Modeling and Forecasting the Impact of Türkiye's Technological Development on Economic Growth

Öz

This study fundamentally examines the relationship between the economy and technology. In this context, the impact of technological innovation and development on economic growth in Türkiye was analyzed using data from the period 1996-2020. Gross Domestic Product (GDP) was employed as the dependent variable, while the number of patent applications (PA) and the number of articles published in scientific and technical journals (STJ) were used as independent variables Multiple linear regression and Bayesian regression analysis were used as the methodology. According to the findings, it was concluded that the impact of technological development indicators on economic growth is positive.

Anahtar Kelimeler

• Bayesian Regression Analysis
• Technological Development
• Monte Carlo Method
• Economy

Türkiye’nin Teknolojik Gelişiminin Ekonomik Büyümeye Etkisinin Modellenmesi ve Tahminlenmesi

Öz

Bu çalışma temelde, ekonomi-teknoloji ilişkisinin incelenmesine dayanmaktadır. Bu kapsamda, 1996-2020 dönemine ait verilerle Türkiye’deki teknolojik yenilik ve gelişimin ekonomik büyümeye etkisinin değerlendirilmesi için, gayri safi yurtiçi hasıla (GSYİH) (bağımlı değişken) ile patent başvuru sayısı (yerleşik olan ve yerleşik olmayan) (PBS) ve bilimsel ve teknik dergilerde yayımlanan makale sayısı (BTM) (bağımsız değişenler) kullanılmıştır. İlgili veri seti Dünya Bankası resmi veri sitesinden elde edilmiştir. Çalışmada yöntem olarak, regresyon analizi ve Bayesyen regresyon analizi kullanılmıştır. Elde edilen bulgulara göre, teknolojik gelişim göstergelerinin ekonomik büyümeye etkisinin pozitif yönlü olduğu sonucuna varılmıştır.

Anahtar Kelimeler

• Bayesyen Regresyon Analizi
• Teknolojik Gelişim
• Monte Carlo Yöntemi
• Ekonomi

Kaynakça

1. Ablay, M. V., & Doğan, A. (2024). The role of R&D expenditures, information and communication technology products exports and high-technology products exports on Turkey’s technological development. İktisadi İdari ve Siyasal Araştırmalar Dergisi, 9(24), 428-446. https://doi.org/10.25204/iktisad.1409735
2. Afkham, B. M., Knudsen, K., Rasmussen, A. K., & Tarvainen, T. (2024). A Bayesian approach for consistent reconstruction of inclusions. Inverse Problems, 40(4), 045004. https://doi.org/10.1088/1361-6420/ad2531
3. Algan, N., Manga, M. & Tekeoğlu, M. (2017). Teknolojik gelişme göstergeleri ile ekonomik büyüme arasındaki nedensellik ilişkisi: Türkiye örneği. International Conference on Eurasian Economies (pp. 332-338).
4. Alofaysan, H., Radulescu, M., Balsalobre-Lorente, D., & Mohammed, K. S. (2024). The effect of eco-friendly and financial technologies on renewable energy growth in emerging economies. Heliyon, 10(17), e36641. https://doi.org/10.1016/j.heliyon.2024.e36641
5. Altındağ, İ. (2015). Bayesci doğrusal olmayan yapısal eşitlik modeli [Yayımlanmamış doktora tezi]. Konya Selçuk Üniversitesi.
6. Amrani, A., Diepeveen, D., Murray, D., Jones, M. G., & Sohel, F. (2024). Multi-task learning model for agricultural pest detection from crop-plant imagery: A Bayesian approach. Computers and Electronics in Agriculture, 218, 108719. https://doi.org/10.1016/j.compag.2024.108719
7. Anser, M. K., Ahmad, M., Khan, M. A., Nassani, A. A., Haffar, M., & Zaman, K. (2024). The “IMPACT” of web of science coverage and scientific and technical journal articles on the world’s income: Scientific informatics and the knowledge-driven economy. Journal of the Knowledge Economy, 15(1), 3147-3173. https://doi.org/10.1007/s13132-023-01302-z
8. Bernardo, J. M., & Smith, A. F. M. (2000). Bayesian theory, John Wiley & Sons Inc.

