribution and group extraction distribution, and gini indicators. Standard deviations are shown between brackets.

(1) (2) (3) (4)

VARIABLES Total group contribution

Gini in contributions

Extraction slope (absolute value)

Gini in extractions

Lagged gini in contributions

-31.590** 0.428* 12.725** 0.209** (1.828) (0.053) (0.351) (0.008)

Lagged extraction slope 0.434** (0.018) Lagged gini in extractions -7.660** 0.141 0.442**

(0.161) (0.029) (0.016) Treatment -0.909* 0.014** -0.357 0.008 (0.078) (0.000) (0.580) (0.037) Wave 2.360 0.033 -0.019 0.030 (2.666) (0.005) (0.283) (0.066) Treatment * Wave 1.303* -0.028** 0.990 -0.002 (0.106) (0.002) (0.371) (0.021) Round -0.402 0.015*** 0.064 0.006** (0.071) (0.000) (0.069) (0.000) Rule 2 (Rotation) 2.066 -0.073*** -0.067 -0.003 (0.612) (0.001) (0.293) (0.017) Rule 3 (Communication) 8.723* -0.189** -1.049 -0.069 (1.127) (0.003) (0.213) (0.034) Wave * Rule 2 0.430 0.001 0.247 -0.003 (0.503) (0.002) (0.042) (0.034) Wave * Rule 3 0.345 -0.005 -0.596 -0.050 (1.062) (0.006) (1.291) (0.073) Treatment * Rule 2 0.512*** -0.002* 0.042 -0.003** (0.003) (0.000) (0.018) (0.000) Treatment * Rule 3 3.716** -0.028** -0.853* 0.007* (0.085) (0.002) (0.130) (0.001) Workshop assistance -2.367 -0.035** 0.256** -0.046* (proportion in group) (0.440) (0.002) (0.005) (0.006) Repitent group -1.775 -0.013 -1.394 -0.036 (2.695) (0.002) (0.233) (0.019) Initial resource 0.056 -0.001** (0.010) (0.000) Constant 22.407 -0.028 -4.575 0.340 (10.083) (0.210) (3.137) (0.064) Observations 1,120 1,120 1,097 1,120 R-squared 0.527 0.481 0.417 0.502 Clustered errors by aqueduct

YES YES YES YES

Socioeconomic and community controls

YES YES YES YES

Notes: Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

25

Regression results show that there are pre-existent differences between aqueducts.

Learning processes in the second wave depend also on the aqueduct; that is on the

group receiving the workshop. The total group contributions in the second wave are

significantly higher in Pastor Ospina, while the gini coefficient in contributions is lower.

Thus the pre-existent differences that showed worse group provision levels and higher

contribution inequality in Pastor Ospina in the first wave reversed in the second wave.

Interestingly, we found that the higher the proportion of participants who assisted the

workshop in the game group, the lower the gini contributions indicator.

Regarding our experimental design, the gini in contributions, gini in extractions and

extraction slope in the previous round, play a significant role in predicting the total

group provisions, the gini in contributions, the extraction slope and the gini in

extractions in the next round, which reflects the importance of each group dynamics in

the individual behavior. Furthermore, there is a small but significant effect of the initial

resource produced each round. It seems that the more water produced, the higher the

space to improve equity in extraction distribution, as the gini in extractions lowers.

7. Concluding: What we have learned from returning to these aqueducts?

The experimental design we have used allows us to explore the role that contributions

and appropriation decisions have in determining the sustainability of administering

irrigation systems through collective action and self-governance. The interaction

between the goals of efficiency and equity in the provision of the public good and the

allocation of water, respectively, shows that face-to-face communication can have a

powerful effect in both accounts. This is no news as previous literature reports such

findings. However, we have taken the effort a step further by returning back to the same

communities and repeating these experiments with the same and other participants.

Our goal was to explore how a trial and error process, within stages in the games and

between waves, could provide lessons regarding the social and individual learning

through these games.

We tested the learning process both within sessions and between waves. Within a

particular session we have shown how the transition from the baseline to a second stage

where we rotated players across all five positions ABCDE had no major positive effects.

This is interesting as very frequently rotation systems are preferred by common-pool

resource as rules for allocating rights and duties. The transition from the baseline fixed

position stage (rounds 1-5) to the rotation stage (rounds 6-10) did not create

improvements in contributions nor fairness in the distribution of water, which suggests

that the rotation scheme induced a retaliation effect in those who had been in the

downstream positions in the first stage, who increased their extraction when allowed to

take the upstream positions. As shown in figures 11 and 12, the gini coefficients shows

26

slight increase from stage 1 to stage 2. Such increased inequality is stopped during the

third stage when players are allowed to talk to each other.

