Cause and effect – or why the 2021 Nobel Prize is nothing less than an empirical revolution | with Paul Hünermund
Nov 23, 2021
auto_awesome
Paul Hünermund, assistant professor of Strategy and Innovation, discusses why the Nobel Prize in Economics was awarded to David Card, Joshua Angrist, and Guido Imbens. They explore the revolutionary framework of natural experiments and the practical implications of their research in labor markets, education, and business decision-making. The podcast also delves into the role of machine learning in causal analysis and invites feedback and subscription.
Natural experiments provide valuable insights into various fields by allowing researchers to observe treatment and control groups in real-world scenarios.
The research of the Nobel Prize winners has influenced various fields, including economics and management sciences, and has contributed to enhanced understanding of causal relationships in education and business contexts.
Deep dives
Natural Experiments and Causal Inference
Natural experiments, unlike controlled lab experiments, are real-world scenarios or policy changes that researchers can exploit to study causal relationships. For example, David Card and Alan Kruger's study on the minimum wage increase in New Jersey compared fast food restaurants in New Jersey with those in Pennsylvania to analyze the impact of the policy change. Natural experiments allow researchers to observe treatment and control groups in natural settings and provide valuable insights into various fields, such as labor economics and education.
Contributions and Methodological Innovations
The Nobel Prize in Economics recognized the contributions of David Card, Joshua Angrist, and Gido Inbins in two areas: labor markets and education, and methodological advancements in causal inference with observational data. Card's study on the minimum wage challenged conventional wisdom about its impact on unemployment. Angrist and Inbins developed statistical tools for causal inference when controlled experiments are not feasible. These innovations have influenced various fields, including economics and management sciences.
Implications for Policy and Decision Making
The research of the Nobel Prize winners has had significant implications for both policy and decision making. Their work has helped shape labor market policies and improved understanding of causal relationships in education and business contexts. For instance, AB testing, commonly used in online platforms like LinkedIn and Airbnb, is an example of applying experimental design in a business setting. Additionally, researchers are exploring the combination of structural and natural experimental approaches, as well as leveraging machine learning techniques for causal inference, to enhance the precision and robustness of studies.
In this episode Paul Hünermund explains why the Nobel prize in Economics this year was given to the three researchers David Card, Joshua Angrist and Guido Imbens and what companies can learn from their research. We talk about how natural experiments sparked an empirical revolution and how machine learning can help us establish causal links to find the answer to everyday questions.
Paul Hünermund is assistant professor of Strategy and Innovation at Copenhagen Business School. In his research he focuses on how firms can leverage new technologies in the space of machine learning and artificial intelligence for value creation and competitive advantage. In doing so he employs a wide variety of tools from econometrics, machine learning, and the field of causal inference.
Get the Snipd podcast app
Unlock the knowledge in podcasts with the podcast player of the future.
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode
Save any moment
Hear something you like? Tap your headphones to save it with AI-generated key takeaways
Share & Export
Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more
AI-powered podcast player
Listen to all your favourite podcasts with AI-powered features
Discover highlights
Listen to the best highlights from the podcasts you love and dive into the full episode