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Is Spatial Bootstrapping a Panacea for Valid Inference?

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    Abstract

    Bootstrapping methods have so far been rarely used to evaluate spatial data sets. Based on an extensive Monte Carlo study we find that also for spatial, cross-sectional data, the wild bootstrap test proposed by Davidson and Flachaire (2008) based on restricted residuals clearly outperforms asymptotic as well as competing bootstrap tests, like the pairs bootstrap.

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    File URL: http://www.wiwi.uni-augsburg.de/vwl/institut/paper/322.pdf
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    Bibliographic Info

    Paper provided by Universitaet Augsburg, Institute for Economics in its series Discussion Paper Series with number 322.

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    Length: pages
    Date of creation: May 2013
    Date of revision:
    Handle: RePEc:aug:augsbe:0322

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    Web page: http://www.wiwi.uni-augsburg.de/vwl/institut
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    Related research

    Keywords: Spatial econometrics; Paired bootstrap; Wild bootstrap; Parameter inference;

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    1. David Brownstone & Robert Valletta, 2001. "The Bootstrap and Multiple Imputations: Harnessing Increased Computing Power for Improved Statistical Tests," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 129-141, Fall.
    2. Daniel C. Monchuk & Dermot J. Hayes & John Miranowski & Dayton M. Lambert, 2010. "Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States," Center for Agricultural and Rural Development (CARD) Publications 10-wp507, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    3. Russell Davidson & Emmanuel Flachaire, 2000. "The Wild Bootstrap, Tamed at Last," Econometric Society World Congress 2000 Contributed Papers 1413, Econometric Society.
    4. James G. MacKinnon, 2002. "Bootstrap inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 35(4), pages 615-645, November.
    5. van Giersbergen, Noud P. A. & Kiviet, Jan F., 2002. "How to implement the bootstrap in static or stable dynamic regression models: test statistic versus confidence region approach," Journal of Econometrics, Elsevier, vol. 108(1), pages 133-156, May.
    6. Russell Davidson & James G. MacKinnon, 1994. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," Working Papers 903, Queen's University, Department of Economics.
    7. Chesher, Andrew & Jewitt, Ian, 1987. "The Bias of a Heteroskedasticity Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 55(5), pages 1217-22, September.
    8. repec:fth:louvco:9924 is not listed on IDEAS
    9. Russell Davidson & James G. MacKinnon, 2004. "The Power of Bootstrap and Asymptotic Tests," Working Papers 1035, Queen's University, Department of Economics.
    10. White, Halbert, 1980. "A Heteroskedasticity-Consistent Covariance Matrix Estimator and a Direct Test for Heteroskedasticity," Econometrica, Econometric Society, vol. 48(4), pages 817-38, May.
    11. Emmanuel Flachaire, 1999. "A better way to bootstrap pairs," Post-Print halshs-00175892, HAL.
    12. Kuan-Pin Lin & Zhi-He Long & Bianling Ou, 2011. "The Size and Power of Bootstrap Tests for Spatial Dependence in a Linear Regression Model," Computational Economics, Society for Computational Economics, vol. 38(2), pages 153-171, August.
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