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An Input-Output Network Structure Analysis Of Selected Countries

Yıl 2017, Cilt: 3 Sayı: 2, 65 - 88, 25.12.2017

Öz

Network analysis is a very effective method which can be used in many different disciplines.
It is possible to use network analysis in many areas of economics as well. Recently, input-output
tables attracted economists who work in this area. Input-output tables give an important source
of data for examining the productive significance of sectors since they reflect the intersectoral flows
of intermediate goods. In this study, national input-output networks of selected nine countries
which are in different levels of development and which have an important place in world trade are
examined. This kind of an analysis may help us understand whether or not there is a connection
between development levels and sectoral relationships. 

Kaynakça

  • Acemoglu, D., Akcigit, U. and Kerr, W. (2016). Networks and the macroeconomy: An empiricalexploration. NBER Macroeconomics Annual, 30 (1), 273–335.
  • —, Carvalho, V. M., Ozdaglar, A. and Tahbaz-Salehi, A. (2012). The network origins of aggregate fluctuations. Econometrica, 80 (5), 1977–2016.
  • Aroche-Reyes, F. (2002). Structural transformations and important coefficients in the north american economies. Economic Systems Research, 14 (3), 257–273.
  • Atan, S. and Arslanturk, Y. (2012). Tourism and economic growth nexus: An input output analysis in Turkey. Procedia-Social and Behavioral Sciences, 62, 952–956.
  • Barabási, A.-L. and Albert, R. (1999). Emergence of scaling in random networks. Science, 286 (5439), 509–512.
  • Bogataj, M., Grubbström, R. W. and Bogataj, L. (2011). Efficient location of industrial activitycells in a global supply chain. International journal of production Economics, 133 (1), 243–250.
  • Carvalho, V. M. (2008). Aggregate fluctuations and the network structure of intersectoral trade. The University of Chicago.
  • Chenery, H. B. and Watanabe, T. (1958). International comparisons of the structure of production. Econometrica: Journal of the Econometric Society, 16, 487–521.
  • Dazhong, C. (2015). China’s integration into the global value chains: A transnational input-output analysis. Economic Research Journal, 9, 002.
  • DeCarlo, L. T. (1997). On the meaning and use of kurtosis. Psychological methods, 2 (3), 292.
  • Dornbusch, R., Fischer, S. and Samuelson, P. A. (1977). Comparative advantage, trade, and payments in a ricardian model with a continuum of goods. The American Economic Review, 67 (5),823–839.
  • Duan, W.-Q. (2012). Modelling the evolution of national economies based on input–output networks. Computational Economics, 39 (2), 145–155.
  • Dupor, B. (1999). Aggregation and irrelevance in multi-sector models. Journal of Monetary Economics, 43 (2), 391–409.
  • Estrada, E. (2015). Introduction to complex networks: structure and dynamics. In Evolutionary Equations with Applications in Natural Sciences, Springer, pp. 93–131.
  • Fagiolo, G., Reyes, J. and Schiavo, S. (2010). The evolution of the world trade web: a weightednetwork analysis. Journal of Evolutionary Economics, 20 (4), 479–514.
  • Foerster, A. T., Sarte, P.-D. G. and Watson, M. W. (2011). Sectoral versus aggregate shocks: A structural factor analysis of industrial production. Journal of Political Economy, 119 (1), 1–38.
  • Freytag, A. and Fricke, S. (2017). Sectoral linkages of financial services as channels of economic development?an input–output analysis of the nigerian and kenyan economies. Review of Development Finance, 7 (1), 36–44.
  • Frohm, E., Gunnella, V. et al. (2017). Sectoral interlinkages in global value chains: spillovers and network effects. Tech. rep.
  • Fuge, M., Tee, K., Agogino, A. and Maton, N. (2014). Analysis of collaborative design networks: A case study of openideo. Journal of Computing and Information Science in Engineering, 14 (2), 021009.
  • Hansda, S. (2005). Sustainability of Services-Led Growth: an input output exploration of the Indian economy. Tech. rep., EconWPA.
  • Hein, O., Schwind, M. and König, W. (2006). Scale-free networks. Wirtschaftsinformatik, 48 (4), 267–275.
  • Hewings, G. J. (1982). The empirical identification of key sectors in an economy: a regional perspective. The Developing Economies, 20 (2), 173–195.
  • Hirschman, A. O. A. O. (1958). The strategy of economic development. Yale Univ. Press.
