Journals / Verimlilik Dergisi / 2026 / Cilt: 59 Sayı: 1

Determinants of Material Productivity

Türkiye'de Materyal Verimliliğinin Belirleyicileri

Uğur Coşkun(MERSİN ÜNİVERSİTESİ, İKTİSADİ VE İDARİ BİLİMLER FAKÜLTESİ, İKTİSAT BÖLÜMÜ)0000-0002-6357-607X
Semiha Aytemiz(MERSİN ÜNİVERSİTESİ, İKTİSADİ VE İDARİ BİLİMLER FAKÜLTESİ, İKTİSAT BÖLÜMÜ, İKTİSAT PR.)0000-0001-6313-5912
Pages
223–234
Publication Date
2025-01-22
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

These results show short-run deviation from equilibrium, and long-run results are obtained using the ARDL bounds test.

📌 3 Key Takeaways

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Objective & Hypothesis:Purpose: Productivity is crucial for a country's effective economic growth paths.
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Key Findings & Data:Findings: According to the ARDL bounds test results, a %1 increase in per capita income and current account balance increases material productivity by %0.03 and %0.02, respectively, while a %1 increase in unemployment decreases material productivity by %0.03 in the 1990-2022 data period in Türkiye.
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Conclusion & Impact:These results show short-run deviation from equilibrium, and long-run results are obtained using the ARDL bounds test.
🔬Design:Modeling & Simulation
📍Scope:2022 Verileri
⚙️Variables:Verimlilik · Materyal Verimliliği · ARDL Sınır Testi

Abstract

Purpose: Productivity is crucial for a country's effective economic growth paths. Material productivity is one of the areas examined in determining and improving a country's productivity. This study aims to examine the determinants of Türkiye's material productivity. Methodology: Time series models are used in the empirical analysis of the variables in the study. ADF and PP unit root tests are used to determine the stationarity levels of the variables. Since stationarity is obtained at different levels, the ARDL bounds test method is applied. These results show short-run deviation from equilibrium, and long-run results are obtained using the ARDL bounds test. Findings: According to the ARDL bounds test results, a %1 increase in per capita income and current account balance increases material productivity by %0.03 and %0.02, respectively, while a %1 increase in unemployment decreases material productivity by %0.03 in the 1990-2022 data period in Türkiye. Originality: The literature has increased in recent years with studies on material productivity. In addition to the limited number of material productivity studies in Türkiye, almost no evaluation of the determinants of material productivity exists.

Özet

Amaç: Verimlilik, ülkelerin etkin iktisadi büyüme sürecinde büyük öneme sahiptir. Materyal verimliliği ülkelerin verimliliklerinin belirlenmesinde ve geliştirilmesinde incelenen alanlardan biridir. Bu çalışmada, Türkiye’nin materyal verimliliğinin belirleyicilerinin incelenmesi amaçlanmaktadır. Yöntem: Çalışmada yer alan değişkenlerin ampirik analizinde zaman serisi modelleri kullanılmaktadır. Değişkenlerin durağanlık düzeylerinin belirlenmesinde kullanılan ADF ve PP birim kök testlerine göre farklı düzeyde durağanlık elde edilmiştir. Bu sonuçlar doğrultusunda ARDL sınır testi ile kısa dönemde ortaya çıkan dengeden sapma ve uzun dönemli sonuçlar elde edilmiştir. Bulgular: ARDL sınır testi sonuçlarına göre Türkiye’de 1990-2022 veri döneminde kişi başına düşen gelirde ve cari işlemler dengesinde %1’lik artış materyal verimliliğini sırasıyla %0,03 ve %0,02 oranında artırırken işsizlikteki %1’lik artış materyal verimliliğini %0,03 oranında azalttığı sonucuna ulaşılmıştır. Özgünlük: Literatürde materyal verimliliğine yönelik çalışmaların son yıllarda arttığı görülmektedir. Türkiye’de materyal verimliliği çalışmalarının kısıtlı olmasının yanı sıra materyal verimliliğinin belirleyicilerine ilişkin çalışma yok denecek kadar azdır.

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Cite This Article

Coşkun, U., Aytemiz, S. (2025). Determinants of Material Productivity. Verimlilik Dergisi, Cilt: 59 Sayı: 1, 223–234. https://doi.org/10.51551/verimlilik.1525423

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References (32)

