Research

Publications

1. Mismatch in the 21st Century: An Overview

   Luca Coraggio, Monica Langella, Armando Miano, Marco Pagano, Marco Stenborg Petterson, Vincenzo Pezone, and Annalisa Scognamiglio

   Labour Economics, 2026

   PDF HTML

   2026
2. Bounds on a slope from size restrictions on economic shocks

   Marco Stenborg Petterson, David Seim, and Jesse M. Shapiro

   American Economic Journal: Microeconomics, 2023

   Abstract PDF PYTHON PACKAGE APPENDIX REPLICATION PACKAGE HTML

   We study the problem of learning about the effect of one market-level variable (e.g., price) on another (e.g., quantity) in the presence of shocks to unobservables (e.g., preferences). We show that economic intuitions about the plausible size of the shocks can be informative about the parameter of interest. We illustrate with a main application to the grain market

   2023

Working Papers

1. Exchange-Rate Regimes and the Behaviour of Exporters

   Cosimo Petracchi, Luca Riva, and Marco Stenborg Petterson

   CSEF Working Paper 789, 2026

   PDF

   2026
2. Unemployment Insurance and Choice of Job Risk

   Marco Pagano, Luca Picariello, Marco Stenborg Petterson, and Valeria Zurla

   Working Paper, 2026

   2026
3. Estimation of a Latent Reference Point: Method and Application to NYC Taxi Drivers

   Marco Stenborg Petterson

   CSEF Working Paper 706, 2024

   Abstract PDF

   I use a dynamic discrete choice model with a latent variable to flexibly estimate reference- dependent utility models. The structure and evolution of the reference point are estimated directly from observational data. I apply the model to the daily labor-supply choices of NYC taxi drivers and use a Bayesian estimation approach. I find that rational expectations are an important determinant of the reference point but do not fully explain its evolution. The refer- ence point adjusts asymmetrically, responding more to positive income shocks than to negative ones. The reference point also has an important transitory component: a shock to the reference point dissipates within hours.

   2024
4. Bayesian Nonparametric Models For Conditional Densities Based On Orthogonal Polynomials

   Andriy Norets, and Marco Stenborg Petterson

   Draft available upon request, 2024

   Abstract Poster

   The paper considers a nonparametric Bayesian model for conditional densities. The model considered is a mixture of orthogonal polynomials with a prior on the number of components. The use of orthogonal polynomials allows for a great deal of flexibility in applications while maintaining useful approximation properties. We provide the posterior contraction rate in the case of Legendre polynomials. The algorithm proposed allows for cross-dimensional moves, allowing it to choose the optimal number of terms in the series expansion conditional on a penalty parameter. We also provide Monte Carlo simulations that show how well the model approximates known distributions also in finite sample situations.

   2024

Selected Work in Progress

1. Inferring a Preference from Stochastic Choice Data

   Geoffroy de Clippel, Toru Kitagawa, Marco Stenborg Petterson, and Kareen Rozen
2. Staffing Courts, Judges’ Preferences, and Judicial Efficiency

   Monica Langella, Marco Nieddu, Lorenzo Pandolfi, and Marco Stenborg Petterson