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This study examines drought from the perspective of farm businesses in order to develop new outcome-based drought indicators. An empirical analysis of Australian farms is presented drawing on data from the Australian Agricultural and Grazing Industry Survey and the related farmpredict micro-simulation model. Farmer drought self-assessment data are used to identify factors influencing farmer perceptions of drought beyond seasonal weather conditions. The results suggest farmers have updated their perception of drought over time to account for long-term shifts in the Australian climate. While instructive, farmer self-assessments cannot be used as drought indicators in practice due to moral hazard issues. In this study, the farmpredict model is applied to develop an objective outcome-based drought indicator for Australian farms. This indicator measures the effects of seasonal weather conditions on farm profits accounting for both production and price impacts. Compared with simple meteorological indexes, this new indicator is more strongly correlated both with actual farm outcomes and with farmers’ own drought assessments. In future, this farm drought indicator could help to address asymmetric information (moral hazard and adverse selection) problems which constrain both government drought programs and private drought insurance markets.
This study examines drought from the perspective of farm businesses in order to develop new outcome-based drought indicators. An empirical analysis of Australian farms is presented drawing on data from the Australian Agricultural and Grazing Industry Survey and the related farmpredict micro-simulation model. Farmer drought self-assessment data are used to identify factors influencing farmer perceptions of drought beyond seasonal weather conditions. The results suggest farmers have updated their perception of drought over time to account for long-term shifts in the Australian climate. While instructive, farmer self-assessments cannot be used as drought indicators in practice due to moral hazard issues. In this study, the farmpredict model is applied to develop an objective outcome-based drought indicator for Australian farms. This indicator measures the effects of seasonal weather conditions on farm profits accounting for both production and price impacts. Compared with simple meteorological indexes, this new indicator is more strongly correlated both with actual farm outcomes and with farmers’ own drought assessments. In future, this farm drought indicator could help to address asymmetric information (moral hazard and adverse selection) problems which constrain both government drought programs and private drought insurance markets.
Defining drought from the perspective of Australian farmers
2022
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
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