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The Drama of the Commons CONCLUSION
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The Drama of the Commons 13 Knowledge and Questions After 15 Years of Research Paul C. Stern, Thomas Dietz, Nives Dolšak, Elinor Ostrom, and Susan Stonich The study of institutions for managing common-pool resources has matured considerably since 1985. This chapter assesses the progress of the field as a scientific enterprise, characterizes what has been learned over the past decade and a half, and identifies a set of key research directions for the next decade of research. We find that the field is making marked progress along a trajectory of development that is common to many maturing areas in the social sciences. Some of the advances have practical value for natural resource managers, though knowledge has not progressed to a point at which managers can be offered detailed guidance. And of course, practical guidance must be based on an understanding of both the scientific knowledge base and the local situation. In this chapter we summarize some key lessons from recent research, discuss seven major challenges of institutional design, identify important directions for future research, including key understudied issues, and note ways that the field can benefit from linkages to several related fields of social science research. PROGRESS OF THE FIELD Research on institutional designs for common-pool resource management has followed a development path that is similar to many other fields of social science that investigate complex real-world phenomena and develop knowledge intended to be useful for managing those phenomena. These fields seek to understand phenomena that are multivariate, path-dependent (i.e., historically contin- We are indebted to James Acheson, Kai Lee, Ronald Mitchell, and the chapter authors of this volume for insightful discussions and written comments on drafts of this chapter.
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The Drama of the Commons gent), and reflexive (i.e., alterable in important ways by the process of studying them). Many of the processes are hard to study with field experiments and care must be taken in generalizing from laboratory experiments. Thus, establishing causation is always a challenge. The complexity of the phenomena also means that models based on nonexperimental data have many parameters to be estimated relative to the number of observations available. Other fields facing this problem include international conflict resolution (Stern and Druckman, 2000) and comparative politics and sociology (King et al., 1994; Ragin, 1987, 2000; Ragin and Becker, 1992). Program evaluation has a long history of dealing with these issues (see, e.g., Cook and Campbell, 1979; Chen, 1990; Chen and Rossi, 1992; Weiss, 1998). Progress in such fields depends on reducing bewildering arrays of phenomena, each with multiple attributes that may be important, into manageable sets of measurable variables. It also depends on developing theory that specifies relationships among the variables, including identification of causal relationships among variables that can be manipulated intentionally. The development path in such fields typically involves at least four elements, all of which are evident in common-pool resource management research. Development and Differentiation of Typologies Typologies are needed to classify the central phenomena under study, the outcomes worthy of investigation, and the factors both internal and external to the central phenomena that shape those phenomena and their effects on larger systems. Without a shared language that differentiates key concepts, theoretical progress is impossible. An example is the increasingly familiar classification of property rights institutions into four major types: individual property, government property, group property, and open access (the absence of rights to exclude) (e.g., Feeny et al., 1990). These types have been further differentiated into subtypes (e.g., Tietenberg, Chapter 6, on subtypes of private property). Another example is the classification of factors affecting institutional functioning into attributes of resources, attributes of appropriators, and attributes of institutions, and of each of these classes into subtypes (see Agrawal, Chapter 2). It can be useful to subdivide these even further. For example, Bardhan and Dayton-Johnson (Chapter 3) identify several kinds of heterogeneity among resource appropriators and conclude that economic heterogeneity and social heterogeneity have independent effects and operate through different causal mechanisms (incentives versus norms). Typologies allow researchers to focus attention on a tractable number of variables and then to state and systematically examine research hypotheses about them.1 Contingent Generalizations A second element of development is a shift from bivariate research hypotheses to contingent or conditional ones. For example, it has become clear that no
