About

Erina Ytsma is an Assistant Professor of Accounting at the Tepper School of Business at Carnegie Mellon University. Her role involves teaching and research within the field of accounting, contributing to the academic community through her expertise. Further details about her specific research focus, background, or key contributions are not provided in the available page text.

Research topics

• Artificial Intelligence
• Computer Science
• Business
• Knowledge management

Selected publications

• Effort and Selection Effects of Performance Pay in Knowledge Creation

  SSRN Electronic Journal · 2022 · 3 citations

  1st authorCorresponding
  • Computer Science
  • Artificial Intelligence
  • Business
  PublisherDOI

• Do Women Respond Less to Performance Pay? Building Evidence from Multiple Experiments

  American Economic Review Insights · 2021-11-30 · 24 citations

  preprintOpen accessSenior author

  Existing empirical work raises the hypothesis that performance pay—whatever its output gains—may widen the gender earnings gap because women may respond less to incentives. We evaluate this possibility by aggregating evidence from existing experiments on performance incentives with male and female subjects. Using a Bayesian hierarchical model, we estimate both the average effect and heterogeneity across studies. We find that the gender response difference is close to zero and heterogeneity across studies is small, while performance pay increases output by 0.36 standard deviations on average. The data thus support agency theory for men and women alike. (JEL C11, C90, J16, J31, J33)

  PublisherOA PDFDOI

• Performance pay in academia: effort, selection and assortative matching

  London School of Economics and Political Science Theses Online (London School of Economics and Political Science) · 2015-08-01

  dissertationOpen access1st authorCorresponding

  This thesis studies the effect of performance pay on effort, selection and matching assortativeness in academia, using the introduction of performance pay in German academia as a natural experiment and employing a newly constructed data set encompassing the affiliations and productivity of the universe of academics in the country.
\nI estimate the pure effort effect in a difference-in-differences framework comparing the productivity of cohorts that started their first tenured position just before the reform, and consequently do not receive performance pay, with those starting their first tenured position after the reform, and therefore do receive performance pay. I find that the effort effect is economically large; amounting to a 35% increase in academic productivity relative to the pre-reform productivity in the control group.
\nI estimate the selection effect by analysing the rate at which academics of different productivity levels switch to the performance pay scheme and by exploiting the fact that the old and new wage scheme compare differently for academics at different ages, which gives rise to selection incentives that are inversely related to age. I find that more productive academics are more likely to select into performance pay, and that this effect is stronger for younger academics.
\nThe empirical framework to study matching assortativeness is informed by a simple matching model in which I show that performance pay increases positive assortative matching if there are positive productivity spillovers, and that this increase is larger if complementarities are stronger. I test this hypothesis in a difference-in-difference framework using a measure of complementarity strength as a continuous treatment variable and find that assortative matching increases more in fields with stronger complementarities, thus providing empirical evidence that performance related pay increases positive assortative matching. This effect is large; amounting to a two- to threefold increase in positive assortative matching.

  OA PDF

• Innovation in the Public Sector: Experiences in E-Procurement and University Research

  Innovation, technology and knowledge management · 2012-11-15

  book-chapterSenior author
  PublisherDOI

Frequent coauthors

• Oriana Bandiera

  6 shared

• Andrea Prat

  5 shared

• Greg Fischer

  3 shared