Behavioral Economics: A Tutorial for Behavior Analysts in Practice (2024)

A Tutorial for Behavior Analysts in Practice

Abstract

In recent years, behavioral economics has gained much attention in psychology andpublic policy. Despite increased interest and continued basic experimentalstudies, the application of behavioral economics to therapeutic settings remainsrelatively sparse. Using examples from both basic and applied studies, weprovide an overview of the principles comprising behavioral economicperspectives and discuss implications for behavior analysts in practice. A callfor further translational research is provided.

Keywords: behavioral economics, demand, discounting, tutorial

The field of study known as behavioral economics initially began asa purely academic attempt at modeling irrational consumer choices, therebychallenging the notion of the rational consumer of traditional economics. However,recent events have launched behavioral economics from a purely academic pursuit tothe forefront of public policy and pop psychology. Mass media books promotingbehavioral economic concepts such as Thaler and Sunstein's Nudge: ImprovingDecisions about Health, Wealth, and Happiness 2008 and Dan Ariely's PredictablyIrrational: The Hidden Forces That Shape Our Decisions 2008and The Upside of Irrationality: The Unexpected Benefits of Defying Logic atWork and at Home 2010 have gained critical acclaim and widespreadpublicity. Thaler and Sunstein's Nudge caught the interest ofPresident Barack Obama (Grunwald,2009), prompting him to appoint Sunstein as the administrator of theOffice of Information and Regulatory Affairs. Suffice it to say, behavioraleconomics has become a staple in the understanding of ways to engineer environmentsto promote sustainable and positive behavior changes. It is because of theseattributes that we propose that a behavioral economic approach to servicedelivery— based upon the principles of behavior analysis, rather thantraditional behavioral economics derived from psychology and economics—canlead to a greater understanding of behavior in academic or therapeutic settings.

Before we provide examples of how behavioral economic concepts may be applied toacademic or therapeutic settings, it is imperative to understand the assumptions ofboth traditional and behavioral approaches to economics. Collectively, the termbehavioral economics describes an approach to understandingdecision making and behavior that integrates behavioral science with economicprinciples (see ). Traditional economics, according to theclassic philosopher and economist John Stuart Mill (see Persky, 1995), assumes that humans exhibitbehavior commensurate with a hom*o economicus profile (the“economic human”). As a hom*o economicus, individualsare assumed to be completely aware of the costs and benefits associated with allpossible actions. Thus, people will subsequently behave in a way that fullymaximizes their long-term gain (i.e., humans are analogous to walking calculators,constantly considering the pros and cons of their actions and computing the bestbehavioral alternatives for the situation). All behaviors are, in this sense,carefully calculated and entirely rational. Although this perspective is laudableand gives the benefit of the doubt to the choices made by human consumers, it isclear that people do not always make decisions that maximize their long-term gain.Of course, this is an empirical question, and one that behavioral economics hasattempted to reconcile.

Behavioral economists assume a contrarian stance that individuals—no mattertheir age or intelligence— are rather myopic with respect to what is best forthem. Behavioral economics assumes irrationality in decisionmaking. As such, individuals are susceptible to temptations and tend to make poorand rash decisions, even though it is clear there are better options that willimprove long-term outcomes. Thalerand Sunstein (2008) propose that the term “Homer”economicus replace the hom*o economicus of traditionaleconomics when describing humans, as most decision makers resemble the fictionalHomer Simpson (e.g., they live for the moment, discount delayed consequences, paypoor attention to detail, and are relatively uninformed of behavioralcosts/benefits). An astute observer of human behavior will undoubtedly agree thatmany behaviors are less-than-rational. Undergraduates check social media pages,rather than take notes during lecture, despite the resulting loss in knowledgeacquisition and possible detriment to their chances of doing well in the class.Children choose a brownie over an apple in the lunch line, despite the long-termdecrements in health. Teachers and administrators deviate from empirically supportedcurricula to gain student approval or make lesson plans easier to implement, despitethe loss in student learning and subsequent dips in evaluations of teachingefficacy.

Notwithstanding the consensus that behavioral economics accounts for irrationalbehaviors, a wide continuum exists within this field with respect to theprinciples that may explain such irrationality.

