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YÜKSELEN PİYASA EKONOMİLERİ KARMASI: EM2-18 MODELİ UYGULAMASI

Yıl 2021, Cilt: 20 Sayı: 40, 632 - 660, 25.06.2021
https://doi.org/10.46928/iticusbe.939364

Öz

Ekonominin makro anlamdaki krizlerden uzak dönemlerinde, ülkelerin sergiledikleri performansların potansiyel performanslarına en yakın sonuçları vereceği varsayılmaktadır. Bu varsayıma karşın sürdürülen performansların krizleri içeren senaryolarda nasıl bir trend izleyeceği özellikle önem taşımaktadır.
Amaç: Çalışmada gelişmekte olan ülkelerden seçilmiş 41 ülkenin 2015-2019 ve 2016-2020 dönemlerinde; büyüme oranı, enflasyon oranı, işsizlik oranı, faiz oranı ve döviz kuru göstergelerinden oluşturulan makroekonomik performanslarına göre Yükselen Piyasa Ekonomileri Karması'nın (EM2-18) belirlenmesi amaçlanmıştır. Bu çerçevede, ülkelerin 2020’de ortaya çıkan pandemi krizinden önceki 2015-2019 dönemiyle krizin dâhil olduğu 2016-2020 dönemi verileri analiz edilmiştir. Ayrıca, söz konusu analiz dönemlerinde Yükselen Piyasa Ekonomileri Karması'nı oluşturan ülkelerin bütçe açığı/GSYH, cari açık/GSYH ve kamu borç stoku/GSYH oranları makroekonomik performansın yan etkileri olarak ele alınmıştır.
Yöntem: Çalışmada, ülkelerin yıllık ve beş yıllık ortalamaları dikkate alınarak makroekonomik performans sıralaması yapmak amacıyla Çok Kriterli Karar Verme Teknikleri kullanılmıştır. Yeni yıl eklendiğinde beş yıllık dönemin ilk yılı çıkarılmaktadır. Analitik Hiyerarşi Süreci (AHP) ile makroekonomik performans göstergeleri ağırlıklandırılarak endeks oluşturulmuş ve ülkelerin TOPSIS modeliyle sıralamaları belirlenmiştir.
Bulgular: 41 ülkeden ilk 18’e girenler, görece daha iyi makroekonomik performansa sahip olduklarından Yükselen Piyasa Ekonomileri Karması'nı oluşturan ülkeler olarak belirlenirken diğerleri ise söz konusu Karma’ya girebilecek aday ülkeler olarak ele alınmıştır. Çalışmada kullanılan modelin makroekonomik performans analizi, geçmiş beş yıllık göstergelerin yıllık ve beş yıllık ortalamalarını dikkate aldığından orta vadeli süreçlerde kamu otoritelerinin tercih ve önceliklerinin doğrudan/dolaylı sonuçlarına da işaret etmektedir. Cari açık, bütçe açığı ve kamu borç stoku göstergelerindeki değişimler analizin öne çıkan önemli başka bir özelliğini yansıtmaktadır. Seçilen ülkelerin coğrafi dağılımı ise dünyanın her bölgesini içerecek şekilde tasarlanmıştır ve yüksek performanslı ülkelerin genel olarak Asya kıtasında kümelendiği görülmüştür.
Özgünlük: Çalışmada kullanılan yaklaşımla literatürde yer alan makroekonomik performans analizi makroekonomik istikrar perspektifiyle birlikte ele alınmakta ve bu yaklaşıma ekonomi politik boyut katılarak farklı bir bakış açısı sunulmaktadır. Böyle bir yaklaşım, ulusal ve küresel ekonomik paydaşların karar alma ve uygulama süreçlerinde kullanabilecekleri makroekonomik veri ve bilgi setinin üretilmesini mümkün kılmaktadır. Modelin daha sonraki uygulamalarında, gerçekleşmiş verilerin yanında göstergelerin yıllık tahminleri kullanılarak Yükselen Piyasa Ekonomileri Karması'nın bir yıl sonraki muhtemel ülkeleri de belirlenecektir.

