| 来源类型 | Working Paper |
| 规范类型 | 报告 |
| DOI | 10.3386/w22569 |
| 来源ID | Working Paper 22569 |
| Imputation in U.S. Manufacturing Data and Its Implications for Productivity Dispersion | |
| T. Kirk White; Jerome P. Reiter; Amil Petrin | |
| 发表日期 | 2016-08-25 |
| 出版年 | 2016 |
| 语种 | 英语 |
| 摘要 | In the U.S. Census Bureau's 2002 and 2007 Censuses of Manufactures 79% and 73% of observations respectively have imputed data for at least one variable used to compute total factor productivity. The Bureau primarily imputes for missing values using mean-imputation methods which can reduce the true underlying variance of the imputed variables. For every variable entering TFP in 2002 and 2007 we show the dispersion is significantly smaller in the Census mean-imputed versus the Census non-imputed data. As an alternative to mean imputation we show how to use classification and regression trees (CART) to allow for a distribution of multiple possible impute values based on other plants that are CART-algorithmically determined to be similar based on other observed variables. For 90% of the 473 industries in 2002 and the 84% of the 471 industries in 2007 we find that TFP dispersion increases as we move from Census mean-imputed data to Census non-imputed data to the CART-imputed data. |
| 主题 | Econometrics ; Data Collection ; Industrial Organization ; Market Structure and Firm Performance ; Industry Studies |
| URL | https://www.nber.org/papers/w22569 |
| 来源智库 | National Bureau of Economic Research (United States) |
| 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/580243 |
| 推荐引用方式 GB/T 7714 | T. Kirk White,Jerome P. Reiter,Amil Petrin. Imputation in U.S. Manufacturing Data and Its Implications for Productivity Dispersion. 2016. |
| 条目包含的文件 | ||||||
| 文件名称/大小 | 资源类型 | 版本类型 | 开放类型 | 使用许可 | ||
| w22569.pdf（255KB） | 智库出版物 | 限制开放 | CC BY-NC-SA | 浏览 | ||
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