IDEAS home Printed from https://ideas.repec.org/a/rsr/supplm/v62y2014i10p120-127.html
   My bibliography  Save this article

Multiple Linear Regression Model Used in Economic Analyses

Author

Listed:
  • Constantin ANGHELACHE

    (Academy of Economic Studies, Bucharest, “Artifex” University of Bucharest)

  • Madalina Gabriela ANGHEL

    (“Artifex” University of Bucharest)

  • Ligia PRODAN

    (Academy of Economic Studies, Bucharest)

  • Cristina SACALA

    (Academy of Economic Studies, Bucharest)

  • Marius POPOVICI

    (Academy of Economic Studies, Bucharest)

Abstract

The multiple regression is a tool that offers the possibility to analyze the correlations between more than two variables, situation which account for most cases in macro-economic studies. The best known method of estimation for multiple regression is the method of least squares. As in the two-variable regression, we choose the regression function of sample and minimize the sum of squared residual values. Another method that allows us to take into account the number of variables factor when determining the validity of harmonization is given by the Akaike information criterion.

Suggested Citation

  • Constantin ANGHELACHE & Madalina Gabriela ANGHEL & Ligia PRODAN & Cristina SACALA & Marius POPOVICI, 2014. "Multiple Linear Regression Model Used in Economic Analyses," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 62(10), pages 120-127, Octomber.
    • Handle: RePEc:rsr:supplm:v:62:y:2014:i:10:p:120-127
    as

    Download full text from publisher

    File URL: http://www.revistadestatistica.ro/supliment/wp-content/uploads/2014/11/RRSS19_2014_A14.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dan CRUCERU & Madalina Gabriela ANGHEL & Aurelian DIACONU, 2016. "The multiple linear regression used to analyse the correlation between variables," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(10), pages 114-117, October.
    2. Florian Blaschke & Biewendt Marcel & Böhnert Arno, 2020. "The Repercussions of the Digital Twin in the Automotive Industry on the New Marketing Logic," European Journal of Marketing and Economics Articles, Revistia Research and Publishing, vol. 4, January -.
    3. Emmanouil Karakostas, 2023. "The Macroeconomic Determinants of the Stock Market Index Performance: The Case of DAX Index," International Journal of Economics & Business Administration (IJEBA), International Journal of Economics & Business Administration (IJEBA), vol. 0(3), pages 21-38.
    4. Mirela PANAIT & Andreea – Ioana Marinescu, 2016. "Statistical-econometric model used for the analysis of the correlation between the Gross Domestic Product and the Labour Productivity," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(11), pages 180-187, November.
    5. Constantin ANGHELACHE & Madalina Gabriela ANGHEL & Cristina SACALA, 2016. "The Financial Sector Influence On Portfolio Dynamics," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(7), pages 9-13, July.
    6. Constantin ANGHELACHE & Alexandru MANOLE & Mădălina Gabriela ANGHEL, 2015. "Analysis of final consumption and gross investment influence on GDP – multiple linear regression model," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(3(604), A), pages 137-142, Autumn.
    7. Adriana AnaMaria DAVIDESCU, 2015. "The Relationship between Shadow Economy and Unemployment Rate. A Ardl Causality Analysis for the Case Of Romania," Romanian Statistical Review, Romanian Statistical Review, vol. 63(4), pages 46-62, December.
    8. repec:agr:journl:v:3(604):y:2015:i:3(604):p:137-142 is not listed on IDEAS

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:rsr:supplm:v:62:y:2014:i:10:p:120-127. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Adrian Visoiu (email available below). General contact details of provider: https://edirc.repec.org/data/stagvro.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.