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528 Chapter 13 Experiments and Quasi-Experiments

The Hawthorne Effect

D uring the 1920s and 1930s, the General Elec- about because their special role in the experiment
tric Company conducted a series of studies of made the workers feel noticed and valued, so they
worker productivity at its Hawthorne plant. In one worked harder and harder. Over the years, the idea
set of experiments, the researchers varied lightbulb that being in an experiment influences subject behav-
wattage to see how lighting affected the productiv- ior has come to be known as the Hawthorne effect.
ity of women assembling electrical parts. In other
experiments they increased or decreased rest periods, But there is a glitch to this story: Careful exami-
changed the workroom layout, and shortened work- nation of the actual Hawthorne data reveals no
days. Influential early reports on these studies con- Hawthorne effect (Gillespie, 1991; Jones, 1992)!
cluded that productivity continued to rise whether Still, in some experiments, especially ones in which
the lights were dimmer or brighter, whether work- the subjects have a stake in the outcome, merely
days were longer or shorter, or whether conditions being in an experiment could affect behavior. The
improved or worsened. Researchers concluded that Hawthorne effect and experimental effects more
the productivity improvements were not the conse- generally can pose threats to internal validity—even
quence of changes in the workplace, but instead came though the Hawthorne effect is not evident in the
original Hawthorne data.

who remain in the sample at the end of the experiment and the differences estima-
tor will be biased. Because attrition results in a nonrandomly selected sample,
attrition that is related to the treatment leads to selection bias (Key Concept 9.4).

Experimental effects. In experiments with human subjects, merely because the
subjects are in an experiment can change their behavior, a phenomenon some-
times called the Hawthorne effect (see the box on this page).

In some experiments, a “double-blind” protocol can mitigate the effect of
being in an experiment: Although subjects and experimenters both know that they
are in an experiment, neither knows whether a subject is in the treatment group
or the control group. In a medical drug experiment, for example, sometimes the
drug and the placebo can be made to look the same so that neither the medical
professional dispensing the drug nor the patient knows whether the administered
drug is the real thing or the placebo. If the experiment is double blind, then both
the treatment and control groups should experience the same experimental effects,
and so different outcomes between the two groups can be attributed to the drug.

Double-blind experiments are clearly infeasible in real-world experiments in
economics: Both the experimental subject and the instructor know whether the