DEĞİŞTİRİLEBİLİR ALANSAL BİRİM PROBLEMİ VE EKONOMİK FAALİYETLERİN MEKÂNSAL YOĞUNLAŞMASI ÜZERİNE BİR DEĞERLENDİRME

Year 2023, Issue: 38, 130 - 145, 30.11.2023

Emrah Özel , Hakan Demirgil

https://doi.org/10.20875/makusobed.1378520

Abstract

Ekonomik birimlerin mekânsal yoğunlaşması, firmaların birbirine yakın konumlanmasıyla elde edilen faydalar, ölçek ekonomilerinden, teknik işgücü havuzundan, düşük nakliye ve iletişim maliyetlerinden ve teknoloji transferlerinden kaynaklanabilir. Ancak, bu yoğunlaşmanın etkili bir şekilde değerlendirilebilmesi ve bölgesel politikaların ekonomik büyüme ve kalkınmaya yönelik etkili bir şekilde geliştirilebilmesi için mekânsal yoğunlaşma ölçümlerinin tutarlı olması gerekmektedir. Bu noktada, mekânsal analizde karşılaşılan bir problem olan değiştirilebilir alansal birim problemine (MAUP) dikkat çekilmektedir. MAUP, toplu verilerin ve idari sınırların kullanılmasından kaynaklanan ve mekânsal analiz sonuçlarını etkileyebilen bir durumu ifade etmektedir. Bu çalışma, literatürde MAUP olarak bilinen bu sorunu ana hatlarıyla ortaya koymakta, önerilen çözüm yollarına vurgu yapmakta ve ekonomik faaliyetlerin yoğunlaşma ölçümlerinde MAUP etkilerini değerlendirmektedir. Genel bir değerlendirme yapıldığında, MAUP etkilerini azaltmak için sınırlandırılmamış bir mekânsal yapı ve bireyselleştirilmiş mekânsal verilerin kullanımının önemli olduğu sonucuna varılabilir. Ayrıca, ekonomik faaliyetlerin mekânsal yoğunlaşması ile ilgili çalışmalarda, kümelenmeye dayalı göstergeleri kullanan yaklaşımların MAUP'u dikkate almadığı, mesafeye dayalı yaklaşımların ise çeşitli açılardan MAUP etkilerini minimize ettiği belirtilmektedir.

Keywords

Değiştirilebilir Alansal Birim Problemi, Yığılma Ekonomileri, Ölçek Etkisi, Bölgeleme Etkisi, Mekansal Yoğunlaşma

AN ASSESSMENT OF THE MODIFIABLE AREAL UNIT PROBLEM AND SPATIAL CONCENTRATION OF ECONOMIC ACTIVITIES

Abstract

The benefits derived from the spatial concentration of economic units, resulting from the close positioning of firms, may stem from economies of scale, a technical labor pool, low transportation and communication costs, and technology transfers. However, for this concentration to be effectively evaluated and regional policies to be developed efficiently for economic growth and development, spatial concentration measurements need to be consistent. At this point, attention is drawn to the modifiable areal unit problem (MAUP), a problem encountered in spatial analysis arising from the use of aggregated data and administrative boundaries, which impacts spatial analysis results. This study outlines the MAUP issue in the literature, emphasizes proposed solutions, and evaluates the impact of MAUP on measurements of the spatial concentration of economic activities. In a general assessment, it can be concluded that an unrestricted spatial structure and the use of personalized spatial data are crucial for mitigating MAUP effects. Additionally, in studies related to the spatial concentration of economic activities, approaches utilizing cluster-based indicators tend to neglect MAUP, while distance-based approaches are noted to minimize MAUP effects from various perspectives.

Keywords

Modifiable Areal Unit Problem, Agglomeration Economies, Scale Effect, Zoning Effect, Spatial Concentration