  • Horvath, M. (1998). Cyclicality and sectoral linkages: Aggregate fluctuations from independent sectoral shocks. Review of Economic Dynamics, 1 (4), 781–808.
  • — (2000). Sectoral shocks and aggregate fluctuations. Journal of Monetary Economics, 45 (1), 69–106.
  • Howell, A. (2012). Network statistics and modeling the global trade economy: exponential random graph models and latent space models: is geography dead? University of California Unpublished Thesis.
  • Hummels, D., Ishii, J. and Yi, K.-M. (2001). The nature and growth of vertical specialization in world trade. Journal of international Economics, 54 (1), 75–96.
  • Jackson, M. O. (2010). Research opportunities in the study of social and economic networks. White paper prepared for the NSF/SBE.
  • Johnson, R. C. and Noguera, G. (2012). Accounting for intermediates: Production sharing and trade in value added. Journal of international Economics, 86 (2), 224–236.
  • Kleinberg, J. M. (1999). Authoritative sources in a hyperlinked environment. Journal of the ACM (JACM), 46 (5), 604–632.
  • Kolaczyk, E. D. (2009). Statistical Analysis of Network Data: Methods and Models. Springer Series in Statistics, Springer-Verlag New York, 1st edn.
  • Kuroiwa, I. et al. (2014). Value added trade and structure of high-technology exports in china. IDE-JETRO Discussion Paper, 449.
  • León, C. and Berndsen, R. J. (2014). Rethinking financial stability: challenges arising from financial networks’ modular scale-free architecture. Journal of Financial Stability, 15, 241–256.
  • —, Machado, C. and Sarmiento, M. (2016). Identifying central bank liquidity super-spreaders in interbank funds networks. Journal of Financial Stability.
  • — and Perez, J. (2013). Authority centrality and hub centrality as metrics of systemic importance of financial market infrastructures. Borradores de Economia, 754, 1–24.
  • Liu, E. (2017). Industrial policies and economic development. https://economics.mit.edu/files/13288.
  • Long Jr, J. B. and Plosser, C. I. (1983). Real business cycles. Journal of political Economy, 91 (1), 39–69.
  • Lovric, M. (2010). Skewness. In International Encyclopedia of Statistical Science, Springer, pp. 1340–1342.
  • Michael, D. K. and Battiston, S. (2009). From graph theory to models of economic networks. a tutorial. Networks, Topology and Dynamics, pp. 23–63.
  • Mitchell, M. (2009). Complexity: A guided tour. Oxford University Press.
  • Neilson, J., Pritchard, B. and Yeung, H. W.-c. (2014). Global value chains and global production networks in the changing international political economy: An introduction. Review of International Political Economy, 21 (1), 1–8.
  • Newman, M. E. J. (2010). Networks: an introduction. Oxford University Press, Oxford.
  • Oecd (2009). Applications of Complexity Science for Public Policy- New Tools for Finding Unanticipated Consequences and Unrealized Opportunities. OECD Publishing.
  • Opsahl, T. and Panzarasa, P. (2009). Clustering in weighted networks. Social networks, 31 (2), 155–163.
  • Powers, W. (2012). The value of value added-measuring global engagement with gross and valueadded trade. World Economics-Abingdon, 13 (4), 19.
  • Rashid, A. (2004). Sectoral linkages; identifying the key growth stimulating sector of the pakistan economy. MPRA Paper No. 27210 Munich.
  • Rasmussen, P. N. (1956). Studies in inter-sectoral relations, vol. 15. E. Harck.
  • Reichardt, J. (2008). Structure in complex networks, vol. 766. Springer.
  • Schnabl, H. (1994). The evolution of production structures, analyzed by a multi-layer procedure. Economic Systems Research, 6 (1), 51–68.
  • Shea, J. (2002). Complementarities and comovements. Journal of Money, Credit, and Banking, 34 (2), 412–433.
  • Singh, N. (2006). Services-led industrialization in india: Assessment and lessons. MPRA Paper No. 1276, Munich.
  • Timmer, M. P., Los, B., Stehrer, R., de Vries, G. J. et al. (2016). An anatomy of the global trade slowdown based on the WIOD 2016 release. Tech. rep., Groningen Growth and Development Centre, University of Groningen.
  • Tregenna, F. (2008). Sectoral engines of growth in South Africa: An analysis of services and manufacturing. 2008.98, Research paper/UNU-WIDER.
  • West, G. R. and Brown, R. P. (2003). Structural change, intersectoral linkages and hollowingout in the taiwanese economy, 1976-1994. Discussion Paper, School of Economics, University of Queensland., (327).
  • Xiang, J., Hu, T., Zhang, Y., Hu, K., Tang, Y.-N., Gao, Y.-Y. and Deng, K. (2016). Linear analysis of degree correlations in complex networks. Pramana, 87 (6), 84.

