OECD Üyesi Ülkelerin Çevre Koruma Harcamalarının Etkinliğinin Belirleyicileri: İki Aşamalı Veri Zarflama Analizi Uygulaması

Yıl 2024, , 124 - 138, 30.09.2024

Senem Koç Arslan , Gülsüm Gürler Hazman

https://doi.org/10.70490/gumrukticaretdergisi.1536364

Öz

Günümüzde yaşanan ve giderek ciddileşen çevresel sorunlar devletleri ve uluslararası örgütleri iklim, çevre ve bunların yönetimi ile ilgili çalışmalar yapmaya, tedbirler almaya ve alternatif politikalar üretmeye zorlamaktadır. Bu kapsamda ülkelerin çevre politikalarına bir perspektif sunmak ve politika geliştirmede yol gösterici olması adına çevre koruma harcamalarını incelemek önem arz etmektedir. Bu çalışmada seçili OECD ülkelerinin çevre koruma harcamalarının etkinliğini görmek ve bu etkinliği belirleyen faktörleri tespit etmek üzere iki aşamalı veri zarflama analizi uygulanmış. 30 OECD ülkesinin 2008-2020 yılları arası çevre koruma harcamalarının etkinliğini belirlemek için veri zarflama analizi-süper etkinlik modeli kullanılmıştır. Yapılan ekinlik analizinde kamu çevre koruma harcamaları girdi olarak kullanılırken ülkelerin yenilenebilir enerji üretimi, ormanlık alan miktarı, CO2 emisyonu, P.M. 2.5 partikül madde maruziyeti ve kişi başı GSYH miktarı çıktı olarak kullanılmıştır. Kullanılan çıktılarda karbondioksit emisyonu ve P.M. 2.5 partikül madde maruziyeti istenmeyen çıktı (undesirable output) olarak yer almıştır. İkinci aşamada ise bu etkinlik skorlarının belirleyicilerini ölçmek üzere klasik panel veri analizi uygulanmıştır. Analiz sonucunda ekonomik büyüme arttıkça çevre koruma harcamalarının etkinliği artmakta; nüfus yoğunluğu dikkate alındığında ise, nüfus yoğunluğu arttıkça çevre koruma harcamalarının etkinliği azalmaktadır.

Anahtar Kelimeler

Süper etkinlik, Çevre Koruma Harcamaları, İki Aşamalı Veri Zarflama Analizi, OECD

Determinants of the Effectiveness of Environmental Protection Expenditures of OECD Countries: Two-Stage Data Envelopment Analysis

Öz

Today's environmental problems are becoming increasingly serious, forcing states and international organizations to study climate, environment, and their management, take measures and produce alternative policies. In this context, it is essential to examine environmental protection expenditures to provide a perspective on countries' environmental policies and to guide policy development. In this study, a two-stage data envelopment analysis was applied to see the effectiveness of environmental protection expenditures of selected OECD countries and to identify the factors that determine this effectiveness. Data envelopment analysis-super efficiency model was used to determine the effectiveness of environmental protection expenditures of 30 OECD countries between 2008-2020. In the efficiency analysis, public environmental protection expenditures were used as inputs. In contrast, countries' renewable energy production, forest area amount, CO2 emissions, P.M. 2.5 particulate matter exposure, and per capita GDP were used as outputs. Carbon dioxide emissions and P.M. 2.5 particulate matter exposure were included as undesirable outputs in the outputs used. In the second stage, classical panel data analysis was applied to measure the determinants of these efficiency scores. As a result of the analysis, as economic growth increases, the effectiveness of environmental protection expenditures increases; however, when population density is taken into account, the effectiveness of environmental protection expenditures decreases as population density increases.

