Author: Hannah Wang
Indonesian women participating in an arisan, a traditional microfinance organization
Research Questions
- To what extent do socially cooperative behaviors and institutions in communities contribute to individuals’ and households’ social mobility outcomes?
- What types of socially cooperative behaviors and institutions are most beneficial for boosting participants’ social mobility outcomes?
Key Social Mobility Finding
Based on preliminary results, participation in different types of community organizations is associated with varying levels of subjective and income social mobility for individuals.
Background
“Social capital refers to the quality of human relations within some well-defined social group that enables members of this group to act in cooperation with one another for achieving mutual benefits. More formally, it is defined as ‘features of social organization such as networks, norms and social trust that facilitate cooperation and coordination for mutual benefit’ (Putnam 1995: 67).”
—Anirudh Krishna, 2003
Why social capital?
In recent years, development scholars and policymakers have identified social capital as a key driver of economic growth. In 2001, the World Bank advocated for promoting social capital as a development strategy, writing that “social cohesion is critical for societies to prosper economically and for development to be sustainable.” This strategy is based on the foundational work of scholars like Fukuyama (1995) and Putnam (1995), who demonstrated that high social capital communities experienced lower transaction costs and greater collective action towards political and economic goals.
What is the impact on social mobility?
Many mechanisms have been posited for the effects of social capital on mutually beneficial forms of social cooperation, including exchange of favors within social networks (Jackson et al. 2012), provision of informal insurance within communities (Breza et al. 2015), informal contract enforcement and cooperation (Chandrasekhar et al. 2014), and collective action on communal goals like environmental conservation and natural resource management. However, more research is needed to clarify the extent to which these social cooperative behaviors benefit their participants and the mechanisms through which these beneficial effects occur.
Methods
Data
Map of 13 Indonesian Provinces covered by IFLS
I use data from multiple waves of the the Indonesia Family Life Surveys, a longitudinal socioeconomic and health survey conducted between 1993 and 2014 on a sample of households representing about 83% of the Indonesian population in 13 out of 26 provinces. The latest wave of IFLS surveys conducted in 2014 included 16,204 households and 50,148 individuals.
Variables
| Social Capital Variables | Description | |
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Community Participation (individuals) | This variable tracks individual adults’ level of participation in a variety of community organizations, including arisans, or traditional Indonesian rotating credit and savings associations (ROSCAS). |
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Citizen Participation (communities) | This variable measures the community’s level of participation in various forms of mutual cooperation like Village Cooperatives and other forms of community development. |
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Social Norms & Cooperation (communities) | For this variable, local experts in traditional law and customs (adat) in each village were surveyed on whether a particular norm holds in the community (e.g. “Is there an ethic of mutual cooperation in this village?”). |
| Social Mobility Variables | Description | |
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Employment Income Mobility (individuals) | To measure income mobility, I found the percentage change in an individual’s annual salary between 2000 and 2014. |
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Subjective Relative Mobility (individuals) | This variable measures individuals’ subjective perception of their own relative mobility over time. I use the question, “Please imagine a six-step ladder where on the bottom (the first step) stand the poorest people, and on the highest step (the sixth step) stand the richest people. On which step are you today?” To measure relative mobility over time, I found the difference between an individual’s perceived socioeconomic status in 2000 and 2014. |
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Business Income Mobility (households) | This variable provides the amount of household income generated from both farm and non-farm businesses. To measure income mobility, I found the percentage change in income for a household between 2000 and 2014. |
Preliminary Results
My preliminary results examined individual participation in community organization in 2000 and social mobility outcomes as measured by changes in employment income and subjective relative mobility from 2000 to 2014.
Participation in Community Organizations
These results showed that the level of participation in different types of community organizations varied significantly. Among the different types of community organizations, participation in voluntary labor and community meetings were the most common.
Subjective Relative Mobility
Individuals most commonly reported seeing no change in their perceived socioeconomic status between 2000 and 2014. However, many individuals reported an increase or decrease in their socioeconomic status, with a roughly normal distribution.
Differences in Social Mobility Outcomes Based on Type of Community Participation
Initial analyses of the social mobility outcomes associated with participation in different types of community organizations show that individuals who participated in Water for Drinking System/Supply community programs and Community Meetings experienced the greatest average increase in income (left); however, individuals who participated in Community Weighing Posts (posyandu), a type of community-based health service facility, and Cooperatives experienced the greatest increase in subjective socioeconomic status (right).
References
Banerjee, Abhijit V. and Chandrasekhar, Arun G. and Duflo, Esther and Jackson, Matthew O., The Diffusion of Microfinance (January 2012). CEPR Discussion Paper No. DP8770.
Jackson, Matthew O., Tomas Rodriguez-Barraquer, and Xu Tan. 2012. “Social Capital and Social Quilts: Network Patterns of Favor Exchange.” American Economic Review, 102 (5): 1857-97.
Arun G. Chandrasekhar & Cynthia Kinnan & Horacio Larreguy, 2014. “Social Networks as Contract Enforcement: Evidence from a Lab Experiment in the Field,” NBER Working Papers 20259, National Bureau of Economic Research, Inc.
Breza, Emily, Arun Chandrasekhar, Daron Acemoglu, Abhijit Banerjee, Sam Bowles, Pascaline Dupas, Matt Elliott, Itay P. Fainmesser, Garance Genicot, B. Golub, Matthew O. Jackson, Jacob D. Leshno, Markus M. Möbius, Muriel Niederle, Rajiv Sethi, Ryan Sheely and Adam Szeidl. “Network Centrality and Informal Institutions: Evidence from a Lab Experiment in the Field.” (2015).
Krishna, Anirudh and Norman Uphoff. “Mapping and Measuring Social Capital: A Conceptual and Empirical Study of Collective Action for Conserving and Developing Watersheds in Rajasthan, India.”
Krishna, Anirudh. “Understanding, Measuring and Utilizing Social Capital: Clarifying Concepts and Presenting a Field Application from India.”
Knack, S., Keefer, P. (1997). Does Social Capital Have an Economic Payoff? A Cross-Country Investigation. Quarterly Journal of Economics 112 (4): 1251-1288.