IDEAS home Printed from https://ideas.repec.org/a/rjr/romjef/vy2010i2p245-264.html
   My bibliography  Save this article

An Analysis Model for the Disturbances Generated by Collinearity in the Context of the OLS Method

Author

Listed:
  • Pavelescu, Florin Marius

    (Institute of National Economy, The Romanian Academy)

Abstract

Under the conditions of OLS use in order to perform multiple linear regressions, both the estimated parameters values and also computed values of some statistical tests such as coefficient of determination, Fisher test or Student test are influenced by collinearity1. The respective influence is revealed by the values of the coefficient of alignment to collinearity hazard. For this reason, this paper presents an analysis model which identifies the factors and their influences on the above-mentioned indicator. On the one hand, we quantify the factors contribution to the arithmetical mean of coefficients of alignment to collinearity hazard, having in view that the respective indicator reveals the collinearity impact on a linear regression model as a whole. On the other hand, we emphasize the necessary conditions for the positivity of all coefficients of alignment to collinearity hazard, in order to avoid the occurrence of “unexpected signs” in case of some estimated parameters. Also, we bring some clarifications and extensions of the other concepts previously proposed by the author such as: the main and secondary explanatory variable, coefficient of mediated by resultative variable correlation between explanatory variables.

Suggested Citation

  • Pavelescu, Florin Marius, 2010. "An Analysis Model for the Disturbances Generated by Collinearity in the Context of the OLS Method," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(2), pages 245-264, July.
    • Handle: RePEc:rjr:romjef:v::y:2010:i:2:p:245-264
    as

    Download full text from publisher

    File URL: http://www.ipe.ro/rjef/rjef2_10/rjef2_10_16.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jansen, W Jos & Schulze, Gunther G, 1996. "Theory-Based Measurement of the Saving-Investment Correlation with an Application to Norway," Economic Inquiry, Western Economic Association International, vol. 34(1), pages 116-132, January.
    2. Pavelescu, Florin Marius, 2004. "Features Of The Ordinary Least Square (Ols) Method. Implications For The Estimation Methodology," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 1(2), pages 85-101, May.
    3. Pavelescu, Florin Marius, 2005. "Impact Of Collinearity On The Estimated Parameters And Classical Statistical Tests Values Of Multifactorial Linear Regressions In Conditions Of O.L.S," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 2(2), pages 50-71.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Florin-Marius PAVELESCU, 2011. "Some aspects of the translog production function estimation," Romanian Journal of Economics, Institute of National Economy, vol. 32(1(41)), pages 131-150, June.
    2. Gertrude Sebunya Muwanga, 2017. "Estimation Of Cob-Douglas And Translog Production Functions With Capital And Gender Disaggregated Labor Inputs In The Usa," Journal of Smart Economic Growth, , vol. 2(3), pages 55-105, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pavelescu, Florin Marius, 2009. "A Review Of Student Test Properties In Condition Of Multifactorial Linear Regression," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 6(1), pages 63-75, March.
    2. Herwartz, H. & Xu, F., 2010. "A functional coefficient model view of the Feldstein-Horioka puzzle," Journal of International Money and Finance, Elsevier, vol. 29(1), pages 37-54, February.
    3. Chakrabarti, Avik, 2006. "The saving-investment relationship revisited: New evidence from multivariate heterogeneous panel cointegration analyses," Journal of Comparative Economics, Elsevier, vol. 34(2), pages 402-419, June.
    4. Anastasios Mastroyiannis, 2007. "Current Account Dynamics and the Feldstein and Horioka Puzzle: the Case of Greece," European Journal of Comparative Economics, Cattaneo University (LIUC), vol. 4(1), pages 91-99, June.
    5. Yannick BINEAU, 2010. "A Empirical Assessment of the Feldstein and Horioka Literature," EcoMod2010 259600030, EcoMod.
    6. Jan Lemmen & Sylvester Eijffinger, 1995. "The quantity approach to financial integration: The Feldstein-Horioka criterion revisited," Open Economies Review, Springer, vol. 6(2), pages 145-165, April.
    7. Taylor, Alan M., 2002. "A century of current account dynamics," Journal of International Money and Finance, Elsevier, vol. 21(6), pages 725-748, November.
    8. Apergis, Nicholas & Tsoumas, Chris, 2009. "A survey of the Feldstein-Horioka puzzle: What has been done and where we stand," Research in Economics, Elsevier, vol. 63(2), pages 64-76, June.
    9. Martin B. Schmidt, 2001. "Savings and Investment: Some International Perspectives," Southern Economic Journal, John Wiley & Sons, vol. 68(2), pages 446-456, October.
    10. Syed Abul Basher & Stefano Fachin, 2013. "The long-run relationship between savings and investment in oil-exporting developing countries: a case study of the Gulf Arab states," OPEC Energy Review, Organization of the Petroleum Exporting Countries, vol. 37(4), pages 429-446, December.
    11. Florin Marius PAVELESCU, 2016. "Economic Cycles and Disembodied Technical Change of Romania’s Economy During the Period 1863-1913," Romanian Journal of Economics, Institute of National Economy, vol. 43(2(52)), pages 133-155, december.
    12. Mariam Camarero & Alejandro Muñoz & Cecilio Tamarit, 2021. "50 Years of Capital Mobility in the Eurozone: Breaking the Feldstein-Horioka Puzzle," Open Economies Review, Springer, vol. 32(5), pages 867-905, November.
    13. Jerry Coakley & Ana-Maria Fuertes & Fabio Spagnolo, 2004. "The Feldstein-Horioka puzzle is not as bad as you think," Money Macro and Finance (MMF) Research Group Conference 2003 17, Money Macro and Finance Research Group.
    14. Florin-Marius PAVELESCU, 2011. "Some aspects of the translog production function estimation," Romanian Journal of Economics, Institute of National Economy, vol. 32(1(41)), pages 131-150, June.
    15. Jos Jansen, W, 1996. "Estimating saving-investment correlations: evidence for OECD countries based on an error correction model," Journal of International Money and Finance, Elsevier, vol. 15(5), pages 749-781, October.
    16. Taylor, Alan M., 1998. "Argentina and the world capital market: saving, investment, and international capital mobility in the twentieth century," Journal of Development Economics, Elsevier, vol. 57(1), pages 147-184, October.
    17. R. López Murphy, F. Navajas, S. Urbiztondo, C. Moskovits, 1996. "Determinantes del Ahorro Interno: El Caso Argentino," Working Papers 51, FIEL.
    18. Tarlok Singh, 2007. "Intertemporal Optimizing Models Of Trade And Current Account Balance: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 21(1), pages 25-64, February.
    19. Florin Marius Pavelescu, 2010. "An Extensive Study on the Disturbances Generated by Collinearity in a Linear Regression Model with Three Explanatory Variables," Romanian Journal of Economics, Institute of National Economy, vol. 31(2(40)), pages 65-93, December.
    20. Hoffmann, Mathias, 2004. "International capital mobility in the long run and the short run: can we still learn from saving-investment data?," Journal of International Money and Finance, Elsevier, vol. 23(1), pages 113-131, February.

    More about this item

    Keywords

    arithmetical mean of coefficients of allignament to collinearity hazard; main explanatory variables; secondary explanatory variables; coefficient of correlation between explanatory variables mediated by resultative variable; structural constraints of a multiple linear regression model.;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

    Statistics

    Access and download statistics

    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:rjr:romjef:v::y:2010:i:2:p:245-264. 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.

    If CitEc recognized a bibliographic 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.

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