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The Drama of the Commons FIGURE 13-1 Schematic representation of an empirically supported contingent relationship between group heterogeneity and institutional performance. single institutional form is best at maintaining resources across a wide range of environmental and social conditions. Researchers have begun to propose hypotheses about conditions under which particular institutional forms are likely to be successful. Similarly, research has shown that simple bivariate relationships of the sustainability of resource management with the size, heterogeneity, and poverty of the user group may be positive, negative, or curvilinear, depending on contextual factors (Agrawal, Chapter 2). Researchers have responded by developing and testing hypotheses that take these contingencies into account. Studies with large numbers of cases (large-n studies) are particularly useful for generating such hypotheses because they allow regularities to be observed in subsamples that differ in factors that change the effect of other variables—the factors that make conclusions contingent. For example, Tang (1992, cited by Bardhan and Dayton-Johnson, Chapter 3) reports that heterogeneity among resource appropriators is associated with poorer performance in irrigation systems that are managed by government agencies, but not in community-managed systems (see Figure 13-1). Apparently, some community-managed systems are able to develop rules of allocation and cost sharing that meet the challenges of heterogeneity, while agency-managed systems are not. Similarly, Varughese and Ostrom (2001) show that various forms of heterogeneity within forest user groups depend for their effects on collective action on the specific form of organization established by the group. Identifying this difference in the effects of heterogeneity requires cases that differ in their degree of heterogeneity among both community-managed and government-managed systems.2 Causal Analysis A third element of development is a shift from correlational to causal analysis. Researchers hypothesize and search for causal paths or mechanisms that can
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The Drama of the Commons account for and explain observed associations. These causal models include interactions such as the one just noted where the effect of one independent variable on the dependent variable changes with the value of a third variable. For example, Bardhan and Dayton-Johnson (Chapter 3) theorize that the effects of heterogeneity may follow several causal paths. “Olson effects” (Olson, 1965; see causal path (a) in Figure 13-2) operate when certain resource users have enough at stake, and enough wealth, to maintain the resource on their own even though there are free riders. Two alternative causal paths, (b) and (c), have negative effects on resources and, according to Bardhan and Dayton-Johnson, are more often consistent with the evidence on the functioning of irrigation systems. Another example of causal models comes from experimental research attempting to understand why communication within a resource user group fosters cooperative outcomes. This research suggests three possible causal mechanisms. Communication may increase group identity or solidarity, create the perception of a consensus to cooperate, or result in actual commitments to cooperate, which function as shared norms to which members adhere (see Kopelman et al., Chapter FIGURE 13-2 Three causal paths describing hypothesized effects of wealth or weath inequality on maintenance of common-pool resources. NOTE: Minus signs (–) signify hypothesized negative effects of wealth or wealth inequality on the variable to the right of the arrow.
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The Drama of the Commons 4). Experimental researchers have been working to understand whether all or only some of these mechanisms are important for understanding the observed communication effect. One advantage of the experimental approach compared to the analysis of an even larger number of case studies from the field is the ability of experimental researchers to structure the values of hypothesized causal variables so as to obtain clear estimates of their effects (Gintis, 2000). The experiment allows critical simplifications not possible with field data. Recent experiments conducted in field settings with Colombian villagers who are responsible for managing local common-pool resources provide complementary evidence to that generated in experimental laboratories located in universities (Cárdenas et al., 2000). Research on communication and group norms is part of a larger effort to build causal models that explain how characteristics of resources and resource-using groups link through social institutions to produce outcomes for resource systems. Figure 13-3 presents a schematic model that specifies some such links in detail, focusing particularly on the roles of monitoring and enforcement of existing rules as mediating factors. The model is generally consistent with available evidence. It is also partly speculative and incomplete (e.g., it does not represent a full range of effects of communication nor does it address how some of these independent variables affect each other and may affect the likelihood of self-organization in the first place). Models such as that in Figure 13-3 do much to advance theory and practice. They move understanding forward from correlation to causation. In doing so they greatly reduce the number of variables and hypotheses to be examined. Such models, when empirically verified, create an importance ranking among the variables: Some emerge as important because of strong direct effects on the sustainability of the resource and other outcomes of concern. Others are important only for their indirect effects. For example, properties of resources and resource users affect resource outcomes only indirectly, mainly by influencing the costs of monitoring and enforcement. Of course, in making policy or designing institutions, the ease with which a variable can be changed, and the consequences