An Input-Output Network Structure Analysis Of Selected Countries

Yıl 2017, Cilt: 3 Sayı: 2, 65 - 88, 25.12.2017

Öz

Ağ analizi pek çok alanda kullanılabilen çok etkin bir yöntemdir. Ağ analizini iktisadın pek çok alanında da kullanmak mümkündür. Bu alanda çalışan iktisatçıların yakın zamanda girdi-çıktı tabloları ilgisini çekmektedir. Girdi-Çıktı tabloları sektörler arası kaynak aktarımını gösterdikleri için, sektörlerin üretkenlik açısından öneminin analiz edilmesi için önemli bir veri kaynağı sunmaktadırlar. Bu çalışmada, seçilmiş dokuz ülkenin girdi-çıktı ağları incelenmiştir. Böyle bir analiz, gelişmişlik düzeyi ile sektörler arası bağlantılar arasında bir ilişki olup olmadığını anlamaya yardımcı olabilir. 

Kaynakça

  • Acemoglu, D., Akcigit, U. and Kerr, W. (2016). Networks and the macroeconomy: An empiricalexploration. NBER Macroeconomics Annual, 30 (1), 273–335.
  • —, Carvalho, V. M., Ozdaglar, A. and Tahbaz-Salehi, A. (2012). The network origins of aggregate fluctuations. Econometrica, 80 (5), 1977–2016.
  • Aroche-Reyes, F. (2002). Structural transformations and important coefficients in the north american economies. Economic Systems Research, 14 (3), 257–273.
  • Atan, S. and Arslanturk, Y. (2012). Tourism and economic growth nexus: An input output analysis in Turkey. Procedia-Social and Behavioral Sciences, 62, 952–956.
  • Barabási, A.-L. and Albert, R. (1999). Emergence of scaling in random networks. Science, 286 (5439), 509–512.
  • Bogataj, M., Grubbström, R. W. and Bogataj, L. (2011). Efficient location of industrial activitycells in a global supply chain. International journal of production Economics, 133 (1), 243–250.
  • Carvalho, V. M. (2008). Aggregate fluctuations and the network structure of intersectoral trade. The University of Chicago.
  • Chenery, H. B. and Watanabe, T. (1958). International comparisons of the structure of production. Econometrica: Journal of the Econometric Society, 16, 487–521.
  • Dazhong, C. (2015). China’s integration into the global value chains: A transnational input-output analysis. Economic Research Journal, 9, 002.
  • DeCarlo, L. T. (1997). On the meaning and use of kurtosis. Psychological methods, 2 (3), 292.
  • Dornbusch, R., Fischer, S. and Samuelson, P. A. (1977). Comparative advantage, trade, and payments in a ricardian model with a continuum of goods. The American Economic Review, 67 (5),823–839.
  • Duan, W.-Q. (2012). Modelling the evolution of national economies based on input–output networks. Computational Economics, 39 (2), 145–155.
  • Dupor, B. (1999). Aggregation and irrelevance in multi-sector models. Journal of Monetary Economics, 43 (2), 391–409.
  • Estrada, E. (2015). Introduction to complex networks: structure and dynamics. In Evolutionary Equations with Applications in Natural Sciences, Springer, pp. 93–131.
  • Fagiolo, G., Reyes, J. and Schiavo, S. (2010). The evolution of the world trade web: a weightednetwork analysis. Journal of Evolutionary Economics, 20 (4), 479–514.
