Estimating the demand and willingness-to-pay for cotton yield monitors Michele C. Marra Æ Roderick M. Rejesus Æ Roland K. Roberts Æ Burton C. English Æ James A. Larson Æ Sherry L. Larkin Æ Steve Martin Published online: 29 July 2009 Ó Springer Science+Business Media, LLC 2009 Abstract Survey data from cotton farmers in six southeastern states of the USA were used to estimate the demand and willingness-to-pay (WTP) for either retrofitting yield monitors onto cotton pickers or to purchase a yield monitor as an option with a new cotton picker. ‘Don’t know’ responses were either omitted, combined with ‘no’ responses or included as a separate category for comparing WTP and estimates of the price elasticity of demand. Our results suggest that treating the ‘don’t know’ response as a separate category provides WTP estimates that are more consistent with expectations than the other approaches. The estimated price elasticities and demand curves indicate that previous users of precision technology are more responsive to changes in price of cotton yield monitors and would be more likely to adopt them when the price decreases. These demand and WTP estimates provide important information that can be used by those who sell cotton yield monitors, as well as policy-makers who may wish to subsidize this technology. Referen- dum contingent valuation was useful for evaluating the demand for any new technology. Keywords Contingent valuation  Ordered probit  Site-specific farming  Yield monitor  Willingness-to-pay (WTP) M. C. Marra (&)  R. M. Rejesus Department of Agriculture and Resource Economics, North Carolina State University, Raleigh, NC 27695, USA e-mail: michele_marra@ncsu.edu R. K. Roberts  B. C. English  J. A. Larson Department of Agricultural Economics, University of Tennessee, Knoxville, TN 37996-4518, USA S. L. Larkin Department of Food and Resource Economics, University of Florida, Gainesville, FL, USA S. Martin Department of Agricultural Economics and Delta Research & Extension Center, Mississippi State University, Stoneville, MS 38776, USA 123 Precision Agric (2010) 11:215–238 DOI 10.1007/s11119-009-9127-z