References

• Aiginger, K. ve Rossi-Hansberg, E. (2006). Specialization and concentration: A note on theory and evidence. Empirica, 33, 255–266. https://doi.org/10.1007/s10663-006-9023-y
• Alker, R. J. (1969). A typology of ecological fallacies. M. Doğan ve S. Rokkan (Eds.) içinde, Quantitative ecological analysis in the social sciences (1. baskı, ss. 69-86). MIT Press.
• Amrhein, C. G. ve Reynolds, H. D. (1996). Using spatial statistics to assess aggregation effects. Geographical Systems, 3(2/3), 143-158.
• Arbia, G. (1989). Spatial Data Configuration in Statistical Analysis of Regional Economic and Related Problems. Kluwer Academic.
• Arbia, G. (1993). Aggregation over time, space and individuals in economic modelling: a generating mechanism approach. G. Gandolfo (Eds.) içinde, Continuous-time econometrics. International studies in economic modelling (1. baskı, ss. 117-132). Springer. https://doi.org/10.1007/978-94-011-1542-1_6
• Arbia, G. (2001). Modelling the geography of economic activities on a continuous space. Papers in Regional Science, 80, 411-424. https://doi.org/10.1007/PL00013646
• Arbia, G., Espa, G., Giuliani, D. ve Dickson, M. M. (2014). Spatio-temporal clustering in the pharmaceutical and medical device manufacturing industry: A geographical micro-level analysis. Regional Science and Urban Economics, 49, 298-304. https://doi.org/10.1016/j.regsciurbeco.2014.10.001
• Arbia, G., Espa, G., Giuliani, D. ve Mazzitelli, A. (2010). Detecting the existence of space–time clustering of firms. Regional Science and Urban Economics, 40(5), 311-323. https://doi.org/10.1016/j.regsciurbeco.2009.10.004
• Arbia, G., Espa, G. ve Quah, D. (2008). A class of spatial econometric methods in the empirical analysis of clusters of firms in the space. Empirical Economics, 34, 81-103. https://doi.org/10.1007/s00181-007-0154-1
• Blalock, H. M. (1964). Causal Inferences in Nonexperimental Research (1. baskı). University of North Carolina Press.
• Butkiewicz, T., Meentemeyer, R. K., Shoemaker, D. A., Chang, R., Wartell, Z. ve Ribarsky, W. (2010). G. Melançon, T. Munzner ve D. Weiskopf (Eds.) içinde. Alleviating the modifiable areal unit problem within probe‐based geospatial analyses (29/3, ss. 923-932). Blackwell. https://doi.org/10.1111/j.1467-8659.2009.01707.x
• Cainelli, G., Ganau, R. ve Jiang, Y. (2020). Detecting space–time agglomeration processes over the Great Recession using firm-level micro-geographic data. Journal of Geographical Systems, 22, 419-445. https://doi.org/10.1007/s10109-020-00332-4
• Ceapraz, I. L. (2008). The concepts of specialisation and spatial concentration and the process of economic integration: theoretical relevance and statistical measures. The case of Romania’s regions. Romanian Journal of Regional Science, 2(1), 68-93.
• Clark, W. A. V. ve Avery, K. L. (1976). The effects of data aggregation in statistical analysis. Geographical Analysis, 8(4), 428-438. https://doi.org/10.1111/j.1538-4632.1976.tb00549.x
• Cressie, N. A. C. (1996). Change of support and the modifiable areal unit problem. Geographical Systems, 3(2-3), 159-180.
• Dark, S. J. ve Bram, D. (2007). The modifiable areal unit problem (MAUP) in physical geography. Progress in Physical Geography, 31(5), 471-479. https://doi.org/10.1177/0309133307083
• Dudley, G. (1991). Scale, aggregation, and the modifiable areal unit problem. The Operational Geographer, 9(3), 28-32.
• Duranton, G. ve Overman, H. G. (2005). Testing for localization using micro-geographic data. The Review of Economic Studies, 72(4), 1077-1106. https://doi.org/10.1111/0034-6527.00362
• Dusek, T. (2005 August 23-27). The modifiable areal unit problem in regional economics. [Conference presentation abstract]. 45th Congress of the European Regional Science Association, Amsterdam, Holland. https://core.ac.uk/download/pdf/7035964.pdf
• Espon. (2006). The Modifiable Areas Unit Problem Final Report. https://www.espon.eu/sites/default/files/attachments/espon343_maup_final_version2_nov_2006.pdf
• Flowerdew, R. (2011). How serious is the Modifiable Areal Unit Problem for analysis of English census data?. Population trends, 145, 102-114. https://doi: 10.1057/pt.2011.20. PMID: 21987016.
• Fotheringham, A. S. (1989). Scale-independent spatial analysis. M. Goodchild ve S. Gopal (Eds.) içinde, The accuracy of spatial databases (1. baskı, ss. 221-228). Taylor & Francis.