Anahtar Kelimeler

Super Efficiency, Environmental Protection Expenditures, Two Stage-DEA, OECD

Kaynakça

• Andersen, P., ve Petersen, N. C. (1993). A Procedure for Ranking Efficient Units in Data Envelopment Analysis. Management Science. 9(10), s. 1261-1264.
• Antonelli, M. A. ve De Bonis, V. (2019). The Efficiency of Social Public Expenditure in European countries: A Two-Stage Analysis. Applied Economics, 51(1), s. 47-60.
• Arltová, M., ve Kot, J. (2023). Do Environmental Taxes Improve Environmental Quality? Evidence from OECD Countries. Prague Economic Papers, 32(1), 26-44.
• Banker, R. D., ve Natarajan, R. (2008). Evaluating Contextual Variables Affecting Productivity Using Data Envelopment Analysis. Operations Research, 56(1), s. 48-58.
• Barrell, A., Dobrzanski, P., Bobowski, S., Siuda, K., ve Chmielowiec, S. (2021). Efficiency of Environmental Protection Expenditures in EU Countries. Energies, 14(24).
• Climate Change Indicators Dashboard. (T.y.). Erişim tarihi 20 Temmuz 2024, https://climatedata.imf.org/
• Chang, C.-P., Dong, M., & Liu, J. (2019). Environmental Governance and Environmental Performance. SSRN Scholarly Paper, Rochester, NY. ,
• Das, P. (2019). Econometrics in Theory and Practice: Analysis of Cross Section, Time Series and Panel Data with Stata 15.1. Springer.
• Deği̇rmenci̇, T., & Aydin, M. (2020). Çevre Koruma Harcamaları ile Gelir Dağılımı ve Ekonomik Büyüme Arasındaki Dinamik İlişkiler: Seçili OECD Ülkeleri için Panel Nedensellik Yaklaşımı. Sosyoekonomi, 28(46), 391-406.
• Doğan, N. (2015). VZA Süper Etkinlik Modelleri ile Etkinlik Ölçümü: Kapadokya’da Faaliyet Gösteren Balon İşletmeleri Üzerine Bir Uygulama. Atatürk Üniversitesi İktisadi ve İdari Bilimler Dergisi, 29(1).
• Ercolano, S., & Romano, O. (2018). Spending for the Environment: General Government Expenditure Trends in Europe. Social Indicators Research, 138(3), 1145-1169.
• Golany, B., ve Roll, Y. (1989). An Application Procedure for DEA. Omega, 17(3), s. 237-250.
• Gómez-Calvet, R., Conesa, D., Gómez-Calvet, A. R., ve Tortosa-Ausina, E. (2020). European Energy Efficiency Evaluation Based on the Use of Super-Efficiency Under Undesirable Outputs in SBM Models. Içinde J. Aparicio, C. A. K. Lovell, J. T. Pastor, ve J. Zhu (Ed.), Advances in Efficiency and Productivity II (ss. 193-208). Springer International Publishing.
• Halkos, G. E., ve Tzeremes, N. G. (2014). Public sector transparency and countries’ environmental performance: A nonparametric analysis. Resource and Energy Economics, 38, s. 19-37.
• He, L., Wu, M., Wang, D., ve Zhong, Z. (2018). A study of the influence of regional environmental expenditure on air quality in China: The effectiveness of environmental policy. Environmental Science and Pollution Research, 25(8), s. 7454-7468.
• Institute, E. (t.y.). About the statistical review. Statistical Review of World Energy. Erişim tarihi: 20 Temmuz 2024, https://www.energyinst.org/statistical-review/about
• Iram, R., Zhang, J., Erdogan, S., Abbas, Q., ve Mohsin, M. (2020). Economics of energy and environmental efficiency: Evidence from OECD countries. Environmental Science and Pollution Research, 27(4), s. 3858-3870.
• Jebali, E., Essid, H., ve Khraief, N. (2017). The analysis of energy efficiency of the Mediterranean countries: A two-stage double bootstrap DEA approach. Energy, 134(C), s. 991-1000.
• Jia, Y. P., ve Liu, R. Z. (2012). Study of the Energy and Environmental Efficiency of the Chinese Economy Based on a DEA Model. Procedia Environmental Sciences, 13, s. 2256-2263.
• Jialu, S., Zhiqiang, M., Mingxing, L., Agyeman, F. O., ve Yue, Z. (2022). Efficiency Evaluation and Influencing Factors of Government Financial Expenditure on Environmental Protection: An SBM Super-efficiency Model Based on Undesired Outputs. Problemy Ekorozwoju, 17(1).
• Karasoy, A., ve Demirtaş, G. (2018). Sağlık Harcamalarının Belirleyicileri Üzerine Bir Uygulama: Çevre Kirliliği ve Yönetişimin Etkilerinin İncelenmesi. İnsan ve Toplum Bilimleri Araştırmaları Dergisi, 7(3).
• Koçak, E., Kınacı, H., ve Shehzad, K. (2021). Environmental efficiency of disaggregated energy R&D expenditures in OECD: A bootstrap DEA approach. Environmental Science and Pollution Research, 28(15), s. 19381-19390.
• Kumar, S., ve Khanna, M. (2009). Measurement of environmental efficiency and productivity: A cross-country analysis. Environment and Development Economics, 14(4), s. 473-495.
• Lacko, R., ve Hajduová, Z. (2018). Determinants of Environmental Efficiency of the EU Countries Using Two-Step DEA Approach. Sustainability, 10(10).
