AGGLOMERATION BONUS PERFORMANCE:AN EXPERIMENTAL STUDY ON LOCAL NETWORKS
SIMANTI BANERJEE, FRANS P. DE VRIES, NICK HANLEY, AND DAAN P. VAN SOEST
The agglomeration bonus is an incentive mechanism to induce adjacent landowners to spatiallycoordinate their land use for the delivery of ecosystem services from farmland. This paper useslaboratory experiments to explore the performance of the agglomeration bonus in achievingthe socially optimal land management configuration in a local network environment where theinformation available to subjects varies and the strategic setting is unfavorable for efficient coordi-nation. The experiments indicate that if subjects are informed about both their direct and indirectneighbors’ actions, they are more likely to produce the socially optimal configuration. Thus effec-tiveness of the policy can be improved by implementing information dissemination exercisesamong landowners. However given the adverse strategic setting, increased game experience leadsto coordination failure and optimal land choices only at the localized level independent of theinformation available to subjects. Thus success of the agglomeration bonus scheme on real land-scapes will have to take account of the roles of both information and experience on participantbehavior.
JEL codes: C72, C91, C92, D83, D85, Q25, Q57.
Improvements to the delivery of ecosystemservices from farmland such as habitat pro-tection, biodiversity conservation, carbonsequestration, and pest management canbe obtained by adopting pro-conservationland uses on properties otherwise devoted toprofit-based agriculture (Swinton et al. 2007).Adopting such pro-conservation land uses istypically costly to the landowner/farmer,meaning that they may require finan-cial compensation for implementing them
Simanti Banerjee is visiting assistant professor of economicsin the Department of Economics, Oberlin College. Frans P.de Vries & Nick Hanley are professors in the Division of Eco-nomics, Stirling Management School, University of Stirling.Daan P. van Soest is professor in the Department of Eco-nomics, Tilburg University. This research was funded by theEuropean Investment Bank (EIB) under the EIB-UniversityResearch Action Programme. The findings, interpretations,and conclusions presented in this article are entirely those ofthe authors and should not be attributed in any manner tothe EIB. The authors thank editor David A. Hennessey, threeanonymous referees, Mirko Moro, James Shortle, AnthonyKwasnica, and participants at the International Workshopon Mechanism Design and the Environment (Royal Societyof Edinburgh, May 2013) for their insightful comments. Anyerrors remain those of the authors. Laboratory support forthe experiments was provided by the Laboratory for Eco-nomics, Management, and Auctions (LEMA), Smeal College ofBusiness, Pennsylvania State University.
(Armsworth et al. 2012). As a result, pay-ment for ecosystem services schemes havebeen introduced by conservation agencies inmany countries to incentivize these changesin land management (Wunder 2005). Forexample, the Conservation Reserve Programin the United States has disbursed nearly$26 billion to retire 36.8 million acres offarmland from agriculture to reduce soilerosion and preserve approximately 1.8 mil-lion acres of wetland habitats (Cowan 2010;Ferris and Siikamäki 2009; Kirwan, Lubowski,and Roberts 2005). In Europe, an increas-ing fraction of total spending on agriculturegoes to funding agri-environmental schemes(Cooper, Hart, and Baldock 2009), with fur-ther increases planned under reforms to thepost-2013 Common Agricultural Policy.
In the context of increasing the environ-mental benefits from farmland management,an important issue is that the spatial coor-dination of land management efforts cangenerate environmental benefits more effec-tively for an important set of ecological andbiodiversity quality indicators (Hanley et al.2012). Encouraging landowners to enrolladjacent land parcels, which are of high
Amer. J. Agr. Econ. 96(4): 1009–1029; doi: 10.1093/ajae/aau048Published online June 16, 2014
ecological value, by attaching greater sign-uppayments to them has been shown to gen-erate higher environmental benefits, such asimproved biodiversity benefits from spatiallycontiguous habitats, than scenarios wherethe incentives are not spatially differentiated(Drechsler et al. 2010; Wätzold et al. 2010).In many instances, land management of geo-graphically proximate (or even adjacent)parcels/properties for creating contiguoushabitat of at least a critical minimum size andestablishing connections between patchesto create habitat corridor linkages, whichfacilitate species mobility, may be beneficialfor biodiversity conservation (Dallimer et al.2010; Margules and Pressey 2000). Further,spatial clustering of organic farm operationscan lead to lower negative impacts on waterquality by minimizing runoff, can mitigatelosses from retiring land to create bufferspreventing pesticide spillover from neighbor-ing conventional farms, and can even reducecertification costs of organic farmers (Parkerand Munroe 2007). Finally, creation of largecontiguous areas of noncrop habitat for nat-ural predators in the landscape can be moresuccessful in eradicating pests than strate-gies that ignore such spatially agglomeratedhabitat management (Landis, Wratten, andGurr 2000; Zhang, van der Werf, and Swinton2010).
One approach to achieving spatial coor-dination of conservation land uses and landmanagement is the agglomeration bonus(AB) subsidy scheme (Parkhurst et al. 2002;Parkhurst and Shogren 2007).1 The AB is atwo-part payment scheme comprising a baselevel compensation for all participants and atop-up bonus that they receive if their neigh-bors also participate and implement similarpro-conservation land-use practices on theirproperties. By rewarding coordinated actionsacross space, land management decisionsof neighboring landowners under the ABscheme can be considered to be strategicinteractions in a coordination game. Thisgame has multiple Nash equilibria that canbe Pareto ranked in terms of payoffs. Theexistence of multiple equilibria can, however,give rise to coordination failure. Experi-mental evidence provided by Parkhurstand Shogren (2005, 2007) and Warziniack,
1 An alternative approach investigated in the literature isauctions for spatially coordinated land management projectprocurement (e.g., Windle et al. 2009).
Shogren, and Parkhurst (2007) indicatesthat spatial coordination is fostered by (a)repeated interaction between players duringwhich they become increasingly familiar withthe game and are able to view the land choicenetworks produced as a result of everyone’schoices, (b) simple spatial targets to whichparticipants can coordinate with relative ease,and (c) nonbinding preplay communicationbefore making a choice. Successful coordina-tion on socially desirable land-use outcomesis also more likely on landscapes with fewerparticipants because of the difficulty ofcoordination in larger groups (Banerjee,Kwasnica, and Shortle 2012).
