Association for Behavior Analysis International

The Association for Behavior Analysis International® (ABAI) is a nonprofit membership organization with the mission to contribute to the well-being of society by developing, enhancing, and supporting the growth and vitality of the science of behavior analysis through research, education, and practice.


49th Annual Convention; Denver, CO; 2023

Event Details

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Symposium #387
Advances in Behavioral Economics
Monday, May 29, 2023
3:00 PM–4:50 PM
Hyatt Regency, Centennial Ballroom B
Area: EAB/BPN; Domain: Theory
Chair: Federico Sanabria (Arizona State University)
Discussant: Steven Hursh (Institutes for Behavior Resources, Inc.; Johns Hopkins University School of Medicine)

In recent years, behavioral economic analyses have delivered key theoretical insights on the nature of reinforcement, with substantial implications for basic and applied behavior analytic research. This symposium will discuss the impact of the latest advances in behavioral economics through a sample of the latest research conducted in the field, obtained from across a broad range of behavior analytic sub-disciplines. These developments include the incorporation of a broader range of reinforcers and behaviors (informational reinforcers, adjunctive behaviors) into the assessment of reinforcer efficacy and value, a review and elaboration of the theoretical principles that guide behavioral economic assessments and analyses, and the translation of these assessments and analyses from the laboratory to regulatory policies related to substance abuse. These advances are drawn from methods and models ranging from hypothetical purchase tasks to behavioral pharmacology and animal behavior. A discussion of this research will lay the path forward for future theoretical, empirical, and applied developments in behavioral economics.

Instruction Level: Intermediate
Keyword(s): Choice behavior, Maximization, Nicotine, Schedule-induced behavior
Treatment Consumption as Maximization of Utilitarian and Information Reinforcement
SHAWN PATRICK GILROY (Louisiana State University)
Abstract: Historical applications of the Operant Demand Framework have emphasized comparisons of direct reinforcer effects (i.e., Utilitarian Reinforcement). Work in this area typically evaluates reinforcers within a similar functional class and explores if, and the degree to which, the consumption of one type of reinforcer may be substitutable with another reinforcer in a similar class (e.g., drug reinforcers). Research applying Consumer Behavior Analysis evaluates consumption as a function of factors that extend beyond direct reinforcer effects (e.g., Informational Reinforcers) and this approach accounts for the indirect social and ecological factors that can influence choice behavior. Data from hypothetical purchase tasks evaluating caregiver preferences for parent-mediated behavior therapy will be reviewed to highlight how both competing and complementary contingencies underpin caregiver choices. Specifically, findings that caregivers differentially maximized different types of contingencies suggest that studies of choice behavior need to account for a broader range of immediate and delayed contingencies. These findings will be discussed in the context of advocating for effective services (i.e., Applied Behavior Analysis).
Are All Reinforcers the Same? Behavioral Assessments of Different Reinforcers and Behavior Acquisition
Abstract: There is contradictory evidence that using different reinforces yield different rates of behaviors. A previous study in our lab suggested that rats did not show differences in rates of lever-pressing or schedule-induced running using water, food, or qualitatively varied reinforcement (water and food). On the other hand, a more recent study showed differences in schedule-induced licking and magazine entering when using a highly valued reinforcer vs. a less valued reinforcer. One of the differences between the first and the second study is the relationship between reinforcers, as water and food (first study) are usually complementary, whereas in the second study, both reinforcers were more likely substitutable, as they were pellets of different flavors. Furthermore, when rats were exposed to reinforcers of different values, they developed different rates of schedule-induced behaviors, more specifically, magazine-entering showed a higher rate when a highly valued reinforcer was used, and licking showed a higher rate when a less valued reinforcer was used, providing evidence of a higher effect of reinforcement value over the most proximal previous behavior. These types of assessments highlight the pertinence of the molecular approach when discussing the mechanisms by which behaviors are acquired.
Behavioral Economics in Tobacco Regulatory Science
JOHN R. SMETHELLS (Hennepin Healthcare Research Institute), Mark G. LeSage (Hennepin Healthcare Research Institute; University of Minnesota)
Abstract: The Center for Tobacco Products (CTP) at the FDA is charged with setting standards for tobacco products, including e-cigarettes, to protect public health. One key focus is to assess how regulatory policies could alter the abuse liability of tobacco products or impact tobacco use in vulnerable sub-populations (i.e., those with depression or ADHD). Behavioral economics provides a method to model tobacco regulatory policy and its effect on the abuse liability of tobacco products using animal models. This presentation will illustrate how our lab has employed behavioral economic analyses to assess how non-nicotine constituents in tobacco and psychiatric comorbidities influence the reinforcing efficacy of nicotine. We have also modeled the impact of changing the price of nicotine on substitution between products using cross-price demand analysis and we’ve derived a commodity relation index that normalizes changes in consumption between dissimilar commodities. Collectively, these studies show how animal models that incorporate behavioral economic approaches can inform the FDA CTP on the potential impact of tobacco regulatory policies on public health.

Theoretical Foundations for Value Assessment: A Demand Equation Drawn From Maximization Principles

FEDERICO SANABRIA (Arizona State University), Cristina Santos (Arizona State University), Matthew Gildea (Arizona State University)

The incentive value of reinforcers is often assessed from parameter estimates obtained from fits of the exponential-demand equation to empirical demand curves. Despite the prevalence of this approach, the specific mathematical expression of the exponential-demand equation is purely descriptive—its merit lies in its goodness-of-fit, not on the soundness of any theoretical premises on which it is based. This presentation shows how an asymptotic demand equation may be built from intuitive maximization principles. We demonstrate that this equation cannot, however, account for key features of empirical data. It is also shown that an additional assumption on the suppressive effects of reinforcement on subsequent behavior aligns the maximization-derived equation with behavioral data. The proposed model is slightly more complex than the exponential-demand equation, but, because it is grounded in theory, it pays its way with parameters that are more readily interpretable in terms of behavioral processes without sacrificing goodness-of-fit. Other discrepancies between the proposed model over the exponential-demand equation, and advantages of the former over the latter, are discussed.




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