IDEAS home Printed from https://ideas.repec.org/h/spr/sptchp/978-981-95-7226-7_2.html

Linear Regression Model: Properties and Estimation

In: Econometrics in Theory and Practice

Author

Listed:
  • Panchanan Das

    (University of Calcutta, Department of Economics)

Abstract

The objectives of any regression analysis are to estimate the unknown parameters in the model, to validate whether the functional form of the model is consistent with the hypothesised model based on the theory, and to use the model to predict future values of the response variable. This chapter discusses linear regression model and its application with cross section data. Linear regression is a method of estimating the conditional expected value of the response or dependent variable given the values of a set of predictor or independent variables. Multiple regression analysis is more amenable to ceteris paribus analysis because it allows us to explicitly control for many other factors which simultaneously affect the dependent variable. The power of multiple regression analysis is that it provides the ceteris paribus interpretation even though the data have not been collected in a ceteris paribus fashion.

Suggested Citation

  • Panchanan Das, 2026. "Linear Regression Model: Properties and Estimation," Springer Texts in Business and Economics, in: Econometrics in Theory and Practice, edition 0, chapter 2, pages 39-64, Springer.
    • Handle: RePEc:spr:sptchp:978-981-95-7226-7_2
    DOI: 10.1007/978-981-95-7226-7_2
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    More about this item

    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:spr:sptchp:978-981-95-7226-7_2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.