BibTex RIS Kaynak Göster

Topological Analysis Among Carbon dioxide Emission, Economic Growth and Electricity Consumption by Using Hierarchical Structure Methods

Yıl 2014, Cilt: 3 Sayı: 2, 1 - 14, 19.01.2015
https://doi.org/10.17100/nevbiltek.210933

Öz

In this study, within the scope of sociophysics, the topological relationships among the CO2 emissions, per capita of Gross Domestic Product (GDP) and electricity consumptions are investigated by using the concept of hierarchical structure methods (minimal spanning tree (MST) and hierarchical tree (HT)) for 25 European countries over the period of 1970-2010. The MST and HT are useful tools for understanding and detecting the global structure, taxonomy and hierarchy in data. From the MSTs and HTs different clusters of countries are identified according to their proximity, economic/social/geological ties, and the relation among countries are determined. Hence, the clustered structure of the countries and the key country/countries in each cluster are detected

Kaynakça

  • Callen E., Shapiro, D. A, Theory of Social Imitation, Phys. Today, 23-28, 1974.
  • Weidlich W., The statistical decription of polarization phenomena in society, Br. J. Math. Statist. Physcol, 24 (1), 251-266, 1971.
  • Vallacher R. R., Nowak A., Zochowski M., “Dynamics of social coordination: The synchronization of internal states in close relationships”, In P. Hauf & F. Forsterling (Eds.), Making minds: The shaping of human minds through social context (pp. 31-46). Amsterdam: John Benjamins Publishing Company. UW, 2007.
  • Kulakowski K., Around the Gap between Sociophysics and Sociology (abs), Prepared for the book 'Lectures on Socio- and Econophysics' after the Summer School on SocioEcono-Physics 2007 in Windberg, 2007.
  • Galam S, Sociophysics: do Humans Behave Like Atoms?, CREA, Paris, November 14-16, 2011.
  • Galam S. Sociophysics: A Physicist’s Modeling of Psycho-political Phenomena, Claiming the Paternity of Sociophysics, pgs. 61-63. Springer, 2012.
  • Mantegna R.N., “Hierarchical structure in financial markets”, Eur. Phys. J. B, 11, 193-197, 1999.
  • Mantegna R.N., Stanley H.E., “An Introduction to Econophysics-Correlation and Complexity in Finance”, Cambridge University Press, Cambridge, 2000.
  • Bonanno G., Caldarelli G., Lillo F., Mantegna R.N., “Topology of correlation-based minimal spanning trees in real and model markets”, Phys. Rev. E, 68, 046130, 2003.
  • Zherebtsov A.A., Kuperin Yu. A., Application of self-organizing maps for clustering DJIA and NASDAQ100 portfolios, cond-mat/ 0305330.
  • Eom C., Oh G., Kim S., “Topological Properties of a Minimal Spanning Tree in the Korean and the American Stock Markets”, J. Korean Phys. Soc., 51, 1432-1436, 2007.
  • Garas A., Argyrakis P., “Correlation study of the Athens Stock Exchange”, Physica A, 380, 399- 410, 2007.
  • Garas A., Argyrakis P., Havlin S., The structural role of weak and strong links in a financial market network, Eur. Phys. J. B 63, 265-271, 2008.
  • Çukur S., Eryigit M., Eryigit R., “Cross correlations in an emerging market financial data”, Physica A, 376, 555-564, 2007.
  • Gilmore C. G., Lucey B. M., Boscia M., “An ever-closer union? Examining the evolution of linkages of European equity markets via minimum spanning trees”, Physica A, 387, 6319-6329, 2008.
  • Sieczka P., Hołyst J.A., “Correlations in commodity markets”, Physica A, 388, 1621-1630, 2009.
  • Brida J. G., Esteban L. P., Risso W. A., Devesa M. J. S., “The international hotel industry in Spain: Its hierarchical structure”, Tourism Management, 31, 57-73, 2010.
  • Spada E., Saglioccca L., Sourdis J., Garbuglia A. R., Poggi V., Fusco C. D., Mele A., “Use of the Minimum Spanning Tree Model for Molecular Epidemiological Investigation of a Nosocomial Outbreak of Hepatitis C Virus Infection”, Journal of Clinical Microbiology, 42, 4230-4236, 2004.
  • Mizuno T., Takayasu H., Takayasu M., “Correlation networks among currencies”, Physica A, 364, 336-342, 2006.
  • Naylor M.J., Rose L.C., Moyle B.J., “Topology of foreign exchange markets using hierarchical structure methods”, Physica A, 382, 199-208, 2007.
  • Keskin M., Deviren B., Kocakaplan Y., “Topology of the correlation networks among major currencies using hierarchical structure methods”, Physica A, 390, 719-730, 2011.
  • Keskin M., Deviren B., Kantar E., Quantitative Finance, submitted.
  • Kocakaplan Y., Deviren B., Keskin M., Hierarchical structures of correlations networks among Turkey’s exports and imports by currencies, Physica A, 391, 6509-6518, 2012.
  • Kantar E., Deviren B., Keskin M., Hierarchical structure of Turkey’s foreign trade, Physica A, 390, 3454-3476, 2011.
  • Kantar E., Deviren B., Keskin M., Investigation of major international and Turkish companies via hierarchical methods and bootstrap approach, The European Physical Journal B, 84, 339- 350, 2011.
  • Kullmann L., Kertész J., Kaski K., Time-dependent cross-correlations between different stock returns: A directed network of influence, Phys. Rev. E, 66, 026125, 2002.
  • Bonanno G., Vandewalle N., Mantegna R.N., Taxonomy of stock market indices, Phys. Rev. E, 62, R7615- R7618, 2000.
  • Bonanno G., Lillo F. Mantegna R.N., High-frequency cross-correlation in a set of stocks, Quant. Finance, 1, 96-104, 2001.
  • Tumminello M., Coronnello C., Lillo F., Miccich`e S., Mantegna R. N., Spanning trees and bootstrap reliability estimation in correlation based networks, Int. J. Bifurcation Chaos, 17, 2319-2329, 2007.
  • Tumminello M., Lillo F., Mantegna R.N., Correlation, hierarchies, and networks in financial markets, J. Econ. Behav. Organ. 75, 40-58, 2010.
  • Onnela .J-P., Chakraborti A., Kaski K., Kertész J.,Kanto A., Dynamics of market correlations: Taxonomy and portfolio analysis, Phys. Rev. E, 68, 056110, 2003.
  • Coelho R., Gilmore C. G., Lucey B., Richmond P., Hutzler S., The evolution of interdependence in world equity markets—Evidence from minimum spanning trees, Physica A, 376, 455-466, 2007.
  • Junior L. S., Franca L. de Paula, Correlation of financial markets in times of crisis, Physica A 391, 187-208, 2012.
  • Gligor M. and Ausloos M., Clusters in weighted macroeconomic networks: the EU case. Introducing the overlapping index of GDP/capita fluctuation correlations, European Physical Journal B 63, 533-539, 2008.
  • Gorski A. Z., Drozdz S., Kwapien J., Oswiecimka, P., Minimal spanning tree graphs and power like scaling in FOREX networks, Acta Physica Polonica A, 114, 531-538, 2008.

