FİNANSAL KOŞULLAR ENDEKSİNİN EKONOMİK BÜYÜMEYE ETKİSİ: BRICS-T ÖRNEĞİ

Finansal koşullar endeksi, bir dizi finansal serinin temel bileşeni olarak kullanılan referans endekstir. İş döngüsündeki dalgalanmaları göz önünde tutarak geleneksel makroekonomik modellere yol göstermeyi amaçlamaktadır. Bu kapsamda çalışmada, BRICS-T ülkelerinde finansal koşullar endeksini temsilen, gecelik faiz, hisse senedi ve reel efektif döviz kurunun ekonomik büyümeye etkisi 1999:M1-2020:M2 döneminde incelenmiştir. Çalışmada yatay kesit bağımlılığını baz alan panel veri analiz yöntemi kullanılmıştır. Elde edilen uzun dönem analiz sonuçlarına göre, BRICS-T ülkelerinde gecelik faiz ve hisse senedindeki %10’luk artış, ekonomik büyümeyi sırasıyla %0.4 ve %0.1 oranında azaltmaktadır. Başka bir deyişle BRICS-T ülkelerinde finansal koşulların ekonomik büyüme üzerindeki etkisi negatiftir.

Anahtar Kelimeler:

Finansal Koşullar Endeksi, Ekonomik Büyüme, BRICS-T Ülkeleri, Yatay Kesit Bağımlılığı

THE EFFECT OF FINANCIAL CONDITIONS INDEX ON ECONOMIC GROWTH: THE CASE OF BRICS-T

The financial conditions index is the reference index used as a key component of a series of financial series. It aims to guide traditional macroeconomic models by taking into account the fluctuations in the business cycle.In this context, the effect of overnight interest, stock and real effective exchange rate on economic growth in the period of 1999:M1-2020:M2, representing the financial conditions index in BRICS-T countries, was examined. In the study was used panel data analysis method which takes into account cross-section dependence. According to the long-term analysis results obtained in BRICS-T countries, an increase of 10% in overnight interest and stocks reduces the economic growth by 0.4% and 0.1%, respectively. In other words, the effect of financial conditions on economic growth in BRICS-T countries is negative.

Keywords:

Financial Conditions Index Economic Growth, BRICS-T Countries, Cross-Section Dependence, Panel AMG,

