Essays On Consumer Choice With Unobserved Choice Sets

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Essays On Consumer Choice With Unobserved Choice Sets

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Author : Maura Coughlin
language : en
Publisher:
Release Date : 2020

Essays On Consumer Choice With Unobserved Choice Sets written by Maura Coughlin and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with categories.

This dissertation consists of three essays that evaluate how consumers make decisions in settings where the researcher may not know the set of alternatives from which observed choices were selected. Many empirical analyses in economics presume the researcher knows the full set of alternatives an individual compared when selecting their most preferred. In practice, this assumption may fail to hold for a variety of reasons. In the first chapter, I introduce the economic setting of unobserved choice sets and consideration sets defining to this work. In the second chapter, my coauthors and I propose a robust method of discrete choice analysis when agents' choice sets are unobserved. Our core model assumes nothing about agents' choice sets apart from their minimum size. Importantly, it leaves unrestricted the dependence, conditional on observables, between agents' choice sets and their preferences. We first establish that the model is partially identified and characterize its sharp identification region. We then apply our theoretical findings to learn about households' risk preferences and choice sets from data on their deductible choices in auto collision insurance. The third chapter evaluates the prescription drug insurance choices of Medicare beneficiaries. I propose an empirical model of demand for prescription drug plans where non-monetary plan attributes stochastically determine the composition of the set of plans that an individual considers, and monetary plan attributes determine the individual's expected utility over contracts in her consideration set. This model reconciles the classic view of insurance contracts as lotteries with purely monetary outcomes with the empirical finding that choice among insurance plans is driven by their non-monetary attributes and financial attributes beyond their impacts on costs. I estimate the model using data from Medicare Part D allowing for unobserved heterogeneity in risk aversion and in consideration sets. I find that the latter plays a crucial role in plan choices, and in contrast to previous literature that assumes full consideration of all plans, I uncover an important role for risk aversion in determining individual choices.

Two Essays On Consumer Choice

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Author : Rishin Roy
language : en
Publisher:
Release Date : 1990

Two Essays On Consumer Choice written by Rishin Roy and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with categories.

Scalable Models Of Consumer Demand With Large Choice Sets

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Author : Robert Nathanael Donnelly
language : en
Publisher:
Release Date : 2019

Scalable Models Of Consumer Demand With Large Choice Sets written by Robert Nathanael Donnelly and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.

