Cooperation and framing effects in provision point mechanisms: Experimental evidence

Ecological Economics 70 (2011) 1200–1210

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Ecological Economics j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / e c o l e c o n

Analysis

Cooperation and framing effects in provision point mechanisms: Experimental evidence Douadia Bougherara a,⁎, Laurent Denant-Boemont b,1, David Masclet b,c,1 a b c

INRA, UMR1302 SMART, F-35000 Rennes, France Department of Economics, University of Rennes 1, Rennes, France CIRANO, Montréal, Canada H3A 2A5

a r t i c l e

i n f o

Article history: Received 16 August 2010 Received in revised form 16 December 2010 Accepted 27 January 2011 Available online 17 March 2011 JEL classification: C9 C92 H41 Q2 Q5 Keywords: Public goods experiment Provision point Framing effects

a b s t r a c t Andreoni (1995) showed that pure framing effects may influence contribution in Voluntary Contribution Mechanisms (VCM) by comparing a standard public goods game, called the positive frame condition (giving to the public good), with a negative frame condition (taking from the public good) where the subjects' choice to purchase a private good makes the other subjects worse off. This paper aims at testing the robustness of such framing effects in the context of Provision Point Mechanisms (PPM). Our approach is original in that it combines both framing and provision point dimensions by comparing maintaining (taking from the public good) and creating (giving to the public good) contexts using Provision Point experiments. Consistent with previous findings, we find that individuals tend to be less cooperative in the maintaining frame than in the creating frame. Our results also show that the framing effects are stronger under a PPM than under a VCM and increase with the provision point level. These results may have important consequences for the management of environmental resources. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Numerous environmental policies are generally aimed at creating a variety of valuable public goods and/or maintaining existing resources (open-sea fisheries, ground water, and forest biodiversity) by reducing, for example, the negative externalities of farming such as water pollution. One main difference between creating and maintaining policies is that individuals are asked to create resources in the former, while in the latter, they have to maintain unchanged an existing level of resources. To illustrate the difference between creating and maintaining resources, let us take the example of the US CSP (Conservation Security Program in the 2002 Farm Bill). This program offers payments both for existing conservation practices but also additional payments for new practices to improve soil, water, air, energy, plant and animal life. “When fully implemented, the CSP will pay producers to adopt or maintain appropriate land-based practices that address one or more resources of concern, such as soil quality,

⁎ Corresponding author at: INRA, ESR, 4 allée Bobierre, CS61103, F-35011, RENNES Cedex, France. Tel.: +33 2 23 48 56 03; fax: +33 2 23 48 53 80. E-mail addresses: [email protected] (D. Bougherara), [email protected] (L. Denant-Boemont), [email protected] (D. Masclet). 1 Faculté des Sciences Economiques, 7 place Hoche, 35 065 Rennes Cedex, France. 0921-8009/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.ecolecon.2011.01.023

water quality, or wildlife habitat. […] Through the CSP, producers can receive annual payments based on conservation practices they had installed on their land before enrollment in the CSP” (Claasen, 2003). Formally, a creating context is related to voluntary contribution mechanisms (VCM) in which each individual member of a group has an opportunity to “create resources” by contributing any fraction of his/her initial endowment to a public good (see Ledyard, 1995, for a survey). In such a VCM setting, each individual has a dominant strategy to allocate zero to the group account, whereas the highest group payoff is reached if all members contribute their entire endowment to the group account. The main overall pattern observed in laboratory experiments is that compared to theoretical predictions, subjects tend to contribute more to the public good (Isaac et al., 1984; Andreoni, 1988; Isaac and Walker, 1988; Ledyard, 1995). While the creating context can be interpreted in terms of voluntary contribution to a public good, the situations of maintaining resources are more related to Common Pool Resource (CPR) situations.2 In a CPR experiment, a finite number of individuals are given an initial

2 CPR games have two characteristics that make them differ from VCM. (i) They are usually framed as a maintaining game. (ii) CPRs display rivalry. In our experiment, the maintaining condition shares only the first feature of the CPR games since no rivalry is introduced.

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endowment which they can allocate between resource extraction activities and an alternative activity. The total revenue obtained from resource extraction depends on the total amount allocated in this activity. Theoretical predictions of this simple game are that unrestricted accesses to CPR lead individuals to withdraw more of the resources than is Pareto optimal. As a consequence, human over-exploitation of the resources can lead to destruction of the common resources (Ostrom et al., 1994).3 While environmental policies are generally aimed indifferently at both creating and/or maintaining a variety of public goods –since they provide similar incentives for both– individuals may behave differently in the two contexts. One possible reason is that individuals may be influenced by a pure framing effect and may perceive that creating resources would induce more positive externalities than maintaining existing resources would. Fearnside (2003) provides a good example of this aspect in the context of Conservation Policy in Brazilian Amazonia. The author sheds light on the dilemma existing between allocating effort and money to create new conservation units (extractive reserves, national parks, national forests) in Brazilian Amazonia vs. efforts devoted to consolidate existing units. While effort is devoted to create new conservation units, the author argues that more effort should also be allocated to maintain existing units that suffer generally from a grave state of degradation and illegal invasion.4 Framing effects have been studied extensively in the experimental literature. Since the seminal work of Amos Tversky and Daniel Kahneman on framing (e.g. Tversky and Kahneman, 1981,1986), economists have been aware that some slight changes in the framing may influence significantly decisions. In a VCM setting, Andreoni (1995) showed that contributions could be influenced by pure framing effects by comparing a standard public good game, called the positive frame condition (giving to the public good), with a negative frame condition (taking from the public good) where the subjects' choice to purchase a private good makes the other subjects worse off. The results of the experiment indicate that subjects contribute more under the positive framing condition, despite similar incentives in both games. Willinger and Ziegelmeyer (1999) replicated Andreoni's results in the case of an interior solution and found similar results. Park (2000) also replicated Andreoni's experiment and found that while there is a significant difference between the two framing conditions in terms of overall contribution rates, there is no significant difference for subjects who have strong cooperative value orientation. Framing has also been found significant in VCM games by Lόpez and Nelson (2005) and by Messer et al. (2007). The main objective of our paper is to provide further support for Andreoni's findings by extending previous existing research on framing effects to the context of Provision Point Mechanisms (PPM). A Provision Point (PP) is a minimum level of aggregate contributions below which the public good is not provided (see Ledyard, 1995).5 The PPM can be formalized as a large N person coordination game as shown by Bagnoli and Lipman (1989). The game has multiple 3 Ostrom et al. (1994) conducted a set of CPR experiments in which they varied the extent of communication possible among subjects. They found that subjects allowed to communicate often achieved nearly cooperative outcomes. If subjects were not allowed to communicate, then the aggregate outcome was best described by Nash equilibrium. However, no individual appeared to play a Nash equilibrium strategy. Keser and Gardner (1999) conducted another experiment to test whether experienced individuals who had some knowledge in game theory play a Nash equilibrium in CPR games. The authors found that subjects rarely play a Nash equilibrium of the CPR game. 4 The grave state of degradation and illegal invasion of some existing units points to the need for forceful action on the part of government authorities to avert the complete destruction of these units. Examples of these include the Jamar and Bom Futuro FLONAs in Rondonia and the Serra do Divisor National Park in Acre, Brazil. 5 The Green Choice program introduced in 1995 by the Niagara Mohawk Power Company of New York constitutes a good illustration of a simplified provision point mechanism designed to fund a threshold public good (see Marks and Croson, 1998). In this program, citizens could voluntarily choose to join the project aimed at promoting non-polluting, renewable resources. The program required a certain minimum number of subscribers since if subscriptions fell short of the needed level, the program would be abandoned.

