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在扩张的观念空间中扩散

Spreading Out Across Expanding Idea Space
NBER Working Papers · 2026 · [{"name": "Ina Ganguli", "affiliation": []}, {"name": "Jeffrey Lin", "affiliation": []}, {"name": "Vitaly Meursault", "affiliation": []}, {"name": "Nicholas F. Reynolds", "affiliation": []}]

中文摘要

近两个世纪以来,美国的发明变得日益不相似:不仅表现为发明者之间正面碰撞的减少,也表现为相邻发明之间距离的持续扩大。我们运用经过验证的神经语言模型,对1836至2023年间超过1100万项美国专利权利要求书的全文进行分析,记录了这种相似性的长期下降趋势;这一趋势还得到专利冲突率(一种衡量独立同时发明的指标)下降98%的佐证。正确衡量这一趋势需要验证,因为同一专利文本的不同表征可能会就发明是趋同还是扩散得出相反的结论。我们的验证框架是专利文本领域的首个系统性比较,用于在这些表征方式中进行选择。我们构建了一个空间竞争模型,发明者在该模型中于观念空间中选择自己的位置。该模型解释了扩散现象,并将其与若干独立记录的模式联系起来——包括每位发明者研发投入的增加、专利价值的上升、知识溢出的减弱,以及研究生产率的下降。其机制具有空间性:随着发明者不断扩散以占据新的领域,发明变得更有价值,但他人吸收这些发明的成本也随之上升。由此,该模型将溢出强度、创新步长和研究生产率,从固定的原始参数转变为发明者定位选择的结果。经校准的分解分析表明,美国研究生产率长期下降中约40%可归因于这些空间力量,这与'捕捞殆尽'和知识负担等传统解释并存。发明者在观念空间中彼此的相对位置,其对增长的重要性不亚于发明者的数量本身。

Abstract

Over nearly two centuries, US inventions have become increasingly dissimilar: not just fewer head-to-head collisions between inventors, but growing distance between neighboring inventions. We document this secular decline in similarity using validated neural language models applied to the full text of claims in over 11 million US patents (1836–2023), corroborated by a 98% decline in patent interference rates, a measure of independent simultaneous invention. Measuring this correctly requires validation, since different representations of the same patent text can yield opposite conclusions about whether inventions are converging or spreading out. Our validation framework, the first systematic comparison for patent text, selects among these representations. We develop a spatial competition model in which inventors choose locations in idea space. The model explains spreading out and connects it to several independently documented patterns — rising R&D investment per inventor, increasing patent values, weakening knowledge spillovers, and declining research productivity. The mechanism is spatial; as inventors spread out to capture new territory, inventions become more valuable but also more costly for others to absorb. In doing so, the model turns spillover intensity, innovation step size, and research productivity from fixed primitives into outcomes of inventor positioning. A calibrated decomposition attributes roughly 40% of the long-run decline in US research productivity to these spatial forces, alongside traditional explanations such as fishing out and the burden of knowledge. Where inventors stand relative to each other in idea space matters as much for growth as how many of them there are.
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