Behavior and Decisions
Dynamic Social Interactions and Smoking Behavior,
with Tiziano Arduini, Onur Ozgur, and Eleonora Patacchini, forthcoming, Economic Journal, 2025.
We study the risky behavior of adolescents. Concentrating on smoking, we structurally estimate a dynamic social interaction model in the context of students’ school networks included in the National Longitudinal Study of Adolescent Health (Add Health). The model allows for forward-looking behavior of agents, addiction effects, and social interactions in the form of preferences for conformity in the social network. We find strong evidence for forward-looking dynamics and addiction effects. We also find that social interactions in the estimated dynamic model are quantitatively large. A misspecified static model would fit data substantially worse while producing a much smaller estimate of the social interaction effect. The estimated dynamic model allows us to decompose the effect on smoking of a permanent shock to students’ preferences in the 10th grade – e.g., a shock to tobacco availability at home or family income – in its own direct component and in the component due to social interactions. Indeed we find large relative social effects in grade 10th, declining in grade 11th and 12th.
Replication of “Procrastination, Deadlines and Performance: Self-Control by Precommitment”
with Kyle Hyndman, 2025.
We present the results of a replication of Study 2 from Ariely and Wertenbroch (2002). We show that the results of the paper do not replicate. In particular, in the replication, changes in the deadlines have a negligible effect on the three performance metrics and several survey metrics that were used in the original study. Evenly spaced deadlines exogenously imposed on participants do not stand apart for their effectiveness in reducing procrastination in participants. While our replication of the main result fails, our data do show several patterns of participant behavior which should be expected. This suggests to us that our replication attempt is of sufficient quality, but the result itself is not robust.
Modeling Adaptive Forward-looking Behavior in Epidemics on Networks
with Leonardo Amid Nemati Fard, Michele Starnini, and Michele Tizzoni, Journal of Economic Behavior and Organizations, forthcoming, 2025.
Incorporating decision-making dynamics during an outbreak poses a challenge for epidemiology, faced by several modeling approaches siloed by different disciplines. We propose an epi-economic model where high-frequency choices of individuals respond to the infection dynamics over heterogeneous networks. Maintaining a rational forward-looking component to individual choices, agents follow a behavioral rule-of-thumb in the face of limited perceived forecasting precision in a highly uncertain epidemic environment. We describe the resulting equilibrium behavior of the epidemic by analytical expressions depending on the epidemic conditions. We study existence and welfare of equilibrium, identifying a fundamental negative externality. We also sign analytically the effects of the behavioral rule-of-thumb at different phases of the epidemic and characterize some comparative statics. Through numerical simulations, we contrast different information structures: global awareness – where individuals only know the prevalence of the disease in the population – with local awareness, where individuals know the prevalence in their neighborhood. We show that agents’ behavioral response through forward-looking choice can flatten the epidemic curve, but local awareness, by triggering highly heterogeneous behavioral responses, more effectively curbs the disease compared to global awareness.
Review of “Modeling Social Behavior: Mathematical and Agent-Based Models of Social Dynamics and Cultural Evolution,” by Paul E. Smaldino. Princeton: Princeton University Press, 2023,
Journal of Economic Literature, 62(4), 1693-95, 2024.
The book is very successful in its aim of introducing the reader to agent-based models, bringing him/her to develop the theoretical skills necessary to apply them to interesting problems. It is less successful, however, as an introduction to the broader study of social dynamics and cultural evolution, in that it disregards any contribution which is does not fit into Agent-Based modeling. In Agent-based models agents move and act as particles, without any rational (or less-than-rational) choice, without any forward-looking calculus, and independent of the specifics of the environment they find themselves in. The severity of this limitation obviously depends on the problem at hand. Given the problem, the intellectual—or even ideological—priors of the (discipline of the) researcher also contribute to evaluating the explanatory power of agent-based models: generally, economists, more than other social scientists, tend to consider rational (or less-than-rational) choice and some forward-looking behavior as fundamental dimensions of models dealing with most socioeconomic phenomena.
Procrastination, Self-Imposed Deadlines, and Other Commitment Devices,
with Kyle Hyndman, forthcoming Economic Theory, 2022.
In this paper we model a decision maker who must exert costly effort to complete a single task by a fixed deadline. Effort costs evolve stochastically in continuous time.
The decision maker optimally waits to exert effort until costs are less than a given threshold, the solution to an optimal stopping time problem. We derive the solution to this model for three cases: (1) exponential decision makers, (2) naıve hyperbolic discounters and (3) sophisticated hyperbolic discounters. Absent deadlines, we show that sophisticated hyperbolic decision makers behave as if they were time consistent but instead have a smaller reward for completing the task, while naıfs never complete the task. In the presence of deadlines, sophisticated decision makers may, counterintuitively, have a threshold which is decreasing as they approach the deadline. An extensive numerical study shows that, unlike exponential or naıfs who always prefer longer deadlines, sophisticated decision makers will often self-impose a binding deadline as a form of commitment, while naıve decision makers will not, and we show how this varies with changes in underlying cost, preference and self-control parameters.
Present-bias, Procrastination and Deadlines in a Field Experiment,
with Kyle Hyndman, Games and Economic Behavior, 119, 339-357, 2020.
