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on Discrete Choice Models |
| By: | Verity Watson, Matt Sutton, Chris Dibben and Mandy Ryan |
| Abstract: | In this paper we illustrate the use of a stated preference method, discrete choice experiments, to derive domain weights for the IMD. To do this, respondents were asked to make a series of choices between two deprivation states. To ensure the realism of, and respondents’ engagement with, the task, we refer to each state as a hypothetical person’s circumstances. In each choice, we ask respondents to state which person needs the most additional support from the government. We show that respondents place greater weight on housing and health, and less weight on employment, than the existing IMD. Creation-Date: 2008-08 |
| URL: | http://d.repec.org/n?u=RePEc:qeh:ophiwp:ophiwp024&r=dcm |
| By: | Jose Apesteguia; Miguel Angel Ballester |
| Abstract: | Suppose that, when evaluating two alternatives x and y by means of a parametric utility function, low values of the parameter indicate a preference for x and high values indicate a preference for y. We say that a stochastic choice model is monotone whenever the probability of choosing x is decreasing in the preference parameter. We show that the standard use of random utility models in the context of risk and time preferences may sharply violate this monotonicity property, and argue that their use in preference estimation may be problematic. In particular, they may pose identication problems and yield biased estimations. We then establish that the alternative random parameter models, in contrast, are always monotone. We show in an empirical application that standard risk-aversion assessments may be severely biased. |
| Keywords: | stochastic choice, preference parameters, random utility models, random parameter models, Risk Aversion, delay aversion |
| JEL: | C25 D81 |
| Date: | 2015–12 |
| URL: | http://d.repec.org/n?u=RePEc:bge:wpaper:859&r=dcm |
| By: | Quan-Hoang Vuong |
| Abstract: | This paper communicates results from a statistical investigation into questions of relationships between sources of health-care information, data sufficiency, and final outcomes of Vietnamese patients' choice of health-care provider. The study employs a data set of 1459 observations collected from a survey in Hanoi in the fourth quarter of 2015. Significant relationships among these factors are identified following categorical data modeling employing the baselinecategory logit (BCL) method. Among the significant results reported, sources ofinformation, cost, and amount of time for seeking information are found to have significant influences on data sufficiency. The quality of information and health professionals’ credibility are critical factors in helping patients choose a healthcare provider In addition, empirical probabilities for different conditions patients face are provided together with insights and policy implications. Final suggestionsemphasize an upgrade of the knowledge base and an increase in public access to information with Internet-based innovations such as smartphone apps and data storage with the participation of healthcare providers and the Ministry of Health's ICT units. The underutilized 115 Emergency Service could also be transformed to function as a call center that helps coordinate and channel requests forinformation across a broad network of health-care professionals for better public use. |
| Keywords: | health-care provider; quality of information; data sufficiency; Vietnam; consumer behavior |
| JEL: | D83 I12 D12 |
| Date: | 2016–01–04 |
| URL: | http://d.repec.org/n?u=RePEc:sol:wpaper:2013/222896&r=dcm |
| By: | Sabina Alkire, James E. Foster, Suman Seth, Maria Emma Santos, Jose M. Roche and Paola Ballon |
| Abstract: | Chapter 10 provides the reader with a general modelling framework for analysing the determinants of poverty measures presented in Chapter 5 for both micro and macro levels of analyses. At the micro level, we present a model where the focal variable is a personÕs poverty status. At the macro level we present a model where the focal variable is an overall poverty measure like the poverty headcount ratio or the adjusted headcount ratio. The chapter presents these regression models within the structure of Generalized Linear Models (GLMÕs), which allow accounting for the bounded and discrete variables. GLMs encompass linear regression models, logit and probit models, and models for fractional data. Thus, they offer a general framework for our analysis of functional relationships with AF measures presented in Chapter 5. |
| Date: | 2015–03 |
| URL: | http://d.repec.org/n?u=RePEc:qeh:ophiwp:ophiwp091_ch10&r=dcm |
| By: | Marc Fleurbaey |
| Abstract: | This paper describes the evaluation of individual situations in terms of equivalent incomes computed from ordinary income by adding or subtracting various terms of willingness-to-pay. It discusses the origin of the approach and its connection with social choice theory and philosophical principles. It also examines the challenges to be addressed for empirical applications of the approach. Creation-Date: 2008-08 |
| URL: | http://d.repec.org/n?u=RePEc:qeh:ophiwp:ophiwp025&r=dcm |
| By: | Adenbaum, Jacob (Federal Reserve Bank of New York); Copeland, Adam (Federal Reserve Bank of New York); Stevens, John J. (Federal Reserve Board) |
| Abstract: | The U.S. federal government enacted fuel efficiency standards for medium and heavy trucks for the first time in September 2011. Rationales for using this policy tool typically depend upon frictions existing in the marketplace or consumers being myopic, such that vehicle purchasers undervalue the future fuel savings from increased fuel efficiency. We measure by how much long-haul truck owners undervalue future fuel savings by employing recent advances to the classic hedonic approach to estimate the distribution of willingness-to-pay for fuel efficiency. We find significant heterogeneity in truck owners’ willingness to pay for fuel efficiency, with the elasticity of fuel efficiency to price ranging from 0.51 at the 10th percentile to 1.33 at the 90th percentile, and an average of 0.91. Combining these results with estimates of future fuel savings from increases in fuel efficiency, we find that long-haul truck owners’ willingness-to-pay for a 1 percent increase in fuel efficiency is, on average, just 29.5 percent of the expected future fuel savings. These results suggest that introducing fuel efficiency standards for heavy trucks might be an effective policy tool to raise medium and heavy trucks’ fuel economy. |
| Keywords: | fuel efficiency standards; durable goods; discrete-choice demand estimation |
| JEL: | D22 L51 L92 |
| Date: | 2016–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:fip:fednsr:756&r=dcm |