However, such patterns differ between the two aqueducts with interesting lessons for

our second level of analysis of the learning effects, that of comparing the two waves. Our

workshop treatment village, Pastor Ospina, improved significantly for the second wave

of games in terms of the distribution of contributions and extracted water (Figures 11

and 12), as well as in terms of efficiency (Figures 9 and 10). A plausible explanation for

such difference could relate to the workshop we conducted between waves for the

Pastor Ospina participants. Our regression analysis supports the claim, but we have only

two observations and results could be confounded by characteristics of Pastor Ospina

itself. Nevertheless, the pre-existing conditions –there were differences in the behavior

observed in the first rounds- did not support such claim as these differences would run

in the opposite direction, that is, the Pastor Ospina participants were showing lower

levels of contributions in wave 1.

Overall we find a series of conflictive learning processes overall that deserve attention.

The possibility of trial and error through participating in these games both within a

session and between waves shows that without a feedback and discussion process with

the groups, the potential for detrimental effects arising from a previous negative

experience could exacerbate the problems of free-riding and taking advantage of

privileged positions to derive rents given previous cases of having been taken advantage

of in a previous stage or wave. This was specially the case for those located in

downstream positions in their first experience. On the other hand, the possibility of

exchanging these experiences through the community workshop, and building a sense of

common good towards higher group contributions for the provision of more water for

all to distribute equally seems to have a powerful effect from the first to the second

wave.

Returning to the literature (Pahl-Wostl et al., 2007; Hamari et al. 2014) and framework

on gamification presented in Figure 1: triggered by the competition and cooperation

dynamics experienced in the game, players’ mental models and their psychological

outcomes changed, which resulted in the adoption of new strategies as the game

progressed. Comparing the way participants played during the different stages of the

game as well as during the first and second waves of the game, we observed significant

changes in players’ behavior. Public incentives (the intrinsic motivational affordance)

became progressively more salient in comparison to private incentives (extrinsic

motivational affordance). In the second wave overall contributions to the public fund

increased; as did equity indicators for water distribution also improved in the second

wave. Game results also show that face-to-face communication and the workshop hold

in one of the groups after the games became important catalysts of the psychological and

behavioral evolution. Communication was seen to increase cooperation and reduce

inequity significantly. Similarly, the group that participated in the workshop showed in

27

the second wave greater improvements in their distribution efficiency and higher

contributions in the communication rounds in comparison to the group that did not

participate in the workshop.

The results obtained also suggest that CPR experiments can help create the capacities

needed between players or by extension, natural resource users, to advance social

learning for CPR management (Pahl-Wost and Hare, 2004). The game helped in the

process of joined problem identification, as the game helped view a real life problem or

situation from a new perspective. We also saw that players became to some extent

aware of each other’s actions and goals. The behavior of some players influenced the

actions of the rest of the players. For example, the behavior of player A at the beginning

of the game had a major impact on the strategies adopted by the rest of the players. If

player A was fair during the first round of the game, the rest of the players contributed

more to the public fund in the subsequent rounds of the game and there was more

equity in water distribution in comparison to when player A was unfair in round 1.

Similarly, players upstream restrained themselves to a certain extent in extracting water

allowing players downstream to acquire more water.

Throughout the second stage of the game, players had to experience every position on

the watershed with the aim of helping players understand the complexity of the CPR

system and how the resource availability fluctuates depending on the player’s location

in the system and the rest of the players’ actions. As a result of these dynamics, the

actors (players) mutual interdependence became explicit during the game. Contrary to

expectations, the rotation rule did not seem to affect either group efficiency in the

provision of water nor the fairness in its distribution.

Face-to-face communication and the workshop proved key in helping players (users)

understand the mutual benefits of cooperation. These two catalysts were critical

elements for building trust among participants. They favored the creation of informal as

well as formal relationships which are all very much needed for building confidence

among players or in a real setting, for the creation of formal and informal institutions

that can monitor and guide water or other natural resources management. Face-to-face

communication proved indeed very effective in improving cooperation and reducing

inequity. Similarly, the power of CPR experiments seems to increase when a workshop

was provided at the end of the game. Overall, CPR experiments seem to be a promising

tool to stimulate group learning and the development of shared meanings and values, all

so important for advancing social learning and fostering joint action or collective action.

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Appendices

Table xx. Regression results for analyses for individual level data for contribution percentages by each position assigned in base line. Between brackets are the standard deviations.

(1) (2) (3) (4) (5) VARIABLES A B C D E Wave -5.6275*** -39.1541*** 2.0057** 0.0573 -0.8557** (0.0033) (0.5860) (0.0454) (0.0221) (0.0391) Treatment -2.5236** -40.3539*** -9.6616** -0.2235* -2.9043** (0.1177) (0.5610) (0.2043) (0.0276) (0.0574) Treatment * Wave 1.7805* 23.9539*** 8.6908** 0.3277** 2.1555** (0.1487) (0.3243) (0.2344) (0.0113) (0.0481) Workshop -4.9514** 16.7729** 3.7789*** -0.2365 -

