Impact of communication and information on a complex heterogeneous closed water catchment environment

Authors


Abstract

[1] This paper uses an experimental design that combines the use of an environmental levy with community involvement in the formation of group agreements and strategies to explore the impact of information and communication on water use in a complex heterogeneous environment. Participants in the experiments acted as farmers faced with monthly water demands, uncertain rainfall, possible crop loss, and the possibility of trading in water entitlements. The treatments included (1) no information on environmental consequences of extraction, (2) the provision of monthly aggregate environmental information, (3) the provision of monthly aggregate extraction information and a forum for discussion, and (4) the public provision of individual extraction information and a forum for discussion giving rise to potential verbal peer sanctions. To account for the impact of trade, the treatments were blocked into three market types: (1) no trade, (2) open call auctions, and (3) closed call auctions. The cost to the community of altering the natural flow regime to meet extractive demand was socialized through the imposition of an environmental levy equally imposed on all players.

1. Introduction

[2] Managing the environmental consequences of water extraction from rivers is complex and likely to require a combination of economic instruments and community involvement in coordinating aggregate extraction strategies [Common, 1995; Randall, 1981]. Water as a common pool resource is partially characterized by enforceable, exclusive and transferable rights to utilize a defined amount from the total available water. In addition, a substantial component of the water confers a mutually shared, environmental benefit to the owners of those extractive rights, which is both nonexcludable and subtractable [Ostrom et al., 1992]. Aggregate irrigation extraction imposes a reduction of those mutually shared benefits.

[3] This paper uses an experimental design that combines the use of an environmental levy with community involvement in the crafting of group agreements and strategies to explore the impact of information and communication on water use in a complex heterogeneous environment. Participants in the experiments acted as farmers faced with monthly water demands, uncertain rainfall, possible crop loss, and the possibility of trading in water entitlements. The treatments included (1) no information on the environmental consequences of water extraction, (2) the provision of monthly aggregate environmental information, (3) the provision of monthly aggregate extraction information and a forum for discussion, and (4) the public provision of individual extraction information and a forum for discussion giving rise to potential verbal peer sanctions. To account for the impact of trade, the treatments were blocked into three market types: (1) no trade, (2) open call auctions, and (3) closed call auctions. The cost to the community of altering the natural flow regime to meet extractive demand was socialized through the imposition of an environmental levy equally imposed on all players.

2. Experimental Assessment of Resource Policy Options

[4] Experimental economics provides a way to examine policy options under laboratory conditions and compare predicted outcomes with direct observations of economic behavior. Experimental economics yields a formalized, replicable approach to rapidly assess alternate policy directives, typically expressed as market outcomes, prior to catchment-wide implementation [Dinar et al., 1998]. The methodology provides a relatively inexpensive means of institutional analysis coupled with substantially reduced time horizons. Well-designed experiments allow for the evaluation of participant willingness to exchange, the stability of diverse institutional structures across an array of market conditions, and the efficacy of policy directives and highlight potential detrimental outcomes, which may compromise a water reform process. The application of experimental results can provide water authorities and decision makers with sufficiently robust information to circumvent or mitigate the consequences of inappropriate policy commitments, minimizing the time for trial and error and associated social expense [Murphy et al., 2000].

[5] Plott and Porter [1996] highlighted an additional advantage of evaluating and developing economic policies using experimental methods. Plott and Porter [1996] argued that designing an experiment requires specification of the details of a policy and the economic environment the policy is designed for. Accordingly, this process raises questions that might never be asked until the policy is actually implemented. “The very act of creating an experiment means that issues of timing, systems for gathering and reporting information, methods for resolving conflicts and uncertainties, and other institutional details that give policy life are specified in operational (as opposed to abstract) terms” [Plott and Porter, 1996, p. 237].

[6] Roth [1995] argued that policy experiments are generally motivated by the type of policy question that interests regulatory agencies and the experimental environment is typically designed to resemble those aspects of the naturally occurring environment that are the policy target. This enables economists to utilize the scientific method in formulating policy advice, especially when existing theories are inadequate.

[7] Researchers, including Dinar et al. [1998] and Murphy et al. [2000], have designed and employed experimental water markets to explore the policy implications of water trade in the western United States. Experimental water markets can be used to examine new market institutions, policy reforms, and even simulate environmental conditions such as periods of high rainfall or drought.