A key issue that has received limited atten-tion in the AB literature, and that forms thefocus of this article, is that the outcome ofstrategic interactions between landownersdepends on the amount of information avail-able to them about other landowners’ landmanagement choices. This article reportsresults of a laboratory experiment that variesthe information each participant receivesabout the land-use decisions others makewithin the purview of an AB scheme. Ourinterest in this issue is motivated by boththe nature of relationships within farm-ing communities and the existing scientificliterature on equilibrium selection and indi-vidual behavior in coordination games.Interpersonal relationships in agriculturalcommunities are a product of socioeconomicties and the private properties’ locations onthe farming landscape. Farmers may rou-tinely lend and borrow machinery to/fromneighbors, lobby together to influencelocal or national policy determination, orbecome members of the same (regional)input-purchasing and marketing cooperatives(Hanson et al. 2004; Parker and Munroe2007). These ties facilitate the generation andflow of information that is conducive to coop-eration with respect to (local) biodiversityand natural resources management (Prettyand Ward 2001; Pretty and Smith 2004;Schusler and Decker 2003; Isaac et al. 2007).
Under the AB scheme, where theeconomic returns to farmers from land man-agement actions are a product of strategicinteractions with their neighbors, varying thelevels of information available to a farmerabout their neighbors’ actions is likely tochange their land-use decisions and con-servation payments earned. The literatureon the impact of information on individ-ual decisions in strategic settings supports
Simanti Banerjee et al. The Impact of Information Provision on Agglomeration Bonus Performance 1011
this claim. Experimental studies suggestthat providing more information to sub-jects increases economic efficiency in termsof Nash equilibria selected in coordina-tion games (Berninghaus and Ehrhart 2001;Devetag 2003) and trust games (Bracht andFeltovich 2009). Yet Wilson and Sell (1997)find that more information reduces efficiencyin public good games, whereas in the study byDuffy and Feltovich (2002), there is no signif-icant impact of providing information aboutothers’ choices on game outcomes. Thus,the impact of information on choices andthe Nash equilibria selected is a function ofthe nature of the strategic environment andthe features of the game itself. Therefore, indetermining the effectiveness of an AB-basedpolicy scheme in delivering environmen-tal benefits through spatially coordinatedland management, we need to explicitly con-sider the role of information variation onlandowners’ land-use decisions.
For this purpose, we analyze the impact ofvarying the information available to studentsubjects who assume the role of landownersin a laboratory experiment. The labora-tory allows us to exercise control over thestrategic environment—the testbed (Plott1997)—and to evaluate the impact of theinformation treatment on land manage-ment decisions and types of spatial patternsproduced. The controlled and context-freelaboratory environment permits the “wind-tunnel testing” of the AB scheme for internalvalidity and analysis of general principles ofhuman behavior under the treatment condi-tions (Schram 2005) before it can be tested inricher field contexts with actual landownerswhose motivations for participation (or not)in conservation programs have both eco-nomic and noneconomic drivers (Bowers andLane 2009; Sheeder and Lynne 2011).
The experiments involve subjects arrangedon a circular local network where eachsubject is directly linked to a subset of allindividuals in the group (a direct neighboreach in the clockwise and anticlockwisedirection) and indirectly to everyone elsethrough their direct linkages (Jackson 2010).Within this network setup, we vary the infor-mation subjects receive by way of feedbackafter they have made a choice in the ABcoordination game. In the baseline controlsessions, subjects obtain information aboutthe choices and payoffs of their two directneighbors. This information feedback formatis similar to those implemented in prior AB
experiments. In the treatment sessions, sub-jects’ information sets additionally includeknowledge about the choices and payoffsof their closest indirect neighbors (i.e., theirdirect neighbors’ direct neighbors). This tre-atment specification is different from existingAB research and is motivated by the factthat, although people may be aware of thestrategic interactions within their closestdomain of interaction (i.e., their neigh-bors, friends, and/or networked partners),they usually do not have full informationabout all relevant strategic interactions inthe economy or within their social networkbeyond this closest domain (Alós-Ferrer andWeidenholzer 2008). Moreover, it is quitelikely that the impact of indirectly linkednetworked individuals’ choices on a singleplayer’s behavior is decreasing with the dis-tance between them. Given these factors,our experimental treatment investigates therole of the extra feedback information onthe emergence and persistence of efficientcoordination and effective ecosystem ser-vices provision in a strategic AB policyenvironment.
Note that the impact of more informationis ex ante unclear. Receiving informationabout actions selected by one’s direct andindirect neighbors may facilitate coordinationon the efficient Nash equilibrium. But theopposite outcome may be obtained as well—if one observes that the more distant subjectdid not choose the Pareto efficient strategy,one may anticipate that one’s direct neighbormay also decide the same, implying that oneis better off refraining from choosing the effi-cient strategy too. Our experimental resultsindicate that providing more informationproduces a significant difference in subjectbehavior and resultant AB configurations.Overall there is more efficient coordinationin the groups with more information rela-tive to those where information exchange islimited to direct neighbors only. The positiveimpact of extra information on coordinationis quite substantial, but we also find that,given the parameterization of our game, theeffect is still not large enough to prevent thedecrease in the share of subjects coordinat-ing on the Pareto efficient equilibrium overtime. Although in early periods of the exper-iments more information results in a largershare of subjects coordinating on the efficientNash equilibrium, with repeated interac-tion subjects’ behavior switches toward theinefficient Nash equilibrium with efficient
coordination persisting at the localized levelonly.
The Model
Consider K players, indexed i = 1, . . . , K,representing landowners, each of who has afixed position on a landscape represented bya circular local network. This network repre-sentation simultaneously introduces a spatialcomponent into the strategic setting and cap-tures the features of farming communities inwhich social networks play an important rolein sustainable resource management (Bodinand Crona 2009). On this circular landscapethe neighborhood structure is symmetricwhereby all K landowners have two directneighbors: one each in the clockwise andanticlockwise direction.2 These two individ-uals make up the local neighborhood of alandowner. Landowners are indirectly linkedto other networked individuals by their directneighbors. This network is illustrated infigure 1.
