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The Market for Used Cars: A New Test of the Lemons Model AgEcon
Emons, Winand; Sheldon, George.
The lemons model assumes that owners of used cars have an informational advantage over potential buyers with respect to the quality of their vehicles. Owners of bad cars will try to sell them to unsuspecting buyers while owners of good cars will hold on to theirs. Consequently, the quality of traded automobiles should be sub-average. In contrast to previous work, the following paper tests both the assumption of informational asymmetry and the prediction of sub-average traded car quality using a sample consisting of all 1985 cars registered in the Swiss canton of Basle-City over the period 1985-1991. Our data support both the assumption and the prediction of the lemons model. The lemons problem does not appear to be widespread, however. Das "Lemons"-Modell...
Tipo: Working or Discussion Paper Palavras-chave: Adverse Selection; Used Car Market; Duration Models; Marketing; C41; D82; L15; L62.
Ano: 2002 URL: http://purl.umn.edu/26353
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Should Basic Underwriting Rules be Applied to Average Crop Revenue Election and Supplemental Revenue? AgEcon
Barnaby, Glenn Arthur, Jr..
This paper considers methods to adversely select on Average Crop Revenue Election (ACRE) and Supplemental Revenue (SURE). In the case of winter wheat, farmers had a large amount of a priori yield and price information before electing 2009 ACRE. Prior to the August 14 sign-up for ACRE, wheat was 3 months into the marketing year. In most years nearly half of the national average price is determined in the first 3 months of the marketing year. With this available information it was clear that Oklahoma, Texas, and Washington wheat would collect the maximum or near the maximum ACRE payment, while there was little chance that ACRE would pay on Colorado wheat.
Tipo: Journal Article Palavras-chave: Adverse Selection; Average Crop Revenue Election; Crop Insurance; Supplemental Revenue; Agribusiness; Agricultural and Food Policy; Agricultural Finance; Crop Production/Industries; Farm Management; Political Economy; Risk and Uncertainty; Q18.
Ano: 2010 URL: http://purl.umn.edu/92590
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OPTIONAL UNIT POLICY IN CROP INSURANCE AgEcon
Shaik, Saleem; Atwood, Joseph A..
Utilizing ordered logit we examine the presence of two kinds of asymmetric information-adverse selection (intertemporal variability) and moral hazard (interspatial and/or residual variability) as revealed by the choice of optional units in Federal crop insurance utilizing Risk Management Agency's 1996-2000 cotton yield and loss data files. Further, a tobit model is estimated to examine the factors explaining the loss cost ratio from Risk Management Agency perspective. Potential costs of adverse selection and/or moral hazard in optional unit provision are estimated to be as high as $180 million in US cotton over the 1996-2000 period. Keywords: Adverse Selection, Moral Hazard, Optional Unit Policy, Crop Insurance, U.S. Cotton, Logit and Tobit models.
Tipo: Conference Paper or Presentation Palavras-chave: Adverse Selection; Moral Hazard; Optional Unit Policy; Crop Insurance; U.S. Cotton; Logit and Tobit models.; Risk and Uncertainty.
Ano: 2002 URL: http://purl.umn.edu/19741
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Role of Panel Analysis in Identifying Asymmetric Information with Optional Unit Provision in Federal Crop Insurance AgEcon
Shaik, Saleem.
This paper has a two-fold contribution, first we demonstrate the relationship of spatial, temporal and residual yield risk estimated from a two-way panel random effects model to asymmetric information with an optional unit provision in the federal crop insurance program. Second, the yield risk components are incorporated in a discrete choice model to examine the presence of asymmetric information due to potential yield switching with optional unit provisions. Empirical application to 1998 U.S. cotton crop insurance data reveals the presence of asymmetric information with optional unit provisions.
Tipo: Report Palavras-chave: Adverse Selection; Moral Hazard; Optional Unit Policy; Crop Insurance; U.S. Cotton; Crop Production/Industries; Demand and Price Analysis; D82; G22; Q10.
Ano: 2009 URL: http://purl.umn.edu/54983
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