| 来源类型 | Working Paper
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| 规范类型 | 报告
|
| DOI | 10.3386/w27182
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| 来源ID | Working Paper 27182
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| Latent Dirichlet Analysis of Categorical Survey Expectations |
| Evan M. Munro; Serena Ng
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| 发表日期 | 2020-05-18
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| 出版年 | 2020
|
| 语种 | 英语
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| 摘要 | Beliefs are important determinants of an individual's choices and economic outcomes, so understanding how they differ across individuals is of considerable interest. Researchers often rely on surveys that report individual expectations as qualitative data. We propose using a Bayesian hierarchical latent class model to summarize and interpret observed heterogeneity in categorical expectations data. We show that the statistical model corresponds to an economic structural model of information acquisition, which guides interpretation and estimation of the model parameters. An algorithm based on stochastic optimization is proposed to estimate a model for repeated surveys when beliefs follow a dynamic structure and conjugate priors are not appropriate. Guidance on selecting the number of belief types is also provided. Two examples are considered. The first shows that there is information in the Michigan survey responses beyond the consumer sentiment index that is officially published. The second shows that belief types constructed from survey responses can be used in a subsequent analysis to estimate heterogeneous returns to education. |
| 主题 | Econometrics
; Estimation Methods
; Macroeconomics
|
| URL | https://www.nber.org/papers/w27182
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| 来源智库 | National Bureau of Economic Research (United States)
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| 引用统计 |
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| 资源类型 | 智库出版物
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| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/584855
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推荐引用方式
GB/T 7714 |
Evan M. Munro,Serena Ng. Latent Dirichlet Analysis of Categorical Survey Expectations. 2020.
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文件名：
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w27182.pdf
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格式：
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Adobe PDF
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