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JournalISSN: 0002-9092

American Journal of Agricultural Economics 

Oxford University Press
About: American Journal of Agricultural Economics is an academic journal published by Oxford University Press. The journal publishes majorly in the area(s): Agriculture & Agricultural productivity. It has an ISSN identifier of 0002-9092. Over the lifetime, 10662 publications have been published receiving 371111 citations.


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Journal ArticleDOI
Theodore Schultz1

4,827 citations

Journal ArticleDOI
TL;DR: In this article, two distinct types of welfare measures are introduced and then estimated from Bishop and Heberlein's data, based on the hypothesis of utility maximization, and measures of compensating and equivalent surplus are derived from the fitted models.
Abstract: Since the work of Bishop and Heberlein, a number of contingent valuation experiments have appeared involving discrete responses which are analyzed by logit or similar techniques. This paper addresses the issues of how the logit models should be formulated to be consistent with the hypothesis of utility maximization and how measures of compensating and equivalent surplus should be derived from the fitted models. Two distinct types of welfare measures are introduced and then estimated from Bishop and Heberlein's data.

2,829 citations

Posted Content
TL;DR: The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the U.S. Department of Agriculture (USDA), Agricultural Research Service.
Abstract: The Soil and Water Assessment Tool (SWAT) model is a continuation of nearly 30 years of modeling efforts conducted by the U.S. Department of Agriculture (USDA), Agricultural Research Service. SWAT has gained international acceptance as a robust interdisciplinary watershed modeling tool, as evidenced by international SWAT conferences, hundreds of SWAT-related papers presented at numerous scientific meetings, and dozens of articles published in peer-reviewed journals. The model has also been adopted as part of the U.S. Environmental Protection Agency's BASINS (Better Assessment Science Integrating Point & Nonpoint Sources) software package and is being used by many U.S. federal and state agencies, including the USDA within the Conservation Effects Assessment Project. At present, over 250 peer-reviewed, published articles have been identified that report SWAT applications, reviews of SWAT components, or other research that includes SWAT. Many of these peer-reviewed articles are summarized here according to relevant application categories such as streamflow calibration and related hydrologic analyses, climate change impacts on hydrology, pollutant load assessments, comparisons with other models, and sensitivity analyses and calibration techniques. Strengths and weaknesses of the model are presented, and recommended research needs for SWAT are provided.

2,274 citations

Journal ArticleDOI
TL;DR: In this paper, a double-bounded dichotomous choice contingent valuation survey was proposed to improve the statistical efficiency of conventional dichotomy-choice contingent valuation surveys by asking each respondent a second question which depends on the response to the first question.
Abstract: The statistical efficiency of conventional dichotomous choice contingent valuation surveys can be improved by asking each respondent a second dichotomous choice question which depends on the response to the first question—if the first response is "yes," the second bid is some amount greater than the first bid; while, if the first response is "no," the second bid is some amount smaller. This "double-bounded" approach is shown to be asymptotically more efficient than the conventional, "singlebounded" approach. Using data from a survey of Californians regarding their willingness to pay for wetlands in the San Joaquin Valley, we show that, in a finite sample, the gain in efficiency can be very substantial.

1,704 citations

Performance
Metrics
No. of papers from the Journal in previous years
YearPapers
202354
202283
2021155
202092
201989
201896