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首页> 美国政府科技报告 >Cleaning Up the Errors in the Monthly Employment Situation Report: A Multivariate211 State-Space Approach
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Cleaning Up the Errors in the Monthly Employment Situation Report: A Multivariate211 State-Space Approach

机译：清理月度就业情况报告中的错误：多元211国家空间方法

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This paper estimates the underlying state of the labor market, assuming data in211u001ethe monthly Employment Situation are contaminated by measurement error and other 211u001etransient noise. To better filter out unobserved noise, the methodology exploits 211u001ecorrelations among labor-market series. Household employment and labor force have 211u001ecross-correlated sampling errors; establishment employment and hours-worked may, 211u001ealso. The Kalman filtering procedure also exploits fundamental economic 211u001erelationships among these series. Error cross-correlations and economic 211u001erelationships shape a multivariate labor-market model where observed variables 211u001eembody unobserved components: trend, cycle and noise. Maximum-likelihood 211u001eestimation enables construction of labor series from which noise components have 211u001ebeen removed.

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