Artikel
Forecasting in small business management
This work aims to verify an authorial forecasting method from a system of interdependent equations, which is based on empirical equations of the structural form and is mainly intended for econometric micromodels. The prediction procedure will be analogous to the so-called chain prediction that is used for recursive models. The difference-compared with the prediction from a recursive model-entails the necessity of using one of the reduced-form empirical equations to begin the procedure of constructing a sequence of forecasts from successive structural-form empirical equations. The research results presented above indicate that the above-proposed iterative forecasting method from structural-form equations of a system of interdependent equations guarantees synchronization of forecasts as part of a closed cycle of relations. A different number of iterations is required to obtain convergent forecasts. It can be noticed that the further ahead the forecasted period is, the more iterations should be carried out to obtain convergent forecasts. Small business management with the use of forecasting can be done remotely. Rapid updates of statistical information will require cloud-based communication. Completion of data in a cloud will allow, on one hand, accurate assessment of expired forecasts and, on the other, to update the predictor equations. This can be carried out at any place with Internet access.
- Sprache
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Englisch
- Erschienen in
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Journal: Risks ; ISSN: 2227-9091 ; Volume: 9 ; Year: 2021 ; Issue: 4 ; Pages: 1-17 ; Basel: MDPI
- Klassifikation
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Wirtschaft
Multiple or Simultaneous Equation Models; Multiple Variables: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
- Thema
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econometric forecasting
econometric micromodel
small business management
small industrial enterprise
synchronization of forecasts
- Ereignis
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Geistige Schöpfung
- (wer)
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Wiśniewski, Jerzy W.
- Ereignis
-
Veröffentlichung
- (wer)
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MDPI
- (wo)
-
Basel
- (wann)
-
2021
- DOI
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doi:10.3390/risks9040069
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:45 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Artikel
Beteiligte
- Wiśniewski, Jerzy W.
- MDPI
Entstanden
- 2021
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