Personality Traits, Preferences and Economic Success

这个研究项目的重点是个人特质、个人偏好和经济成功之间的关系。目标是更好地理解个人偏好的形成和经济决策，并结合双重处理的概念。人格特质本质上是难以测量的，所以经验方法应该考虑到测量误差的存在。迄今为止采用的大多数经验方法依赖于简单的参数化和线性潜在结构模型。最近，贝叶斯因素结构模型被提出，使研究人员能够同时解决测量误差问题和内生性问题。此外，贝叶斯方法允许分析具有大量测量值和因素的模型，这些模型可以通过适当的简约贝叶斯因素选择技术进行内生选择。实证研究将基于大规模面板数据，使用计量经济模型和贝叶斯因子模型对因果治疗效果进行非实验评估。该项目还将有助于在方法上改进这些模型。

This research project focuses on the relationship between personal traits, individual preferences, and economic success. The goal is to achieve a better understanding of individual preference formation and economic decision making incorporating the concept of dual-processing.Personality traits are inherently hard to measure, so empirical approaches should take into account the presence of measurement errors. Most of the empirical approaches adopted thus far rely on simple parametric and linear latent structure models. More recently, Bayesian factor structure models have been proposed which allow the researcher to tackle both the measurement error problem and the endogeneity problem. Moreover, the Bayesian approach allows for analyzing models with large number of measurements and factors, which can be selected endogenously by appropriate parsimonious Bayesian factor selection techniques.The empirical studies will be based on large scale panel data using econometric models for nonexperimental evaluation of causal treatment effects and Bayesian factor models. The project will also contribute to a methodological advancement of these models.