Data and Code for: Age Set vs. Kin: Culture and Financial Ties in East Africa
Principal Investigator(s): View help for Principal Investigator(s) Jacob Moscona, Harvard University; Awa Ambra Seck, Harvard University
Version: View help for Version V1
Name | File Type | Size | Last Modified |
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Replication | 07/03/2024 05:25:PM |
Project Citation:
Moscona, Jacob, and Seck, Awa Ambra. Data and Code for: Age Set vs. Kin: Culture and Financial Ties in East Africa. Nashville, TN: American Economic Association [publisher], 2024. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2024-07-10. https://doi.org/10.3886/E192224V1
Project Description
Summary:
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We study how social organization shapes patterns of economic interaction and the effects of national
policy, focusing on the distinction between age-based and kin-based groups in sub-Saharan Africa.
Motivated by ethnographic accounts suggesting that this distinction affects redistribution, we analyze a cash transfer program in Kenya and find that in age-based societies there are consumption
spillovers within the age cohort, but not the extended family, while in kin-based societies we find
the opposite. Next, we document that social structure shapes the impact of policy by showing that
Uganda’s pension program had positive effects on child nutrition only in kin-based societies.
Scope of Project
Subject Terms:
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Social structure;
redistribution;
financial networks;
age sets;
family;
pensions
JEL Classification:
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G51 Household Finance: Household Saving, Borrowing, Debt, and Wealth
O12 Microeconomic Analyses of Economic Development
Z10 Cultural Economics; Economic Sociology; Economic Anthropology: General
G51 Household Finance: Household Saving, Borrowing, Debt, and Wealth
O12 Microeconomic Analyses of Economic Development
Z10 Cultural Economics; Economic Sociology; Economic Anthropology: General
Geographic Coverage:
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Kenya and Uganda
Time Period(s):
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2006 – 2016
Universe:
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Individuals and households in Northern Kenya (Hunger Safety Net Program data) and in Uganda (Demographic and Health Surveys). In both cases, also focus on a population of children under the age of five for part of the analysis.
Data Type(s):
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experimental data;
observational data;
survey data
Methodology
Unit(s) of Observation:
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Individual
Geographic Unit:
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District/sub-location
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