A landowner’s choice set in the AB gameis related to how they manage their land.Each landowner i owns one plot of landand can choose between two land manage-ment options, σi = G, N . Option G refers toconservation management on agriculturalland (“land sharing”) (Balmford, Green, andPhalan 2012), and N refers to retirement ofcropland such as under the ConservationReserve Program with land being convertedto nature farming, what Balmford, Green,
2 Because there are no edge effects, using a circular networkstructure implies that all subjects face identical decision prob-lems. This ensures that we are able to isolate the impact ofthe information treatment (that changes the subjects’ strategicuncertainty in the coordination game) on choices and AB per-formance without having to worry about potential confoundingproblems arising from subjects having different levels of strategicuncertainty owing to a varying number of neighbors.
and Phalan 2012 call “land sparing.” Bothland management options thus provideecosystem services, but the N type more sothan G.3
Let us now specify society’s benefits fromenvironment-friendly land managementunder the two options G and N . Any par-cel of land under either land managementoption yields ecosystem service benefits,s(σi), and let these “stand-alone” benefits belarger under N than under G.4 Let us assumethat s(G) = 5 and s(N) = 10. Environmentalagglomeration benefits exist for both typesof land management options. We assumethat these benefits are larger for N than forG given the nature of ecosystem servicesdelivered from land-sparing and land-sharingoptions. Further, we assume that, regardlessof network size K, agglomeration benefitsdenoted by b(σi) are generated on the basisof similar land-use choices made by player iand their direct neighbors only.
Let niσ denote the number of neighbor-ing plots adjacent to that of landowner ithat are under the same land managementoption σi as the plot of landowner i. The totalagglomeration benefits are then denoted byniσb(σi). Let the agglomeration benefit valuesbe b(G) = 10 and b(N) = 40. Hence, for anygiven value of niσ (which is equal to 0, 1, or2 given the circular local network setup),both s(σi) and b(σi) are strictly larger for Nthan for G. We assume that the landscape-level environmental benefit contribution ofa landowner choosing a management optiondepends on the direct neighbors’ decisionsbut not on those of their indirect neigh-bors in order to capture the spatial nature
3 Of course, the third option is not participating and using theland for intensive agriculture. This possibility is, however, notimplemented in the experiment because our focus is on the role ofinformation in influencing landowners’ choice of one conservationstrategy over the other. We thus implicitly assume that compen-sation is sufficiently generous for both conservation strategies tomake participation incentive compatible. This assumption is notat odds with reality because Payment for Ecosystem Servicesschemes have been known to overcompensate landowners toguarantee participation (Kirwan, Lubowski, and Roberts 2005;Muñoz-Piña et al. 2008).
4 Uncultivated or retired land, N , usually provides good habitatfor those species that do not prefer the open nature of cultivatedland, such as the boreal toad (Keinath and McGee 2005) and birdslike the sage grouse (Crawford et al. 2004). Noncrop habitats onretired tracts like flower patches and hedgerows are beneficial forincreasing the populations of natural pollinators such as honeybees (Carvell et al. 2007). On the other hand, the cultivatedland management option G is conducive to species that like the“openness” of such fields. Meadow birds such as the burrowingand short-eared owls typically rely on grasslands for nesting andhunting but thrive less well on land retired from agriculture andabandoned to nature.
Simanti Banerjee et al. The Impact of Information Provision on Agglomeration Bonus Performance 1013
of environmental processes and benefits,which are often decreasing with increasinggeographical distance. Also, the conserva-tion benefits provided by selecting N are thesame, independent of whether the direct andindirect neighbors to one’s left (right) chooseGN(NG) or NN. The same is true for the Goption.
In addition to the conservation benefitsof land use, society values agricultural prof-its too, and these are assumed to be largerunder G than under N . Let r(σi) denote alandowner’s profits from agriculture. Whenland is managed for agricultural production,profits are positive (r(G) = 55) whereas theyare zero when land is abandoned to nature(r(N) = 0). Depending on the land-use choiceof direct neighbors, the social benefits pro-vided by landowner i’s land-use choice readsas:
w(σi) = r(σi) + s(σi) + niσb(σi)(1)
σi = G, N ∀i = 1, 2, . . . , K.
We are interested in the efficiency of land-usedecisions in the presence of agglomerationbenefits and not in how rents are allocatedbetween landowners and the government(or the taxpayer). For simplicity, we there-fore assume that landowners receive thefull social benefits generated by their pro-environmental land-use activities (i.e., theyreceive subsidies equal to s(σi) + niσb(σi)).The government thus implements a pay-ment scheme where the subsidy is set atthe Pigouvian level5,6 and expression (1) isthe total payment received by landowneri when choosing land option σi. This speci-fication of the payoff function is similar tothe one implemented by Parkhurst et al.(2002) and Parkhurst and Shogren (2007)where landowners’ payoffs depend upon
5 By making this assumption, we ignore the fact that raisingfunds for subsidies results in welfare losses to society becausetaxes tend to be distortionary.
6 The reader may argue that given these modeling decisionsthe regulator can implement the optimal pattern by setting thesubsidy equal to fifty-five or higher if landowners choose N andzero otherwise. This will make choosing N a dominant strategy,independent of what the other landowners choose—there is nocoordination problem. Altough this is correct, this scheme is notinformative in explaining how subjects behave in the presence ofsubsidies where their payoffs depend on both their own and others’decisions. Moreover, in the real world the regulator may not befully aware of both the opportunity costs of land conservationand the conservation benefits from agglomeration. Then payinglandowners the social benefits of their actions would ensure thatsocial welfare is maximized with certainty.
Table 1. Summary of Parameter Values andGame Payoffs
Market return to abandoned land: r(N) = 0Market return to managed agricultural land:
the management option and the number ofparticipating neighbors choosing that sameaction.