Kaynakça

  • Andres, J., Domenech, R., & Molinas, C. (1996). Macroeconomic performance and convergence in OECD countries. European Economic Review, 40(9), 1683-1704.
  • Ardielli, E. (2019). Use of TOPSIS method for assessing of good governance in European Union countries. Review of Economic Perspectives, 3, 2011-231.
  • Azimifard, A., Moosavirad, S. H., & Ariafar, S. (2018). Selecting sustainable supplier countries for Iran's steel industry at three levels by using AHP and TOPSIS methods. Resources Policy, 57, 30-44.
  • Balcerzak, A. P., & Pietrzak, M. B. (2016). Application of TOPSIS Method for Analysis of Sustainable Development in European Union Countries. Institute of Economic Research Working Papers, 22, 82-92.
  • Balioti, V., Tzimopoulos, C., & Evangelides, C. (2018). Multi-criteria decision making using topsis method under fuzzy environment. Application in spillway selection. Multidisciplinary Digital Publishing Institute Proceedings, 2(11), 637-645.
  • Bekaert, G., Erb, C. B., Harvey, C. R., & Viskanta, T. E. (1997). What matters for emerging equity market investments. Emerging markets quarterly, 1(2), 17-46.
  • Brauers, W. K., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, 35, 445-469.
  • Cheng, E. W., & Li, H. (2001). Analytic hierarchy process. Measuring Business Excellence, 5(3).
  • Easterly, W., & Schmidt-Hebbel, K. (1993). FISCAL DEFICITS AND MACROECONOMIC PERFORMANCE IN DEVELOPING COUNTRIES. The World Bank Research Observer, 8(2), 211-237.
  • Ekren, N., & Fındıkçı, M. (2016). AHP ve VIKOR yöntemleri ile avrupa birliği’ne üye ülkeler ve türkiye'nin ekonomik performanslarının değerlendirilmesi. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi,, 17(33), 525-536.
  • Ekren, N., Aykaç Alp, E., & Yağmur, M. H. (2017). Macroeconomic performance index: a new approach to calculation of economic wellbeing. Applied Economics, 49(53), 5462–5476.
  • Erdoğan Fındıkçı, M. (2020). Türkiye dâhil seçilmiş yükselen piyasa ekonomileri için makroekonomik performans ölçümü: Mukayeseli bir analiz. (Yayımlanmamış doktora tezi). İstanbul Ticaret Üniversitesi Finans Enstitüsü Finansal Anabilim Dalı, İstanbul.
  • Ewa, L. (2009). Okun`s and Barro`s Misery Index as an alternative poverty assessment tool. Recent estimations for European countries. MPRA, 1-11.
  • Frankel, J. A. (2010). Monetary policy in emerging markets: a survey. National Bureau of Economic Research(No. w16125).
  • Ghura, D., & Grennes, T. J. (1993). The real exchange rate and macroeconomic performance in Sub-Saharan Africa. Journal of Development Economics, 42(1), 155-174.
  • Greenaway, D., & Nam, C. H. (1988). Industrialisation and macroeconomic performance in developing countries under alternative trade strategies. Kyklos, 41(3), 419-435.
  • Husain, A. M., Mody, A., & Rogoff, K. S. (2005). Exchange rate regıme durability and performance in developing versus advanced economies. Journal of Monetary Economics, 52(1), 35-64.
  • IFC. (2020, Nisan 13). Establishing "emerging markets". International Finance Group: https://www.ifc.org/wps/wcm/connect/corp_ext_content/ifc_external_corporate_site/about+ifc_new/ifc+history/establishing-emerging-markets adresinden alındı
  • Kahn, M. E., Mohaddes, K., Ng, R. N., Peseran, M. H., Raissi, M., & Yang, J.-C. (2019). Long-Term Macroeconomic Effects of Climate Change: A Cross-Country Analysis. NBER Working Paper, 1-55.
  • Khramov, V., & Lee, J. R. (2013). The Economic Performance Index (EPI): an intuitive indicator for assessing a country's economic performance dynamics in an historical perspective. IMF.
  • Leal, J. E. (2020). AHP-Express: A Simplified Version of The Analytical Hierarchy Process Method. MethodsX,, 7, 1-11.
  • Marquis, C., & Raynard, M. (2015). Institutional strategies in emerging markets. Academy of Management Annals, 9(1), 291-335.
  • Mateusz, P., Danuta, M., Małgorzata, Ł., Mariusz, B., & Kesra, N. (2018). TOPSIS and VIKOR methods in study of sustainable development in the EU countries. Procedia Computer Science, 126, 1683-1692. Mishkin, F. S. (2009). Globalization, Macroeconomic Performance, and Monetary Policy. Journal of Money, Credit and Banking, 41(1), 187-196.
  • Roszkowska, E. (2011). Multi-criteria decision making models by applying the TOPSIS method to crisp and interval data. Multiple Criteria Decision Making/University of Economics in Katowice,, 6, 200-230.
  • Saaty, T. L. (2001). Fundamentals of the analytic hierarchy process. In The analytic hierarchy process in natural resource and environmental decision making. Springer, 15-35.
  • Saaty, T. L. (2008). The Analytic Hierarchy and Analytic Network Measurement Processes: applications to decisions under risk. European Journal of Pure And Applied Mathematics, 1(1), 83-98.
  • Sokolov, V., Lee, B.-J., & Mark, N. C. (2011). Linkages between exchange rate policy and macroeconomic performance. Pacific Economic Review, 16(4), 395-420.
  • Vavrek, R., & Chovancová, J. (2019). Assessment of economic and environmental energy performance of EU countries using CV-TOPSIS technique. Ecolohical Indicators, 106, -.
  • Wang, C.-N., & Le, A. L. (2018). Measuring the Macroeconomic Performance among Developed Countries and Asian Developing Countries: Past, Present, and Future. Sustainability, 10(3664).
  • Wankhede, S. V., & Hole, J. A. (2020). MOORA and TOPSIS Based Selection of Input Parameter in solar powered absorption refrigeration system. International Journal of Ambient Energy, 1-6. doi:https://doi.org/10.1080/01430750.2020.1831600
  • Yıldırım, Z., & Ivrendi, M. (2016). Exchange rate fluctuations and macroeconomic performance. Journal of Economic Studies.

