Headshot of Daniela Hochfellner

Pension Reforms and their Implications for Establishment Survivals

(Paper by Daniela Hochfellner, Peter Berg, Marissa Eckrote, Mary Hamman, Matthew Piszczek, and Christopher Ruhm)

Abstract: This paper adds to the overall empirical investigation of the effects of pension reform on employers. Using administrative data on establishments, we document that gradual increases in pensionable ages, introduced in a 1992 pension reform, had a high impact across establishments due to their pre-policy differences in worker age distributions. Using this variation as a source of identification, we examine whether establishments which experience different shifts in retirement eligibility patterns differ in their probability of survival. We model establishment closures and worker layoffs by estimating discrete time hazard models, including a shift-share approach to address potential endogeneity. Our results suggest that the share of older workers in an establishment is positively associated with layoffs in establishments. 

Headshot of Daniela Hochfellner

Daniela Hochfellner is a Research Assistant Professor at CUSP. She also is an Adjunct Research Assistant Professor at the Institute for Social Research, Survey Research Center at the University of Michigan.

For CUSP’s Data Facility, Daniela implements statistically grounded approaches to data integration, data use and dissemination of policies and procedures. She takes part in user support and quality assurance processes for data providers and data facility users. Her research addresses the economics of labor markets, migration, aging and health and ethics in human subject research. For instance, she has been studying the integration processes of immigrants. In addition, Daniela pursues research on labor market participation of older workers, and effects of social security reforms on retirement transition and health outcomes. Her work on research ethics addresses data confidentiality and methods of protecting privacy in the presence of an increasing demand of “big data” in social sciences.

She has worked with survey data, administrative data, and big-data and has a deep knowledge and extensive experience in linkages of social security records, administrative information and survey data. Daniela has been awarded funding for her research from the Alfred, P Sloan Foundation, the National Science Foundation and from the German Ministry of Education and Research.

Daniela Hochfellner received her PhD in Sociology from the University of Bamberg (in Germany). Prior to joining CUSP, Daniela was a Research Investigator at the Institute for Social Research, Survey Research Center at the University of Michigan. Daniela also was a Researcher at the Research Data Centre at the Institute for Employment Research in Nuremberg, Germany.