Notwithstanding the consensus that behavioral economics accounts for irrationalbehaviors, a wide continuum exists within this field with respect to the principlesthat may explain such irrationality. On one end of the continuum,theorists take a more cognitive perspective, and contend that irrational behaviorsare the result of mentalistic or psychological causes such asstereotype biases, cognitive fallacies, or psychological predispositions (see Camerer, 1999; ). On the opposite side of the continuum lie the behaviorist'sperspective that irrationality is grounded in principles of operant learning (seeMadden, 2000; Skinner, 1953), assuming thatenvironmental influences establish particular negative consequences (thoseassociated with irrational or problematic behaviors; e.g., risk taking, cheating ontests, unhealthy food choices) as having more reinforcing value than other morepositive consequences (those associated with rational or desirable behaviors; e.g.,self-control, studying for a test, healthy food choices). Behavioral economists havetermed this approach the “reinforcer pathology” model, suggesting thatpathological patterns of responding for differentially valued reinforcers may be amore parsimonious and conceptually systematic explanation for irrational behaviorsthan mentalistic constructs (). For the remainderof this tutorial, we will speak exclusively of behavioral economics using thebehaviorist perspective for two reasons. First, while behavioral economics stemmingfrom psychology and economics feature an interesting and dense literature base, thebehaviorist perspective is parsimonious and does not require abstract theoreticalexplanations that are difficult to empirically evaluate and observe. Becausebehavioral economics is expressed in the language of operant learning, a languagethat is familiar to behavior analysts, the behaviorist approach provides a frameworkthat is easily understood and recommendations on how environments can be altered inways that promote positive behavior change can be implemented relatively quickly.Second, recent research has begun to suggest that behaviorist perspectives ofeconomic principles can succinctly explain the findings of the more mentalisticapproaches to irrational behaviors (e.g., ; ). By using a perspective that is conceptually systematicwith radical behaviorism to explain these irrational behaviors, environmentalinfluences of irrational behaviors are analyzed, which in turn suggest thatenvironmental solutions can be employed to help improve decision making.

The behaviorist approach to behavioral economics was explicitly summarized by Hursh (1980), who proposedthat economic concepts could better advance a science of human behavior. Hursh (1984) further advisedthat operant concepts could help explain principles of behavioral economics. Inshort, behavior analysis provides both complementary and explanatory solutions tobehavioral economic concepts. The concepts outlined by Hursh (1980, 1984) for understanding behavioral economicsinclude (a) demand functions, (b) reinforcer competition, and (c) open versus closedeconomies. In recent years, behavior analysts have also added the concept ofdiscounting to this list (see ).

The present tutorial explores how each of these four concepts can contribute to anunderstanding of the ecology of applied settings. Also, these concepts can helpestablish a number of theoretical underpinnings for effective behavior managementprocedures. We believe that behavioral economics is particularly suited forapplication in practical settings for several reasons. First, behavioral economicshas a large and dense evidence base supporting its use and efficacy in laboratorystudies, thus the principles discussed here are well established through empiricalresearch. Second, although behavioral economics has experienced a relative boom inexperimental support, its applied utility remains largely undocumented in lesscontrolled therapeutic settings. A secondary purpose of this tutorial, therefore, isto challenge behavioral practitioners and researchers to integrate these principlesand concepts into their own practices to broaden the applied knowledge base ofbehavioral economic concepts in academic and therapeutic settings. We believe thatbehavioral economics has much to offer, despite the relative paucity of research andseemingly esoteric nature of this topic. Novel research applying behavioral economicprinciples to challenges in therapeutic settings is well overdue. Thirdly, becausebehavioral economics considers the interplay of economic systems and multipleecologies of reinforcement, this approach is an excellent complement to Sheridan and Gutkin's(2000) and Burns'(2011) call for ecological approaches to assessment and interventionconceptualization in treatment settings. By doing so, behavioral economicconsiderations fall squarely within the behavior analytic approach to therapeuticservices that behavior analysts have been advocating for some time ().Finally, and perhaps most importantly, behavioral economic approaches are inherentlyefficient because they focus on relatively simple environmental factors that canpromote positive behavior change. In an era of economic uncertainty and budgetaryconstraints, cost-effective empirically supported interventions are at a premium.Applying behavioral economic concepts to service delivery settings may be an idealsolution for today's economic challenges.

