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Türkiye’de İçsel Büyüme Modeline Kademeli Bir Bakış: Kantil Regresyon Yaklaşımı

Yıl 2021, Cilt 6, Sayı IERFM Özel Sayısı, 225 - 246, 30.12.2021
https://doi.org/10.30784/epfad.1024719

Öz

Bu çalışmada, Türkiye ekonomisinin dinamiklerinin 1990-2020 dönemleri arasında izlenmesine olanak sağlayacak bir içsel büyüme modeli tahminlemek ve kademesel yapıyı ortaya çıkarmak amaçlanmaktadır. Araştırmaya kapsamındaki makroekonomik göstergelerin doğrusallık davranışları Harvey, Leybourne ve Xiao (2008) testiyle; durağanlık yapıları ise ADF (1979, 1981), Lee ve Strazicich (2004) ve Hepsağ (2019) birim kök testleri ve KPSS (1992) durağanlık testi aracılığıyla ayrıntılı bir şekilde araştırılmıştır. Tahminlenen makroekonometrik modelin teorik problemlerinin üstesinden gelmek amacıyla ilk aşamada RALS tekniğine başvurulmuştur. Bu modelden sağlanan bütünsel çıkarımlar Ar-Ge harcamaları ve ihracat hacminin Kişi Başı GSYİH üzerinde arttırıcı etkisi olduğu yönündedir. Daha ayrıntılı ve kademeli bir bakış için ise kantil regresyon yaklaşımından faydalanılmış ve böylelikle içsel büyüme değişkenlerinin, Kişi Başı GSYİH’nin farklı kantilleri üzerindeki etkisini gözlemlemeye olanak sağlanmıştır. Bulgular, Ar-Ge harcamalarının, düşük kantillerde Kişi Başı GSYİH değerleri üzerindeki etkisinin giderek arttığını ancak yüksek kantiller üzerinde istatistiki bir anlamlılığı olmadığını göstermektedir. İhracat hacminin ise Ar-Ge ile tam tersi bir etki alanı olduğu, Kişi Başı GSYİH’nin düşük kantilleri üzerinde istatistiki bir anlamlılığı bulunmazken yüksek kantiller üzerinde arttırıcı bir etkisi olduğu kaydedilmiştir. Böylelikle Ar-Ge harcamalarının, Kişi Başı GSYİH’ye ivme kazandırması beklenirken yüksek kantillere geçişte hızlandırma etkisini ihracat yüklenmektedir. Ampirik bulgular Ar-Ge'ye dayalı içsel büyüme ve ihracattan beslenen büyüme teorisinin geçerliliğine ilişkin kanıtlar sunmaktadır.