This dissertation consists of three essays related to the analysis of heterogeneity in consumer preferences based on individual level data on historical choices. In particular, they are connected by their application of modern Bayesian approaches to model consumers who differ both in their preferences for observed characteristics as well as their preferences for characteristics that are unobserved by the econometrician, but can instead be inferred from the correlations in choice behavior across different subsets of the population of consumers. The three chapters of this dissertation are also connected by their focus on scalability (both in computation and statistical efficiency) to large choice sets. Large choice sets are all around us, and the rise of E-commerce is leading to even larger sets of products that consumers can choose between. The average grocery store has tens of thousands of unique SKUs. The South Bay region around Stanford University has thousands of restaurants to choose between when you decide to go out for lunch. Large web retailers like Amazon sell hundreds of millions of distinct items. Individual level data on choices in situations like these present both opportunities and challenges. While these data sources are often large and rich in information, it is almost always the case that the number of choice occasions that we observe for any single individual is very small relative to the number of possible items they could have chosen between. Some types of products are easily described as a bundle of characteristics that consumers have preferences over, for example cars (horsepower, number of doors, leather seats) or digital cameras (resolution, zoom, flash), however for many other product categories it is more difficult to find a ''feature representation'' of products that accurately captures the heterogeneity in preferences across consumers. What are the characteristics that differ between Coke and Pepsi that lead to such strong disagreements over which is best. My work builds on recently developed approaches from machine learning for estimating models with large numbers of latent variables. This allows us to infer latent ''characteristics'' of products that are not directly observed by the econometrician, but can be inferred based on similarities in choice patterns across a large set of consumers. This allows us to model consumer preferences with heterogeneity in preferences for both observed and unobserved product characteristics. The first chapter of this dissertation is a paper written together with Susan Athey, David Blei, Francisco Ruiz, and Tobias Schmidt which analyzes consumer choices over lunchtime restaurants using data from a sample of several thousand anonymous mobile phone users in the San Francisco Bay Area. The data is used to identify users' approximate typical morning location, as well as their choices of lunchtime restaurants. We build a model where restaurants have latent characteristics (whose distribution may depend on restaurant observables, such as star ratings, food category, and price range), each user has preferences for these latent characteristics, and these preferences are heterogeneous across users. Similarly, each restaurant has latent characteristics that describe users' willingness to travel to the restaurant, and each user has individual-specific preferences for those latent characteristics. Thus, both users' willingness to travel and their base utility for each restaurant vary across user-restaurant pairs. We use a Bayesian approach to estimation. To make the estimation computationally feasible, we rely on variational inference to approximate the posterior distribution, as well as stochastic gradient descent as a computational approach. Our model performs better than more standard competing models such as multinomial logit and nested logit models, in part due to the personalization of the estimates. We analyze how consumers re-allocate their demand after a restaurant opens or closes and compare our predictions to the actual realized outcomes. Finally, we show how the model can be used to analyze counterfactual questions such as what type of restaurant would attract the most consumers in a given location. The second chapter is a paper written together with Susan Athey, David Blei, and Francisco Ruiz applies a similar approach in the context of supermarket scanner data. This paper demonstrates a method for estimating consumer preferences among discrete choices, where the consumer makes choices from many different categories. The consumer's utility is additive in the different categories, and her preferences about product attributes as well as her price sensitivity vary across products. Her preferences are correlated across products. We build on techniques from the machine learning literature on probabilistic models of matrix factorization, extending the methods to account for time-varying product attributes, a more realistic functional form for price sensitivity, and products going out of stock. We incorporate the information about the product hierarchy, so that consumers are assumed to select at most one alternative within a category. We evaluate the performance of the model using held-out data from weeks with price changes. We show that our model improves over traditional modeling approaches that consider each category in isolation, when we evaluate the ability of the model to predict responsiveness to price changes (using held-out data from a large number of price changes that occurred in our sample). We show that one source of the improvement is the ability of the model to accurately estimate heterogeneity in preferences (by pooling information across categories); another source of improvement is its ability to estimate the preferences of consumers who have rarely or never made a purchase in a given category in the training data. We consider counterfactuals such as personally targeted price discounts, showing that using a richer model such as the one we propose substantially increases the benefits of personalization in discounts. The third chapter of this dissertation proposes a novel estimator for learning heterogeneous consumer preferences based on both browsing and purchase data from online retailers with large product assortments. This work was done in collaboration with Ilya Morozov. Despite increasing availability data on the product pages consumers browse prior to making a purchase, the existing marketing literature provides little guidance on how retailers can use it to make better marketing decisions. In this paper, we propose an empirical framework that allows to efficiently extract information from consumers' search histories and use it to design personalized product recommendations. Our framework is based on the standard consideration set model from the marketing literature. To extract information from the unstructured search data, we augment the model with rich consumer heterogeneity and include several unobserved product characteristics. We then propose a way to estimate this model's parameters using a latent factorization approach from the computer science literature. The proposed framework can be seen as combining a structural approach to modeling consumer consideration from marketing with nonparametric estimation methods commonly used in the computer science. We are in discussion with a large online retailer to gain access to data and to run an AB test to experimentally validate the effects of improved rankings and recommendations of products.

Demand Estimation With Heterogeneous Consumers And Unobserved Product Characteristics

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Author : Patrick Bajari
language : en
Publisher:
Release Date : 2001

Demand Estimation With Heterogeneous Consumers And Unobserved Product Characteristics written by Patrick Bajari and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2001 with Consumers' preferences categories.