Küresel Karbondioksit Emisyonu, Ekonomik Büyüme ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi

Yıl 2014, Cilt: 3 Sayı: 2, 1 - 14, 19.01.2015
https://doi.org/10.17100/nevbiltek.210933

Öz

Bu çalışmada, sosyofizik kapsamında yirmibeş Avrupa ülkesinin çevre kirlilikleri, ekonomik büyümeleri ve elektrik tüketimleri arasındaki topolojik ilişkiler hiyerarşik yapı yöntemleri [en küçük örten ağaç (minimal spanning tree, MST) ve hiyerarşik ağaç (hierarchical tree, HT)] kullanılarak 1970 ile 2010 yılları arasında detaylıca incelenmiştir. MST ve HT'ler verilerdeki hiyerarşiyi, sınıflandırmayı ve küresel yapıyı tespit etmek ve anlamak için kullanışlı seçeneklerdir. Ekonomik, sosyal, jeolojik ilişkilerine ve yakınlıklarına göre MST’lerden ve HT’lerden farklı kümeler tanımlanıp ve çevre kirliliği, ekonomik büyüme ve elektrik tüketimleri arasındaki ilişkiler belirlenmiştir. Böylece küme yapıları ve her bir kümedeki anahtar ülke/ülkeler de tespit edilmiştir.