9. Cavdar, S. C., & Aydin, A. D. (2015). An empirical analysis about technological development and innovation indicators. Procedia-Social and Behavioral Sciences, 195, 1486-1495.
10. Congdon, P. (2006), Bayesian statistical modelling (2nd ed.). John Wiley & Sons Inc.
11. Dam, M. M., & Yıldız, B. (2016). BRICS-TM ülkelerinde Ar-Ge ve inovasyonun ekonomik büyüme üzerine etkisi: Ekonometrik bir analiz. Akdeniz İ.İ.B.F. Dergisi, 16(33), 220-236.
12. Dhar, B. K., Shaturaev, J., Kurbonov, K., & Nazirjon, R. (2023). The causal nexus between innovation and economic growth: An OECD study. Social Science Quarterly, 104(4), 395-405. https://doi.org/10.1111/ssqu.13261
13. Ding, C., Liu, C., Zheng, C., & Li, F. (2022). Digital Economy, technological innovation and high-quality economic development: Based on spatial effect and mediation effect. Sustainability, 14(1), 216, https://doi.org/10.3390/su14010216.
14. Dobrzański, P., Bobowski, S., Chrysostome, E., Velinov, E., & Strouhal, J. (2021). Toward innovation-driven competitiveness across African countries: An analysis of efficiency of R&D expenditures. Journal of Competitiveness, 13(1), 5-22. http://dx.doi.org/10.7441/joc.2021.01.01
15. Doğan, A. (2022a). Ulusal ve uluslararası teknoloji haber web siteleri kullanılabilirliğinin içerik analizi ile karşılaştırmalı incelenmesi. Kahramanmaraş Sütçü İmam Üniversitesi Sosyal Bilimler Dergisi, 19(3), 1481-1501. https://doi.org/10.33437/ksusbd.1193673
16. Doğan, A. (2022b). Yönetim bilişim sistemleri öğrencilerinin alana yönelik algılarının ölçümü üzerine uygulamalı bir araştırma. Journal of Politics, Economy and Management, 5(2), 110-129.
17. Doğan, A., Ablay, M. V., & Ağca, A. (2024). Investigation of the effects of technological development indicators on employment in Türkiye: A Bayesian approach. Sosyoekonomi, 32(62), 115-129. https://doi.org/10.17233/sosyoekonomi.2024.04.06
18. Dubois, D., & Prade, H., (1988). Possibility theory (E.F. Harding, Trans.;1st ed.). Plenum Press. (Original work published 1985)
19. Ekici, O. (2005). Bayesyen regresyon ve WinBUGS ile bir uygulama [Yayımlanmamış yüksek lisans tezi]. İstanbul Üniversitesi.
20. Goldstein, M., & Wooff, D. (2007). Bayes linear statistics: Theory and methods. John Wiley & Sons Inc.
21. Greenberg, E. (2013), Introduction to Bayesian econometrics (2nd ed.). Cambridge University Press.
22. Gündoğdu, S. (2016). Balıklarda büyüme parametrelerinin Bayesyen istatistiksel yöntemle tahmini [Yayımlanmamış doktora tezi]. Çukurova Üniversitesi.
23. Hahn, E. D. (2014), Bayesian methods for management and business: Pragmatic solutions for real problems. John Wiley & Sons Inc.
24. Jabeen, G., Wang, D., Işık, C., Alvarado, R., & Ongan, S. (2024). Role of energy utilization intensity, technical development, economic openness, and foreign tourism in environmental sustainability. Gondwana Research, 127, 100-115. https://doi.org/10.1016/j.gr.2023.03.001
25. Javaid, M., Haleem, A., Singh, R. P., & Sinha, A. K. (2024). Digital economy to improve the culture of industry 4.0: A study on features, implementation and challenges. Green Technologies and Sustainability, 2(2), 100083. https://doi.org/10.1016/j.grets.2024.100083
26. Jiao, J., Song, J., & Ding, T. (2024). The impact of synergistic development of renewable energy and digital economy on energy intensity: Evidence from 33 countries. Energy, 295, 130997. https://doi.org/10.1016/j.energy.2024.130997
27. Judge, G. G., Griffiths, W. E., Hill, R. C., Lütkepohl, H., & Chao Lee, T. (1991). The theory and practice of econometrics (2nd ed.). John Wiley & Sons Inc.
28. Judijanto, L., Manu, C. M. A., Sitopu, J. W., Mangelep, N. O., & Hardiansyah, A. (2024). The impact of mathematics in science and technology development. International Journal of Teaching and Learning, 2(2), 451-458.
