摘要翻译:
不同的代理人需要做出预测。他们观察相同的数据,但有不同的模型:他们使用不同的解释变量进行预测。我们研究哪一个智能体认为他们有最好的预测能力--用最小的主观后验均方预测误差来衡量--并展示它如何依赖于样本量。在小样本的情况下,我们给出的结果表明它是一个使用低维模型的智能体。对于大样本,它通常是一个具有高维模型的agent,可能包括不相关的变量,但从不排除相关的。我们应用我们的结果来刻画生产性资产拍卖中的获胜模型,论证简单模型的企业家和投资者在新行业中会被过度代表,并理解在资产定价文献中解释预期股票收益横截面变化的“因素”的激增。
---
英文标题:
《Competing Models》
---
作者:
Jose Luis Montiel Olea, Pietro Ortoleva, Mallesh M Pai, Andrea Prat
---
最新提交年份:
2021
---
分类信息:
一级分类:Economics 经济学
二级分类:Theoretical Economics 理论经济学
分类描述:Includes theoretical contributions to Contract Theory, Decision Theory, Game Theory, General Equilibrium, Growth, Learning and Evolution, Macroeconomics, Market and Mechanism Design, and Social Choice.
包括对契约理论、决策理论、博弈论、一般均衡、增长、学习与进化、宏观经济学、市场与机制设计、社会选择的理论贡献。
--
一级分类:Computer Science 计算机科学
二级分类:Machine Learning 机器学习
分类描述:Papers on all aspects of machine learning research (supervised, unsupervised, reinforcement learning, bandit problems, and so on) including also robustness, explanation, fairness, and methodology. cs.LG is also an appropriate primary category for applications of machine learning methods.
关于机器学习研究的所有方面的论文(有监督的,无监督的,强化学习,强盗问题,等等),包括健壮性,解释性,公平性和方法论。对于机器学习方法的应用,CS.LG也是一个合适的主要类别。
--
一级分类:Economics 经济学
二级分类:Econometrics 计量经济学
分类描述:Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论,微观计量经济学,宏观计量经济学,通过新方法发现的经济关系的实证内容,统计推论应用于经济数据的方法论方面。
--
---
英文摘要:
Different agents need to make a prediction. They observe identical data, but have different models: they predict using different explanatory variables. We study which agent believes they have the best predictive ability -- as measured by the smallest subjective posterior mean squared prediction error -- and show how it depends on the sample size. With small samples, we present results suggesting it is an agent using a low-dimensional model. With large samples, it is generally an agent with a high-dimensional model, possibly including irrelevant variables, but never excluding relevant ones. We apply our results to characterize the winning model in an auction of productive assets, to argue that entrepreneurs and investors with simple models will be over-represented in new sectors, and to understand the proliferation of "factors" that explain the cross-sectional variation of expected stock returns in the asset-pricing literature.
---
PDF链接:
https://arxiv.org/pdf/1907.03809