• Fotheringham, A. S. ve Sachdeva, M. (2022). Scale and local modeling: new perspectives on the modifiable areal unit problem and Simpson’s paradox. Journal of Geographical Systems, 24(3), 475-499. https://doi.org/10.1007/s10109-021-00371-5
• Fotheringham, A. S. ve Wong, D. W. S. (1991). The modifiable areal unit problem in multivariate statistical analysis. Environment and Planning A, 23(7), 1025–1044. https://doi.org/10.1068/a231025
• Gehlke, C. E. ve Biehl, K. (1934). Certain effects of grouping upon the size of the correlation coefficient in census tract material. Journal of the American Statistical Association, 29(185A), 169-170. https://doi.org/10.1080/01621459.1934.10506247
• Goodchild, M. F. (1979). The aggregation problem in location‐allocation. Geographical Analysis, 11(3), 240-255. https://doi.org/10.1111/j.1538-4632.1979.tb00692.x
• Gotway, C. C. A. ve Young L. J. (2004). A spatial view of the ecological inference problem. G. King, O. Rosen ve M. Tanner (Eds.) içinde, Ecological inference: New methodological strategies, (1. baskı, ss. 233-234). Oxford.
• Green, M. (1993). Ecological fallacies and the modifiable areal unit problem. Lancaster University Research Report (Vol. 27).
• Hallet, M. (2002). Regional specialisation and concentration in the EU. J.R. Cuadrado-Roura ve M. Parellada (Eds.) içinde, Regional convergence in the European Union. (1. baskı, ss. 53-76). Springer.
• Hannan, M. T. (1972). Approaches to the aggregation problem Laboratory for Social Research. https://stacks.stanford.edu/file/druid:nj069fk8338/TR46%20Approaches%20to%20the%20Aggregation%20Problem.pdf
• Hennerdal, P. ve Nielsen, M. M. (2017). A multiscalar approach for identifying clusters and segregation patterns that avoids the modifiable areal unit problem. Annals of the American Association of Geographers, 107(3), 555-574. https://doi.org/ 10.1080/24694452.2016.1261685
• Holt, D. T., Steel, D. G. ve Tranmer, M. (1996a). Area homogeneity and the modifiable areal unit problem. Geographical Systems, 3(2/3), 181-200.
• Holt, D. T., Steel, D. G., Tranmer, M. ve Wrigley, N. (1996b). Aggregation and ecological effects in geographically based data. Geographical Analysis, 28(3), 244-261. https://doi.org/10.1111/j.1538-4632.1996.tb00933.x
• Isaaks, E. H. ve Srivastava, R. M. (1989). Applied Geostatistics (1. baskı). Oxford University Press.
• Kopczewska, K., Churski, P., Ochojski, A. ve Polko, A. (2017). Measuring regional specialization: A new approach. Palgrave Macmillan. https://doi.org/10.1007/978-3-319-51505-2
• Kopczewska, K., Churski, P., Ochojski, A. ve Polko, A. (2019). SPAG: Index of spatial agglomeration. Papers in Regional Science, 98(6), 2391-2424. https://doi.org/10.1111/pirs.12470
• Larsen, J. L. (2000). The modifiable areal unit problem: A problem or a source of spatial information?. (Yayın nu. 9962420)[Doktora tezi, Ohio State Üniversitesi]. https://www.proquest.com/docview/304635509?
• Li, L., Ban, H., Wechsler, S.P. ve Xu, B., (2018). Spatial data uncertainty. B. Huang (Eds.) içinde, Comprehensive geographic information systems. (5. baskı, ss. 313–340). Elsevier. https://doi.org/10.1016/ b978-0-12-409548-9.09610-x
• Lloyd, C. D. (2014). Exploring spatial scale in geography (1. baskı). John Wiley ve Sons. https://doi.org/10.1002/9781118526729
• Longley, P. A., Goodchild, M. F., Maguire, D. J. ve Rhind, D. W. (2011). Geographic information systems and science (3. baskı). John Wiley & Sons.
• Manley, D. (2014). Scale, aggregation, and the modifiable areal unit problem. M. Fischer ve P. Nijkamp (Eds.) içinde, Handbook of regional science. Springer. https://doi.org/10.1007/978-3-642-23430-9_69
• Maoh, H. ve Kanaroglou, P. (2007). Geographic clustering of firms and urban form: A multivariate analysis. Journal of Geographical Systems, 9, 29-52. https://doi.org/10.1007/s10109-006-0029-6
• Marcon, E. ve Puech, F. (2003). Evaluating the geo-graphic concentration of industries using distance-based methods. Journal of Economic Geography, 3(4), 409–428.
• Marcon, E. ve Puech, F. (2009). Measures of the geographic concentration of industries: Improving distance-based methods. Journal of Economic Geography, 10(5), 745–762. https://doi.org/10.1093/jeg/lbp056
• Marshall, A. (1920). Principles of economics. Macmillan.
• Moellering, H. ve Tobler, W. (1972), Geographical variances. Geographical Analysis, 4, 34-50. https://doi.org/10.1111/j.1538-4632.1972.tb00455.x
• Mori, T. ve Smith, T. (2014). A probabilistic modeling approach to the detection of industrial agglomeration. Journal of Economic Geography, 14(3), 547–588. https://doi.org/10.1093/jeg/lbs062
