91Ó°ÊÓ

In their book SuperFreakonomics, authors Steven Levitt and Stephen Dubner describe the research of behavioral economist John List. List recruited customers and dealers at a baseball-card show to participate in an experiment in which the customer would state how much he was willing to pay for a single baseball card. The prices ranged from \(\$ 4\) (lowball) to \(\$ 50\) (premium card). The dealer would then give the customer a card that was supposed to correspond to the offer price. In this setting, the dealer could certainly give the buyer a card worth less than the offer price, but this rarely happened. The card received by the buyer was close in value to the price offered. Next, List went to the trading floor at the show and again recruited customers. But this time the customers approached dealers at their booth. The dealers did not know they were being watched. The scenario went something like this: as the customer approached the dealer's booth, he would say, "Please give me the best Derek Jeter card you can for \(\$ 20 . "\) In this scenario, the dealers consistently ripped off the customers by giving them cards worth much less than the offer price. In fact, the dealers who were the worst offenders were the same dealers who refused to participate in List's study. Do you believe that individuals who volunteer for experiments are scientific do- gooders? That is, do you believe that in designed experiments subjects strive to meet the expectations of the researcher? In addition, do you believe that results of experiments may suffer because many experiments require individuals to volunteer, and individuals who are not do-gooders do not volunteer for studies? Now, explain why control groups are needed in designed experiments and the role they can play in neutralizing the impact of scientific do- gooders.

Step by step solution

01

Understand the Context

The question explores the behavior of individuals in experiments, focusing on whether participants aim to meet researchers' expectations and whether experiment results suffer because non-volunteers impact the results. The example involves behavior at a baseball-card show.

02

Define Key Terms

Identify and understand key terms such as 'scientific do-gooders,' which refers to individuals who participate in experiments to help researchers, and 'control groups,' which are groups in experiments that are not subjected to the treatment or manipulation to provide a baseline for comparison.

03

Analyze Participant Behavior

Consider the first scenario where customers state their price for a baseball card, and dealers provide cards matching the price. Recognize how this controlled setting might influence both dealers and customers to behave differently from normal circumstances.

04

Compare to Uncontrolled Setting

Evaluate the second scenario where dealers are unaware they are part of an experiment. Notice how their behavior changes when they aren't consciously participating, often cheating customers when they don't think they're being observed.

05

Assess the Impact on Experiment Validity

Reflect on how volunteer participants (scientific do-gooders) might behave differently to meet experimenter expectations compared to non-volunteers, potentially skewing results. Non-volunteers might not be represented, causing biased results.

06

Explain the Need for Control Groups

Describe how control groups help neutralize biases by providing a comparison group that does not receive the treatment. This helps identify whether the observed effects are due to the experimental manipulation or other factors.

07

Conclude with the Role of Control Groups

Summarize that control groups are essential for balancing the impact of any potential bias introduced by scientific do-gooders. They provide a clearer picture of the true effects of the experimental manipulation.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

Scientific Do-Gooders

In behavioral economics, a 'scientific do-gooder' is someone who participates in experiments with the intent to help the researcher or to behave in what they think is the 'right' way. This term is crucial when designing experiments, as these individuals might alter their behavior to align with what they perceive the experimenter wants. For instance, in John List's baseball-card study, the dealers who knew they were part of an experiment may have behaved honestly to match the researchers' expectations. However, this can create a bias because their behavior might not represent typical conditions. Therefore, data from 'scientific do-gooders' could skew the results and give a false impression of reality.

Control Groups

Control groups are essential in experimental design. They act as a baseline that does not receive any experimental treatment or manipulation. This allows researchers to compare outcomes between the treated group and the control group. In the context of John List's study, if we have two groups of dealers—one that knows they're part of an experiment and one that doesn't—we can compare their behaviors. The control group eliminates biases that might arise from 'scientific do-gooders.' This helps researchers objectively determine the impact of the specific conditions being tested. Without a control group, it would be challenging to discern if the observed changes are due to the treatment or some other external factors.

Experimental Validity

Experimental validity is about ensuring the results of a study genuinely reflect what they are supposed to measure. It's divided into internal and external validity. Internal validity means the study accurately demonstrates a cause-effect relationship between variables, while external validity refers to the extent to which the results can be generalized to other settings. In List's experiment, internal validity would be strong if we can confidently say that the behavior of dealers is directly influenced by whether they know they're in an experiment. External validity would be strong if these findings can be applied to other markets outside the baseball-card show. Ensuring high experimental validity often requires carefully designed control groups to neutralize biases.

Participant Bias

Participant bias occurs when individuals modify their behavior because they are aware they are part of an experiment. In John List's research, dealers in the first scenario might have behaved more ethically because they knew they were being observed. This skews the data, as their behavior is not entirely natural. To mitigate participant bias, researchers often use blind or double-blind study designs where participants or both researchers and participants are unaware of certain aspects of the experiment. This helps ensure that the behavior observed is more likely to reflect true, unaltered actions. Understanding participant bias is vital for interpreting experimental results accurately and maintaining the integrity of the study.