The impact of climate policy uncertainty on agricultural investments

Abstract

Purpose: The agricultural sector is strategically important for sustainable development and food security. However, climate change and the increasing physical and political uncertainties that come with it put investments in this sector at risk. This study examines the relationship between climate policy uncertainty and agricultural investments in the USA from 1995-2022. Design/Methodology/Approach: Symmetric and asymmetric causality tests, as well as the Nonlinear ARDL method are used to analyze the relationships between variables. Nonlinear methods allow us to measure asymmetric effects on the dependent variable by evaluating the positive and negative changes of the explanatory variables separately. Findings: No symmetric causality relationship is found between the variables. However, there is a statistically significant asymmetric causality from the positive shock of climate policy uncertainty to the negative shock of agricultural investments. The results of the NARDL model robust this finding. Accordingly, increases in climate policy uncertainty reduce agricultural investments in the long run. Originality/Value: This study fills the gap in the literature by examining the impact of climate policy uncertainty on investments in the agricultural sector. This provides a new perspective to understand the long-term consequences of this relationship in a highly climate-sensitive area such as the agricultural sector.

Keywords

• Agricultural investments
• agriculture
• climate change
• climate policy uncertainty
• NARDL

İklim politikası belirsizliğinin tarımsal yatırımlara etkisi

Abstract

Amaç: Tarım sektörü hem sürdürülebilir kalkınma hem de gıda güvenliği açısından stratejik bir öneme sahiptir. Ancak, iklim değişikliği ve buna bağlı olarak artan fiziksel ve politik belirsizlikler, bu sektördeki yatırımları riske atmaktadır. Bu çalışmanın amacı, ABD’de iklim politikası belirsizliği ile tarımsal yatırımlar arasındaki ilişkiyi 1995-2022 dönemi için incelemektir. Tasarım/Metodoloji/Yaklaşım: İklim politikası belirsizliği ile tarımsal yatırımlar arasındaki ilişkileri analiz etmek için doğrusal olmayan ARDL yöntemi ve asimetrik nedensellik testi kullanılmaktadır. Nonlinear yöntemler, açıklayıcı değişkenlerin pozitif ve negatif değişimlerini ayrı ayrı değerlendirerek bağımlı değişken üzerindeki asimetrik etkileri ölçmeyi sağlamaktadır. Bulgular: NARDL modelinin sonuçlarına göre, iklim politikası belirsizliğindeki artışlar uzun dönemde tarımsal yatırımları azaltmaktadır. Asimetrik nedensellik testi, NARDL modeli tarafından tanımlanan asimetrik ilişkiler için ek kanıt sağlamaktadır. İklim politikası belirsizliğinin pozitif şokundan tarımsal yatırımların negatif şokuna doğru istatistiksel olarak anlamlı bir asimetrik nedensellik vardır. Özgünlük/Değer: Çalışma, iklim politikası belirsizliğinin yatırımlar üzerindeki etkisini tarım sektörü açısından inceleyerek literatürdeki boşluğu doldurmaktadır. Bu, tarım sektörü gibi iklime oldukça duyarlı bir alanda, söz konusu ilişkinin uzun vadeli sonuçlarını anlamaya yönelik yeni bir perspektif sağlamaktadır.

Keywords

• İklim değişikliği
• iklim politikası belirsizliği
• tarım
• tarımsal yatırımlar

References

1. Abdulai, M. G., Ustarz, Y., and Dary, S. K. (2024), “Does global economic and climate policy uncertainty affect private investment? Evidence from sub‐Saharan Africa”, International Social Science Journal, 74, pp.1193-1211. https://doi.org/10.1111/issj.12504
2. Adaman, F., Avcı, D., Kocagöz, U. and Yeniev, G. (2020), İklim Değişikliği Bağlamında Tarımda Dönüşümün Politik Ekolojisi, İstanbul Politikalar Merkezi Sabancı Üniversitesi Stifung Mercator Girişimi.
3. Antón, J., Cattaneo, A., Kimura, S., and Lankoski, J. (2013), “Agricultural risk management policies under climate uncertainty”, Global Environmental Change, 23(6), pp.1726-1736. https://doi.org/10.1016/j.gloenvcha.2013.08.007
4. Assunção, J., and Chein, F. (2016), “Climate change and agricultural productivity in Brazil: future perspectives”, Environment and Development Economics, 21(5), pp.581-602. https://doi.org/10.1017/S1355770X1600005X
5. Aysan, A.F., Cepni, O., and Yousef, T.M. (2024), “Tracking climate policy uncertainty in MENA”, Middle East Council on Global Affairs, Issue brief, September 2024, pp.1-13.
6. Bai, D., Ye, L., Yang, Z., and Wang, G. (2024), “Impact of climate change on agricultural productivity: a combination of spatial Durbin model and entropy approaches”, International Journal of Climate Change Strategies and Management, 16(4), pp.26-48. https://doi.org/10.1108/IJCCSM-02-2022-0016e
7. Borozan, D., and Pirgaip, B. (2025), “Does uncertainty in climate policy play a role in shaping renewable energy use? Evidence from the USA”, Environment, Development and Sustainability, 27, pp.2259–2284. https://doi.org/10.1007/s10668-023-03965-9
8. Butzer, R., Mundlak, Y., and Larson, D. F. (2012), “Measures of fixed capital in agriculture”, Productivity Growth in Agriculture: An International Perspective, Wallingford UK: CABI, pp. 313-334. https://doi.org/10.1079/9781845939212.0