[8] On the basis of the theoretical research in experimental economics this research examines applied economic policy, which requires more realistic simulations of economic environments that depend closely on policies developed to account for the social, economic, and biophysical complexities of water as a common pool resource. Water extraction for irrigation in many river systems is adversely altering the flow pattern, resulting in an environmental externality. In this study the cost of the externality is socialized equally among the water extractors. This research explores the way farmers may react to such a common pool problem. The research is funded from a consortium of state and federal water authorities that requires high levels of contextualization to achieve external validity and thus acceptance of the research results. In the experiments, participants acted as farmers extracting water from a river system to grow an irrigated crop. As farmers, participants faced monthly water demands, uncertain rainfall, possible crop loss, and the possibility of trading in water entitlements.

3. Research Questions and Hypotheses

[9] The research questions and hypotheses explored were concerned with the common pool nature of riverine environments. Water extraction in many river systems adversely impacts on the flow regime, resulting in an environmental externality. Research by Ostrom [1990, 1998] suggests that common pool resources can be effectively managed if there are information and communication options available to those using the resource. Options for sanctions imposed on those who default on a group strategy are also possible and may reinforce cooperative strategies [Ostrom et al., 1992; Posner and Rasmusen, 1999]. This research builds on the work by Ostrom et al. [1992] and Posner and Rasmusen [1999] by questioning in a context-specific laboratory environment the following hypotheses.

[10] Hypothesis 1 is as follows: Providing aggregate extraction information will not significantly modify extraction levels to produce greater accordance with the environmental flow regime. The notion is that providing only aggregate information on extraction, a common practice, is too crude to provide individual players with sufficient information to consider coordination possible. Aggregate extraction above the environmental target, for example, may result in all players reducing their extraction, which because of a lack of coordination, may result in an equal problem of less than required flow regime.

[11] Hypothesis 2 is as follows: Allowing communication between players on extraction will allow social contracts to form to minimize the environmental externality. The coordination problem proposed in hypothesis 1 may be overcome by providing communication between the players on issues of extraction.

[12] Hypothesis 3 is as follows: Providing individual extraction information and opportunities for players to communicate will further enforce the social contract and minimize the environmental externality. The notion is not to enforce a penalty, but through social pressure arising from providing individual extraction information, players will conform to the environmental flow objective. In essence, the public provision of individual extraction information and a forum for discussion will give rise to potential verbal peer sanctions.

[13] The ability of players to coordinate their extractions or free ride will, in part, depend on the stability of the distribution of water extraction entitlements through time. At the same time as governments are exploring social interactions of this nature they are also expanding markets for water extraction entitlements as a mechanism for promoting more efficient use of available water supplies under a variety of auction structures including closed and open call auctions. In a closed call market, potential buyers submit sealed bids to buy, and potential sellers submit sealed offers to sell. The market is “called,” and trades are executed by a clearinghouse, in this case the water authority, at a competitive equilibrium price. The authority notifies successful traders and releases the market price and volume traded information only. In open call markets, all the bids and offers are made public. Market theory would suggest that increasing market knowledge during an open call trading period would increase the level of trade and market efficiency. An open call auction is one in which the bids to buy and sell are publicly available as they are lodged.

[14] The short-term leasehold water markets, which dominate water trade in countries such as Australia, are susceptible to changes in localized weather conditions and crop-watering demands during each season. These markets therefore introduce a level of uncertainty into rates of water extraction and thus may confound strategies to coordinate or promote free riding. The working hypothesis is that the introduction of a closed call auction will result in higher levels of economic efficiency compared to no trade, and an open call auction will result in further increases compared to a closed call auction. Each treatment was therefore blocked to take account of the impact of trade and auction structures.

[15] The hypotheses and associated issues led to the development of four treatments within each market environment. The experimental treatments comprised three incremental sets of information levels presented to the participants and a no-information control. The first treatment tested for behavioral changes of participants when presented with real time data of aggregate abstractions compared to the natural flow regime of the experimental setting. The notion is that simultaneously informing the group of monthly natural flows, monthly aggregate extractions, and the associated environmental levy will encourage participants to coordinate extraction to reduce subsequent environmental costs.

[16] The second treatment explored the effect of group communication and the development and implementation of voluntary, cooperative social contracts to reconcile the difference between natural flows and aggregate abstractions. In this context the traders were given time to discuss the nature of the levy prior to commencement of the experiment. Players were given the option of either equal proportional changes or individually determined changes in monthly extraction volumes. Both experimental groups decided by consensus to implement voluntary individual changes in monthly extraction levels. Individual behavioral responses were expressed experimentally as monthly aggregate extraction volumes. Each month, following a period of discussion, participants voluntarily committed to water extraction targets prior to the announcement of their actual monthly farm-specific rainfall, thereby internalizing the risk of rainfall variability on the individual participants. The research hypothesis predicts that monthly discussion sessions will reduce the environmental cost of aggregate extractions.