of those changes on issues other than commons management, often will be as important as the size of the direct or indirect effect of a variable on commons sustainability. In addition, because institutional design choices are normally the result of negotiation among political actors, the technical characteristics of the options are weighed in the context of their political acceptability. Models like that in Figure 13-3 can also advance understanding by grouping variables and making connections to related fields of study. In the model shown in Figure 13-3, communication, dense social networks, and practices of reciprocity all affect outcomes through exactly the same causal paths. This suggests that these variables may be considered as multiple indicators of a single underlying construct—perhaps what has been called strength of community (Singleton and Taylor, 1992; Gardner and Stern, 1996), social ties (Petrzelka and Bell, 2000), or
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The Drama of the Commons FIGURE 13-3 A schematic causal model postulating ways that costs of monitoring and enforcement mediate between characteristics of resources and resource users and outcomes of resource management institutions. NOTE: Boxes in top part of left column refer to characteristics of resource users and their groups; boxes in bottom part with italic text refer to characteristics of resources. All arrows indicate posited positive relationships. social capital (Putnam et al., 1993; Ostrom and Ahn, 2001; but see Abel and Stephen, 2000). It also suggests that what has been learned in research on these constructs may be relevant to problems of designing resource management institutions. Causal models can be useful to practitioners by helping them to identify
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The Drama of the Commons potential ways to intervene to produce desired effects. This model redirects attention from variables on the left of the figure, none of which can be changed directly by institutional design, toward features that are more amenable to institutional solutions, in the middle of the figure.3 Integration of Research Results The fourth element in the development of research is the integration of results from various research methods, each of which has its own contribution to offer—and its own limitations. Causal models of the sort described in the previous section are one form of integration, but here we are also referring to formal methods of integration and making sense of cross-study comparisons. Controlled experimental research (see Kopelman et al., Chapter 4) provides the strongest evidence for establishing relationships of cause and effect. But it is hard to apply to understanding complex phenomena like resource management institutions because they are hard to simulate realistically in the laboratory and because opportunities for field experiments are limited. Experiments seem to be most useful for understanding influences on the behavior of individuals and small groups that can be simulated in the laboratory. Because experiments must almost always be carried out in simulated resource-use situations, however, their external validity— that is, their relevance beyond the simulation setting—is always open to question. Case studies have been the most frequently used method in studies of resource institutions. Careful case studies can provide deep understanding of realistic settings. It is difficult, however, to generalize from any single case, with all its contextual and historical uniqueness, to other situations. Careful comparisons across cases, such as was done in the studies reviewed by Agrawal (Chapter 2), can better distinguish phenomena unique to a single case from those with some generality. But as long as case study authors use a wide diversity of theoretical approaches and thus collect data that are not comparable across studies, rarely are there enough cases available with similar variables to support strong generalizations—the data usually leave room for alternative interpretations. Researchers sometimes turn to multivariate data sets of moderate size to provide stronger evidence. Bardhan and Dayton-Johnson (Chapter 3) report on the results of some such multivariate studies, and databases are being developed that will support future studies of this type (see Gibson et al., 2000a; Poteete and Ostrom, 2001). This research strategy adds breadth not available from individual or small-n case studies, but it is limited by the range and quality of measures available for all cases in the data sets. Sometimes, variables of theoretical importance are not measured at all in a data set or can be measured only by using rough proxies. For example, Dayton-Johnson (2000) uses the number of villages where irrigators live as a measure of social heterogeneity. This measures spatial heterogeneity, but may not measure social or economic heterogeneity. Another important research method involves the use of formal deductive
