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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. Gourieroux,Christian & Monfort,Alain, 1995. "Statistics and Econometric Models," Cambridge Books, Cambridge University Press, number 9780521471626, December.
    3. 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.
    4. 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.
    5. 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.
    6. Caroline Minter Hoxby, 1994. "Do Private Schools Provide Competition for Public Schools?," NBER Working Papers 4978, National Bureau of Economic Research, Inc.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Kadane, Joseph B, 1971. "Comparison of k-Class Estimators when the Disturbances are Small," Econometrica, Econometric Society, vol. 39(5), pages 723-737, September.
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    Cited by:

    1. Hellstrom, Jorgen, 2001. "Unit root testing in integer-valued AR(1) models," Economics Letters, Elsevier, vol. 70(1), pages 9-14, January.
    2. 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.

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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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