Category Archives: Research

A new agent symmetry criterion for social choice

It is time to write something longer than a tweet on this research topic, which in my opinion, trying to be as objective as possible, is very promising and conceptually important. I have worked on this with collaborators Jacky Lo, Geoff Pritchard and especially Rupert Freeman.

Let’s start with the model where we first noticed this new concept, namely one-to-one matching under ordinal preferences (“housing allocation”). Each of N agents has strict preferences over a set of N objects and we aim to find an assignment, namely a bijection between agents and objects. The famous mechanism called Serial Dictatorship fixes an order on the agents, and lets them choose in turn their most preferred object from those remaining. On the other hand, Top Trading Cycles starts with a fixed allocation, and gets each agent to point to the most preferred object. There must be at least one cycle, and we redistribute objects along the cycle so everyone in the cycle is satisfied. After removing these agents and objects, we continue with 2nd preferences, etc, until we reach a final assignment. A famous result of Abdulkadiroglu and Sonmez says that if the choosing order for SD is taken uniformly at random (this is called RSD), as is the initial allocation for TTC (which we call TTC-RE), then the probability distribution over assignments for these different-looking mechanisms is the same.

However, imagine yourself as an agent when RSD is used. No matter how you feel before the choosing order is determined, if you turn out to be at the beginning, you know you will always get your first choice object. If you turn out to be at the end, you know that you will have to take whatever is left. There is clear bias toward the front of the choosing order. On the other hand, it seems clear that no agent in TTC-RE will be as systematically advantaged just by virtue of their position in the mechanism.

A standard social choice concept is anonymity, meaning that a mechanism treats agents symmetrically, and the outcomes depend only on the profile of agent preferences, not the identities of the agents. However full anonymity is not possible in this model. RSD is anonymous, but once the choosing order is determined, the resulting SD is not anonymous. Similarly TTC-RE is anonymous but TTC is not. Yet TTC seems more symmetric than SD.  It seems there is an elusive criterion involving agent symmetry. The randomization discussed above turns out to be a red herring – we can define it in the deterministic case directly.

Our idea is to define such a criterion using average-case analysis. For a fixed probability distribution P on profiles (e.g. the uniform distribution), we consider the expected rank distribution for each agent, and if this is the same for all agents we call the mechanism order symmetric with respect to P. Some restriction on P is needed, because a point mass concentrated on a unanimous profile will prevent all mechanisms from being order symmetric. We show that provided P has sufficient symmetry between agents and between objects, TTC is order symmetric but SD is very far from being so. In other words, no agent is disadvantaged once the randomness in the mechanism is realized, and before preferences are elicited.

Not only does this definition clarify the difference between SD and TTC, it suggests tweaks to existing mechanisms. Full order symmetry may not be achieved in some situations, but we can try to equalize the bias between agents. The Boston mechanism clearly treats those early  in the tiebreaking order much better than those later in the order. A simple idea is to reverse the tiebreaking order after the first round. Simulations show this reduces bias substantially.

I feel that this idea has a bright future, with possible extensions to other social choice models and to practical mechanism design. Now we need a journal or conference to see that – we have had surprising difficulty in getting published. The two types of randomness can be confusing, and many researchers seem to think about fairness in terms of outcomes rather  than a procedural criterion of this sort. Some may just not think it is important, but we should first ensure there is no misunderstanding.

Swing models

Bernie Grofman and I have submitted a paper on what I feel is a fundamental methodological issue in the study of electoral systems, namely how to infer district-level vote changes given national-level vote changes. This has direct relevance to election forecasting and study of partisan gerrymandering, for example. We show that uniform swing and proportional swing, by far the most commonly used methods, fail various natural axioms, and we give an alternative method that does satisfy the axioms. Interestingly, we show that on real data there is very little difference between the predictions made by these methods.

(don’t have) ACOW (man)

I gave an invited talk in this online Zoom-workshop originally supposed to be held at the Mittag-Leffler Institute in Stockholm. The talk can be found at the Youtube channel which has many (other!) good talks. This meeting was a lot better than I had expected, and it is interesting to speculate on the future of academic conferences even once Covid-19 is vanquished. Thanks to the organizers for all their hard work.

A new citation-based measure of researcher impact

Zhou Tang and I have submitted a paper, my first in the area of scientometrics, to Quantitative Science Studies. I may be biased, but I feel this idea has potential.

The most commonly used publication metrics for individual researchers are the the total number of publications, the total number of citations, and Hirsch’s h-index. Each of these  increases throughout a researcher’s career, making it less suitable for evaluation of junior researchers or assessing recent impact.  We aim to study non-cumulative measures that answer the question “in terms of citation impact, what have you done lately?”

We single out six measures from the rather sparse literature, including Hirsch’s m-index, a time-scaled version of the h-index. We introduce new measures based on the idea of “citation acceleration”. After presenting several axioms for non-cumulative measures, we conclude that one of our new measures has much better theoretical justification. We present a small-scale study of its performance on real data and conclude that it shows substantial promise for future use.

 

NSF funded project 2019-2021

Along with the excellent collaborators listed below, I have been funded by NSF for a project entitled Collaborative Research: From Brains to Society: Neural Underpinnings of Collective Behaviors Via Massive Data and Experiments. Apart from the topic, an interesting point about this project is how it arose. NSF advertised an Ideas Lab on “Harnessing the Data Revolution”. Those selected (from a very lightweight application) were sequestered in a hotel near Washington DC in late May, and cleverly guided by professional facilitators to form groups, and propose projects. Since the participants were chosen not to know each other already, this was an intense and at times stressful exercise. Somehow I became involved in an interesting project that differs considerably from my initial ideas, with collaborators Caterina Stamoulis (neuroscience, Harvard), Jie Gao (CS, Stony Brook), Brandon Behlendorf (sociology, Albany), Prodromos Daoutidis (engineering, Minnesota) and Brandon Sepulvado (sociology, NORC). I highly recommend the Ideas Lab experience, which is different from any other grant-related experience I have had.

Lattice walks in the positive orthant

The paper Higher Dimensional Lattice Walks: Connecting Combinatorial and Analytic Behavior (with the excellent Stephen Melczer) has been accepted by SIAM J. Discrete Math. We consider the enumeration of nearest-neighbor walks on the non-negative lattice in d-dimensional space. Previous work in this area has established asymptotics for the number of walks in certain families of models by applying the techniques of analytic combinatorics in several variables (ACSV), where one encodes the generating function of a lattice path model as the diagonal of a multivariate rational function. Melczer and Mishna obtained asymptotics when the set of steps is symmetric over every axis; in this setting one can always apply the methods of ACSV to a multivariate rational function whose whose set of singularities is a smooth manifold (the simplest case). Here we go further, providing asymptotics for models with generating functions that must be encoded by multivariate rational functions with non-smooth singular sets. In the process, our analysis connects past work to deeper structural results in the theory of analytic combinatorics in several variables. One application is a closed form for asymptotics of models defined by step sets which are symmetric over all but one axis. As a special case, we apply our results in dimension 2 to give a rigorous proof of asymptotics conjectured by Bostan and Kauers; asymptotics for walks returning to boundary axes and the origin are also given.

Research news

A few papers are working their way through the journal system:

Once all these are finally done, I can get back to some work on generating functions, after several years, which I am very much looking forward to.