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Effects of MAUP on spatial econometric models

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  • Giuseppe Arbia
  • Francesca Petrarca

Abstract

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Suggested Citation

  • Giuseppe Arbia & Francesca Petrarca, 2011. "Effects of MAUP on spatial econometric models," Letters in Spatial and Resource Sciences, Springer, vol. 4(3), pages 173-185, October.
    • Handle: RePEc:spr:lsprsc:v:4:y:2011:i:3:p:173-185
    DOI: 10.1007/s12076-011-0065-9
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    References listed on IDEAS

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    1. Daniel A. Griffith & David W. S. Wong & Thomas Whitfield, 2003. "Exploring Relationships Between the Global and Regional Measures of Spatial Autocorrelation," Journal of Regional Science, Wiley Blackwell, vol. 43(4), pages 683-710, November.
    2. Kelejian, Harry H & Prucha, Ingmar R, 1998. "A Generalized Spatial Two-Stage Least Squares Procedure for Estimating a Spatial Autoregressive Model with Autoregressive Disturbances," The Journal of Real Estate Finance and Economics, Springer, vol. 17(1), pages 99-121, July.
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    Cited by:

    1. Haoying Wang & Guohui Wu, 2022. "Modeling discrete choices with large fine-scale spatial data: opportunities and challenges," Journal of Geographical Systems, Springer, vol. 24(3), pages 325-351, July.
    2. Nathaly M Rivera, 2019. "Spatial Aggregation Bias in Implicit Prices of Environmental Amenities," Economics Bulletin, AccessEcon, vol. 39(2), pages 1184-1194.
    3. Guilherme Resende & Alexandre Carvalho & Patrícia Sakowski & Túlio Cravo, 2016. "Evaluating multiple spatial dimensions of economic growth in Brazil using spatial panel data models," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 1-31, January.
    4. Margherita Gerolimetto & Stefano Magrini, 2016. "A spatial analysis of employment multipliers in the US," Letters in Spatial and Resource Sciences, Springer, vol. 9(3), pages 277-285, October.
    5. Norton, Daniel & Hynes, Stephen, 2018. "Estimating the Benefits of the Marine Strategy Framework Directive in Atlantic Member States: A Spatial Value Transfer Approach," Ecological Economics, Elsevier, vol. 151(C), pages 82-94.
    6. Mendiola, Lorea & González, Pilar & Cebollada, Àngel, 2014. "The link between urban development and the modal split in commuting: the case of Biscay," Journal of Transport Geography, Elsevier, vol. 37(C), pages 1-9.
    7. Guilherme Resende & Tulio Cravo, 2013. "What about regions in regional science? An exercise of convergence using different geographic scales of European Union," ERSA conference papers ersa13p772, European Regional Science Association.
    8. Giuseppe Espa & Danila Filipponi & Diego Giuliani & Davide Piacentino, 2014. "Decomposing regional business change at plant level in Italy: A novel spatial shift-share approach," Papers in Regional Science, Wiley Blackwell, vol. 93, pages 113-135, November.
    9. Mar Ortega-Reig & Carsten Schürmann & Adrian Ferrandis Martínez & Andrew Copus, 2023. "Measuring Access to Services of General Interest as a Diagnostic Tool to Identify Well-Being Disparities between Rural Areas in Europe," Land, MDPI, vol. 12(5), pages 1-30, May.
    10. Giuseppe Espa & Danila Filipponi & Diego Giuliani & Davide Piacentino, 2012. "Business change in Italian regions. A spatial shift-share approach to plant-level data," Department of Economics Working Papers 1205, Department of Economics, University of Trento, Italia.
    11. Mingyue Jiang & Yizhen Wu & Zhijian Chang & Kaifang Shi, 2021. "The Effects of Urban Forms on the PM 2.5 Concentration in China: A Hierarchical Multiscale Analysis," IJERPH, MDPI, vol. 18(7), pages 1-16, April.
    12. Danny Wende, 2019. "Spatial risk adjustment between health insurances: using GWR in risk adjustment models to conserve incentives for service optimisation and reduce MAUP," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 20(7), pages 1079-1091, September.
    13. Guilherme Mendes Resende & Tulio A. Cravo, 2014. "What about regions in regional science? A convergence exercise using different geographic scales of European Union," Economics Bulletin, AccessEcon, vol. 34(3), pages 1381-1395.
    14. Vicente Rios & Lisa Gianmoena, 2021. "On the link between temperature and regional COVID‐19 severity: Evidence from Italy," Regional Science Policy & Practice, Wiley Blackwell, vol. 13(S1), pages 109-137, November.
    15. Heike Delfmann & Sierdjan Koster & Philip McCann & Jouke Van Dijk, 2014. "Population Change and New Firm Formation in Urban and Rural Regions," Regional Studies, Taylor & Francis Journals, vol. 48(6), pages 1034-1050, June.
    16. Alberto Díaz Dapena & Fernando Rubiera Morollón & Dusan Paredes Araya, 2017. "Are there different local patterns of convergence concealed beneath the regional level? An analysis for US states and counties using a multilevel approach," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 58(3), pages 623-640, May.
    17. Juan C Duque & Henry Laniado & Adriano Polo, 2018. "S-maup: Statistical test to measure the sensitivity to the modifiable areal unit problem," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-25, November.
    18. Alberto Díaz Dapena & Esteban Fernández Vázquez & Fernando Rubiera Morollón, 2016. "The role of spatial scale in regional convergence: the effect of MAUP in the estimation of $$\beta $$ β -convergence equations," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(2), pages 473-489, March.
    19. Andre Fernandes Tomon Avelino & Kathy Baylis & Jordi Honey-Rosés, 2016. "Goldilocks and the Raster Grid: Selecting Scale when Evaluating Conservation Programs," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-24, December.

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    More about this item

    Keywords

    Aggregation effect; Loss in efficiency; MAUP; SARAR models; Scale effect; Spatial econometric; C21; C31; C5;
    All these keywords.

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling

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