This tutorial will detail each of the behavioral economic concepts that have beendiscussed in both the experimental and applied literature. We will describe eachconcept using lay examples, supplementing these discussions with examples from basicand applied research. Finally, we will provide implications of each concept forbehavior analysts in practice when evaluating their own settings or interventionstrategies.

General Principles and Basic Terminology

A number of economic terms will be used throughout the remainder of thetutorial—terms such as commodity, consumption, cost, benefit,price, and unit price. Therefore, it is important thatthese terms be defined before proceeding. We will use a running example throughoutthis section to aid in defining and elucidating the core concepts associated withbehavioral economic analyses. For this example, consider a child who is working toobtain tokens exchangeable for backup reinforcers. Tokens are contingent upon anumber of words read correctly per minute during a reading intervention.

Commodity. In traditional economics, a commodity is a good or event thatis available in the market for purchase/consumption. In behavioral economics, theterm commodity refers to the reinforcer or item for which an individual will work toobtain. Similar to reinforcers, commodities may range from tangible (e.g., toys) tointangible goods (e.g., teacher attention). In our example above, the primarycommodity of interest is tokens (obtained via correctly read words). One could alsoconsider the backup reinforcers as a secondary commodity (obtained via expenditureof tokens).

Consumption. In economic analyses, consumption is the process ofengaging with the commodity of interest following a purchase, given its cost. Inbehavioral economics, the term consumption refers to the amount of a commodityobtained in a given session or observation (e.g., number of tokens or praisestatements earned). Most often we are concerned with total consumption, or theoverall amount of a commodity obtained within a session. Using the previous example,reading a prespecified number of words correctly per minute during the interventionenables the consumption of tokens by the student. Exchanging the tokens for otheritems or activities results in the consumption of backup reinforcers.

Cost, benefit, and unit price. To consume a commodity, an individual orgroup of individuals must meet some requirement related to cost, benefit, and unitprice. When we speak of cost in behavioral economic terms, we are referring to somerequirement an individual has to meet in order to obtain a given commodity (). Most commonly, cost is quantified by the number ofresponses required to obtain the commodity (e.g., ten responses or fixed ratio[FR] 10) but may also be measured in other characteristics, such as theexpenditure of effort, the amount of money exchanged, or the amount of time thatpasses until the delivery of a reinforcer. The term benefit refersto the amount of a commodity that can be obtained (Hursh et al., 2013). For example, tenresponses may allow a person to obtain one token. Together, the cost and benefit ofa commodity comprise the price of a commodity. In behavioral economics, the price iscalculated as a ratio of costs and benefits and is referred to as unitprice (for the remainder of this tutorial, price and unit price will beused interchangeably). Within our running example, the cost of each token is tocorrectly read the specified number of words within a minute. The cost of eachbackup reinforcer is the number of tokens exchangeable for the item or activity.During the first phase of the intervention, the behavior analyst may require oneword read correctly per minute to access a token; thus, the unit price equals thecost (one word read correctly per minute) divided by the benefit (one token), whichequals 1.00. As the intervention progresses, the behavior analyst may start to fadethe tokens, thereby increasing the unit price of tokens. Rather than one wordcorrect for one token (a unit price of 1.00), the behavior analyst may require twowords correct in a minute to access a token (two words divided by one token equals aunit price of 2.00). Exchanging the tokens for other goods also operates using unitprices. For example, if 10 tokens equal 10 minutes of computer time, the unit priceis 1.00. However, 20 tokens may access 40 minutes of computer time, equating to aunit price of .50.

The Law of Demand. At the crux of behavioral economics is thelaw of demand, which suggests that consumption declines whenthe unit price of a given commodity increases (). Using thereading intervention example, consider what might happen if the unit price of atoken became very high. Suppose that 100 words read correctly per minute resulted inthe consumption of one token. At such a high unit price, the student may stopresponding and no longer consume reinforcers (tokens and the backup reinforcers).The law of demand suggests that any reinforcer, regardless of the strength ofpreference for that commodity, will lose its relative reinforcing efficacy if theunit price becomes too large. Loss of reinforcing efficacy suggests that thecommodity's classification as a reinforcer will be lost and responding toaccess that commodity will no longer persist.

