Comparison of Inertia of Statistical Methods for Forecasting of Unemployment under Conditions of Economic Depression

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12510%2F09%3A00011038" target="_blank" >RIV/60076658:12510/09:00011038 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Comparison of Inertia of Statistical Methods for Forecasting of Unemployment under Conditions of Economic Depression

Popis výsledku v původním jazyce

Suitable models of unemployment rate development in Czech Republic under condition of economic depression were created and presented in this paper. Models?s were based on exponential smoothing and training of artificial neural networks. The most suitablemodels were exponential eventually damped model with additive seasonality and multilayer perceptron. March?s and April?s unemployment rate forecast was 7.58?7.89 % and 7.63?8.33 % for exponential smoothing respective 7.3?7.45 % and 6.62?8.22 % for multilayer perceptron. Recalculation of exponential smoothing model and retraining of ANNs is necessary at the time when it is possible obtain fresh values of the unemployment rate regarding to the present economic situation and relevant forecasting.

Název v anglickém jazyce

Comparison of Inertia of Statistical Methods for Forecasting of Unemployment under Conditions of Economic Depression

Popis výsledku anglicky

Suitable models of unemployment rate development in Czech Republic under condition of economic depression were created and presented in this paper. Models?s were based on exponential smoothing and training of artificial neural networks. The most suitablemodels were exponential eventually damped model with additive seasonality and multilayer perceptron. March?s and April?s unemployment rate forecast was 7.58?7.89 % and 7.63?8.33 % for exponential smoothing respective 7.3?7.45 % and 6.62?8.22 % for multilayer perceptron. Recalculation of exponential smoothing model and retraining of ANNs is necessary at the time when it is possible obtain fresh values of the unemployment rate regarding to the present economic situation and relevant forecasting.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Lucrari Stintifice

ISSN

1453-1410

e-ISSN

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Svazek periodika

11

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

RO - Rumunsko

Počet stran výsledku

8

Strana od-do

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Kód UT WoS článku

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EID výsledku v databázi Scopus

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