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The Drama of the Commons theory, typically the theory of games (e.g., Falk et al., Chapter 5), of rational action (e.g., Bardhan and Dayton-Johnson, Chapter 3), or of optimal allocation (e.g., Tietenberg, Chapter 6). Formal theory has the virtue of precision, although the relevance of any particular formulation to practical situations can be determined only by empirical evidence. Put another way, deductions from theory generate hypotheses to explore with empirical methods. If observations do not square with theory, the theory can sometimes be elaborated to account for the data, thus generating new insights. An example is Tietenberg’s explanation (Chapter 6) of why tradable permits seem to work better for controlling emission of air pollutants than for controlling the use of fisheries and water resources. Using simple economic models, advocates have promoted tradable permits for all three resource types, but experience calls attention to differences, particularly in the importance of negative externalities. Fishers of nonregulated species and downstream water users often are harmed by tradable-permit institutions. In contrast, the permitting systems for air pollutants do not seem to have produced externalities that have disrupted these institutions. In this instance, case studies reveal the need for theorists and institutional designers to give more attention to negative externalities produced by permit holders. Because no research method is definitive, knowledge is best advanced by combining research methods in a strategy that is often referred to as “triangulation” (e.g., Campbell and Fiske, 1959) or “critical multiplism” (Cook, 1985, 1993). Results from using one method may offer hypotheses to explore with other methods, answer questions another method cannot answer, or call into question consistent conclusions from another method. A growing body of literature is intended to facilitate integration across methods and even hybridization of them (Bennett and George, 2001; King et al., 1994; McGinnis, 2000; Ragin, 1987, 2000; Ragin and Becker, 1992). Also relevant to research integration are methods of meta-analysis (e.g., Glass et al., 1981; Rosenthal, 1984; Petitti, 2000). All these kinds of exchange contribute to knowledge. Since the mid-1980s, increased communication and integration across methods of common-pool resource management research has benefitted the field. Toward a Conceptual Framework As this volume makes evident, researchers continue to identify variables that may be important for understanding and controlling the effects of resource management institutions. Agrawal (Chapter 2) identifies more than 30 such variables taken from a broad examination of the literature—and this list will surely get longer as research continues. As Agrawal notes, such a long list of variables creates significant challenges for research because of the large number of possible associations and causal relationships that must be examined. As he also notes, the development of theory presents one way through the thicket of possible
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The Drama of the Commons hypotheses. Theory can potentially limit the number of theoretically meaningful propositions that are worth examining. Theoretical propositions are beginning to emerge from recent research, as illustrated by the propositions presented by the relationships in Figures 13-1, 13-2, and 13-3. Other propositions, drawn from Chapters 2 through 12, are listed in the Appendix. We believe it is useful at this time to suggest a general conceptual framework within which such propositions can be placed. The classes of variables identified by Agrawal and others can be arranged into four broad functional categories defined by their possible theoretical relationships: Possible interventions, or independent variables. These are influential factors, including attributes of institutions, that can be altered by policy intervention over the short run. Outcomes, or dependent variables. These are things of importance to resource users that may be affected by resource conditions, resource use, and interventions. Contingencies, or moderator variables. These are factors that are out of the practical control of short-run policy interventions but that may determine how an intervention affects an outcome. Mediators, or intervening variables. These are factors that may affect outcomes but that may in turn be affected by interventions, subject to contingencies. The typical relationships among these types of variables are represented schematically in the causal model shown in Figure 13-4. A grouping of variables from the commons literature into the four categories appears in Box 13-1.4 This framework and causal model highlights some points that may be worth special attention in future research and practical analysis. One is that interventions often affect outcomes only indirectly through their effects on key intervening variables. The immediate policy challenge is often to influence variables such as the ease of monitoring the resource or adherence to group norms. The model highlights three tasks for theory: (1) to clarify how key intervening variables affect outcomes; (2) to identify the contingencies under which those mediators become critical; and (3) to identify the conditions under which particular interventions can successfully influence them. The framework also suggests that outcomes of interest depend on a variety of policy variables, not only on the design of resource management institutions. Thus, there may be more ways to achieve desired objectives than are immediately apparent. Figure 13-3 can be seen as an elaboration and specification of the general model. It shows a variety of contingencies along the left edge and postulates their effects on a set of mediators (the center of the figure), all of which in turn affect outcomes. Figure 13-3 adds theoretical specificity by identifying key contingencies and mediators and by postulating causal links among the mediators. It does not, however, postulate effects of interventions on the variables in the figure.
