Paul Huebner - Stockholm School of Economics

Abstract

This paper provides a guide for using causal inference with asset prices and quantities. Our framework revolves around an elementary assumption about portfolio demand: homogeneous substitution conditional on observables. Under this assumption, standard cross-sectional instrumental variables or difference-in-differences regressions identify the relative demand elasticity between assets with the same observables, the difference between own-price and cross-price elasticity. However, we uncover a missing coefficient problem: cross-sectional estimators mechanically absorb substitution patterns across assets. Recovering substitution is essential to answer many natural counterfactual questions, and requires analyzing the response of portfolios to exogenous time-series variation. The same principles apply to the estimation of multipliers measuring the price impact of supply or demand shocks. Our assumption maps to familiar restrictions on covariance matrices in classical asset pricing models, encompasses demand models such as logit, and accommodates rich substitution patterns even outside of these models. We discuss how to design experiments satisfying this condition and offer diagnostics to validate it.

Additional information:

• Speaker: Paul Huebner 
• Time: Wednesday, 22.04.2026, 14:45 - 16:00
• Location: Faculty Lounge, Room 0.036
• Further links:
  • Paul Huebner's webpage
• Organizer: Finance Group
• Contact:
  • Almut Lunkenheimer
  • +49 228 73-9228
  • ifs@uni-bonn.de