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来源类型 | Working Paper |
规范类型 | 报告 |
DOI | 10.3386/w20325 |
来源ID | Working Paper 20325 |
Finite Population Causal Standard Errors | |
Alberto Abadie; Susan Athey; Guido W. Imbens; Jeffrey M. Wooldridge | |
发表日期 | 2014-07-24 |
出版年 | 2014 |
语种 | 英语 |
摘要 | When a researcher estimates the parameters of a regression function using information on all 50 states in the United States, or information on all visits to a website, what is the interpretation of the standard errors? Researchers typically report standard errors that are designed to capture sampling variation, based on viewing the data as a random sample drawn from a large population of interest, even in applications where it is difficult to articulate what that population of interest is and how it differs from the sample. In this paper we explore alternative interpretations for the uncertainty associated with regression estimates. As a leading example we focus on the case where some parameters of the regression function are intended to capture causal effects. We derive standard errors for causal effects using a generalization of randomization inference. Intuitively, these standard errors capture the fact that even if we observe outcomes for all units in the population of interest, there are for each unit missing potential outcomes for the treatment levels the unit was not exposed to. We show that our randomization-based standard errors in general are smaller than the conventional robust standard errors, and provide conditions under which they agree with them. More generally, correct statistical inference requires precise characterizations of the population of interest, the parameters that we aim to estimate within such population, and the sampling process. Estimation of causal parameters is one example where appropriate inferential methods may differ from conventional practice, but there are others. |
主题 | Econometrics ; Estimation Methods |
URL | https://www.nber.org/papers/w20325 |
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/577998 |
推荐引用方式 GB/T 7714 | Alberto Abadie,Susan Athey,Guido W. Imbens,et al. Finite Population Causal Standard Errors. 2014. |
条目包含的文件 | 条目无相关文件。 |
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