Araştırma Makalesi
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Yıl 2024, Cilt: 16 Sayı: 2, 89 - 106, 14.01.2025

Kerem Sezerer , Burak Arslan

https://doi.org/10.33818/ier.1518663

Öz

Kaynakça

  • Abdoh, W.M.Y.M., N. H. M. Yusuf., S. A. M. Zulkifli, N. Bulot and N. J. Ibrahim ,(2016). Macroeconomic Factors That Influence Exchange Rate Fluctuation In ASEAN Countries. International Academic Research Journal of Social Science, 2 (1), 89-94.
  • Adusei, M. and E.Y. Gyapong (2017). The impact of macroeconomic variables on exchange rate volatility in Ghana: The Partial Least Squares Structural Equation Modelling Approach. Research in International Business and Finance, 42, 1428-1444. Aka, K. (2020). Seçilmiş Makroekonomik Göstergelerin Döviz Kuru Üzerinde Etkisi: Türkiye Ekonomisi Üzerine Bir Uygulama. BDDK Bankacılık ve Finans Piyasalar Dergisi, 14 (1), 99-117. Antwi, S. and M. Issah (2020). The effect of macroeconomic variables on exchange rate: Evidence from Ghan. Cogent Economics & Finance, 8 (1), 1-19. Breitung, J. (2001) The Local Power of Some Unit Root Tests for Panel Data. In: Baltagi, B.H., Ed., Nonstationary Panels, Panel Cointegration, and Dynamic Panels, Emerald Group Publishing Limited, Bingley.
  • Breusch, T.S. and A.R. Pagan (1980) The Lagrange Multiplier Test and Its Application to Model Specification in Econometrics. Review of Economic Studies, 47, 239-253.
  • Carissa, N. and R. Khoirudin (2020). The factors affecting the rupiah exchange rate in Indonesia. Journal Economi Pembangunan, 18 (1), 37-46.
  • Chi-Wei, S. (2012), The relationship between exchange rate and macroeconomic variables in China. Zbornik Radova Ekonomskog Fakulteta u Rijeci, 30(1), 33-56. Dengiz, S. (2022). Enflasyon hedeflemesi döviz kuru ilişkisinin analizi: Seçilmiş OECD ülkeleri üzerine bir uygulama (Unpublished Doctoral Dissertation). Süleyman Demirel University Institute of Social Sciences, Isparta.
  • Eberhardt, M. (2012). Estimating panel time-series models with heterogeneous slopes. The Stata Journal, 12(1),61-71.
  • Eberhardt, M. and S. Bond (2009). Cross-section dependence in nonstationary panel models: A novel estimator (MPRA Paper No.17692).
  • Eberhardt, M. and F. Teal (2010). Productivity analysis in global manufacturing production, Economics Series Working Papers 515, University of Oxford, Department of Economics.
  • Erkan, R. (2024). Yüksek teknoloji ürünü ihracat pazarlarında Türkiye’nin yeri ve bu pazarların gelişimine etki eden faktörler. (Unpublished Doctoral Dissertation). Uludağ University Institute of Social Sciences, Bursa.
  • Eşsiz, E. (2022). Döviz kuru ve enflasyon arasındaki ilişkinin Dinamik Analizi (Unpublished master's thesis). Dicle University Institute of Social Sciences, Diyarbakır. Federal Reserve System. (2014). Statement on longer-run and monetary policy strategy. https://www.federalreserve.gov/monetarypolicy/files/20140211_mprfullreport.pdf (accessed June 17, 2023).
  • Friedman, M. (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. American Statistical Association, 32, 675-701.
  • Frees, E. W. 1995. Assessing cross-sectional correlation in panel data. Journal of Econometrics 69: 393–414.
  • Goldin, K.D. (1966), Economic growth and the individual, The Journal of Finance, 21(3), 550-551.
  • Gür, B .(2022). Enflasyon ve döviz kuru ilişkisi: Türkiye örneği. International Journal of Applied Economic and Finance Studies, 7(2), 153-163. Hacıevliyagil, N. and Y. Demir (2016). Döviz kurunun temel makro ekonomik değişkenlerle ilişkisi: Türkiye ve BRICS ülkeleri karşılaştırması. Finans Politik ve Ekonomik Yorumlar, (615), 41-64. International Monetary Fund. (2023). World economic Outlook 2023 OCT Navigating Global Divergences. https://www.imf.org/external/datamapper/datasets/WEO (accessed August 15, 2023).
  • İşler, D. (2021). Türkiye ve diğer bazı ülkelerdeki makroekonomik değişkenler ve döviz kuru arasındaki ilişki. (Unpublished Doctoral Dissertation). Beykent University Graduate School, Ankara. Jamil M., A. Rasheed ,A. Maqbool and Z. Mukhtar (2023). Cross‑cultural study the macro variables and its impact on exchange rate regimes. Future Business Journal, 9 (9), 1-14. Kaboro, J. and N. Mose (2021). The impact of macroeconomic variables on Exchange rate uncertain. Financial Internet Quarterly, Sciendo, Warsaw, 17 (3), 47-55. Kamer, Ainur A. and Condrea E. (2012). Some empirical evidence about the effects macroeconomic variables on the exchange rate in Romania. Transformati in Business and Economics, 11 (2), 435-450. Kaplan, F. and S. Yapraklı (2014). Ekonomik kırılganlık endeksi göstergelerinin döviz kuru üzerindeki etkileri: Kırılgan 12 ülke üzerine panel veri analizi. Uluslararası Alanya İşletme Fakültesi Dergisi, 6 (3), 111-121.
  • Khan, M. K., J. Teng and M. I. Khan (2019). Cointegration between macroeconomic factors and the exchange rate USD/CNY. Financial Innovation, 5 (5), 1-15.
  • Kubar, Y. and H. Çoban (2021). Makroekonomik değişkenlerin döviz kuru değişmelerine etkisi: Bir panel veri analizi. Finansal Araştırmalar ve Çalışmalar Dergisi, 13 (24), 189-206. Kuncoro, H. and F. Fafurida (2023). Current account imbalances and exchange rate volatility: Empirical evidence from Indonesia. Ekonomski Horizonti; Kragujevac, 25 (1), 17-30.
  • Makhdom, A.M. (2020). Makroekonomik göstergeler ile döviz kuru arasındaki ilişkinin analizi: (2005:01-2019:10) Türkiye uygulaması (Unpublished master's thesis). Hacı Bayram Veli University, Institute of Social Sciences, Ankara. Mariano,C., V. Sablan, J. R. Sardon and R. Mae (2015). Investigation of the factors affecting real exchange rate in the Philippines. Review Of Integrative Business And Economics Research, 5 (4), 171-202. Muhammad, T. and J. Khan (2012). Factors affecting the nominal exchange rate of Pakistan: An econometric investigation. Asian Economic and Financial Review. 2 (2), 421-428. Nucu, E. A. (2011). The relationship between exchange rate and key macroeconomic indicators. Case study: Romania. The Romanian Economic Journal, 14 (41), 127-145.
  • Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. IZA Discussion Paper, (1240), 1-39.
  • Pesaran, M. H. (2006). Estimation and inference in large heterogenous panels with multifactor error structure. Econometrica, 74, 967-1012.
  • Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93.
  • Pastore, A.C., M.C. Pinotti and L.P. Almeida (2004). Public debt, exchange rate shocks and inflation targets. Revista de Economia Contemporânea, 13 (3), 1-37.
  • Sadıç, E. (2019). Ekonomik kırılganlık endeksi göstergelerinin döviz kuru üzerindeki etkisi: Gelişmekte olan ülkeler üzerine bir uygulama (Unpublished master's thesis). Dokuz Eylül University, Institute of Social Sciences, İzmir.
  • Su, Ö. (2015). Türkiye’de döviz kurunu etkileyen faktörlerin parasalcı yaklaşımla analizi (1980-2010) (Unpublished master's thesis). Kocaeli University, Institute of Social Sciences, Kocaeli. Şit, M. and H. Karadağ (2019). Döviz Kurunu Belirleyen Ekonomik Faktörler: Türkiye Ekonomisi için ARDL Sınır Testi Uygulaması. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 23, 51-168.

