Schneider, Eric B. ORCID: 0000-0001-7682-0126 (2020) Collider bias in economic history research. Explorations in Economic History, 78. ISSN 0014-4983
Text (Collider Bias in Economic History Research)
- Accepted Version
Download (405kB) |
Abstract
Economic historians have long been aware of many forms of bias that could lead to spurious causal inferences. However, our approach to these biases has been muddled at times by dealing with each bias separately and by confusion about the sources of bias and how to mitigate them. This paper shows how the methodology of directed acyclical graphs (DAGs) formulated by Pearl (2009) and particularly the concept of collider bias can provide economic historians with a unified approach to managing a wide range of biases that can distort causal inference. I present ten examples of collider bias drawn from economic history research, focussing mainly on examples where the authors were able to overcome or mitigate the bias. Thus, the paper addresses how to diagnose collider bias and also strategies for managing it. The paper also shows that quasi-random experimental designs are rarely able to overcome collider bias. Although all of these biases were understood by economic historians before, conceptualising them as collider bias will improve economic historians’ understanding of the limitations of particular sources and help us develop better research designs in the future.
Item Type: | Article |
---|---|
Official URL: | https://www.sciencedirect.com/journal/explorations... |
Additional Information: | © 2020 Elsevier Inc. |
Divisions: | Economic History |
Subjects: | H Social Sciences > HC Economic History and Conditions |
JEL classification: | N - Economic History > N0 - General > N01 - Development of the Discipline: Historiographical; Sources and Methods N - Economic History > N3 - Labor and Consumers, Demography, Education, Health, Income, and Wealth > N30 - Economic History: Labor and Consumers, Demography, Education, Health, Income and Wealth: General, International, or Comparative (Migration) |
Date Deposited: | 16 Sep 2020 09:12 |
Last Modified: | 12 Dec 2024 02:19 |
URI: | http://eprints.lse.ac.uk/id/eprint/106578 |
Actions (login required)
View Item |