Electronic copy available at: http://ssrn.com/abstract=2186126 1 GREAT PLACES TO WORK ® : RESILIENCE IN TIMES OF CRISIS Ana Carvalho (corresponding author) University of Minho Economics and Management School 4710-057 Braga Portugal Tel: +351 253604510 Fax: +351 253601380 Email: anac@eeg.uminho.pt Nelson Areal University of Minho Economics and Management School 4710-057 Braga Portugal Tel: +351 253604510 Fax: +351 253601380 Email: nareal@eeg.uminho.pt Abstract We study the resilience of the “100 Best Companies to Work for in America” in times of financial crises by analyzing their long-term financial performance. Apart from implementing methods that tackle the statistical problems of stock returns, we use a conditional model to measure financial performance in periods of market growth (‘bull’ markets) and market downturn (‘bear’ markets). Our results sustain the proposition that ‘best companies to work for’ are resilient in times of crisis since neither their financial performance nor their systematic risk are affected during bear markets: top companies continue to outperform the market during periods of crises, and the performance of lower-ranked great workplaces does not deteriorate. Moreover, we find that previous studies were overestimating performance, and only great workplaces on the top half of the rankings exhibit positive excessive returns. We conclude that, in general, this award has an impact on these firms’ reputations that allows investors to acknowledge the value of outstanding employee relations and correctly incorporate it into stock prices. They fail to do so for the top ranking companies, however, reinforcing the notion that outstanding people management entails intrinsic benefits with financial value that are difficult to discern due to its intangible nature. Keywords: ‘best-practice’ HRM, best employer awards, financial performance; bull and bear markets; conditional models. Aknowledgements: The research for this paper is financed by the Portuguese Foundation for Science & Technology (Fundação para a Ciência e Tecnologia – FCT) under project PTDC/EGE-GES/121377/2010. We are indebted to Prof. Chris Brewster (University of Reading, UK) and Prof. Chris Adcock (University of Sheffield, UK), for their comments on earlier versions of this paper. We also acknowledge the contribution of the participants of the 2012 IFSAM Congress and the 2012 PFN Conference.