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The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015)

Yıl 2020, , 111 - 128, 10.05.2020
https://doi.org/10.25294/auiibfd.734217

Öz

In this study, we analyze the relationships among science, technology, and economic growth in Turkey for the period 1980 - 2015. We fitted linear regression and ARDL models by using scientific articles and patents as representatives for the scientific and technological outputs, respectively. The results obtained from the fitted models reveal that there is no significant statistical evidence showing a strong relation between science, technology, and economic growth. There are two possible interpretations of the results. First, the ties between university and industry are weak in Turkey. Second scientific papers of Turkey do not impact the productive sectors of Turkish economy directly.

Kaynakça

  • Åslund, A. (2013). "Why Growth in Emerging Economies is Likely to Fall". Working Paper, Peterson Institute for International Economics, Washington, DC.
  • Barbi, F. C. (2016). "ARDL: Auto Regressive Distributed Lag time series model" R package version 0.0.6.
  • Bernardes, A. T. and Albuquerque, E. D. M. (2003). "Cross-over, Thresholds, and Interactions Between Science and Technology: Lessons for Less-Developed Countries". Research Policy, 32(5): 865-885.
  • Castellacci, F. (2008). "Technology Clubs, Technology Gaps and Growth Trajectories". Structural Change and Economic Dynamics, 19(4): 301-314.
  • Castellacci, F. and Natera, J. M. (2013). "The Dynamics of National Innovation Systems: A Panel Cointegration Analysis of the Coevolution Between Innovative Capability and Absorptive Capacity". Research Policy, 42(3): 579-594.
  • Chaves, C. V. and Moro, S. (2007). "Investigating the Interaction and Mutual Dependence Between Science and Technology". Research Policy, 36(8): 1204-1220.
  • Dickey, D. A., and Fuller, W. A. (1979). "Distribution of the Estimators for Autoregressive Time Series with a Unit Root". Econometrica, 49(4): 1057-1072.
  • Dickey, D. A., and Fuller, W. A. (1981). "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root". Journal of the American Statistical Association, 74(366): 427-431.
  • Dosi, G., Llerena, P., and Labini, M. S. (2006). "The Relationships Between Science, Technologies and Their Industrial Exploitation: An illustration through the Myths and Realities of the So-Called ‘European Paradox". Research Policy, 35(10): 1450-1464.
  • Enders, W. (2015). Applied Econometric Time Series. Wiley, United States of America.
  • Fagerberg, J., Srholec, M., and Knell, M. (2007). "The Competitiveness of Nations: Why Some Countries Prosper While Others Fall Behind". World Development, 35(10): 1595-1620.
  • Fagerberg, J. and Srholec, M. (2008). "National Innovation Systems, Capabilities and Economic Development". Research Policy, 37(9): 1417-1435.
  • Fagerberg, J. and Srholec, M. (2017). "Capabilities, Economic Development, Sustainability". Cambridge Journal of Economics, 41(3): 905-926.
  • Feenstra, R., Inklaar, R., and Timmer, M. (2015). “The Next Generation of the Penn World Table”. American Economic Review, 105(10): 3150-3182.
  • Furman, J. and Hayes, R. (2004). "Catching Up or Standing Still?: National Innovative Productivity Among Follower Countries, 1978–1999". Research Policy, 33(9): 1329-1354.
  • Furman, J., Porter, M. E., and Stern, S. (2002). "The Determinants of National Innovative Capacity". Research Policy, 31(6): 899-933.
  • Jaffe, A. (1989). "Real Effects of Academic Research". The American Economic Review, 79(5): 957-970.
  • Kim, Y. K. and Lee, K. (2015). "Different Impacts of Scientific and Technological Knowledge on Economic Growth: Contrasting Science and Technology Policy in East Asia and Latin America". Asian Economic Policy Review, 10(1): 43-66.
  • Kwiatkowski, D., Phillips, P., Schmidt, P., and Shin, Y. (1992). "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root". Journal of Econometrics, 54: 159-178. Lee, K. and Kim, Y. K. (2018). "Comparing the National Innovation Systems in East Asia and Latin America: Fast Versus Slow". Thomas Clarke ve Keun Lee(ed.) In Innovation in the Asia Pacific, Springer. Singapore.
  • Lee, L. C., Lin, P. H., Chuang, Y. W., and Lee, Y. Y. (2011). "Research Output and Economic Productivity: a Granger Causality Test." Scientometrics, 89: 465-478.
  • Lucas, R. E. (1988). "On the mechanics of economic development". Journal of Monetary Economics, 22(1): 3-42.
  • Mankiw, G., Romer, D., and Weil, D. (1992). "A contribution to the Empirics of Economic Growth". The Quarterly Journal of Economics, 107(2): 407-437.
  • Moritz, S., and Bartz-Beielstein, T. (2017). "imputeTS: Time Series Missing Value Imputation R". The R Journal, 9(1): 207-218.
  • Narayan, P. (2005). "The Saving and Investment Nexus for China: Evidence from Cointegration Tests". Applied Economics, 37(17): 1979-1990.
  • Narin, F., Hamilton, K. S., and Olivastro, D. (1997). "The Increasing Linkage Between U.S. Technology and Public Science". Research Policy, 26(3): 317-330.
  • Pesaran, M. H., Shin, Y., and Smith, R. J. (2001). "Bounds Testing Approaches to the Analysis of Level Relationships". Journal of Applied Econometrics, 16(3): 289-326.
  • Pesaran, M. H. (2015). Time Series and Panel Data Econometrics. Oxford University Press, United Kingdom.
  • Phillips, P. and Perron, P. (1988). "Testing for a Unit Root in Time Series Regression". Biometrika, 75(2): 335-346.
  • Popov, V. and Jomo, K. S. (2018). "Are Developing Countries Catching Up?". Cambridge Journal of Economics, 42(1): 33-46.
  • R Core Team. (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
  • Romer, P. M. (1990). "Endogenous Technological Change". Journal of Political Economy, 98(5): 71-102.
  • Solow, R. M. (1957). "Technical Change and the Aggregate Production Function". The Review of Economics and Statistics, 39(3): 312-320.
  • Tunalı, Ç. B. (2016). "Do Scientific Products Contribute to the Level of Output? Empirical Evidence from the European Union Countries". Advances in Management & Applied Economics, 6(3): 59-83.
  • Zeileis, A., Leisch, F, Hornik, K., and Kleiber, C. (2002). "Strucchange: An R Package for Testing for Structural Change in Linear Regression Models". Journal of Statistical Software, 7(2): 1-38.
  • Zeileis, A. (2019). "pwt9: Penn World Table (Version 9.x)". R package version 9.1-0.

