Research
Work in progress
- A Random-Effects Model Reveals Strong Positive Sorting in CEO Labor Markets (with Miklós Koren, Krisztina Orbán, and Álmos Telegdy), DOI
Abstract
If markets allocate CEOs efficiently across firms, better managers should sort into better firms. The correlation between firm and manager quality is therefore central to understanding misallocation and aggregate productivity. Because manager quality is unobserved, the standard empirical strategy from matched worker-firm data is to estimate latent firm and worker effects and ask whether higher-quality workers sort to higher-quality firms. In CEO labor markets, however, careers are short and mobility is sparse, so fixed-effects estimates of latent quality are noisy and their implied correlation is badly biased. We instead model firm and manager effects as a Gaussian Markov random field on the bipartite CEO–firm network. Estimating four distributional parameters—rather than hundreds of thousands of individual effects—avoids limited mobility bias, while the sparsity of the precision matrix makes likelihood-based estimation feasible on the full network. Applied to Hungarian administrative data from 1990 to 2018, the model yields strong positive assortative matching (rho = 0.7). By contrast, two-way fixed effects on the same data imply rho = -0.6, and leave-one-out bias correction reduces the magnitude but does not resolve the discrepancy. In a model-based counterfactual, perfect sorting (rho = 1) would raise aggregate output by about 6%.
- The Directions of Technical Change (with Miklós Koren, and Zsófia Bárány), DOI
Abstract
Generative AI is directional: it performs well in some task directions and poorly in others. Knowledge work is directional and endogenous as well: workers can satisfy the same job requirements with different mixes of tasks. We develop a high-dimensional model of AI adoption in which a worker uses a tool when it raises their output. Both the worker and the AI tool can perform a variety of tasks, which we model as convex production possibility sets. Because the tool requires supervision from the worker’s own time and attention budget, adoption is a team-production decision, similar to hiring a coworker. The key sufficient statistics are the worker’s pre-AI shadow prices: these equal the output gain from a small relaxation in each task direction, and they generally differ from the worker’s observed activity mix. As AI capability improves, the set of adopted directions expands in a cone centered on these autarky prices. Near the entry threshold, small capability improvements generate large extensive-margin expansions in adoption. The model also delivers a structured intensive margin: between the entry and all-in thresholds, optimal use is partial. We parametrize the model in a simple but flexible way that nests most existing task-based models of technical change.
- The Inflation Reduction Act: Short-Term Industry Dynamics and Local Impacts
Abstract
This paper studies the short-run effects of the Inflation Reduction Act on firm behavior and the geography of clean-energy investment in the United States. Using firm-level product descriptions and tract-level investment data, I show that fossil-fuel firms have become more similar to renewable-energy firms since 2022. I further find that Energy Community designation increased local clean-energy capital expenditure by 7–8 percent, with the largest responses in hydrogen, electrolyzers, and critical minerals.
- Attention in Procurement (with Miklós Koren, Sergey Lychagin, and Adam Szeidl)
- Causal Random Deforestation: A Global REDD+ Evaluation (with Lucas Konrad, Lukas Vashold, and Nikolas Kuschnig)
Peer-reviewed publications
Evaluating Tampon Tax Reforms using Transaction Based Scanner Data (2025) (with Klara Kinnl), Journal of Economic Behavior & Organization. DOI
- A preliminary version of this paper was presented at the European Parliament’s FEMM committee workshop on 08/12/2022.
Abstract
We study price and volume effects of value-added tax (VAT) reductions for period products. We exploit varying treatment intensities and timing in several European countries and find that prices decrease by 10–13 %. This corresponds to full pass-through 12 months after the VAT reduction. The average effect on aggregate purchase volumes is statistically zero, and we find no evidence that low-income households are disproportionately affected by the reforms. We find homogeneous pass-through for market- and product-level competition measures and provide suggestive evidence that households’ propensity to purchase branded products increases in the months after the tax reform.
Start-up acquisitions, venture capital and innovation: A comparative study of Google, Apple, Facebook, Amazon and Microsoft (2025) Wohak, U., Gugler, K., Szücs, F.. International Journal of Industrial Organization. DOI
Abstract
We evaluate the impact of big-tech acquisitions on the incentives for venture capital (VC) investment and innovation. Using data on several hundred acquisitions by Google, Apple, Facebook, Amazon and Microsoft (GAFAM), we study the evolution of VC investment and patenting in affected technology fields relative to control groups. The results show a clear negative impact on VC investment, while the effect on innovation depends on the acquirer and period. Over time, the treatment effects on both outcomes improve, as GAFAM firms' product and tech-portfolios become more similar. Yet, around 14% of acquisitions impact both metrics negatively.
Using Natural Language Processing to Delineate Digital Markets (2024) Wohak, U., Gugler, K., Szücs, F.. Stanford Computational Antitrust. Link (PDF)
Abstract
Delineating relevant antitrust markets poses substantial challenges, particularly so in nascent, digital markets, where data on prices, quantities, and costs often are not available. This study evaluates a complementary approach using Natural Language Processing techniques along with business descriptions of relevant firms to define markets. Applying this method to a sample of start-up acquisitions, we find considerable overlap between our approach and expert assessments by the European Commission.