000236126 001__ 236126
000236126 005__ 20180123004342.0
000236126 037__ $$a333-2016-14586
000236126 041__ $$aen_US
000236126 084__ $$aQ10
000236126 084__ $$aQ12
000236126 084__ $$aQ18
000236126 245__ $$aA Comparison of Stated and Revealed Risk Preferences using Safety-First
000236126 260__ $$c2016
000236126 269__ $$a2016
000236126 270__ $$mssharma3@unl.edu$$pSharma,   Sankalp
000236126 270__ $$mkschoengold2@unl.edu$$pSchoengold,   Karina
000236126 300__ $$a25
000236126 336__ $$aConference Paper/ Presentation
000236126 390__ $$aOur dataset is confidential and the resulting analysis cannot be shared without the permission of USDA-NASS. We are awaiting the completion of their internal review of our work and then the results will be shared.
000236126 500__ $$aOur dataset is confidential and the resulting analysis cannot be shared without the permission of USDA-NASS. We are awaiting the completion of their internal review of our work and then the results will be shared.
000236126 520__ $$aIn this paper we determine the risk preferences of crop producers using the safety-first method. Our methodology is unique, since it utilizes both price and yield risk in the producer’s optimization problem. We then compare the derived preferences with the stated preferences of the producers. The stated preferences are obtained from a lottery-style game designed to elicit producers’ risk preferences. The study is conducted with data from producers in Nebraska, Iowa and South Dakota and the results indicate that there is in fact a relationship between the preferences derived from our structural model and the ones stated by the producers in the game. This is an important result from a policy-making perspective, as it validates the use of behavior elicitation surveys about risk preferences. Such surveys are often easier to administer and less expensive than collecting information on revealed preferences.
000236126 542__ $$fLicense granted by Sankalp Sharma (ssharma3@unl.edu) on 2016-05-26T03:17:06Z (GMT):

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000236126 650__ $$aCrop Production/Industries
000236126 650__ $$aFarm Management
000236126 650__ $$aInstitutional and Behavioral Economics
000236126 650__ $$aProduction Economics
000236126 650__ $$aRisk and Uncertainty
000236126 6531_ $$aRisk analysis
000236126 6531_ $$arisk aversion
000236126 6531_ $$afarm decision-making
000236126 700__ $$aSharma, Sankalp
000236126 700__ $$aSchoengold, Karina
000236126 773__ $$d2016
000236126 8564_ $$s616322$$uhttp://ageconsearch.umn.edu/record/236126/files/Sharma_Schoengold_2016.pdf
000236126 887__ $$ahttp://purl.umn.edu/236126
000236126 909CO $$ooai:ageconsearch.umn.edu:236126$$pGLOBAL_SET
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  Previous issue date: 2016
000236126 982__ $$gAgricultural and Applied Economics Association>2016 Annual Meeting, July 31-August 2, Boston, Massachusetts
000236126 980__ $$a333