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Prior Information In Econometric Global Optimization Problems: A Bootstrap Approach

Author

Listed:
  • Agapie, Adriana

    (Institute for Economic Forecasting, Romanian Academy, Bucharest)

Abstract

The paper analyzes the regression problem for small and undersized sample. Two classical algorithms are compared: Simulated Annealing (SA) versus Repetitive Stochastic Guesstimation (RSG). An improved version of RSG is built and compared to the previous two algorithms. The author concludes that a complete comparison among SA, RSG and RSGBOOT has to be done preliminary on every model to be estimated since these stochastic optimization algorithms are very sensitive to model specification.

Suggested Citation

  • Agapie, Adriana, 2000. "Prior Information In Econometric Global Optimization Problems: A Bootstrap Approach," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 110-121, December.
    • Handle: RePEc:rjr:romjef:v::y:2000:i:4:p:110-121
    as

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    More about this item

    Keywords

    optimization algorithms; SA; RSG; RSGBOOT; Monte Carlo;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics

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