Voting rules as statistical estimators

We adopt an `epistemic' interpretation of social decisions: there is an objectively correct choice, each voter receives a `noisy signal' of the correct choice, and the social objective is to aggregate these signals to make the best possible guess about the correct choice. One epistemic method is to fix a probability model and compute the maximum likelihood estimator (MLE), maximum a posteriori estimator (MAP) or expected utility maximizer (EUM), given the data provided by the voters. We first show that an abstract voting rule can be interpreted as MLE or MAP if and only if it is a scoring rule. We then specialize to the case of distance-based voting rules, in particular, the use of the median rule in judgement aggregation. Finally, we show how several common `quasiutilitarian' voting rules can be interpreted as EUM.voting; maximum likelihood estimator; maximum a priori estimator; expected utility maximizer; statistics; epistemic democracy; Condorcet jury theorem; scoring rule

Assessment of Social Preference in Automotive Market using Generalized Multinomial Logistic Regression

Individual auto market share is always one of the major concerns of any auto manufacturing company. It indicates a lot of things about the company such as profitability, competitiveness, short term and long term development and so on. The focus of this paper is to construct a quantitative model that can precisely formulate the social welfare function of the auto market by relating the auto market share with the utilities of the significant vehicle-purchasing criteria (e.g. reliability, safety, etc.) that concern vehicle buyers. Social welfare function is defined as the additive form of the utility of each criterion considered, it’s a good estimation of the customer preferences. The assessment methods used in this research include random utility theory and B-spline fitted logistic regression model. G-test is applied to select the criteria that is significant to the vehicle market social welfare, pseudo R-squareds are used as the model goodness-of-fit measures and Kendall rank correlation coefficient and Matthews correlation coefficient are applied to validate the assessment model. A case study using the U.S. auto market and vehicles related data collected in years of 2013 and 2014 are conducted to illustrate the assessment process of the social welfare function, and the data from 2015 are used to validate the assessment model.Master of Science in EngineeringIndustrial and Systems Engineering, College of Engineering and Computer ScienceUniversity of Michigan-Dearbornhttp://deepblue.lib.umich.edu/bitstream/2027.42/136069/1/Assessment of Social Preference in Automotive Market using Generalized Multinomial Logistic Regression.pdfDescription of Assessment of Social Preference in Automotive Market using Generalized Multinomial Logistic Regression.pdf : Master of Science in Engineering Thesi