← The Casebook

Tide table · when to expect high water

Projection Bias

People exaggerate the degree to which their future tastes will resemble their current tastes, leading them to overpredict the influence of their present transient states (hunger, weather, emotions) on future preferences and decisions.

Ebb & flood · the bias surges on a cyclePrediction · Charted
High waterthe bias floods
High waterthe bias floods
High waterthe bias floods
Low waterquiet · safe window
Low waterquiet · safe window

The lunar pull · the condition that drives the surge

Why the water moves

Projection bias arises because people understand qualitatively that their tastes change over time but systematically underestimate the magnitude of those changes. When in a 'hot' state (hunger, anger, cold), individuals find it difficult to imagine how they would feel in a 'cold' state, and vice versa. Loewenstein (1996) described these as 'empathy gaps'—people fail to appreciate the impact of transient states on their own future preferences. The bias persists even when people have experienced state-dependent preference changes in the past.

Some research suggests projection bias may be partially explained by memory-based mechanisms rather than purely imaginative failures—people may simply fail to recall how different states felt.

Prediction reliability — replication

Projection bias has been replicated in multiple field settings (catalog orders, housing markets, car markets) and laboratory studies. The effect is well-documented across diverse domains. Acland and Levy (2015) found evidence for projection bias in gym attendance using a structural estimation approach. The consistency of findings across weather, food, housing, and health domains supports the robustness of the bias.

Recorded tides

range 95%

Catalog orders and weather projection bias. If the order-date temperature declined by 30°F, the return probability increased by 3.95%. Consumers overpredicted the relevance of current cold weather for their future needs, buying items they later returned when weather warmed.

Conlin, O'Donoghue, & Vogelsang, 2007 · window: Large-scale catalog order dataset

range —

Housing and car market projection bias. Houses with swimming pools sold for relatively more in summer than in winter; convertible sales were higher in spring. Consumers systematically overpaid for weather-sensitive goods based on current weather conditions.

Busse, Pope, Pope, & Silva-Risso, 2012 · window: Housing and automobile transaction data

range —

Hunger and food preference projection bias. Workers chose unhealthy candy bars when currently hungry, both for immediate consumption and for future delivery, underappreciating how their preferences would shift when satiated. Hungry shoppers in Nisbett and Kanouse (1968) bought as if they would remain permanently famished.

Loewenstein, O'Donoghue, & Rabin, 2003 · window: Multiple studies reviewed

King tides · logged extremes

  • Catalog clothing returns driven by weather · 2007

    A major catalog retailer found that customers ordering cold-weather clothing during cold snaps returned items at significantly higher rates, costing the company in shipping and restocking expenses. The pattern was consistent with consumers overpredicting how much they would need warm clothing based on current weather.

  • Housing market seasonal overpayment for pools · 2012

    Homebuyers in warm climates paid premium prices for houses with swimming pools during summer months, overpredicting their future use of the pool. The hedonic premium for pools varied seasonally by thousands of dollars, representing a systematic misforecast of future preferences.

  • Medical treatment decisions under emotional distress · 2005

    Patients receiving adverse test results made treatment decisions while in states of fear and anxiety that would not persist throughout the treatment period. Loewenstein (2005) documented how projection bias leads patients to choose overly aggressive treatments because they fail to anticipate emotional adaptation.

Tide warning · the safe window

Use 'cooling-off periods' for decisions made under transient states. Delay important purchases or commitments until you are in a neutral emotional and physical state. When possible, seek advice from someone currently in the state you expect to be in when the decision takes effect.

Cooling-off periods have been shown to reduce impulsive purchases and are mandated for certain high-stakes decisions. Conlin et al. (2007) showed that awareness of projection bias can be built into decision architectures to improve outcomes.

Reading the gauge in the wild

Watch for decisions made under transient states (hunger, cold weather, emotional arousal) that commit you to future actions. If you are shopping while hungry, house-hunting in extreme weather, or making commitments while angry, you may be projecting current preferences too far into the future.

Almanac compiled from George Loewenstein, Ted O'Donoghue, Matthew Rabin, 2003 — Projection Bias in Predicting Future Utility.

Neighbouring waters

File your own case

Open the same case on your own draft.

Paste a memo, a research draft, or a strategy argument. It is scored against all 175 cards, and the strongest two or three risks come back with the evidence quoted and one practical next check.

Open a case on your draft →