The Purdue University-CME Group Ag Economy Barometer improved in April to a reading of 121, which was 8 points higher than a month earlier. Despite this month’s increase, the ag sentiment index remains 32% lower than its April 2021 reading. This month’s modest rise in the barometer was attributable to an improvement in ag producers’ perspective on their current situation as well as what they expect for the future. The Index of Current Conditions rose 7 points to a reading of 120 while the Index of Future Expectations rose 9 points to an index value of 122. Similar to the barometer, both the current conditions and future expectations indices remain well below year ago levels. Ongoing strength in commodity prices appeared to be responsible for the modest sentiment improvement, although producers’ concerns about both rising input costs and their difficulties in procuring inputs continues to hold back sentiment. The Purdue University-CME Group Ag Economy Barometer sentiment index is calculated each month from 400 U.S. agricultural producers’ responses to a telephone survey. This month’s survey was conducted from April 18-22, 2022.
6 pages., Authors examined the social welfare implications of introducing GM crops for GM and non-GM producers as well as for GM and non-GM consumers. Results indicated that "the adoption of GM technologies based on market incentives may actually reduce societal welfare. This adoption can be seen as immiserizing technological change."
Qaim, Matin (author), Kathage, Jonas (author), Kassie, Menale (author), and Shiferaw, Bekele (author)
Format:
Paper
Publication Date:
2013-02
Published:
Tanzania
Location:
Agricultural Communications Documentation Center, Funk Library, University of Illinois Box: 186 Document Number: D00902
Notes:
GlobalFood Discussion Paper No. 19, RTG 1666 GlobalFood, Transformation of global agri-food systems: trends, driving forces and implications for developing countries, Georg-August-University of Gottingen, Gottingen, Germany, February 2013. 28 pages.
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.
20 pgs, Off-farm employment opportunities are thought to have an effect on farm exit rates, though evidence on the sign of this effect has been mixed. Examining this issue in the context of Japanese agriculture, we find that farm exits are related to off-farm income as a share of household income, and more specifically to the nature of off-farm work. Two econometric models are developed: a hierarchical Bayesian linear model and a hierarchical Bayesian Poisson model. Both models perform well in predicting exit rates across the towns and prefectures of Japan.
