Abstract:

Climate change may have detrimental effects on different sectoral growth in global economy and according to the Intergovernmental Panel on Climate Change, the impacts of climate change will be more vigorous in the coming years. The climatic and non-climatic driving forces behind the economic sectoral performances involve short- and long-run interconnections among variables. This study attempts to investigate the effect of climatic factors (temperature and precipitation) along with non-climatic factors, including foreign direct investment (FDI), human capital index (HCI), natural capital (NC), and information and communication technology (ICT) on three major sectors of the economy (agricultural sector, industrial sector, and service sector) through non-linear model framework by employing cross-sectionally augmented autoregressive distributed lag (CS-ARDL) estimation technique. It considers a panel of 56 selected countries from different income groups, including high-income countries, upper-middle-income countries, lower-middle-income countries, and low-income countries, covering the period 1985-2022. The confirmation of slope heterogeneity, cross-sectional dependence, stationarity, and cointegration among variables lends support to the robustness of results. The augmented mean group (AMG) robustness test was applied to check robustness and the results were found mostly consistent with estimation method. The results revealed that upper-middle-income countries are more vulnerable to extreme temperatures compared to high-income countries. The results also confirmed an inverted U-shaped relationship between each sector’s output and precipitation in upper-middle-income countries. In contrast, for upper-middle-income, lower-middle-income, and low-income countries, this relation exists in industrial sector only in long run. This indicates that precipitation is initially beneficial for production activities. However, beyond a certain threshold of precipitation, this trend reverses, i.e., the output of the economic sectors tends to decline. Furthermore, there is no supporting evidence that confirms a short-run non-linear relation between precipitation and agricultural yields. In upper-middle-income countries, the results confirmed that FDI is a driving factor behind both agricultural sector and service sector in long run while short-run results indicated a negative association but insignificant. This study also showed that in long run, an increase in HCI contributes to improving the output of the three sectors for high-income countries. The empirical findings provide valuable insights for policy-makers and governments to formulate coherent adaptation and mitigation strategies, thereby accelerating the transition of sectoral productivity from low to high levels in the sample countries.

Key words: Climate change, Agricultural sector, Industrial sector, Service sector, Foreign direct investment (FDI), Cross-sectionally augmented autoregressive distributed lag (CS-ARDL)