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来源类型Working Paper
规范类型报告
DOI10.3386/t0257
来源IDTechnical Working Paper 0257
Bias from Classical and Other Forms of Measurement Error
Dean R. Hyslop; Guido W. Imbens
发表日期2000-08-01
出版年2000
语种英语
摘要We consider the implications of a specific alternative to the classical measurement error model, in which the data are optimal predictions based on some information set. One motivation for this model is that if respondents are aware of their ignorance they may interpret the question what is the value of this variable?' as what is your best estimate of this variable?', and provide optimal predictions of the variable of interest given their information set. In contrast to the classical measurement error model, this model implies that the measurement error is uncorrelated with the reported value and, by necessity, correlated with the true value of the variable. In the context of the linear regression framework, we show that measurement error can lead to over- as well as under-estimation of the coefficients of interest. Critical for determining the bias is the model for the individual reporting the mismeasured variables, the individual's information set, and the correlation structure of the errors. We also investigate the implications of instrumental variables methods in the presence of measurement error of the optimal prediction error form and show that such methods may in fact introduce bias. Finally, we present some calculations indicating that the range of estimates of the returns to education consistent with amounts of measurement error found in previous studies. This range can be quite wide, especially if one allows for correlation between the measurement errors.
主题Econometrics ; Estimation Methods
URLhttps://www.nber.org/papers/t0257
来源智库National Bureau of Economic Research (United States)
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资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/565391
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GB/T 7714
Dean R. Hyslop,Guido W. Imbens. Bias from Classical and Other Forms of Measurement Error. 2000.
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