We study the identification and estimation of preferences in hedonic discrete choice models of demand for differentiated products. In the hedonic discrete choice model, products are represented as a finite dimensional bundle of characteristics, and consumers maximize utility subject to a budget constraint. Our hedonic model also incorporates product characteristics that are observed by consumers but not by the economist. We demonstrate that, unlike the case where all product characteristics are observed, it is not in general possible to uniquely recover consumer preferences from data on a consumer's choices. However, we provide several sets of assumptions under which preferences can be recovered uniquely, that we think may be satisfied in many applications. Our identification and estimation strategy is a two stage approach in the spirit of Rosen (1974). In the first stage, we show under some weak conditions that price data can be used to nonparametrically recover the unobserved product characteristics and the hedonic pricing function. In the second stage, we show under some weak conditions that if the product space is continuous and the functional form of utility is known, then there exists an inversion between a consumer's choices and her preference parameters. If the product space is discrete, we propose a Gibbs sampling algorithm to simulate the population distribution of consumers' taste coefficients.

Essays In Consumer Choice

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Author : Salar Jahedi
language : en
Publisher:
Release Date : 2009

Essays In Consumer Choice written by Salar Jahedi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009 with categories.

Essays In Consumer Choice And Consumer Demand

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Author : Joonhwi Joo
language : en
Publisher:
Release Date : 2018

Essays In Consumer Choice And Consumer Demand written by Joonhwi Joo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with categories.

In chapter 2 (coauthored with Ali Hortacsu), we study the relation between logit demand systems and constant elasticity of substitution (CES) demand systems. We develop a characteristics based demand estimation framework for the Marshallian demand system obtained by solving a budget-constrained constant elasticity of substitution (CES) utility maximization problem. From our Marshallian CES demand system, we derive the same market share equation of Berry (1994), Berry et al. (1995)'s characteristics based logit demand system. Furthermore, our CES demand estimation framework can accommodate zero predicted and observed market shares by separating intensive and extensive margins, and allows a semiparametric estimation strategy that is flexible regarding the distribution of unobservable product characteristics. We apply the framework to scanner data on cola sales, where we show estimated demand curves can be upward sloping if zero market shares are not accommodated properly.

Essays On Dynamic Choice Behavior

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Author : Peruvemba B. Seetharaman
language : en
Publisher:
Release Date : 1998

Essays On Dynamic Choice Behavior written by Peruvemba B. Seetharaman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with categories.

Essays In Modeling The Consumer Choice Process

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Author : Taylor Baldwin Bentley
language : en
Publisher:
Release Date : 2015

Essays In Modeling The Consumer Choice Process written by Taylor Baldwin Bentley and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Electronic dissertations categories.