Using expression (1), table 1 presents thesocial (and private) welfare associated witheach land management option and corre-sponding payoffs associated with the ABscheme involving a landowner and two directneighbors. On the basis of this payoff table,the AB scheme resembles the stag hunt coor-dination game. This three-player game hastwo pure strategy Nash equilibria where allplayers choose G or N . These Nash equilib-ria are Pareto ranked in terms of payoffs.The payoffs for coordination on N is 90,whereas the payoffs for coordination on G is80, implying that the all-N equilibrium is thePareto dominant one. On the other hand, theNash equilibrium corresponding to G is therisk-dominant Nash equilibrium because (a)the cost imposed on a player is higher whenthey choose N and neighbors deviate andselect G and (b) the range within which thepayoffs for selecting G for any combinationof neighbors’ strategy choices vary and islower if the player chooses G than N .7 At thenetwork level, choice of the same strategyby all K players creates a convention: thePareto efficient convention all-N or the riskdominant all-G convention.
Harsanyi and Selten (1988) argue that insuch coordination games the players’ col-lective rationality regarding higher payoffswill lead them to coordinate to the Pareto
7 Following Harsanyi and Selten, the deviation loss associatedwith G is seventy and with N is thirty.
efficient Nash equilibrium. Yet this outcomeis predicated on the risk and payoff-dominantNash equilibria corresponding to the samestrategy. In our AB policy setting this is notthe case because choosing the natural landmanagement option N , although lucrative,is riskier relative to strategy G because ityields a higher payoff loss when neighborsdo not coordinate on N . In an environmentwhere every individual is subject to strategicuncertainty about other players’ choices, thisrelative risk ranking may make G more likelythan N . The combination of direct and indi-rect links on local networks increases players’strategic uncertainty even further. Thesefeatures, in turn, may prevent the achieve-ment of the social optimum and lead to theinefficient outcome—a scenario referredto as coordination failure. On the basis ofthis setup and our conjectures, our studyexplores the impact of varying the amountof information available to subjects abouttheir neighbors’ previous choices on theirlikelihood of choosing N and coordinating onthe socially optimum all-N outcome.
Experimental Design and Procedures
We consider twelve subjects arranged ona circle with every subject having a directneighbor to their left and right. These directneighbors are referred as the clockwise (left)and anticlockwise (right) neighbors in theexperimental instructions. All subjects arerandomly assigned an ID ranging from oneto twelve to preserve player anonymity andidentify their direct neighbors. For example,the player with ID 1 is directly linked toplayers with IDs 12 and 2. Every subject isindirectly connected to the remaining nineplayers by their direct neighbors. Becauselandowner identity and location does notchange regularly on actual geographical land-scapes, we adopt a fixed matching schemewhereby all networked players’ IDs and loca-tion remain unchanged during the lifetimeof the experiment. Additionally, the fixedmatching scheme permits us to study theimpact of subjects’ reputation for the playof a particular strategy on other subjects’choices.
Each session has thirty periods duringwhich subjects play the AB game with theirtwo direct neighbors with payoffs as shownin table 1. We record data for twelve sessions:six baseline sessions termed 2INFO and six
treatment sessions termed 4INFO. The base-line is referred to as 2INFO because eachsubject receives feedback about their twodirect neighbors’ current and all past periods’actions. The label 4INFO signifies that in thetreatment sessions a subject receives choiceinformation about the actions of the fourplayers closest to them on the network: theirdirect neighbors and their direct neighbors’direct neighbors (i.e., their closest indirectneighbors).8 Per our model specification, inboth treatments payoffs are determined byown and direct neighbors’ choices only.
The experiments for this study were con-ducted at the Laboratory for Economics,Management, and Auctions at the Pennsylva-nia State University in February 2012 usingstudent subjects. In total 144 subjects par-ticipated in twelve twelve-subject sessionsresulting in six independent observationsfor each treatment. The show-up fee was $5,and experimental earnings were convertedinto actual currency at the rate of 150 exper-imental dollars to $1. The experiments wereimplemented using Z-Tree (Fischbacher2007), and sessions lasted between forty-fiveand sixty minutes. The average subject earn-ings for the 2INFO and 4INFO sessions were$19.95 and $22.38, respectively.
At the beginning of every session, a figurerepresenting the circular network and play-ers’ neighbors was shown to the subjects.Figure 1 represents the landscape informa-tion shown to subjects in the 2INFO sessions.In the 4INFO sessions, the location of theclosest indirect neighbors were labeled inthe figure as well. This diagram is providedin the supplementary online appendix. Theinstructions (included in the supplementaryonline appendix) were made available ona computer screen and were read aloud tomaintain an environment of common knowl-edge. Subjects were informed about their roleas a landowner with two types of land man-agement actions that would generate payoffs.No other contextual terminology, such asecosystem services, biodiversity conservation,or endangered species, was included in theexperimental instructions.
We adopted this context-free approach(a) to study behavior and land-use outcomes
8 To keep the instructions simple, we used the phrase “localneighborhood” in the instructions for 4INFO sessions to refer tothe set of direct and indirect neighbors whose responses wouldbe visible to players in all periods. However, in the “Results”section of the article, the phrase “local neighborhood” refers tothe set of direct neighbors only.
Simanti Banerjee et al. The Impact of Information Provision on Agglomeration Bonus Performance 1015
Figure 2. Average share of N choices by period and treatment
while subjects were responding to finan-cial incentives and reputational incentivesproduced during repeated interactions withthe same set of neighbors under the twoinformation conditions and (b) becauseexplicit consideration of noneconomic moti-vations toward conservation that typicallyvary between private landowners wouldimpose subject heterogeneity in our exper-iment, which can potentially confound theresults of our information treatment (inaddition to being orthogonal to it). In keep-ing with the game-theoretic nature of theexperiment, the instructions mentioned thatsubjects’ payoffs would be influenced by theirneighbors’ actions. They were also informedthat the game would be repeated for thirtyperiods. Before starting the experiment, allsubjects participated in a quiz about differentfeatures of the experiment to verify theirunderstanding of the strategic environment,the game choices, and the associated payoffs.
Results
This section is organized into a discussionof individual choices and spatial configu-rations on the network, followed by theanalysis of underlying behavior explainingthe experimental outcomes.
