What Incentives Are (and Why They Matter)
An incentive is anything that changes the perceived benefits or costs of an action, making that action more or less attractive. Economists focus on incentives because they provide a practical way to predict behavior: when incentives change, choices tend to change in systematic, often predictable ways.
Incentives work through two channels:
- Payoffs: what you gain or lose (money, time, comfort, reputation).
- Constraints: what is allowed, required, or feasible (rules, deadlines, limited access, eligibility).
Monetary incentives
Monetary incentives directly affect financial outcomes.
- Prices and fees: higher prices discourage buying; lower prices encourage it.
- Wages and bonuses: higher pay for a task tends to increase supply of effort/time.
- Taxes and penalties: increase the cost of certain actions.
- Subsidies and discounts: reduce the cost of certain actions.
Non-monetary incentives
Non-monetary incentives can be just as powerful, and sometimes stronger than money.
- Time and convenience: shorter wait times, easier checkout, faster delivery.
- Social approval and status: praise, recognition, reputation, “likes,” professional credibility.
- Fairness and identity: people may comply or resist based on what feels fair or consistent with their values.
- Information and uncertainty: clearer information can increase action; uncertainty can delay or deter it.
- Rules and enforcement: the chance of being caught and punished changes behavior even when the monetary amount is unchanged.
How Economists Use Incentives to Predict Responses
To anticipate what people will do when conditions change, economists ask: What action became relatively more attractive, and for whom? The core idea is to identify the decision-maker, the available options, and how a change in prices, rules, or information shifts the relative attractiveness of those options.
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A practical prediction checklist (step-by-step)
- Define the decision: What choice is being made? (e.g., drive vs. transit; buy brand A vs. brand B; comply vs. evade)
- List the feasible options: What alternatives are realistic? Include “do nothing” and “delay.”
- Identify the relevant incentives: Money, time, hassle, risk, social pressure, moral concerns, etc.
- Specify what changed: Price increased? Penalty introduced? Subsidy removed? Deadline moved up? Information clarified?
- Predict substitution: Which option is now relatively cheaper/easier/safer/more approved?
- Check for constraints and heterogeneity: Who can actually switch? Who is stuck? (income, location, schedule, access)
- Look for unintended consequences: Could the change create new behaviors that offset the goal?
- Compare intentions vs. incentives: Does the policy’s goal match what it rewards or penalizes?
Changes in Constraints That Commonly Shift Behavior
1) Higher prices (or higher time costs)
When the cost of an option rises, people tend to reduce use of that option and shift toward alternatives—especially those that are now relatively cheaper.
Example: coffee shop pricing
- If the price of a latte rises from $5 to $7 while drip coffee stays at $3, some customers switch to drip coffee, smaller sizes, or brew at home.
- Others may not switch (strong preferences, habit, higher income), but the overall pattern is a reduction in the higher-priced choice.
Non-monetary version: If a service becomes slower (longer wait times), some users switch even if the dollar price is unchanged.
2) Penalties and enforcement
Penalties increase the expected cost of an action. But the effect depends on both the size of the penalty and the probability of enforcement.
Example: late return policy
- A library introduces a $1/day late fee. Some patrons return books sooner.
- If enforcement is weak (fees rarely collected), behavior may change little.
- If reminders and automatic billing increase enforcement, behavior changes more.
Key prediction: People respond to the expected penalty: expected cost = penalty amount × chance of being penalized.
3) Subsidies and discounts
Subsidies lower the cost of an action, making it more attractive. They can increase participation, but they can also shift behavior in ways that are not intended.
Example: transit subsidy
- A city offers discounted monthly transit passes. Ridership increases, especially among those who were close to switching already.
- Some riders who previously walked or biked may switch to transit (a substitution that may or may not match the policy’s goals).
Design detail: A subsidy that is easy to claim (automatic discount) tends to have a larger effect than one that requires paperwork (high hassle cost).
4) Deadlines and timing incentives
Deadlines change the cost of delaying. They can increase completion rates, but they can also cause bunching (many people acting at the last moment) and reduce quality if rushed.
Example: assignment deadline
- Move the deadline earlier: more people start earlier, but some may submit lower-quality work if they lose time.
- Introduce a late penalty: fewer late submissions, but more last-minute submissions.
