IDEAS home Printed from
   My bibliography  Save this article

Multiple linear regression used to analyse the corelation between GDP and some variables


  • Constantin Anghelache

    (Bucharest University of Economic Studies, “ARTIFEX” University of Bucharest)

  • Cristina SACALÃ

    (Bucharest University of Economic Studies)


Statistical researchers often use a linear relationship to predict the (average) numerical value of Y for a given value of X using a straight line (called the regression line). If you know the slope and the y-intercept of that regression line, then you can plug in a value for X and predict the average value for Y. In other words, you predict (the average) Y from X. If you establish at least a moderate correlation between X and Y through both a correlation coefficient and a scatterplot, then you know they have some type of linear relationship.

Suggested Citation

  • Constantin Anghelache & Cristina SACALÃ, 2016. "Multiple linear regression used to analyse the corelation between GDP and some variables," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(9), pages 94-99, September.
  • Handle: RePEc:rsr:supplm:v:64:y:2016:i:9:p:94-99

    Download full text from publisher

    File URL:
    Download Restriction: no

    References listed on IDEAS

    1. Charles R. Hulten & Paul Schreyer, 2010. "GDP, Technical Change, and the Measurement of Net Income: the Weitzman Model Revisited," NBER Working Papers 16010, National Bureau of Economic Research, Inc.
    2. Ryan Macdonald, 2010. "Real Gross Domestic Income, Relative Prices, And Economic Performance Across The Oecd," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 56(3), pages 498-518, September.
    3. Constantin ANGHELACHE & Madalina Anghel, 2015. "Model of analysis of the dynamics of the DFI (DFI) sold correlated with the evolution of the GDP at European level," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 63(10), pages 79-85, October.
    4. 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.
    5. Charles I. Jones & Peter J. Klenow, 2016. "Beyond GDP? Welfare across Countries and Time," American Economic Review, American Economic Association, vol. 106(9), pages 2426-2457, September.
    6. Ramcharan, Rodney, 2007. "Does the exchange rate regime matter for real shocks? Evidence from windstorms and earthquakes," Journal of International Economics, Elsevier, vol. 73(1), pages 31-47, September.
    7. Clara Capelli & Gianni Vaggi, 2013. "A better indicator of standards of living: The Gross National Disposable Income," DEM Working Papers Series 062, University of Pavia, Department of Economics and Management.
    Full references (including those not matched with items on IDEAS)


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

    Cited by:

    1. Constantin Anghelache & Aurelian DIACONU & Andreea Ioana MARINESCU & Marius POPOVICI, 2016. "Comparative study of the evolution of the Gross Domestic Product indicator," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(12), pages 165-172, December.
    2. repec:rsr:supplm:v:65:y:2017:i:2:p:122-129 is not listed on IDEAS
    3. Constantin ANGHELACHE & Ion PARTACHI & Madalina-Gabriela ANGHEL & Gyorgy BODO & Radu STOIAN, 2016. "General theoretical notions on univariate regression," Romanian Statistical Review Supplement, Romanian Statistical Review, vol. 64(11), pages 136-144, November.

    More about this item


    regression; correlation; intercept; variables;


    Access and download statistics


    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:64:y:2016:i:9:p:94-99. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Adrian Visoiu). General contact details of provider: .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.