Dr. Yannick Schindler, Ellison Institute of Technology
YouTube Stream: https://www.youtube.com/watch?v=HrUyORoqgPc
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Abstract:
Economists are often asked deceptively simple questions: if (x) changes, what happens to (y)? The difficulty is that, outside the laboratory, (x) rarely changes in isolation. Prices respond to demand, teachers favor good students, and safety courses are attended by the most timid. Correlation alone therefore seldom reveals what would happen under any kind of policy change. This talk offers an intuition-first introduction to how economists attempt to recover causal effects from messy real-world data. The talk explores why prediction and causation require different kinds of evidence, how economic models can expose the failures of naïve comparisons, and how natural experiments can sometimes reveal the missing counterfactual. Three case studies bring these ideas to life: the consequences of bank failures for firms, the surprising relationship between shingles vaccination and dementia, and the debate over whether remote work or AI is responsible for deteriorating outcomes among early-career workers. No prior economics is required.
Bio:
Yannick Schindler is a Senior Research Economist at the Ellison Institute of Technology in Oxford, where he leads research teams studying how AI and robotics are reshaping the economy, with a particular focus on their impacts on science and innovation. He has previously held research positions at Stanford University, Princeton University, London Business School, and the European Central Bank, and holds a PhD in Economics from the London School of Economics. He also guest lectures at the University of Oxford.