Collective action has both intrinsic and instrumental value. Being part of a group and participating toward meeting a common objective provides direct benefits to individuals. In the Ethiopian survey data used in this study, individuals who reported having larger networks also reported higher levels of happiness. Such correlations are not unique to Ethiopia. Using data from the World Values Survey, Helliwell and Putnam (2004) found that individuals who reported higher levels of individual and collective civic engagement also reported higher scores on measures of subjective well-being. Collective action is also a means to an end. For example, the joint management of irrigation canals, rangelands, and fisheries involves actions by groups that allow individuals to generate higher and more sustainable incomes. This chapter focuses on a specific, instrumental dimension of collective action: the role of groups and networks in helping households in poor communities manage their exposure to risks and cope with shocks to their livelihoods, which are identified as an important determinant of poverty and well-being by Di Gregorio et al. (this volume, Chapter 2). In doing so, the chapter builds on research addressing how poor households respond to shocks; see Morduch (2005) and references therein, the review paper by Skoufias and Quisumbing (2005), and the recent collection edited by Dercon (2005). These show that in the face of shocks households can partially smooth consumption, but not perfectly; as might be expected, idiosyncratic shocks (for instance, low or late rainfall on household plots) are more likely to be insured collectively than are generalized shocks (such as low rainfall on most plots in the village). In most empirical studies of risk smoothing-for example, that of Townsend (1994)-the insurance unit has been assumed to be the village. Studies using Townsend's approach have often found that households are able to cope with idiosyncratic shocks but not covariate shocks, implying that local insurance mechanisms are inadequate to cope with aggregate shocks. More recent studies (for example, that of Munshi and Rosenzweig 2005) have begun to question the assumption that the appropriate unit of risk smoothing is the village. They suggest that consumption is smoothed within subcaste networks that extend beyond the village. Indeed, the literature on migration and remittances suggests that networks can cross geographic boundaries, with the formation of migrant networks at destination sites affected by shocks in the original locality (Munshi 2003). There is also a subset of studies that has attempted to isolate the role of gift giving and informal loans in helping households to cope with shocks. The results indicate that households are not perfectly "altruistic"; the problems of asymmetric information and limited commitment mean that households are not likely to be fully insured (Foster and Rosenzweig 2000; Ligon, Thomas, and Worral 2000). 1 However, such analyses do not assess whether responses differ depending on the nature of the shock, and indicators for collective action and participation in different types of networks are generally either absent or rudimentary. There are some exceptions. Fafchamps and Lund (2003) differentiated among different types of risk, specifically addressing how different sorts of networks are used. They showed that risk sharing appears to occur mostly in very small networks of close friends and families-networks that may not have the heterogeneity required to efficiently share risk. In the case of Ethiopia, Dercon and Krishnan (2000) specifically addressed potential gender differences in terms of risk coping and found that poor women, particularly in one region, are less able to smooth consumption in the face of risks. The collective action literature shows that the density of networks in general, and participation in more formal groups in particular, can lead to either more effective participation in community-based activities (White and Runge 1994; Isham and Kahkonen 2002) or higher household incomes (Narayan and Pritchett 1999; Pender and Scherr 2002; Haddad and Maluccio 2003). However, there is a lack of consensus on the impact of heterogeneity on collective action. In most empirical studies in which researchers have used various measures of heterogeneity to examine its impact on collective action or on household incomes directly, the impact of any type of heterogeneity has tended to be negative or not significant (Ahuja 1998; Alesina and La Ferrara 2000; Bardhan 2000; McCarthy and Vanderlinden 2004; Place et al. 2004), with the interesting exception of results reported by Grootaert (2001). It is often hypothesized that heterogeneity of any sort makes finding agreements mutually beneficial and acceptable to all more costly and that sociocultural heterogeneity in particular is likely to reduce trust among group members and also to reduce the efficacy of social sanctioning (Easterly and Levine 1997). On the other hand, much of the literature on group formation and networks highlights the added benefits to diversity (or heterogeneity) among members along any number of dimensions. Risk pooling is certainly more efficient when one's income is less correlated with that of other members of the groups, which implies that having members with different agricultural activities and occupational structures is better for the insurance mechanism. Many networks exist to share information; clearly if everyone has the same background and the same current sociocultural and economic profile, there is little need to rely on networks to share information. Finally, there may be economies of scope in terms of information gathering-or accumulation of other assets, for that matter. In this case, economic heterogeneity also favors the pooling of resources to the benefit of all. Because there may be competing impacts of different types of heterogeneity on the functioning of groups, it becomes critical to examine which groups are able to harness the positive effects of heterogeneity and mitigate its negative effects. Finally, if groups differ in terms of degree of heterogeneity and geographic dispersion, what kinds of enforcement mechanisms can be used to ensure compliance with network objectives and norms of behavior? Members of local networks are easier to monitor, but local networks are less able to insure against covariate shocks. Spatially diversified networks offer some protection against covariate shocks, but network members will be more difficult to monitor. If information and communications technologies are poor, more distant network members may not even be aware of a shock that occurred in their original communities. Interest in these issues is more than just a matter of academic curiosity. Understanding these networks is as crucial to understanding the determinants of poverty and the policies necessary to move people out of poverty as understanding land tenure or access to financial capital. A misunderstanding of the roles of these networks can lead to policy changes that have unintended consequences on the functioning of the networks, with potentially damaging effects on the capacity of the poor to mitigate, and cope with, the effects of shocks. At the same time, a better understanding of such networks can lead to the identification of policies that complement networks that already serve the poor well and also to policies that can substitute for networks that simply are not reaching the poor. In terms of the conceptual framework presented in Chapter 2, this chapter focuses on the impact of risks and shocks (especially natural shocks in the form of drought, death, and illness) on household well-being and the role of local collective action institutions in dealing with these risks. We show the impact of asset endowments (human and natural capitals, in particular) on the severity of these shocks, as well as on the composition of the groups and networks. We also discuss the size of collective action institutions and their scope to effectively contribute to poverty and vulnerability reduction. Using the language of the conceptual framework, the discussion focuses almost exclusively on the internal actors (iddir members) in the action arena, which is represented by the iddir (burial societies or funeral association). The patterns of interaction that emerge here are the innovative forms of cooperation (through cash transfers and loans given to iddir members to cope with a shock) and rules (governing that composition and operation of iddir) that allow poor households to achieve certain poverty-related outcomes, such as maintaining necessary levels of income and fulfilling basic needs, as well as sustaining these groups. More generally, this chapter highlights the potential of local forms of collective action beyond economic groups (such as credit and savings associations) to enable poor households to cope with local shocks by overcoming the problems of moral hazard and adverse selection that the typical insurance schemes face. It provides an interesting bridge from the natural resource management (NRM) literature to the non-NRM poverty studies by showing how the same principles that apply to collective action for resource management (effective rules on membership, sanctions for noncompliance, and so on) can translate into non-NRM arenas and create conditions and incentives for effective group operation-in this case, for managing risks. It adds new insights to the discussion of the impact of heterogeneity on the effectiveness and sustain-ability of local groups and networks, which is of great interest and has long been debated in the NRM literature. 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