Is Spatial Bootstrapping a Panacea for Valid Inference?
AbstractBootstrapping 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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Bibliographic InfoPaper provided by Universitaet Augsburg, Institute for Economics in its series Discussion Paper Series with number 322.
Date of creation: May 2013
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Spatial econometrics; Paired bootstrap; Wild bootstrap; Parameter inference;
Find related papers by JEL classification:
- C18 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Methodolical Issues: General
- C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
- R11 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Regional Economic Activity: Growth, Development, Environmental Issues, and Changes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-06-04 (All new papers)
- NEP-ECM-2013-06-04 (Econometrics)
- NEP-URE-2013-06-04 (Urban & Real Estate Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- 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.
- 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.
- Daniel C. Monchuk & Dermot J. Hayes & John A. Miranowski & Dayton M. Lambert, 2011. "Inference Based On Alternative Bootstrapping Methods In Spatial Models With An Application To County Income Growth In The United States," Journal of Regional Science, Wiley Blackwell, vol. 51(5), pages 880-896, December.
- Daniel C. Monchuk & Dermot J. Hayes & John Miranowski, 2008. "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 08-wp471, Center for Agricultural and Rural Development (CARD) at Iowa State University.
- Monchuk, Daniel C. & Hayes, Dermot J. & Miranowski, John & Lambert, Dayton, 2013. "Inference Based on Alternative Bootstrapping Methods in Spatial Models with an Application to County Income Growth in the United States," Staff General Research Papers 36121, Iowa State University, Department of Economics.
- Russell Davidson & Emmanuel Flachaire, 2000.
"The Wild Bootstrap, Tamed at Last,"
Econometric Society World Congress 2000 Contributed Papers
1413, Econometric Society.
- Russell Davidson & Emmanuel Flachaire, 2001. "The wild bootstrap, tamed at last," LSE Research Online Documents on Economics 6560, London School of Economics and Political Science, LSE Library.
- Russell Davidson & Emmanuel Flachaire, 2001. "The Wild Bootstrap, Tamed at Last," Working Papers 1000, Queen's University, Department of Economics.
- Davidson, R. & Flachaire, E., 1999. "The Wild Bootstrap, Tamed at Last," G.R.E.Q.A.M. 99a32, Universite Aix-Marseille III.
- Emmanuel Flachaire, 2001. "The Wild Bootstrap, Tamed at Last," STICERD - Distributional Analysis Research Programme Papers 58, Suntory and Toyota International Centres for Economics and Related Disciplines, LSE.
- James G. MacKinnon, 2002. "Bootstrap inference in econometrics," Canadian Journal of Economics, Canadian Economics Association, vol. 35(4), pages 615-645, November.
- 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.
- Russell Davidson & James G. MacKinnon, 1994.
"Graphical Methods for Investigating the Size and Power of Hypothesis Tests,"
903, Queen's University, Department of Economics.
- Davidson, Russell & MacKinnon, James G, 1998. "Graphical Methods for Investigating the Size and Power of Hypothesis Tests," The Manchester School of Economic & Social Studies, University of Manchester, vol. 66(1), pages 1-26, January.
- Chesher, Andrew & Jewitt, Ian, 1987. "The Bias of a Heteroskedasticity Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 55(5), pages 1217-22, September.
- repec:fth:louvco:9924 is not listed on IDEAS
- Russell Davidson & James G. MacKinnon, 2004.
"The Power of Bootstrap and Asymptotic Tests,"
1035, Queen's University, Department of Economics.
- 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.
- Emmanuel Flachaire, 1999.
"A better way to bootstrap pairs,"
- 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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