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Santiago Acerenza

Publications and source records attributed to Santiago Acerenza.

7 recordsLinked to original sources

Sharp bounds for within-household encouragement designs with interference

Experiments with spillovers create incentives for strategic behavior: when one household member's treatment can affect another, take-up decisions become interdependent. We propose an instrumental-variables framework grounded in game theory, in which take-up is a Nash equilibrium among a small number of agents, and all variables are discrete. Under minimal assumptions, without specifying how equilibria are selected, we derive sharp non-parametric bounds for direct, indirect, offer-mediated, and policy-targeting effects. Game-theoretic restrictions such as supermodularity, symmetry, and dominance can be layered on via a tractable linear program, and we characterize when each does or does not tighten the identified set. We illustrate the usefulness of our approach to study household experiments by reanalyzing a banking intervention in Kenya.

econ.EM↗

Stochastic Frontier meets Breakdown Frontier

This paper studies sensitivity analysis in stochastic frontier models by developing relaxations of the baseline assumptions imposed on the latent inefficiency and noise components, and characterize bounds for a benchmark technical-efficiency object under such relaxations. We then derive the associated breakdown frontier for conclusions about conditional technical efficiency and illustrate the procedure using a well-known dataset. We show the estimation and inference of the breakdown frontier. We also extend the analysis for widely used alternative specifications of the stochastic frontier error structure, that is, the Normal-Truncated Normal, Normal-Exponential, and Normal-Half Normal cases. Finally, we suggest avenues for extending this analysis under heteroskedasticity, the relaxation of input exogeneity, and applications using panel data. Code for empirical implementation is also provided.

econ.EM↗

Local Average and Marginal Treatment Effects with a Misclassified Treatment

This paper studies identification of the local average and marginal treatment effects (LATE and MTE) with a misclassified binary treatment variable. We derive bounds on the (generalized) LATE and exploit its relationship with the MTE to further bound the MTE. Indeed, under some standard assumptions, the MTE is a limit of the ratio of the variation in the conditional expectation of the observed outcome given the instrument to the variation in the true propensity score, which is partially identified. We characterize the identified set for the propensity score, and then for the MTE. We show that our LATE bounds are tighter than the existing bounds and that the sign of the MTE is locally identified under some mild regularity conditions. We use our MTE bounds to derive bounds on other commonly used parameters in the literature such as the policy relevant treatment parameter (PRTE) and illustrate the practical relevance of our derived bounds through numerical and empirical results.

econ.EM↗

Was Javert right to be suspicious? Marginal Treatment Effects with Duration Outcomes

We identify the distributional and quantile marginal treatment effect functions when the outcome is right-censored. Our method requires a conditionally exogenous instrument and random censoring. We propose asymptotically consistent semi-parametric estimators and valid inferential procedures for the target functions. To illustrate, we evaluate the effect of alternative sentences (fines and community service vs. no punishment) on recidivism in Brazil. Our results highlight substantial treatment effect heterogeneity: we find that people whom most judges would punish take longer to recidivate, while people who would be punished only by strict judges recidivate at an earlier date than if they were not punished.

econ.EM↗

The Markup falsification Adaptative Set

In this paper we provide a constructive way for researchers to salvage the classic De Loecker and Warzynski (2012) markup recovery procedure when falsified. To do this, we consider continuous relaxations of the standard assumptions behind markup estimation. By computing the values of the markup as a function of the relaxations across the set of non-falsified models, we obtain an identified set for the markup which generalizes the standard baseline markup estimand to account for possible falsification without the need to impose additional assumptions. We illustrate our results using Chilean data from Raval (2023).

econ.EM↗

Testing identifying assumptions in Tobit Models

We develop sharp, testable implications for the identifying assumptions of Tobit and IV-Tobit models: linear index, (joint) normality of errors, treatment (instrument) exogeneity, and relevance. The new sharp testable equalities can detect all possible observable violations of the identifying conditions. The proposed test procedure for the model's validity uses existing inference methods for intersection bounds. Simulations suggest adequate test size and power in detecting exogeneity and error structure violations. We review and propose alternatives to partially identify the parameters of interest under less restrictive assumptions. We revisit a study of married women's labor supply in Lee (1995) to demonstrate the test's practical implementation.

econ.EM↗

Partial Identification of Marginal Treatment Effects with discrete instruments and misreported treatment

This paper provides partial identification results for the marginal treatment effect ($MTE$) when the binary treatment variable is potentially misreported and the instrumental variable is discrete. Identification results are derived under different sets of nonparametric assumptions. The identification results are illustrated in identifying the marginal treatment effects of food stamps on health.

econ.EM↗