Demand Functions

In any kind of economy, the price-setting agent (i.e., the retailer, the behavioranalyst) seeks to identify the highest price that consumers will tolerate assumingthe commodity of interest is sensitive to the law of demand. In the reading exampleabove, the behavior analyst would be interested in the highest number of words thestudent will read in order to earn each token. The degree to which consumptionremains stable across price increases is considered the consumers'demand. Demand that maintains a stable level of consumptionacross price increases is considered inelastic. For example, thestudent above may consume just as many tokens if the tokens cost three words perminute or six words per minute. That is, consumption does not change as a functionof price. When a price becomes too high and exceeds the consumer's threshold ofacceptability, consumption of the commodity decreases, resulting inelastic demand. This falls within the assumptions of the law ofdemand. Elastic demand is depicted in the demand curve in the left panel of Figure 1. As Figure 1 illustrates,consumption of the target commodity is plotted on the y-axis as a function of unitprice (which is plotted on the x-axis). In the simulated data comprising Figure 1, consumption remainsrelatively constant until a unit price of approximately 20; this constitutes theinelastic portion of the demand curve. Consumption subsequently decreases as unitprices become higher than 20, indicating elasticity. The unit price at which zerocommodities or reinforcers are consumed is termed the breakpoint.

A second way to examine the relationship between consumption and price is with thework function, depicted in the right panel of Figure 1. The work function illustrates howresponding—rather than consumption— increases and decreases withincreases in price. Similar to the demand curve plot (left panel of Figure 1), responding isdepicted as a function of unit price. The reader will note that the point in whichthe pattern moves from inelastic to elastic is equal across the demand and workfunctions of Figure 1; aunit price of approximately 20. Conceptually, this indicates that the peak level ofresponding is associated with the highest unit price that sustained consumption.

Comparisons of reinforcer demand are one way to examine relative reinforcer efficacy.Researchers have likened this measure as an index of “behavior-maintenancepotency” (, p. 192), suggesting that reinforcers under strongdemand will maintain behavior at higher response requirements than alternativereinforcers of lesser demand. An important consideration when evaluating reinforcersis that reinforcer efficacy is a multifaceted construct (; ).Thus, behavior analysts must consider the collective factors of derived responserates, demand elasticity, and breakpoints for each reinforcer examined, takingspecial precautions to ensure that the context of the evaluation is held constant topermit comparisons of relative reinforcer efficacy using demand curve analyses.

Hursh and colleagues () provided a seminal studyon the utility of demand curves when considering demand for preferred commodities intheir paper using rats working for food pellets. The price was set by manipulatingthe number of responses necessary to earn access to the food. As the priceincreased, the rats' consumption of food (demand) and numbers of responses(work) initially increased (inelastic), but eventually resulted in a point ofelasticity wherein consumption and responding decreased, similar to the exampledemand and work functions in Figure1.

Whether intentional or not, behavior analysts manipulate demand functions on adaily basis. This concept is not restricted to incentive-based programs such astoken economies or reinforcement schedules.

Borrero and colleagues () applied the logic of acost-benefit analysis to reinforcer demand using descriptive data on children'ssevere problem behavior. These researchers first calculated prices for reinforcersby dividing the number of problem behaviors observed (cost) by the number ofreinforcers obtained during an observation interval (benefit). This calculationresulted in a unit price for the reinforcers. They then plotted consumption ofreinforcers across unit prices and yielded demand curve functions akin to thosedescribed above. The findings from the Borrero et al. study suggest thatchildren's problem behavior can be assessed within an economic framework,similar to studies done in basic experimental laboratories. In a proactive approachto treatment conceptualization within an economic framework, Roane, Lerman, and Vorndran (2001) applieddemand analyses to the examination of reinforcer efficacy in children withdevelopmental disabilities. Toys previously identified as highly preferred generatedhigher breakpoints than toys identified as less-preferred as the unit price of thesecommodities were increased. The highly preferred toys that produced higherbreakpoints served as more effective reinforcers in treating problem behavior.

