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Small continuous surveys and the Kalman filter

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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.

Suggested Citation

  • Jo Thori Lind, 2002. "Small continuous surveys and the Kalman filter," Discussion Papers 333, Statistics Norway, Research Department.
    • Handle: RePEc:ssb:dispap:333
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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 177-177, 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.
    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 163-175, April.
    4. Watson, Mark W. & Engle, Robert F., 1983. "Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models," Journal of Econometrics, Elsevier, vol. 23(3), pages 385-400, December.
    5. R. H. Shumway & D. S. Stoffer, 1982. "An Approach To Time Series Smoothing And Forecasting Using The Em Algorithm," Journal of Time Series Analysis, Wiley Blackwell, vol. 3(4), pages 253-264, July.
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    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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