29. Kagermann, H., Wahlster, W., & Helbig, J. (2013). Recommendations for implementing the strategic initiative industrie 4.0. Final report of the Industrie 4.0 Working Group. Forschungsunion, Germany: Acatech.
30. Karadağ, Ö. (2011). Bayesci hiyerarşik modeller [Yayımlanmamış yüksek lisans tezi]. Hacettepe Üniversitesi.
31. Karakostas, E. (2022). What determines the medium and hich technology products exports: The case of Germany. International Journal of Advanced Economics, 4(3), 40-52. https://doi.org/10.51594/ijae.v4i3.316
32. Khan, T., & Emon, M. H. (2024). Exploring the potential of the blue economy: A systematic review of strategies for enhancing international business in Bangladesh in the context of indo-pacific region. Review of Business and Economics Studies, 12(2), 55-73. https://doi.org/10.26794/2308-944X-2024-12-2-55-73
33. Khan, Y., & Hassan, T. (2024). Promoting sustainable development: Evaluating the influence of natural resources, high-tech export and corruption on CO2 emissions in developing economies. Resources Policy, 88, 104511. https://doi.org/10.1016/j.resourpol.2023.104511
34. Kiani, T. A., Sabir, S., Qayyum, U., & Anjum, S. (2022). Estimating the effect of technological innovations on environmental degradation: Empirical evidence from selected ASEAN and SAARC countries. Environment, Development and Sustainability, 25, 6529-6550. https://doi.org/10.1007/s10668-022-02315-5
35. King, R., Morgan, B., Gimenez, O., & Brooks, S. (2009). Bayesian analysis for population ecology. Chapman and Hall/CRC Press.
36. Koehrsen, W., (2018). Introduction to Bayesian lineer regression, towards data science. https://towardsdatascience.com/introduction-to-Bayesian-linear-regression-e66e60791ea7 (Erişim tarihi: 20 Kasım 2024).
37. Kozlova, E., & Didenko, N. (2022). Impact of technological development factors on the quality of life: a comparative analysis of E7 and G7. International Journal for Quality Research, 16(2), 625–642. https://doi.org/10.24874/IJQR16.02-18
38. Kruschke, J. K, Aguinis, H., & Joo, H. (2012). The time has come: Bayesian methods for data analysis in the organizational sciences. Organizational Research Methods, 15(4), 722–752. https://doi.org/10.1177/1094428112457829
39. Küçük, S. (2021). Endüstri 4.0 kavramının ve sürecinin bilinirliği üzerine Karaman organize sanayi bölgesinde bir araştırma [Yayımlanmamış yüksek lisans tezi]. Karamanoğlu Mehmet Bey Üniversitesi.
40. Lee, J.J., & Chu, C. T. (2012). Bayesian clinical trials in action. Statistics in Medicine, 31(25), 2955-2972. https://doi.org/10.1002/sim.5404
41. Liu, Y., Xie, Y., & Zhong, K. (2024). Impact of digital economy on urban sustainable development: Evidence from Chinese cities. Sustainable Development, 32(1), 307-324. https://doi.org/10.1002/sd.2656
42. Mccarthy, M. A. (2007). Bayesian methods for ecology. Cambridge University Press.
43. Mehmood, K., Iftikhar, Y., & Khan, A. N. (2022). Assessing eco technological innovation efciency using dea approach: Insights from the OECD countries. Clean Technologies and Environmental Policy, 24, 3273-3286. https://doi.org/10.1007/s10098-022-02378-y
44. Mora Apablaza, L., & Navarrete, C. (2022). Patents as indicators of the technological position of countries on a global level?. Scientometrics, 127, 1233–1246. https://doi.org/10.1007/s11192-022-04268-y
45. Panagiotidis, T., Papapanagiotou, G., & Stengos, T. (2024). A Bayesian approach for the determinants of bitcoin returns. International Review of Financial Analysis, 91, 103038. https://doi.org/10.1016/j.irfa.2023.103038
46. Petralia, S., Balland, P. A., & Morrison, A. (2017). Climbing the ladder of technological development. Research Policy, 46(5), 956–969. https://doi.org/10.1016/j.respol.2017.03.012