Reinforcer Competition

In economics, commodities compete for consumers' spending or resources. Thiscompetition is what fuels the supply and demand effects previously discussed.Multiple commodities are at work in any given environment, and these commodities caninteract with each other in several different ways. We can categorize the status ofa commodity as being (a) substitutable, (b)complementary, or (c) independent based upontheir effects on spending (see Green & Freed; 1993, Hursh, 2000; Madden, 2000). Commodities aresubstitutable if and when increases in one commodity'sunit price conforms to the law of demand (i.e., consumption of that commoditydecreases as a function of increased unit price) while there is a simultaneousincrease in consumption of a second concurrently available commodity at a lower unitprice. An example of substitutability may be a situation wherein a client initiallydemonstrates indifference for cherry and strawberry flavored candies, the clientlikes both and chooses each of them equally. However, when strawberry candiesundergo a unit price increase (e.g., more responses or tokens are required to accessthe strawberry candy), preference shifts to cherry candies. Complementaryreinforcers are those that feature simultaneous increases or decreases inconsumption of both commodities, despite unit price manipulations on only one of thecommodities. Consider a situation in which a behavior analyst works to increase herclient's physical activity as part of a weight loss program by increasing theprice required to play video games. As the unit price of video game accessincreases, its consumption decreases, along with decreases of consumption of saltysnacks despite no unit price manipulation on the snacks. That is, salty snacks oftengo along with playing video games, so decreases in video game consumption result inconcomitant decreases in salty snack consumption. Because consumption changed in thesame direction for both commodities in the context of one commodity's increasein unit price, we would functionally define video game play and salty snack foods ascomplementary reinforcers. Finally, independent reinforcers feature no change inconsumption, despite changes in consumption of a concurrently available alternativecommodity as a function of unit price manipulations. An example of independenceusing the previous example would be where increases in the unit price of video gameaccess have no effect on consumption of water. These two reinforcers are not relatedto each other, so changes in unit price for either one would have no effect onconsumption of the other. In sum, these concepts categorize the effects of multiplereinforcers on behavior. When new commodities are introduced into the economicsystem, it is useful to determine status of new commodities to determine how itinteracts with other commodities already at work in the environment.

When the price was equal, the rats preferred root beer. However, as the price ofthe root beer increased and the Tom Collins mix remained relatively low, therats exhibited a preference for Tom Collins mix; thus, root beer and Tom Collinsmix were considered substitutable.

To understand the role of competitive reinforcers, behavioral economists typicallyemploy demand curve analyses as described above (see Bickel et al., 2000; ). In one exampleof the substitutability of reinforcers, Rachlin, Green, Kagel, and Battalio (1976)provided rats the choice between root beer and Tom Collins mix when both wereassociated with an equal and low response requirement (i.e., the number of leverpresses necessary to obtain the drink). When the price was equal, the rats preferredroot beer. However, as the price of the root beer increased and the Tom Collins mixremained relatively low, the rats exhibited a preference for Tom Collins mix; thus,root beer and Tom Collins mix were considered substitutable. In this comparison,Rachlin and colleagues provided the first demonstration of the interplay betweendemand and substitutability in operant behavior.

In Figure 3, exampleillustrations of both substitutable and complementary reinforcers are provided. Inthe left panel, substitutable reinforcers are illustrated (e.g., tokens and peerattention). As the price of Commodity A (e.g., tokens) increases, consumption ofthat commodity eventually becomes elastic and decreases. Concurrently, Commodity B(e.g., peer attention)—which has a lower unit price that has notincreased—begins to be consumed relatively more often when Commodity A reachesa point of elasticity due to the increase in price. In the right panel of Figure 3, a complementaryrelation is depicted (e.g., token delivery and praise), where increases in price forCommodity A result in decreased consumption of both Commodities A and B.

In an interesting translation of reinforcer competition, Salvy, Nitecki, and Epstein (2009) examinedthe degree to which social activities and food serve as substitutable reinforcersfor both lean and overweight preadolescent youth. The preparation consisted ofhaving the youth press a computer mouse button to earn access to tater tots orsocial time with familiar or unfamiliar peers. When the response requirement (theprice) for food increased while that for social time with an unfamiliar peerremained constant, the participants worked harder and earned more social time.Alternatively, when the price of social time with unfamiliar peers increased (andthat of food remained constant), participants worked harder and earned more food.Interestingly, the researchers found that food and social time with familiar peers(friends) were independent. That is, participants always worked harder to engage insocial time with friends, regardless of the price for social time or food.Collectively, these data imply that food and social time with unfamiliar peers maybe substitutable reinforcers, and that social time with friends is always morereinforcing than food. This offers behavior analysts important practicalimplications for designing interventions to counter obesity in school-agedchildren.

