Türk Savunma ve Havacılık Sanayisinde Üretim Faktörlerinin Analizi

Year 2025, Volume: 59 Issue: 4, 985 - 1002, 08.10.2025

Fethi Aslan

https://doi.org/10.51551/verimlilik.1730323

Abstract

Amaç: Bu çalışmanın amacı, Türk savunma ve havacılık sanayisinde istihdam, teknoloji geliştirme ve ürün geliştirme harcamalarının ciro üzerindeki etkilerini inceleyerek, sektörel büyüme dinamiklerini belirlemektir.
Yöntem: Çalışmada, Cobb-Douglas üretim fonksiyonu sektörel verilere dayalı olarak uygulanmıştır. Analiz güvenilirliğini arttırmak amacıyla Bootstrap yeniden örnekleme ve Monte Carlo simülasyon tekniklerinden yararlanılmıştır.
Bulgular: Elde edilen bulgular, Türk savunma ve havacılık sanayisinde istihdam, teknoloji geliştirme ve ürün geliştirme harcamalarının sektörel büyüme üzerinde anlamlı ancak farklılaşan etkiler oluşturduğunun ortaya koymaktadır. Ürün geliştirme harcamaları büyüme performansı (ciro) üzerinde en güçlü etkiye sahiptir. Bununla birlikte, teknoloji geliştirme harcamalarının etkisinin beklenenden düşük seviyede kalmıştır. İstihdam faktörünün ise ürün geliştirme faktörüne yakın bir katkı sağlamıştır.
Orjiinallik: Bu çalışmanın özgünlüğü, savunma ve havacılık sektöründe üretim faktörlerinin ekonomik etkisini analiz etmek için Cobb-Douglas üretim fonksiyonunun Bootstrap ve Monte Carlo simülasyon teknikleriyle güçlendirildiği metodolojik açıdan yenilikçi yaklaşımında yatmaktadır. Ayrıca, teknoloji geliştirme ve ürün geliştirme faktörlerinin etkisinin ayrıştırılarak incelenmesiyle bu kritik sektörde detaylı bir faktör analizi sunan ilk çalışmalardan biri olma özelliği taşımaktadır. Bununla birlikte hızlı bir şekilde büyüyen Türk savunma ve havacılık sanayisinde teknoloji geliştirme harcamalarının beklenenin altında etkili olduğu bulgusu özgün bir ampirik katkı sunmaktadır.

Keywords

Ekonometrik Analiz , Verimlilik , Bootstrap , Monte Carlo , Ürün Geliştirme , Teknoloji Geliştirme

Analysis of Production Factors in Turkish Defense and Aerospace Industry

Abstract

Purpose:The aim of this study is to identify the dynamics of sectoral growth in the Turkish defense and aerospace industry by examining the effects of employment, technology development, and product development expenditures on turnover.
Method: In this study, the Cobb-Douglas production function was applied based on sectoral data. Bootstrap resampling and Monte Carlo simulation techniques were utilized to improve the reliability of the analysis.
Findings: The findings show that employment, technology development, and product development expenditures all have significant effects on sectoral growth in the Turkish defense and aerospace industry. Product development has the strongest impact on turnover. The effect of technology development is lower than expected. Employment provides a contribution close to that of product development.
Originality: The originality of this study lies in its methodologically innovative approach. It strengthens the analysis of the economic effects of production factors in the defense and aerospace industry by combining the Cobb-Douglas production function with Bootstrap and Monte Carlo simulation techniques. Additionally, by separately examining the effects of technology development and product development factors, this study is among the first to provide a detailed factor analysis in this critical sector. At the same time, the finding that technology development expenditures have had a less-than-expected impact in the rapidly growing Turkish defense and aerospace industry provides a unique empirical contribution.

Keywords

Econometric Analysis , Productivity , Bootstrap , Monte Carlo , Product Development , Technology Development

