| 来源类型 | Article |
| 规范类型 | 其他 |
| DOI | 10.1016/j.euroecorev.2015.03.009 |
| Unveiling covariate inclusion structures in economic growth regressions using latent class analysis. | |
| Crespo Cuaresma J; Gruen B; Hofmarcher P; Humer S; Moser M | |
| 发表日期 | 2016 |
| 出处 | European Economic Review 81: 189-202 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | We propose the use of Latent Class Analysis methods to analyze the covariate inclusion patterns across specifications resulting from Bayesian Model Averaging exercises. Using Dirichlet Process clustering, we are able to identify and describe dependency structures among variables in terms of inclusion in the specifications that compose the model space. We apply the method to two datasets of potential determinants of economic growth. Clustering the posterior covariate inclusion structure of the model pace formed by linear regression models reveals interesting patterns of complementarity and substitutabiliy across economic growth determinants. |
| 主题 | World Population (POP) |
| 关键词 | Economic Growth Determinants Bayesian Model Averaging Latent Class Analysis Dirichlet Processes |
| URL | http://pure.iiasa.ac.at/id/eprint/11694/ |
| 来源智库 | International Institute for Applied Systems Analysis (Austria) |
| 引用统计 | |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/130728 |
| 推荐引用方式 GB/T 7714 | Crespo Cuaresma J,Gruen B,Hofmarcher P,et al. Unveiling covariate inclusion structures in economic growth regressions using latent class analysis.. 2016. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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