General Results
Figure 2 and table 2 present the averageshare of N choices for all sessions for both
treatments over thirty periods. We maketwo observations. First, the average shareof N choices in 2INFO falls from 63% toalmost zero after twenty periods and thenstays under 10% for the remaining peri-ods. In the 4INFO treatment, N choices fallfrom 73% in period 1 to 18% in period 30.That is, with increasing experience the vastmajority of the subjects end up choosing therisk-dominant option. This result correspondsto theoretical evidence on contagion of riskdominant choices on local networks providedby both Ellison (1993) and Weidenholzer(2010) and experimental evidence recordedin Keser, Ehrhart, and Berninghaus (1998)and Berninghaus, Ehrhart, and Keser (2002).The reduction in the frequency of efficientN choices and the increase in instances ofcoordination failure is also consistent withexperimental evidence obtained in other non-network coordination game environmentssuch as the minimum and average effortgames (Van Huyck, Battalio, and Beil 1990,1991) and public good games (Andreoni 1988;Keser and van Winden 2000).
An explanation for this result is that overmultiple periods of interaction, most sub-jects’ strategic uncertainty in the game getsresolved in favor of G because this canreduce the magnitude of payoff loss in theevent of their neighbors’ failure to coordi-nate on the efficient N strategy. This resultis markedly different from the previous ABstudies by Parkhurst et al. (2005), Parkhurstand Shogren (2007) and Warziniack, Shogren,and Parkhurst (2007) which (a) implement
features such as a random matching protocoland non-binding pre-play communicationwhich increase the frequency of the efficientchoice; (b) do not consider any networkeffects; and (c) announce the spatial con-figurations produced as a result of subjects’choices at the end of a period to everyone.
The second observation is that, althoughthe average share of N choices is falling in4INFO, in every period the value is higherin 4INFO than in 2INFO. Thus, informa-tion about choices of more players on thenetwork delays the decay in efficient coor-dination but cannot prevent it. If player iobserves that their direct neighbor player(i + 1) chose N but that their indirectneighbor player (i + 2) chose G, they mayanticipate that player (i + 1) will most likelyswitch to G (because choosing G is the bestresponse when neighbors choose differentstrategies), inducing player i to choose G aswell.
In our experiments, a transition to G fol-lowing the above reasoning is likely becausethe payoff matrix produces conditions thatare quite adverse for coordination on theefficient equilibrium. The payoff differencebetween the NNN and GGG outcomes is10. This difference is less than the payoff lossof forty associated with choosing N whenat least one neighbor deviates from NN toNG in the current period. Additionally, thepayoff difference between a choice of N andG when facing previous choices correspond-ing to NG is twenty. Hence, a player standsto lose much higher payoffs from choosingN repeatedly to influence G-playing neigh-bors to choose N in order to earn a payoffof ninety. Thus, the prospect of generating anNNN outcome is not worth the payoff lossesneeded to do so. As a result, the tendency ofvoluntary loss-making to influence neighborsto choose N is weakened, contributing tothe decrease in the likelihood of efficient
Simanti Banerjee et al. The Impact of Information Provision on Agglomeration Bonus Performance 1017
Table 3. Average and Standard Deviations(in parentheses) of N Choices for Period 1and over All 30 Periods
Mann–WhitneyTreatment Test
Share of NChoices 2INFO 4INFO p Value
Average in 0.63 0.74 0.11period 1 (0.487) (0.443)
Averaged 0.19 0.43 0.03over all 30periods
(0.397) (0.495)
coordination with increasing experience. Infact, debriefing subjects after every sessionrevealed that an increasing number of sub-jects chose G or switched from N to G owingto the magnitudes of the out-of-equilibriumpayoffs relative to the Nash equilibrium ones.
The importance of the relative magnitudesof these out-of-equilibrium payoffs on equi-librium selection has been documented inrelation to stag hunt games by Straub (1995)as well. In light of this scenario, our resultsindicate that coordination is less likely tounravel if more information is provided. Ifextra information on the network is able toincrease the frequency of N choices underthe current adverse payoff circumstances,the extra information may result in subjectssuccessfully coordinating on the payoff-dominant equilibrium if the circumstances forcoordination are more favorable.
Let us analyze the result more formally.Table 3 reports the shares of N choices forboth treatments using two types of observa-tions: average N choices for the first periodtaking each subject’s action as an indepen-dent observation (implying that there are sixindependent observations from six sessions ineach cell of the table) and the same averagedover all thirty periods for six groups. Usingstandard Mann–Whitney tests9 (with cor-responding p values presented in table 3),we find no significant treatment effect in thefirst period. However, over the experimentallifetime of thirty periods there is a signifi-cant impact of information (at 5% level ofsignificance).
Lack of significance in period 1 is to beexpected because subjects are randomly
9 Table I in the supplementary online appendix contains dataused for the Mann–Whitney tests.
assigned to both treatments, face the samepayoff table, and make decisions withoutreceiving any feedback about the choicesof others. Considering all thirty periodstogether, subjects’ strategic uncertaintyassociated with choosing the (risky) payoffefficient strategy is lower in 4INFO (rel-ative to 2INFO) because they are able toview the current and all previous choices oftheir direct and closest indirect neighbors.As a result, strategic uncertainty for manysubjects gets resolved in favor of N , lead-ing to an upfront increase in N choices in4INFO and significantly more N choiceson average in 4INFO relative to 2INFO.This result holds regardless of the fact that,owing to the adverse payoff conditions andlack of visibility of more than 50% of theparticipants’ choices, N choices fall in bothtreatments with repeated interactions. Ourfindings are also supportive of the theoreti-cal model by Alós-Ferrer and Weidenholzer(2008) in which players successfully choosethe efficient strategy when receiving informa-tion from two direct and two closest indirectneighbors.
