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Microbased Time Series Analysis: Estimating the autocorrelation function using survey sampling IV


  • Lundquist, Peter

    (Dept. of Economic Statistics, Stockholm School of Economics)


Analysts using data from official statistical authorities often neglect the fact that data frequently are collected using sample surveys. In this paper the impact of sampling error on the estimation of the autocovariance and the autocorrelation function is studied under a micro based superpopulation time series model. Uncritical use of data published by statistical agencies may result in biased estimators. The bias is caused by the sampling error and is different from aggregation bias. Different estimators are investigated theoretically as well as with the help of simulations.

Suggested Citation

  • Lundquist, Peter, 1994. "Microbased Time Series Analysis: Estimating the autocorrelation function using survey sampling IV," SSE/EFI Working Paper Series in Economics and Finance 40, Stockholm School of Economics.
  • Handle: RePEc:hhs:hastef:0040

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    References listed on IDEAS

    1. Kenneth Rogoff, 1985. "The Optimal Degree of Commitment to an Intermediate Monetary Target," The Quarterly Journal of Economics, Oxford University Press, vol. 100(4), pages 1169-1189.
    2. Obstfeld, Maurice, 1997. "Destabilizing effects of exchange-rate escape clauses," Journal of International Economics, Elsevier, vol. 43(1-2), pages 61-77, August.
    3. Persson, Torsten & Tabellini, Guido, 1993. "Designing institutions for monetary stability," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 39(1), pages 53-84, December.
    4. Kydland, Finn E & Prescott, Edward C, 1977. "Rules Rather Than Discretion: The Inconsistency of Optimal Plans," Journal of Political Economy, University of Chicago Press, vol. 85(3), pages 473-491, June.
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    More about this item


    Microbased time series analysis; superpopulation model; sampling error; autocorrelation function;

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods


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