How to assess future agricultural performance under climate change? A case-study on the Veneto region

Agricultural and Food Economics

Laura Onofri¹  Federica Bianchin¹  Vasco Boatto¹ 

[1] Department of Land, Environment, Agriculture and Forestry, University of Padua;

关键词: Climate change;    IPCC;    Cobb-Douglas/translog production function estimation;    Production inputs marginal productivity;   

DOI  :  10.1186/s40100-019-0131-y

来源: DOAJ

【 摘 要 】

Abstract In this paper, we have constructed and tested a simple methodology for assessing and predicting climate change effects on agricultural yields. The methodology follows two steps. First, we econometrically estimate the marginal product of key production inputs (e.g., labor and land), through the estimation of production functions. Then, we predict future agricultural sector performance, by assuming a future with climate-induced changes in the land use and in agricultural labor use, under different IPCC scenarios. We also assume that no dramatic technological change in agriculture production will occur in the near future, so that the selected inputs will present the same marginal product. We assume that the agricultural sector might develop differently under different climate change-induced scenarios and that the use of land and labor will change accordingly. In this way, we are able to compute predictions on the agricultural sector performance in the future, under very different circumstances. We apply the methodology for predicting the sector performance of the Veneto region in 2030. Results differ according to the selected IPCC scenario and consequent input use variations. In the selected case study, for instance, land presents a very high productivity and climate-induced changes in the land use might dramatically (positively and negatively) affect agricultural yields under different IPCC scenarios. In this perspective, the climate change adaptation and mitigation policies and options should primarily aim at the preservation of land productivity in Veneto.

【 授权许可】

Unknown