Mekansal Ekonometri ve Sosyal Bilimlerde Kullanım Alanları

Year 2016, , 401 - 436, 15.06.2016

Sevgi Tuzcu

https://doi.org/10.1501/SBFder_0000002398

Cited By: 3

Abstract

Sosyal bilimler literatüründe, “sosyal normların”, “komşuluk etkilerinin” veya “referans gruplarının”
bireylerin karar verme süreci üzerindeki etkisi uzun zamandır tartışılmaktadır. Ne var ki, geleneksel
yöntemlerdeki gözlemlerin birbirinden bağımsız olduğu varsayımı, söz konusu etkiyi yansıtamamakta ve
çalışmalarda hataların olmasına yol açmaktadır. Mekânsal ekonometriyi, gözlemler arasındaki komşuluk
ilişkilerini ve bu ilişkilerin neden olduğu sorunları dikkate alan yöntemler bütünü olarak tanımlamak
mümkündür. Burada, dikkat edilmesi gereken noktalardan biri, mekânın, bir başka deyişle gözlemler
arasındaki uzaklığın nasıl belirlendiğidir. Mekân, bölgesel çalışmalarda ele alındığı şekliyle coğrafik olarak
tanımlanabilirken, ekonomik uzaklık ya da kişisel uzaklık gibi soyut kavramlarla da ifade edilebilir. Bu
nedenle, çalışmanın gerekliliklerine uygun bir “mekân” tanımının yapılması büyük önem taşımaktadır. Bu
çalışma, öncelikle her biri farklı anlamlara gelen mekânsal regresyon çeşitlerini sınıflandırmakta ve bu
yönüyle, söz konusu yöntemler arasında seçim yapmak isteyen araştırmacılara yol göstermeyi
amaçlamaktadır. Çalışmanın bir diğer katkısı ise farklı uzaklık tanımlarına göre çalışmaları incelemesi ve
literatürden örnekler sunmasıdır. Bu örnekler, uzaklığın coğrafi olarak tanımlanıp tanımlanmamasına göre iki
grupta ele alınmıştır.

Keywords

Konum, Mekânsal Regresyon, Coğrafi Uzaklık, Ekonomik Uzaklık, Komşuluk Etkisi

Spatial Econometrics and Its Usage in Social Sciences

Abstract

Social science literature has long discussed the importance of so-called “social norms”, “neighborhood effects” or “peer influences” on the decision making process of individuals. However,
traditional econometric techniques usually rely on the assumption that observetations are independent from each other, and therefore cannot reflect these effects, and often leads to incorrect inferences. Spatial econometrics can be considered as the modeling techniques that account for the peculiarities caused by the space component. Here, one of the most critical points of spatial models is the definition of the neighborhood, in other words, the location of observations. The proximity among locations can be defined based on the geography as in the regional studies or economic distances. Even abstract concepts of proximity, such as the inter-personal distance, can be used in such techniques. Hence, the distance definition that is appropriate to the notion of the study plays an important role. This study attempts to classify the spatial regressions, in which each one of which has a different interpretation, and tries to guide the researches while selecting the correct modeling technique. Another major point of this study is that it presents examples of studies in the field according to their distance definitions.

Keywords

Location, Spatial Regression, Geographical Distance, Economical Distance, Neighborhood Effect