Kaynakça

  • Aghion, P. and Howitt, P. (1992). A Model of Growth Through Creative Destruction. Econometrica, 60(2), 323-351. doi:10.3386/w3223
  • Altin, O. and Kaya, A. A. (2009). Turkiye’de Ar-Ge Harcamalari ve Ekonomik Buyume Arasindaki Nedensel Iliskinin Analizi. Ege Academic Review, 9(1), 251-259. Retrieved from https://dergipark.org.tr/
  • Dickey, D. A. and Fuller W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association, 74(366), 427-431. https://doi.org/10.1080/01621459.1979.10482531
  • Dickey, D. A. and Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49, 1057-1072. https://doi.org/10.2307/1912517
  • Genç, M. C. ve Atasoy, Y. (2010). Ar-Ge Harcamaları ve Ekonomik Büyüme İlişkisi: Panel Veri Analizi. Bilgi Ekonomisi ve Yönetimi Dergisi, 5(2), 27-34. Retrieved from https://dergipark.org.tr/
  • Gittleman, M. and Wolff, E. N. (1995). R&D Activity and Cross-country Growth Comparisons. Cambridge Journal of Economics, 19, 189-189. https://doi.org/10.1093/oxfordjournals.cje.a035303
  • Göçer, İ. (2013). Ar-Ge Harcamalarının Yüksek Teknolojili Ürün İhracatı, Dış Ticaret Dengesi ve Ekonomik Büyüme Üzerindeki Etkileri. Maliye Dergisi, 165(2), 215-240. Retrieved from https://www.researchgate.net/
  • Granger, C. W. J. and Newbold, P. (1974). Spurious Regressions in Econometrics. Journal of Econometrics, 2(2), 111-120. https://doi.org/10.1016/0304-4076(74)90034-7
  • Grossman, G. M. and Helpman, E. (1990). Trade, Innovation, and Growth. The American Economic Review, 80(2), 86-91. Retrieved from https://www.jstor.org/
  • Grossman, G. M. and Helpman, E. (1994). Endogenous Innovation in the Theory of Growth. Journal of Economic Perspectives, 8(1), 23-44. doi:10.1257/jep.8.1.23
  • Grossman, G. M. and Helpman, E. (1991). Innovation and Growth in the Global Economy. London: The MIT Press.
  • Gülmez, A. ve Yardımcıoğlu, F. (2012). OECD Ülkelerinde Ar-Ge Harcamaları ve Ekonomik Büyüme İlişkisi: Panel Eşbütünleşme ve Panel Nedensellik Analizi (1990-2010). Maliye Dergisi, 163(1), 335-353. Retrieved from https://www.researchgate.net/
  • Harvey, D. I., Leybourne, S. J. and Xiao, B. (2008). A Powerful Test for Linearity When the Order of Integration is Unknown. Studies Nonlinear Dynamics and Econometrics, 12(3), (article 2), https://doi.org/10.2202/1558-3708.1582.
  • Hepsağ, A. (2019). A Unit Root Test Based on Smooth Transition and Nonlinear Adjustment. Communications in Statistics-Simulation and Computation, 50(3), 625-632. https://doi.org/10.1080/03610918.2018.1563154
  • Howitt, P. and Aghion, P. (1998). Capital Accumulation and Innovation as Complementary Factors in Long-Run Growth. Journal of Economic Growth, 3(2), 111-130. https://doi.org/10.1023/A:1009769717601
  • Im, K. and Schmidt, P. (2008). More Efficient Estimation under Non-normality When Higher Moments Do Not Depend on the Regressors, Using Residual-augmented Least Squares. Journal of Econometrics, 144, 219–233. https://doi.org/10.1016/j.jeconom.2008.01.003
  • Khraief, N., Shahbaz, M., Heshmati, A. and Azam, M. (2020). Are Unemployment Rates in OECD Countries Stationary ? Evidence from Univariate and Panel Unit Root Tests. The North American Journal of Economics and Finance, 51, 1-15. https://doi.org/10.1016/j.najef.2018.08.021
  • Kruse, R. 2011. A New Unit Root Test Against ESTAR Based on a Class of Modified Statistics. Statistical Papers, 52(1), 71–85. https://doi.org/10.1007/s00362-009-0204-1
  • Koenker, R. and Basset, G. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. Retrieved from https://www.jstor.org/
  • Koenker, R. (2005). Quantile Regression, USA: Cambridge University Press.
  • Kwiatkowski, D., Phillips, P.C. B., Schmidt, P. and Shin, Y. (1992). Testing The Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That The Economic Time Series Have a Unit Root?. Journal of Econometrics, 54, 159-178. https://doi.org/10.1016/0304-4076(92)90104-Y
  • Lee, J. and M. C. Strazicich. (2003). Minimum Lagrange multiplier unit root test with two structural breaks. Review of Economics and Statistics 85(4), 1082–1089. Retrieved from https://www.jstor.org/
  • Lee, J. and M. C. Strazicich. (2004). Minimum LM Unit Root Test with One Structural Break. (Department of Economics Appalachian State University Working Paper No. 04-17). Retrieved from https://www.researchgate.net/
  • Lichtenberg, F. R. (1992). R&D Investment and International Productivity Differences (NBRE Working Paper No. w4161). Retrieved from https://www.nber.org/papers/w4161.
  • Özel, H. A. (2012). Ekonomik Büyümenin Teorik Temelleri. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 2(1), 63-72. Retrieved from https://dergipark.org.tr/
  • Perron, P. (1989). The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis. Econometrica, 57(6), 1361-1401. Retrieved from https://www.jstor.org/
  • Phillips, P.C. B ve Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2), 335-346. https://doi.org/10.1093/biomet/75.2.335
  • Romer, P. M. (1986). Increasing Returns and Long-Run Growth. Journal of Political Economy, 94(5), 1002-1037. Retrieved from https://www.jstor.org/
  • Romer, P. M. (1990). Endogenous Technological Change. Journal of Political Economy, 98(5, Part 2), 71-102. Retrieved from https://www.jstor.org/
  • Schlitzer, G. (1995). Testing Stationarity of Economic Time Series: Further Monte Carlo Evidence. Ricerche Economiche, 2, 125–144. https://doi.org/10.1016/0035-5054(95)90019-5
  • Seyidoğlu, H. (2006). İktisat Biliminin Temelleri. İstanbul: Güzem Can Yayınları No:21.
  • Türedi, S. (2013). Bilgi ve İletişim Teknolojilerinin Ekonomik Büyümeye Etkisi: Gelişmiş ve Gelişmekte Olan Ülkeler İçin Panel Veri Analizi. Gümüshane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 4(7), 299-322. Retrieved from https://app.trdizin.gov.tr/
  • Yanyun, Z. and Mingqian, Z. (2004 July). R&D and Economic Growth-Panel Data Analysis in ASEAN+ 3 Countries. Paper presented at the Korea and the World Economy III. Seoul Conference, Korea.
  • Yeldan, E. (2002, Yaz). Neoliberal Küreselleşme İdeolojisinin Kalkınma Söylemi Üzerine Değerlendirmeler. Praksis,7, 19-34. Retrieved from https://www.praksis.org/
  • Yıldırım, S. (2009). Aghion-Howitt Büyüme Modeli Çerçevesinde Ekonomik Özgürlük ve Ekonomik Büyüme Arasındaki İlişkinin Panel Veri Analizi. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, (25), 259-268. Retrieved from https://app.trdizin.gov.tr/
  • Zivot, E. and Andrews, D. W. K. (1992). Further Evidence on the Great Crash, the Oil Price Shock, and the Unit-Root Hypothesis. Journal of Business & Economic Statistics, 10(3), 251-270. https://doi.org/10.1198/073500102753410372