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efficient Nash equilibria where the cost of the public project is exactly covered. Several studies have shown that a PPM is generally more efficient than a simple VCM to assess individual valuations since it increases the proportion of demand revealed by alleviating the free riding problem (Rondeau et al., 1999; Rose et al., 2002; Champ et al., 1997; Poe et al., 2002; Rondeau et al., 2005). Furthermore several studies argue that the PPM would be more robust to changes in experimental parameters, information provided to participants and subject type as compared to the VCM. Other experimental studies have investigated the effects of existing (or not) money-back guarantee (i.e. whether or not contributions are wasted if the provision point is not reached). Most of the studies (with the notable exception of Dawes et al., 1986) show that the absence of money refund leads to lower contribution levels compared to situations where money-back guarantee is possible (Isaac et al., 1989; Rapoport and Eshed-Levy, 1989; Cadsby and Maynes, 1999). In a field context of a real charitable-giving campaign, List and Lucking-Reiley (2002) also showed that imposing a refund increased contributions significantly. Our study investigates several issues that previous literature has left unaddressed. First, we investigate whether framing effects are more (or less) important under PPM than under VCM. Second, we examine to what extent framing is sensitive to changes in provision point levels by varying the provision point level (low, medium and high). Precisely we examine whether framing effects interact with the level of the provision point. To our knowledge, comparing framing effects under various provision point levels has never been tested previously. Third, we investigate the effects of framing on the probability of providing (maintaining) a public good. Our experimental design consists of several treatments that differ in the existence of a provision point (VCM vs. PPM), the level of the provision point (low, medium or high) and the framing context (creating vs. maintaining framing). The creating framing condition corresponds to a classical VCM where all tokens are initially placed in the private account and subjects can contribute to the group account. In contrast, the maintaining treatment condition corresponds to a setting in which all tokens are initially placed in the public investment and subjects can withdraw tokens. Our protocol slightly differs from Andreoni's. In Andreoni's protocol, tokens are initially placed in a third account which is neither the private account nor the public account since subjects are to allocate these tokens between the private and the public account. In contrast, in our protocol, tokens were initially placed in the public account (maintaining condition) or in the private account (creating condition). Our paper is also related to Sonnemans et al. (1998) and Kotani et al. (2008), both of which tested framing effects in the context of binary contribution for step-level public goods/bads. Consistent with Andreoni's study, Sonnemans et al. find that framing effects are present in such a setting while Kotani et al. find only a negligible framing effect at the aggregate level.6 In contrast to these previous studies that focus on a single binary contribution public good where individuals only have the choice between contributing a positive amount or nothing, we investigate here framing effects in the context of continuous contribution public goods with different provision points. To anticipate our results, we find that in all treatments, individuals tend to be more cooperative under a creating frame than under a maintaining frame. Our data also indicate that framing effects are stronger under PPM than under VCM and increase with the provision point levels. Finally, we find that the probability of providing (maintaining) a public good decreases significantly with the provision

6 As is clear from the above discussion, the results on the effect of framing in step level public goods/bads are mixed. The results of Sonnemans et al. suggest that framing has a positive effect on contribution levels, while Kotani et al. argue that framing has no significant effect. Their study differs from Sonnemans et al.'s study since the PPM is played under a stranger matching protocol and no questions are asked to the participants during the experiments.

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point level but to a lesser extent under the creating frame compared to the maintaining frame. The paper is organized as follows. Section 2 describes the experimental design and experimental protocol. Section 3 presents theoretical predictions and behavioral conjectures about the expected treatment effects. The results of the study are presented in Section 4. Section 5 contains our concluding remarks. 2. Experimental Design 2.1. Treatments Our experimental design consists of two settings. The creating setting refers to a standard public good game where all tokens are initially in the private account. Four subjects are provided with 20 tokens each. We consider four different conditions: no provision point (i.e. PP = 0), a low provision point level (PP = 28), a medium provision point level (PP = 60), and a high provision point level (PP = 80). In provision point mechanisms, the good is provided only if contributions reach a provision point. Excess contributions give a higher level of public good according to a given linear function. In our PPM, there is no money back guarantee. The payoff function of participant i contributing ci to the public account is the following: 8 4 > > > > uðci Þ = 20−ci + 0:4 ∑ ck < k=1 > > > > : uðci Þ = 20−ci

4

if ∑ ck ≥ PP k=1

ð1Þ

4

if ∑ ck b PP

3. Theoretical Considerations

k=1

where ci is the contribution of player i and 20 is the initial endowment of each agent. The marginal per capita return (MPCR) of the public good is 0.4. So, each ECU (Experimental Currency Unit) contributed to the group account yields a payoff of 0.4 ECU to each of the four members of the group. Each ECU not contributed by the subject is credited to her/his private account. The second setting is called the Maintaining setting that corresponds to a public good game where all tokens (80) are initially in the group account. Four subjects are allowed to withdraw up to 20 tokens from the group account. We also consider four provision point levels: 0, 28, 60 and 80. The payoff function of participant i withdrawing wi from the public account is the following: " # 8 4 4 > > > > uðwi Þ = wi + 0:4 × 80− ∑ wk if 80− ∑ wk ≥ PP < k=1 k=1 > > > > : uðwi Þ = wi