We study procrastination in the context of a field experiment involving students who must exert costly effort to complete certain tasks by a fixed deadline. We document a robust demand for commitment, in the form of self-imposed deadlines. On the other hand, deadlines do not increase completion rates in our experiment. Furthermore, while we find that present-bias is widespread in the sample, and present-biased students procrastinate in single task treatments, we find that they successfully manage to self-control in repeated task treatments. Finally, we find evidence that students do not set deadlines optimally and that deadlines may hurt them, due to various behavioral components of students’ anticipation formation mechanisms; specifically, partial naïveté at the deadline setting stage and over-confidence about the ability to complete the task and to persevere on a task after a failed attempt.
Learning Epidemiology by Doing: The Empirical Implications of a Spatial-SIR Model with Behavioral Responses,
with Andrea Moro, forthcoming, Journal of Urban Economics, 2022.
We simulate a spatial behavioral model of the diffusion of an infection to understand the role of geographic characteristics: the number and distribution of outbreaks, population size, density, and agents’ movements. We show that several invariance properties of the SIR model concerning these variables do not hold when agents interact with neighbors in a (two dimensional) geographical space. Indeed, the spatial model’s local
interactions generate matching frictions and local herd immunity effects, which play a fundamental role in the infection dynamics. We also show that geographical factors change how behavioral responses affect the epidemic. We derive relevant implications for estimating the effects of the epidemic and policy interventions that use panel data from several geographical units.
Government Policy with Time Inconsistent Voters,
with Alessandro Lizzeri and Leeat Yariv, American Economic Review, 105(6): 1711–37, 2015.
Behavioral economics presents a “paternalistic” rationale for benevolent government intervention. This paper presents a model of public debt where voters have self-control problems and attempt to commit using illiquid assets. In equilibrium, government accumulates debt to respond to individuals’ desire to undo their commitments, which leads individuals to rebalance their portfolio, in turn feeding into a demand for further debt accumulation. As a consequence, (i) large (and distortionary) government debt accumulation occurs, and (ii) banning illiquid assets could improve individuals’ welfare. These results offer a new rationale for balanced budget rules in constitutions to restrain governments’ responses to voters’ self-control problems.
Other People’s Money: An Experimental Study of the Impact of the Competition for Funds,
with Marina Agranov and Andy Schotter, Experimental Economics, 17:564–585, 2014.
In this paper we experimentally investigate the impact that competing for funds has on the risk-taking behavior of laboratory portfolio managers compensated through an option-like scheme according to which the manager receives (most of) the compensation only for returns in excess of pre-specified strike price. We find that such a competitive environment and contractual arrangement lead, both in theory and in the lab, to inefficient risk taking behavior on the part of portfolio managers. We then study various policy interventions, obtained by manipulating various aspects of the competitive environment and the contractual arrangement, e.g., the Transparency of the contracts offered, the Risk Sharing component in the contract linking portfolio managers to investors, etc. While all these interventions would induce portfolio managers, at equilibrium, to efficiently invest funds in safe assets, we find that, in the lab, Transparency is most effective in incentivising managers to do so. Finally, we document a behavioral “Other People’s Money” effect in the lab, where portfolio managers tend to invest the funds of their investors in a more risky manner than their Own Money, even when it is not in either the investors’ or the managers’ interest to do so.
Present-Bias, Quasi-Hyperbolic Discounting, and Fixed Costs,
with Jess Benhabib and Andy Schotter, Games and Economic Behavior, 69(2), 205-223, 2010.
A vast literature in experimental psychology has studied time preferences by eliciting preferences over various alternative rewards obtained at different times, that is, over reward–time pairs.1 Representations of such time preferences include a specification of discounting. This literature has documented various behavioral regularities with regards to discounting. The most important of such regularities is called “reversal of preferences.” It occurs, for example, when a subject prefers $10 now rather than $12 in a day, but he/she prefers $12 in a year plus a day rather than $10 in a year. Reversals of preferences are not consistent with exponential discounting. Psychologists (e.g., Herrnstein, 1961; de Villiers and Herrnstein, 1976; Ainslie and Herrnstein, 1981; see also Ainslie, 1992, 2001) and also behavioral economists (e.g., Elster, 1979; Laibson, 1997; Loewenstein and Prelec, 1992; O’Donoghue and Rabin, 1999) have noted that reversals of preferences are instead consistent with a rate of time preference which declines with time. Various specifications of discounting with this property, notably hyperbolic discounting and quasi-hyperbolic discounting have been suggested..
Modeling Internal Commitment Mechanisms and Self-Control: A Neuroeconomics Approach to Consumption-Saving Decisions,
with Jess Benhabib, Games and Economic Behavior, 52(2), 460-92 (special Issue on Neuroeconomics), 2004
We provide a new model of consumption–saving decisions which explicitly allows for internal commitment mechanisms and self-control. Agents have the ability to invoke either automatic processes that are susceptible to the temptation of ‘over-consuming,’ or alternative control processes which require internal commitment but are immune to such temptations. Standard models in behavioral economics ignore such internal commitment mechanisms. We justify our model by showing that much of its construction is consistent with dynamic choice and cognitive control as they are understood in cognitive neuroscience. The dynamic consumption–saving behavior of an agent in the model is characterized by a simple consumption–saving goal and a cut-off rule for invoking control processes to inhibit automatic processes and implement the goal. We discuss empirical tests of our model with available individual consumption data and we suggest critical tests with brain-imaging and experimental data.