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Small continuous surveys and the Kalman filter

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Author Info
Jo Thori Lind () (Statistics Norway)

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Abstract

The time series nature of repeated surveys is seldom taken into account. I present a statistical model of repeated surveys and construct a computationally feasible estimator based on the Kalman filter. The novelty is that the estimator efficiently uses the whole underlying data set. However, for computational purposes, we only need the first and second empirical moments of the data.

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Publisher Info
Paper provided by Research Department of Statistics Norway in its series Discussion Papers with number 333.

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Date of creation: Nov 2002
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Handle: RePEc:ssb:dispap:333

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Related research
Keywords: Surveys; Kalman filter; time series.;

Find related papers by JEL classification:
C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions
C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Other Model Applications
C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Microeconomic Data

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References listed on IDEAS
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  1. Pfeffermann, Danny, 1991. "Estimation and Seasonal Adjustment of Population Means Using Data from Repeated Surveys: Reply," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 177, April.
  2. Andrew Harvey & Chia-Hui Chung, 2000. "Estimating the underlying change in unemployment in the UK," Journal Of The Royal Statistical Society Series A, Royal Statistical Society, vol. 163(3), pages 303-309. [Downloadable!] (restricted)
  3. Pfeffermann, Danny, 1991. "Estimation and Seasonal Adjustment of Population Means Using Data from Repeated Surveys," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 163-75, April.
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This page was last updated on 2009-12-18.

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