ð2aÞ

4

if 80− ∑ wk b PP k=1

which is equivalent to 8 4 4 > > > wk if 80− ∑ wk ≥ PP > < uðwi Þ = wi + 32−0:4k∑ =1 k=1 > > > > : uðwi Þ = wi

of framing effects over time and to what extent individuals are influenced by changes in frame. For these reasons we also ran some sessions under a within-subject design whereby the same subjects played the creating and maintaining settings, successively (sessions 9–25). More precisely in each within-subject session, there were 30 periods of interaction, divided into two segments of 15 periods with a different treatment in each segment. To control for order effects, we ran about half the within-subject sessions in one order and the other half in the other order. Running sessions under both a within and a between-subject design should improve the robustness of our findings. Table 1 contains some summary information about each of the sessions. The first four columns indicate the session number, the number of subjects who took part in the session, the number of fourperson groups in the session, and the treatment. The fifth through seventh columns indicate the particular rules in effect in each of the segments of the session. All of the sessions were conducted at the LABEX, at the University of Rennes 1, Rennes, France. Between 12 and 24 individuals took part in each session, for a total of 388 participants. In each session, subjects were randomly assigned to groups of four individuals. The experiment was computerized and the scripts were programmed using the Z-Tree platform (Fischbacher, 2007). No subject took part in more than one session. We ran the experiment under a partner matching protocol (participants were not rematched within each group after each period).

4

:

ð2bÞ

if 80− ∑ wk b PP k=1

We provide in this section a brief theoretical discussion and behavioral assumptions. 3.1. Theoretical Predictions The equilibria in both creating and maintaining settings are the same. It can easily be seen from Eq. (1) that individual i's earnings are maximized at ci = 0 in the condition without provision point (i.e. PP = 0). Therefore, if the game is played once, there is a dominant strategy to contribute zero. If the game is finitely repeated, the only subgame perfect equilibrium of the game is for all players to contribute zero in each period. Respectively, in the maintaining context, all subjects should withdraw all their 20 tokens from the group account. Let us now consider the theoretical predictions for the games with strictly positive provision points. Provision point games have multiple Nash equilibria in which the level of provision point is exactly allocated to the group account. Among these possible Nash equilibria, there exist two symmetric equilibria in which all individuals follow similar strategies. The first symmetric equilibrium called strong free riding equilibrium is one in which all individuals contribute nothing (i.e. ci = 0). The second symmetric equilibrium is characterized by ci = PP/n for all participants. Contributing PP/n is the best response for player i if he or she believes that each other player will also contribute PP/n. In addition to the symmetric equilibria there are also several asymmetric equilibria that are threshold equilibria in that they n

2.2. Participants and Sessions

require that ∑ ci = PP and that ci ≤ αPP where αPP is the amount

The experiment consisted of 25 sessions. In a first series of experiments, we ran sessions under a between-subject design (sessions 1–8). In each session, there were 30 periods of interaction. The advantage of using a between-subject design is that it avoids potential order effects. However the main limitation with a betweensubject design is that we lack control for individual-specific unobservables. Furthermore a between-subject design cannot inform us about the dynamics of the game, whether there is some persistency

each individual receives if the provision point PP is reached by the group as a whole (i.e. the product of contributions by MPCR). It is important to notice that no equilibrium can exist in which more than PP tokens are allocated; each player would prefer to keep the extra tokens and invest them in her or his private account. In the low provision point game, in addition to the strong free riding equilibrium, all combinations totaling to 28 are Nash equilibria provided subjects which contribute strictly less than 12 tokens: (7, 7, 7, 7) (6, 8, 7,7)…. (11, 11, 3, 3). The medium provision point game

i=1

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Table 1 Characteristics of the experimental sessions. Session number

Number of subjects

Number of groups

Treatments

Periods 1–15

Periods 16–30

Provision point

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

24 20 24 24 24 24 20 24 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12 12

6 5 6 6 6 6 5 6 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3

C0 M0 C28 M28 C60 M60 C80 M80 M0 + C0 M0 + C0 M28 + C28 M28 + C28 M60 + C60 M60 + C60 M80 + C80 M80 + C80 C0 + M0 C0 + M0 C0 + M0 C28 + M28 C28 + M28 C60 + M60 C60 + M60 C80 + M80 C80 + M80

C0 M0 C28 M28 C60 M60 C80 M80 M0 M0 M28 M28 M60 M60 M80 M80 C0 C0 C0 C28 C28 C60 C60 C80 C80

C0 M0 C28 M28 C60 M60 C80 M80 C0 C0 C28 C28 C60 C60 C80 C80 M0 M0 M0 M28 M28 M60 M60 M80 M80

No provision pointa No provision pointa Low provision pointa Low provision pointa Medium prov. pointa Medium prov. pointa High prov. pointa High prov. pointa No provision point No provision point Low provision point Low provision point Med. provision point Med. provision point High provision point High provision point No provision point No provision point No provision point Low provision point Low provision point Med. provision point Med. provision point High provision point High provision point

a

30 periods without restart.

(PP = 60) also includes several Nash equilibria each totaling to 60 tokens. In the high provision point game (PP = 80), there are two symmetric Nash equilibria in which each member of the group provides an equal contribution: a Pareto superior equilibrium (20, 20, 20, and 20) and risk dominant equilibrium (0, 0, 0, and 0). The same equilibria are obtained in the maintaining situations. The following Table 2 gives an overview about the theoretical predictions for each treatment. 3.2. Behavioral Conjectures A possible objection to the expectation of similar behavior in both creating and maintaining framings is that players may be influenced by the framing of the game. Framing effects have been identified in social dilemma games. Andreoni (1995) and Willinger and Ziegelmeyer (1999) find that average contributions to a public good are higher when the equivalent game is framed positively (giving to the public good) than negatively (taking from the public good).7 Sonnemans et al. (1998) found similar framing effects in the context of binary contribution for step-level public goods/bads. Based on this previous evidence, we conjecture that such framing effects should also hold for continuous PPM settings. Our first conjecture is stated more precisely below. Conjecture 1. In all treatments (for all provision point levels), subjects should contribute more in the creating condition than in the maintaining condition. Our second conjecture concerns the interaction effects between provision point and framing on contribution levels. The effect of in7 Andreoni (1995) designed a public goods experiment with two frames. The positive frame corresponds to the standard public goods game with a 60-token endowment where individual contributions to the public good yield a positive externality on other subjects. The negative frame endows subjects with 60 tokens and tells subjects that each token they invest in the private account will reduce the earnings of the other players (contributions to the private good yield a negative externality on other subjects). The result of the paper is that cooperation is improved in the positive externality context as compared to the negative externality context. Thus, according to the author, “it must be that people enjoy doing a good deed more than they enjoy not doing a bad deed” (Andreoni, 1995, p. 11).