Non-monetary incentive: A public commitment (e.g., presenting progress weekly) can act like a deadline by adding reputational stakes.
Common Predictable Patterns
Substitution toward relatively cheaper options
When one option becomes more costly (in money, time, risk, or hassle), people tend to substitute toward alternatives that deliver similar benefits at lower relative cost.
| Change | Likely substitution | Why |
|---|---|---|
| Parking fee increases | Transit, carpool, park farther away | Driving/parking becomes relatively more expensive |
| Streaming subscription price rises | Cheaper service, ad-supported tier, cancel | Entertainment alternatives become relatively cheaper |
| Longer wait times at a clinic | Different clinic, telehealth, delay visit | Time cost rises |
Unintended consequences
Changing incentives can produce side effects because people adapt creatively. A policy aimed at one behavior can shift behavior elsewhere.
Example: “No-show” fee at a doctor’s office
- Intention: reduce missed appointments.
- Possible response: some patients cancel earlier (desired), but others may avoid booking appointments at all if they fear uncertainty in their schedule (undesired).
- Another response: patients may book fewer follow-ups, potentially worsening health outcomes.
Example: bonus for speed
- Intention: increase productivity.
- Possible response: workers prioritize speed over quality, increasing errors or returns.
Intentions vs. incentives
What matters for behavior is not what a rule or policy says it wants, but what it rewards and penalizes in practice.
Example: customer service metrics
- If agents are rewarded for short call times, they may end calls quickly rather than solve problems thoroughly.
- If agents are rewarded for high satisfaction scores, they may spend longer, offer concessions, or avoid difficult cases.
Practical takeaway: To predict behavior, look at the metric that determines outcomes for the decision-maker (pay, grades, approval, access), not the stated mission.
Information as an Incentive: When Knowledge Changes Choices
Information changes perceived costs and benefits. Even without changing prices, new information can shift behavior by changing beliefs about quality, risk, or social norms.
Example: energy usage report
- Households receive a report comparing their energy use to neighbors.
- Some reduce consumption due to social comparison (a non-monetary incentive), even if prices stay the same.
Example: clearer fees
- If a bank makes overdraft fees more transparent, some customers keep higher balances or opt out of overdraft coverage.
Prediction tip: Ask whether the information is salient (noticed), credible, and actionable. If not, behavior may not change much.
Mini-Lab: Predicting Responses to Fees, Removals, and Shifts
Scenario A: A fee is introduced
Case: A gym introduces a $10 fee for late cancellations.
- Step 1 (options): cancel earlier, attend anyway, accept the fee, stop booking classes.
- Step 2 (who can switch): people with predictable schedules can cancel earlier; those with unstable schedules may reduce bookings.
- Step 3 (unintended consequence): fewer bookings could reduce class utilization or membership satisfaction.
Scenario B: A fee is removed
Case: A retailer removes a $5 delivery fee.
- Prediction: more deliveries, fewer in-store pickups, potentially more returns if ordering becomes “too easy.”
- Capacity constraint: delivery times may lengthen, adding a non-monetary cost that partially offsets the fee removal.
Scenario C: A fee is shifted (who pays changes)
Case: A ticketing platform shifts a service fee from buyers to sellers.
- Immediate incentive change: buyers see lower posted prices; sellers receive less per sale.
- Likely responses: sellers may raise listed prices, reduce supply, or change product quality; buyers may purchase more if the total price feels lower.
- Key question: does the shift change the total cost of the transaction or mainly the salience of the fee?
Reflection Questions (Short Predictions)
- A city introduces a $2 fee for disposable cups. What substitutions do you expect (reusable cups, bottled drinks, fewer purchases), and for which groups?
- A university removes late fees for library books but increases reminder messages and auto-renewal. Do you expect more late returns, fewer, or no change? Why?
- A rideshare app shifts a cancellation fee from riders to drivers (drivers lose pay when riders cancel). How might drivers change acceptance behavior or positioning?
- A workplace adds a deadline for submitting expense reports, with no monetary penalty. What non-monetary incentives might still make compliance rise?
- A store adds a “small order fee” under $15, then later replaces it with a slightly higher per-item price for everyone. How might behavior differ between the two designs?