47. Richardson, S., & Best, N. (2003). Bayesian hierarchical models in ecological studies of health–environment effects. Environmetrics Society, 14(2), 129-147. https://doi.org/10.1002/env.571
48. Scheines, R., Hoijtink, H., & Boomsma, A. (1999). Bayesian estimation and testing of structural equation models. Psychometrika, 64(1), 37-52.
49. Shah, N., Zehri, A. W., Saraih, U. N., Abdelwahed, N. A. A., & Soomro, B. A. (2024). The role of digital technology and digital innovation towards firm performance in a digital economy. Kybernetes, 53(2), 620-644. https://doi.org/10.1108/K-01-2023-0124
50. Shodiev, J., & Zarina, R. (2024). Digital economy as a factor of transformation of economic systems. International Journal of Recently Scientific Researcher's Theory, 2(1), 162-166.
51. Sinha, M., & Sengupta, P. P. (2022). FDI inflow, ICT expansion and economic growth: An empirical study on asia-pacific developing countries. Global Business Review 23(3), 804–821. https://doi.org/10.1177/0972150919873839
52. Sojoodi, S., & Baghbanpour, J. (2024). The relationship between high-tech industries exports and GDP growth in the selected developing and developed countries. Journal of the Knowledge Economy, 15(1), 2073-2095. https://doi.org/10.1007/s13132-023-01174-3
53. Sony, M. (2020). Pros and cons of implementing industry 4.0 for the organizations: A review and synthesis of evidence. Production & Manufacturing Research, 8(1), 244–272. https://doi.org/10.1080/21693277.2020.1781705
54. Şeker, A. (2019). Teknolojik gelişme ve yüksek teknoloji ihracatının ekonomik karmaşıklık endeksi üzerindeki etkisi: Türkiye örneği. Yönetim ve Ekonomi, 26(2), 377-395. https://doi.org/10.18657/yonveek.581397
55. Tekin, A., & Demirel, O. (2022). Bilimsel ve teknolojik performansın ekonomik büyümeye etkisi: OECD ülkeleri üzerine bir panel veri analizi. Sosyoekonomi, 30(51), 353-364. https://doi.org/10.17233/sosyoekonomi.2022.01.17 Temiz, R. (2017). Bulanık Bayesci hipotez testlerinin karşılaştırılması [Yayımlanmamış yüksek lisans tezi]. Ege Üniversitesi.
56. The World Bank. (2023, August). The World Bank Open Data. https://databank.worldbank.org/source/world-development-indicators
57. Tuskan, Y., & Erzin, Y. (2024). Application of Monte Carlo simulation technique for slopes stabilized with piles. Afyon Kocatepe University – Journal of Science and Engineering. 24(1), 117-125. https://doi.org/10.35414/akufemubid.1287644
58. Uyar, Ş. (2020). Teknoloji transferi ve ekonomik büyüme arasındaki ilişki: Türkiye örneği (1984-2018) [Yayımlanmamış yüksek lisans tezi]. Aydın Adnan Menderes Üniversitesi.
59. Westphal, L. E. (2002). Technology strategies for economic development in a fast changing global economy. Economics of Innovation and New Technology, 11(4-5), 275-320. https://doi.org/10.1080/10438590200000002
60. Wikipedia, (2025). An essay towards solving a problem in the doctrine of chances, https://en.wikipedia.org/wiki/An_Essay_Towards_Solving_a_Problem_in_the_Doctrine_of_Chances (Erişim tarihi: 20 Ocak 2025).
61. Yurtçu, M. (2018). Parametrik olmayan Bayes yöntemiyle ortak değişkenlere göre yapılan test eşitlemelerinin karşılaştırılması [Yayımlanmamış doktora tezi]. Hacettepe Üniversitesi.
62. Zainab, T., Wani, Z. A., & Bhat, M. A. (2018). Scientific research in relation to Gross Domestic Product (GDP) a comparative study of China and India. 5th International Symposium on Emerging Trends and Technologies in Libraries and Information Services (ETTLIS) (pp. 328-330). IEEE.
63. Zhang, W., & Yang, J. (2015). Forecasting natural gas consumption in China by Bayesian model averaging. Energy Reports, 1, 216–220. https://doi.org/10.1016/j.egyr.2015.11.001