creasing the provision point is not clear-cut. Asch et al. (1993) find that contribution levels are similar in PPM and VCM. Isaac et al. (1989) use three provision point levels: a high (248), a medium (216) and a low (108) level which correspond to 100%, 87% and 44% respectively of the total token endowment in the group. Isaac et al. (1989) report that, when compared with a VCM, a PPM improves cooperation in early periods, but does not succeed in increasing overall contributions.8 Isaac et al. have tried to solve this apparent contradiction by suggesting the existence of two opposite effects induced by the existence of provision points: the focal point and the assurance assumptions. According to the focal point assumption, contributions should be higher under the PPM because the provision point serves as a focal point for individual decisions. The focal point assumption should play an important role in the equilibrium selection. In particular, participants may be attracted by symmetric Nash equilibria and particularly by the symmetric Paretosuperior Nash equilibrium. According to Cadsby and Maynes (1999), the symmetric nature of these equilibria may make them focal points. For similar reasons, the players may also hope for the symmetric Paretosuperior Nash equilibrium to be a focal point, but choosing focal points is always somewhat arbitrary (Rasmusen and Hirshleifer, 1989). The opposite effect, known as the assurance assumption, conjectures that contributions will be lower in the PPM since subjects may choose not to contribute in order to avoid large penalties if the provision point is not reached. Subjects willing to contribute enough to reach the provision point could suffer from the behavior of other participants who contribute too little and thus impose large penalties on others if the provision point is not reached. Precisely, under the assurance problem conjecture, contribution will be lower in PPM since “small departures from equilibrium contributions by other participants can impose large penalties upon those attempting to contribute enough to obtain high provision equilibria” (Isaac et al., 1989 p.223). However, if the focal point hypothesis dominates, one should observe that subjects contribute more to the provision point public good than to the standard public good.

8 In a different environment (with a money back guarantee and a proportional rebate rule), Rondeau et al. (1999) find that the PPM is generally superior to VCM in terms of efficiency.

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Table 2 Overview about Nash equilibrium predictions. Framing provision point level

Creating

Maintaining

PP = 0 PP = 28 PP = 60

ci = 0 ∀ i ∈ {1, …, n} n ci = 0 ∀ i ∈ {1, …, n} and 0≤ci b12∀i∈f1; …; ng with ∑ ci = 28

wi = 20 ∀ i ∈ {1, …, n} n wi = 20 ∀ i ∈ {1, …, n} and 8bwi ≤20∀i∈f1; …; ng with ∑ wi = 52

ci = 0 ∀ i ∈ {1, …, n} and 0≤ci ≤20∀i∈f1; …; ng with ∑ ci = 60 i=1 ci = 0 ∀ i ∈ {1, …, n} and ci = 20 ∀ i ∈ {1, …, n}

wi = 20 ∀ i ∈ {1, …, n} and 0≤wi ≤20∀i∈f1; …; ng with ∑ wi = 20 i=1 wi = 20 ∀ i ∈ {1, …, n} and wi = 0 ∀ i ∈ {1, …, n}

i=1 n

PP = 80

Focal point and assurance effects should exist both under the creating and maintaining framings. However we conjecture that the assurance effect should be higher under the maintaining frame compared to the creating frame. The reason is that penalties for deviating from the equilibrium may be perceived as being higher under the maintaining treatment. This is because participants may perceive the disutility of losing something they have (in the maintaining treatment) as greater compared to the disutility of failing to gain something (in the creating treatment). This refers to the loss aversion theory of Kahneman and Tversky (1979) according to which choices people make between pairs of lotteries are reversed when the equivalent pairs of lotteries are framed in the domain of losses instead of gains. Using the language of Kahneman and Tversky: “The aggravation that one experiences in losing a sum of money appears to be greater than the pleasure associated with gaining the same amount”. Such phenomenon is referred to as loss aversion. Thus, if the subjective disutility of losing all the tokens initially placed in the group account in the maintaining treatment is greater than the subjective utility of gaining something in the creating treatment, then one should expect that more people will choose to withdraw their tokens in the maintaining treatment and therefore less cooperative choices will be made under the maintaining treatment than in the creating treatment. This is stated precisely in our second conjecture:

4. Results 4.1. Creating vs. Maintaining Frames In this section we seek to measure the influence of framing effects on contribution levels. Fig. 1 illustrates the time path of group contributions by period in all treatments, comparing the maintaining and creating contexts in sessions 1–8. The period number is shown on the horizontal axis and the average group contribution on the vertical axis, where the maximum possible group contribution is 80. This figure shows the same pattern for all provision point levels: initially there is a positive level of contribution to the group account and the level of contribution declines with repetition. Fig. 1 also indicates that for all provision point levels, subjects contribute more under the creating setting. On average people contribute 22.6 ECU in the C0 treatment and 18.96 ECU in the M0 treatment. A Mann–Whitney pairwise statistical test comparing contribution levels between treatments, maintaining the conservative assumption that each group's activity over the session is a unit reports significant differences between C0 and M0 treatments in sessions 1–8 (z = − 1.82, p = 0.056, two-tailed). Mann–Whitney pairwise tests also indicate that contributions are significantly higher under the C60 treatment (mean = 58.06) than in the M60 (mean = 27.96) treatment (z = − 1.684, p b 0.1, twotailed) and also higher under the C80 (mean = 28.62) treatment than in the M80 (mean = 9.65) treatment (z = − 1.826, p = 0.068, two-tailed). Finally, a similar test comparing contributions in the

Average group contribution

Average group contribution

Conjecture 2. The assurance effect should be higher under the maintaining condition, leading to a greater difference in contributions between the creating and maintaining conditions as the provision point increases.

50 45 40 35 30 25 20 15 10 5 0 1

3

5

7

i=1 n

50 45 40 35 30 25 20 15 10 5 0

9 11 13 15 17 19 21 23 25 27 29

1

3

5

7

9 11 13 15 17 19 21 23 25 27 29

Periods

Periods

m0

c28

Average group contribution

Average group contribution

c0 70 60 50 40 30 20 10 0 1

3

5

7

9 11 13 15 17 19 21 23 25 27 29

70 60 50 40 30 20 10 0 1

3

5

7

9 11 13 15 17 19 21 23 25 27 29

Periods c60

M28

m60 Fig. 1. Average contribution per treatment in sessions 1–8.

Periods C80

M80

D. Bougherara et al. / Ecological Economics 70 (2011) 1200–1210

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Table 3 Determinants of contribution and framing effects in sessions 1–8 (random effects Tobit estimates). Dep.Var: ci,t Models

RE Tobit

RE Tobit

RE Tobit

RE Tobit

Treat.

