What's the best way to run experiments in behavioral economics?

1 Choose a relevant question

The first step in any experiment is to define a clear and specific research question that addresses a relevant problem or gap in knowledge. You should also have a well-founded theoretical framework that guides your hypotheses and predictions. For example, you might want to investigate how framing, nudging, or incentives affect people's choices, preferences, or behavior in a certain domain, such as health, education, or finance. You should also consider the ethical implications and potential impact of your question and intervention.

2 Select a suitable method

The next step is to choose a method that fits your question, budget, and resources. There are different types of experiments in behavioral economics, such as lab experiments, field experiments, natural experiments, and online experiments. Each method has its own advantages and disadvantages, depending on the level of control, realism, generalizability, and scalability. You should weigh the pros and cons of each method and select the one that best suits your objectives and constraints.

3 Design a robust protocol

The third step is to design a protocol that ensures the validity and reliability of your experiment. This includes defining your target population, sample size, sampling method, treatment and control groups, randomization procedure, outcome variables, and data collection methods. You should also pre-register your protocol and analysis plan to avoid bias and p-hacking. Moreover, you should pilot test your protocol to check for feasibility, clarity, and potential problems.

4 Implement and monitor your experiment

The fourth step is to implement and monitor your experiment according to your protocol. This involves recruiting and consenting participants, delivering the treatment and control conditions, collecting and storing data, and tracking and resolving any issues or deviations. You should also follow the ethical principles and guidelines of your institution and field, such as protecting the privacy and confidentiality of participants, obtaining informed consent, and minimizing harm or deception.

5 Analyze and interpret your data

The fifth step is to analyze and interpret your data using appropriate statistical techniques and software. You should follow your pre-registered analysis plan and report any deviations or adjustments. You should also test the assumptions of your models, check for outliers and missing data, and perform sensitivity and robustness checks. You should interpret your results in light of your hypotheses, theory, and previous literature, and discuss the limitations and implications of your findings.

6 Communicate and disseminate your results

The final step is to communicate and disseminate your results to your audience and stakeholders. You should write a clear and concise report or paper that summarizes your research question, methods, results, and conclusions. You should also use visual aids, such as graphs, tables, or charts, to illustrate your data and findings. Moreover, you should share your data and code publicly, if possible, to enable replication and verification. You should also seek feedback and peer review from other experts and practitioners in your field.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?