• Lacko, R., Hajduová, Z., ve Markovič, P. (2023). Socioeconomic determinants of environmental efficiency: The case of the European Union. Environmental Science and Pollution Research, 30(11), s. 31320-31331.
• Li, M., ve Wang, Q. (2014). International environmental efficiency differences and their determinants. Energy, 78, s. 411-420.
• Liu, J.-B., ve Zhao, B.-Y. (2023). Study on environmental efficiency of anhui province based on sbm-dea model and fractal theory. Fractals, 31(04), s. 2340072.
• Ma, D., Li, G., ve He, F. (2021). Exploring PM2.5 Environmental Efficiency and Its Influencing Factors in China. International Journal of Environmental Research and Public Health, 18(22).
• McDonald, J. (2009). Using least squares and tobit in second stage DEA efficiency analyses. European Journal of Operational Research, 197(2), s. 792-798.
• Özkan, M., ve Özcan, A. (2018). Veri Zarflama Analizi (VZA) ile Seçilmiş Çevresel Göstergeler Üzerinden Bir Değerlendirme: OECD Performans İncelemesi. Yönetim Bilimleri Dergisi, 16(32).
• Pearce, D., ve Palmer, C. (2001). Public and Private Spending for environmental Protection: A Cross-Country Policy Analysis. Fiscal Studies, 22(4), 403-456.
• Scheel, H. (2001). Undesirable Outputs in Efficiency Valuations. European Journal of Operational Research, 132(2), s. 400-410.
• Shuai, S., ve Fan, Z. (2020). Modeling The Role of Environmental Regulations in Regional Green Economy Efficiency of China: Empirical evidence from super efficiency DEA-Tobit model. Journal of Environmental Management, 261, s. 110227.
• Simar, L., ve Wilson, P. W. (2007). Estimation and inference in two-stage, semi-parametric models of production processes. Journal of Econometrics, 136(1), s. 31-64.
• Simar, L., ve Wilson, P. W. (2011). Two-stage DEA: Caveat emptor. Journal of Productivity Analysis, 36(2), s. 205-218.
• Sun, K., Sun, L., School, T. and F. of, ve Northeast, E. and F. of U. (2016). A Study of Expenditure Efficiency of Fiscal Environment Protection Based on Input-output Ratio A DEA-Tobit Analysis Based on Panel Data of Prefectural-Level Cities of Jilin Province. Taxation and Economy, 5, s. 101-106.
• Tan, J., Su, X., ve Wang, R. (2023). Exploring the Measurement of Regional Forestry Eco-Efficiency and Influencing Factors in China Based on the Super-Efficient DEA-Tobit Two Stage Model. Forests, 14(2).
• Tatoğlu, F. Y. (2020). Panel Veri Ekonometrisi (5. Baskı). Beta Yay.
• Tu, B., Tao, X., ve Guo, N. (2017). Governmental Spending on Public Cultural Services: Efficiency and Influencing Factors Analysis Based on DEA-Tobit. Journal of Service Science and Management, 10(03).
• Wang, P. (2018). Analysis of the efficiency of public environmental expenditure based on data envelopment analysis (DEA)-Tobit model: Evidence from central China. Nature Environment and Pollution Technology, 17, s. 43-48.
• World Development Indicators, DataBank. (t.y.). Erişim tarihi 20 Temmuz 2024, https://databank.worldbank.org/source/world-development-indicators
• Wu, X., ve Guo, J. (2021). Inputs Optimization to Reduce the Undesirable Outputs by Environmental Hazards: A DEA Model with Data of PM2.5 in China. Içinde X. Wu ve J. Guo (Ed.), Economic Impacts and Emergency Management of Disasters in China (ss. 547-580). Springer Nature.
• Yalçin, A. Z., ve Gök, M. (2015). Avrupa Birliği ve Türkiye’de Kamu Çevre Koruma Harcamalarının Analizi. Uluslararası Yönetim İktisat ve İşletme Dergisi, 11(25).
• Yasmeen, R., Zhang, X., Tao, R., ve Shah, W. U. H. (2023). The Impact of Green Technology, Environmental Tax And Natural Resources On Energy Efficiency And Productivity: Perspective of OECD Rule of Law. Energy Reports, 9, s. 1308-1319.
• Zhang, J., Qu, Y., Zhang, Y., Li, X., ve Miao, X. (2019). Effects of FDI on the Efficiency of Government Expenditure on Environmental Protection Under Fiscal Decentralization: A Spatial Econometric Analysis for China. International Journal of Environmental Research and Public Health, 16(14).
• Zhou, P., Ang, B. W., ve Poh, K. L. (2008). A Survey of Data Envelopment Analysis in Energy And Environmental Studies. European Journal of Operational Research, 189(1), s. 1-18.
• Zhou, P., Poh, K. L., ve Ang, B. W. (2016). Data Envelopment Analysis for Measuring Environmental Performance. Içinde S.-N. Hwang, H.-S. Lee, ve J. Zhu (Ed.), Handbook of Operations Analytics Using Data Envelopment Analysis (ss. 31-49). Springer US.
• Zhu, J. (2001). Super-efficiency and DEA sensitivity analysis. European Journal of Operational Research, 129(2), s. 443-455.
• OECD Veri Tabanı, Air pollution exposure. (2023). OECD. Erişim tarihi: 20 Temmuz 2024, https://www.oecd.org/en/data/indicators/air-pollution-exposure.html