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How Do Neighbors Influence Investment in Social Capital? Homeownership and Length of Residence

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Abstract

This paper uses individual data from Japan to explore how the circumstances of where a person resides is related to the degree of their investment in social capital. Controlling for unobserved area-specific fixed effects and various individual characteristics, I found (1) not only that homeownership and length of residence are positively related to investment in social capital, but also that rates of homeownership and long-time residency in a locality increase an individual’s investments in social capital. Also, (2) the effects of local neighborhood homeownership and local length of residence are distinctly larger than those of an individual’s homeownership or length of residence.

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Notes

  1. 1.

    Some works have criticized the ambiguity of the definition of social capital and pointed out drawbacks in measurement (e.g., Paldam 2000; Durlauf 2002a, b).

  2. 2.

    Social network considered as social capital appears to make a contribution to technological diffusion among colleagues (Yamamura 2008a).

  3. 3.

    It is found that people are less inclined to cooperate to resolve collective problems in more heterogeneous communities (Alesina and LaFerrara 2000; Yamamura 2008b).

  4. 4.

    Glaeser et al. (2002) applies standard optimal investment to analyze the social capital formation.

  5. 5.

    The data for this secondary analysis, “Social Policy and Social Consciousness survey (SPSC), Shogo Takekawa,” were provided by the Social Science Japan Data Archive, Information Center for Social Science Research on Japan, Institute of Social Science, The University of Tokyo.

  6. 6.

    According to the data used in this research, 4 areas do not contain metropolitan cities. Thus, only 40 local groups exist in the data.

  7. 7.

    For instance; (1) membership of nonprofessional organizations, (2) knowing the names of local political luminaries (the head of the local school board and the local U.S. representative), (3) voting in local elections, (4) church attendance, (5) gardening, and (6) trying to solve local problems.

  8. 8.

    DiPasquale and Glaeser (1999) considered the average group homeownership rate as an exogenous variable and used it as an instrument variable. Similar results are obtained if the same estimation method is employed using the data used for this research, although estimation results are not reported. I regard such a group average variable as more useful for capturing the neighborhood effect as an independent variable.

  9. 9.

    Sample size is 3075 when all observations are used for estimations. As shown in Table 1, observations are 2349 when HOME takes 1. Thus, the homeownership rate in the sample is 76%. More precisely, the 2349 homeownerships are made up of 1878 individual ownership and 471 of parent ownership. Therefore, the sample size used in the alternative estimations becomes 1197 since the individual homeownership observations are omitted. In this case, the parent homeownership rate becomes 39%. In short, the sample used in estimations of Tables 4 and 6 is divided into the sample of individual homeowners and others. The sample excluding individual owners is used for estimations in Tables 5 and 7.

  10. 10.

    A continuous variable that captures the number of years at home is not available. However, LIVE10 and LIVE20 are available and so were used in this paper. A continuous variable has more precise information about the length of residence and so should be used in a future study.

  11. 11.

    People would suffer from ostracism if they infringe social norms considered as local rules, leading to people following norms (Hayami 2001). Such a community mechanism seems to be, to a certain extent, effective even in modern Japanese society (Yamamura 2008c).

  12. 12.

    DiPasquale and Glaeser “generate an estimate of the local homeownership rate by calculating the average homeownership rate in each city-size category in each state” (DiPasquale and Glaeser 1999, p.377).

  13. 13.

    Generational heterogeneity also increases social trust in Japan (Yamamura 2008e).

  14. 14.

    Annen (2001) argued that the exclusive social capital induces the rent-seeking activity.

  15. 15.

    Knack (2003) made it evident that the positive effect of the inclusive social capital is observed while the negative effect of exclusive social capital is not observed.

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Correspondence to Eiji Yamamura.

Appendix

Appendix

Table 6 Determinants of investment for social capital (Ordered Probit model)
Table 7 Determinants of investment for social capital: Living in home owned by parents (Ordered Probit model)

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Yamamura, E. How Do Neighbors Influence Investment in Social Capital? Homeownership and Length of Residence. Int Adv Econ Res 17, 451–464 (2011). https://doi.org/10.1007/s11294-011-9318-z

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Keywords

  • Social capital
  • Homeownership
  • Length of residence

JEL

  • D71
  • R11
  • R23