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ESA – World Meeting Rome, June 30, 2007. Inequality, networks and distributive decisions: A field experiment. Ben D’Exelle University of Antwerp - IOB Maastricht University Arno Riedl Maastricht University. Research questions.
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ESA – World Meeting Rome, June 30, 2007 Inequality, networks and distributive decisions: A field experiment Ben D’Exelle University of Antwerp - IOB Maastricht University Arno Riedl Maastricht University
Research questions What determines “giving” in small-scale (“face-to-face”) societies : • Social networks: social distance, network structure, individual position within networks • Individual characteristics of community members (economic variables, sex, age, education, etc.) • Correlation between both dimensions? • Use of a dictator game experiment, complemented with survey data on individual characteristics and social networks
Literature references • Social networks and dictator game giving: • Leider, Mobius, Rosenblat & Do (2006): dictators give 50% more to friends than to strangers • Goeree, McConnell, Mitchell, Tromp & Yariv (2006): Distance in networks lowers giving • Brañas-Garza, Cobo-Reyes, Paz Espinosa, Jiménez & Ponti (2006): Social integration (betweenness) increases giving.
Experimental design & procedures • What is new about our experiment: • Large heterogeneity: rural village where poverty and inequality are highly present (economic inequality; sex; education; age) • Multiple relations: details on the type of relation (15 types)
Experimental design & procedures • Dictator game (divide 20 coins of 1 c$) with 1 stranger and 5 different (randomly selected) village members; • max. earnings = two days income (6.7$) • Minimizing reciprocity by one-way anonymity: only dictator knows the identity of the recipient • Decentralized setup: individual visits (lower self-selection; lower public exposure; no communication) • Reduce experimenter-effect: use of rings (to maintain weight of boxes) + sealing of boxes + recording of decisions by supervisor • First, the networks (trust-building with participants); then, the experiment in one day (to limit contagion)
Results 1 2
Procedure to study social relations • Measuring social networks: • Use of small cards, each representing a household (on each card the names of both husband and wife) • Do you know the household? (93.5% of all possible dyads) • Do you have a social relation with one of its members? • Give details on the type of relation (e.g. land, labor, mutual support, family, religion, neighbor, etc.). • Completeness of networks: 100 out of 123 adults (81.3%)
Procedure to study social relations • Analyzing social networks: • Only household heads. Other members were rarely mentioned. • Members of the same household are always linked whatever the type of relation we are looking at. • OR-networks: we symmetrized the adjacency matrix. We took the maximum value and missing values were eliminated by the non-missing value in the other direction. • Few missing values remained (3.5%); conversion into zeros.
Mutual support network in the village (N = 123) density = 0.0321 (matrix average); mean degree = 3.919 (3.754); freeman’s graph centralization measure = 21.73%
Conclusions • Networks matter for dictator giving • But, it depends on the networks you look at • General relation: • Distance and Bocanich centrality • Mutual support: • Ties within the ego-network (norm-based behaviour) • Sex and economic variables remain important, when controlling for networks
Multivariate analysis Regression on coins left to recipient Random effects (panel model); robust standard errors
Mutual support networks Distance Centrality
Multivariate analysis Regression on number of coins left to recipient
Correlation between networks and individual characteristics • Possible correlation between networks and individual characteristics (economic assets, sex, age, etc.) • Most important networks that may be influenced by individual characteristics are mutual support relations, economic relations (any kind of economic transaction) and friendship relations
Network formation: • Procedure to analyze individual social relations: • We only took account of the household heads. People only very occasionally mentioned other household members. • Second, members of the same households are always linked whatever the type of relation we are looking at. • We symmetrized the resulting adjacency matrix. For each dyad in each of both directions, we took the maximum value and missing values were eliminated by the non-missing value in the other direction. • After this only a limited number of missing values remained, which we converted into zeros. • Most important networks that may be influenced by individual characteristics are friendship relations and mutual support relations
Multivariate analysis Regression on number of coins left to recipient
Individual network position • Centrality: degree centrality • But, the links other people have are important too: • The links other people have: • Control of access and benefits (structural holes; Burt, 1992) • Leadership position (responsibility) • Searching costs (Coleman, 1990) • The links other people have in the ego-network: • Reputation effects (Burt, 1992) • Norm-based behavior (reputation effects, indirect reciprocity): importance of mutual support networks • Distinguish between mutual support relations and general (whatever type) relations; the first are more specific and may be related with social norms
Mutual support networks 2. Centrality
Mutual support networks 2. Centrality
Research questions • Our interest comes from the current debate in development economics on decentralization : • Decentralization: delegation to the local level of any type of decision-making • In our case: the task to distribute aid resources → less costly but also less control on distributive outcomes • Two ways for the policymaker to maintain certain influence on distribution • One focus: monitoring mechanisms • Other focus (= our focus): influencing local determinants behind local distributive processes
Experimental design • First, mapping of social networks; confidence is built with local participants; support of local leaders • Then, experiment in one-day; contagion is limited • Payments to recipients are made the day after; recipients are likely to have played as dictator too (acceptance of payments!)