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The Drama of the Commons would yield results about heterogeneity that are an artifact of the proportion of cases that were government and community managed. 3 Of course, the malleability of any of the factors depends on the context, including the technologies available. For example, governments can build reservoirs that change the storage capacity of an irrigation system. Malleability is time dependent—what is impossible to change in the short run may be relatively easy to change in the long run. 4 It is important to keep in mind that the classification offered is heuristic. Reasonable people might disagree about which variables fit into which categories, and the appropriate categorization will certainly change across contexts. Our hope is that these categories can sharpen thinking, not that they provided a definitive categorization of all variables important in the dynamics of the commons. 5 The cross-field applicability of these conclusions is best illustrated by the fact that many of the key sentences in the next seven paragraphs are taken directly or paraphrased closely from a previous National Research Council (2000:12-13) work on international conflict resolution. 6 Much of the language in this and the next two paragraphs is taken from National Research Council (2000:15); the ideas draw heavily on the work of George (1993). 7 Of course, monitoring is less than perfectly accurate and may be so inaccurate as to convey no information or even perverse information about the resource and the management institution. Management is of course much less likely to be successful in the absence of accurate monitoring, but how accurate is accurate enough depends on the context. 8 When the dynamics of a resource are nonlinear and unpredictable, the standard assumptions about the ability of prices and markets to allocate resources may not apply—price signals may not adequately indicate impending shortages. REFERENCES Abel, T.D., and M. Stephen 2000 The limits of civic environmentalism. American Behavioral Scientist 44:614-628. Agrawal, A., with C. Britt and K. Kanel 1999 Decentralization in Nepal: A Comparative Analysis. A Report on the Participatory District Development Program. San Francisco, CA: ICS Press. Agrawal, A., and G.N. Yadama 1997 How do local institutions mediate market and population pressures on resources?: Forest panchayats in Kumaon, India. Development and Change 28(3):435-465. Aldrich, H.E., and P.V. Marsden 1988 Environments and organizations. In Handbook of Sociology, N.J. Smellser, ed. Newbury Park, CA: Sage. Asquith, N.M. 1999 How Should the World Bank Encourage Private Sector Investment in Biodiversity Conservation? Durham, NC: Sanford Institute of Public Policy, Duke University. Axelrod, R. 1984 The Evolution of Cooperation. New York: Basic Books. Barkin, J.S., and G.E. Shambaugh 1999 Anarchy and the Environment. The International Relations of Common Pool Resources. Albany: State University of New York Press. Becker, C.D. 1999 Protecting a garua forest in Ecuador: The role of institutions and ecosystem valuation. Ambio 28(2):156-161. Benedick, R. 1991 Ozone Diplomacy: New Directions in Safeguarding the Planet. Cambridge, MA: Harvard University Press.
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The Drama of the Commons APPENDIX TO CHAPTER 13 Table 13-A presents a collection of findings or propositions put forward by the authors of Chapters 2 to 12 of this volume. It is organized under five headings: Institutional Arrangements, Resource System Characteristics, Group and Individual Characteristics, External Environment, and Interaction among Factors. In terms of the schematic causal model of Figure 13-4, the first heading includes propositions that focus on interventions and the next three headings focus on contingencies. The last category, with one proposition in it, reflects the likelihood that interventions are shaped by contingencies. Of necessity, the box is telegraphic, covering only the highlights and attempting to summarize careful arguments in single phrases. It is not a full summary of what we know. Rather, we view it as a guide back to the theoretical and substantive content of the 11 chapters that form the heart of the book. TABLE 13-A Hypotheses about Resource Management Institutions Proposed in Chapters 2 to 12 Institutional Arrangements ◆ Effective commons management is a cross-scale co-management process (local, governmental, national, supranational) that allocates specific tasks to the proper level of social organization and ensures that cross-scale interactions produce complementary actions rather than actions that interfere with or undermine one another (Ch. 6, Ch. 8, Ch. 9, Ch. 12). ◆Higher level institutions lack sensitivity to the knowledge, rights, and interests of local stakeholders (Ch. 8). ◆Rather than identifying the “appropriate institutional level,” we need to examine how various institutional levels could be vertically linked (Ch. 8 and Ch. 9). ◆Linking institutions vertically can result in tensions between benefits and costs of institutional arrangements at various levels. These tensions depend on the characteristics of the resource and of the resource users (Ch. 8). ◆Successful commons management requires a system of resilient institutions that evolve over time and reflect dynamics of the ecosystem (and the goods and services they provide) (Ch. 12 and Ch. 9). ◆Tradable permits are more successful in air pollution programs than in fisheries and water resources. The initial allocation problems of tradable permits are least intense for air pollution and most intense for fisheries (Ch. 6). ◆Tradable permits are a flexible approach to resource management. Successful applications of tradable permits can simultaneously protect the resources and provide sustainable incomes for users (Ch. 6). ◆Common property regimes easily evolve within close-knit relations and promote adaptation, long-term stability, and risk sharing (Ch. 7). ◆Tradable environmental allowances apply to loose and stranger relations, and encourage investment, innovation, and commerce (Ch. 7).
