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Policy Innovation in Local Jurisdictions: Testing the Neighborhood Influence Against the Free-Riding Hypothesis

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  • Rincke, Johannes
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    Abstract

    Before making difficult decisions, individuals tend to collect information on decision makers in reference groups. With respect to policy innovations in a decentralized public sector, this may give rise to positive neighborhood influence on adoption decisions. On the other hand, due to learning externalities, an incentive exists to free-ride on policy experiments of others. In this paper, U.S. data on school district policies are used to show that with respect to policy experiments, decision makers indeed are heavily affected by decision makers in reference groups. The results suggest that if a given district's neighbors' expected benefits from adopting a new policy increase, this substantially increases the original district's probability of adoption. The paper thus rejects the free-riding hypothesis and supports the view that in federal systems the diffusion of policy innovations is stimulated by horizontal interactions between jurisdictions. --

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    Paper provided by ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research in its series ZEW Discussion Papers with number 05-08.

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    Date of creation: 2005
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    Handle: RePEc:zbw:zewdip:2898

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    1. Timothy Besley & Anne Case, 1992. "Incumbent Behavior: Vote Seeking, Tax Setting and Yardstick Competition," NBER Working Papers 4041, National Bureau of Economic Research, Inc.
    2. Case, Anne, 1992. "Neighborhood influence and technological change," Regional Science and Urban Economics, Elsevier, vol. 22(3), pages 491-508, September.
    3. Brock,W.A. & Durlauf,S.N., 2000. "Discrete choice with social interactions," Working papers 7, Wisconsin Madison - Social Systems.
    4. Hautsch, Nikolaus & Klotz, Stefan, 2003. "Estimating the neighborhood influence on decision makers: theory and an application on the analysis of innovation decisions," Journal of Economic Behavior & Organization, Elsevier, vol. 52(1), pages 97-113, September.
    5. Scharfstein, David S & Stein, Jeremy C, 1990. "Herd Behavior and Investment," American Economic Review, American Economic Association, vol. 80(3), pages 465-79, June.
    6. Krasker, William S. & Kuh, Edwin & Welsch, Roy E., 1983. "Estimation for dirty data and flawed models," Handbook of Econometrics, in: Z. Griliches† & M. D. Intriligator (ed.), Handbook of Econometrics, edition 1, volume 1, chapter 11, pages 651-698 Elsevier.
    7. Katz, Michael L & Shapiro, Carl, 1986. "Technology Adoption in the Presence of Network Externalities," Journal of Political Economy, University of Chicago Press, vol. 94(4), pages 822-41, August.
    8. Strumpf, Koleman S, 2002. " Does Government Decentralization Increase Policy Innovation?," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 4(2), pages 207-41.
    9. Manski, Charles F, 1993. "Identification of Endogenous Social Effects: The Reflection Problem," Review of Economic Studies, Wiley Blackwell, vol. 60(3), pages 531-42, July.
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    Cited by:
    1. Rincke, Johannes, 2005. "Neighborhood Influence and Political Change: Evidence from US School Districts," ZEW Discussion Papers 05-16, ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
    2. Johannes Rincke, 2005. "Neighborhood Influence and Political Change: Evidence from US School Districts," Public Economics 0511011, EconWPA.

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