No provision point (1)

PP28 (2)

PP60 (3)

PP80 (4)

Maintaining Creating

Ref. 6.423⁎⁎⁎ (1.964) 1.132⁎⁎

Ref. 0.156 (2.457) 8.276⁎⁎⁎

Ref. 14.137⁎⁎⁎ (3.046) 3.431⁎⁎⁎

Ref. 35. 239⁎⁎⁎ (11.443) 18.708⁎⁎⁎

Period

(1.029) 1.688 (1.035) −0.571⁎⁎⁎

(1.039) −5.799⁎⁎⁎ (1.0130) −0.354⁎⁎⁎

(1.013) −1.601⁎ (1.033) −0.300⁎⁎⁎

(6.583) 2.122 (6.453) −2.266⁎⁎⁎

Constant

(0.045) 5.588⁎⁎⁎

(0.045) 7.296⁎⁎⁎

Obs Left cens. Right cens. Log likelihood

(1.409) 1320 600 53 −2668.29

(0.042) 6.551⁎⁎⁎ (1.786) 1440 702 59 −2724.27

(0.288) −5.792 (7.880) 1320 978 252 −1179.11

Sessions 1–8

Creating*last 10 periods Last 10 periods

(2.194) 1440 449 258 −2939.08

RE Tobit = random effects Tobit. ⁎⁎⁎ Significant at the 0.01 level. ⁎⁎ Significant at the 0.05 level. ⁎ Significant at the 0.1 level.

Result 1. For all treatments, contribution levels are significantly higher under the creating condition.

4.1.1. Support for Result 1 Table 3 shows the results of estimates on the determinants of the individual contribution decision. Since each subject is observed a number of times (30 times), we appeal to panel data methods with random effects. Table 3 displays the results of Tobit models in which the dependent variable is the contribution choice of subjects. Tobit models account for both left- and right-censoring, which may be justified by the number of left and right-censored observations in the sample. We also ran additional estimates using GLS models that report very similar findings (not reported here but available upon request). The variable “creating” takes value 1 if subjects are playing treatments C0, C28, C60 or C80 and 0 otherwise. The reference variable here is the maintaining treatment. We introduced a trend variable “period” and a dummy variable “10 last periods” to measure the dynamics of contribution levels. Finally we also introduced an interaction variable “creating*10 last periods” to check whether framing effects are higher in the last periods of the game. The estimates presented in Table 3 show that for all treatments individuals contribute significantly more under a creating frame. The “creating” variable is significant for all provision point levels (except for PP = 28). However the positive and significant coefficient associated to the “creating*10 last periods” in column (2) indicates that framing effects also exist for PP = 28 but only for the last 10 periods of the game. The “creating*10 last periods” variable is positive and highly significant in most of the estimates, indicating that the creating effects are higher in the last periods of the game. Finally the negative and significant coefficient associated to the trend variable confirms previous findings. This result is in line with a number of other experiments, which have documented that contributions tend

to decline with repetition (Isaac et al., 1984; Isaac and Walker, 1988; Andreoni, 1988; Weimann, 1994; Keser, 1996). 4.2. Robustness Check To check the robustness of our results to changes in the parameters of the game as well as the persistency over time of framing effects, the same treatments have been run under a withinsubject design in which the same subjects played the creating and maintaining settings, successively (sessions 9–25). To control for order effects, we ran about half sessions in one order (sessions 9–16) and the other half in the other order (session 17–25). Figs. 2 and 3 show the time path of group contributions by period in all treatments for sessions 9–16 and 17–25, respectively. Fig. 4 provides additional information about contribution levels on pooled data averaged on 15 periods, which eases comparisons across treatments. These figures show that people contribute more under a creating condition. A Wilcoxon signed rank test on pooled data indicates that contributions are significantly higher in the C0 treatment (mean = 26.6) than in the M0 (mean = 23.95) treatment (p = 0.08, two-tailed). A similar test indicates that contributions are also significantly higher in the C28 (mean = 32.18) than in the M28 (mean = 25.96) treatment (p b 0.1, two-tailed). The difference of contribution between C60 (mean = 47.52) and M60 (mean = 33.37) is highly significant in the last 5 periods of the game only (p = 0.04,

Average group contribution

C28 (mean = 23.74) and M28 (mean = 16.67) treatments indicates that people contribute significantly more in the C28 treatment than in the M28 but in the last ten periods only (p b 0.1). No significant difference is found between these treatments before period 20. All together, these findings indicate that people contribute significantly more under a creating condition than under a maintaining condition. This is stated more precisely in Result 1.

80 70 60 50 40 30 20 10 0 1

3

5

7

9 11 13 15 17 19 21 23 25 27 29

Periods M0C0

M28C28

M60C60

M80C80

Fig. 2. Average contribution per treatment in sessions 9–16.

D. Bougherara et al. / Ecological Economics 70 (2011) 1200–1210

Average group contribution

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80 70 60 50 40 30 20 10 0 1

3

5

9 11 13 15 17 19 21 23 25 27 29

7

Periods C0M0

C28M28

C60M60

C80M80

Fig. 3. Average contribution per treatment in sessions 17–27.

50

4.3. Interaction between Provision Points and Framing Effects In this section we focus our attention on the interaction between provision point levels and framing effects. Our findings indicates that in both contexts (creating and maintaining) the average contribution increases with the provision point level and reaches a peak for PP = 60. Interestingly, our data also shows that the difference in contribution between the creating and maintaining condition increases with the level of the provision point. For example, difference in contribution between C28 and M28 is 6.65 units while it amounts to 14.42 units between C60 and M60. These findings are stated more precisely in Result 2.

Average group contribution

Average group contribution

two-tailed). Finally, contribution levels are also significantly higher in the C80 (mean = 44.67) than in the M80 (mean = 36.83) treatment (p = 0.07, two-tailed). Fig. 2 shows that the introduction of a creating frame in period 16 has a positive effect on contribution in most of the treatments. In contrast, Fig. 3 indicates that contribution level declines after period 16 when the creating frame has been removed. However the decline of contribution level is rather slow, suggesting a kind of persistency of the creating frame even after it has been removed. Table 4 provides more formal evidence of these findings. It shows the determinants of contribution levels for sessions 9–25. Since our second experiment allowed the same subjects to play the creating and maintaining settings successively, we controlled for possible order effects by introducing a dummy variable “order” that takes 1 for periods 16–30 and 0 otherwise. We also introduced a dummy variable “CM” that takes 1 if subjects played the creating treatment in the first 15 periods (i.e. sessions 17–25) and 0 otherwise (sessions 9–16). Finally we introduced an interaction variable “creating*5 last periods” to check whether framing effects are higher in the last periods of the game.