Analysis of Spatial Patterns on LocalNetworks
Having presented the impacts of informationand repeated interactions on the frequencywith which the Pareto efficient N choice isselected, let us next analyze the location ofthese N choices and the development ofthe land choice configurations over multi-ple periods. Figures 3–5 present snapshotsof the network configurations in each ofthe six sessions for periods 1, 15, and 30,10
where N choices are marked with trianglesand G choices with circles. The spatial pat-terns in these periods reflect the difficulty ofcoordinating on the Pareto dominant all-Nequilibrium. Although all groups start withbetween seven and nine subjects (mostlyadjacent) choosing N in the first period, inthe final period very few adjacent N choicesremain.
Table 4 presents the number of groupsand the earliest period in which any groupreached an equilibrium configuration. We
10 We classify our thirty-period experiment into three equallyspaced time intervals signifying the initial, intermediate, and finalstages. Configuration of choices from all other periods can bedetermined on the basis of data in the supplementary onlineappendix.
Simanti Banerjee et al. The Impact of Information Provision on Agglomeration Bonus Performance 1019
Figure 5. Period 30 choices
Note: N choice G choice
Table 4. Number of Groups and Earliest Period in which all-N and all-G ConventionsReached
2INFO 4INFO
No. of Groups No. of GroupsReach at Least Period in Which Reach at Least Period in Which
Convention Once First Originated Once First Originated
all-N 0 — 1 7all-G 5 12 3 23
find that there is only one cohort that is ableto reach an all-N equilibrium in 4INFO. Thisefficient land-use configuration is producedin period 7 in the sixth cohort and is stablewith some variation until period 22. Beyondthis period, only a few localized N choicespersist. Of the remaining five 4INFO groups,localized N choices transition to the all-Goutcome in three groups (which is producedearliest in any of the groups in period 23).In the remaining two groups, only isolatedN choices remain. In 2INFO, on the otherhand, all-N is never produced and the all-Goutcome is obtained at the earliest in period12. This risk-dominant network level conven-tion is both stable and resilient. Of the five
groups that reach this pattern in period 30,two groups never deviate away from it andthe three that do revert back to it in one totwo periods. The stability and resilience ofthe all-G convention is consistent with theo-retical evidence provided by Alós-Ferrer andWeidenholzer (2006).
To support a formal analysis of theseland-use outcomes, we construct a metricto measure the degree of spatial contiguitygenerated by the AB scheme in terms ofcontiguous N and G choices on the circularnetwork. This metric measures the number oflocalized clusters of similar land-use decisionsproduced by any three adjacent players (i.e.,a player and their direct neighbors on the
In this expression, D ∈ {2INFO, 4INFO}refers to the treatment, Z ∈ {G, N} indi-cates whether the metric measures theshare of clusters of N choices or G choices,t = 1, . . . , 30 denotes period, and yit = 1 ifσi = Z or yit = 0 otherwise. This metric cantake a minimum value of 0 when no threeadjacent players make the same choice,implying that subjects cannot coordinatetheir decisions even within their local neigh-borhood where choices are always visible.The maximum value of the metric is twelve,which is obtained when an all-G or all-Nconvention is produced. This is because everyplayer is at the center of one distinct localneighborhood. On the basis of this metric, wecan evaluate the development of CD,Z
t overtime to identify how coordinated land-usepatterns on the network change during theexperiment.12 Figure 6 and table 2 presentthe session-level average values of C2INFO,N
t ,C4INFO,N
t , C2INFO,Gt , and C4INFO,G
t for all thirtyperiods.
The positive values of the metric in allperiods imply that the AB scheme is ableto reduce fragmentation of land use andincentivize the creation of localized clus-ters of N and G choices and the all-N andall-G outcome for enhanced delivery ofecosystem services. Additionally, variation ininformation available about subjects’ choicesproduces significant differences in the natureof these spatial patterns. Table 5 reports thep values associated with Mann–Whitneytests for the N clustering and G clustering
11 We conducted the contiguity analysis with cluster sizes ofthree and two (which is a weaker measure of contiguity) andobtained the same qualitative results. Owing to the similarity inresults and the fact that our AB game is a three-player gamenested in a larger local network in which a two-sized cluster doesnot capture all the strategic effects faced by a player, we onlyinclude the three-cluster analysis in this article.
12 We do not present our analysis in terms of the all-Nconvention because it originates in only one group. The analysisof localized choices is more informative in representing thevariability in land-use choices observed on the network owing tothe treatment implementation and increased game experience.
Table 5. Average and Standard Devia-tions (in parentheses) of Localized N and GClustering for All 30 Periods
Mann–WhitneyTreatment Test
Averaged overAll 30 Periods 2INFO 4INFO p Value
Average of N 0.99 3.17 0.045clustering (1.74) (3.51)
Average of G 8.13 4.91 0.03clustering (3.91) (3.99)
metrics for all thirty periods (six independentobservations per cell in both cases).13
We find that the level of N clustering issignificantly different (p = 0.045) in strategicenvironments with information exchangebetween more participants (in 4INFO) thanin those where information flows are limited(in 2INFO). Thus, additional informationincentivizes land-use patterns correspondingto the efficient Nash equilibrium con-figuration at least within subjects’ localneighborhoods. However, with limited infor-mation flows and repeated interactions overall thirty periods, nearly all subjects (69 of72) switch to G in 2INFO (whereas there aremany subjects still selecting N in 4INFO),so that on average a significant treatment-induced difference (p = 0.03) in the overalllevels of G clustering emerges.
Analysis of Individual Behavior
This section presents an analysis of fac-tors affecting individual behavior in theexperiment. We model the likelihood ofmaking a socially efficient N choice as afunction of a series of factors exogenousand lagged-endogenous to subjects withina dynamic random effects probit regressionframework with the subject representingthe random effect. The dependent vari-able is a binary variable yit taking a valueof 1 for an N choice and 0 for a G choiceby subject i (i = 1, 2, . . . , 144) in periodt (t = 1, 2, . . . , 30).