• Openshaw, S. ve Taylor, P. J., (1979). A million or so correlation coefficients: Three experiments on the modifiable areal unit problem. N. Wrigley (Eds.) içinde, Statistical applications in the spatial sciences, (1. baskı, ss. 127–144). Pion.
• Openshaw, S. (1983). The modifiable areal unit problem. (Concepts and Techniques in Modern Geography Vol. 38). Geo Books. https://www.uio.no/studier/emner/sv/iss/SGO9010/openshaw1983.pdf
• Openshaw, S. (1984). Ecological fallacies and the analysis of areal census data. Environment and Planning A: Economy and Space, 16(1), 17-31. https://doi.org/10.1068/a160017
• Pablo, M. F. ve Arauzo, C. J. M. (2020). Spatial distribution of economic activities: A network approach. Journal of Economic Interaction and Coordination, 15, 441-470. https://doi.org/10.1007/s11403-018-0225-8
• Pawitan, G. ve Steel, D. G. (2009). Exploring the MAUP from a spatial perspective, Centre for Statistical and Survey Methodology, University of Wollongong Working Paper. https://ro.uow.edu.au/cgi/viewcontent.cgi?article=1039&context=cssmwp
• Perle, E. D. (1977). Scale changes and impacts on factorial ecology structures. Environment and Planning A, 9(5), 549-558. https://doi.org/10.1068/a090549
• Robinson, A. H. (1956). The necessity of weighting values in correlation analysis of areal data. Annals of the Association of American Geographers, 46(2), 233-236.
• Robinson, W. S. (1950). Ecological correlations and the behavior of individuals. American Sociological Review, 15(3), 351–357. https://doi.org/10.2307/2087176
• Quah, D. ve Simpson, H. (2003). Spatial cluster empirics. London School of Economics Working Paper Series. https://eprints.lse.ac.uk/2041/
• Sawicki, D. S. (1973). Studies of aggregated areal data: Problems of statistical inference. Land Economics, 49(1), 109–114. https://doi.org/10.2307/3145339
• Scholl, T. ve Brenner, T. (2011). Testing for clustering of industries-evidence from micro geographic data. https://www.econstor.eu/bitstream/10419/111871/1/wp2011-02.pdf
• Sémécurbe, F., Tannier, C. ve Roux, S. G. (2016). Spatial distribution of human population in France: Exploring the modifiable areal unit problem using multifractal analysis. Geographical Analysis, 48(3), 292-313. https://doi.org/10.1111/gean.12099
• Steel, D. G. ve Holt, D. T. (1996). Analysing and adjusting aggregation effects: The ecological fallacy revisited. International Statistical Review/Revue Internationale de Statistique, 64(1), 39-60. https://doi.org/10.2307/1403423
• Taylor, P. J. (1977). Quantitative methods in geography. Houghton Mifflin.
• Tian, Z. (2013). Measuring agglomeration using the standardized location quotient with a bootstrap method. Journal of Regional Analysis and Policy, 43(2), 186-197. https://doi.org/10.22004/ag.econ.243958
• Tobler, W. (1989). Frame independent spatial analysis. M. Goodchild ve S. Gopal (Eds.) içinde, Accuracy of spatial databases (ss. 115−122). CRC Press.
• Wong, D. W. S. (1996). Aggregation effects in geo-referenced data. S. L. Arlinghaus (Eds.) içinde, Practical handbook of spatial statistics (ss. 83-106). CRC Press.
• Wong, D. W. S. (2004). The modifiable areal unit problem (MAUP). D.G. Janelle, B. Warf ve K. Hansen (Eds.) içinde, WorldMinds: Geographical perspectives on 100 problems (ss. 571–575). Springer.
• Wong, D. W. S. (2009). Modifiable areal unit problem. R. Kitchin ve N. Thrift (Eds.) içinde, International encyclopedia of human geography (ss. 169–174). Elsevier.
• Xu, P. P., Huang, H. L., Cheng, Y. M. ve Ma, M. (2014). Addressing the modifiable areal unit problem in traffic safety: Definition, potential solutions, and future research. J. Ma, Y. Yin, H. Huang ve D. Pan (Eds.) içinde, CICTP 2014: Safe, smart, and sustainable multimodal transportation systems (ss. 2279-2290). ASCE Book Series.
• Ye, X. (2020). The impacts of the modifiable areal unit problem (MAUP) on linear regression. (Yayın nu. 27735342)[Doktora tezi, New York State Üniversitesi]. https://www.proquest.com/docview/2384582032?
• Young, L. J. ve Gotway, C. A. (2007). Linking spatial data from different sources: the effects of change of support. Stochastic Environmental Research and Risk Assessment, 21, 589-600. https://doi.org/10.1007/s00477-007-0136-z
• Yule, G. U. ve Kendall, M. G. (1950). An introduction to the theory of statistics (14. baskı). Charles Griffin & Co. Ltd.