The estimates presented in Table 4 confirm our previous findings. They show that individuals contribute significantly more under a creating frame. Furthermore the “creating*5 last periods” captures a positive and significant coefficient in almost all treatments (except the no provision point condition), indicating that the creating effects are higher in the last periods of the game. The “order” variable captures a negative and significant coefficient, indicating that subjects contribute significantly less in periods 16–30 than in the first segment of the experiment in sessions 9–25. If we look at the “CM” variable, it indicates that individuals contribute significantly more in sessions where people first play the creating condition (sessions 17–25). A possible explanation is that subjects who play first the creating condition may seek to maintain the same level of cooperation even after the creating frame has been removed. This result is consistent with Fig. 3. Finally, Table 4 indicates that contribution levels are higher under the highest provision point levels compared to the situation without provision point. A t-test indicates that there is no significant difference between the PP = 60 and the PP = 80. To summarize, in all treatments, the introduction of framing affects contributions significantly. Our Result 1 replicates Andreoni (1995), who found that subjects contribute more under the positive frame condition. The interesting point is that we extended this finding to the case of provision point public goods experiments.

45 40 35 30 25 20 15 10 5

45 40 35 30 25 20 15 10 5 0

0 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15

1

2

3

4

5

6

8

9 10 11 12 13 14 15

c28

m0

m28

70

70

Average group contribution

Average group contribution

c0

7

Periods

Periods

60 50 40 30 20 10 0 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15

50 40 30 20 10 0 1

2

3

4

5

6

7

8

9 10 11 12 13 14 15

Periods

Periods c60

60

m60

c80

Fig. 4. Average contribution per treatment in sessions 9–27 (pooled data).

M80

D. Bougherara et al. / Ecological Economics 70 (2011) 1200–1210

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Table 4 Determinants of contribution and framing effects in sessions 9–25 (random effect Tobit estimates). Dep.Var: ci,t Models

RE Tobit

RE Tobit

RE Tobit

RE Tobit

Sessions 9–25 Treat.

No provision point (1)

PP28 (2)

PP60 (3)

PP80 (4)

All treat. (5)

Maintaining Creating

Ref. 1.056⁎⁎ (0.474) −0.128 (0.802)

Ref. 2.067⁎⁎⁎ (0.471) 1.559⁎⁎

Ref. 3.260⁎⁎⁎ (0.631) 1.548⁎

Ref. 12.520⁎⁎⁎ (2.805) 16.647⁎⁎⁎

Ref. 2.838⁎⁎⁎ (0.342) 2.062⁎⁎⁎

(0.791)

(1.077)

(4.764)

(0.578) −1.040⁎⁎⁎ (0.278) 2.750⁎⁎

Creating*last 5 periods Order CM

(1.264) Ref. 1.241 (1.736) 4.312⁎⁎ (1.737) 6.693⁎⁎⁎

No PP PP 28 PP 60 PP 80 Last 5 periods Period Constant Obs Left cens. Right cens. Log likelihood

−1.091 (0.818) −0.46⁎⁎⁎ (0.079) 8.483⁎⁎⁎ (0.764) 1800 508 124 −4646.8

−1.343 (0.823) −0.32⁎⁎⁎ (0.079) 7.808⁎⁎⁎ (0.857) 1440 375 69 −3774.79

−2.311⁎⁎ (1.106) −0.678⁎⁎⁎ (0.106) 12.827⁎⁎⁎ (1.432) 1440 429 185 −3498.63

11.747⁎⁎ (4.795) −4.257⁎⁎⁎ (0.509) 33.064⁎⁎⁎ (6.337) 1440 584 631 −1798.04

(1.748) −0.113 (0.598) −0.786⁎⁎⁎ (0.057) 7.698⁎⁎⁎ (1.434) 6120 1896 1009 −14311.58

RE Tobit = random effects Tobit. ⁎⁎⁎ Significant at the 0.01 level. ⁎⁎ Significant at the 0.05 level. ⁎ Significant at the 0.1 level.

Result 2. Framing effects are significantly higher under PPM than under VCM. Furthermore, the positive framing effects increase with provision point levels.

4.3.1. Support for Result 2 Table 5 provides formal evidence of the existence of interaction effects between framing and provision points. The independent variables include dummy variables for the creating condition and for each provision point level. The “provision point” variable is a dummy variable that takes 1 if subjects play a treatment with a provision point and 0 otherwise. The interaction variable “creating*provision point” aims at measuring whether framing effects are more (or less) important under PPM treatments compared to the standard VCM without provision point. This variable captures a positive and significant coefficient, indicating that creating effects are higher under PPM than under VCM. The positive and significant coefficient associated with the variable “PP = 60” indicates that individuals contribute significantly more under the intermediate provision point than in a standard VCM in the maintaining condition. However the coefficients associated to the variables “PP = 28” and “PP = 80” are not significant, suggesting no significant difference between these provision point and a standard VCM under the maintaining condition. In contrast, the “PP28*creating”, “PP60*creating” and “PP80*creating” variables capture a positive and significant coefficient, indicating that contribution levels are higher under these provision point levels compared to the standard VCM under the creating condition. A t-test comparing the coefficients associated with the variables “PP60*creating” and “PP80*creating” indicates a significant difference, suggesting that the framing effect is higher for the highest provision point level. No significant difference is found between “PP60*creating” and “PP28*creating”.

4.4. How Increasing the Provision Point Affects Provision or Maintenance of the Public Good? The fact that provision points may have positive effects on contribution levels does not necessarily mean that it is enough so that the provision point is attained. In contrast, our data indicate that the probability of maintaining or reaching a provision point declines steadily when the provision point level increases. On average, people maintain the lower provision point (i.e. PP = 28) in 35% of cases in the maintaining condition. This probability is only 22% and 9.5% for PP = 60 and PP = 80, respectively. Similarly the probability of reaching a provision point decreases with the level of the provision point under the creating condition (55%, 56% and 29%, respectively for PP = 28, 60 and 80). Interestingly our data reveal that the reduction of the probability induced by the increase of provision point level is lower under the creating frame. These findings are summarized in Result 3. Result 3. The probability of providing (maintaining) a public good decreases significantly with the level of the provision point but to a lesser extent under the creating frame compared to the maintaining frame. 4.4.1. Support for Result 3 To further explore how the provision (or maintenance) of public goods is affected by the provision point levels and framing effects, we estimated Random Effects Probit models on the probability of attaining (maintaining) the provision point level. Results are reported in Table 6. The dependent variable takes the value 1 if group i reaches (maintains) the provision point in period t, and 0 otherwise. The independent variables include dummy variables for provision points PP = 60 and PP = 80. The omitted case is PP = 28. We also introduced

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Table 5 Determinants of contribution and provision point effects in all sessions (random effect Tobit estimates). Dep.Var: ci,t Models

RE Tobit

RE Tobit

RE Tobit

Treat.

