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Climate change is a spontaneous process which can be observed over a longer duration of time - around ten to fifteen years. It refers to long-term shifts in temperatures and weather patterns. Climate variation has been identified as the major cause of year-to-year fluctuations in agricultural production in both developed and developing countries. The present paper investigates the impact of climate change on agricultural productivity by employing the stochastic frontier production function proposed by Battese and Coelli (1995) with time varying effect using panel data spanning from 1995 to 2022 for four leading agricultural countries - Brazil, China, India and US. The stochastic frontier production function is based on the Cobb-Douglas production function in which agricultural output is regressed on various inputs along with the climate parameter to capture the technical efficiency effects involved in production function. The estimated results suggest that there is a significant negative impact of climate change on agricultural production as well as its technical efficiency. The correlation results also indicate that climate change has a detrimental impact on agricultural output as well as labour productivity. There is need for policies that jointly address sustainable development and climate change. Three broad categories of action are required - cutting emissions, adapting to climate change and financing for required adjustments. Alternative development pathways such as pursuing institutional changes and stimulating clean technology innovations can affect climate change. While excessive government intervention is inadvisable, if climate change is left unchecked, it will be a drag on the economy. [ABSTRACT FROM AUTHOR]

Transfers, in the form of subsidies, are a government intervention aimed at boosting economic development. These are provided through various instruments that affect production and trade. The Organisation for Economic Co-operation and Development classifies these instruments into categories from most to least distorting. In its strategy of deregulating the world market, it encourages the use of the latter in agricultural policy. Nonetheless, the effect of this recommendation on the value of agricultural production has been poorly researched. This work assessed the relationship between the amounts of support in different agricultural policy instruments used and the value of the production of subsidized agricultural products (VpS) in Mexico, Brazil, and Chile during the period 1995-2020, through a multiple linear regression model with the stepwise backward elimination procedure. The results show that the transfer items that were relevant to explain the VpS in Mexico were: storage, marketing and other physical infrastructure, support based on area and number of animals, extension services, safety and inspection of agricultural products and institutional infrastructure (p< 0.05), in Brazil they were: research, market prices and education (p< 0.05) and in Chile they were: research, storage, marketing and other physical infrastructure, and farm restructuring (p< 0.05). It should be noted that all instruments with a significant effect on the VpS are classified as less distortive, except for the market price support present in Brazil. [ABSTRACT FROM AUTHOR]