Kaynakça

  • Callen E., Shapiro, D. A, Theory of Social Imitation, Phys. Today, 23-28, 1974.
  • Weidlich W., The statistical decription of polarization phenomena in society, Br. J. Math. Statist. Physcol, 24 (1), 251-266, 1971.
  • Vallacher R. R., Nowak A., Zochowski M., “Dynamics of social coordination: The synchronization of internal states in close relationships”, In P. Hauf & F. Forsterling (Eds.), Making minds: The shaping of human minds through social context (pp. 31-46). Amsterdam: John Benjamins Publishing Company. UW, 2007.
  • Kulakowski K., Around the Gap between Sociophysics and Sociology (abs), Prepared for the book 'Lectures on Socio- and Econophysics' after the Summer School on SocioEcono-Physics 2007 in Windberg, 2007.
  • Galam S, Sociophysics: do Humans Behave Like Atoms?, CREA, Paris, November 14-16, 2011.
  • Galam S. Sociophysics: A Physicist’s Modeling of Psycho-political Phenomena, Claiming the Paternity of Sociophysics, pgs. 61-63. Springer, 2012.
  • Mantegna R.N., “Hierarchical structure in financial markets”, Eur. Phys. J. B, 11, 193-197, 1999.
  • Mantegna R.N., Stanley H.E., “An Introduction to Econophysics-Correlation and Complexity in Finance”, Cambridge University Press, Cambridge, 2000.
  • Bonanno G., Caldarelli G., Lillo F., Mantegna R.N., “Topology of correlation-based minimal spanning trees in real and model markets”, Phys. Rev. E, 68, 046130, 2003.
  • Zherebtsov A.A., Kuperin Yu. A., Application of self-organizing maps for clustering DJIA and NASDAQ100 portfolios, cond-mat/ 0305330.
  • Eom C., Oh G., Kim S., “Topological Properties of a Minimal Spanning Tree in the Korean and the American Stock Markets”, J. Korean Phys. Soc., 51, 1432-1436, 2007.
  • Garas A., Argyrakis P., “Correlation study of the Athens Stock Exchange”, Physica A, 380, 399- 410, 2007.
  • Garas A., Argyrakis P., Havlin S., The structural role of weak and strong links in a financial market network, Eur. Phys. J. B 63, 265-271, 2008.
  • Çukur S., Eryigit M., Eryigit R., “Cross correlations in an emerging market financial data”, Physica A, 376, 555-564, 2007.
  • Gilmore C. G., Lucey B. M., Boscia M., “An ever-closer union? Examining the evolution of linkages of European equity markets via minimum spanning trees”, Physica A, 387, 6319-6329, 2008.
  • Sieczka P., Hołyst J.A., “Correlations in commodity markets”, Physica A, 388, 1621-1630, 2009.
  • Brida J. G., Esteban L. P., Risso W. A., Devesa M. J. S., “The international hotel industry in Spain: Its hierarchical structure”, Tourism Management, 31, 57-73, 2010.
  • Spada E., Saglioccca L., Sourdis J., Garbuglia A. R., Poggi V., Fusco C. D., Mele A., “Use of the Minimum Spanning Tree Model for Molecular Epidemiological Investigation of a Nosocomial Outbreak of Hepatitis C Virus Infection”, Journal of Clinical Microbiology, 42, 4230-4236, 2004.
  • Mizuno T., Takayasu H., Takayasu M., “Correlation networks among currencies”, Physica A, 364, 336-342, 2006.
  • Naylor M.J., Rose L.C., Moyle B.J., “Topology of foreign exchange markets using hierarchical structure methods”, Physica A, 382, 199-208, 2007.
  • Keskin M., Deviren B., Kocakaplan Y., “Topology of the correlation networks among major currencies using hierarchical structure methods”, Physica A, 390, 719-730, 2011.
  • Keskin M., Deviren B., Kantar E., Quantitative Finance, submitted.
  • Kocakaplan Y., Deviren B., Keskin M., Hierarchical structures of correlations networks among Turkey’s exports and imports by currencies, Physica A, 391, 6509-6518, 2012.
  • Kantar E., Deviren B., Keskin M., Hierarchical structure of Turkey’s foreign trade, Physica A, 390, 3454-3476, 2011.
  • Kantar E., Deviren B., Keskin M., Investigation of major international and Turkish companies via hierarchical methods and bootstrap approach, The European Physical Journal B, 84, 339- 350, 2011.
  • Kullmann L., Kertész J., Kaski K., Time-dependent cross-correlations between different stock returns: A directed network of influence, Phys. Rev. E, 66, 026125, 2002.
  • Bonanno G., Vandewalle N., Mantegna R.N., Taxonomy of stock market indices, Phys. Rev. E, 62, R7615- R7618, 2000.
  • Bonanno G., Lillo F. Mantegna R.N., High-frequency cross-correlation in a set of stocks, Quant. Finance, 1, 96-104, 2001.
  • Tumminello M., Coronnello C., Lillo F., Miccich`e S., Mantegna R. N., Spanning trees and bootstrap reliability estimation in correlation based networks, Int. J. Bifurcation Chaos, 17, 2319-2329, 2007.
  • Tumminello M., Lillo F., Mantegna R.N., Correlation, hierarchies, and networks in financial markets, J. Econ. Behav. Organ. 75, 40-58, 2010.
  • Onnela .J-P., Chakraborti A., Kaski K., Kertész J.,Kanto A., Dynamics of market correlations: Taxonomy and portfolio analysis, Phys. Rev. E, 68, 056110, 2003.
  • Coelho R., Gilmore C. G., Lucey B., Richmond P., Hutzler S., The evolution of interdependence in world equity markets—Evidence from minimum spanning trees, Physica A, 376, 455-466, 2007.
  • Junior L. S., Franca L. de Paula, Correlation of financial markets in times of crisis, Physica A 391, 187-208, 2012.
  • Gligor M. and Ausloos M., Clusters in weighted macroeconomic networks: the EU case. Introducing the overlapping index of GDP/capita fluctuation correlations, European Physical Journal B 63, 533-539, 2008.
  • Gorski A. Z., Drozdz S., Kwapien J., Oswiecimka, P., Minimal spanning tree graphs and power like scaling in FOREX networks, Acta Physica Polonica A, 114, 531-538, 2008.
Toplam 35 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Fizik
Yazarlar

