Browsing by Author "DeShazo, J. R."
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Item Open Access Differential Attention to Attributes in Utility-theoretic Choice Models(University of Oregon, Dept of Economics, 2008-10) Cameron, Trudy Ann; DeShazo, J. R.We show in a theoretical model that benefits of allocating additional attention to evaluating the marginal attribute with in choice set depend upon the expected utility loss from making a suboptimal choice as a result of ignoring that incremental attribute. Guided by this analysis, we then develop a very general and practical empirical method for measuring the individual's propensity to attend to attributes. As a proof of concept, we offer an empirical example of our method using a conjoint analysis of demand for programs to reduce health risks. Our results suggest that respondents differentially allocate attention across attributes, as a function of the mix of attribute levels in a choice set. This behavior can cause researchers who fail to model attention allocation to incorrectly estimate the marginal utilities derived from selected attributes. This illustrative example is a first attempt to implement an attention-corrected choice model with a sample of field data from a conjoint choice experiment.Item Open Access An Empirical Model of Demand for Future Health States when Valuing Risk-Mitigating Programs(University of Oregon, Dept. of Economics, 2004-03) Cameron, Trudy Ann; DeShazo, J. R.We develop a structural option price model in which individuals choose among competing risk-mitigating programs to alter their probability of experiencing future years in various degraded health states. The novel aspects of this model include separate estimates of the marginal utilities of avoiding years of morbidity and lost life-years. With these marginal utilities, we may evaluate a broad spectrum of probabilistic health outcomes over any period of an individual’s future life. The model also reduces potential biases associated with singleperiod, single-risk models typically used to produce estimates of the Value of a Statistical Life (VSL) by allowing individuals to substitute risk mitigation across competing sources of risk and across future years of their lives. We evaluate this model using data from a national survey that contains a choice experiment on demand for the mitigation of illness-specific risks.Item Open Access Scenario Adjustment in Stated Preference Research(University of Oregon, Dept of Economics, 2009-11-22) Cameron, Trudy Ann; DeShazo, J. R.; Johnson, Erica H.Stated preference (SP) survey methods have been used increasingly to assess willingness to pay for a wide variety of non-market goods and services, including reductions in risks to life and health. Poorly designed SP studies are subject to a number of well-known biases, but many of these biases can be minimized when they are anticipated ex ante and accommodated in the study’s design or during data analysis. We identify another source of potential bias, which we call “scenario adjustment,” where respondents assume that the substantive alternative(s) in an SP choice set, in their own particular case, will be different than the survey instrument describes. We use an existing survey, developed to ascertain willingness to pay for private health-risk reduction programs, to demonstrate a strategy to control and correct for scenario adjustment in the estimation of willingness to pay. This strategy involves data from carefully worded follow-up questions and ex post econometric controls for each respondent’s subjective departures from the intended choice scenario. Our research has important implications for the design of future SP surveys.Item Open Access Test of Choice Set Misspecification for Discrete Models of Consumer Choice(University of Oregon, Dept. of Economics, 2001-11-05) DeShazo, J. R.; Cameron, Trudy Ann; Saenz, Manrique, 1971-We develop and evaluate a test of choice set misspecification for a multinomial logit choice model. This test determines whether the choice set designated by the researcher mistakenly assigns relevant substitutes to the numeraire good. We develop this test by generalizing the traditional McFadden-type conditional logit model to evaluate whether the traditional model is conditioned on an overly restrictive set of substitution possibilities. The test has a convenient feature: while it requires information on potentially relevant, but omitted, substitute goods, it does not require the researcher to observe consumers? choices among these omitted potential substitutes if they select the numeraire good (which contains these omitted substitutes). A comparison of the traditional multinomial logit choice model and our more general model suggests that choice set misspecification may produce biased parameters that distort welfare estimates to a consequential extent.