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The Drama of the Commons ◆Tradable environmental allowances are less adaptive to natural environment and more adaptive to human demand; common property regimes are the reverse (Ch. 7). ◆Nongovernmental or governmental organizations should undertake institutional development when individuals or small groups are unwilling and/or able to bear the required costs (Ch. 11). ◆Institutions affect which type of individuals (selfish or reciprocal) are pivotal in social outcomes (Ch. 5). ◆Sanctioning enhances cooperation when there are some reciprocators and the cost of sanctioning is not too high (Ch. 5). ◆Communication enhances cooperation by facilitating coordination, by providing chances to express approval and disapproval, and by creating group identity (Ch. 4 and Ch. 5). ◆Reciprocity, the essential element stimulating cooperation in multiple-time games, results from an individual’s perception of relative payoffs and kindness of other individuals in the game (Ch. 5). ◆Successful institutions find the right balance between incentives, social influence manipulation, and sanctions (Ch. 4). Resource System Characteristics ◆Larger, simple, and single-focus resources with additive resource use are more easily managed by tradable permits than small, complex, and interactive resources with subtractive use (Ch. 7). ◆Complex resource systems severely limit predictive ability but do not preclude understanding (Ch. 10). ◆Local variations in biogeophysical conditions challenge unified institutional designs made at higher levels (Ch. 8). ◆Resource characteristics are associated with both more or less co-management. Less comanagement tends to occur in air pollution and other large-scale resources and more comanagement tends to occur in groundwater basins and fisheries (Ch. 6). Group and Individual Characteristics ◆Smaller groups more effectively evoke prosocial instincts than larger groups (Ch. 12) and are more likely to achieve cooperation (Ch. 4). ◆Economic and social heterogeneity have independent effects that operate through different causal mechanisms (incentives versus norms). Either may hamper collective action when large start-up costs are involved (Ch. 3). ◆Heterogeneity in power leads to defection and overharvesting (Ch. 4). ◆People generally have a disposition to cooperate with each other, although dispositions vary considerably from person to person, society to society, and time to time. The variation is best explained by the existence of complex cultural traditions of social institutions (Ch. 12). ◆Evolved prosocial tendencies among human beings combined with culturally evolved institutions make cooperation more likely and more effective (Ch. 12). ◆Users are more likely to devise institutions governing resources if they have good information about the variables that affect the structure of a resource and its dynamics and the seriousness of resource depletion. Identifying factors that affect the dynamics of a resource and that can be manipulated by institutional design is important to the adaptation of institutions (Ch. 11). ◆Individual differences (motives, trust and fear, gender, and culture) and nonindividual differences (institutional design, social structure, perception of the cause of resource depletion, and framing of the problem) affect individuals’ decisions about the extent of resource use (Ch. 4).
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The Drama of the Commons ◆Interaction of economic incentives and social mechanisms affect the performance of institutions governing resources (Ch. 3). External Environment ◆Development in computer and information technology decreases monitoring costs and thereby improves institutional performance (Ch. 6). ◆Not the market but the rapid change that accompanies market penetration is the reason for destabilizing traditional commons institutions (Ch. 12). Interaction among Factors ◆The emergence of common-pool resource institutions depends on collective-choice/rule-in-use and features of both the resources in question and their users (Ch. 11 and Ch. 2). Compiled with the help of: T.K. Ahn, Jianxun Wang, Oyebade Kunle Oyerinde, Paul Aligica, Workshop in Political Theory and Policy Analysis, Indiana University.
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The Drama of the Commons This page in the original is blank.
Representative terms from entire chapter: