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Original scientific paper
https://doi.org/10.1080/1331677X.2015.1081828

Forecasting public expenditure by using feed-forward neural networks

Magdalena Radulescu
Banica Logica
Tatiana Zamfiroiu

Fulltext: english, pdf (434 KB) pages 668-686 downloads: 221* cite
APA 6th Edition
Radulescu, M., Logica, B. & Zamfiroiu, T. (2015). Forecasting public expenditure by using feed-forward neural networks. Economic research - Ekonomska istraživanja, 28 (1), 668-686. https://doi.org/10.1080/1331677X.2015.1081828
MLA 8th Edition
Radulescu, Magdalena, et al. "Forecasting public expenditure by using feed-forward neural networks." Economic research - Ekonomska istraživanja, vol. 28, no. 1, 2015, pp. 668-686. https://doi.org/10.1080/1331677X.2015.1081828. Accessed 19 Feb. 2020.
Chicago 17th Edition
Radulescu, Magdalena, Banica Logica and Tatiana Zamfiroiu. "Forecasting public expenditure by using feed-forward neural networks." Economic research - Ekonomska istraživanja 28, no. 1 (2015): 668-686. https://doi.org/10.1080/1331677X.2015.1081828
Harvard
Radulescu, M., Logica, B., and Zamfiroiu, T. (2015). 'Forecasting public expenditure by using feed-forward neural networks', Economic research - Ekonomska istraživanja, 28(1), pp. 668-686. https://doi.org/10.1080/1331677X.2015.1081828
Vancouver
Radulescu M, Logica B, Zamfiroiu T. Forecasting public expenditure by using feed-forward neural networks. Economic research - Ekonomska istraživanja [Internet]. 2015 [cited 2020 February 19];28(1):668-686. https://doi.org/10.1080/1331677X.2015.1081828
IEEE
M. Radulescu, B. Logica and T. Zamfiroiu, "Forecasting public expenditure by using feed-forward neural networks", Economic research - Ekonomska istraživanja, vol.28, no. 1, pp. 668-686, 2015. [Online]. https://doi.org/10.1080/1331677X.2015.1081828

Abstracts
In this paper, we analyse the correlation of the public expenses by functions with real GDP growth, elaborating a model of estimating and forecasting the main public expenses in some selected Central and Eastern European (CEE) countries: Hungary, Poland, the Czech Republic, Bulgaria and Romania. These countries have not adopted the euro yet. This paper presents several forecasting models for the CEE countries public expenditures, during 2015–2016. The models offer a base for the analysis of the potential budgetary implications of the government policies for the target countries. A short- and mid-term forecast for public expenditure is an important part of the modern methods of governmental management for the Central and
Eastern European countries. This involves taking into account a wide range of factors, from GDP, inflation, demographic evolution and age share, to public expenditure type correlation. Such a forecast can be obtained with the help of artificial neural networks (ANNs), using the application GMDH Shell, which proved its ability to create complex and accurate forecasts for the economic, social and financial domains.

Keywords
public spending; Central and Eastern European countries; forecasting model; neural networks; budgetary policy; economic growth

Hrčak ID: 171553

URI
https://hrcak.srce.hr/171553

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