有吸引力还是有攻击性?一种用于估计视觉外观回报的人脸识别和机器学习方法

IF 1.8 3区 经济学 Q2 ECONOMICS
Guodong Gou, B. Humphreys, Mohammad Iqbal Nouyed, Yang Zhou
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引用次数: 1

摘要

本文通过说明使用计算机视觉和机器学习方法来识别面部特征,为经济学中的面部特征研究提供了方法上的贡献。我们分析了一流大学体育项目的首席足球教练的面部外观溢价来说明这一方法。具体来说,我们通过应用于可观察面部特征的神经网络方法对这些特征进行定量测量,来估计面部吸引力和攻击性溢价。参数回归结果显示,有吸引力的员工工资折扣的证据,以及积极溢价的证据。非参数梯度结果提供了类似的定性含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Attractive or Aggressive? A Face Recognition and Machine Learning Approach for Estimating Returns to Visual Appearance
This paper provides a methodological contribution by illustrating the use of computer vision and machine learning methods to identify facial characteristics for the study of facial characteristics in economics. We analyze facial appearance premia for head football coaches at big-time college sports programs to illustrate this methodology. Specifically, we estimate facial attractiveness and aggressiveness premia using quantitative measures of these characteristics from a neural network approach applied to observable facial features. Parametric regression results show evidence of a salary discount for attractive employees along with evidence of an aggressiveness premium. Nonparametric gradient results provide similar qualitative implications.
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来源期刊
CiteScore
3.20
自引率
17.60%
发文量
36
期刊介绍: Journal of Sports Economics publishes scholarly research in the field of sports economics. The aim of the journal is to further research in the area of sports economics by bringing together theoretical and empirical research in a single intellectual venue. Relevant topics include: labor market research; labor-management relations; collective bargaining; wage determination; local public finance; and other fields related to the economics of sports. Published quarterly, the Journal of Sports Economics is unique in that it is the only journal devoted specifically to this rapidly growing field.
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