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Forecasting based on Very Small Samples and Additional Non-Sample Information

Author

Listed:
  • Brännäs, Kurt

    (Department of Economics, Umeå University)

  • Hellström, Jörgen

    (Department of Economics, Umeå University)

Abstract

Generalized method of moments estimation and forecasting is introduced for very small samples when additional non-sample information is available. Small simulation experiments are conducted for the linear model with errors-in-variables and for a Poisson regression model. Two empirical illustrations are included. One is based on Ukrainian imports and the other on private schools in a Swedish county.

Suggested Citation

  • Brännäs, Kurt & Hellström, Jörgen, 1998. "Forecasting based on Very Small Samples and Additional Non-Sample Information," Umeå Economic Studies 472, Umeå University, Department of Economics.
    • Handle: RePEc:hhs:umnees:0472
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    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Thomas A. Downes & Shane M. Greenstein, 1996. "Understanding the Supply Decisions of Nonprofits: Modelling the Location of Private Schools," RAND Journal of Economics, The RAND Corporation, vol. 27(2), pages 365-390, Summer.
    3. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521405515, October.
    4. Kadane, Joseph B, 1971. "Comparison of k-Class Estimators when the Disturbances are Small," Econometrica, Econometric Society, vol. 39(5), pages 723-737, September.
    5. Arthur Lewbel, 1997. "Constructing Instruments for Regressions with Measurement Error when no Additional Data are Available, with an Application to Patents and R&D," Econometrica, Econometric Society, vol. 65(5), pages 1201-1214, September.
    6. Thursby, Jerry G & Thursby, Marie C, 1984. "How Reliable Are Simple, Single Equation Specifications of Import Demand?," The Review of Economics and Statistics, MIT Press, vol. 66(1), pages 120-128, February.
    7. Caroline Minter Hoxby, 1994. "Do Private Schools Provide Competition for Public Schools?," NBER Working Papers 4978, National Bureau of Economic Research, Inc.
    8. Boylan, T. A. & Cuddy, M. P. & O'Muircheartaigh, I., 1980. "The functional form of the aggregate import demand equation : A comparison of three European economies," Journal of International Economics, Elsevier, vol. 10(4), pages 561-566, November.
    9. Gourieroux, Christian & Monfort, Alain & Trognon, Alain, 1984. "Pseudo Maximum Likelihood Methods: Applications to Poisson Models," Econometrica, Econometric Society, vol. 52(3), pages 701-720, May.
    10. Brannas, Kurt, 1995. "Prediction and control for a time-series count data model," International Journal of Forecasting, Elsevier, vol. 11(2), pages 263-270, June.
    11. Kennedy, Peter, 1991. "An Extension of Mixed Estimation, with an Application to Forecasting New Product Growth," Empirical Economics, Springer, vol. 16(4), pages 401-415.
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    Cited by:

    1. Nikas Rudholm, 2001. "Entry and the Number of Firms in the Swedish Pharmaceuticals Market," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 19(3), pages 351-364, November.
    2. Hellstrom, Jorgen, 2001. "Unit root testing in integer-valued AR(1) models," Economics Letters, Elsevier, vol. 70(1), pages 9-14, January.

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    More about this item

    Keywords

    Generalized method of moments; additional information; forecasting; Ukrainian imports; private schools;
    All these keywords.

    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
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access
    • F17 - International Economics - - Trade - - - Trade Forecasting and Simulation
    • I20 - Health, Education, and Welfare - - Education - - - General

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