9. Carney, M. (2015), “Breaking the tragedy of the horizon–climate change and financial stability”. Speech given at Lloyd’s of London, 29, pp.1-16.
10. Chan, K. F., and Malik, I. (2022), “Climate policy uncertainty and the cross-section of stock returns”, Available at SSRN 4075528. http://dx.doi.org/10.2139/ssrn.4075528
11. Chen, Z., Zhang, L., and Weng, C. (2023), “Does climate policy uncertainty affect Chinese stock market volatility?”, International Review of Economics & Finance, 84, pp.369-381. https://doi.org/10.1016/j.iref.2022.11.030
12. Climate Policy Uncertainty, available at: www.policyuncertainty.com (accessed 05 January 2025).
13. Dinç, M. (2022), “İklim politikası belirsizliği CO2 emisyonunu etkiler mi? ABD'den ampirik kanıtlar”, Ankara Hacı Bayram Veli Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, 24(3), pp.1077-1108. https://doi.org/10.26745/ahbvuibfd.1105745
14. European Parliament. (2025), “US withdrawal from the Paris Climate Agreement and from the WHO”, European Parliament Think Tank, https://www.europarl.europa.eu/thinktank/en/document/EPRS_ATA(2025)767230 (accessed 01 February 2025).
15. FAOSTAT (2021), Agricultural Investments and Capital Stock 2011–2021 Global and Regional Trends, FAOSTAT Analytical Brief 54, (accessed in https://openknowledge.fao.org/server/api/core/bitstreams/19617d9a-65a5-4c83-b7a6-3e6b7dc7cbf5/content)
16. Feyen, E, Utz, R., Huertas, I.Z., Bogdan, O., and Moon, J.. (2020), “Macro-financial aspects of climate change”. World Bank Policy Research Working Paper, 9109, pp.1-59.
17. Fried, S., Novan, K. M., and Peterman, W. (2021), “The macro effects of climate policy uncertainty”, Finance and Economics Discussion Series 2021-018. Washington: Board of Governors of the Federal Reserve System, pp.1-48. https://doi.org/10.17016/FEDS.2021.018
18. Fuss, S., Szolgayova, J., Obersteiner, M., and Gusti, M. (2008). “Investment under market and climate policy uncertainty”, Applied Energy, 85(8), pp.708-721. https://doi.org/10.1016/j.apenergy.2008.01.005
19. Gavriilidis, K. (2021), “Measuring climate policy uncertainty”, Available at SSRN: https://ssrn.com/abstract=3847388
20. Granger, C. W. and Yoon, G. (2002), “Hidden cointegration”. Department of Economics Working Paper. University of California, San Diego
21. Hacker, R. S. and Hatemi-J, A. (2006), “Tests for causality between integrated variables using asymptotic and bootstrap distributions: Theory and application”, Applied Economics, 38(13), pp.1489-1500. https://doi.org/10.1080/00036840500405763
22. Hashmi, S. M., Yu, X., Syed, Q. R., and Rong, L. (2024), “Testing the Environmental Kuznets Curve (EKC) hypothesis amidst climate policy uncertainty: Sectoral analysis using the novel Fourier ARDL approach”, Environment, Development and Sustainability, 26(7), pp.16503-16522. https://doi.org/10.1007/s10668-023-03296-9
23. Hatemi-J A. (2012), “Asymmetric causality tests with an application”, Empirical Economics, 43, pp.447–456. https://doi.org/10.1007/s00181-011-0484-x
24. He, M., and Zhang, Y. (2022), “Climate policy uncertainty and the stock return predictability of the oil industry”, Journal of International Financial Markets, Institutions and Money, 81, 101675, pp.1-21. https://doi.org/10.1016/j.intfin.2022.101675
25. Heumesser, C., Fuss, S., Szolgayová, J., Strauss, F., and Schmid, E. (2012), “Investment in irrigation systems under precipitation uncertainty”, Water Resources Management, 26, pp.3113-3137. https://doi.org/10.1007/s11269-012-0053-x
26. Hoang, K. (2022), “How does corporate R&D investment respond to climate policy uncertainty? Evidence from heavy emitter firms in the United States”, Corporate Social Responsibility and Environmental Management, 29(4), pp.936-949. https://doi.org/10.1002/csr.2246