References

• Akerlof, George (1997), “Social Distance and Social Decisions”, Econometrica, 65 (5): 1005-1027.
• Anselin, Luc (1986), “Some Further Notes on Spatial Models and Regional Science”, Journal of Regional Science, 26 (4): 799-802.
• Anselin, Luc (1988), Spatial Econometrics: Methods and Models (First Edit, Dordrecht: Kluwer Academic Publishers).
• Anselin, Luc (2000), “Spatial Analyses of Crime”, Criminal Justice, 4 (2): 213-262.
• Anselin, Luc (2001), “Spatial Econometrics”, Baltagi, Badi H. (Der.), A Companion to Theoretical Econometrics (Oxford, UK: Blackwell Publishing): 310-330.
• Anselin, Luc (2003), “Spatial Externalities, Spatial Multipliers, and Spatial Econometrics”, International Regional Science Review, 26 (2): 153-166.
• Anselin, Luc (2006), “Spatial Econometrics”, Mills,Terence C. ve Kerry Patterson (Der.), Palgrave Handbook of Econometrics Vol. 1 Econometric Theory (New York: Palgrave Macmillan): 901-969.
• Anselin, Luc (2010), “Thirty Years of Spatial Econometrics”, Papers in Regional Science, 89 (1): 3- 26.
• Anselin, Luc ve Daniel A. Griffith (1988), “Do Spatial Effecfs Really Matter in Regression Analysis?”, Papers in Regional Science, 65 (1): 11-34.
• Anselin, Luc, Julie Le Gallo ve Hubert Jayet (2008), “Spatial Panel Econometrics”, Matyas, Laszlo ve Patrick Sevestre (Der.), The Econometrics of Panel Data Advanced Studies in Theoretical and Applied Econometrics (Verlag-Berlin-Heidelberg: Springer): 625-660.
• Arbia, Giuseppe (2006), Spatial Econometrics (New York: Springer Berlin Heidelberg).
• Beck, Nathaniel, Kristian Skrede Gleditsch ve Kyle Beardsley (2006), “Space is More than Geography: Using Spatial Econometrics in the Study of Political Economy”, International Studies Quarterly, 50 (1): 27-44.
• Conley, Timothy G. (1999), “GMM Estimation with Cross Sectional Dependence”, Journal of Econometrics, 92 (1): 1-45.
• Conley, Timothy G. ve Giorgio Topa (2002), “Socio-Economic Distance and Spatial Patterns in Unemployment”, Journal of Applied Econometrics, 17 (4): 303-327.
• Conley, Timothy G. ve Bill Dupor (2003), “A Spatial Analysis of Sectoral Complementarity”, Journal of Political Economy, 111 (2): 311-352.
• Corrado, Luisa ve Bernard Fingleton (2012), “Where is the Economics in Spatial Econometrics?”, Journal of Regional Science, 52 (2): 210-239.
• Dow, Malcolm M., Micheal L. Burton, Douglas R. White ve Karl P. Reitz (1984), “Galton‟s Problem as Network Autocorrelation”, American Ethnologist, 11 (4): 754-770.
• Elhorst, J. Paul (2010), “Applied Spatial Econometrics: Raising the Bar”, Spatial Economic Analysis, 5 (1): 9-28.
• Elhorst, J. Paul (2014), “Linear Spatial Dependence Models for Cross-Section Data”, Spatial Econometrics from Cross-Sectional Data to Spatial Panels (Berlin, Heidelberg: Springer): 5-37.
• Ertur, Cem ve Wilfried Koch (2007), “Growth, Technological Interdependence and Spatial Externalities: Theory and Evidence”, Journal of Applied Econometrics, 22 (6): 1033-62.
• Florax, Raymond J. G. M. ve Arno J. Van Der Vlist (2003), “Spatial Econometric Data Analysis: Moving Beyond Traditional Models”, International Regional Science Review, 26 (3): 223- 243.
• Getis, Arthur ve J. Keith Ord (1992), “The Analysis of Spatial Association by Use of Distance Statistics”, Geographical Analysis, 24 (3): 189-206.
• Gibbons, Stephen ve Henry G. Overman (2012), “Mostly Pointless Spatial Econometrics?”, Journal of Regional Science, 52 (2): 172-191.
• Griffith, Daniel A. ve Jean H. P. Paelinck (2011), “Non-Standard Spatial Statistics and Spatial Econometrics”, Advances in Geographic Information Science: v-xxix.
• Harris, Richard, John Moffat ve Victoria Kravtsova (2011), “In Search of „W‟ ”, Spatial Economic Analysis, 6 (3): 249-270.
• Holly, Sean, M. Hashem Pesaran ve Takashi Yamagata (2010), “A Spatio-Temporal Model of House Prices in the USA”, Journal of Econometrics, 158 (1): 160-173.
• LeSage, James P. (1997), “Regression Analysis of Spatial Data”, Journal of Regional Analysis and Policy, 27 (2): 83-94.
• LeSage, James P. ve R. Kelley Pace (2009), Introduction to Spatial Econometrics (Florida: Chapman and Hall).
• Lin, Tse-Min, Chin - En Wu ve Feng-Yu Lee (2006), “ „Neighborhood‟ Influence on the Formation of National Identity in Taiwan: Spatial Regression with Disjoint Neighborhoods”, Political Research Quarterly, 59 (1): 35-46.
• Manski, Charles F. (1993), “Identification of Endogenous Social Effects: The Reflection Problem”, The Review of Economic Studies, 60 (3): 531-542.
• Manski, Charles F. (2000), “Economic Analysis of Social Interactions”, Journal of Economic Perspectives, 14 (3): 115-136.
• Ord, Keith (1975), “Estimation Methods for Models of Spatial Interaction”, Journal of the American Statistical Association, 70 (349): 120-126.
• Pinkse, Joris ve Margaret Slade (2004), “Mergers, Brand Competition, and the Price of a Pint”, European Economic Review, 48 (3): 617-643.
• Pinkse, Joris, Margaret Slade ve Craig Brett (2002), “Spatial Price Competition: A Semiparametric Approach”, Econometrica, 70 (3): 1111-1153.
• Rey, Sergio J. ve Brett D. Montouri (1999), “US Regional Income Convergence: A Spatial Econometric Perspective”, Regional Studies, 33 (2): 143-156.
• Simmons, Beth A. ve Zachary Elkins (2004), “The Globalization of Liberalization: Policy Diffusion in the International Political Economy”, American Political Science Review, 98 (1): 171-189.
• Tirtiroglu, Dogan, Basak Tanyeri, Ercan Tirtiroglu ve Kenneth N. Daniels (2011), “Banking Geography and Cross-Fertilization in the Productivity Growth of US Commercial Banks”, Koç University-TÜSİAD Economic Research Forum Working Paper Series, No: 1108.
• Tobler, Waldo R. (1970), “A Computer Movie Simulating Urban Growth in the Detroit Region”, Economic Geography, 46 (Supplement: Proceedings): 234-240.
• Ward, Michael D. ve Kristian Skrede Gleditsch (2008), Spatial Regression Models (Los Angeles: Sage Publications). Yeşilyurt, M. Ensar (2008), “Eğitim Sektöründe Etkinlik ve Mekânsal İlişkiler”, İktisat, 23 (263): 53- 69.
• Yıldırım, Jülide, Nadir Öcal ve Süheyla Özyıldırım (2009), “Income Inequality and Economic Convergence in Turkey: A Spatial Effect Analysis”, International Regional Science Review, 32 (2): 221-254.
• Zeren, Fatma (2011), “Mekânsal Etkileşim Analizi”, Ekonometri ve İstatistik, (12): 18-39.
• Zeren, Fatma ve Burcu Kılınç Savrul (2012), “Türkiye‟de Şehirleşmeyi Etkileyen Faktörler: Mekânsal Ekonometri Analizi”, Journal of Yasar University, 28 (7): 4749-4765.