Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/162347 
Authors: 
Year of Publication: 
2017
Citation: 
[Journal:] IZA World of Labor [ISSN:] 2054-9571 [Article No.:] 336 [Publisher:] Institute for the Study of Labor (IZA) [Place:] Bonn [Year:] 2017
Publisher: 
Institute for the Study of Labor (IZA), Bonn
Abstract: 
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.
Subjects: 
linear regression
ordinary least squares
model specification
estimation and inference
causality
JEL: 
C1
C20
C51
C52
Persistent Identifier of the first edition: 
Document Type: 
Article

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