27. Khalid, A. A., Mahmood, F., and Rukh, G. (2016), “Impact of climate changes on economic and agricultural value added share in GDP”, Asian Management Research Journal, 1(1), pp.35-48.
28. Kisswani, K. M., Elian, M. I., Lahiani, A., and Mefteh-Wali, S. (2024), “The role of climate policy uncertainty, renewable energy use, and geopolitical risk towards low-carbon emission: Evidence from selected ASEAN countries”, Environmental Economics and Policy Studies, pp.1-29. https://doi.org/10.1007/s10018-024-00430-3
29. Li, J., Kong, T., and Gu, L. (2024), “The impact of climate policy uncertainty on green innovation in Chinese agricultural enterprises”, Finance Research Letters, 62, 105145, pp.1-7. https://doi.org/10.1016/j.frl.2024.105145
30. Li, X., and Su, C. W. (2022), “Does climate policy uncertainty matter for macroeconomic conditions? Evidence from China”, Available at SSRN, (March 26, 2022). http://dx.doi.org/10.2139/ssrn.4319781
31. Lv, W., and Li, B. (2023), “Climate policy uncertainty and stock market volatility: Evidence from different sectors”, Finance Research Letters, 51, 103506, pp.1-6. https://doi.org/10.1016/j.frl.2022.103506
32. Network for Greening the Financial System (NGFS) (2020), Climate Change and Monetary Policy: Initial Takeaways, NGFS Technical Document, June 2020.
33. Neuhoff, K. (2007). “Investment decisions under climate policy uncertainty”, Round Table of Climate Strategies on Investment Uncertainty, Cambridge (2007), pp.1-16.
34. Noailly, J., Nowzohour, L., and Van Den Heuvel, M. (2022), “Does environmental policy uncertainty hinder investments towards a low-carbon economy?”, (No. w30361), National Bureau of Economic Research. https://www.doi.org/10.3386/w30361
35. Nordhaus, W. (2013), İklim Kumarı: Isınan Dünyada Risk, Belirsizlik ve İktisat. (Translate, Cesi Mizrahi), Doğan Kitap, İstanbul.
36. Ortiz-Bobea, A., Ault, T. R., Carrillo, C. M., Chambers, R. G., and Lobell, D. B. (2021), “Anthropogenic climate change has slowed global agricultural productivity growth”, Nature Climate Change, 11(4), pp.306-312. https://doi.org/10.1038/s41558-021-01000-1
37. Ouattara, P. D., Kouassi, E., Egbendewe, A. Y., and Akinkugbe, O. (2018), “Climate uncertainty and agricultural soil conservation investment decisions”, Climate Change Economics, 9(2), pp.1-23. https://doi.org/10.1142/S2010007818500045
38. Ozdemir, D. (2022), “The impact of climate change on agricultural productivity in Asian countries: A heterogeneous panel data approach”, Environmental Science and Pollution Research, 29, pp. 8205-8217. https://doi.org/10.1007/s11356-021-16291-2
39. Pardey, P. G. and Alston, J.M. (2020), “The drivers of US agricultural productivity growth”, 2020 Agricultural Symposium: The Roots of Agricultural Productivity Growth, St. Louis, MO: Fed. Res. Bank Kansas City, pp.5-28.
40. Perron, P. (1989), “The Great Crash, the oil price shock, and the unit root hypothesis”, Econometrica, 57, pp.1361-1401. https://doi.org/10.2307/1913712
41. Perron, P. and Vogelsang, T.J. (1992), “Nonstationarity and level shifts with an application to purchasing power parity”, Journal of Business & Economic Statistics, 10, pp.301–320. https://doi.org/10.2307/1391544
42. Pesaran, M. H., Shin, Y., and Smith, R. J. (2001), “Bounds testing approaches to the analysis of level relationships”, Journal of Applied Econometrics, 16(3), pp.289-326. https://doi.org/10.1002/jae.616
43. Phillips, P. C. and Perron, P. (1988), “Testing for a unit root in time series regression”, Biometrika, 75(2), pp.335-346. https://doi.org/10.1093/biomet/75.2.335
44. Ren, X., Shi, Y., and Jin, C. (2022), “Climate policy uncertainty and corporate investment: evidence from the Chinese energy industry”, Carbon Neutrality, 1, pp.1-14. https://doi.org/10.1007/s43979-022-00008-6