[17] Finally, the disclosure of individual extraction levels as a form of sanction, therefore reinforcing agreed aggregate extraction targets, will facilitate further reductions in the level of the environmental cost. The hypothesis therefore is that the treatment introducing identification of contract defaulters and the possibility of verbal peer sanctions will reduce the level of environmental costs.

4. Experimental Design

[18] A complete block design was used with the four common pool resource treatments and three market structures (including a no-trade structure). The experimental design is presented in Table 1. Two groups of 12 traders were involved in simultaneously replicated experiments. Each group traded for 1 year for each treatment and block combination, a total of 12 years of trading, each year taking approximately 2 hours. An experimental session simulated a whole year of monthly trading in the water markets. In aggregate a total of 24 years of water trade and extraction was simulated during the experiments. Student subjects were recruited from Griffith University (Brisbane, Australia) through advertising billboards and posters placed across the campus and a designated website.

Table 1. Experimental Designa
TreatmentsNo InformationAggregate InformationAggregate Information and DiscussionAggregate Information, Discussion, and Sanctions
  • a

    Note that sessions were run concurrently and represent 12 monthly trading periods.

No tradetwo sessionstwo sessionstwo sessionstwo sessions
Closed calltwo sessionstwo sessionstwo sessionstwo sessions
Open calltwo sessionstwo sessionstwo sessionstwo sessions

[19] As the experimental environment was quite complex and the students had no natural affinity with the issues at hand (recruited from the student population at an urban university), the students were taken through an extensive series of training sessions in the experimental procedures and protocols prior to the experiment. The students were well trained in the principles of trading water entitlements and managing a model farm. The students were not exposed to the more salient issues, such as an environmental externality and ability to communicate, prior to the experiment formally beginning. Throughout the experimental sessions, instructors were on hand to answer procedural questions.

5. Market Environment

[20] The experimental environment involved players acting as irrigators with options concerning the management of a model farm inclusive of options for trading water. Participants accessed treatment-specific instructions by logging on to the experimental Web site, scrolling through a PowerPoint™ slide series, and following the prescribed screen prompts. A complete set of PowerPoint instructions are available from the author on request The slideshow presentations varied according to the treatment combination in each session, with slides added for each successive treatment. Participants accessed a computer network link at the end of the instruction slides that allowed them to log on to the experiment session. The experimental sessions were conducted using an experimental water-trading program known as Mwater, an experimental economics software package available for use by staff, students, and visitors to the laboratory at Griffith University. Through the Mwater package, participants viewed their general farm characteristics, including their water allocation and crop water requirements. The package also allowed them to trade in an open or closed market environment, view their monthly and year-to-date water usage and income tables, and view information on extraction levels according to the treatment requirements of the experiment.

[21] Participants were not allowed to talk to each other except in experimental sessions where communication was specified by the treatment. Participants were provided with a calculator if requested and were also able to use a spreadsheet to perform farm-specific calculations.

5.1. Farm Characteristics

[22] Each of the 12 participants in each experimental session was provided with a unique set of model farm characteristics that governed the value of water used on their farm (information on the individual farm characteristics is not reported in order to maintain the integrity of the data for future experiments; further information on the farm characteristics can be obtained from the authors), the volume (megaliters (ML), 1 ML = ∼1.23 acre-feet of water) of allocated water for the year, farm-specific historic median rainfall, and maximum and minimum water requirements for the farm-specific crop in each month. Isolating the important decision variables involved consultation and trials with a large number of farmers in focus groups. Focus group meeting and trial field experiments were held at Yanco in New South Wales and Shepparton in Victoria. Approximately 60 farmers attended in total. Information was provided both as yearly totals and as monthly figures. The totals, such as the size of each farm's remaining water allocation, were updated monthly as water was applied to the farm's crop and as water was bought or sold. Table 2 displays typical information about each model farm's characteristics that is provided to the participants from the start of the water year. All values except for the “marginal value of water” are updated monthly. The general consensus of the farmers involved in field trials during development was that state and federal agencies provide them with typical farm budget data (e.g., gross margins). It is this data that farmers focus on in the first instance, and it is up to the farmers to realize the increasing opportunity cost of not continuing to irrigate once the decision to progressively invest water in a crop is made. As this is something that is learnt by farmers (especially when they suffer crop loss) rather than information provided to them, the advice given was to leave the reported marginal value of water constant and include the notion of increasing marginal value through the threat of crop loss and associated lost income.