A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES

Yıl 2024, Cilt: 16 Sayı: 2, 89 - 106, 14.01.2025

Kerem Sezerer , Burak Arslan

https://doi.org/10.33818/ier.1518663

Öz

The volatility of exchange rates is considered to be an important measure of a country's economic vulnerability and has a direct or indirect causal relationship with a large number of macroeconomic variables. The aim of this study is to analyze the macroeconomic variables in the economic vulnerability index that affect the exchange rate for developing countries and the extent to which they affect the exchange rate, and to make policy recommendations. We conducted a panel data analysis using data from 11 developing countries between 2000 and 2022 for this purpose. We performed the analyses using the Augmented Mean Group (AMG) estimator. As a result of the analyses, it is found that there is a negative and statistically significant relationship between the real effective exchange rate and inflation, private sector credit debt/GDP and gross public debt/GDP ratio. In addition, the relationship between Real effective exchange rate and current account deficit/GDP ratio, External debt/GDP ratio and growth rate is positive and statistically insignificant. As a policy recommendation, it can be said that for stable and sustainable economic management in developing countries, the exchange rate level should be less volatile and should be compatible with reliable fiscal and monetary policies.

Anahtar Kelimeler

Augmented Mean Group (AMG) Estimator Real Effective Exchange Rate Developing Countries Panel Data Analysis Macroeconomic Indicators

