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摘要翻译：
我们展示了城市规模扩大中规模收益的增加是如何人为地、系统地和可预测地出现的，而没有任何排序或正外部性。我们采用了一个模型，其中个体生产力是独立的，在所有城市中都是同分布的对数正态随机变量。利用极值理论分析了当对数生产率方差大于最小城市人口规模对数规模的两倍时，规模报酬递增的悖论现象。我们的贡献是推导出由这一机制产生的人工标度指数的分析预测，并开发一个简单的统计检验来试图区分给定的估计是真实的还是人工的。我们的分析结果验证了分析模拟和真实微观数据的工资在哥伦比亚各城市。我们展示了当每个城市工人的随机样本规模为其总规模的1%$或更少时，哥伦比亚数据中是如何出现人工标度指数的。
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英文标题：
《Artificial Increasing Returns to Scale and the Problem of Sampling from
Lognormals》
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作者：
Andres Gomez-Lievano, Vladislav Vysotsky, Jose Lobo
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最新提交年份：
2020
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分类信息：
一级分类：Economics 经济学
二级分类：General Economics 一般经济学
分类描述：General methodological, applied, and empirical contributions to economics.
对经济学的一般方法、应用和经验贡献。
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一级分类：Physics 物理学
二级分类：Physics and Society 物理学与社会
分类描述：Structure, dynamics and collective behavior of societies and groups (human or otherwise). Quantitative analysis of social networks and other complex networks. Physics and engineering of infrastructure and systems of broad societal impact (e.g., energy grids, transportation networks).
社会和团体（人类或其他）的结构、动态和集体行为。社会网络和其他复杂网络的定量分析。具有广泛社会影响的基础设施和系统（如能源网、运输网络）的物理和工程。
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一级分类：Quantitative Finance 数量金融学
二级分类：Economics 经济学
分类描述：q-fin.EC is an alias for econ.GN. Economics, including micro and macro economics, international economics, theory of the firm, labor economics, and other economic topics outside finance
q-fin.ec是econ.gn的别名。经济学，包括微观和宏观经济学、国际经济学、企业理论、劳动经济学和其他金融以外的经济专题
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英文摘要：
We show how increasing returns to scale in urban scaling can artificially emerge, systematically and predictably, without any sorting or positive externalities. We employ a model where individual productivities are independent and identically distributed lognormal random variables across all cities. We use extreme value theory to demonstrate analytically the paradoxical emergence of increasing returns to scale when the variance of log-productivity is larger than twice the log-size of the population size of the smallest city in a cross-sectional regression. Our contributions are to derive an analytical prediction for the artificial scaling exponent arising from this mechanism and to develop a simple statistical test to try to tell whether a given estimate is real or an artifact. Our analytical results are validated analyzing simulations and real microdata of wages across municipalities in Colombia. We show how an artificial scaling exponent emerges in the Colombian data when the sizes of random samples of workers per municipality are $1\%$ or less of their total size.
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PDF链接：
https://arxiv.org/pdf/1807.09424
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