Forecast the Gross Value Added in Construction Sector of Bulgaria with SARIMA Model
Plamen Yankov (),
Julian Vasilev (),
Pavel Petrov (),
Liliya Mileva () and
Svetlana Todorova ()
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Plamen Yankov: University of Economics - Varna, Varna, Bulgaria
Pavel Petrov: University of Economics - Varna, Varna, Bulgaria
Liliya Mileva: University of Economics - Varna, Varna, Bulgaria
Svetlana Todorova: University of Economics - Varna, Varna, Bulgaria
Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, 2021, vol. 10, issue 1, 45-54
Construction is an important sector for national economies because it contributes with relatively high gross value added (GVA). The purpose of this study is to forecast GVA in a short-term period based on seasonal ARIMA models. Quarterly time series data from 2010 to 2020 are used for modelling and forecasting. Stationarity is achieved after differencing both - seasonal and non-seasonal component of the data. Based on autocorrelation plots SARIMA model is selected as most accurate. Ljung-Box test for the absence of autocorrelation confirms that the model is adequate and suitable to forecast. The current study is conducted as part of the research project BG05M2OP001-1.002-0002-C02 "Digitalization of Economy in a Big Data Environment".
Keywords: SARIMA; gross value added; forecast; construction (search for similar items in EconPapers)
JEL-codes: E17 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:vra:journl:v:10:y:2021:i:1:p:45-54
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