arXiv subjects

Christophe Bruneel-Zupanc

Publications and source records attributed to Christophe Bruneel-Zupanc.

3 recordsLinked to original sources

arXiv2025

Don't (fully) exclude me, it's not necessary! Causal inference with semi-IVs

This paper proposes semi-instrumental variables (semi-IVs) as an alternative to instrumental variables (IVs) to identify the causal effect of a binary (or discrete) endogenous treatment. A semi-IV is a less restrictive form of instrument: it affects the selection into treatment but is excluded only from one, not necessarily both, potential outcomes. Having two continuously distributed semi-IVs, one excluded from the potential outcome under treatment and the other from the potential outcome under control, is sufficient to nonparametrically point identify marginal treatment effect (MTE) and local average treatment effect (LATE) parameters. In practice, semi-IVs provide a solution to the challenge of finding valid IVs because they are often easier to find: many selection-specific shocks, policies, prices, costs, or benefits are valid semi-IVs. As an application, I estimate the returns to working in the manufacturing sector on earnings using sector-specific characteristics as semi-IVs.

econ.EM↗

arXiv2025

Dynamic Discrete-Continuous Choice Models: Identification and Conditional Choice Probability Estimation

This paper develops a general framework for dynamic models in which individuals simultaneously make both discrete and continuous choices. The framework incorporates a wide range of unobserved heterogeneity. I show that such models are nonparametrically identified. Based on constructive identification arguments, I build a novel two-step estimation method in the lineage of Hotz and Miller (1993) and Arcidiacono and Miller (2011) but extended to simultaneous discrete-continuous choice. In the first step, I recover the (type-dependent) optimal choices with an expectation-maximization algorithm and instrumental variable quantile regression. In the second step, I estimate the primitives of the model taking the estimated optimal choices as given. The method is especially attractive for complex dynamic models because it significantly reduces the computational burden associated with their estimation compared to alternative full solution methods.

econ.EM↗

arXiv2024

Identification with possibly invalid IVs

This paper proposes a novel identification strategy relying on quasi-instrumental variables (quasi-IVs). A quasi-IV is a relevant but possibly invalid IV because it is not exogenous or not excluded. We show that a variety of models with discrete or continuous endogenous treatment which are usually identified with an IV - quantile models with rank invariance, additive models with homogenous treatment effects, and local average treatment effect models - can be identified under the joint relevance of two complementary quasi-IVs instead. To achieve identification, we complement one excluded but possibly endogenous quasi-IV (e.g., "relevant proxies" such as lagged treatment choice) with one exogenous (conditional on the excluded quasi-IV) but possibly included quasi-IV (e.g., random assignment or exogenous market shocks). Our approach also holds if any of the two quasi-IVs turns out to be a valid IV. In practice, being able to address endogeneity with complementary quasi-IVs instead of IVs is convenient since there are many applications where quasi-IVs are more readily available. Difference-in-differences is a notable example: time is an exogenous quasi-IV while the group assignment acts as a complementary excluded quasi-IV.

econ.EM↗