University of Sistan and Baluchestan Stable Economy Journal 2821-1049 7 2 2026 07 07 Modeling Economic Growth with Emphasis on the Effects of Climatic Variables (Temperature and Precipitation) Using a Hybrid Approach of Bayesian Model Averaging and Spline Regression Modeling Economic Growth with Emphasis on the Effects of Climatic Variables (Temperature and Precipitation) Using a Hybrid Approach of Bayesian Model Averaging and Spline Regression 169 200 10005 10.22111/sedj.2026.55430.1705 FA Mojtaba Mohammadnejadi Moodi economic development and planning department, faculty of economics and management. University of Tabriz, Tabriz, Iran Seyed Kamal Sadeghi department of economic development and planning, faculty of economics and management, University of Tabriz, Tabriz, Iran Davud Behbudi department of economic development and planning, faculty of economics and management, University of Tabriz, Tabriz, Iran Habib Agajani department of economics, faculty of economics and management, University of Tabriz, Tabriz, Iran Journal Article 2026 05 25 The relationship between climate variability and economic growth—particularly through temperature and precipitation—has become a central topic in growth economics and environmental economics. Empirical evidence indicates that the impact of these climatic variables on economic performance is often non‑linear and non‑uniform over time, implying that traditional linear models may reduce estimation accuracy and overlook important structural information. Accordingly, the main objective of this study is to model economic growth with an emphasis on the roles of temperature and precipitation using a hybrid framework that integrates Bayesian Model Averaging (BMA) with panel spline regression. This exploratory study examines 57 member countries of the Organization of Islamic Cooperation (OIC) over the period 1985–2023. In the first stage, the most efficient modeling strategy was selected from among BMA, TVP‑DMA, TVP‑DMS, and WALS. The in‑sample forecasting results confirmed the superiority of the Bayesian Model Averaging approach. Using this method, twenty robust determinants of economic growth were identified, with economic openness emerging as the most influential variable. The results further showed that while temperature change and precipitation ranked lower in the posterior inclusion probabilities, both exerted a negative and statistically significant effect on economic growth. In the second stage, a three‑knot panel spline regression was employed to examine how the intensity of these effects varies across different regimes. The findings revealed that, unlike many economic variables that follow an inverted‑U pattern, the negative impact of precipitation and temperature on economic growth becomes progressively stronger across subsequent knots The relationship between climate variability and economic growth—particularly through temperature and precipitation—has become a central topic in growth economics and environmental economics. Empirical evidence indicates that the impact of these climatic variables on economic performance is often non‑linear and non‑uniform over time, implying that traditional linear models may reduce estimation accuracy and overlook important structural information. Accordingly, the main objective of this study is to model economic growth with an emphasis on the roles of temperature and precipitation using a hybrid framework that integrates Bayesian Model Averaging (BMA) with panel spline regression. This exploratory study examines 57 member countries of the Organization of Islamic Cooperation (OIC) over the period 1985–2023. In the first stage, the most efficient modeling strategy was selected from among BMA, TVP‑DMA, TVP‑DMS, and WALS. The in‑sample forecasting results confirmed the superiority of the Bayesian Model Averaging approach. Using this method, twenty robust determinants of economic growth were identified, with economic openness emerging as the most influential variable. The results further showed that while temperature change and precipitation ranked lower in the posterior inclusion probabilities, both exerted a negative and statistically significant effect on economic growth. In the second stage, a three‑knot panel spline regression was employed to examine how the intensity of these effects varies across different regimes. The findings revealed that, unlike many economic variables that follow an inverted‑U pattern, the negative impact of precipitation and temperature on economic growth becomes progressively stronger across subsequent knots https://sedj.usb.ac.ir/article_10005_53fa9c3ed6413af1de80208a58a84f73.pdf