In this dissertation, I utilize and develop empirical tools to help academics and practitioners model the consumer's choice process. This collection of three essays strives to answer three main research questions in this theme. In the first paper, I ask: how is the consumer's purchase decision impacted by the search for general product-category information prior to search for their match with a retailer or manufacturer ("sellers")? This paper studies the impact of informational organic keyword search results on the performance of sponsored search advertising. We show that, even though advertisers can target consumers who have specific needs and preferences, for many consumers this is not a sufficient condition for search advertising to work. By allowing consumers to access content that satisfies their information requirements, informational organic results can allow consumers to learn about the product category prior to making their purchase decision. We develop a model characterize the situation in which consumers can search for general information about the product category as well as for information about the individual sellers' offerings. We estimate this model using a unique dataset of search advertising in which commercial websites are restricted in the organic listing, allowing us to identify consumer clicks as informational (from organic links) or purchase oriented (from sponsored links). With the estimation results, we show that consumer welfare is improved by 29%, while advertisers generate 19% more sales, and search engines obtain 18% more paid clicks, as compared to the scenario without informational links. We conduct counterfactuals and find that consumers, advertisers, and the search engine are significantly better off when the search engine provides "free" general information about the product. When the search engine provides information about the advertisers' specific offerings, however, there are fewer paid clicks and advertisers at high ad positions will obtain lower sales. We further investigate the implications on the equilibrium advertiser bidding strategy. Results show that advertiser bids will remain constant in the former scenario. When the search engine provides advertiser information, advertisers will increase their bids because of the increased conversion rate; however, the search engine still loses revenue due to the decreased paid clicks. The findings shed important managerial insights on how to improve the effectiveness of search advertising. In the second paper, I ask: how is the consumer's search for information, during their choice process and in an advertising context, influenced by the signaling theory of advertising? Using a dataset of travel-related keywords obtained from a search engine, we test to what extent consumers are searching and advertisers are bidding in accordance with the signaling theory of advertising in literature. We find significant evidence that consumers are more likely to click on advertisers at higher positions because they infer that such advertisers are more likely to match with their needs. Further, consumers are more likely to find a match with advertisers who have paid more for higher positions. We also find strong evidence that advertisers increase their bids when there is an improvement in the likelihood that their offerings match with consumers' needs, and the improvement cannot be readily observed by consumers prior to searching advertisers' websites. These results are consistent with the predictions from the signaling theory. We test several alternative explanations and show that they cannot fully explain the results. Furthermore, through an extension we find that advertisers can generate more clicks when competing against advertisers with higher match value. We offer an explanation for this finding based on the signaling theory. In the third paper, I ask: can we model the consumer's choice of brand as a sequential elimination of alternatives based on shared or unique aspects while incorporating continuous variables, such as price? With aggregate scanner data, marketing researchers typically estimate the mixed logit model, which accounts for non-IIA substitution patterns among brands, which arise due to similarity and dominance effects in demand. Using numerical examples and analytical illustrations, this research shows that the mixed logit model, which is widely believed to be a highly flexible characterization of brand switching behavior, is not well designed to handle non-IIA substitution patterns. The probit allows only for pair-wise inter-brand similarities, and ignores third-order or higher dependencies. In the presence of similarity and dominance effects, the mixed logit model and the probit model yield systematically distorted marketing mix elasticities. This limits the usefulness of mixed logit and probit for marketing decision-making. We propose a more flexible demand model that is an extension of the elimination-by-aspects (EBA) model (Tversky 1972a, 1972b) to handle marketing variables. The model vastly expands the domain of applicability of the EBA model to aggregate scanner data. Using an analytical closed-form that nests the traditional logit model as a special case, the EBA demand model is estimated with marketing variables from aggregate scanner data in 9 different product categories. It is compared to the mixed logit and probit models on the same datasets. In terms of multiple fit and predictive metrics (LL, BIC, MSE, MAD), the EBA model outperforms the mixed logit and the probit in a majority of categories in terms of both in-sample fit and holdout predictions. The results show significant differences in the estimated price elasticity matrices between the EBA model and the comparison models. In addition, a simulation shows that the retailer can improve gross profits up to 34.4% from pricing based on the EBA model rather than the mixed logit model. Finally, the results suggest that empirical IO researchers, who routinely use mixed logit models as inputs to oligopolistic pricing models, should consider the EBA demand model as the appropriate model of demand for differentiated products.

The Continuum Of Choice Essays On How Consumer Decisions Are Made Changed And Perceived

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Author : Katherine N. Barasz
language : en
Publisher:
Release Date : 2016

The Continuum Of Choice Essays On How Consumer Decisions Are Made Changed And Perceived written by Katherine N. Barasz and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.

This research investigates the continuum of choice--unseen, unanticipated causes and consequences of consumer decisions. Three essays investigate hidden factors that influence the choices we make, subtle ways to affect choice at the moment of execution, and the overlooked signals that our choices convey (correctly or incorrectly) about us to others. Essay one investigates the perverse tendency to hope for the worst: when faced with a difficult decision (e.g., whether or not to have surgery), people can paradoxically feel subjectively better with--and even actively prefer--objectively worse but certain news (e.g., "95% chance of a disease") over objectively better but more uncertain news (e.g., "50% chance of a disease"). This, in turn, has the potential to meaningfully change people's subsequent choices and preferences in unexpected ways. Essay two examines a subtle intervention to change people's decisions about engagement levels: arbitrarily grouping discrete tasks or items together as part of an apparent "set" motivates people to reach perceived completion points--or finish a pseudo-set--even in the absence of extrinsic incentives. Essay three explores the judgments people make after observing others' choices; specifically, upon learning of someone's choice of one option, people erroneously believe that person must dislike dissimilar options, leading to a pervasive and systematic prediction error.

Essays On Consumer Choice

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Author : Pavitra Jindahra
language : en
Publisher:
Release Date : 2005

Essays On Consumer Choice written by Pavitra Jindahra and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with categories.