A popular objection to planning I keep hearing, especially in the startup world, is “but we don’t have enough data”. Indeed, not having enough data is the reason why you should be planning: to find out step-by-step if the reality matches your anticipation, and where exactly it deviates from it. Planning is the art of avoiding negative surprises, and you should practice it early on. — As I pointed out in my last entry, the first time you’re tasked with providing evidence that your business idea is not a bunch of hooey, you likely got nothing. So I asked you to make something up, and mark it with a tag “not entirely random but probably not…

Economic design fields — auction design, market design, mechanism design — have become success stories for economics, especially for their linkage to Silicon Valley tech companies. But economic education still lacks far behind when it comes to teaching design fundamentals. We try to change that. — The story begins about a year ago, when Cem F Dagdelen, founder of Curve Labs, and I met up for coffee. One of the ideas we tinkered with was how to teach economics “the Bauhaus way”. …

Belief propagation and causal inference are two intertwined concepts that have emerged from distinct fields of study: econometrics and artificial intelligence. Since the “connectionist revolution” of the mid-1980s, researchers have been trying to understand how causal beliefs propagate through real or imagined networks. These ideas have revolutionized both computer science and economics, initially separately, but increasingly in close if not always harmonious contact, with statistics as mediating language.

Since I’m semi-frequently being asked about what my work entails, here is a short explainer of some of the major themes in my work put in context. — Industrial engineer turned economist On my Linkedin page, and in most of my other self descriptions, I call myself ”industrial engineer-turned-economist” or some variant thereof. Both professions deal with the deeply embedded mathematical layer of the economy, from two very different perspectives: industrial engineers operate inside companies, economists operate inbetween companies. …

When examining historical or religious texts, the quest for truth can be akin to navigating a labyrinth. Among the many tools used by biblical scholars to discern the authenticity of a textual claim, the “Criterion of Embarrassment” stands out as a valuable and thought-provoking approach. — This criterion not only aids in evaluating the veracity of statements within religious contexts but can also be applied in a wider scope of information assessment. And it can even be inverted.

The pursuit of knowledge and understanding lies at the heart of scientific inquiry. Scientists strive to uncover the mysteries of the natural world, unravel past events, and make sense of the present. However, what sets science apart is its unique capacity to venture into the unknown — the future. — The unique quality of the future, being unknown and yet to unfold, sets it apart from the present and the past, which are selectively accessible to some based on available evidence and historical records.

In the realm of dynamic systems, the timing of responses and reactions can significantly impact performance. One such phenomenon, known as “late overreaction,” can have far-reaching consequences on system behavior. — Understanding Late Overreaction Late overreaction refers to a delayed response to a change or disturbance in a dynamic system. This delayed response can manifest in various fields, such as finance, engineering, ecology, supply chain, and especially human decision-making.

In an increasingly globalized world, businesses are interconnected through complex multi-tiered networks of suppliers, manufacturers, distributors, and retailers. The processes involved in delivering products or services to end consumers encompass various stages known as value chains. Ensuring the integrity of these value chains is crucial for businesses to build trust, maintain reputation, and meet the ever-growing demand for transparency.

In the world of population dynamics and forecasting, understanding the different growth patterns of various phenomena is essential. While in popular parlance the nonsensical “exponential growth” may dominate the headlines in early stages of an epidemic, it is the logistic curve that offers a more nuanced and realistic representation of growth dynamics, allowing us to predict the trajectory with relative ease.