References

• Acemoglu, D., (2011). "Lectures in Labor Economics", MIT Economics Department, https://economics.mit.edu, (Erişim tarihi: 10.03.2025).
• Aristodemou, L., Tietze, F., O'Leary, E. and Shaw, M. (2019). "A Literature Review on Technology Development Process (TDP) Models", Cambridge Working Papers in Economics, 6, 1-30. https://doi.org/10.17863/CAM.35692
• Aslan, F. (2023). "Teknoloji Geliştirme Sürecinin Değerlendirilmesi İçin Olgunluk Modeli Önerisi: ARGE–500 Firmalarının Faaliyet ve Yaklaşımlarına Yönelik Bir Uygulama", Yayınlanmamış Doktora Tezi, Fırat Üniversitesi Sosyal Bilimler Enstitüsü, Elazığ.
• Başeğmez, H. and Onalan, O. (2018). "Estimation of Economic Growth Using Grey Cobb-Douglas Production Function:An Application for US Economy", Pressacademia, 7(2), 178-190. https://doi.org/10.17261/Pressacademia.2018.840
• Belin, J. and Guille, M. (2019). "Innovation Dynamics in Defence Industries", Disruptive Technology and Defence Innovation Ecosystems, Editor: Barbaroux, P., Wiley, 1-30. https://doi.org/10.1002/9781119644569.ch1
• Belt, V., Ri, A. and Akinremi, T. (2021). "The UK's Business R&D Workforce: Skills, Sector Trends and Future Challenges", www.enterpriseresearch.ac.uk, (Erişim tarihi: 14.03.2025).
• Bond, S. and Söderbom, M. (2005). "Adjustment Costs and the Identification of Cobb-Douglas Production Functions", Working Paper Series, Institute for Fiscal Studies, London, https://doi.org/10.1920/wp.ifs.2005.0504
• Bower, J. (2018). "Resource Allocation Theory", The Palgrave Encyclopedia of Strategic Management, Editor: Augier, M. and Teece, D.J., Palgrave Macmillan, London, 1445-1448.
• Chen, Y. C. (2018). "STAT 516: Stochastic Modeling of Scientific Data, Lecture 7: Monte Carlo Methods", http://faculty.washington.edu/yenchic/18A_stat516/html, (Erişim tarihi: 10.06.2025).
• Diwan, R. K. (1968). "On The Cobb-Douglas Production Function", Southern Economic Journal, 34(3), 410. https://doi.org/10.2307/1055504
• Dritsaki, C. and Stamatiou, P. (2018). "Cobb-Douglas Production Function: The Case of Poland's Economy", Advances in Time Series Data Methods in Applied Economic Research, Editor: Tsounis, N. and Vlachvei, A., Springer International Publishing, Cham, 465-483.
• Durbin, J. and Watson, G.S. (1971). "Testing for Serial Correlation in Least Square Regression III", Biometrika, 58, 1-19.
• European Defence Agency. (2024). "Defence Data 2023-2024", www.eda.europa.eu, (Erişim tarihi: 14.03.2025). Fernandes, M. and Centrone, M. (2024). "Improving the Quality of European Spending on Defence: Cost of Non Europe Report", https://data.europa.eu/doi/10.2861/2105737, (Erişim tarihi: 14.03.2025).
• Fraser, I. (2002). "The Cobb-Douglas Production Function: An Antipodean Defence?", Economic Issues, 7(1), 39-58.
• Gaida, J., Wong-Leung, J., Robin, S. and Cave, D. (2023). "ASPI's Critical Technology Tracker – The Global Race for Future Power", https://www.aspi.org.au/report/critical-technology-tracker/, (Erişim tarihi: 14.03.2025).
• Hayami, Y. (1970). "On The Use of The Cobb-Douglas Production Function on The Cross-Country Analysis of Agricultural Production", American Journal of Agricultural Economics, 52(2), 327-329. https://doi.org/10.2307/1237509
• Hartley, K. (2012). "Defence-Industrial Issues: Employment, Skills, Technology and Regional Impacts", https://basicint.org/publications/keith-hartley/2012/defence-industrial-issues-employment-skills-technology-and-regional, (Erişim tarihi: 21.03.2025).
• Hoch, I. (1958). "Simultaneous Equation Bias in the Context of The Cobb-Douglas Production Function", Econometrica, 26(4), 566. https://doi.org/10.2307/1907517
• Hooke, R. (2005). "The Defence Industry in the 21st Century", https://www.pwc.pl/en/publikacje/defence _industry_ads.pdf, (Erişim tarihi: 21.03.2025).
• Jarque, C.M. and Bera, A.K. (1987). "A Test For Normality of Observations and Regression Residuals", International Statistical Review/Revue Internationale de Statistique, 163-172.
• Jermalavičius, T. (2009). "Defence Research & Development: Lessons from NATO Allies", www.icds.ee, (Erişim tarihi: 21.03.2025).
• Josheski, D., Lazarov, D. and Koteski, C. (2011). "Cobb-Douglas Production Function Revisited, VAR and VECM Analysis and a Note on Fischer/Cobb-Douglas Paradox", https://mpra.ub.uni-muenchen.de, (Erişim tarihi: 21.03.2025).
• Khatun, T. and Afroze, S. (2016). "Relationship Between Real GDP and Labour and Capital By Applying The Cobb-Douglas Production Function: A Comparative Analysis Among Selected Asian Countries", Journal of Business Studies, 37(1), 113-129.
• Kim, H. Y. (2013). "Statistical Notes for Clinical Researchers: Assessing Normal Distribution (2) Using Skewness and Kurtosis", Restorative Dentistry & Endodontics, 38(1), 52. https://doi.org/10.5395/rde.2013.38.1.52
