Sera Gazı Risklerinin Pay Piyasası Getirisine Etkisi: G7 Ülkeleri Üzerine Bir Uygulama

Öz

Bu çalışmada sera gazı risklerinin pay piyasa getirisine etkisi araştırılmıştır. Sera gazı olarak karbondioksit, metan ve azot gazı salınımları alınırken; pay piyasası olarak dünyanın en gelişmiş yedi ülkesi olarak ifade edilen G7 ülkeleri pay piyasası gösterge endeksleri baz alınmıştır. Veri kısıtı dolayısıyla çalışmanın kapsamı 2000-2020 dönem aralığı olarak belirlenmiş ve panel veri analiz yöntemi uygulanmıştır. Çalışmada sırasıyla içsellik ve çoklu doğrusallık sorunları, yatay kesit bağımlılığı ve homojenlik/heterojenlik testleri sınanmış, elde edilen bulgular doğrultusunda birim kök analizi yapılarak model tahmini gerçekleştirilmiştir. Yapılan analizler sonucunda çalışmada kullanılan değişkenler arasında içsellik ve çoklu doğrusal bağlantı sorunlarının olmadığı, yatay kesit bağımlılığının olduğu, değişkenlerin düzeyde durağan olduğu I(0), panelde otokorelasyon sorununun olduğu ve tahmin edilecek modelde sabit etkiler modeli ile tahminleme yapmanın uygun olduğu tespit edilmiştir. Otokorelasyon sorununu çözen dirençli model tahmincisi ile yapılan tahminleme sonucunda karbondioksit ve metan gazının pay piyasa getirisini negatif yönde etkilediği, azot gazının ise pay piyasa getirisini pozitif yönde etkilediği tespit edilmiştir. Bu bulgular, yatırımcıların iklim değişikliğine ilişkin endişelerini sera gazı emisyonları aracılığıyla hisse senedi piyasalarına yansıttıklarını göstermektedir.

Anahtar Kelimeler

• Pay Piyasa Getirisi
• Sera Gazı
• Panel Veri Analizi

The Impact of Greenhouse Gas Risks on Stock Market Returns: An Application on G7 Countries

Öz

This study investigates the impact of greenhouse gas risks on stock market returns. While carbon dioxide, methane, and nitrogen gas emissions are taken as greenhouse gases; the stock market benchmark indices of the G7 countries, which are defined as the seven most developed countries in the world, are taken as the basis for the stock market. Due to data limitations, the scope of the current study has been set as the 2000-2020 time period and the panel data analysis method has been applied. In this study, endogeneity and multicollinearity problems, cross-sectional dependence, and homogeneity/heterogeneity tests are tested respectively, and the model is estimated by performing unit root analysis in line with the findings obtained. The results of the analyses indicate that there are no endogeneity and multicollinearity problems among the variables used in the study, there is cross-sectional dependence, the variables are stationary at level I(0), there are problems of autocorrelation in the panel and it is appropriate to estimate the model with the fixed effects model. As a result of the estimation with the robust model estimator that solves the problem of autocorrelation, it is found that carbon dioxide and methane have a negative effect on stock market return, while nitrogen gas has a positive effect on stock market return. These findings suggest that investors reflect their concerns about climate change to stock markets through greenhouse gas emissions.

Anahtar Kelimeler

• Stock Market Returns
• Greenhouse Gas
• Panel Data Analysis

Kaynakça

1. Aharon, D. Y., Baig, A. S., Jacoby, G. and Wu, Z. (2024). Greenhouse gas emissions and the stability of equity markets. Journal of International Financial Markets, Institutions & Money, 92, 1-20. https://doi.org/10.1016/j.intfin.2024.101952
2. Antoniuk, Y. and Leirvik, T. (2024). Climate change events and stock market returns. Journal of Sustainable Finance & Investment, 14(1), 42-67. https://doi.org/10.1080/20430795.2021.1929804
3. Bai, J. and NG, S. (2004). A PANIC attack on unit roots and cointegration. Econometrica, 72(4), 1127-1177. https://doi.org/10.1111/j.1468-0262.2004.00528.x
4. Baltagi, B. H. (2005). Econometric analysis of panel data (3rd edition). West Sussex: Wiley. Retrieved from https://library.wbi.ac.id/repository/27.pdf
5. Baltagi, B. H., and Li, Q. (1991). A joint test for serial correlation and random individual effects. Statistics & Probability Letters, 11(3), 277-280. https://doi.org/10.1016/0167-7152(91)90156-L
6. Barbera-Marine, M. G., Fabregat-Aibar, L., Neumann-Calafell, A. M. and Terceño, A. (2023). Climate change and stock returns in the European market: An environmental intensity approach. Journal of Environmental Management, 345, 1-7. https://doi.org/10.1016/j.jenvman.2023.118927
7. BMJ (2023). COP28 decision to “transition away” from fossil fuels is hailed as milestone but loopholes are decried. Retrieved from https://www.bmj.com/content/383/bmj.p2941
8. Bollen, N. (2007). Mutual fund attributes and investor behavior. Journal of Financial and Quantitative Analysis, 42(3), 683–708. Retrieved from https://www.jstor.org/stable/27647316