All treat. (1)

All treat. (2)

All treat. (3)

Creating

1.298⁎⁎⁎ (0.473) Ref. 1.699⁎

1.303⁎⁎⁎ (0.471) Ref.

0.096 (0.494)⁎⁎ Ref.

−0.527 (1.572) 5.604⁎⁎⁎

−0.520 (1.575) 5.565⁎⁎⁎

(1.573) −0.335 (1.601)

(1.577) −0.371 (1.604)

1.870⁎⁎⁎ (0.704) 3.008⁎⁎⁎

1.864⁎⁎⁎ (0.702) 3.016⁎⁎⁎

(0.716) 6.649⁎⁎⁎ (0.775) −0.543⁎⁎⁎ (0.016)

(0.714) 6.660⁎⁎⁎ (0.774) −0.546⁎⁎⁎ (0.024) 3.453⁎⁎⁎

No PP PP PP*creating

(1.310) 3.586⁎⁎⁎ (0.572)

PP28 PP60 PP80

Interac. Var. PP28*creat PP60*creat. PP80*creat. Period

−0.544⁎⁎⁎ (0.016)

Creating*last periods Last periods Constant

7.471⁎⁎⁎ (1.130) 11,640

7.484⁎⁎⁎ (1.098) 11,640

(0.443) −1.824⁎⁎⁎ (0.407) 8.124⁎⁎⁎ (1.106) 11,640

RE Tobit = random effects Tobit. ⁎⁎⁎ Significant at the 0.01 level. ⁎⁎ Significant at the 0.05 level. ⁎ Significant at the 0.1 level.

a dummy for the creating condition as well as interaction variables “provision point x*creating” (with x = 60, 80). The left panel (columns (1) and (2)) displays the results of the RE Probit models. The right panel (columns (3) and (4)) reports the corresponding marginal effects of the random effect Probit models presented in columns (1) and (2), respectively. With respect to the reference treatment (i.e. PP = 28), we observe that the probability of maintaining the public good decreases when the provision point level increases. The probability decreases by 17.1 and 39.6 percentage points in PP60 and PP80, respectively with respect to the reference treatment with PP = 28 in the maintaining condition.9 Interestingly, Table 6 shows that the introduction of a creating frame has a positive effect on the probability of providing the public good. Column (4) shows that if the participants play under the creating condition, the probability is reduced by only 1.4 and 15.8 percentage points in PP = 60 and PP = 80, respectively compared to the reference treatment with PP = 28.

5. Discussion and Policy Implications Our aim in this study was to analyze the combination of two effects: the effects of framing and provision point levels by implementing provision point games under two different framing conditions (creating vs. maintaining conditions). 9 Using the results from Table 6 (column (4)), the calculations are: with respect to the reference state, we must add the coefficient − 0.171 of “PP60” to the coefficient 0.157 of “PP60*creating”.

Our main findings are the following. First, we generalized Andreoni's finding in the case of provision point public goods experiments showing that Andreoni's assumption still holds in provision point mechanisms. In all treatments, it is easier to promote cooperation when individuals are settled in a creating context rather than in a maintaining context. Such a result, although consistent with Andreoni's results, could be viewed as counterintuitive because it might initially be thought that it would be easier to maintain a public good than to create it. Second, we find that the probability of providing (maintaining) a public good declines with the level of the provision point but to a lesser extent under a creating frame. Third, our data show that framing effects are stronger under PPM than under VCM and increase with the provision point level. Our findings may be interpreted according to the loss aversion theory of Kahneman and Tversky (1979). A possible interpretation of these results, consistent with the loss aversion theory is that people may perceive as higher the disutility of losing all the tokens initially placed in the group account in the maintaining treatment compared to the disutility of failing to gain something by reaching the provision point in the creating treatment. As a consequence more people choose to withdraw their tokens and therefore less cooperative choices are made under the maintaining treatment than in the creating treatment. A number of topics remain for future research. We have interpreted our findings regarding stronger framing effects under PPM than under VCM according to the loss aversion theory. A direction for future research may be to go one step further in the investigation of the role of loss aversion. This may be done by relating our findings to precise individual measures of risk/loss aversion.10 For instance, one may ask subjects to make several binary risky choices under both a loss and a gain frame, (see De Martino et al., 2006). Another direction for future research would be to investigate whether our findings are affected by changes in the parameters of the games, in particular changes in MPCRs or in step returns (i.e. the ratio of the individual value of the public good to the individual share of the cost, see Croson and Marks, 2000; Cadsby et al., 2008). Indeed our results hold for given parameters and could differ for different MPCR or step returns. A further examination of this is called for. Finally, it could be also interesting to replicate our analysis in the context of a field experiment to check for the robustness of our findings in a field context. This questions the external validity of our findings. Of course our results are not the final word on the matter. To keep the experiment simple, we had to leave out many important features of the mechanisms presented above. For instance very much has to do with politics not economics, which by then, stand beyond the scope of this paper. Nevertheless, there are many reasons to believe that the framing effects we observed in our controlled laboratory may also exist in real life. Several studies have found that behaviors observed in laboratory experiments are correlated with behavior in the field (see for example Benz and Meier, 2008 in the context of donations). Although these games are stylized and simple, they can illustrate a number of important features of international actions. For instance our findings may be interpreted in line with the current debates about changes in the rules and policies provided by the Kyoto Protocol on Climate Change. The objective of the agreement negotiated in Kyoto, Japan in December 1997 was the “stabilization of greenhouse gas concentrations in the atmosphere at a level that would prevent dangerous anthropogenic interference with the climate system”. One policy included in the Kyoto Agreement and called the Protocol's Clean Development Mechanism was aimed at creating new resources via tree planting in order to absorb carbon dioxide from the atmosphere. However many countries have shed light on the paradoxical situation generated by the Kyoto Protocol, which gives credits to countries for planting trees to reduce carbon 10

We thank an anonymous referee for this remark.