Three separate models are presented.Model I considers the impact of the twoexogenous variables: the information treat-ment D to which every subject is randomlyassigned and the period variable denoted
13 Data for the Mann–Whitney tests are included in Tables IIand III in the supplementary online appendix.
Simanti Banerjee et al. The Impact of Information Provision on Agglomeration Bonus Performance 1021
Figure 6a. Average localized N Clustering by treatment and period
Figure 6b. Average localized G Clustering by treatment and period
by t that controls for the impact of subjects’game experience and familiarity within theexperimental environment on their likeli-hood of making an N choice. In additionto these exogenous variables, in model IIthe effect of a subject’s previous periodchoice on the likelihood of selecting N in anyperiod is considered. This variable, denotedby yi(t−1), controls for an effect that hasbeen variously termed strategy inertia, aprecedence effect, or simply “force of habit.”An interaction term between the periodvariable and the lagged choice is included to
evaluate whether the role of precedence indetermining the likelihood of an N choice inthe current period varies as subjects becomemore experienced.
Because neighbors’ choices influence asubject’s action, model III includes a variableni(t−1), which measures the frequency ofdirect neighbors’ previous period N choices.This variable can take a value betweenzero and two depending on the number ofneighbors selecting N . An interaction termbetween the neighbors’ choice variable andthe period variable is considered to explore
Note: Standard errors are in parentheses. A ∗∗∗ represents statistical significance at 1% level and ∗∗ represents statistical significance at 5% level.
the effect the frequency of neighbors’ choiceshave on a subject’s likelihood of choosingN at different levels of experience. A thirdinteraction term between ni(t−1) and yi(t−1) isincluded to analyze whether strategy inertiagets reinforced within the local neighborhooddepending on circumstances favorable for theefficient strategy choice (i.e., the number ofneighbors choosing N). All other variablesfrom the two previous models are included inmodel III as well.
The random effects structure of the errorterm has a component ui, which is thetime-invariant unobserved heterogeneityassociated with subject i and the randomcomponent εit for every period. The fullmodel with all variables and α represent-ing the omitted categories is presented inexpression (3). In evaluating model perfor-mance, we use the value of the log-likelihoodgenerated during the estimation.
yit = α + D + βyi(t−1) + γt + δtyi(t−1)(3)
+ θni(t−1) + πtni(t−1)
+ μyi(t−1)ni(t−1) + ui
+ εit(i = 1, 2, . . . . . . .144;
× t = 1, 2, . . . . . . 30)
Table 6 presents the regression estimatesfor the three models. Consistent with ourprior discussion, the information treatmentdummy estimate is positive and significant (at1% level) in all the models. We also obtaina negative and significant estimate (at 1%level) for the period variable in all models,providing support for the negative trend inN choices observed for both treatments. Thisresult follows from the strategic uncertaintyin the game getting resolved in favor of G,owing to the adverse payoff circumstancesassociated with making an N choice and suf-fering high payoff losses (losses of 20 or 70)given neighbors’ selections.
Results from model II indicate that a sub-ject’s behavior in the previous period has apositive and significant (at 1% level of sig-nificance) impact on current period choiceof N (i.e., subjects are significantly morelikely to select N if they chose N in the pre-vious period). This means the presence of a
Simanti Banerjee et al. The Impact of Information Provision on Agglomeration Bonus Performance 1023
positive precedent effect for the choice of N ,which can be attributed to strategy lock-in orstrategy inertia (Blume 1993). Once havingselected a certain strategy, subjects maintainthat choice for a few periods. The fact thatthis estimate is positive and significant inmodel III as well indicates that inertia maydelay subjects’ response to their neighbors’past choices for a few periods even if theswitch may be a best response. In coordina-tion games such as the AB, one explanationfor the strategy lock-in is subjects’ voluntaryloss-making behavior (Brandts and Cooper2006). Players voluntarily inflict payoff lossesupon themselves by choosing N , even iftheir neighbors are choosing G, to signaltheir sustained commitment toward choosingNand build a reputation for selecting N . Suchcostly signaling can be useful in reducingneighbors’ strategic uncertainty in favor of N ,leading them to switch from G to N in subse-quent periods. More generally, the precedenteffect also captures the role of human habitin economic decision-making: subjects oftenadhere to what they have done in the pastregardless of consequences because a changerequires them to act consciously, which iscognitively effortful (Kahneman 2003; Thalerand Sunstein 2008).
The estimate for the interaction betweenprecedence and the period variable is posi-tive and significant in model II. Per figure 7a,which presents the marginal effect of theinteraction between own previous choiceand period variable with 95% confidenceintervals (generated using routines suggestedby Xu and Long (2005) in Stata on the basis
of Ai and Norton (2003)) used to interpretinteractions in nonlinear regressions, weobtain a positive and significant interactioneffect for all period values (none of the con-fidence intervals include 0). Although theestimate of the interaction term is not sig-nificant in model III, figure 7b indicates apositive and significant interaction effect aswell given the nature of the confidence inter-vals. Thus, per figure 7a and 7b, the effect ofprecedence on current choice is significantlydifferent at varying levels of subject experi-ence. With increased familiarity in the game,habit is harder to break: an N choice madein the previous period in later phases of thegame is more likely to be reinforced thanwhen this choice is made in the early phaseof the game.
Results from model III provide insightsinto the likelihood of strategy selectionand behavior consistent with the principleof Nash equilibrium. The estimate for thenumber of direct neighbors choosing N inthe previous period is positive and signifi-cant (at the 1% level). Sustained choice ofN by neighbors reduces a subject’s strate-gic uncertainty in favor of N , at least withintheir local neighborhood. Consequently, sub-jects are more likely to make an N choicein the current period to create or increasethe likelihood of creating an N clusterat the center of which they earn a payoffof 90. This significant effect of neighbors’choices—taken together with the precedenteffect—explains the appearance of the all-Noutcome and localized N clusters in bothtreatments.
11.
52
2.5
Effe
cts
on L
inea
r P
redi
ctio
n
0 10 20 30Period
(a)
2INFO 4INFO
Figure 7a. Marginal effect of interaction between own previous choice and period variablewith 95% confidence intervals
2INFO, Neighbors Choosing N = 0 2INFO, Neighbors Choosing N = 1
2INFO, Neighbors Choosing N = 2 4INFO, Neighbors Choosing N = 0
4INFO, Neighbors Choosing N = 1 4INFO, Neighbors Choosing N = 2
(b)
Figure 7b. Marginal effect of interaction between own previous choice and period variablewith 95% confidence intervals calculated at three values of N choice by neighbors in previousperiod −0, 1, 2
11.
