Using linear regression to establish empirical relationships

Artikel

Linear regression is a powerful tool for investigating the relationships between multiple variables by relating one variable to a set of variables. It can identify the effect of one variable while adjusting for other observable differences. For example, it can analyze how wages relate to gender, after controlling for differences in background characteristics such as education and experience. A linear regression model is typically estimated by ordinary least squares, which minimizes the differences between the observed sample values and the fitted values from the model. Multiple tools are available to evaluate the model.

Object Details

• Language: Englisch

References and Relationships

• Bibliographic citation: Journal: IZA World of Labor ; ISSN: 2054-9571 ; Year: 2017 ; Bonn: Institute for the Study of Labor (IZA)

Classification and Topics

• Classification: Wirtschaft ; Single Equation Models; Single Variables: General ; Model Construction and Estimation ; Model Evaluation, Validation, and Selection
• Subject: linear regression ; ordinary least squares ; model specification ; estimation and inference ; causality

Contributors, Places and Time

• Event: Geistige Schöpfung
• (who): Verbeek, Marno
• Event: Veröffentlichung
• (who): Institute for the Study of Labor (IZA)
• (where): Bonn
• (when): 2017

Further information

• DOI: doi:10.15185/izawol.336
• Handle: http://hdl.handle.net/10419/162347
• Last update: 10.03.2025, 11:45 AM CET