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Akdeniz, C. & Çatık, A. N. (2017). Türkiye için finansal koşulların bir analizi: Faktör ve VAR modellerinden bulgular. Eskişehir Osmangazi Üniversitesi İİBF Dergisi, 12(1), 99-120.
Arrigoni, S., Beck, R., Ca' Zorzi, M. & Stracca, L. (2020). Globalisation: What’s at stake for Central Banks. Erişim Tarihi: 15.09.2020, https://voxeu.org/article/globalisation-what-s-stake-central-banks.
Balcilar,M., Thompsonb, K., Guptab,R. & Eydenb, R. (2016). Testing the asymmetric effects of financial conditions in South Africa: A nonlinear vector autoregression approach, Journal of International Financial Markets Institutions and Money, Erişim Tarihi: 15.09.2020.
Brave, S. & Butters, R. A. (2011). Monitoring financial stability: a financial conditions index approach. Federal Reserve Bank of Chicago Economic Perspectives, 2011, 22-43.
Bond, S. R., & Eberhardt, M. (2013). Accounting for unobserved heterogeneity in panel time series models. Nuffield College, University of Oxford, mimeo.
Breusch, T. S. & Pagan, A. R. (1980). The Lagrange Multiplier test and its applications to model specification tests in econometrics. Review of Economic Studies, 47(1), 239-253.
Charleroy, R. & Stemmer, M. A. (2014). An emerging market financial conditions index: A VAR approach. Documents de travail du Centre d'Economie de la Sorbonne 14068, 1-27.
Choi, In (1993). Asymptotic normality of the least-squares estimates for higher order autoregressive integrated processes with some applications. Econometric Theory, 9(2), 263-282.
Davis, E. P, Kirby, S. & Warren, J. (2016). The estimation of financial conditions indices for the major OECD countries. OECD Economics Department Working Papers, 1335, 1-30.
Dempster, A. P., Laird, N. M. & Rubin, D. B. (1977). Maximum likelihood from incomplete data via the EM algorithm. Wiley for the Royal Statistical Society, 39(1), 1-38.
Doz, C., Giannone, D. & Reichlin, L. (2006). A quasi maximum likelihood approach for large approximate dynamic factor models. European Central Bank Working Paper, 674, 1-38.
Dumičić, M. & Krznar, I. (2013). Financial conditions and economic activity. Croation National Bank, 37, 1-14.
Eberhardt, M. & Bond, S. (2009). Cross-section dependence in nonstationary panel models: A novel estimator. Munich Personal RePEc Archive Paper, No: 17692.
Ejem, C. & Ogbonna, U. G. (2020). Financial conditions index and economic performance in Nigeria. American Finance & Banking Review, 5(1), 62-70.
FRED- Federal Reserve Economic Data (2020). Erişim Tarihi: 20.09.2020, https://fred.stlouisfed.org/categories/18.
Gauthier, C., Graham, C. & Liu, Y. (2004). Financial conditions indexes for Canada. Bank of Canada Working Paper, 22, 1-37.
Guichard, S., Haugh, D. & Turner, D. (2009). Quantifying the effect of financial conditions in the Euro Area, Japan, United Kingdom and United States. Economics Department Working Papers, 677, 1-35.
Guihuana, Z. & Yu, W. (2014). Financial conditions index’s construction and its application on financial monitoring and economic forecasting. Procedia Computer Science, 31 (2014), 32-39.
Gumata, N., Klein, N. & Ndou, E. (2012). A financial conditions index for South Africa. IMF Working Paper, 196, 1-19.
Güloğlu, B. & İvrendi, M. (2010). Output fluctuations: Transitory or permanent?. The case of Latin America. Applied Economics Letters, 17(4), 381-386.
Hadri, K. & Kurozumi, E. (2012). A simple panel stationarity test in the presence of serial correlation and a common factor. Economics Letters, 115(1), 31-34.
Hatzius, J., Hooper, P., Mishkin, F., Schoenholtz, K. L. &Watson, M. W. (2010). Financial conditions indexes: A fresh look after the financial crisis. University of Chicago Booth School of Business, Initiative on Global Markets, Erişim Tarihi: 15.09.2020, http://research.chicagobooth.edu/igm/events/ docs/2010usmpfreport.pdf.
Ho, G. & Lu, Y. (2013). A financial conditions index for Poland. IMF Working Paper, 252, 1-14.
Jolliffe, I. T. (2002). Principal component analysis (2. Baskı). New York: Springer.
Kapetanios, G., Price, S. & Young, G. (2018). A UK financial conditions index using targeted data reduction: Forecasting and structural identification. Bank of England Working Paper, 699,1-32.
Kara, H., Özlü, P. & Ünalmış, D. (2015). Türkiye için finansal koşullar endeksi. TCMB Çalışma Tebliği, 13, 1-31.
Kaya, E. & Barut, A. (2020). Finansal koşulların değerlendirilmesi: Türkiye için endeks bazlı bir çalışma. Maliye Dergisi, 177, 121-144.
Kim, H. S. & Sanchez, M. J. (2017). Financial conditions: Do the ups and downs affect the rest of the economy?. Federal Reserve Bank of St. Louis, 8-12.
Koop, G. & Korobilis, D. (2014). A new index of financial conditions. European Economic Review, 71, 101-116.
Kurt, S., Sezgin, F. & Sart, G. (2018). G7 ülkelerinde patent üretimini etkileyen değişkenler için panel veri analizi, Yönetim Bilimleri Dergisi, 16(32), 285-298.
Menyah, K., Nazlıoğlu, Ş. & Wolde-Rufael, Y. (2014). Financial development, trade openness and economic growth in African countries: New insights from a panel causality approach. Economic Modelling, 37, 386-394.
Pesaran, M. H. (2004). General diagnostic tests for cross section dependence in panels. Cambridge Working Papers in Economics, 435, 1-39.
Pesaran, M. H. & Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142(1), 50-93.
Pesaran, M. H., Ullah, A. & Yamagata, T. (2008). A bias-adjusted Lm test of error cross-section independence. Econometrics Journal, 11(1), 105-127.
Sahoo, M. (2017). Financial conditions index (fci), inflation and growth: Some evidence. Theoretical and Applied Economics, 3(612), 147-172.
Shumway, R. H. & Stoffer, D. S. (1982). An approach to time series smoothing and forecasting using the EM algorithm. Journal of Time Series Analysis, 3(4), 253-264.
Sul, D., Phillips, P. C. B. & Choi, C. Y. (2005). Prewhitening bias in HAC estimation. Oxford Bulletin of Economics and Statistics, 67(4), 517-546.
Stock, J. H. & Watson, M. W. (2002). Forecasting using principal components from a large number of predictors, Journal of the American Statistical Association, 97(460), 1167-1179.
Swamy, P. A. V. B. (1970). Efficient inference in a random coefficient regression model, Econometrica. 38(2), 311-323.
Switson, A. (2008). Financial conditions index: Putting credit where credit is due prepared. IMF Working Paper, 161, 1-31.
Toda, H. Y. & Yamamoto, T. (1995). Statistical inference in vector autoregressions with possibly integrated Processes. Journal of Econometrics, 66(1-2), 225-250.
Westerlund, J. (2008). Panel cointegration tests of the fisher effect. Journal of Applied Econometrics, 23, 193‐233.