52
2.5
Effe
cts
on L
inea
r P
redi
ctio
n
0 1 2
Number of Neighbors Choosing N
2INFO, Period = 1 4INFO, Period = 1
2INFO, Period = 15 4INFO, Period = 15
2INFO, Period = 30 4INFO, Period = 30
(c)
Figure 7c. Marginal effect of interaction between own previous choice and number of previ-ous efficient choice by neighbors variable with 95% confidence intervals calculated at 3 periodvalues −1, 15, 30
Finally, we focus on the two interactioneffects, which try to explain subject behav-ior given a favorable situation for efficientcoordination within their local neighbor-hood. The estimate for the interaction termbetween the precedent and neighbors’ pre-vious choice variable is positive. Figure 7cprovides the diagrammatic representation ofthe marginal effect of interaction betweenprecedent and number of neighbors selectingN in the previous period for three candi-date periods: 1, 15, and 30. We find the true
interaction effect to be significant because 0is not in any of the confidence intervals. Thus,strategy inertia associated with an efficientN choice is even stronger if more neighborschose N previously. The interaction termbetween the period variable and neighbors’choices is positive and significant (at 1%level of significance). Figure 7d representsthe true interaction effect, which is posi-tive and significant and interpreted in thesame manner. Thus, a subject’s likelihood ofselecting N as a function of their neighbors’
Simanti Banerjee et al. The Impact of Information Provision on Agglomeration Bonus Performance 1025
.51
1.5
2E
ffect
s on
Lin
ear
Pre
dict
ion
0 10 20 30Period
2INFO, Previous Choice = G 2INFO, Previous Choice = N
4INFO, Previous Choice = G 4INFO, Previous Choice = N
(d)
Figure 7d. Marginal effect of interaction between number of previous efficient choice byneighbors and period variable with 95% confidence intervals calculated at two values ofprevious choice 0(G) and 1(N)
previous N choices is higher in later peri-ods. Despite being more likely to choose Gto avoid suffering payoff losses, with moreexperience more N choices in a subject’slocal neighborhood in the previous periodmay serve as a credible signal to them tochoose N in the current period to generatean N cluster and earn higher payoffs.
These two interaction effects pertaining tothe local neighborhood represent the relativeimpact of the strategic interactions within thelocal neighborhood and the overall networkenvironment. They suggest that the effect ofdirect neighbors’ choices are stronger rela-tive to all indirect ones, whereby N clusterssurvive in three of the twelve experimentalsessions in the final period, even if manysubjects’ strategic uncertainty is resolved infavor of G. The value of the log-likelihoodis the highest for model III, indicating thatthis model most accurately explains the vari-ability in subject behavior in the experimentsthat produces different spatial patterns andcorresponding conservation benefit streams.
Conclusion
Improving the design of agri-environmentschemes involving payments for ecosystemservices often requires attention to the spatialconfigurations of land uses that generate con-servation benefits. In such cases, the AB canserve as a policy mechanism to incentivize
coordination when landowners/farmers canvoluntarily choose how to manage theirland. However, under a conservative payoffscenario, risk and payoff dominance mayselect different Nash equilibria in the ABgame, leading to the problem of potentialcoordination failure on the Pareto efficientequilibrium (Straub 1995). In this article,we experimentally investigate in the labora-tory the extent of spatial coordination to thesocially optimal, Pareto efficient land man-agement outcome on local networks undertwo information conditions within such apayoff scenario.
Our study is based on the fact thatboth direct and indirect linkages betweenlandowners in networks can impact thenature of strategic interactions and theresultant likelihood of coordination wheninformation flows between landowners arelimited. Information on the choices of otherlandowners in the network can then reducestrategic uncertainty and improve the like-lihood of coordination toward the sociallyoptimal outcome. We find that spatial coor-dination to the Pareto efficient outcomeis significantly higher when subjects havemore information available about the landmanagement choice and payoffs of theirneighbors.
Given that there is considerable gen-eralizability of results from the lab to thefield (Kessler and Vesterlund forthcoming),our study result lends hope for improved
coordination to enhance ecosystem servicesdelivery if restrictions on informationexchange between landowners are relaxed.One of the many ways to do so would be foruniversity extension staff to liaise with poten-tial participants in an AB-type scheme in aneighborhood (e.g., a catchment), althoughthis comes at a cost. Experience with con-servation auctions in Australia suggeststhat such close contacts between extensionpersonnel and farmers can be crucial indetermining the extent of participation andthe quality of outcomes (Reeson, Williams,and Whitten 2011). Another method wouldbe to disseminate information in farmingcommunity networks through Internet bul-letin boards and key actors (“model” or“demonstration” farmers) who are linkedto many others and can serve to reduce thelevels of strategic uncertainty, hence facilitat-ing spatial coordination (Prell, Hubacek, andReed 2009).
However, despite the fact that moreinformation induces a higher degree of coor-dination on the Pareto optimal equilibrium,over time a switch to the risk-dominantoutcome is found. Such a result is con-trary to outcomes of previous AB studiesby Parkhurst et al. (2002), Parkhurst andShogren (2007), and Warziniack, Shogren,and Parkhurst (2007). One of the causes ofthe difference in outcomes is that using amore realistic network representation, asin our study, increases the strategic uncer-tainty of players compared with the onesused before. Also, we deliberately chosean experimental parameterization that isadverse to efficient coordination to obtainthe starkest possible results. In the con-text of improving the delivery of ecosystemservices and other conservation benefitsthrough land management on local networks,this result implies that when participantsrespond only to financial incentives, in thelong run the AB may prove to be onlypartially effective in generating localizedcoordination patterns for ecosystem servicesdelivery. For an environmental regulator orconservation agency, finding a way of ame-liorating this tendency of coordination tomove away from the Pareto optimal out-come (maybe by appealing to participants’noneconomic behavioral and environmentalmotivations) is important if the conserva-tion benefits of spatial coordination by anAB scheme are to be maintained in the longrun.
Supplementary Material
Supplementary material is available at http://oxfordjournals.org/our_journals/ajae/ online.
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