Causality
Data(s) |
01/01/2015
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Resumo |
Making correct causal claims is important for research and practice. This article explains what causality is, and how it can be established via experimental design. Because experiments are infeasible in many applied settings, researchers often use "observational" methods to estimate causal models. In these situations, it is likely that model estimates are compromised by endogeneity. The article discusses the conditions that engender endogeneity and methods that can eliminate it. |
Identificador |
http://serval.unil.ch/?id=serval:BIB_608DC25301A1 doi:10.1002/9781118785317.weom060023 http://my.unil.ch/serval/document/BIB_608DC25301A1.pdf http://nbn-resolving.org/urn/resolver.pl?urn=urn:nbn:ch:serval-BIB_608DC25301A14 |
Idioma(s) |
en |
Publicador |
Vodosek, M. den Hartog, D. N. |
Direitos |
info:eu-repo/semantics/openAccess |
Fonte |
Wiley Encyclopedia of Management (3 ed., Vol. VI, International Management). |
Tipo |
info:eu-repo/semantics/bookPart incollection |