2017
DOI: 10.2139/ssrn.3014477
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Identification and Generalizability in Accounting Research: A Discussion of Christensen, Floyd, Liu, and Maffett (2017)

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Cited by 21 publications
(28 citation statements)
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“…BDJO and most recent literature on the effect of disclosure regulation use a difference‐in‐differences (DiD) approach. The challenges with the DiD approach are extensively discussed in the context of accounting disclosure studies by, among others, Leuz and Wysocki () and Glaeser and Guay (). Rather than repeat their points, I will focus on the importance of institutional knowledge for designing a good identification strategy.…”
Section: Broad‐ Versus Narrow‐sample Evidence In Disclosure Regulatiomentioning
confidence: 99%
See 3 more Smart Citations
“…BDJO and most recent literature on the effect of disclosure regulation use a difference‐in‐differences (DiD) approach. The challenges with the DiD approach are extensively discussed in the context of accounting disclosure studies by, among others, Leuz and Wysocki () and Glaeser and Guay (). Rather than repeat their points, I will focus on the importance of institutional knowledge for designing a good identification strategy.…”
Section: Broad‐ Versus Narrow‐sample Evidence In Disclosure Regulatiomentioning
confidence: 99%
“…Given how difficult it is to attain perfect identification in studies on disclosure regulation and that the key identification assumptions are often untestable, convincing evidence of causal relationships likely comes from multiple studies that collectively update our priors (Glaeser and Guay ). However, this Bayesian approach to research only works if the studies rely on different variation.…”
Section: Broad‐ Versus Narrow‐sample Evidence In Disclosure Regulatiomentioning
confidence: 99%
See 2 more Smart Citations
“…Put differently, there is a price that we pay for identification. Many studies on standard setting and financial market regulation that provide causal estimates do so in very specific settings and as a result, their estimates (or the magnitudes of their estimates) have limited generalisability (see also Wysocki 2016, Glaeser andGuay 2017). This limitation also arises with field experiments.…”
Section: Importance Of Causal Inferences and The Tradeoff Between Intmentioning
confidence: 99%