Gulyas, Andreas - Ass.-Prof.

The Role of Wages and Benefits in Job Search

23 June 2026
3:00 - 3:30 PM Lecture Hall 6
Faculty of Business, Economics and Statistics

This paper studies how wages and job benefits influence job seekers using a large-scale field experiment. We provide users of 112 Swiss job boards with additional information about wages and benefits for the jobs they viewed. This allowes us to estimate how sensitive applications are to wages and to measure willingness to pay for 12 job benefits.
A complementary survey experiment captured job seekers’ beliefs before and after receiving this information.
The results show that a 1% increase in posted wages raises the likelihood of viewing and applying by 0.5%.
Accounting for partial updating of expectations, we find the true wage elasticity is about 3, indicating job seekers are fairly well informed about wage differences.
Four benefits—home office, company car, and childcare—are especially valued, and since higher-paying firms offer more benefits, overall job-value inequality exceeds wage inequality.

TIERNEY, Kevin - Universitätsprofessor

Is the future of Operations Research Large Language Models?“

23 June 2026
3:30 - 4:00 PM Lecture Hall 6
Faculty of Business, Economics and Statistics

The operations research (OR) community has long sought to make writing heuristics to solve optimization problems faster and easier through established paradigms, freely available frameworks, and automated parameter tuning. OR specialists play a decisive role in this process: they experiment with different heuristics and metaheuristics, implement them, and examine their efficacy. This process is time‑consuming, requiring weeks or even months to develop methods for large‑scale optimization problems. Automated heuristic‑discovery techniques based on large language models (LLMs) are fundamentally changing how OR specialists develop heuristics. These techniques can create heuristics for optimization problems that rival state‑of‑the‑art OR methods in solution quality within just a few days, requiring only limited human input. This talk will show my group’s work on creating methods for automated heuristic discovery and discuss how LLMs can solve real-world decision problems. Finally, the talk will examine how the field of OR will evolve in the near future with the rise of LLMs.