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Avoiding biases from data-dependent specification search: an application to a tillage choice model AgEcon
Sengupta, Sanchita; Kurkalova, Lyubov A.; Kling, Catherine L..
The study evaluates the gains of avoiding data-dependent specification search on an estimation sample in an application to discrete choice models. We incorporate data splitting, the process by which the total available sample is randomly split in two or more sub-samples with the first (specification) sub-sample used for specification search, and the second (estimation) sub-sample used for obtaining clean estimates using the model chosen on the specification sub-sample according to a set criterion. We estimate 14 binary Logit models of the adoption of conservation tillage corresponding to the major sub-watersheds of the Upper Mississippi River Basin. For each of the sub-watershed models, we use the specification sub-sample to choose the explanatory...
Tipo: Conference Paper or Presentation Palavras-chave: Research Methods/ Statistical Methods.
Ano: 2006 URL: http://purl.umn.edu/21399
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VALUATION OF RANCHETTE AMENITIES: A HEDONIC APPROACH AgEcon
Sengupta, Sanchita; Osgood, Daniel E..
Throughout the Western United States, production ranches are being subdivided into recreation -oriented "ranchettes". This paper presents a hedonic model for ranchettes, introducing the use of remote sensing vegetative indices and neighborhood characteristics. It is found that increased greenness, access to roads, cities, and proximity to open space increase sale prices.
Tipo: Conference Paper or Presentation Palavras-chave: Land Economics/Use.
Ano: 2002 URL: http://purl.umn.edu/36547
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