9. Born, B. and Breitung, J. (2016). Testing for serial correlation in fixed-effects panel data models. Econometric Reviews, 35(7), 1290-1316. https://doi.org/10.1080/07474938.2014.976524
10. Breusch, T. S. and Pagan, A. R. (1980) The lagrange multiplier test and its application to model specification in econometrics. Review of Economic Studies, 47, 239-253. https://doi.org/10.2307/2297111
11. Bui, H. M., Nguyen, S. V., Huynh, A. T., Bui, H. N., Nguyen, H. T. T., Pern, Y. S., Bui, X. T. and Nguyen, H. T. (2023). Correlation between nitrous oxide emissions and economic growth in Vietnam: An autoregressive distributed lag analysis. Environmental Technology & Innovation, 29, 1-12. https://doi.org/10.1016/j.eti.2022.102989
12. Cao, M. and Wei, J. (2005). Stock market returns: A note on temperature anomaly. Journal of Banking & Finance, 29, 1559-1573. https://doi.org/10.1016/j.jbankfin.2004.06.028
13. Chang, C. L., Ilomäki, J., Laurila, H. and McAleer, M. (2020). Causality between CO2 emissions and stock markets. Energies, 13, 1-14. https://doi.org/10.3390/en13112893
14. Choi, I. (2002). Combination unit root tests for cross-sectionally correlated panels. Hong Kong University of Science and Technology Publisher. Retrieved from https://hdl.handle.net/1783.1/129
15. Cooley, D. (2012). Return periods and return levels under climate change. A. AghaKouchak, K. Hsu, D. Easterling, S. Schubert, and S. Sorooshian (Ed.), Extremes in a changing climate detection, analysis and uncertainty, (pp. 97-114). Springer Link. https://doi.org/10.1007/978-94-007-4479-0_4
16. Faccini, R., Matin, R. and Skiadopoulos, G. (2021). Are climate change risks priced in the U.S. stock market?. Danmarks National Bank-Working Paper, 169, 1-52. Retrieved from: https://www.econstor.eu/handle/10419/245990
17. Freeman, R. E. (1984). Strategic management: A stakeholder approach. Pitman Publisher. https://doi.org/10.1017/CBO9781139192675
18. Hlavackova, C. (2022) The relationship between carbon emissions and stock market performance (Bachelor Thesis, University of Amsterdam, Amsterdam Business School BSc Business Administration Specialisation Finance). Retrieved from: https://scripties.uba.uva.nl/
19. Jiang, R. and Weng, C. (2020). Climate change risk and agriculture-related stocks. S&P Global Market Intelligence, 0(0), 1-35. http://dx.doi.org/10.2139/ssrn.3506311
20. Kim, J. H. (2019). Multicollinearity and misleading statistical results. Korean Journal of Anesthesiology, 72(6), 558-569. https://doi.org/10.4097/kja.19087
21. Li, C., Liu, Y. and Pan, L. (2024). A study of impact of climate change on the U.S. stock market as exemplified by the NASDAQ 100 index constituents. Scientific Reports, 14(15468), 1-9. https://doi.org/10.1038/s41598-024-66109-7
22. Liesen, A., Figge, F., Hoepner, A. and Patten, D. M. (2017). Climate change and asset prices: Are corporate carbon disclosure and performance priced appropriately?. Journal of Business Finance & Accounting, 44(1-2), 36-52. https://doi.org/10.1111/jbfa.12217
23. Mátyás, L. and Sevestre, P. (1996). The econometrics of panel data. Kluwer Academic Publishers. Retrieved from: https://link.springer.com/book/10.1007/978-94-009-0137-7
24. Menard, S. (1995). Applied logistic regression analysis (2nd Edition). Thousand Oaks: Sage Publications. Retrieved from https://www.google.com.tr/books/edition/Applied_Logistic_Regression_Analysis/ EAI1QmUUsbUC?hl=en&gbpv=1&pg=PP7&printsec=frontcover
25. Mosca, F. and Civera, C. (2017). The evolution of CSR: An integrated approach. Symphonya Emerging Issues in Management, 1, 16-35. https://doi.org/10.4468/2017.1.03mosca.civera
26. Noh, J. H. and Park, H. (2023). Greenhouse gas emissions and stock market volatility: An empirical analysis of OECD countries. International Journal of Climate Change Strategies and Management, 15(1), 58-80. https://doi.org/10.1108/IJCCSM-10-2021-0124
27. Nur, T. and Korkmaz, T. (2022). Serbest nakit akışları, temsil maliyetleri ve firma performansı arasındaki ilişki: BİST’te işlem gören firmalar üzerine bir araştırma. Finans Ekonomi ve Sosyal Araştırmalar Dergisi, 7(1), 103-120. https://doi.org/10.29106/fesa.1072926
28. Pagnottoni, P., Spelta, A., Flori, A. and Pammolli, F. (2022). Climate change and financial stability: Natural disaster impacts on global stock markets. Physica A, 599, 1-23. https://doi.org/10.1016/j.physa.2022.127514
29. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics, 22, 265–312. https://doi.org/10.1002/jae.951
30. Pesaran, M. H. and Yamagata, T. (2008). Testing slope homogeneity in large panels. Journal of Econometrics, 142, 50-93. https://doi.org/10.1016/j.jeconom.2007.05.010
31. Phillips, P. C. B. and Sul, D. (2003). Dynamic panel estimation and homogeneity testing under cross section dependence. Econometrics Journal, 6(1), 217-259. https://doi.org/10.1111/1368-423X.00108
32. Sakın, I. and Kefe, I. (2023). The impact of carbon emissions on firms’ financial performance: An application in BIST sustainability index. Trends in Business and Economics, 38(1), 39-47. Retrieved from: https://dergipark.org.tr/en/pub/trendbusecon/issue/83049/1429652
33. Salehi, M., Fahimifard, S. H., Zimon, G., Bujak, A. and Sadowski, A. (2022). The effect of co2 gas emissions on the market value, price and shares returns. Energies, 15, 1-17. https://doi.org/10.3390/en15239221
34. Smith, S. S. (2015). Accounting, governance and stakeholder reporting, and economic. Journal of Applied Business and Economics, 17(2), 76-80. Retrieved from https://www.proquest.com/docview/1726797465?pq-origsite=gscholar&fromopenview=true&source type=Scholarly%20Journals
35. Tabachnick, B. G., and Fidell, L. S. (2001). Using multivariate statistics. Allyn and Bacon Publisher. Retrieved from https://www.google.com.tr/books/edition/Using_Multivariate_Statistics/lVtqAAAAMAAJ?hl=en &gbpv=0&bsq=Using%20multivariate%20statistics%202001
36. Tekin, B. (2019). Turizme dayalı büyüme modeli ile ekonomiye dayalı turizm büyümesi modelinin test edilmesi: Panel veri analizi. Busıness & Management Studies: An Internatıonal Journal, 7(1), 118-134. http://dx.doi.org/10.15295/bmij.v7i1.1049
37. Topaloglu, E. E. (2018). Bankalarda finansal kırılganlığı etkileyen faktörlerin panel veri analizi ile belirlenmesi. Eskişehir Osmangazi Üniversitesi İktisadi ve İdari Bilimler Dergisi, 13(1), 15-38. https://doi.org/10.17153/oguiibf.344856
38. United Nations (2015). Climate Change – UNFCCC. Retrieved from https://unfccc.int/process-and-meetings/the-paris-agreement
39. United Nations (2020). The intergovernmental panel on climate change. Retrieved from https://www.ipcc.ch/2020/
40. United Nations (2023). Climate Change Conference – COP28. Retrieved from https://www.cop28.com/en/
41. Venturini, A. (2022). Climate change, risk factors and stock returns: A review of the literature. International Review of Financial Analysis, 79, 1-18. https://doi.org/10.1016/j.irfa.2021.101934
42. Vlady, S. (2015). The effect of climate change on Australian stock equity returns. International Journal in Economics and Business Administration, 3(3), 88-109. https://doi.org/10.35808/ijeba/80
43. Wang, L., Li, S., and Gao, S. (2014). Do greenhouse gas emissions affect financial performance? – An empirical examination of Australian public firms. Business Strategy and the Environment, 23, 505-519. https://doi.org/10.1002/bse.1790
44. Whittaker, M. (2000). Global climate change: Uncovering hidden investment risk and opportunity. The Geneva Papers on Risk and Insurance. Issues and Practice, 25(4), 619-628. Retrieved from https://www.jstor.org/stable/41952555
45. Wilson, M. (2003). Corporate sustainability: What is it and where does it come from? Ivey Business Journal. Retrieved from https://iveybusinessjournal.com/ibj_issue/march-april-2003/
46. World Bank. (2024). World Bank Open Data. Retrieved from https://data.worldbank.org/
47. World Resources Institute (2004). The greenhouse gas protocol. Retrieved from https://ghgprotocol.org/sites/default/files/standards/ghg-protocol-revised.pdf
48. Yusuf, A. M., Abubakar, A. B. and Mamman, S. O. (2020). Relationship between greenhouse gas emission, energy consumption, and economic growth: evidence from some selected oil-producing African countries. Environmental Science and Pollution Research, 27, 15815-15823. https://doi.org/10.1007/s11356-020-08065-z
49. Ziegler, A., Busch, T. and Hoffmann, V. H. (2011). Disclosed corporate responses to climate change and stock performance: An international empirical analysis. Energy Economics, 33, 1283-1294. https://doi.org/10.1016/j.eneco.2011.03.007