دانلود مقاله ISI انگلیسی شماره 41781
عنوان فارسی مقاله

پیش بینی "پیش بینی های جمعیت شناختی"

کد مقاله سال انتشار مقاله انگلیسی ترجمه فارسی تعداد کلمات
41781 2014 8 صفحه PDF سفارش دهید 6770 کلمه
خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.
عنوان انگلیسی
Forecasting demographic forecasts
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : International Journal of Forecasting, Volume 30, Issue 4, October–December 2014, Pages 1128–1135

کلمات کلیدی
انتظار مشروط - پیش بینی به روز رسانی - پیش بینی جمعیت - انتظارات عقلایی - تردید
پیش نمایش مقاله
پیش نمایش مقاله پیش بینی "پیش بینی های جمعیت شناختی"

چکیده انگلیسی

Consider the financial sustainability of public finances in the context of stochastic demographics. Such analyses have typically been made under the assumption that future demographic developments are deterministic. When stochastic demographics have been considered, the problems have been simplified by assuming that the decision makers in the economic system behave as if they had perfect foresight as regards demographics. More realistically, we assume that the decision makers base their decisions on the forecasts of the future population, but revise their decisions when it turns out that the demographics do not follow the expected path. We contrast the nature of demographic uncertainty with that of financial markets, and argue that it is not realistic to assume that the revisions will occur according to the full rational expectations paradigm. Instead, the decision makers are assumed to revise according to the most recent point forecast. To implement this approach, we tailor standard nonparametric regression techniques to the task of computing the required future conditional expectations. Specifically, we assume that an approximation to the predictive distribution of the future population is available in terms of simulated population counts. The required conditional expectations are then obtained by averaging the future evolution of a set of sample paths that come from the neighborhood of a target path. This is formally equivalent to nn-nearest neighbor kernel regression. The degree of smoothing can be chosen via cross-validation. An illustration based on a stochastic forecast of the population of Finland is given.

خرید مقاله
پس از پرداخت، فوراً می توانید مقاله را دانلود فرمایید.