By Matt Harrington, BCBA · Behaviorist Book Club · Research-backed answers for behavior analysts
The matching law describes the relationship between the relative rate of an organism's behavior and the relative rate of reinforcement available for that behavior. In practice, organisms allocate responding proportionally to the reinforcement they receive — richer schedules attract more behavior. For BCBAs, the matching law explains why challenging behavior persists even when alternative behaviors are taught: if the challenging behavior produces reinforcement on a richer or more immediate schedule than the alternative, it will continue to predominate. This framework directs clinicians to design reinforcement schedules that make adaptive alternatives more competitive, not just to teach them.
Temporal discounting is the systematic reduction in the perceived value of a reinforcer as the delay to its delivery increases. The larger-later versus smaller-sooner choice is the classic demonstration: most organisms — including humans — prefer a smaller immediate reward over a larger delayed one, and this preference intensifies as the delay to the larger reward increases. For BCBAs, this means that the effectiveness of a reinforcer is not just a function of its magnitude or quality but also of how immediately it is delivered. Clients who show steep temporal discounting require immediate or near-immediate reinforcement to maintain motivated, on-task behavior.
Standard economic models assume exponential discounting — a constant rate of devaluation per unit of delay, producing consistent preferences over time. Hyperbolic discounting, which better fits empirical data from both human and non-human subjects, produces a steeper devaluation at short delays and a shallower slope at longer delays. This creates preference reversals: a person may prefer a larger delayed reward over a smaller immediate one when both are far in the future but reverse that preference as the smaller immediate reward approaches. Leonard Green's research has been central to establishing hyperbolic discounting as the more empirically accurate model of choice behavior.
Behavioral economics emerged from the intersection of experimental psychology and neoclassical economics in the mid-20th century. Researchers like Herrnstein showed that choice behavior in the laboratory was governed by quantifiable reinforcement relationships rather than the utility maximization assumed by classical economics. Leonard Green's work extended this by examining how delay and probability affect reinforcer value in ways that standard economic models failed to predict. This body of research demonstrated that behavioral data, collected under controlled conditions, could generate insights about decision-making that were both scientifically rigorous and practically applicable to real-world economic behavior.
The matching law implies that changes in reinforcement schedules for one response will affect behavior allocation across all available responses in the environment. When practitioners thin reinforcement schedules for adaptive behavior — as is necessary for generalization and maintenance — the relative value of that behavior may decrease, making challenging behavior more competitive. Schedule thinning should therefore be gradual, with monitoring for shifts in behavior allocation. The matching law also suggests that enriching the reinforcement schedule for adaptive alternatives is often more effective than attempting to eliminate reinforcement for challenging behavior alone.
Research using delay discounting tasks has consistently found steeper-than-average discounting in individuals with ADHD, substance use disorders, gambling disorders, and some presentations within autism spectrum disorder. Elevated impulsivity, which is partly defined by steep temporal discounting, is a transdiagnostic feature across several conditions common in the populations BCBAs serve. Understanding that these are measurable behavioral characteristics — not purely volitional choices — is clinically important: it shifts the intervention from moral exhortation to schedule design and delay tolerance building through systematic behavioral procedures.
While temporal discounting describes the devaluation of reinforcers as a function of delay, probability discounting describes the devaluation of reinforcers as a function of outcome uncertainty. A reinforcer available with certainty is preferred over a probabilistic reinforcer of equal magnitude, and this preference intensifies as probability decreases. In clinical settings, probability discounting affects clients' responses to variable reinforcement schedules, tolerance for uncertainty in naturalistic teaching contexts, and willingness to attempt tasks with uncertain success. Steep probability discounting may manifest as avoidance of novel or unpredictable situations.
Building delay tolerance involves systematic delay fading — beginning with immediate reinforcement delivery and gradually increasing the delay to backup reinforcers while maintaining behavior. Token economies serve this function by interposing conditioned reinforcers (tokens) between behavior and backup reinforcer delivery, effectively bridging the delay gap. The initial token ratio should be lean enough to be motivating but not so lean that the backup reinforcer loses value due to the delay involved. Data on behavior rates during delay increases should guide the pace of fading, with the criterion that behavior remains stable before increasing delay further.
Green expressed concern about stagnation in the field — specifically, the risk that behavior analysis might settle into established methods without the kind of rigorous innovation and cross-disciplinary engagement that characterized the productive decades of the 1960s and 70s. He emphasized the importance of maintaining scientific rigor and pursuing basic research questions that may not have immediate applied payoff but that ultimately generate the theoretical advances the field needs. This concern is a call for BCBAs to remain engaged with the experimental literature and to value basic science as the foundation of sound applied practice.
FCT is most effective when the communicative alternative is placed on a reinforcement schedule that is at least as rich — in rate, delay, and magnitude — as the schedule maintaining challenging behavior. The matching law predicts that if the communicative alternative produces reinforcement on a relatively lean schedule while challenging behavior continues to produce reinforcement quickly, behavior will continue to allocate toward challenging behavior. This is why the efficiency principle in FCT — ensuring the alternative produces reinforcement more quickly and reliably — is not merely a procedural suggestion but a direct application of matching law logic to treatment design.
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All behavior-analytic intervention is individualized. The information on this page is for educational purposes and does not constitute clinical advice. Treatment decisions should be informed by the best available published research, individualized assessment, and obtained with the informed consent of the client or their legal guardian. Behavior analysts are responsible for practicing within the boundaries of their competence and adhering to the BACB Ethics Code for Behavior Analysts.