1,720,962 research outputs found
Identification in the Random Utility Model
Full text linkThe random utility model is known to be unidentified, but there are times
when the model admits a unique representation. We offer two characterizations
for the existence of a unique random utility representation. Our first
characterization puts conditions on a graphical representation of the data set.
Non-uniqueness arises when multiple inflows can be assigned to multiple
outflows on this graph. Our second characterization provides a direct test for
uniqueness given a random utility representation. We also show that the support
of a random utility representation is identified if and only if the
representation itself is identified.Comment: 23 pages, 2 figure
An alternative approach for nonparametric analysis of random utility models
Full text linkWe readdress the problem of nonparametric statistical testing of random utility models proposed in Kitamura and Stoye (2018). Although their test is elegant, it is subject to computational constraints which leaves execution of the test infeasible in many applications. We note that much of the computational burden in Kitamura and Stoye's test is due to their test defining a polyhedral cone through its vertices rather than its faces. We propose an alternative but equivalent hypothesis test for random utility models. This test relies on a series of equality and inequality constraints which defines the faces of the corresponding polyhedral cone. Building on our testing procedure, we develop a novel axiomatization of the random utility model
The limits of identification in discrete choice
Full text linkThis paper uncovers tight bounds on the number of preferences permissible in identified random utility models. We show that as the number of alternatives in a discrete choice model becomes large, the fraction of preferences admissible in an identified model rapidly tends to zero. We propose a novel sufficient condition ensuring identification, which is strictly weaker than some of those existing in the literature. While this sufficient condition reaches our upper bound, an example demonstrates that this condition is not necessary for identification. Using our new condition, we show that the classic “Latin Square” example from social choice theory is identified from stochastic choice data
Correlated Choice
Full text linkWe study random joint choice rules, allowing for interdependence of choice
across agents. These capture random choice by multiple agents, or a single
agent across goods or time periods. Our interest is in separable choice rules,
where each agent can be thought of as acting independently of the other. A
random joint choice rule satisfies marginality if for every individual choice
set, we can determine the individual's choice probabilities over alternatives
independently of the other individual's choice set. We offer two
characterizations of random joint choice rules satisfying marginality in terms
of separable choice rules. While marginality is a necessary condition for
separability, we show that it fails to be sufficient. We provide an additional
condition on the marginal choice rules which, along with marginality, is
sufficient for separability
Estimation in English auctions with unobserved heterogeneity
No full textWe propose a framework for identification and estimation of a private values model with unobserved heterogeneity from bid data in English auctions, using variation in the number of bidders across auctions, and extend the framework to settings where the number of bidders is not cleanly observed in each auction. We illustrate our method on data from eBay Motors auctions. We find that unobserved heterogeneity is important, accounting for two thirds of price variation after controlling for observables, and that welfare measures would be dramatically misestimated if unobserved heterogeneity were ignored
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Random Utilities and How to Find Them
No full textPh.D.In this dissertation, I study the random utility model. The random utility model is an extension of the classic paradigm of economics which assumes that decision makers choose according to some underlying preference. The random utility model extends this paradigm by allowing for heterogeneity across either a population of decision makers or across time for the same decision maker. This heterogeneity is modeled as there being a distribution over preferences inducing a distribution over choices. In Chapter 1, I study when an analyst is able to recover the underlying distribution over preferences from choice data. I provide fully characteristic conditions under which we are able to recover the underlying distribution over preferences. In Chapter 2, I readdress the problem of testing the random utility model. While axiomatic tests of the random utility model have been known, only recently has a hypothesis test for the random utility model been developed which can be applied to real data. However, this hypothesis test is not computationally feasible in many reasonable applications. I provide an alternative hypothesis test, applicable to real data, that offers large computational improvements over the current standard methodology. In Chapter 3, I study the random utility model in a dynamic setting where a decision maker's past choices can impact their preference today. First, I broach the problem of aggregation. In general, if a decision maker's preference depends on their history of choices, the time average of their choices does not coincide with the random utility model. I provide characteristic conditions for when the random utility model is an accurate model of time aggregated choice. Second, I develop a test for this type of dynamic random utility when we have time disaggregated but population level data. I provide a fully characteristic axiomatic test as well as a hypothesis test for history dependent random utility for this type of data
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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