Kaynakça

  • Abdoh, W.M.Y.M., N. H. M. Yusuf., S. A. M. Zulkifli, N. Bulot and N. J. Ibrahim ,(2016). Macroeconomic Factors That Influence Exchange Rate Fluctuation In ASEAN Countries. International Academic Research Journal of Social Science, 2 (1), 89-94.
  • Adusei, M. and E.Y. Gyapong (2017). The impact of macroeconomic variables on exchange rate volatility in Ghana: The Partial Least Squares Structural Equation Modelling Approach. Research in International Business and Finance, 42, 1428-1444. Aka, K. (2020). Seçilmiş Makroekonomik Göstergelerin Döviz Kuru Üzerinde Etkisi: Türkiye Ekonomisi Üzerine Bir Uygulama. BDDK Bankacılık ve Finans Piyasalar Dergisi, 14 (1), 99-117. Antwi, S. and M. Issah (2020). The effect of macroeconomic variables on exchange rate: Evidence from Ghan. Cogent Economics & Finance, 8 (1), 1-19. Breitung, J. (2001) The Local Power of Some Unit Root Tests for Panel Data. In: Baltagi, B.H., Ed., Nonstationary Panels, Panel Cointegration, and Dynamic Panels, Emerald Group Publishing Limited, Bingley.
  • Breusch, T.S. and A.R. Pagan (1980) The Lagrange Multiplier Test and Its Application to Model Specification in Econometrics. Review of Economic Studies, 47, 239-253.
  • Carissa, N. and R. Khoirudin (2020). The factors affecting the rupiah exchange rate in Indonesia. Journal Economi Pembangunan, 18 (1), 37-46.
  • Chi-Wei, S. (2012), The relationship between exchange rate and macroeconomic variables in China. Zbornik Radova Ekonomskog Fakulteta u Rijeci, 30(1), 33-56. Dengiz, S. (2022). Enflasyon hedeflemesi döviz kuru ilişkisinin analizi: Seçilmiş OECD ülkeleri üzerine bir uygulama (Unpublished Doctoral Dissertation). Süleyman Demirel University Institute of Social Sciences, Isparta.
  • Eberhardt, M. (2012). Estimating panel time-series models with heterogeneous slopes. The Stata Journal, 12(1),61-71.
  • Eberhardt, M. and S. Bond (2009). Cross-section dependence in nonstationary panel models: A novel estimator (MPRA Paper No.17692).
  • Eberhardt, M. and F. Teal (2010). Productivity analysis in global manufacturing production, Economics Series Working Papers 515, University of Oxford, Department of Economics.
  • Erkan, R. (2024). Yüksek teknoloji ürünü ihracat pazarlarında Türkiye’nin yeri ve bu pazarların gelişimine etki eden faktörler. (Unpublished Doctoral Dissertation). Uludağ University Institute of Social Sciences, Bursa.
  • Eşsiz, E. (2022). Döviz kuru ve enflasyon arasındaki ilişkinin Dinamik Analizi (Unpublished master's thesis). Dicle University Institute of Social Sciences, Diyarbakır. Federal Reserve System. (2014). Statement on longer-run and monetary policy strategy. https://www.federalreserve.gov/monetarypolicy/files/20140211_mprfullreport.pdf (accessed June 17, 2023).
  • Friedman, M. (1937) The use of ranks to avoid the assumption of normality implicit in the analysis of variance. American Statistical Association, 32, 675-701.
  • Frees, E. W. 1995. Assessing cross-sectional correlation in panel data. Journal of Econometrics 69: 393–414.
  • Goldin, K.D. (1966), Economic growth and the individual, The Journal of Finance, 21(3), 550-551.
  • Gür, B .(2022). Enflasyon ve döviz kuru ilişkisi: Türkiye örneği. International Journal of Applied Economic and Finance Studies, 7(2), 153-163. Hacıevliyagil, N. and Y. Demir (2016). Döviz kurunun temel makro ekonomik değişkenlerle ilişkisi: Türkiye ve BRICS ülkeleri karşılaştırması. Finans Politik ve Ekonomik Yorumlar, (615), 41-64. International Monetary Fund. (2023). World economic Outlook 2023 OCT Navigating Global Divergences. https://www.imf.org/external/datamapper/datasets/WEO (accessed August 15, 2023).
