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Models and indicators used in macroeconomic forecast

Author

Listed:
  • Constantin ANGHELACHE

    (Bucharest University of Economic Studies/„Artifex„ University of Bucharest)

  • Mirela PANAIT

    (Petroleum-Gas University of Ploiesti)

  • Andreea - Ioana MARINESCU

    (Bucharest University of Economic Studies)

  • Georgiana NITA

    (Bucharest University of Economic Studies)

Abstract

In this article, the authors aim to analyze the links between certain macroeconomic indicators, using simple linear regression model and multiple. Thus, initially, will be addressed some general notions on macroeconomic forecast. Further extend the analysis will be used by applying simple linear regression models and multiple. The indicators used, GDP, consumption, export, import, is in fact variable interconnection. By using regression function, will be offered in terms of quantity, show the existence and intensity of existing interdependence and its analysis based on regression model. Using data series published by the National Statistics Institute, we look at the GDP in the period 1995-2015, the correlation between GDP and actual individual final consumption of households and links between GDP, on the one hand, and final consumption, the level of exports and imports, on the other hand, using multiple linear regression model.

Suggested Citation

  • Constantin ANGHELACHE & Mirela PANAIT & Andreea - Ioana MARINESCU & Georgiana NITA, 2017. "Models and indicators used in macroeconomic forecast," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(3), pages 40-48, March.
  • Handle: RePEc:rsr:supplm:v:65:y:2017:i:3:p:40-48
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    References listed on IDEAS

    as
    1. Constantin ANGHELACHE & Janusz GRABARA & Alexandru MANOLE, 2016. "Using the Dynamic Model ARMA to Forecast the Macroeconomic Evolution," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(1), pages 3-13, January.
    2. Corbae,Dean & Durlauf,Steven N. & Hansen,Bruce E. (ed.), 2006. "Econometric Theory and Practice," Cambridge Books, Cambridge University Press, number 9780521807234.
    3. Ghysels,Eric & Osborn,Denise R., 2001. "The Econometric Analysis of Seasonal Time Series," Cambridge Books, Cambridge University Press, number 9780521565882, January.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Constantin ANGHELACHE & Madalina-Gabriela ANGHEL & Gyorgy BODO, 2017. "Theoretical Aspects Of The Role Of Information In The Process Of Decisions/Risks Modeling," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(6), pages 102-111, June.
    2. Florin Paul Costel LILEA & Andreea – Ioana MARINESCU, 2017. "Macroeconomic Forecast Models – Concepts And Theoretical Notions," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(6), pages 118-123, June.
    3. Florin Paul Costel LILEA & Aurelian DIACONU & Radu Titus MARINESCU & Gyorgy BODO, 2017. "Structural Methods Used In Forecasting Studies," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(4), pages 66-74, April.

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    More about this item

    Keywords

    linear regression macro-economic indicator; GDP evolution; correlation; multiple regression; parameter;
    All these keywords.

    JEL classification:

    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E60 - Macroeconomics and Monetary Economics - - Macroeconomic Policy, Macroeconomic Aspects of Public Finance, and General Outlook - - - General

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