Diego
Aparicio

Assistant Professor of Marketing

• Ph.D. in Economics, Massachusetts Institute of Technology

Diego Aparicio is an Assistant Professor in the Marketing Department at IESE Business School. He teaches Marketing Management in the MBA Program.

His research studies optimal pricing and assortment decisions, online platforms, retailing, and applied topics in corporate finance. Prior to joining IESE, he worked in the finance and technology industries.

His research has been featured at the NBER, The Economist, Bloomberg, and the BLS, among others.

Areas of interest.

• Pricing
• Economics of Digitization
• Artificial Intelligence
• Lab Experiments
• Industrial Organization

Publications

Journal Articles (refereed)

APARICIO, D., METZMAN, Z., RIGOBON, R. (2024). The pricing strategies of online grocery retailers. QME-Quantitative Marketing and Economics, 22 (1), 1–21, doi:10.1007/s11129-023-09273-w. APARICIO, D., RIGOBON, R. (2023). Quantum prices. Journal of International Economics, 143, Article 103770. doi:10.1016/j.jinteco.2023.103770. APARICIO, D., SIMESTER, D. (2022). Price frictions and the success of new products. Marketing Science, 41 (6), 1029-1182, ii. doi:10.1287/mksc.2022.1367. APARICIO, D., AVENANCIO-LEÓN, C. F. (2022). Is banning corporate contributions enough?. The Dynamics of incomplete campaign finance reform. The Journal of Law and Economics, 65 (3), 581-606. doi:10.1086/718973. APARICIO, D., CAVALLO, A. (2021). Targeted price controls on supermarket products. The Review of Economics and Statistics, 103 (1), 60-71. doi:10.1162/rest_a_00880. APARICIO, D., BERTOLOTTO, M. I. (2020). Forecasting inflation with online prices. International Journal of Forecasting, 36 (2), 232-247. doi:10.1016/j.ijforecast.2019.04.018. APARICIO, D., LOPEZ DE PRADO, M. (2018). How hard is it to pick the right model?. MCS and backtest overfitting. Algorithmic Finance, 7 (1-2), 53-61. doi:10.3233/AF-180231. APARICIO, D., FRAIMAN, D. (2015). Banking networks and leverage dependence in emerging countries. Advances in Complex Systems, 18 (7 n8). doi:10.1142/S0219525915500228.

Working Papers

SPANN, M., BERTINI, M., KOENIGSBERG, O., ZEITHAMMER, R., APARICIO, D., CHEN , Y., FANTINI, F., JIN, G., MORWITZ, V., LESZCZYC, P., ... VITORINO, M. (2024). Algorithmic pricing. Implications for consumers, managers, and regulators (No. w32540). Cambridge, MA: National Bureau of Economic Research. APARICIO, D., ECKLES, D., KUMAR, M. (2023). Algorithmic pricing and consumer sensitivity to price variability. MARTÍNEZ DE ALBÉNIZ, V., APARICIO, D., BALSACH, J. (2022). The Effects of COVID-19 on the Retail Economy: Store Restrictions, Consumer Panic, and Travel Shocks.

Proceedings

LADA, A., PEYSAKHOVICH, A., APARICIO, D., BAILEY, M. (2019). Observational data for heterogeneous treatment effects with application to recommender systems. EC '19: Proceedings of the 2019 ACM Conference on Economics and Computation (pp. 199-213). New York, NY: Association for Computing Machinery.

Articles in other publications

BERTINI, M., APARICIO, D., AYDINLI, A. (2023). Can friction improve your customers' experiences? MIT Sloan Management Review, 64 (2), 42-47.

Book Chapters

APARICIO, D., MISRA, K. (2022). Artificial intelligence and pricing. In Sudhir, K. and Toubia, O. (Eds.), Artificial intelligence in marketing (pp. 103-124). Bingley: Emerald Publishing Limited.