Table 2. Typical Farm Characteristics
CharacteristicValue
Water supply available960 ML
Historic usable rainfall to end of year498 ML
Estimated maximum water needs to end of year1275 ML
Estimated minimum water needs to end of year1020 ML
Marginal value of water$97
Traders income total$10

[23] Table 3 is an example of a water use table displaying water requirements for each month. Actual rainfall is provided before each irrigator decides how much water to use from their allocation in that month. Allocated and total water use are displayed for all previous months.

Table 3. A Typical Water Use Table
MonthHistoric Median RainfallMaximum Water UsageActual RainfallAllocated Water UsedTotal Water UseMinimum Crop Water RequirementsQuantity SoldQuantity Bought
October5221449148197171 200
November3619838  158  
December48186   149  
January46169   135  
September00   0  

5.2. Crop Loss

[24] Players faced uncertainty of rainfall and possible crop loss. “Crop loss” refers to any lost potential income caused by irrigating less than the minimum crop water requirements. If monthly minimum water requirements were met, the whole crop was maintained. However, if total water use was less than the minimum crop water requirements in any month, then the area of crop was proportionally reduced. The potential income from the irrigated land left fallow was lost for the whole year. New minimum and maximum water requirements were then provided for the rest of the year. Rainfall was also reduced accordingly.

5.3. Income Calculations

[25] Participants received A$10 turn up payment plus the traders' income earned during each experiment. The monthly farm income equaled total water usage times their marginal value of water, less crop loss, plus the income from the sale of water less the cost of water bought. Through a series of exchange rates, farm incomes were converted to traders' income in order to account for differences in farm sizes and characteristics. Table 4 displays a typical farm income table, including the values for market clearance prices and farm and trader's income.

Table 4. Typical Farm Income Table
 Value
MonthOctober
Total water usage197
Monthly income from crop19109
Crop loss0
Equilibrium price60
Cost of water bought12000
Total monthly income7109
Trader's income7.12

[26] With increasing community involvement and empowerment of self-regulation as a mechanism for implementing water policy it is necessary to explore the level of accordance with group agreements and the impact of supplying environmental information. The nature of the damage caused to riverine ecosystems is a social cost borne by all in the community. In the experiments this is measured by the value of the environmental levy.

5.4. Environmental Levy

[27] In the experiments an environmental levy was introduced to create an experimental environment in which an individual's payoff depended both on their own actions and the actions of all other members of their group. The experimental river system consists solely of the 12 players' farms. The important environmental attribute of the system is located upstream of the farms. The flow upstream is completely dependent on the monthly aggregate extractive demand of the players. Consistent with the utilization of a common pool resource, an individual player's final payment was comprised of the proceeds from their farm income (namely, farm and trading activities) less their proportional share of the costs of a change in riverine environmental services. A change in environmental services is measured as a change in natural flows resulting from the extraction of irrigation water. The monthly volume of natural flows reflects the experimental catchment's historic median environmental flows and is illustrated in Figure 1. The imposed environmental levy creates a system of incentives in the experiment consistent with the interdependency imposed by environmental externalities.

Figure 1.

Historic median environmental flows.

[28] The levy was one trader dollar per 100,000 units, calculated as the squared difference between aggregate extraction and historical median environmental flows as shown in Figure 1.

equation image

The value of the environmental levy reflects increasing marginal environmental damages as the divergence between natural flows and extraction increases (Figure 2). This means that each additional ML of allocated water used by any individual farmer had a proportionally greater environmental cost.

Figure 2.

The calculated value of the experimental environmental levy.

6. Results

[29] This section reports the findings of the research. Three metrics were used to evaluate the experimental results: (1) the level of accordance with environmental targets, measured by the environmental levy, (2) the average farmer income measured by trader's income, and (3) the ratio of trader's income to environmental levy. Received wisdom suggests that the implications of laboratory findings should be interpreted cautiously beyond the specific institutional setting of the experiment.

6.1. Impact of the Provision of Information, Discussion Forums, and Sanctions on Meeting Environmental Targets

[30] It is expected that the level of environmental damage caused by water extraction will increase as a result of trade and decline with information, discussion, and individual extraction disclosure. Table 5 presents the combined results of the 2 years of experiments.

Table 5. Information/Communication and Trade Treatments: Environmental Levy Mean Valuesa
 No Information, $AggregateInformation, $Aggregate Information and Discussion, $Individual Information and Discussion, $Average
  • a

    Information/communication treatment means with the same letter in parentheses were not statistically different at α = 0.05. Trade treatment means with the same letter in parentheses were not statistically different at α = 0.10.

No Trade5.485.032.713.304.13
Closed Call7.626.284.526.206.16 (d)
Open Call5.758.804.514.445.88 (a)
Average6.28 (a)6.70 (a)3.91 (a)4.65 (ab) 

[31] Tisdell [2001], using linear programming models, found that trade exacerbates the differences between extractive and environmental flow regimes. In this study, statistical analysis of the environmental levies arising from the experiments found significant differences in the levies between the trade and no-trade treatments at α = 0.063 but no statistical difference in environmental levies between closed and open call markets. The results of the experiments were statistically analyzed using analysis of variance techniques and least significant difference post hoc tests as appropriate. Compared to no-trade treatments, the closed call auction experiments resulted in the average levy increasing from $4.13 to $6.16.

[32] Coordinating individual actions to converge with environmental targets is difficult if aggregate extraction information is provided without a means of communication. Providing only aggregate information did not produce a statistically significant change in the environmental levy compared to no information, whereas providing aggregate information with communication produced a statistically significant reduction in the environmental levy compared to no information or aggregate information only. It was hypothesized that the public provision of individual extraction information and a forum for discussion would give rise to potential verbal peer sanctions and greater conformity to the environmental flow target. This did not occur. The environmental levy in experimental environments involving individual information and discussion were not statistically different to environments where participants were provided with no information or aggregate information with or with communication. In summary, it appears that the environmental damage arising from water extraction is minimized in environments where there is no trade and farmers are provided with aggregate extraction information and a forum for discussion.

6.2. Impact of the Provision of Information, Discussion Forums, and Sanctions on Aggregate Traders' Income

[33] Traders' incomes were calibrated to ensure equal potential income and used to compare the impact of the various treatments and auction structures. Table 6 presents the average trader's income for each treatment/block combination. In terms of trade, there was no statistical difference in the average income earned when there was no trade compared to experiments involving closed call auctions. While there was also no statistical difference in average income between closed and open call auctions, open call auctions produced a statistically larger average mean income compared to that earned in no-trade experimental settings.

Table 6. Information/Communication and Trade Treatments: Mean Trader's Incomea
 No Information, $Aggregate Information, $Aggregate Information and Discussion, $Individual Information and Discussion, $Average, $
  • a

    Treatment means with the same letter in parentheses were not statistically different at α = 0.05.

No Trade38.1039.5543.2042.8840.94 (a)
Closed Call40.7144.2644.2846.1743.85 (ab)
Open Call45.2443.2249.6747.5946.43 (b)
Average41.35 (d)42.34 (de)45.72 (e)45.55 (e) 

[34] Discussion with aggregate or individual information led to statistically higher levels of average traders' income compared to no information. In the same vein as the environmental levy, there was no statistical difference in average income between no information and the provision of aggregate information. There was no statistical difference in average income between the provision of aggregate information, with or without discussion, and the provision of individual information with discussion.

[35] What these results suggest is that the provision of aggregate information alone does not contribute to improvements in either the environmental flow or average income, that trade results in worsening environmental conditions and, in the case of closed call auctions, that it does not significantly improve average incomes.

6.3. Ratio of Income and Environmental Levies

[36] Trade-offs between maximizing extractive income and riverine environmental flow regimes is common. One metric to measure that trade-off is the income per unit of environmental damage. It can be seen from Table 7 that providing aggregate information and a forum for discussion without trade maximized the return per unit of environmental damage. Further, compared to aggregate information and discussion, providing individual information provided lower returns per unit of environmental damage and was therefore counter productive in all cases. The worst return per unit of environmental damage results from providing aggregate information in an open call trade environment.

Table 7. Environmental Ratios
TreatmentMarket TypeIncomeLevyRatio
Aggregate information and discussionno trade43.202.7115.94
Individual information and discussionno trade42.883.3013.00
Aggregate information and discussionopen call49.674.5111.00
Individual information and discussionopen call47.594.4410.72
Aggregate information and discussionclosed call44.284.529.80
Aggregate informationno trade39.555.037.87
No informationopen call45.245.757.87
Individual information and discussionclosed call46.176.207.45
Aggregate informationclosed call44.266.287.05
No informationno trade38.105.486.96
No informationclosed call40.717.625.34
Aggregate informationopen call43.228.804.91

6.4. Environmental Agreements and Accordance

[37] During the discussion period, participants were able to form agreements on aggregate extraction. Information on their aggregate agreement and aggregate extraction was provided. In the final series of experiments, individual agreement and extraction variations were provided. The level of accordance reported in Table 8 is based on the inverse sum squared difference between the monthly aggregate agreement and aggregate extraction. The level of accordance with the agreement was greatest in no trade with individual information and discussion experiments. Provision of aggregate information led to higher levels of accordance in closed call experiments compared to open call experiments. In contrast, open call experiments produced higher levels of accordance in experiments where individual extractions were disclosed. Disclosure of the agreed and actual individual extractions improved the level of accordance in the no trade and open call experiments but not in the closed call experiments. The lowest level of accordance occurred in open call market with aggregate information experiments.

Table 8. Level of Accordance With Agreementsa
 Aggregate Information and DiscussionIndividual Information and Discussion
  • a

    Accordance measure = equation image.

No trade0.01650.0241
Closed0.01280.0100
Open0.00570.0133

7. Conclusion

[38] Experimental economics yields a formalized, replicable approach to rapidly assess alternate policy directives, typically expressed as market outcomes, prior to catchment-wide implementation [Dinar et al., 1998]. The methodology provides a relatively inexpensive means of institutional analysis coupled with substantially reduced time horizons. This research examined applied economic policy, which requires more realistic simulations of economic environments that depend closely on policies developed to account for the social, economic, and biophysical complexities of water as a common pool resource. To enable this complex analysis to occur, this project has developed a number of methodical systems, inclusive of extensive survey design and analysis to experimental economics.

[39] The primary hypothesis of this study was that the level of environmental damage caused by water extraction will increase as a result of trade and decline with information, discussion, and individual extraction disclosure. Statistical analysis of the environmental levies arsing from the experiments found significant differences in the levies between the trade and no-trade treatments. Hypothesis 1 states that providing aggregate extraction information alone will significantly modify extraction levels to produce greater accordance with the environmental flow regime. Hypothesis 2 states that allowing communication between players on their extraction intentions will allow social contracts to form and as a corollary minimize the environmental externality. In the experimental setting of the research it was found that the provision of aggregate extraction information without a formalized and appropriate forum for communication is not effective in promoting players' coordinating their extractions to avoid environmental damage. Disclosure of individual information is also not effective in modifying people's extractions to be more in accordance with environmental targets. The environmental damage was minimized by providing aggregate extraction information and a forum for discussion without a trading environment. Average traders' income was maximized providing information on aggregate extraction, environmental targets, and a forum for discussion in an open call market. Providing aggregate information and a forum for discussion without trade maximized the return per unit of environmental damage.

[40] Hypothesis 3 states that providing individual extraction information and opportunities for players to communicate will further enforce the social contract and minimize the environmental externality. The provision of information, be it market information or extraction information, should modify behavior in an environment such as this. An open call auction, where the bid values are common knowledge, should produce greater market efficiency compared to a closed call auction. Information on extraction and, in particular, on others' individual extraction levels should promote greater accordance with the environmental objective and minimize free riding. This research found that the provision of individual information, compared to the coarser aggregate information, was found to be counterproductive. Knowing that individual extraction levels were to be public resulted in the groups setting less stringent reduction targets. Ostrom et al. [1992] argues that providing avenues for communication should assist in dealing with public good problems of the type explored in this paper. This research found that even in a quite complex experimental environment, communication combined with aggregate information assisted players in coordinating their individual actions to minimize an environmental externality arising from their aggregate behavior.

[41] A generally received wisdom notes that the implications of laboratory findings should be interpreted cautiously beyond the specific institutional setting of the experiment. In applying the findings of this research to specific catchments one should always be mindful of the particular characteristics of the catchment and the transaction costs and possible institutional constraints and opportunities associated with providing an effective forum for group communication and the dissemination of information.

Acknowledgments

[42] The financial support of the Cooperative Research Centre for Catchment Hydrology and Land and Water Australia is gratefully acknowledged. The authors would also like to thank the research assistants, Nadine Brodeur and Paul Locke, for their work on the project. We would also like to thank the two anonymous reviewers for their comments.

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