  • Foerster, A. T., Sarte, P.-D. G. and Watson, M. W. (2011). Sectoral versus aggregate shocks: A structural factor analysis of industrial production. Journal of Political Economy, 119 (1), 1–38.
  • Freytag, A. and Fricke, S. (2017). Sectoral linkages of financial services as channels of economic development?an input–output analysis of the nigerian and kenyan economies. Review of Development Finance, 7 (1), 36–44.
  • Frohm, E., Gunnella, V. et al. (2017). Sectoral interlinkages in global value chains: spillovers and network effects. Tech. rep.
  • Fuge, M., Tee, K., Agogino, A. and Maton, N. (2014). Analysis of collaborative design networks: A case study of openideo. Journal of Computing and Information Science in Engineering, 14 (2), 021009.
  • Hansda, S. (2005). Sustainability of Services-Led Growth: an input output exploration of the Indian economy. Tech. rep., EconWPA.
  • Hein, O., Schwind, M. and König, W. (2006). Scale-free networks. Wirtschaftsinformatik, 48 (4), 267–275.
  • Hewings, G. J. (1982). The empirical identification of key sectors in an economy: a regional perspective. The Developing Economies, 20 (2), 173–195.
  • Hirschman, A. O. A. O. (1958). The strategy of economic development. Yale Univ. Press.
  • Horvath, M. (1998). Cyclicality and sectoral linkages: Aggregate fluctuations from independent sectoral shocks. Review of Economic Dynamics, 1 (4), 781–808.
  • — (2000). Sectoral shocks and aggregate fluctuations. Journal of Monetary Economics, 45 (1), 69–106.
  • Howell, A. (2012). Network statistics and modeling the global trade economy: exponential random graph models and latent space models: is geography dead? University of California Unpublished Thesis.
  • Hummels, D., Ishii, J. and Yi, K.-M. (2001). The nature and growth of vertical specialization in world trade. Journal of international Economics, 54 (1), 75–96.
  • Jackson, M. O. (2010). Research opportunities in the study of social and economic networks. White paper prepared for the NSF/SBE.
  • Johnson, R. C. and Noguera, G. (2012). Accounting for intermediates: Production sharing and trade in value added. Journal of international Economics, 86 (2), 224–236.
  • Kleinberg, J. M. (1999). Authoritative sources in a hyperlinked environment. Journal of the ACM (JACM), 46 (5), 604–632.
  • Kolaczyk, E. D. (2009). Statistical Analysis of Network Data: Methods and Models. Springer Series in Statistics, Springer-Verlag New York, 1st edn.
  • Kuroiwa, I. et al. (2014). Value added trade and structure of high-technology exports in china. IDE-JETRO Discussion Paper, 449.
  • León, C. and Berndsen, R. J. (2014). Rethinking financial stability: challenges arising from financial networks’ modular scale-free architecture. Journal of Financial Stability, 15, 241–256.
  • —, Machado, C. and Sarmiento, M. (2016). Identifying central bank liquidity super-spreaders in interbank funds networks. Journal of Financial Stability.
  • — and Perez, J. (2013). Authority centrality and hub centrality as metrics of systemic importance of financial market infrastructures. Borradores de Economia, 754, 1–24.