A Gradual View of the Endogenous Growth Model in Turkey: The Quantile Regression Approach

Yıl 2021, Cilt 6, Sayı IERFM Özel Sayısı, 225 - 246, 30.12.2021
https://doi.org/10.30784/epfad.1024719

Öz

This study aims to estimate an endogenous growth model that will allow the dynamics of the Turkish economy to be followed in the 1990-2020 period and to reveal the gradual structure of this model. The linearity behavior of the macroeconomic indicators, which are the subject of the research, was determined by the Harvey, Leybourne and Xiao (2008) test; stationarity structures were investigated in detail through ADF (1979, 1981), Lee and Strazicich (2004) and Hepsağ (2019) unit root tests and KPSS (1992) stationarity test. In order to deal with the theoretical problem of the estimated macroeconometric model, the residual augmented least squares (RALS) technique was applied in the first step. The overall inferences from this model are that R&D expenditures and export volume have an increasing effect on GDP per capita. For a more detailed and graduated view, the quantile regression technique was used and it was possible to observe the effect of endogenous growth variables on different quantiles of GDP per capita. Findings show that the effect of R&D expenditures on GDP per capita values in lower quartiles is increasing, but it is not statistically significant in the upper quartiles. It has been noted that the export volume has the opposite effect with R&D, and while there is no statistical significance on lower quartiles of GDP per capita, it has an increasing effect in the upper quartiles. Thus, while R&D expenditures are expected to accelerate the GDP per capita, exports are burdened with the acceleration effect in the transition to upper quartiles. Empirical findings provide evidence for the validity of R&D based endogenous growth and export supported growth theory.

Kaynakça

  • Aghion, P. and Howitt, P. (1992). A Model of Growth Through Creative Destruction. Econometrica, 60(2), 323-351. doi:10.3386/w3223
  • Altin, O. and Kaya, A. A. (2009). Turkiye’de Ar-Ge Harcamalari ve Ekonomik Buyume Arasindaki Nedensel Iliskinin Analizi. Ege Academic Review, 9(1), 251-259. Retrieved from https://dergipark.org.tr/
  • Dickey, D. A. and Fuller W. A. (1979). Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association, 74(366), 427-431. https://doi.org/10.1080/01621459.1979.10482531
  • Dickey, D. A. and Fuller, W. A. (1981). Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root. Econometrica, 49, 1057-1072. https://doi.org/10.2307/1912517
  • Genç, M. C. ve Atasoy, Y. (2010). Ar-Ge Harcamaları ve Ekonomik Büyüme İlişkisi: Panel Veri Analizi. Bilgi Ekonomisi ve Yönetimi Dergisi, 5(2), 27-34. Retrieved from https://dergipark.org.tr/
  • Gittleman, M. and Wolff, E. N. (1995). R&D Activity and Cross-country Growth Comparisons. Cambridge Journal of Economics, 19, 189-189. https://doi.org/10.1093/oxfordjournals.cje.a035303
  • Göçer, İ. (2013). Ar-Ge Harcamalarının Yüksek Teknolojili Ürün İhracatı, Dış Ticaret Dengesi ve Ekonomik Büyüme Üzerindeki Etkileri. Maliye Dergisi, 165(2), 215-240. Retrieved from https://www.researchgate.net/
  • Granger, C. W. J. and Newbold, P. (1974). Spurious Regressions in Econometrics. Journal of Econometrics, 2(2), 111-120. https://doi.org/10.1016/0304-4076(74)90034-7
  • Grossman, G. M. and Helpman, E. (1990). Trade, Innovation, and Growth. The American Economic Review, 80(2), 86-91. Retrieved from https://www.jstor.org/
  • Grossman, G. M. and Helpman, E. (1994). Endogenous Innovation in the Theory of Growth. Journal of Economic Perspectives, 8(1), 23-44. doi:10.1257/jep.8.1.23
  • Grossman, G. M. and Helpman, E. (1991). Innovation and Growth in the Global Economy. London: The MIT Press.
  • Gülmez, A. ve Yardımcıoğlu, F. (2012). OECD Ülkelerinde Ar-Ge Harcamaları ve Ekonomik Büyüme İlişkisi: Panel Eşbütünleşme ve Panel Nedensellik Analizi (1990-2010). Maliye Dergisi, 163(1), 335-353. Retrieved from https://www.researchgate.net/
  • Harvey, D. I., Leybourne, S. J. and Xiao, B. (2008). A Powerful Test for Linearity When the Order of Integration is Unknown. Studies Nonlinear Dynamics and Econometrics, 12(3), (article 2), https://doi.org/10.2202/1558-3708.1582.
  • Hepsağ, A. (2019). A Unit Root Test Based on Smooth Transition and Nonlinear Adjustment. Communications in Statistics-Simulation and Computation, 50(3), 625-632. https://doi.org/10.1080/03610918.2018.1563154
  • Howitt, P. and Aghion, P. (1998). Capital Accumulation and Innovation as Complementary Factors in Long-Run Growth. Journal of Economic Growth, 3(2), 111-130. https://doi.org/10.1023/A:1009769717601
  • Im, K. and Schmidt, P. (2008). More Efficient Estimation under Non-normality When Higher Moments Do Not Depend on the Regressors, Using Residual-augmented Least Squares. Journal of Econometrics, 144, 219–233. https://doi.org/10.1016/j.jeconom.2008.01.003
  • Khraief, N., Shahbaz, M., Heshmati, A. and Azam, M. (2020). Are Unemployment Rates in OECD Countries Stationary ? Evidence from Univariate and Panel Unit Root Tests. The North American Journal of Economics and Finance, 51, 1-15. https://doi.org/10.1016/j.najef.2018.08.021
  • Kruse, R. 2011. A New Unit Root Test Against ESTAR Based on a Class of Modified Statistics. Statistical Papers, 52(1), 71–85. https://doi.org/10.1007/s00362-009-0204-1
  • Koenker, R. and Basset, G. (1978). Regression Quantiles. Econometrica, 46(1), 33-50. Retrieved from https://www.jstor.org/
  • Koenker, R. (2005). Quantile Regression, USA: Cambridge University Press.