0.6021*** (0.1039) (0.2662) (0.0412) (0.0550) (0.0044) Round -0.0010 0.0029* -0.0007 -0.0094 -0.0133 (0.0036) (0.0002) (0.0022) (0.0026) (0.0026) Rule 2 0.0068 0.0740** 0.0385 0.2132*** 0.2294 (0.0288) (0.0035) (0.0502) (0.0013) (0.0490) Rule 3 0.1294 0.0903 0.0699 0.3411 0.5889* (0.1801) (0.0246) (0.0362) (0.0948) (0.0639) Treatment * Rule 2 -0.0107** 0.0212*** 0.0456** 0.0060* -

0.0368*** (0.0005) (0.0003) (0.0008) (0.0007) (0.0004) Treatment * Rule 3 0.0773 0.1243** 0.1911*** 0.0545*** 0.0420* (0.0258) (0.0070) (0.0004) (0.0008) (0.0038) Rule 2 * Location in watershed

-0.0145* -0.0391*** -0.0302 -0.0510* -0.0471

(A=1; B=2; C=3; D=4; E=5)

(0.0014) (0.0005) (0.0195) (0.0070) (0.0118)

Rule 3 * Location in watershed

0.0053 -0.0042 0.0015 -0.0375 -0.0800*

(A=1; B=2; C=3; D=4; E=5)

(0.0447) (0.0088) (0.0064) (0.0188) (0.0109)

Lagged share resource left

0.0330 0.0699 0.0983 0.0718 0.0535

(0.0183) (0.0214) (0.0368) (0.0411) (0.0085) Age 0.0711** -0.1228*** -0.1031*** -0.0258** -0.0100** (0.0020) (0.0015) (0.0010) (0.0017) (0.0002) Gender -5.0575** 12.3466*** 0.5028* 0.7344** -0.2772** (0.1245) (0.1827) (0.0424) (0.0365) (0.0061) Constant 14.4742*** 111.1027*** 9.0779** 0.9905** 9.1488** (0.0323) (1.5411) (0.2950) (0.0757) (0.2712) Observations 1,067 1,097 1,067 1,011 1,025

32

R-squared 0.4794 0.5231 0.4855 0.5324 0.5478 Session fixed effects and errors clustered by aqueduct

YES YES YES YES YES

Socioeconomic and community controls

YES YES YES YES YES

Notes: Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1

33

Table xx. Regression results for analyses for individual level data for fair extraction

indicator by each position assigned in base line. Between brackets are the standard

deviations.

(1) (2) (3) (4) (5) VARIABLES A B C D E (dep. Variable : fair extraction)

Wave 53.2578*** 100.7242** -58.0212** 18.1885 -651.1453** (0.7908) (4.9031) (1.6317) (4.1685) (33.6475) Treatment 40.2415* 319.9390* -62.3216* 30.3884* -688.7098** (5.6406) (34.4383) (9.1444) (4.6837) (33.9141) Treatment * Wave -33.1151 -203.48** 66.6076* -31.078* 645.9914** (5.5950) (14.0923) (8.6509) (4.8526) (32.9007) Workshop 25.8159* -186.8166 -67.0247** -0.7686 -116.1460** (3.1706) (34.4688) (3.0253) (0.1888) (8.2057) Round 0.4278 0.3312 0.1219 -0.1357 -0.0135 (0.2233) (0.1937) (0.1308) (0.3669) (0.6442) Rule 2 1.3475 -2.9120 -2.5827 0.3067 1.0137 (3.6604) (1.3334) (0.5431) (2.7689) (5.5004) Rule 3 0.5972 -2.7681 -0.4727 1.3715 0.9416 (4.7182) (1.5369) (1.2567) (4.2189) (8.1506) Treatment * Rule 2 -1.3170** -1.0548* 0.4308** 1.1838** 0.6075* (0.0575) (0.1043) (0.0071) (0.0800) (0.0882) Treatment * Rule 3 1.5787 1.3745 -0.3094 1.7894 5.2022** (0.8522) (0.5467) (0.0500) (0.2921) (0.1121) Location in watershed 3.0218 3.3141* 3.2003* 3.9177* 3.5353 (A=1; B=2; C=3; D=4; E=5)

(1.3657) (0.4149) (0.2901) (0.5461) (0.9353)

Initial resource -0.0769* -0.0439 -0.0326** -0.0163 -0.0100 (0.0096) (0.0309) (0.0008) (0.0109) (0.0087) Relative contribution -0.8289 -2.6724 -5.8934*** -7.4281 -1.4733 (13.2631) (1.3532) (0.0638) (7.5840) (4.1017) Gender 38.4541* -71.7636 3.4887 -13.03* -140.6131** (3.8436) (14.9815) (1.0172) (1.3981) (7.3871) Constant -183.387** -190.3599* 228.5063** -40.8572 2,744.5515** (8.3269) (29.8909) (5.8715) (7.6464) (132.5059) Observations 1,034 1,075 999 913 886 R-squared 0.4823 0.3849 0.5075 0.4378 0.3029 Session Fixed effects and errors clustered by aqueduct

YES YES YES YES YES

Socioeconomic and community controls

YES YES YES YES YES

Robust standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1