How can you identify biased economic data?

1 What is bias in economic data?

Bias in economic data refers to any systematic error or deviation from the true or objective value of a variable, indicator, or measure. Bias can result from intentional or unintentional factors, such as data manipulation, cherry-picking, sampling errors, measurement errors, or cognitive biases. Bias can affect the quality and credibility of economic data, and make them incomparable, inconsistent, or irrelevant. Bias can also affect the interpretation and communication of economic data, and influence the opinions and actions of policymakers, businesses, consumers, and researchers.

2 How to identify the source of economic data?

One of the first steps to identify biased economic data is to check the source of the data. The source is the entity or organization that collects, produces, or publishes the data. The source can reveal a lot about the purpose, agenda, and perspective of the data. For example, data from government agencies may reflect official policies or political interests, data from private companies may reflect commercial interests or competitive advantages, and data from academic institutions may reflect theoretical frameworks or research agendas. You should always look for the credentials, reputation, and transparency of the source, and compare it with other sources that provide similar or related data.

3 How to identify the method of economic data?

Another step to identify biased economic data is to check the method of the data. The method is the process or technique that is used to collect, analyze, or present the data. The method can reveal a lot about the accuracy, reliability, and validity of the data. For example, data from surveys may be affected by sampling errors, non-response errors, or response errors, data from experiments may be affected by design errors, randomization errors, or measurement errors, and data from models may be affected by specification errors, estimation errors, or prediction errors. You should always look for the details, assumptions, and limitations of the method, and compare it with other methods that are used for similar or related data.

4 How to identify the context of economic data?

A third step to identify biased economic data is to check the context of the data. The context is the background or situation that surrounds the data. The context can reveal a lot about the relevance, significance, and implications of the data. For example, data from different time periods may be affected by seasonal, cyclical, or structural changes, data from different regions or countries may be affected by cultural, institutional, or environmental differences, and data from different sectors or industries may be affected by market, technological, or regulatory factors. You should always look for the trends, patterns, and comparisons of the data, and compare it with other data that are relevant or significant for the same or related context.

5 How to identify the presentation of economic data?

A final step to identify biased economic data is to check the presentation of the data. The presentation is the way that the data are displayed, reported, or communicated. The presentation can reveal a lot about the message, intention, and influence of the data. For example, data from graphs or charts may be affected by scaling, labeling, or coloring choices, data from tables or numbers may be affected by rounding, aggregation, or indexing choices, and data from texts or narratives may be affected by framing, wording, or emphasizing choices. You should always look for the clarity, consistency, and completeness of the presentation, and compare it with other presentations that are clear, consistent, and complete.

6 How to avoid biased economic data?

To avoid biased economic data, you should always be critical, curious, and cautious when you encounter any economic data. You should always ask yourself questions such as: Who is the source of the data? What is their purpose and agenda? How did they collect, analyze, or present the data? What are their methods and assumptions? When and where did they collect the data? What is the context and situation of the data? How did they display, report, or communicate the data? What are their messages and intentions? How do they compare with other sources, methods, contexts, and presentations? By asking these questions, you can identify and evaluate the potential biases in economic data, and make informed and rational decisions based on reliable and valid data.

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?