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Essays on the demand for innovations.
~
Useche, Maria del Pilar.
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Essays on the demand for innovations.
紀錄類型:
書目-語言資料,印刷品 : Monograph/item
正題名/作者:
Essays on the demand for innovations./
作者:
Useche, Maria del Pilar.
面頁冊數:
199 p.
附註:
Adviser: Bradford L. Barham.
Contained By:
Dissertation Abstracts International68-04A.
標題:
Economics, Agricultural. -
電子資源:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3261512
Essays on the demand for innovations.
Useche, Maria del Pilar.
Essays on the demand for innovations.
- 199 p.
Adviser: Bradford L. Barham.
Thesis (Ph.D.)--The University of Wisconsin - Madison, 2007.
This dissertation demonstrates a flexible methodology that accounts for the importance of product characteristics on the demand for new agricultural technologies and shows how preferences for individual traits impart variable effects on this demand. It extends the characteristics-based framework to account for decisions taken by boundedly-rational individuals in environments where traits are not fully observed. The model is implemented empirically for the case of genetically modified (GM) corn using survey data from Minnesota and Wisconsin farmers.Subjects--Topical Terms:
626648
Economics, Agricultural.
Essays on the demand for innovations.
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A first essay addresses the issue that the agricultural technology literature has typically explained adoption in terms of farm and farmer characteristics with little consideration for technological traits. It applies discrete-choice techniques used by consumer demand analysts to technology adoption, recovers estimates for the values of different combinations of traits and incorporates regional dimensions of the demand for these traits.
520
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The second essay extends the trait-framework to analyze the information problem of decision-makers (DM) when traits are imperfectly observed and cognition is less than perfect. The extended model underscores the effects on demand of immeasurable uncertainty due to information problems. It also highlights identification issues faced by analysts and measurement biases associated with standard rationality assumptions.
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The third essay empirically implements the extended model. The discussion focuses on the character of DM stored and processed data, the confidence of DM in the accuracy of expectations and of decision criteria when this confidence is low and expectations are not uniquely defined. The main results confirm that individual traits, heterogeneity of tastes for traits, and farm/farmer characteristics shape GM corn adoption decisions. In addition, immeasurable uncertainty increases as local conditions become less homogeneous and as computational ability, own experience and nearby adoption rates decrease. Measurement biases associated with full rationality assumptions are found to increase when DM have low computational ability, low experience and when their farming conditions differ widely from average adopter ones. Finally, models assuming low confidence in observed data, ambiguity and pessimistic expectations about traits are found to predict sample shares better than models which assume that farmers do not face ambiguity or are optimistic about the traits of new varieties.
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