  1. Ateş, Sanlı (2012). “Türkiye İmalat Sanayinde Toplam Faktör Verimliliği ve Uzun Dönem Büyüme İIişkileri”, Turkish Economic Association, Discussion Paper, No. 2012/70, Ankara.
  2. Bahn-Walkowiaki B. ve Steger, S. (2015). “Resource Targets in Europe and Worldwide: An Overview”, Resources, 4, 597-620. https://doi.org/10.3390/resources4030597
  3. Bianchi, M., Valle, I. ve Tapia, C. (2021). “Material Productivity, Socioeconomic Drivers and Economic Structures: A Panel Study for European Regions”, Ecological Economics, 183, 106948. https://doi.org/10.1016/j.ecolecon.2021.106948
  4. Bräuninger M. ve Panenberg, M. (2002). “Unemployment and Productivity Growth: An Empirical Analysis within An Augmented Solow Model”, Economic Modelling, 19, 105-120.
  5. Brigenzu, S. ve Moriguchi, Y. (2002). “Material Flow Analysis”, A Handbook of Industrial Ecology, (Editors: R.U. Ayres ve L.W. Ayres), Edward Edgar Publishing.
  6. Chen, P. ve Semmler, W. (2018). “Short and Long Effects of Productivity on Unemployment”, Open Economies Review, 29, 853-878. https://doi.org/10.1007/s11079-018-9486-z
  7. CSIRO (2024). “Technical Annex for Global Material Flows Database”, CSIRO Australia’s National Science Agency.
  8. Cuñado, J. ve Gracia, F.P. (2005). “Current Account and Productivity: Evidence for Some European Countries”, Journal of Policy Modeling, 27(1), 75-89. https://doi.org/10.1016/j.jpolmod.2004.12.007
  9. Dechezleprêtre, A. ve Sato, M. (2017). “The Impacts of Environmental Regulations on Competitiveness”, Review of Environmental Economics and Policy, 11(2), 183-206.
  10. Dickey, D.A. ve Fuller, W.A. (1981). “Likelihood Ratio Statistic For Autoregressive Time Series with A Unit Root”, Econometrica, 49(4), 1057-1072.
  11. Dünya Bankası. (2024). https://databank.worldbank.org/home, (Erişim Tarihi: 25.06.2024).
  12. Eurostat (2001). “Economy-Wide Material Flow Accounts and Derived Indicators A Methodological Guide”, European Comission, Luxembourg.
  13. Eurostat (2018). “Economy-Wide Material Flow Accounts Handbook”, European Union, Luxemburg. Fernández-Herrero, L. ve Duro, J.A. (2019). “What Causes Inequality in Materail Productivity Between Countries?”, Ecological Economics, 162, 1-16. https://doi.org/10.1016/j.ecolecon.2019.04.007
  14. Flacheneker, F. (2018). “The Causal Impact of Material Productivity on Macroeconomic Competitiveness in the European Union”, Environmental Economics and Policy Studies, 20, 17-46. https://doi.org/10.1007/s10018-016-0180-3
  15. Gan, Y., Zhang, T., Liang, S., Zhao, Z. ve Li, N. (2013). “How to Deal with Resource Productivity Relationships Between Socioeconomic Factors and Resource Productivity”, Journal of Industrial Ecology, 17(3), 440-451. https://doi.org/10.1111/j.1530-9290.2012.00547.x
  16. Global Material Flows Database. (2024). https://www.resourcepanel.org/global-material-flows-database, (Erişim Tarihi: 25.06.2024).
  17. Hannula, M. (2002). “Total Productivity Measurement Based on Partial Productivity Ratios”, International Journal of Production Economies, 78, 57-67. https://doi.org/10.1016/S0925-5273(00)00186-9
  18. Krausmann, F., Schandl, H., Eisenmenger, N., Giljum, S. ve Jackson, T. (2017).” Material Flow Accounting: Measuring Global Material Use for Sustainable Development”, Annual Review of Environment and Resources, 42, 647-675. https://doi.org/10.1146/annurev-environ-102016-060726
  19. Kumar, S. (2006). “Environmentally Sensitive Productivity Growth: A Global Analysis Using Malmquist- Luenberger Index”, Ecological Economics, 56, 280-293. https://doi.org/10.1016/j.ecolecon.2005.02.004
  20. OECD. (2019). “Global Material Resource Outlook to 2060: Economic Drivers and Environmental Consequences”, OECD Publishing, Paris.
  21. OECD. (2001). “Measuring Productivity Measurement of Aggregate and Industry-Level Productivity Growth”, OECD Publishing, Paris.
  22. OECD. (2015). “Material Resources, Productivity and the Environment”, OECD Green Growth Studies, OECD Publishing, Paris. http://dx.doi.org/10.1787/9789264190504-en
  23. Pesaran, M.H., Shin, Y. ve Smith, J.R. (2001). “Bounds Testing Approaches To The Analysis of Level Relationships”, Journal of Applied Econometrics, 16, 289-326.
  24. Phillips, P.C.B. ve Perron, P. (1988), “Testing for a Unit Root in Time Series Regression”, Biometrika, 75(2), 335-346.
  25. Pivoňka, T. (2014). “The Impact of Productivity on Current Account in Central Europe Countries”, Procedia Economics and Finance, 14, 471-480.
  26. Sevüktekin, M. ve Çınar, M. (2015). “Ekonometrik Zaman Serileri Analizi Eviews Uygulamalı”, Dora Yayıncılık, Bursa.
  27. Siggel, E. (2006). “International Competitiveness and Comparative Advantage: A Survey and a Proposal for Measurement”, Journal of Industry, Competition and Trade, 6, 137-159. https://doi.org/10.1007/s10842-006-8430-x
  28. Solow, R.M. (1956). “A Contribution to the Theory of Economic Growth”, The Quarterly Journal of Economics, 70(1), 65-94.
  29. Solow, R.M. (1957). “Technical Change and the Aggregate Production Function”, The Review of Economics and Statics, 39(3), 312-320.
  30. Steinberger, J.K. ve Krausmann, F. (2011). “Material and Energy Productivity”, Environmental Science&Technology, 45,1169- 1176. http://dx.doi.org/10.1021/es1028537
  31. Steinberger, J.K., Krausmann, F., Getzner, M., Schandl, H. ve West, J. (2013). “Development and Dematerialization: An International Study”, PLoS ONE, 8 (10), e70385. https://doi.org/10.1371/journal.pone.0070385
  32. UNEP. (2016). “Global Material Flows and Resource Productivity: Assessment Report for the UNEP International Resource Panel, Paris.