Optimizing Distance-Based Methods for Big Data Analysis
AbstractDistance-based methods for measuring spatial concentration such as the Duranton-Overman index undergo an increasing popularity in the spatial econometrics community. However, a limiting factor for their usage is their computational complexity since both their memory requirements and running-time are in O(n2). In this paper, we present an algorithm with constant memory requirements and an improved running time, enabling the Duranton-Overman index and related distance-based methods to run big data analysis. Furthermore, we discuss the index by Scholl and Brenner (2012) whose mathematical concept allows an even faster computation for large datasets than the improved algorithm does.
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Bibliographic InfoPaper provided by Philipps University Marburg, Department of Geography in its series Working Papers on Innovation and Space with number 2013-09.
Length: 15 pages
Date of creation: 06 Oct 2013
Date of revision:
Spatial concentration; Duranton-Overman index; big-data analysis; MAUP; distance-based measures;
Find related papers by JEL classification:
- C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General
- M13 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - New Firms; Startups
- R12 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General Regional Economics - - - Size and Spatial Distributions of Regional Economic Activity; Interregional Trade (economic geography)
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-06-24 (All new papers)
- NEP-CMP-2013-06-24 (Computational Economics)
- NEP-ECM-2013-06-24 (Econometrics)
- NEP-GEO-2013-06-24 (Economic Geography)
- NEP-URE-2013-06-24 (Urban & Real Estate Economics)
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- Glenn Ellison & Edward L. Glaeser & William Kerr, 2007.
"What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns,"
NBER Working Papers
13068, National Bureau of Economic Research, Inc.
- Glenn Ellison & Edward L. Glaeser & William R. Kerr, 2010. "What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns," American Economic Review, American Economic Association, vol. 100(3), pages 1195-1213, June.
- Glenn Ellison & Edward L. Glaeser & William R. Kerr, 2007. "What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns," Harvard Business School Working Papers 07-064, Harvard Business School.
- William Kerr & Edward Glaeser & Glenn Ellison, 2007. "What Causes Industry Agglomeration? Evidence from Coagglomeration Patterns," Working Papers 07-13, Center for Economic Studies, U.S. Census Bureau.
- Stefania Vitali & Mauro Napoletano & Giorgio Fagiolo, 2013.
"Spatial Localization in Manufacturing: A Cross-Country Analysis,"
Taylor & Francis Journals, vol. 47(9), pages 1534-1554, October.
- Stefania Vitali & Mauro Napoletano & Giorgio Fagiolo, 2009. "Spatial Localization in Manufacturing: A Cross-Country Analysis," Documents de Travail de l'OFCE 2009-07, Observatoire Francais des Conjonctures Economiques (OFCE).
- Stefania Vitali & Mauro Napoletano & Giorgio Fagiolo, 2009. "Spatial Localization in Manufacturing: A Cross-Country Analysis," LEM Papers Series 2009/04, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
- Stefania Vitali & Mauro Napoletano & Giorgio Fagiolo, 2009. "Spatial Localization in Manufacturing: A Cross-Country Analysis," Papers in Evolutionary Economic Geography (PEEG) 0906, Utrecht University, Section of Economic Geography, revised Jun 2009.
- Mauro Napoletano & Giorgio Fagiolo, 2009. "Spatial Localization in Manufacturing: A Cross-Country Analysis," Sciences Po publications 2009/04, Sciences Po.
- Thomas Klier & Daniel P. McMillen, 2008.
"Evolving Agglomeration In The U.S. Auto Supplier Industry,"
Journal of Regional Science,
Wiley Blackwell, vol. 48(1), pages 245-267.
- Thomas H. Klier & Daniel McMillen, 2006. "Evolving agglomeration in the U.S. auto supplier industry," Working Paper Series WP-06-20, Federal Reserve Bank of Chicago.
- Reinhold Kosfeld & Hans-Friedrich Eckey & Jørgen Lauridsen, 2009.
"Spatial Point Pattern Analysis and Industry Concentration,"
MAGKS Papers on Economics
200916, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
- Reinhold Kosfeld & Hans-Friedrich Eckey & Jørgen Lauridsen, 2011. "Spatial point pattern analysis and industry concentration," The Annals of Regional Science, Springer, vol. 47(2), pages 311-328, October.
- Eric Marcon & Florence Puech, 2010. "Measures of the geographic concentration of industries: improving distance-based methods," Journal of Economic Geography, Oxford University Press, vol. 10(5), pages 745-762, September.
- Tobias Scholl & Thomas Brenner, 2013. "Detecting Spatial Clustering Using a Firm-Level Index," Working Papers on Innovation and Space 2012-02, Philipps University Marburg, Department of Geography.
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