  • İşler, D. (2021). Türkiye ve diğer bazı ülkelerdeki makroekonomik değişkenler ve döviz kuru arasındaki ilişki. (Unpublished Doctoral Dissertation). Beykent University Graduate School, Ankara. Jamil M., A. Rasheed ,A. Maqbool and Z. Mukhtar (2023). Cross‑cultural study the macro variables and its impact on exchange rate regimes. Future Business Journal, 9 (9), 1-14. Kaboro, J. and N. Mose (2021). The impact of macroeconomic variables on Exchange rate uncertain. Financial Internet Quarterly, Sciendo, Warsaw, 17 (3), 47-55. Kamer, Ainur A. and Condrea E. (2012). Some empirical evidence about the effects macroeconomic variables on the exchange rate in Romania. Transformati in Business and Economics, 11 (2), 435-450. Kaplan, F. and S. Yapraklı (2014). Ekonomik kırılganlık endeksi göstergelerinin döviz kuru üzerindeki etkileri: Kırılgan 12 ülke üzerine panel veri analizi. Uluslararası Alanya İşletme Fakültesi Dergisi, 6 (3), 111-121.
  • Khan, M. K., J. Teng and M. I. Khan (2019). Cointegration between macroeconomic factors and the exchange rate USD/CNY. Financial Innovation, 5 (5), 1-15.
  • Kubar, Y. and H. Çoban (2021). Makroekonomik değişkenlerin döviz kuru değişmelerine etkisi: Bir panel veri analizi. Finansal Araştırmalar ve Çalışmalar Dergisi, 13 (24), 189-206. Kuncoro, H. and F. Fafurida (2023). Current account imbalances and exchange rate volatility: Empirical evidence from Indonesia. Ekonomski Horizonti; Kragujevac, 25 (1), 17-30.
  • Makhdom, A.M. (2020). Makroekonomik göstergeler ile döviz kuru arasındaki ilişkinin analizi: (2005:01-2019:10) Türkiye uygulaması (Unpublished master's thesis). Hacı Bayram Veli University, Institute of Social Sciences, Ankara. Mariano,C., V. Sablan, J. R. Sardon and R. Mae (2015). Investigation of the factors affecting real exchange rate in the Philippines. Review Of Integrative Business And Economics Research, 5 (4), 171-202. Muhammad, T. and J. Khan (2012). Factors affecting the nominal exchange rate of Pakistan: An econometric investigation. Asian Economic and Financial Review. 2 (2), 421-428. Nucu, E. A. (2011). The relationship between exchange rate and key macroeconomic indicators. Case study: Romania. The Romanian Economic Journal, 14 (41), 127-145.
  • Pesaran, M. H. (2004). General Diagnostic Tests for Cross Section Dependence in Panels. IZA Discussion Paper, (1240), 1-39.
  • Pesaran, M. H. (2006). Estimation and inference in large heterogenous panels with multifactor error structure. Econometrica, 74, 967-1012.
  • Pesaran, M. H., & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93.
  • Pastore, A.C., M.C. Pinotti and L.P. Almeida (2004). Public debt, exchange rate shocks and inflation targets. Revista de Economia Contemporânea, 13 (3), 1-37.
  • Sadıç, E. (2019). Ekonomik kırılganlık endeksi göstergelerinin döviz kuru üzerindeki etkisi: Gelişmekte olan ülkeler üzerine bir uygulama (Unpublished master's thesis). Dokuz Eylül University, Institute of Social Sciences, İzmir.
  • Su, Ö. (2015). Türkiye’de döviz kurunu etkileyen faktörlerin parasalcı yaklaşımla analizi (1980-2010) (Unpublished master's thesis). Kocaeli University, Institute of Social Sciences, Kocaeli. Şit, M. and H. Karadağ (2019). Döviz Kurunu Belirleyen Ekonomik Faktörler: Türkiye Ekonomisi için ARDL Sınır Testi Uygulaması. Uluslararası İktisadi ve İdari İncelemeler Dergisi, 23, 51-168.
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Panel Veri Analizi
Bölüm Makaleler
Yazarlar