Teknolojik ve Bilimsel Bilginin Türkiye'de Ekonomik Büyümeye Etkisi (1980 - 2015)

Yıl 2020, , 111 - 128, 10.05.2020
https://doi.org/10.25294/auiibfd.734217

Öz

Bu çalışma, Türkiye'de 1980 - 2015 döneminde bilim, teknoloji ve ekonomik büyüme arasındaki ilişkileri analiz etmektedir. Bilimsel yayınlar ve patent verileri sırasıyla bilimsel ve teknolojik çıktıları temsil etmektedir. Çalışmada doğrusal regresyon ve ARDL modelleri kullanılmıştır. Uygulanan modellerden elde edilen sonuçlar, bilim, teknoloji ve ekonomik büyüme arasında güçlü bir ilişki olduğunu gösteren önemli bir istatistiksel kanıt olmadığını ortaya koymaktadır. Çalışmanın sonuçlarına bağlı olarak, iki temel çıkarıma ulaşmak mümkün olabilmektedir. Birincisi, Türkiye'de üniversite ile sanayi arasında bulunan bağlar zayıftır. İkincisi ise, bilimsel makaleler, Türkiye ekonomisinin üretken sektörlerini doğrudan etkilememektedir.

Kaynakça

  • Åslund, A. (2013). "Why Growth in Emerging Economies is Likely to Fall". Working Paper, Peterson Institute for International Economics, Washington, DC.
  • Barbi, F. C. (2016). "ARDL: Auto Regressive Distributed Lag time series model" R package version 0.0.6.
  • Bernardes, A. T. and Albuquerque, E. D. M. (2003). "Cross-over, Thresholds, and Interactions Between Science and Technology: Lessons for Less-Developed Countries". Research Policy, 32(5): 865-885.
  • Castellacci, F. (2008). "Technology Clubs, Technology Gaps and Growth Trajectories". Structural Change and Economic Dynamics, 19(4): 301-314.
  • Castellacci, F. and Natera, J. M. (2013). "The Dynamics of National Innovation Systems: A Panel Cointegration Analysis of the Coevolution Between Innovative Capability and Absorptive Capacity". Research Policy, 42(3): 579-594.
  • Chaves, C. V. and Moro, S. (2007). "Investigating the Interaction and Mutual Dependence Between Science and Technology". Research Policy, 36(8): 1204-1220.
  • Dickey, D. A., and Fuller, W. A. (1979). "Distribution of the Estimators for Autoregressive Time Series with a Unit Root". Econometrica, 49(4): 1057-1072.
  • Dickey, D. A., and Fuller, W. A. (1981). "Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root". Journal of the American Statistical Association, 74(366): 427-431.
  • Dosi, G., Llerena, P., and Labini, M. S. (2006). "The Relationships Between Science, Technologies and Their Industrial Exploitation: An illustration through the Myths and Realities of the So-Called ‘European Paradox". Research Policy, 35(10): 1450-1464.
  • Enders, W. (2015). Applied Econometric Time Series. Wiley, United States of America.
  • Fagerberg, J., Srholec, M., and Knell, M. (2007). "The Competitiveness of Nations: Why Some Countries Prosper While Others Fall Behind". World Development, 35(10): 1595-1620.
  • Fagerberg, J. and Srholec, M. (2008). "National Innovation Systems, Capabilities and Economic Development". Research Policy, 37(9): 1417-1435.
  • Fagerberg, J. and Srholec, M. (2017). "Capabilities, Economic Development, Sustainability". Cambridge Journal of Economics, 41(3): 905-926.
  • Feenstra, R., Inklaar, R., and Timmer, M. (2015). “The Next Generation of the Penn World Table”. American Economic Review, 105(10): 3150-3182.
