Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

Simple versus complex models: evaluation, accuracy, and combining.

D A Ahlburg

    Mathematical Population Studies
    |July 1, 1995
    PubMed
    Summary

    It is too early to determine if complex or causal demographic forecasting models are superior. Combining forecasts may enhance accuracy, and searching for a single best model is questionable.

    Related Concept Videos

    You might also read

    Related Articles

    Articles linked to this work by shared authors, journal, and citation graph.

    Sort by
    Same author

    Determinants of extramarital sex in the Philippines.

    Health transition review : the cultural, social, and behavioural determinants of health·1996
    Same author

    The demographic and employment characteristics of home care aides: a comparison with nursing home aides, hospital aides, and other workers.

    The Gerontologist·1995
    Same author

    New realities of the American family.

    Population bulletin·1992
    Same author

    Alternative projections of the U.S. population.

    Demography·1990
    Same author

    Is population growth a deterrent to development in the South Pacific?

    Journal of the Australian Population Association·1988
    Same author

    Population forecasts for South Pacific nations using autoregressive models, 1985-2000.

    Journal of the Australian Population Association·1987

    Area of Science:

    • Demography
    • Statistical Modeling
    • Forecasting Science

    Background:

    • The accuracy of demographic forecasting models is a persistent challenge.
    • Existing research often focuses on comparing specific model types (simple vs. complex, causal vs. noncausal).
    • The optimal approach for demographic prediction remains debated.

    Purpose of the Study:

    • To critically evaluate the current state of comparing demographic forecasting models.
    • To question the pursuit of a single, universally superior model.
    • To explore alternative strategies for improving forecast accuracy.

    Main Methods:

    • Literature review and theoretical analysis of forecasting model performance.
    • Conceptual examination of model complexity and causality in demography.
    Keywords:
    Estimation TechnicsEvaluationEvaluation MethodologyMeasurementModels, TheoreticalPopulation ForecastPopulation ProjectionReliabilityResearch MethodologyWorld

    Related Experiment Videos

  • Exploration of ensemble methods for forecast combination.

    • Main Results:

    • Current evidence is insufficient to definitively rank simple versus complex or causal versus noncausal demographic models.
    • The conditions under which different model types excel are not yet well-established.
    • The search for a singular 'best' model may be a misguided objective.

    Conclusions:

    • Decisive conclusions on the superiority of specific demographic model types are premature.
    • Further research is needed to understand model performance under various conditions.
    • Combining multiple forecasts is a promising strategy to enhance overall accuracy in demography.