Kerem Sezerer 0009-0009-0705-841X

Burak Arslan 0000-0002-1465-1870

Yayımlanma Tarihi 14 Ocak 2025
Gönderilme Tarihi 18 Temmuz 2024
Kabul Tarihi 11 Aralık 2024
Yayımlandığı Sayı Yıl 2024 Cilt: 16 Sayı: 2

Kaynak Göster

APA Sezerer, K., & Arslan, B. (2025). A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES. International Econometric Review, 16(2), 89-106. https://doi.org/10.33818/ier.1518663
AMA Sezerer K, Arslan B. A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES. IER. Ocak 2025;16(2):89-106. doi:10.33818/ier.1518663
Chicago Sezerer, Kerem, ve Burak Arslan. “A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES”. International Econometric Review 16, sy. 2 (Ocak 2025): 89-106. https://doi.org/10.33818/ier.1518663.
EndNote Sezerer K, Arslan B (01 Ocak 2025) A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES. International Econometric Review 16 2 89–106.
IEEE K. Sezerer ve B. Arslan, “A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES”, IER, c. 16, sy. 2, ss. 89–106, 2025, doi: 10.33818/ier.1518663.
ISNAD Sezerer, Kerem - Arslan, Burak. “A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES”. International Econometric Review 16/2 (Ocak 2025), 89-106. https://doi.org/10.33818/ier.1518663.
JAMA Sezerer K, Arslan B. A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES. IER. 2025;16:89–106.
MLA Sezerer, Kerem ve Burak Arslan. “A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES”. International Econometric Review, c. 16, sy. 2, 2025, ss. 89-106, doi:10.33818/ier.1518663.
Vancouver Sezerer K, Arslan B. A PANEL DATA ANALYSIS OF EFFECTS OF ECONOMIC VULNERABILITY INDEX INDICATORS ON REAL EFFECTIVE EXCHANGE RATE IN DEVELOPING COUNTRIES. IER. 2025;16(2):89-106.