EMERGING MARKET ECONOMIES MIX: IMPLEMENTATION OF THE EM2-18 MODEL

Yıl 2021, Cilt: 20 Sayı: 40, 632 - 660, 25.06.2021
https://doi.org/10.46928/iticusbe.939364

Öz

It is assumed that the performances of the countries will give the closest results to their potential performances in the periods of the economy away from the macro crises. Despite this assumption, it is particularly important to see what trend sustained performances will follow in scenarios involving crises. It is assumed that the performances of the countries will give the closest results to their potential performances in the periods of the economy away from the macro crises.
Objective: In the study, it was aimed to determine the Emerging Markets Mix (EM2-18) of 41 countries selected from developing countries based on their relative macroeconomic performances, which is formed from indicators of growth rate, inflation rate, unemployment rate, interest rate, and exchange rate in 2015-2019 and 2016-2020 periods. In this framework, the data of selected countries for the 2015-2019 period before the global pandemic crisis that emerged in 2020 and the 2016-2020 period, including the crisis, were analysed. In addition, budget deficit / GDP, current account deficit / GDP, and public debt stock / GDP ratios of Emerging Markets Mix countries in the analysed periods are considered as side effects of macroeconomic performance.
Method: In the study, Multi-Criteria Decision Making Techniques were used to rank the macroeconomic performance by considering the annual and five-year averages of the countries. When the new year is added, the first year of the five-year period is removed. The index was created by weighting the macroeconomic performance indicators with the Analytical Hierarchy Process (AHP), and then the rankings of the countries were determined using the TOPSIS model.
Findings: While the top 18 out of 41 countries are determined as the countries that make up the Emerging Markets Mix since they have relatively better macroeconomic performance, others are considered as candidate countries that can enter this Mix. Since the macroeconomic performance analysis of the model used in the study takes into account the annual and five-year averages of the past five-year indicators, it also points to the direct and indirect results of the preferences and priorities of public authorities in medium-term processes. The changes in the current account deficit, budget deficit and high public debt stock indicators reflect an important feature of the analysis that stands out in this context. The geographical distribution of the selected countries has been designed to include every region of the world and it has been observed that high-performance countries generally cluster in the Asian continent.
Originality: With the approach used in the study, the macroeconomic performance analysis in the literature is considered together with the macroeconomic stability perspective and a different perspective is created by adding the political economy dimension to this approach. Such an approach makes it possible to produce macroeconomic data and information sets that national and global economic stakeholders can use in decision-making and implementation processes. In the subsequent applications of the model, the possible countries of the Emerging Markets Mix in the next year will be determined by using the annual estimates of the indicators as well as the realised data.

