Tales Left Tails Tell: Addressing Left-Side Truncation in Strategy Research

Richard Hunt () and Daniel Lerner
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Daniel Lerner: Deusto Business School, Universidad Deusto

No 2017-04, Working Papers from Colorado School of Mines, Division of Economics and Business

Abstract: This study takes up the issue of left-side truncation (LST) in strategy research. Since reliable data on early-stage and failed firms are often unavailable for analysis, empirical findings are often derived from observations involving survivors. But, what if the missing data bear little resemblance to that which is available? Leveraging a dataset that comprehensively captures an entire industry, including firms that commonly pass unobserved, we demonstrate how LST materially affects empirical results and theoretical acuity. Our analysis suggests that the tools typically used to address LST have flaws that hinder their applicability to many of key questions posed by strategy scholars. In response, and to facilitate more thorough reporting of truncation effects, we present an effective, easy-to-use Truncation Factor.

Keywords: Missing data; Left-side truncation; Research methods; Strategic management; Entrepreneurship; Truncation factor; Non-ignorable data; Statistics (search for similar items in EconPapers)
Pages: 24 pages
Date: 2017-10
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http://econbus-papers.mines.edu/working-papers/wp201704.pdf First version, 2017 (application/pdf)

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Persistent link: https://EconPapers.repec.org/RePEc:mns:wpaper:wp201704

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