D. Bougherara et al. / Ecological Economics 70 (2011) 1200–1210

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Table 6 Probability of attaining the provision point (RE probit). Dep.Var: proba. of attaining the provision point Models

Creating Order Provision point 28 Provision point 60 Provision point 80

RE probit All treatments except no provision point treatment

All treatments except no provision point treatment

(1)

(2)

(3)

(4)

0.696⁎⁎⁎ (0.096) 0.091 (0.097) Ref. −0.607⁎ (0.422) −2.315⁎⁎⁎

0.101 (0.096) Ref. −0.894⁎⁎ (0.434) −2.732⁎⁎⁎

0.158⁎⁎⁎ (0.037) 0.020 (0.023) Ref. −0.122⁎ (0.080) −0.349⁎⁎⁎

0.023 (0.023) Ref. −0.171⁎⁎ (0.080) −0.396⁎⁎⁎

(0.470)

(0.485)

(0.081)

(0.085)

Interact. Var. Provision point 28*creating Provision point 60*creating

Ref. 0.591⁎⁎⁎ (0.165) 0.819⁎⁎⁎

Provision point 80*creating Period Constant Obs

Marginal effects dy/dx

−0.059⁎⁎⁎ (0.005) 0.216 (0.304) 2580

(0.199) −0.059⁎⁎⁎ (0.005) 0.552⁎ (0.302) 2580

0.157⁎⁎⁎ (0.057) 0.238⁎⁎⁎ −0.013⁎⁎⁎ (0.002)

(0.076) −0.013⁎⁎⁎ (0.002)

2580

2580

RE Probit = random effects Probit. ⁎⁎⁎ Significant at the 0.01 level. ⁎⁎ Significant at the 0.05 level. ⁎ Significant at the 0.1 level.

dioxide emissions whereas nothing is really done to encourage countries not to engage in deforestation. Recently a group of countries called the “Tropical Rainforest” coalition has put forward an alternative proposition to preserve the environment by giving credits to countries not only for planting trees but also for protecting the current rainforest ecosystem from deforestation. As shown by our results, policies focusing on environmental goods to be maintained need to give more incentives to individuals than policies focusing on goods to be created. Acknowledgments We thank Tim Cason and the participants in the seminars at the 2007 French Meetings of Experimental Economics in Lyon and at the AFSE Meeting in Paris, France for their helpful remarks on a preliminary version of the article. The authors thank Elven Priour for the programming and organization of the sessions. Financial support from the Agence Nationale de la Recherche (ANR-08-JCJC-0105-01, “CONFLICT” project) is gratefully acknowledged. Appendix. General Instructions for C60–M60 You are now taking part in an economic experiment. If you read the following instructions carefully, you can, depending on your decisions and the decisions of others, earn a considerable amount of money. It is therefore very important that you read these instructions with care. The instructions we have distributed to you are solely for your private information. It is prohibited to communicate with the other participants during the experiment. Should you have any questions please ask us. If you violate this rule, we shall have to exclude you from the experiment and from all payments. During the experiment your entire earnings will be calculated in ECU (Experimental Currency Units). At the end of the experiment the total amount of ECU you have earned will be converted to ECU at the

following rate: 1 ECU = 0:02 Euro: Each participant receives a lump sum payment of 3 Euros at the beginning of the experiment. At the end of the experiment your entire earnings from the experiment will be immediately paid to you in cash. The experiment is divided into periods. In each period the participants are divided into groups of four. You will therefore be in a group with 3 other participants. Detailed Instructions for Periods 1–15 At the beginning of each period each participant receives 20 ECU. In the following we call this his or her endowment. Your task is to decide how to use your endowment. You have to decide how many of the 20 ECU you want to contribute to a project and how many of them to keep for yourself. The consequences of your decision are explained in detail below. Your endowment in each period is 20 ECU. You have to decide how many ECUs to contribute to the project by choosing a number between 0 and 20. After choosing your contribution you must press the ok button. Once you have done this, your decision can no longer be revised. After all members of your group have made their decision your screen will show you the total amount of ECUs contributed to the project by each of the four group members (including your contribution). This screen shows you how many ECUs you have earned. Your income consists of two parts: 1) the ECU which you have kept for yourself 2) the income from the project. Two cases are possible: (1) if the total amount allocated by the group (including your contribution) to the group account is higher or equals 60 ECU, then you will receive 40% of the total contribution of all 4 group members to the project (the total includes your own

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contribution). (2) If the total amount allocated to the group account is less than 60, then you receive nothing from the project. Your income in ECU in each period is therefore: (1) If the total amount to the group account is 60 your income is: (20-your contribution to the project) + 0.4 ⁎ (total contributions to the project). (2) If the total amount to the group account is less than 60, your income is: (20-your contribution to the project). The income of each group member from the project is calculated in the same way, this means that each group member receives the same income from the project. For example, suppose the total of the contributions of all group members is 70 ECU. In this case each member of the group receives 40%(70) = 28 ECU. If the total contribution to the project is 9 ECU, then each member of the group also receives nothing from the project. Detailed Instructions for Periods 16–30 In this new experience, you are still in a group with the 3 same other participants. At the beginning of each period a total amount of 80 ECU is allocated to the group account. This amount corresponds to a common project that gives each group member a payoff of 32 ECUs. Your task is to decide how many ECUs to withdraw from the group account between 0 and 20 ECUs. The consequences of your decision are explained in detail below. A total of 80 ECU is allocated to the group account that corresponds to a common project. You have to decide how many ECUs to withdraw from the project by choosing a number between 0 and 20. After choosing your contribution you must press the ok button. Once you have done this, your decision can no longer be revised. After all the members of your group have made their decision your screen will show you the total amount of ECUs that has been withdrawn from the project and the amount that remains in the project. This screen also shows you how many ECU you have earned. Your income consists of two parts: 1) the ECU which you have withdrawn from the project for yourself 2) the income from the project. Two cases are possible: (1) if the total amount remaining in the group account is at least 60 ECUs, then you will receive 40% of the total amount. (2) If the total amount remaining in the group account is less than 60, then you receive nothing from the project. Your income in ECU in each period is therefore: (1) If the total amount remaining in the group account is at least 60 your income is: (your withdrawal from the project) + 0.4 ⁎ (total amount remaining in the project). (2) If the total amount remaining in the group account is less than 60, your income is: (your withdrawal from the project). The income of each group member from the project is calculated in the same way, this means that each group member receives the same income from the project. For example, suppose the total withdrawal from the project is 10 ECUs. Then since 70 ECUs remain in the group account, each participant receives a payoff that is 40%(70) = 28 ECUs. If the total withdrawal from the project is 71 ECUs, then each member of the group also receives nothing from the project.

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