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Biases in Farm-Level Yield Risk Analysis due to Data Aggregation

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  • Finger, Robert

Abstract

We investigate biases in farm-level yield risk analysis caused by data aggregation from the farm-level to regional and national levels using the example of Swiss wheat and barley yields. The estimated yield variability decreases significantly with increasing level of aggregation, with crop yield variability at the farm-level being up to 2.38 times higher than indicated from national data. Our results show furthermore that inference on shape parameters based on aggregated data might be misleading. Using an example of farm yield insurance, we show that using crop yield variability estimates from aggregated levels leads to erroneous insurance contract specifications. Dieser Beitrag untersucht unter Verwendung Schweizer Ertragsdaten für Weizen und Gerste potentielle Fehler, die bei der Analyse von Ertragsrisiken durch die Aggregation von Betriebsdaten auf regionalen oder nationalen Niveaus entstehen. Die geschätzte Ertragsvariabilität sinkt signifikant mit einem steigenden Aggregationsniveau, wobei die Ertragsvariabilität auf Betriebsebene bis zu 2,38-mal grösser seien kann, als dies durch nationale Daten angedeutet wird. Des Weiteren zeigen die Resultate, dass Rückschlüsse über Schiefe und Kurtosis der Erträge, basierend auf aggregierten Daten, irreführend sein können. Mittels eines Versicherungsbeispiels wird zudem gezeigt, dass die Ausgestaltung einer Versicherung, basierend auf aggregierten Daten, zu falschen Ergebnissen führen kann.

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  • Finger, Robert, 2012. "Biases in Farm-Level Yield Risk Analysis due to Data Aggregation," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 61(01), pages 1-14, February.
    • Handle: RePEc:ags:gjagec:199770
    DOI: 10.22004/ag.econ.199770
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    2. Pelka, Niels & Mußhoff, Oliver, 2015. "Das Risikoreduzierungspotenzial von Wetterindexversicherungen im Agribusiness – Die Bedeutung des Aggregationsniveaus von Ertragszeitreihen," German Journal of Agricultural Economics, Humboldt-Universitaet zu Berlin, Department for Agricultural Economics, vol. 64(02), June.
    3. Schmitt, Jonas & Offermann, Frank & Söder, Mareike & Frühauf, Cathleen & Finger, Robert, 2022. "Extreme weather events cause significant crop yield losses at the farm level in German agriculture," Food Policy, Elsevier, vol. 112(C).
    4. Duden, C. & Offermann, F., 2019. "Farmers' risk exposition and its drivers," 171st Seminar, September 5-6, 2019, Zürich, Switzerland 333722, European Association of Agricultural Economists.
    5. Djanibekov, Utkur & Finger, Robert, 2015. "The effects of variability under farm land consolidation process: A perspective of cotton-growing farmers in Uzbekistan," 2015 Conference, August 9-14, 2015, Milan, Italy 211829, International Association of Agricultural Economists.
    6. Christopher N. Boyer & B. Wade Brorsen & Emmanuel Tumusiime, 2015. "Modeling skewness with the linear stochastic plateau model to determine optimal nitrogen rates," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 1-10, January.
    7. Dörschner, Till & Musshoff, Oliver, 2013. "Does the risk attitude influence the farmers' willingness to participate in agri-environmental measures? – A normative approach to evaluate ecosystem services," 53rd Annual Conference, Berlin, Germany, September 25-27, 2013 156112, German Association of Agricultural Economists (GEWISOLA).
    8. Dörschner, T. & Mußhoff, O., 2014. "Does the Risk Attitude Influence and Farmers’ Willingness to Participate in Agri-Environmental Measures? – A Normative Approach to Evaluate Ecosystem Services," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 49, March.
    9. Castañeda-Vera, Alba & Garrido, Alberto, 2017. "Evaluation of risk management tools for stabilising farm income under CAP 2014-2020," Economia Agraria y Recursos Naturales, Spanish Association of Agricultural Economists, vol. 17(01), June.
    10. ZGAJNAR, Jaka, 2016. "Simulation Model Based On Iacs Data; Alternative Approach To Analyse Sectoral Income Risk In Agriculture," Review of Agricultural and Applied Economics (RAAE), Faculty of Economics and Management, Slovak Agricultural University in Nitra, vol. 19(1), pages 1-9, April.
    11. Djanibekov, Utkur & Finger, Robert, 2018. "Agricultural risks and farm land consolidation process in transition countries: The case of cotton production in Uzbekistan," Agricultural Systems, Elsevier, vol. 164(C), pages 223-235.

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