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An Examination of the Dynamic Behavior of Local Governments Using GMM Bootstrapping Methods

Author

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  • Dahlberg, Matz

    () (Department of Economics)

  • Johansson, Eva

    () (Department of Economics)

Abstract

Recent Monte Carlo evidence has shown that tests based on asymptotic critical values tend to reject a true null too often, while tests based on bootstrap critical values have empirical sizes that are very close to the nominal ones. This casts doubt on the growing number of studies indicating considerable dynamics in local government behavior since they all rely on asymptotic critical values. Using GMM bootstrapping techniques, this paper re-investigates the dynamic interrelationship between local government revenues and expenditures. Further, the results are compared with those obtained using asymptotical critical values. The panel covers 265 Swedish municipalities over the period 1979-1987. A lag of one year is found in the expenditures equation, while no dynamics is found in the own-source revenues and grants equations. These results, while contrasting sharply with those obtained when asymptotic critical values are used, are well in line with the theoretical explanations given in the literature for dynamic behavior in the local public sector.

Suggested Citation

  • Dahlberg, Matz & Johansson, Eva, 1997. "An Examination of the Dynamic Behavior of Local Governments Using GMM Bootstrapping Methods," Working Paper Series 1997:11, Uppsala University, Department of Economics.
  • Handle: RePEc:hhs:uunewp:1997_011
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    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Holtz-Eakin, Douglas & Newey, Whitney & Rosen, Harvey S, 1989. "The Revenues-Expenditures Nexus: Evidence from Local Government Data," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 30(2), pages 415-429, May.
    3. Barro, Robert J, 1979. "On the Determination of the Public Debt," Journal of Political Economy, University of Chicago Press, vol. 87(5), pages 940-971, October.
    4. Davidson, Russell & MacKinnon, James G., 1999. "The Size Distortion Of Bootstrap Tests," Econometric Theory, Cambridge University Press, pages 361-376.
    5. Rubinfeld, Daniel L., 1987. "The economics of the local public sector," Handbook of Public Economics,in: A. J. Auerbach & M. Feldstein (ed.), Handbook of Public Economics, edition 1, volume 2, chapter 11, pages 571-645 Elsevier.
    6. Bergström, Pål & Dahlberg, Matz & Johansson, Eva, 1997. "GMM Bootstrapping and Testing in Dynamic Panels," Working Paper Series 1997:10, Uppsala University, Department of Economics.
    7. Dahlberg, Matz & Lindström , Tomas, 1996. "Are Local Governments Governed by Forward Looking Decision Makers?," Working Paper Series 1996:20, Uppsala University, Department of Economics.
    8. Joel L. Horowitz, 1996. "Bootstrap Methods in Econometrics: Theory and Numerical Performance," Econometrics 9602009, EconWPA, revised 05 Mar 1996.
    9. Hall, Peter & Horowitz, Joel L, 1996. "Bootstrap Critical Values for Tests Based on Generalized-Method-of-Moments Estimators," Econometrica, Econometric Society, vol. 64(4), pages 891-916, July.
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    11. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    12. Matz Dahlberg & Eva Johansson, 1998. "The revenues-expenditures nexus: panel data evidence from Swedish municipalities," Applied Economics, Taylor & Francis Journals, vol. 30(10), pages 1379-1386.
    13. Manuel Arellano & Stephen Bond, 1991. "Some Tests of Specification for Panel Data: Monte Carlo Evidence and an Application to Employment Equations," Review of Economic Studies, Oxford University Press, vol. 58(2), pages 277-297.
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    More about this item

    Keywords

    GMM bootstrapping; local governments; revenues-expenditures nexus;

    JEL classification:

    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • H72 - Public Economics - - State and Local Government; Intergovernmental Relations - - - State and Local Budget and Expenditures

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