Jaume Vives-i-Bastida

Synthetic IV estimation in panels with Ahmet Gulek

Co-winner of the Best Student Paper Award of the International Applied Econometrics Association (2024)

Abstract 

We propose a Synthetic Instrumental Variables (SIV) estimator for panel data that combines the strengths of instrumental variables and synthetic controls to address unmeasured confounding. We derive conditions under which SIV is consistent and asymptotically normal, even when the standard IV estimator is not. Motivated by the finite sample properties of our estimator, we introduce an ensemble estimator that simultaneously addresses multiple sources of bias and provide a permutation-based inference procedure. We demonstrate the effectiveness of our methods through a calibrated simulation exercise, two shift-share empirical applications, and an application in digital economics that includes both observational data and data from a randomized control trial. In our primary empirical application, we examine the impact of the Syrian refugee crisis on Turkish labor markets. Here, the SIV estimator reveals significant effects that the standard IV does not capture. Similarly, in our digital economics application, the SIV estimator successfully recovers the experimental estimates, whereas the standard IV does not.

Stretching the Net: Multidimensional Regularization (Econometric Theory, 2023)

Synthetic Controls in Action with Alberto Abadie (Econometric Society Monographs, forthcoming)

Bayesian and Frequentist Inference for Synthetic Controls with Ignacio Martinez

Predictor Selection for Synthetic Controls (revise and resubmit at Journal of Econometrics) 

Bagged Polynomial Regression and Neural Networks with Sylvia Klosin 

Synthetic Experimental Design for a UBI Pilot Study [Policy Technical Report: Ivalua]

The Effects of Regulating Food Delivery Platform Design with Alejandro Sabal

Abstract: There is rising interest amongst regulators in understanding how different platform design choices affect welfare. In this project we focus on two important mechanisms platforms have at their disposal: (1) offering preferential treatment to producers in consumer search and (2) determining producer payments (commission fees). We study the welfare implications of different platform choices in the empirical setting of a food delivery platform that bargains with producers to set commission fees and to adjudicate fixed ranking slots in the consumer search wall. Using transaction level data and click stream search data from a large food delivery platform, we show that both mechanisms are important in practice. Producers with low commission fees are preferred by consumers, and low commission fees are used to attract valuable “anchor” producers that drive consumers into the platform. Search preferencing is also important. Using an A/B test in which rank was randomized we show that search rank is a driver of consumption. To evaluate the impact of different platform designs on consumer and restaurant welfare, we develop a structural model featuring a consumer demand with search frictions, bargaining between restaurants and the platform over ranks and commission fees, and restaurant and consumer entry into the platform. Using the model, we compute counterfactual experiments to assess the impact of regulations forbidding platforms from providing preferential rank to larger restaurants and from setting differential commission fees across restaurants.

Pushing Back Against Private Practice: the Spanish Physician Public Exclusivity Bonus with Jon Gruber, Nuria Mas and Judit Vall

Draft coming soon!