| 来源类型 | Discussion paper |
| 规范类型 | 论文 |
| 来源ID | DP9026 |
| DP9026 Improving the Performance of Random Coefficients Demand Models: the Role of Optimal Instruments | |
| Frank Verboven; Mathias Reynaert | |
| 发表日期 | 2012-06-24 |
| 出版年 | 2012 |
| 语种 | 英语 |
| 摘要 | We shed new light on the performance of Berry, Levinsohn and Pakes' (1995) GMM estimator of the aggregate random coefficient logit model. Based on an extensive Monte Carlo study, we show that the use of Chamberlain's (1987) optimal instruments overcomes most of the problems that have recently been documented with standard, non-optimal instruments. Optimal instruments reduce small sample bias, but prove even more powerful in increasing the estimator's efficiency and stability. Other recent methodological advances (MPEC, polynomial-based integration of the market shares) greatly improve computational speed, but they are only successful in terms of bias and efficiency when combined with optimal instruments. |
| 主题 | Industrial Organization |
| 关键词 | Optimal instruments Random coefficients demand model |
| URL | https://cepr.org/publications/dp9026 |
| 来源智库 | Centre for Economic Policy Research (United Kingdom) |
| 资源类型 | 智库出版物 |
| 条目标识符 | http://119.78.100.153/handle/2XGU8XDN/537859 |
| 推荐引用方式 GB/T 7714 | Frank Verboven,Mathias Reynaert. DP9026 Improving the Performance of Random Coefficients Demand Models: the Role of Optimal Instruments. 2012. |
| 条目包含的文件 | 条目无相关文件。 | |||||
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