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The Influence of Social Capital on Work Participation and Income Earning in Indonesia

The Influence of Social Capital on Work Participation and Income Earning in Indonesia

Title: The Influence of Social Capital on Work Participation and Income Earnings in Indonesia

Author: Yefin Amandri Meidika

Item Type : Thesis (Thesis)

Affiliations: Master of Management Science Study Program, Faculty of Economics and Business, Universitas Airlangga , Surabaya, Indonesia

Publisher: Universitas Airlangga

 

Abstract

This study aims to analyze the influence of social capital on work participation and labor income. Social capital is formed by three dimensions: 1) trust and tolerance, 2) groups and networks, and 3) reciprocity and collective action. Data were obtained from the 2017 Happiness Level Measurement Survey. Micro household data analyzed were 58,806 households. Binary logistic regression was used to analyze the influence of social capital on work participation. The influence of social capital on income was examined using ordinal logistic regression analysis. The work participation model involving the independent variable of social capital was able to explain better than the work participation model that did not involve social capital. From the results of the study, it was found that network and reciprocity significantly influenced work participation. Trust did not significantly influence individuals' willingness to work. Extensive involvement in several communities gave rise to weaker ties (weak ties). Weak ties are useful when someone wants to obtain information about job vacancies. Analysis of the income model showed that three dimensions of social capital significantly and positively influenced income. Trust had the greatest influence when associated with income. Trust forms within communities with strong ties but fewer members (strong ties). Strong ties are beneficial when someone wants to earn a higher income from their work.

Keywords: social capital, labor market, income, binary logistic regression, ordinal logistic regression

 

Sources: http://repository.unair.ac.id/94166/