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Estimation of Time Series of Latent Variables in an Accounting System Petrol Consumption of Norwegian Households 1973-1995




We present an approach for estimating time series of a set of latent variables satisfying accounting identities. We concentrate on a simple case study and comment on possible generalizations. The model consists of three main parts: (i) A system of accounting identities, e.g., a subsystem of the national accounts, which variables are considered latent. (ii) A measurement model connecting the latent variables to indicators from different sources, including micro and macro data. (iii) Stochastic processes of a subset of the latent variables in the accounting system, with stochastic trend and random walk as alternative models. The model is given a state space formulation and the Kalman filter and EM algorithms implemented in the software STAMP, are used to estimate the parameters and the time series of the latent variables. The approach is applied to estimate petrol consumption of the household and nonhousehold sectors in Norway 1973-1995, from observation of macro data on total petrol consumption and survey data of household expenditures for petrol. Satisfactory model properties are obtained. The stochastic trend model gives smooth and plausible estimates of the time series of latent petrol consumption of the household and nonhousehold sectors.

Suggested Citation

  • Jørgen Aasness & Liv Belsby, 1997. "Estimation of Time Series of Latent Variables in an Accounting System Petrol Consumption of Norwegian Households 1973-1995," Discussion Papers 203, Statistics Norway, Research Department.
  • Handle: RePEc:ssb:dispap:203

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    References listed on IDEAS

    1. Sichel, Daniel E, 1994. "Inventories and the Three Phases of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 269-277, July.
    2. Hamilton, James D., 1996. "Specification testing in Markov-switching time-series models," Journal of Econometrics, Elsevier, vol. 70(1), pages 127-157, January.
    3. Durland, J Michael & McCurdy, Thomas H, 1994. "Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 279-288, July.
    4. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    5. Knut Rosendahl, 1997. "Does improved environmental policy enhance economic growth?," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 9(3), pages 341-364, April.
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    More about this item


    National accounts; latent variables; stochastic trends; state space models.;

    JEL classification:

    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access


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