management practices can influence the variance but not the mean of the WTP distribution. However, Boyle (1989) was not able to identify if this effect varies across the population by information sets. Third, we focus very specifically on objective characteristics of the good which we can confirm were unknown to the subject. Other studies of information in a stated preference context focus on different forms of information such as redundant information (Viscusi and O'Connor, 1984), the relative cost of management versus a subject’s income (Bergstrom et. al. 1989), and specificity of management actions (Boyle 1989). Our paper estimates the marginal impact of both information and acquired knowledge about public good attributes on WTP, conditional on prior knowledge levels. In addition, because we are able to test for ex ante and ex post knowledge states, vary levels of information, identify that information creates knowledge and subsequently estimate WTP, we have the necessary features to link this large and somewhat older literature on information effects in contingent valuation to a newer economics literature on updating and valuation. Specifically, recent advances highlight how cognitive constraints, costly effort, endogenous search and confirmatory bias can influence both learning and subsequent valuation (Aadland et al., 2007; Caplin and Dean, 2015; Caplin et al., 2011; De los Santos et al., 2012; Rabin and Schrag, 1999) . This is important, as recent evidence suggests there can be unexpected departures from neoclassical models of updating in stated preference studies (LaRiviere et al., 2014). Finally, because we simultaneously track both the causal effects of information on knowledge and knowledge on valuation, we are able to compare several different models of learning, information process and preference formation in a unified framework. To our knowledge, this is the first such comparison in a stated preference survey. Together with our results on learning, our results turn out to be consistent with three models of preference formation: 1) Confirmatory Bias (Rabin and Schrag 1999), 2) heterogeneous preferences and endogenous costly information acquisition decisions similar in spirit to Caplin and Dean (2011 and 3) a timing lag between learning and preference formation.
management practices can influence the variance but not the mean of the WTP distribution. However, Boyle (1989) was not able to identify if this effect varies across the population by information sets. Third, we focus very specifically on objective characteristics of the good which we can confirm were unknown to the subject. Other studies of information in a stated preference context focus on different forms of information such as redundant information (Viscusi and O'Connor, 1984), the relative cost of management versus a subject’s income (Bergstrom et. al. 1989), and specificity of management actions (Boyle 1989). Our paper estimates the marginal impact of both information and acquired knowledge about public good attributes on WTP, conditional on prior knowledge levels. In addition, because we are able to test for ex ante and ex post knowledge states, vary levels of information, identify that information creates knowledge and subsequently estimate WTP, we have the necessary features to link this large and somewhat older literature on information effects in contingent valuation to a newer economics literature on updating and valuation. Specifically, recent advances highlight how cognitive constraints, costly effort, endogenous search and confirmatory bias can influence both learning and subsequent valuation (Aadland et al., 2007; Caplin and Dean, 2015; Caplin et al., 2011; De los Santos et al., 2012; Rabin and Schrag, 1999) . This is important, as recent evidence suggests there can be unexpected departures from neoclassical models of updating in stated preference studies (LaRiviere et al., 2014). Finally, because we simultaneously track both the causal effects of information on knowledge and knowledge on valuation, we are able to compare several different models of learning, information process and preference formation in a unified framework. To our knowledge, this is the first such comparison in a stated preference survey. Together with our results on learning, our results turn out to be consistent with three models of preference formation: 1) Confirmatory Bias (Rabin and Schrag 1999), 2) heterogeneous preferences and endogenous costly information acquisition decisions similar in spirit to Caplin and Dean (2011 and 3) a timing lag between learning and preference formation.