  • Kwiatkowski, D., Phillips, P.C. B., Schmidt, P. and Shin, Y. (1992). Testing The Null Hypothesis of Stationarity Against the Alternative of a Unit Root: How Sure Are We That The Economic Time Series Have a Unit Root?. Journal of Econometrics, 54, 159-178. https://doi.org/10.1016/0304-4076(92)90104-Y
  • Lee, J. and M. C. Strazicich. (2003). Minimum Lagrange multiplier unit root test with two structural breaks. Review of Economics and Statistics 85(4), 1082–1089. Retrieved from https://www.jstor.org/
  • Lee, J. and M. C. Strazicich. (2004). Minimum LM Unit Root Test with One Structural Break. (Department of Economics Appalachian State University Working Paper No. 04-17). Retrieved from https://www.researchgate.net/
  • Lichtenberg, F. R. (1992). R&D Investment and International Productivity Differences (NBRE Working Paper No. w4161). Retrieved from https://www.nber.org/papers/w4161.
  • Özel, H. A. (2012). Ekonomik Büyümenin Teorik Temelleri. Çankırı Karatekin Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 2(1), 63-72. Retrieved from https://dergipark.org.tr/
  • Perron, P. (1989). The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis. Econometrica, 57(6), 1361-1401. Retrieved from https://www.jstor.org/
  • Phillips, P.C. B ve Perron, P. (1988). Testing for a Unit Root in Time Series Regression. Biometrika, 75(2), 335-346. https://doi.org/10.1093/biomet/75.2.335
  • Romer, P. M. (1986). Increasing Returns and Long-Run Growth. Journal of Political Economy, 94(5), 1002-1037. Retrieved from https://www.jstor.org/
  • Romer, P. M. (1990). Endogenous Technological Change. Journal of Political Economy, 98(5, Part 2), 71-102. Retrieved from https://www.jstor.org/
  • Schlitzer, G. (1995). Testing Stationarity of Economic Time Series: Further Monte Carlo Evidence. Ricerche Economiche, 2, 125–144. https://doi.org/10.1016/0035-5054(95)90019-5
  • Seyidoğlu, H. (2006). İktisat Biliminin Temelleri. İstanbul: Güzem Can Yayınları No:21.
  • Türedi, S. (2013). Bilgi ve İletişim Teknolojilerinin Ekonomik Büyümeye Etkisi: Gelişmiş ve Gelişmekte Olan Ülkeler İçin Panel Veri Analizi. Gümüshane Üniversitesi Sosyal Bilimler Enstitüsü Elektronik Dergisi, 4(7), 299-322. Retrieved from https://app.trdizin.gov.tr/
  • Yanyun, Z. and Mingqian, Z. (2004 July). R&D and Economic Growth-Panel Data Analysis in ASEAN+ 3 Countries. Paper presented at the Korea and the World Economy III. Seoul Conference, Korea.
  • Yeldan, E. (2002, Yaz). Neoliberal Küreselleşme İdeolojisinin Kalkınma Söylemi Üzerine Değerlendirmeler. Praksis,7, 19-34. Retrieved from https://www.praksis.org/
  • Yıldırım, S. (2009). Aghion-Howitt Büyüme Modeli Çerçevesinde Ekonomik Özgürlük ve Ekonomik Büyüme Arasındaki İlişkinin Panel Veri Analizi. Dumlupınar Üniversitesi Sosyal Bilimler Dergisi, (25), 259-268. Retrieved from https://app.trdizin.gov.tr/
  • Zivot, E. and Andrews, D. W. K. (1992). Further Evidence on the Great Crash, the Oil Price Shock, and the Unit-Root Hypothesis. Journal of Business & Economic Statistics, 10(3), 251-270. https://doi.org/10.1198/073500102753410372

Ayrıntılar

Birincil Dil Türkçe
Konular İktisat
Bölüm Makaleler
Yazarlar

Merve ALTAYLAR (Sorumlu Yazar)
DOKUZ EYLUL UNIVERSITY
0000-0001-5413-5048
Türkiye


Serap DURSUN
TRAKYA ÜNİVERSİTESİ
0000-0001-8683-0854
Türkiye

Yayımlanma Tarihi 30 Aralık 2021
Yayınlandığı Sayı Yıl 2021, Cilt 6, Sayı IERFM Özel Sayısı

Kaynak Göster

APA Altaylar, M. & Dursun, S. (2021). Türkiye’de İçsel Büyüme Modeline Kademeli Bir Bakış: Kantil Regresyon Yaklaşımı . Ekonomi Politika ve Finans Araştırmaları Dergisi , IERFM Özel Sayısı , 225-246 . DOI: 10.30784/epfad.1024719

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