Open and Closed Economies

One of the most commonly known and recited economic principles is that of“supply and demand.” John Locke succinctly described this principle in1691 by writing that:

the measure of the value of Money, in proportion to any thing purchasable by it,is the quantity of the ready Money we have, in Comparison with the quantity ofthat thing and its Vent; or which amounts to the same thing, The price of anyCommodity rises or falls, by the proportion of the number of Buyers and Sellers.[sic] (p. 16)

In sum, when a commodity is in short supply, its value increases. Tokens, forexample, are effective in changing behavior because they are in short supply.However, if a behavior analyst offered tokens on a noncontingent schedule, therewould be a diminished demand for tokens such that the clients no longer emit thebehaviors that previously resulted in contingent token delivery.

In his seminal papers on the application of economic principles to the experimentalanalysis of behavior, Hursh(1980, 1984)described any behavioral experiment— in the present case, any behavioralintervention program—as being an economic system. In such“economies,” the value of the reinforcer depends on its relativeavailability both within and outside the system. When reinforcers are available onlyin the target system, the economy is considered “closed.” For example, asetting where staff attention is only available via functional communication wouldconstitute a closed economy. On the contrary, economies that permit supplementalaccess to the reinforcer outside the target system are considered“open.” In a setting with an open economy, staff attention would beavailable through many modes of communication, ranging from appropriate functionalcommunication to inappropriate forms of attention-motivated behaviors such asself-injury or aggression. As the notion of supply and demand suggests, supplementalaccess to the reinforcer outside the target system increases its supply andsubsequently decreases its demand. In classroom settings where extra credit pointsare abundantly available (open economies), assignment completion may be low becausethere is plenty of opportunity to access class points outside of the bounds of thein-class assignments and homework. In a classroom where there is no extra creditavailable (closed economies), assignment completion may be high because the studentsmust work within the bounds of the in-class assignments and homework to earn theirpoints.

In a basic example of open and closed economies, LaFiette and Fantino (1989) compared pigeonsresponding under conditions in which sessions were run for either (a) 1 h whilemaintained at 80% free-feeding body weight with free postsession access tofood (i.e., an open economy) or (b) 23.5 h without a food deprivation procedure(i.e., a closed economy). As predicted, results indicated substantially higher ratesof responding in the closed economy conditions. Collier, Johnson, and Morgan (1992) yieldedsimilar open vs. closed economy effects, but also documented a reward magnitudeeffect in the closed economy wherein smaller reward magnitudes generated higherrates of responding than larger ones.

In academic or therapeutic contexts, all academic or behavioral interventions fallinto either an open or closed economy classification. Given the experimentalfindings from nonhuman studies on this topic and the implications they have on theway classroom contingencies are designed, it is unfortunate that no studies (that weare aware of) have explicitly compared open and closed economies in traditionalclassrooms with neurotypical students. While very few in number, there arefortunately two articles that address open and closed economies with individualswith developmental disabilities in applied settings using academic tasks asoperants.

Roane, Call, and Falcomata(2005) compared responding under open and closed economies for both anadult and an adolescent with developmental disabilities. The behavior of interestfor the adult was a vocational task (mail sorting) while the behavior of interestfor the adolescent was math problem completion. Prior to the experimentalmanipulation, the researchers recorded the amount of time the participants spentengaging in preferred activities; video watching for the adult, video game playingfor the adolescent. These observations were used to fix the percentage of time theparticipants could engage in the activity during open economy conditions(approximately 75%). During both open and closed economy conditions,participants could earn access to their preferred activity by meeting responserequirements programmed on PR schedules. Participants received supplemental accessto preferred activities following experimental sessions in the open economycondition. The degree of post-session supplemental access varied depending on theamount of reinforcement obtained during the sessions, with each daily amountequaling 75% of the pre-experimental observation lengths. In the closedeconomy, no supplemental access to the preferred activities was provided outside ofthe sessions. Results replicated those obtained in nonhuman studies; both open andclosed economies increase responding from baseline levels, with relatively higherrates of responding occurring in closed economy conditions. Moreover, Roane andcolleagues demonstrated that PR breakpoints were substantially higher in the closedeconomies, supporting the notion that limited supply increases the potency/demand ofthe reinforcer.

