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Causality in the Sciences$
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Phyllis McKay Illari, Federica Russo, and Jon Williamson

Print publication date: 2011

Print ISBN-13: 9780199574131

Published to Oxford Scholarship Online: September 2011

DOI: 10.1093/acprof:oso/9780199574131.001.0001

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The error term and its interpretation in structural models in econometrics

The error term and its interpretation in structural models in econometrics

Chapter:
(p.361) 17 The error term and its interpretation in structural models in econometrics
Source:
Causality in the Sciences
Author(s):

Damien Fennell

Publisher:
Oxford University Press
DOI:10.1093/acprof:oso/9780199574131.003.0017

This chapter explores what the error term represents in structural models in econometrics and the assumptions about the error terms that are used for successful statistical and causal inference. The error term is of particular interest because it acts as a coverall term for parts of the system that are not fully known about and not explicitly modelled. The chapter attempts to bring some of the key assumptions imposed on the error term for different purposes (statistical and causal inference) and to ask to what extent the conditions imposed on the error term can be empirically tested in some way.

Keywords:   error term, econometrics, structural models, causal inference

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