25pgs, We combine farm accounting data with high-resolution meteorological data, and climate scenarios to estimate climate change impacts and adaptation potentials at the farm level. To do so, we adapt the seminal model of Moore and Lobell (2014) who applied panel data econometrics to data aggregated from the farm to the regional (subnational) level. We discuss and empirically investigate the advantages and challenges of applying such models to farm-level data, including issues of endogeneity of explanatory variables, heterogeneity of farm responses to weather shocks, measurement errors in meteorological variables, and aggregation bias. Empirical investigations into these issues reveal that endogeneity due to measurement errors in temperature and precipitation variables, as well as heterogeneous responses of farms toward climate change may be problematic. Moreover, depending on how data are aggregated, results differ substantially compared to farm-level analysis. Based on data from Austria and two climate scenarios (Effective Measures and High Emission) for 2040, we estimate that the profits of farms will decline, on average, by 4.4% (Effective Measures) and 10% (High Emission). Adaptation options help to considerably ameliorate the adverse situation under both scenarios. Our results reinforce the need for mitigation and adaptation to climate change.
Hayden, Victor F. (author) and Agricultural Publishers Association, Chicago, Illinois.
Format:
Letter
Publication Date:
1932-03-03
Published:
USA
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Document Number: C36835
Notes:
Agricultural Publishers Association Records, Series No. 8/3/80, Box 11, Special Bulletin No. 22. 3 pages., Letter from the APA executive secretary to the USDA Office of Information suggests giving prominence to the more favorable phases of the agricultural situation. Sends a rewritten news release, as example.