In an extension to Roane etal.'s (2005) study, Kodak, Lerman, and Call (2007) evaluated theeffects of reinforcer choice under open (i.e., post-session reinforcement available)and closed economies on math problem completion for three children withdevelopmental disabilities. The general procedure mimicked that of Roane andcolleagues, with the exception of a choice of math problems to be completed and theuse of edible reinforcers. Two stacks of math problems were present during both openand closed economies; one stack of problems was associated with the top-rankededible from a preference assessment, and the other stack was associated with thesecond-ranked edible. Again, responding was highest under closed economy conditions.Interestingly, participants switched preference away from the top-ranked edible tothe second-ranked edible when the PR schedules for the top-ranked edible wererelatively high in the closed economy condition. These findings provide furtherconfidence in the cross-species generality of the open vs. closed economy phenomena,and provide a more ecologically valid depiction of how open and closed economiesmight function in applied settings when more than one reinforcer may be concurrentlyavailable for a target behavior.

Delay Discounting

Behavioral economic studies of intertemporal choice and decision making haverepeatedly demonstrated that humans (and nonhumans) are rather myopic when facedwith delayed consequences (). In these studies, researchers typically askparticipants to choose between receiving hypothetical monetary outcomes at variousdelays, such as $100 in 10 years, or $150 in 12 years. If theparticipants are like most people who have taken part in such studies, they probablychoose the $150 (in 12 years); after all, $150 is greater than$100. Now, suppose the participants are presented with another choice; thistime, they can choose to receive $100 right now or $150 two years fromnow. When presented with this decision, many individuals who previously chose thelarger delayed reward switch to preferring the smaller immediate reward. Thisphenomenon is termed a preference reversal (see Ainslie, 1974; )and implies that individuals' values of delayed rewards are myopic in nature(e.g., ). Interestingly, both the difference in delay and the difference inreward magnitude are identical in both decision-making tasks; however, preferencehas reversed.

According to traditional economic theory, humans lawfully make rational choices.Given the results of the decision-making task above, this is clearly not the case.This notion of preference reversals may explain why individuals make manyless-than-optimal decisions, such as planning to study for a major test but insteadwatching a television show, using credit cards with high interest rates toimmediately purchase an item that will take a while to pay off, or eating unhealthyfoods that taste good now but ultimately harm long-term health. These types ofirrational choices can be explained by a phenomenon that behavioral economists calldiscounting (see ). Discountingdescribes a behavioral pattern in which contextual factors associated with thereward (in this case, delay until the receipt of the reward) diminishes the value ofa given outcome.

Mazur (1987) was one of thefirst researchers to assess rates of delay discounting by using an adjustingdelay procedure. In Mazur's procedure, pigeons repeatedly chosebetween a larger amount of food pellets after an adjusting delay and a smalleramount of food pellets after a fixed delay. If the pigeon chose the larger laterreward (LLR), the delay to the LLR would increase on the subsequent trial. On theother hand, if the pigeon chose the smaller sooner reward (SSR), the delay to theLLR would decrease on the subsequent trial. This procedure was used to determine thepoint at which the pigeon switched from choosing the LLR to the SSR. The value atwhich switching from the LLR to the SSR is termed an indifferencepoint because it is the point at which the subjective values of bothalternatives are deemed equal. Mazur used several different mathematical functionsto explain the manner in which the pigeons discounted delayed outcomes, and whenplotted, Mazur found that the obtained indifference points followed a hyperbolicfunction.

Figure 4 illustrates atypical discounting curve that follows a hyperbolic function. Various delay valuesare plotted on the x-axis and the subjective value of a reinforceris plotted on the y-axis. As the delay to the receipt of the rewardincreases, the subjective value of the reward decreases. Thus, delayed outcomes aresubjectively valued less than more immediate outcomes.

