Garett Jones - Do Immigrants Import Their Economic Destiny?
🧭 Thesis: migrants transmit norms and institutional preferences; short-run effects are modest, but over decades they can tilt governance and prosperity.
🧬 Deep Roots (SAT): migration-adjusted States, Agriculture, Technology scores predict today’s institutions, people carry advantages more than places do. For example:
Australia has quite a low ancestral technology score: Aboriginal Australians used little of the world’s cutting edge technology in 1500 A.D. But since Australia is now overwhelmingly populated by the descendants of British migrants, Australia’s migration-adjusted technology score is currently quite high.
🧪 Attitudes travel: inherited trust, redistribution preferences, and familism persist; low trust in government leads to demand for regulation; putting family above moral action (“familism”) lowers civic participation and innovation.
📊 New Voters = New Policies: enfranchisement evidence shows policy moves with new voters (e.g., social spending out of GDP increased by 0.6-1.2% in the short-run as a consequence of women’s suffrage, while the long-run effect is three to eight times larger).
🌏 Diaspora case: higher post-1500 Chinese migration shares in Asia correlate with greater economic freedom (Singapore/HK/Taiwan ≫ Laos/Myanmar), hinting at peaceful institutional drift.
🧭 Policy read: assimilation is two-way and exceptions exist, but if you must bet, high-SAT inflows are likelier to nudge institutions towards markets, liberalism, and prosperity over time.
🔗 Do Immigrants Import Their Economic Destiny? – burchellwilson.substack.com
B. Hauth - the legibility bottleneck
🧩 Core bottleneck in making more innovative companies: According to the author, it’s not capital, engineers, or ideas - it’s investors’ inability to see genuine hard-tech competence, so they over-rely on brittle proxies (degrees, papers, PR).
🎓 Credential decay: once a number becomes the target, people game it; the metric stops reflecting substance (Goodhart’s Law in plain English).
🧑🚀 The Musk workaround: rare founders self-learn enough to do first-principles vetting and cull fools; the scarce role is the illegibility interpreter between deep tech and money.
🏛️ Market symptoms: credential inflation, “experience-only” funnels, ageism, drawn-out hiring, and H-1B usage for cost/control/count/caste, are signals of evaluation failure, not real talent scarcity.
🧱 Bottom line: the US lacks institutions that reliably make deep technical competence legible to capital; until that gap closes, innovation is throttled.
🔗 the legibility bottleneck – bhauth.com
David Chapman - How To Think Real Good
🧠 Core idea: effective reasoning is mostly about choosing and revising frames - not just using Bayes’ Theorem or any single formalism.
🧩 Formulation first: pick a vocabulary/level that makes the relevant distinctions and compresses complexity; formulations aren’t “true/false”, only useful.
🧪 Working heuristics: start with concrete examples; solve a simpler version first, then iterate.
🌐 Steal from everywhere: learn broad maths, plus anthropology/psychology/philosophy; cultivate a “bag of tricks” so you can spot which tool fits which problem.
Join us next week for three more intriguing topics that challenge the norm and expand your horizons! ✌️
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