Inequality, networks and distributive decisions: A field experiment Ben D’Exelle University of Antwerp - IOB Maastricht University Arno Riedl Maastricht University ESA – World Meeting Rome, June 30, 2007

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 Research questions

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: 1. Large heterogeneity: rural village where poverty and inequality are highly present (economic inequality; sex; education; age) 2. Multiple relations: details on the type of relation (15 types)

 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) Experimental design & procedures

Results 21

Economic resources (between subject analysis)

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%)

 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. Procedure to study social relations

Mutual support network in the village (N = 123) density = (matrix average); mean degree = (3.754); freeman’s graph centralization measure = 21.73%

Social distance (general relation)

Coef.S.E. Sex of the dictator (1 = male; 0 = female) Land: dictator yes; recipient yes (dummy) Land: dictator yes; recipient no (dummy) Land: dictator no; recipient yes (dummy) Distance Size of ego-network (dictator) Number of ties in ego-network (dictator) Power (Bonacich; neg. beta) Number of decision (min. = 1; max. = 5) Constant Dep. var. = coins to recipient

General relation Coef.S.E. Sex of the dictator (1 = male; 0 = female) ** Land: dictator yes; recipient yes (dummy) Land: dictator yes; recipient no (dummy) Land: dictator no; recipient yes (dummy) Distance Size of ego-network (dictator) Number of ties in ego-network (dictator) Power (Bonacich; neg. beta) Number of decision (min. = 1; max. = 5) Constant *** R-squared Number of observations 280 Dep. var. = coins to recipient

General relation Coef.S.E. Sex of the dictator (1 = male; 0 = female) *** Land: dictator yes; recipient yes (dummy) ** Land: dictator yes; recipient no (dummy) ** Land: dictator no; recipient yes (dummy) Distance 0.364*** Size of ego-network (dictator) ** Number of ties in ego-network (dictator) Power (Bonacich; neg. beta) ** Number of decision (min. = 1; max. = 5) Constant *** R-squared Number of observations 280 Dep. var. = coins to recipient

General relation Mutual support Coef.S.E.Coef.S.E. Sex of the dictator (1 = male; 0 = female) *** ** Land: dictator yes; recipient yes (dummy) ** Land: dictator yes; recipient no (dummy) ** Land: dictator no; recipient yes (dummy) Distance 0.364*** Size of ego-network (dictator) ** Number of ties in ego-network (dictator) ** Power (Bonacich; neg. beta) ** Number of decision (min. = 1; max. = 5) * Constant *** *** R-squared Number of observations 280 Dep. var. = coins to recipient

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

Mutual support networks Distance Centrality

 Do dictators take account of their economic situation?  Do female dictators behave differently? The influence of individual characteristics

Sex of dictator FemaleMale Sex of the dictator Sign. = N = 30 N = 27 Coins to stranger (mean)

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

 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 Network formation:

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

Wealth ranking of recipient

Economic resources (within subject analysis)

Sex of dictator and recipient

Mutual support networks 2. Centrality

Mutual support networks 2. Centrality

Logit regression on directed relations

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!)