mechanisms that might be used to ameliorate negative impacts of heterogeneity. The second strand of literature, on the other hand, starts from the premise that greater civic engagement facilitates public good provision, in part because such engagement alleviates negative effects of heterogeneity. Within this strand, empirical studies document factors that facilitate or inhibit collective action outcomes in community-driven development and social fund projects in developing countries, with some papers specifically focusing on the role of women’s leadership representation and voice. A more limited set of papers attempts to identify the effect on welfare of local public good provision through collective action.

This paper ties together both strands of literature by first developing a stylized theoretical model of “community welfare optimization”, and then by testing hypotheses stemming from the model empirically. We build on the insights from the game theoretic literature and model a community seeking to maximize social welfare but subject to transactions costs of acting collectively. In particular, we posit that negotiating, monitoring and enforcement costs are a function of the schedule of individual members’ agreed contributions. Schedules that fully reflect underlying heterogeneity are seen as “fair”, and lead to lower monitoring and enforcement costs; however, negotiation costs are higher than agreeing on more simple schedules, such as equal contributions by all. While highly stylized, maximizing over community welfare as a function of transactions costs enables us to explicitly highlight informational requirements necessary to construct such a fair schedule in the face of heterogeneity, which is often obscured in extant game-theoretic models.

We empirically test the theoretical model by utilizing the unique data solicited through the Household and Community Questionnaires of the nationally-representative Malawi Third Integrated Household Survey (IHS3) 2010/11 and linking the geo-referenced HIS3 household and community data to geospatial and administrative data sources. Subsequently, we (i) formulate a composite index, based on principal components analysis, of community collective capacity for public good provision, (ii) regress the index as a function of a rich set of attributes that corresponds to the theoretical model, and (iii) examine the effects of collective capacity for public good provision on community median estimates of maize yield and household real annual consumption expenditures per capita in a Two-Stage Least Squares Framework that takes into account the non-random nature of the explanatory variable of interest. Our data-intensive exercise is conducted at the community level, limited to the rural enumeration areas visited as part of the IHS3. By relying on the IHS3, and bringing in data from other geospatial and administrative sources, the paper contributes to the otherwise limited empirical analyses based on nationally representative data with large sample sizes. To the best of our knowledge, no largesample analyses have been able to test whether community leadership that reflects underlying community heterogeneity improves public good provision, although there is some case study evidence to support that hypothesis.

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