  • Furman, J. and Hayes, R. (2004). "Catching Up or Standing Still?: National Innovative Productivity Among Follower Countries, 1978–1999". Research Policy, 33(9): 1329-1354.
  • Furman, J., Porter, M. E., and Stern, S. (2002). "The Determinants of National Innovative Capacity". Research Policy, 31(6): 899-933.
  • Jaffe, A. (1989). "Real Effects of Academic Research". The American Economic Review, 79(5): 957-970.
  • Kim, Y. K. and Lee, K. (2015). "Different Impacts of Scientific and Technological Knowledge on Economic Growth: Contrasting Science and Technology Policy in East Asia and Latin America". Asian Economic Policy Review, 10(1): 43-66.
  • Kwiatkowski, D., Phillips, P., Schmidt, P., and Shin, Y. (1992). "Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root". Journal of Econometrics, 54: 159-178. Lee, K. and Kim, Y. K. (2018). "Comparing the National Innovation Systems in East Asia and Latin America: Fast Versus Slow". Thomas Clarke ve Keun Lee(ed.) In Innovation in the Asia Pacific, Springer. Singapore.
  • Lee, L. C., Lin, P. H., Chuang, Y. W., and Lee, Y. Y. (2011). "Research Output and Economic Productivity: a Granger Causality Test." Scientometrics, 89: 465-478.
  • Lucas, R. E. (1988). "On the mechanics of economic development". Journal of Monetary Economics, 22(1): 3-42.
  • Mankiw, G., Romer, D., and Weil, D. (1992). "A contribution to the Empirics of Economic Growth". The Quarterly Journal of Economics, 107(2): 407-437.
  • Moritz, S., and Bartz-Beielstein, T. (2017). "imputeTS: Time Series Missing Value Imputation R". The R Journal, 9(1): 207-218.
  • Narayan, P. (2005). "The Saving and Investment Nexus for China: Evidence from Cointegration Tests". Applied Economics, 37(17): 1979-1990.
  • Narin, F., Hamilton, K. S., and Olivastro, D. (1997). "The Increasing Linkage Between U.S. Technology and Public Science". Research Policy, 26(3): 317-330.
  • Pesaran, M. H., Shin, Y., and Smith, R. J. (2001). "Bounds Testing Approaches to the Analysis of Level Relationships". Journal of Applied Econometrics, 16(3): 289-326.
  • Pesaran, M. H. (2015). Time Series and Panel Data Econometrics. Oxford University Press, United Kingdom.
  • Phillips, P. and Perron, P. (1988). "Testing for a Unit Root in Time Series Regression". Biometrika, 75(2): 335-346.
  • Popov, V. and Jomo, K. S. (2018). "Are Developing Countries Catching Up?". Cambridge Journal of Economics, 42(1): 33-46.
  • R Core Team. (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
  • Romer, P. M. (1990). "Endogenous Technological Change". Journal of Political Economy, 98(5): 71-102.
  • Solow, R. M. (1957). "Technical Change and the Aggregate Production Function". The Review of Economics and Statistics, 39(3): 312-320.
  • Tunalı, Ç. B. (2016). "Do Scientific Products Contribute to the Level of Output? Empirical Evidence from the European Union Countries". Advances in Management & Applied Economics, 6(3): 59-83.
  • Zeileis, A., Leisch, F, Hornik, K., and Kleiber, C. (2002). "Strucchange: An R Package for Testing for Structural Change in Linear Regression Models". Journal of Statistical Software, 7(2): 1-38.
  • Zeileis, A. (2019). "pwt9: Penn World Table (Version 9.x)". R package version 9.1-0.
Toplam 35 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Ekonomi
Bölüm Makaleler
Yazarlar