45. Ren, X., Li, J., He, F., and Lucey, B. (2023), “Impact of climate policy uncertainty on traditional energy and green markets: Evidence from time-varying granger tests”. Renewable and Sustainable Energy Reviews, 173, 113058, pp.1-18. https://doi.org/10.1016/j.rser.2022.113058
46. Said, S. E. and Dickey, D. A. (1984), “Testing for unit roots in autoregressive-moving average models of unknown order”, Biometrika, 71(3), pp.599-607. https://doi.org/10.1093/biomet/71.3.599
47. Salisu, A., Omoke, P., and Fadiya, O. (2023), “Climate policy uncertainty and crude oil market volatility”, Energy Research Letters, 4(1), 1-5. https://doi.org/10.46557/001c.38781
48. Shin, Y., Yu, B., and Greenwood-Nimmo, M. (2014), “Modelling asymmetric cointegration and dynamic multipliers in a nonlinear ARDL framework”, Festschrift in honor of Peter Schmidt: Econometric Methods and Applications, pp.281-314.
49. Stevanović, M., Popp, A., Lotze-Campen, H., Dietrich, J. P., Müller, C., Bonsch, M., ... and Weindl, I. (2016), “The impact of high-end climate change on agricultural welfare”, Science Advances, 2(8), e1501452, pp.1-9. https://www.doi.org/10.1126/sciadv.1501452
50. Tian, L. and Li, X. (2023), “Does climate policy uncertainty affect carbon emissions in China? A novel dynamic ARDL simulation perspective”, Humanities and Social Sciences Communications, 10(1), pp.1-10. https://doi.org/10.1057/s41599-023-02102-1
51. Tol, R.S.J. (2019), Climate Economics Economic Analysis of Climate, Climate Change and Climate Policy, Edward Elgar, Cheltenham, UK.
52. United States Department of Agriculture Economic Research Service Database, (accessed 20 January 2025).
53. USDA (2013), Climate Change and Agriculture in the United States: Effects and Adaptation, USDA Technical Bulletin 1935, February 2013.
54. Vander Donckt, M. and Chan, P. (2019), “The new FAO global database on agriculture investment and capital stock”, FAO Statistics Working Paper pp.19-16. http://www.fao.org/3/ca6133en/ca6133en.pdf
55. Wang, K. H., Kan, J. M., Qiu, L., and Xu, S. (2023), “Climate policy uncertainty, oil price and agricultural commodity: From quantile and time perspective”, Economic Analysis and Policy, 78, pp.256-272. https://doi.org/10.1016/j.eap.2023.03.013
56. Wang, M., Song, Y., and Zhang, X. (2024), “Climate risk and green total factor productivity in agriculture: The moderating role of climate policy uncertainty”, Risk Analysis, 2024, pp.1-15. https://doi.org/10.1111/risa.17639
57. Zeng, Q., Ma, F., Lu, X., and Xu, W. (2022), “Policy uncertainty and carbon neutrality: evidence from China”, Finance Research Letters, 47, 102771. pp.1-6. https://doi.org/10.1016/j.frl.2022.102771
58. Zhang, Z., Cheng, S., Wang, C., Song, S., and Feng, Y. (2023), “Climate policy uncertainty and corporate investment efficiency: evidence from China”, Journal of Environmental Planning and Management, pp.1-21. https://doi.org/10.1080/09640568.2023.2276062
59. Zhao, L., Ma, Y., Chen, N., and Wen, F. (2025), “How does climate policy uncertainty shape corporate investment behavior?”, Research in International Business and Finance, 74, 102696, pp.1-12. https://doi.org/10.1016/j.ribaf.2024.102696
60. Zhou, D., Siddik, A. B., Guo, L., and Li, H. (2023), “Dynamic relationship among climate policy uncertainty, oil price and renewable energy consumption—findings from TVP-SV-VAR approach”, Renewable Energy, 204, pp.722-732. https://doi.org/10.1016/j.renene.2023.01.018
61. Zhou, Z., Yu, Z., and Gao, S. (2022), “Climate shocks and farmers’ agricultural productive investment: Resisting risk or escaping production?”, Frontiers in Ecology and Evolution, 10, 895265, pp.1-11. https://doi.org/10.3389/fevo.2022.895265