The most widely used procedures for determining discounting parameters in humans havebeen variations on a procedure originally created by Rachlin, Raineri, and Cross (1991). In thisprocedure, participants make choices between two hypothetical outcomes:$1,000 now and $1,000 after varying delays. At the start of eachdelay, the amount of the two alternatives is set equal. On each consecutive trial,the amount of the alternative delivered immediately decreases by an amount until thealternatives are $1 now vs. $1,000 after the delay. After thedescending portion is completed, the procedure repeats in an ascending order untilthe alternatives are, again, both valued at $1,000. An indifference point isthen obtained by averaging the point in which the participant switches from theimmediate outcome to the delayed outcome (for the descending sequence) and the pointat which the switch is made from the delayed outcome to the immediate outcome (forthe ascending sequence). Even though these procedures typically use hypotheticalrewards, researchers have found that there is no difference in obtained rates ofdiscounting when real or hypothetical rewards are used (; Madden et al., 2003).

Green, Myerson, and Ostaszewski(1999) compared discounting rates of typically developing sixth-gradechildren with discounting rates of older adults. Results suggested that childrendiscounted more steeply, indicating preference for smaller sooner rewards. In anextension of this research, Reedand Martens (2011) assessed discounting rates for 46 typically developingsixth-grade students. The researchers then implemented a class-wide interventiontargeting on-task behavior by delivering reinforcement immediately after a classperiod, or tokens that could be exchanged 24 hours later for a back-up reinforcerfor on-task behavior. Reed and Martens found that discounting rates adequatelypredicted on-task behavior during the intervention. In other words, for thosestudents who showed higher discounting scores, the delayed rewards were lesseffective in improving on-task behavior than immediate rewards. These studiessuggest that children do indeed discount delayed rewards, and such discounting isassociated with real-world outcomes of interest to school-based practitioners. Thesediscounting effects also appear to be more pronounced in children diagnosed withattention-deficit hyperactivity disorder (ADHD; ; Scheres et al.,2006).

The notion that preferring smaller sooner rewards over larger later ones isirrational provides an impetus for practitioners to design interventions that areconceptually systematic with respect to behavioral economics. In a classic study,Schweitzer and Sulzer-Azaroff(1988) operationally defined self-control as preference for largerdelayed rewards. In their study, the researchers offered children the choice betweentwo boxes; one box with one reinforcer, the other with three reinforcers. In apre-assessment, the researchers documented a discounting effect wherein the childrenpreferred to have an immediately available smaller reward (the box with only onereinforcer) to a delayed and larger reward. They then implemented a self-controltraining procedure that began by asking the children to choose either box, both ofwhich were immediately available. When both were immediately available, the childrenchose the box associated with more reinforcers. The procedure progressed bygradually increasing the durations of the delay for the box with more reinforcersacross subsequent sessions. At post-assessment, the researchers found that four outof the five children shifted their preference for the delayed reinforcer away fromtheir pre-assessment preference for the immediate reinforcer. These results suggestthat viewing self-control as a form of discounting may have implications forclassroom instruction and behavior management. More importantly, it may be possibleto design behavioral interventions to promote self-control choices in children.

Conclusion

Behavioral economics represents the interplay between economic principles andbehavior change considerations. The notion of behavioral economics in academic ortherapeutic settings is most accurately described as a ubiquitous concept ratherthan a behavior change procedure since these principles are in play regardless ofwhether change agents have intentionally programmed such contingencies orinterventions. As an ever-present concept, behavior analysts in practice should seekto identify the behavioral economic principles actively controlling clients'behaviors and find ways to restructure contingencies to promote desired outcomes.Across disciplines, behavioral economic concepts remain relatively undocumented innonclinical settings, such as home-based services, regular education classrooms, andthe workplace. Applied behavioral economists, behavior analysts, educators, andclinicians alike would profit from integrating such concepts into topics of everydayrelevance. While scientific translation across these disciplines remain relativelysparse (; Reed,2008), bridging the gap between behavioral science and practice represents anexcellent avenue for use-inspired research () to improvebehavior analytic service delivery. As behavioral economics continues to rise inpopularity in the behavioral sciences (; Camerer, 1999) and publicpolicy (e.g., Grunwald,2009; ), it would behoove applied researchers and practitioners to beginproffering examples of these concepts in both science and practice. The conceptsoffered in this article are merely starting points for potentially exciting andeffective applications in behavior analytic settings.

Footnotes

References