All Else Equal: “Disentangling Causation and Correlation” with Guido Imbens
Aug 7, 2024
auto_awesome
Renowned economist Guido Imbens, a Nobel Prize winner in 2021, joins hosts Jonathan Berk and Jules van Binsbergen to unpack the complex relationship between causation and correlation. They explore how assumptions can misguide business decisions using relatable examples, like Starbucks influencing local sales. Discover surprising research on family succession, revealing that firms with daughters as firstborns often outshine others, and why rigorous testing is crucial for accurate insights in decision-making. Dive into the nuances that could reshape your perspective!
Understanding the distinction between correlation and causation is vital for decision-makers to avoid misguided strategies in business.
Natural variations can provide valuable insights into causal relationships, especially when controlled experiments are impractical in real-world scenarios.
Deep dives
Understanding Correlation vs. Causality
The distinction between correlation and causality is crucial for decision-makers, as confusing the two can lead to misguided strategies. For instance, a cycle bar franchise might see an increase in sales after a Starbucks opens nearby, leading to the assumption that the Starbucks caused the sales boost. However, it is possible that both are influenced by a third factor, like a booming economy, or that Starbucks chose the location due to anticipated growth in the area. This highlights the importance of analyzing various possibilities before concluding that one event caused another.
The Role of Controlled Experiments
Controlled experiments are essential for establishing causality, but they often present practical challenges in the real world. By randomly selecting locations to open a Starbucks next to existing cycle bars, researchers would create a treatment and control group to observe any differences in sales growth. This 'difference in differences' approach allows for more accurate conclusions about causality if the random assignment is done properly. Unfortunately, such ideal conditions are rare, demanding researchers to seek quasi-experimental designs to deduce causal effects from naturally occurring variables.
Natural Variation and Business Decisions
Natural variation can provide insights into causality when traditional experiments are unfeasible. For example, researchers might examine how the gender of a firstborn child influences the decision to pass family firms to heirs, using this inherent randomness to assess the impact on business success. This method showcases how understanding these variations can lead to significant findings that inform business practices, such as determining whether family succession is beneficial. It suggests that businesses should increasingly recognize and utilize natural variations to inform decisions about strategies and operations.
It can be tempting to think one thing causes another because they happen in succession, but there’s a lot to unwrap in the idea of causality. This week, If/Then is featuring an episode from the podcast All Else Equal: Making Better Decisions. Listen as hosts and finance professors Jonathan Berk and Jules van Binsbergen explain the difference between correlation and causality, and examine cases where it is tempting to assume one thing caused another. Their guest for this episode, Guido Imbens, is a professor of Economics at Stanford Graduate School of Business, and was awarded the Nobel Prize in 2021.
All Else Equal: Making Better Decisions Podcast is a production of Stanford GSB and is produced by University FM. It is hosted by Jonathan Berk, The A.P. Giannini Professor of Finance at Stanford GSB, and Jules van Binsbergen, The Nippon Life Professor in Finance, Professor of Finance, at The Wharton School. Each episode provides insight into how to make better decisions.