• Kleyn, J., Arashi, M., Bekker, A. and Millard, S. (2017). "Preliminary Testing of the Cobb-Douglas Production Function and Related Inferential Issues", Communications in Statistics—Simulation and Computation, 46(1), 469-488. https://doi.org/10.1080/03610918.2014.968724
• KPMG. (2016). "The Role of Capital and Labour in Driving Economic Growth in Australia", http://www.kpmg.com.au, (Erişim tarihi: 21.03.2025).
• Kubicek, K. (2022). "Human Capital ROI: The Positive Impact on Business Performance", https://www.forbes.com/councils/forbeshumanresourcescouncil/2022/09/09/humancapital-roi-the-positive-impact-on-business-performance, (Erişim tarihi: 21.05.2025).
• Markowski, S., Hall, P. and Dessi, A. (1997). "Defence R&D and the Management of Australia's Defence Technology", Prometheus, 15(2). https://doi.org/10.1080/08109029708632073
• Mauro, F. and Thoma, K. (2016). "The Future of EU Defence Research", European Parliament. Brussels.
• McKean, R. N., Hitch, C. J., Enke, S., Enthoven, A. C., Hoag, M. W., McGuire, C. B. and Wohlstetter, A. (1960). "The Economics of Defense in the Nuclear Age", Harvard University Press. https://doi.org/10.4159/harvard.9780674865884
• Nobelius, D. (2002). “Managing R&D Processes: Focusing on Technology Development, Product Development, and Their Interplay”, Unpublished Dissertation, Chalmers University of Technology, Göteborg.
• Oswald, W. A. (2014). "Understanding Technology Development Processes Theory & Practice", Unpublished Master's Thesis, Massachusetts Institute of Technology, Cambridge.
• Osti, D. (2023). "Returns to Scale with a Cobb-Douglas Production Function for Four Small Northern Italian Firms", https://mpra.ub.uni-muenchen.de/116351, (Erişim tarihi: 14.04.2025).
• Parham, D. and Segarajasekeran, P. (2016). "IT Use and Australia's Productivity: Where Are We Now?", https://www.infrastructure.gov.au/sites/default/files/documents/BCR-Digital%20Productivity%20-Report-FINAL-8-Feb.pdf, (Erişim tarihi: 21.05.2025).
• Savunma Sanayi Başkanlığı. (2025). "Savunma Sanayimiz", https://www.ssb.gov.tr/WebSite/contentlist.aspx?PageID=47&LangID=1, (Erişim tarihi: 09.04.2025).
• Sheasley, W.D. (1999). "Leading the Technology Development Process", Research-Technology Management, 42(3), 49-55. https://doi.org/10.1080/08956308.1999.11671284
• Shuang-hong, B., Si-yong, Z. and Rui, S. (2006). "The Analysis on the Technological Advancement Effect in the Defence Industry”, International Conference on Management Science and Engineering (2006), Lille, France. https://doi.org/10.1109/ICMSE.2006.314122
• Srivastava, M.S., and Singh, B. (1989). "Bootstrapping in Multiplicative Models", Journal of Econometrics, 42(3), 287-297. https://doi.org/10.1016/0304-4076(89)90054-7
• Stig, D. C. (2015). “Technology Platforms: Organizing and Assessing Technological Knowledge to Support its Reuse in New Applications”, Unpublished Dissertation, Chalmers University of Technology, Gothenburg, Sweden.
• Torres, J.L. (2020). "The Production of National Defense and the Macroeconomy", PLOS One, 15(10). https://doi.org/10.1371/journal.pone.0240299
• Ulrich, K. T. and Eppinger, S. D. (2016). “Product Design and Development”, McGraw-Hill Education, New York. United Nations. (1990). “Projection Methods for Integrating Population Variables into Development Planning”, New York.
• Vasyl'yeva, O. (2021). "Assessment of Factors of Sustainable Development of the Agricultural Sector Using the Cobb-Douglas Production Function", Baltic Journal of Economic Studies, 7(2), 37-49. https://doi.org/10.30525/2256-0742/2021-7-2-37-49
• Walsh, V. (1992). “Winning by Design: Technology, Product Design and International Competitiveness”, Blackwell Business, Oxford.
• Wang, J., Song, H., Tian, Z., Bei, J., Zhang, H., Ye, B. and Ni, J. (2021). "A Method for Estimating Output Elasticity of Input Factors in Cobb-Douglas Production Function and Measuring Agricultural Technological Progress", IEEE Access, 9, 26234-26250. https://doi.org/10.1109/ACCESS.2021.3056719
• Wasserman, L. (2017). "Statistical Methods for Machine Learning", https://www.stat.cmu.edu/~ryantibs/statml, (Erişim tarihi: 21.05.2025).
• Wei, T. (2007). "Impact of Energy Efficiency Gains on Output and Energy Use With Cobb-Douglas Production Function", Energy Policy, 35(4), 2023-2030. https://doi.org/10.1016/j.enpol.2006.08.009
• Weiß, M., and Göker, M. (2011). "Molecular Phylogenetic Reconstruction", The Yeasts, 159-174. https://doi.org/10.1016/b978-0-444-52149-1.00012-4
• Yuan, C., Liu, S. and Wu, J. (2009). "Research on Energy-Saving Effect of Technological Progress Based on Cobb-Douglas Production Function", Energy Policy, 37(8), 2842-2846. https://doi.org/10.1016/j.enpol.2009.04.025
• Zhang, Q., Dong, W., Wen, C. and Li, T. (2020). "Study on Factors Affecting Corn Yield Based on the Cobb-Douglas Production Function", Agricultural Water Management, 228, 105869. https://doi.org/10.1016/j.agwat.2019.105869