Kaynakça

  • Andres, J., Domenech, R., & Molinas, C. (1996). Macroeconomic performance and convergence in OECD countries. European Economic Review, 40(9), 1683-1704.
  • Ardielli, E. (2019). Use of TOPSIS method for assessing of good governance in European Union countries. Review of Economic Perspectives, 3, 2011-231.
  • Azimifard, A., Moosavirad, S. H., & Ariafar, S. (2018). Selecting sustainable supplier countries for Iran's steel industry at three levels by using AHP and TOPSIS methods. Resources Policy, 57, 30-44.
  • Balcerzak, A. P., & Pietrzak, M. B. (2016). Application of TOPSIS Method for Analysis of Sustainable Development in European Union Countries. Institute of Economic Research Working Papers, 22, 82-92.
  • Balioti, V., Tzimopoulos, C., & Evangelides, C. (2018). Multi-criteria decision making using topsis method under fuzzy environment. Application in spillway selection. Multidisciplinary Digital Publishing Institute Proceedings, 2(11), 637-645.
  • Bekaert, G., Erb, C. B., Harvey, C. R., & Viskanta, T. E. (1997). What matters for emerging equity market investments. Emerging markets quarterly, 1(2), 17-46.
  • Brauers, W. K., & Zavadskas, E. K. (2006). The MOORA method and its application to privatization in a transition economy. Control and Cybernetics, 35, 445-469.
  • Cheng, E. W., & Li, H. (2001). Analytic hierarchy process. Measuring Business Excellence, 5(3).
  • Easterly, W., & Schmidt-Hebbel, K. (1993). FISCAL DEFICITS AND MACROECONOMIC PERFORMANCE IN DEVELOPING COUNTRIES. The World Bank Research Observer, 8(2), 211-237.
  • Ekren, N., & Fındıkçı, M. (2016). AHP ve VIKOR yöntemleri ile avrupa birliği’ne üye ülkeler ve türkiye'nin ekonomik performanslarının değerlendirilmesi. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi,, 17(33), 525-536.
  • Ekren, N., Aykaç Alp, E., & Yağmur, M. H. (2017). Macroeconomic performance index: a new approach to calculation of economic wellbeing. Applied Economics, 49(53), 5462–5476.
  • Erdoğan Fındıkçı, M. (2020). Türkiye dâhil seçilmiş yükselen piyasa ekonomileri için makroekonomik performans ölçümü: Mukayeseli bir analiz. (Yayımlanmamış doktora tezi). İstanbul Ticaret Üniversitesi Finans Enstitüsü Finansal Anabilim Dalı, İstanbul.
  • Ewa, L. (2009). Okun`s and Barro`s Misery Index as an alternative poverty assessment tool. Recent estimations for European countries. MPRA, 1-11.
  • Frankel, J. A. (2010). Monetary policy in emerging markets: a survey. National Bureau of Economic Research(No. w16125).
  • Ghura, D., & Grennes, T. J. (1993). The real exchange rate and macroeconomic performance in Sub-Saharan Africa. Journal of Development Economics, 42(1), 155-174.
  • Greenaway, D., & Nam, C. H. (1988). Industrialisation and macroeconomic performance in developing countries under alternative trade strategies. Kyklos, 41(3), 419-435.
  • Husain, A. M., Mody, A., & Rogoff, K. S. (2005). Exchange rate regıme durability and performance in developing versus advanced economies. Journal of Monetary Economics, 52(1), 35-64.
  • IFC. (2020, Nisan 13). Establishing "emerging markets". International Finance Group: https://www.ifc.org/wps/wcm/connect/corp_ext_content/ifc_external_corporate_site/about+ifc_new/ifc+history/establishing-emerging-markets adresinden alındı
