A preferred-habitat model of the term structure of interest rates

We model the term structure of interest rates as resulting from the interaction between investor clienteles with preferences for specific maturities and risk-averse arbitrageurs. Because arbitrageurs are risk averse, shocks to clienteles’ demand for bonds affect the term structure— and constitute an additional determinant of bond prices to current and expected future short rates. At the same time, because arbitrageurs render the term structure arbitrage-free, demand effects satisfy no-arbitrage restrictions and can be quite different from the underlying shocks. We show that the preferred-habitat view of the term structure generates a rich set of implications for bond risk premia, the effects of demand shocks and of shocks to short-rate expectations, the economic role of carry trades, and the transmission of monetary policy

A Search-Based Theory of the On-the-Run Phenomenon

Treasury Market, Liquidity, Search

Equilibrium interest rate and liquidity premium with transaction costs.

In this paper we study the effects of transaction costs on asset prices. We assume an overlapping generations economy with two riskless assets. The first asset is liquid while the second asset carries proportional transaction costs. We show that agents buy the liquid asset for short-term investment and the illiquid asset for long-term investment. When transaction costs increase, the price of the liquid asset increases. The price of the illiquid asset decreases if the asset is in small supply, but may increase if the supply is large. These results have implications for the effects of transaction taxes and commission deregulation.

Persuasion bias, social influence, and uni-dimensional opinions.

We propose a boundedly rational model of opinion formation in which individuals are subject to persuasion bias; that is, they fail to account for possible repetition in the information they receive. We show that persuasion bias implies the phenomenon of social influence, whereby one’s influence on group opinions depends not only on accuracy, but also on how well-connected one is in the social network that determines communication. Persuasion bias also implies the phenomenon of unidimensional opinions; that is, individuals’ opinions over a multidimensional set of issues converge to a single “left-right” spectrum. We explore the implications of our model in several natural settings, including political science and marketing, and we obtain a number of novel empirical implications.

A Model of Persuasion - With Implications for Financial Markets

We propose a model of the phenomenon of persuasion. We argue that individual beliefs evolve in a way that overweights the opinions and information of individuals whom they "listen to" relative to other individuals. Such agents can be understood to be acting as though they believe they listen to a representative sample of the individuals with valuable information, even though they may not. We analyze dynamics and convergence of beliefs, characterizing when agents' beliefs converge over time to the same beliefs, and when they instead diverge. Convergent beliefs can be characterized as the weighted average of agents' initial beliefs, and these weights can be interpreted as a measure of ``influence.'' We then explore implications in an asset trading setting. Here we demonstrate that agents profit from being influential as well as being accurate. When agents' choice of whom to listen to is endogenous, we show that an individual's influence can be persistent, even though the individual may be inaccurate.

Social Network Based Substance Abuse Prevention via Network Modification (A Preliminary Study)

Substance use and abuse is a significant public health problem in the United States. Group-based intervention programs offer a promising means of preventing and reducing substance abuse. While effective, unfortunately, inappropriate intervention groups can result in an increase in deviant behaviors among participants, a process known as deviancy training. This paper investigates the problem of optimizing the social influence related to the deviant behavior via careful construction of the intervention groups. We propose a Mixed Integer Optimization formulation that decides on the intervention groups, captures the impact of the groups on the structure of the social network, and models the impact of these changes on behavior propagation. In addition, we propose a scalable hybrid meta-heuristic algorithm that combines Mixed Integer Programming and Large Neighborhood Search to find near-optimal network partitions. Our algorithm is packaged in the form of GUIDE, an AI-based decision aid that recommends intervention groups. Being the first quantitative decision aid of this kind, GUIDE is able to assist practitioners, in particular social workers, in three key areas: (a) GUIDE proposes near-optimal solutions that are shown, via extensive simulations, to significantly improve over the traditional qualitative practices for forming intervention groups; (b) GUIDE is able to identify circumstances when an intervention will lead to deviancy training, thus saving time, money, and effort; (c) GUIDE can evaluate current strategies of group formation and discard strategies that will lead to deviancy training. In developing GUIDE, we are primarily interested in substance use interventions among homeless youth as a high risk and vulnerable population. GUIDE is developed in collaboration with Urban Peak, a homeless-youth serving organization in Denver, CO, and is under preparation for deployment

Robust Multiclass Queuing Theory for Wait Time Estimation in Resource Allocation Systems

In this paper, we study systems that allocate different types of scarce resources to heterogeneous allocatees based on predetermined priority rules-the U.S. deceased-donor kidney allocation system or the public housing program. We tackle the problem of estimating the wait time of an allocatee who possesses incomplete system information with regard, for example, to his relative priority, other allocatees' preferences, and resource availability. We model such systems as multiclass, multiserver queuing systems that are potentially unstable or in transient regime. We propose a novel robust optimization solution methodology that builds on the assignment problem. For first-come, first-served systems, our approach yields a mixed-integer programming formulation. For the important case where there is a hierarchy in the resource types, we strengthen our formulation through a drastic variable reduction and also propose a highly scalable heuristic, involving only the solution of a convex optimization problem (usually a second-order cone problem).We back the heuristic with an approximation guarantee that becomes tighter for larger problem sizes. We illustrate the generalizability of our approach by studying systems that operate under different priority rules, such as class priority. Numerical studies demonstrate that our approach outperforms simulation. We showcase how our methodology can be applied to assist patients in the U.S. deceased-donor kidney waitlist. We calibrate our model using historical data to estimate patients' wait times based on their kidney quality preferences, blood type, location, and rank in the waitlist

The analytics of the Greek crisis: celebratory centenary issue

We provide an empirical and theoretical analysis of the Greek Crisis of 2010. We first benchmark the crisis against all episodes of sudden stops, sovereign debt crises, and lending boom/busts in emerging and advanced economies since 1980. The decline in Greece’s output, especially investment, is deeper and more persistent than in almost any crisis on record over that period. We then propose a stylized macro-finance model to understand what happened. We find that a severe macroeconomic adjustment was inevitable given the size of the fiscal imbalance; yet a sizable share of the crisis was also the consequence of the sudden stop that started in late 2009. Our model suggests that the size of the initial macro/financial imbalances can account for much of the depth of the crisis. When we simulate an emerging market sudden stop with initial debt levels (government, private, and external) of an advanced economy, we obtain a Greek crisis. Finally, in recent years, the lack of recovery appears driven by elevated levels of non-performing loans and strong price rigidities in product markets