  • Liu, E. (2017). Industrial policies and economic development. https://economics.mit.edu/files/13288.
  • Long Jr, J. B. and Plosser, C. I. (1983). Real business cycles. Journal of political Economy, 91 (1), 39–69.
  • Lovric, M. (2010). Skewness. In International Encyclopedia of Statistical Science, Springer, pp. 1340–1342.
  • Michael, D. K. and Battiston, S. (2009). From graph theory to models of economic networks. a tutorial. Networks, Topology and Dynamics, pp. 23–63.
  • Mitchell, M. (2009). Complexity: A guided tour. Oxford University Press.
  • Neilson, J., Pritchard, B. and Yeung, H. W.-c. (2014). Global value chains and global production networks in the changing international political economy: An introduction. Review of International Political Economy, 21 (1), 1–8.
  • Newman, M. E. J. (2010). Networks: an introduction. Oxford University Press, Oxford.
  • Oecd (2009). Applications of Complexity Science for Public Policy- New Tools for Finding Unanticipated Consequences and Unrealized Opportunities. OECD Publishing.
  • Opsahl, T. and Panzarasa, P. (2009). Clustering in weighted networks. Social networks, 31 (2), 155–163.
  • Powers, W. (2012). The value of value added-measuring global engagement with gross and valueadded trade. World Economics-Abingdon, 13 (4), 19.
  • Rashid, A. (2004). Sectoral linkages; identifying the key growth stimulating sector of the pakistan economy. MPRA Paper No. 27210 Munich.
  • Rasmussen, P. N. (1956). Studies in inter-sectoral relations, vol. 15. E. Harck.
  • Reichardt, J. (2008). Structure in complex networks, vol. 766. Springer.
  • Schnabl, H. (1994). The evolution of production structures, analyzed by a multi-layer procedure. Economic Systems Research, 6 (1), 51–68.
  • Shea, J. (2002). Complementarities and comovements. Journal of Money, Credit, and Banking, 34 (2), 412–433.
  • Singh, N. (2006). Services-led industrialization in india: Assessment and lessons. MPRA Paper No. 1276, Munich.
  • Timmer, M. P., Los, B., Stehrer, R., de Vries, G. J. et al. (2016). An anatomy of the global trade slowdown based on the WIOD 2016 release. Tech. rep., Groningen Growth and Development Centre, University of Groningen.
  • Tregenna, F. (2008). Sectoral engines of growth in South Africa: An analysis of services and manufacturing. 2008.98, Research paper/UNU-WIDER.
  • West, G. R. and Brown, R. P. (2003). Structural change, intersectoral linkages and hollowingout in the taiwanese economy, 1976-1994. Discussion Paper, School of Economics, University of Queensland., (327).
  • Xiang, J., Hu, T., Zhang, Y., Hu, K., Tang, Y.-N., Gao, Y.-Y. and Deng, K. (2016). Linear analysis of degree correlations in complex networks. Pramana, 87 (6), 84.
Toplam 55 adet kaynakça vardır.

Ayrıntılar

Bölüm Makaleler
Yazarlar

Semanur Soyyiğit

Yasemin Asu Çırpıcı

Yayımlanma Tarihi 25 Aralık 2017
Yayımlandığı Sayı Yıl 2017 Cilt: 3 Sayı: 2

Kaynak Göster

APA Soyyiğit, S., & Çırpıcı, Y. A. (2017). An Input-Output Network Structure Analysis Of Selected Countries. Yildiz Social Science Review, 3(2), 65-88.