Şeyma Akkaya Deviren

Yayımlanma Tarihi 19 Ocak 2015
Yayımlandığı Sayı Yıl 2014 Cilt: 3 Sayı: 2

Kaynak Göster

APA Akkaya Deviren, Ş. (2015). Küresel Karbondioksit Emisyonu, Ekonomik Büyüme ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi. Nevşehir Bilim Ve Teknoloji Dergisi, 3(2), 1-14. https://doi.org/10.17100/nevbiltek.210933
AMA Akkaya Deviren Ş. Küresel Karbondioksit Emisyonu, Ekonomik Büyüme ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi. Nevşehir Bilim ve Teknoloji Dergisi. Şubat 2015;3(2):1-14. doi:10.17100/nevbiltek.210933
Chicago Akkaya Deviren, Şeyma. “Küresel Karbondioksit Emisyonu, Ekonomik Büyüme Ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi”. Nevşehir Bilim Ve Teknoloji Dergisi 3, sy. 2 (Şubat 2015): 1-14. https://doi.org/10.17100/nevbiltek.210933.
EndNote Akkaya Deviren Ş (01 Şubat 2015) Küresel Karbondioksit Emisyonu, Ekonomik Büyüme ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi. Nevşehir Bilim ve Teknoloji Dergisi 3 2 1–14.
IEEE Ş. Akkaya Deviren, “Küresel Karbondioksit Emisyonu, Ekonomik Büyüme ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi”, Nevşehir Bilim ve Teknoloji Dergisi, c. 3, sy. 2, ss. 1–14, 2015, doi: 10.17100/nevbiltek.210933.
ISNAD Akkaya Deviren, Şeyma. “Küresel Karbondioksit Emisyonu, Ekonomik Büyüme Ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi”. Nevşehir Bilim ve Teknoloji Dergisi 3/2 (Şubat 2015), 1-14. https://doi.org/10.17100/nevbiltek.210933.
JAMA Akkaya Deviren Ş. Küresel Karbondioksit Emisyonu, Ekonomik Büyüme ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi. Nevşehir Bilim ve Teknoloji Dergisi. 2015;3:1–14.
MLA Akkaya Deviren, Şeyma. “Küresel Karbondioksit Emisyonu, Ekonomik Büyüme Ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi”. Nevşehir Bilim Ve Teknoloji Dergisi, c. 3, sy. 2, 2015, ss. 1-14, doi:10.17100/nevbiltek.210933.
Vancouver Akkaya Deviren Ş. Küresel Karbondioksit Emisyonu, Ekonomik Büyüme ve Elektrik Tüketiminin Hiyerarşik Yapı Yöntemleri Kullanılarak Topolojik Analizi. Nevşehir Bilim ve Teknoloji Dergisi. 2015;3(2):1-14.

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