caa a22 4500 445877839 CHVBK 20180317145533.0 cr unu---uuuuu 170323e20110901xx s 000 0 eng 10.1007/s11187-009-9240-4 doi (NATIONALLICENCE)springer-10.1007/s11187-009-9240-4 Small business survival and sample selection bias [Elektronische Daten] [Hanas Cader, John Leatherman] Analyses of small business and the factors affecting their survival are fairly common in the research literature. The level of research interest may stem from the fact that in the US, only about half of all new small businesses survive after 4years (Headd 2003). However, research attempting to understand the phenomenon that employs data using only information from and about surviving firms may lead to erroneous conclusions regarding the factors that influence firm survival and failure. In this paper, we provide evidence that omitted information about the firms that disappear from the research data over time leads to biased coefficient estimates. Comparing the Heckman two-step estimation approach of switching regression models to a semi-parametric Cox hazard model, the Accelerated Failure Time (AFT) model, we conclude that the Cox ATF approach is the most appropriate model for firm survival analysis. Springer Science+Business Media, LLC., 2009 Firm survival nationallicence Omitted observation nationallicence Selection bias nationallicence Two-stage estimation nationallicence Cader Hanas American University of Kuwait, Safat, Kuwait aut Leatherman John Kansas State University, Manhattan, KS, USA aut Small Business Economics Springer US; http://www.springer-ny.com 37/2(2011-09-01), 155-165 0921-898X 37:2<155 2011 37 11187 https://doi.org/10.1007/s11187-009-9240-4 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s11187-009-9240-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Cader Hanas American University of Kuwait, Safat, Kuwait aut NATIONALLICENCE 700 1- Leatherman John Kansas State University, Manhattan, KS, USA aut NATIONALLICENCE 773 0- Small Business Economics Springer US; http://www.springer-ny.com 37/2(2011-09-01), 155-165 0921-898X 37:2<155 2011 37 11187 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer