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Econometric Model For Analyzing The Influence Of Factors On Final Consumption

Author

Listed:
  • Madalina-Gabriela ANGHEL

    („Artifex” University of Bucharest)

  • Ana CARP

    („Artifex” University of Bucharest)

  • Marian SFETCU

    („Artifex” University of Bucharest)

  • Stefan Gabriel DUMBRAVA

Abstract

Statistic and econometric models can be used, to great effect, in macroeconomic forecasting studies. Thus, we can perform forecasts (prognoses) by using the regression model, either simple, multiple, linear or non-linear. In fact, we resort to a extrapolation of results for a future period, by taking into account the regression parameters. Having in mind the importance of consumption for standard of living, we will analyse the conection between final consumption as explained variable and the private consumption, public consumption and gross available income of population. The multiple linear regression analysis can be used in final consumption recorded at the level of the Romanian economy. To build a linear multiple regression model, we defined the private consumption, public consumption and gross available income as independent variables, while final consumption value was considered a dependent variable, that is the main variable of the model.

Suggested Citation

  • Madalina-Gabriela ANGHEL & Ana CARP & Marian SFETCU & Stefan Gabriel DUMBRAVA, 2017. "Econometric Model For Analyzing The Influence Of Factors On Final Consumption," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 65(10), pages 123-131, October.
  • Handle: RePEc:rsr:supplm:v:65:y:2017:i:10:p:123-131
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    References listed on IDEAS

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    1. Nezih Guner & Gustavo Ventura & Xu Yi, 2008. "Macroeconomic Implications of Size-Dependent Policies," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 11(4), pages 721-744, October.
    2. Robert E. Lucas Jr. & Benjamin Moll, 2014. "Knowledge Growth and the Allocation of Time," Journal of Political Economy, University of Chicago Press, vol. 122(1), pages 1-51.
    3. Ricardo Reis, 2009. "The Time-Series Properties of Aggregate Consumption: Implications for the Costs of Fluctuations," Journal of the European Economic Association, MIT Press, vol. 7(4), pages 722-753, June.
    4. Censolo, Roberto & Colombo, Caterina, 2008. "Public consumption composition in a growing economy," Journal of Macroeconomics, Elsevier, vol. 30(4), pages 1479-1495, December.
    5. Constantin Anghelache & Madalina Gabriela Anghel & Marius Popovici, 2015. "Multiple Regressions Used in Analysis of Private Consumption and Public Final Consumption Evolution," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 5(4), pages 69-73, October.
    6. Constantin Anghelache & Madalina Gabriela Anghel & Ligia Prodan & Cristina Sacala & Marius Popovici, 2015. "Elements concerning the Use of Multiple Regression Models," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 63(4), pages 27-29, April.
    7. Jason Choi & Andrew T. Foerster, 2016. "Consumption Growth Regimes and the Post-Financial Crisis Recovery," Economic Review, Federal Reserve Bank of Kansas City, issue Q II, pages 25-48.
    8. Constantin ANGHELACHE & Madalina Gabriela ANGHEL, 2017. "Econometric Methods And Models Used In The Analysis Of The Factorial Influence Of The Gross Domestic Product Growth," Network Intelligence Studies, Romanian Foundation for Business Intelligence, Editorial Department, issue 9, pages 67-78, June.
    9. Francesca Bastagli & John Hills, 2013. "What Gives? Household Consumption Patterns and the 'Big Trade Off' with Public Consumption," CASE Papers case170, Centre for Analysis of Social Exclusion, LSE.
    10. Jorgenson, Dale W. & Slesnick, Daniel T., 2008. "Consumption and labor supply," Journal of Econometrics, Elsevier, vol. 147(2), pages 326-335, December.
    11. Constantin ANGHELACHE & Marius POPOVICI, 2015. "Analysis Theoretical Model Of The Consumption From The Gross Domestic Product," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 63(11), pages 57-62, November.
    12. repec:cep:sticas:/170 is not listed on IDEAS
    13. N. De Michelis & P. Monfort, 2008. "Some reflections concerning GDP, regional convergence and European cohesion policy," Regional Science Policy & Practice, Wiley Blackwell, vol. 1(1), pages 15-22, November.
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    More about this item

    Keywords

    final consumption; private consumption; public consumption; available gross income; econometric model;
    All these keywords.

    JEL classification:

    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • E21 - Macroeconomics and Monetary Economics - - Consumption, Saving, Production, Employment, and Investment - - - Consumption; Saving; Wealth

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