Seyranlioglu, OnurHan, AysegulAydinbas, Gokcen2025-11-152025-11-1520252619-914910.18016/ksutarimdoga.vi.1652184https://doi.org/10.18016/ksutarimdoga.vi.1652184https://hdl.handle.net/20.500.14517/8528This study aims to examine the impact of climate change and environmental degradation on agricultural credit utilization using annual data for the period 1988-2023 in T & uuml;rkiye. In this paper, stationarity is tested using the Fourier KPSS stationarity test, long-run relationships are analyzed using the Fourier Shin cointegration method, and long-run coefficients are estimated using the Fourier FMOLS method. Finally, the Fourier Toda-Yamamoto causality test is used to explore causal relationships between variables. The findings show that increases in climate change and environmental degradation reduce agricultural credit utilization. On the other hand, agricultural value added, arable agricultural area, and population growth are found to increase agricultural credit utilization. According to the causality analysis results, a unidirectional causality relationship was found from agricultural credit utilization to climate change, while bidirectional causality relationships were found between agricultural credit utilization and agricultural value added and population growth. The results obtained emphasize the importance of restructuring financial policies for the agricultural sector in consideration of environmental and climatic risks and provide an important contribution to the very limited literature by addressing this interaction with Fourier-based econometric analyses.eninfo:eu-repo/semantics/openAccessClimate ChangeEnvironmental DegradationAgricultural CreditFourier ApproximationArticleN/AN/A28615161530WOS:001600511500010