  • Kahn, M. E., Mohaddes, K., Ng, R. N., Peseran, M. H., Raissi, M., & Yang, J.-C. (2019). Long-Term Macroeconomic Effects of Climate Change: A Cross-Country Analysis. NBER Working Paper, 1-55.
  • Khramov, V., & Lee, J. R. (2013). The Economic Performance Index (EPI): an intuitive indicator for assessing a country's economic performance dynamics in an historical perspective. IMF.
  • Leal, J. E. (2020). AHP-Express: A Simplified Version of The Analytical Hierarchy Process Method. MethodsX,, 7, 1-11.
  • Marquis, C., & Raynard, M. (2015). Institutional strategies in emerging markets. Academy of Management Annals, 9(1), 291-335.
  • Mateusz, P., Danuta, M., Małgorzata, Ł., Mariusz, B., & Kesra, N. (2018). TOPSIS and VIKOR methods in study of sustainable development in the EU countries. Procedia Computer Science, 126, 1683-1692. Mishkin, F. S. (2009). Globalization, Macroeconomic Performance, and Monetary Policy. Journal of Money, Credit and Banking, 41(1), 187-196.
  • Roszkowska, E. (2011). Multi-criteria decision making models by applying the TOPSIS method to crisp and interval data. Multiple Criteria Decision Making/University of Economics in Katowice,, 6, 200-230.
  • Saaty, T. L. (2001). Fundamentals of the analytic hierarchy process. In The analytic hierarchy process in natural resource and environmental decision making. Springer, 15-35.
  • Saaty, T. L. (2008). The Analytic Hierarchy and Analytic Network Measurement Processes: applications to decisions under risk. European Journal of Pure And Applied Mathematics, 1(1), 83-98.
  • Sokolov, V., Lee, B.-J., & Mark, N. C. (2011). Linkages between exchange rate policy and macroeconomic performance. Pacific Economic Review, 16(4), 395-420.
  • Vavrek, R., & Chovancová, J. (2019). Assessment of economic and environmental energy performance of EU countries using CV-TOPSIS technique. Ecolohical Indicators, 106, -.
  • Wang, C.-N., & Le, A. L. (2018). Measuring the Macroeconomic Performance among Developed Countries and Asian Developing Countries: Past, Present, and Future. Sustainability, 10(3664).
  • Wankhede, S. V., & Hole, J. A. (2020). MOORA and TOPSIS Based Selection of Input Parameter in solar powered absorption refrigeration system. International Journal of Ambient Energy, 1-6. doi:https://doi.org/10.1080/01430750.2020.1831600
  • Yıldırım, Z., & Ivrendi, M. (2016). Exchange rate fluctuations and macroeconomic performance. Journal of Economic Studies.
Toplam 31 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Bölüm Araştırma Makaleleri
Yazarlar

Nazım Ekren 0000-0002-7550-1673

Mefule Fındıkçı Erdoğan 0000-0003-0150-0990

Kübra Hatice Bildik 0000-0002-7243-5084

Yayımlanma Tarihi 25 Haziran 2021
Gönderilme Tarihi 19 Mayıs 2021
Kabul Tarihi 2 Haziran 2021
Yayımlandığı Sayı Yıl 2021 Cilt: 20 Sayı: 40

Kaynak Göster

APA Ekren, N., Fındıkçı Erdoğan, M., & Bildik, K. H. (2021). YÜKSELEN PİYASA EKONOMİLERİ KARMASI: EM2-18 MODELİ UYGULAMASI. İstanbul Ticaret Üniversitesi Sosyal Bilimler Dergisi, 20(40), 632-660. https://doi.org/10.46928/iticusbe.939364