Furkan Börü 0000-0001-9239-1341

Kemal Dinçer Dingeç Bu kişi benim 0000-0002-5216-4651

Dündar Murat Demiröz Bu kişi benim 0000-0003-1783-9905

Yayımlanma Tarihi 10 Mayıs 2020
Gönderilme Tarihi 3 Temmuz 2019
Kabul Tarihi 22 Aralık 2019
Yayımlandığı Sayı Yıl 2020

Kaynak Göster

APA Börü, F., Dingeç, K. D., & Demiröz, D. M. (2020). The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015). Akdeniz İİBF Dergisi, 20(1), 111-128. https://doi.org/10.25294/auiibfd.734217
AMA Börü F, Dingeç KD, Demiröz DM. The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015). Akdeniz İİBF Dergisi. Mayıs 2020;20(1):111-128. doi:10.25294/auiibfd.734217
Chicago Börü, Furkan, Kemal Dinçer Dingeç, ve Dündar Murat Demiröz. “The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015)”. Akdeniz İİBF Dergisi 20, sy. 1 (Mayıs 2020): 111-28. https://doi.org/10.25294/auiibfd.734217.
EndNote Börü F, Dingeç KD, Demiröz DM (01 Mayıs 2020) The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015). Akdeniz İİBF Dergisi 20 1 111–128.
IEEE F. Börü, K. D. Dingeç, ve D. M. Demiröz, “The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015)”, Akdeniz İİBF Dergisi, c. 20, sy. 1, ss. 111–128, 2020, doi: 10.25294/auiibfd.734217.
ISNAD Börü, Furkan vd. “The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015)”. Akdeniz İİBF Dergisi 20/1 (Mayıs 2020), 111-128. https://doi.org/10.25294/auiibfd.734217.
JAMA Börü F, Dingeç KD, Demiröz DM. The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015). Akdeniz İİBF Dergisi. 2020;20:111–128.
MLA Börü, Furkan vd. “The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015)”. Akdeniz İİBF Dergisi, c. 20, sy. 1, 2020, ss. 111-28, doi:10.25294/auiibfd.734217.
Vancouver Börü F, Dingeç KD, Demiröz DM. The Effect of Technological and Scientific Knowledge on Economic Growth in Turkey (1980 - 2015). Akdeniz İİBF Dergisi. 2020;20(1):111-28.
Dizinler

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