Unconditional Effects of General Policy Interventions

Julian Martinez-Iriarte; Gabriel Montes-Rojas; Yixiao Sun

Home/Archive/arXiv

arXiv · 2201.02292

Unconditional Effects of General Policy Interventions

Julian Martinez-Iriarte·Gabriel Montes-Rojas·Yixiao Sun

View original source ↗Read source document ↗Export metadata ↓

Abstract

This paper studies the unconditional effects of a general policy intervention, which includes location-scale shifts and simultaneous shifts as special cases. The location-scale shift is intended to study a counterfactual policy aimed at changing not only the mean or location of a covariate but also its dispersion or scale. The simultaneous shift refers to the situation where shifts in two or more covariates take place simultaneously. For example, a shift in one covariate is compensated at a certain rate by a shift in another covariate. Not accounting for these possible scale or simultaneous shifts will result in an incorrect assessment of the potential policy effects on an outcome variable of interest. The unconditional policy parameters are estimated with simple semiparametric estimators, for which asymptotic properties are studied. Monte Carlo simulations are implemented to study their finite sample performances. The proposed approach is applied to a Mincer equation to study the effects of changing years of education on wages and to study the effect of smoking during pregnancy on birth weight.

Explore related subjects

econ.EM

Keep this discovery

BibTeX RIS

Julian Martinez-Iriarte, Gabriel Montes-Rojas, Yixiao Sun. 2022-01-07. Unconditional Effects of General Policy Interventions. https://arxiv.org/abs/2201.02292

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

arXiv2026

Identification in Linear Quantile Panel Models

This paper studies identification in linear quantile panel models with unrestricted individual heterogeneity when the number of time periods is fixed and small. We impose strict exogeneity, whereby the conditional quantile restriction holds given the individual's complete regressor history and latent individual effect, but otherwise allow the disturbances to be arbitrarily dependent over time.

econ.EM↗

arXiv2026

Experimental Design for Policy Choice

We show how to optimally design experiments when the resulting data will be used to choose a welfare-maximizing policy subject to constraints. A decision maker seeks to maximize Bayes expected welfare by choosing a policy whose effects depend on an unknown finite-dimensional parameter. The decision maker has access to a first wave of experimental data with a fixed design but may choose the design of a second wave that will be collected before choosing the policy. The resulting experimental design--policy choice problem is a very high-dimensional dynamic program that is generally intractable in finite samples. We propose a tractable approximation based on the limit experiment and show it is asymptotically optimal using a new asymptotic representation theorem for adaptive experiments with continuous treatments. We apply the method to a conditional cash transfer experiment and demonstrate the potential for large gains from tailoring the experiment to the policy choice.

econ.EM↗

arXiv2026

Designing Spatial Treatments

Spatial treatments are interventions assigned to locations potentially distinct from those of the responding units. We study their optimal design under a general model in which a unit's response diminishes with distance to a treated site. Our estimand of interest is an ``uncontaminated'' effect equal to the average impact of a single intervention site over all hypothetical sites. We propose a novel design based on a Mat\'{e}rn point process which separates treatments by a distance of at least $r$. A larger choice of $r$ reduces bias by separating interventions but increases variance by reducing their numerosity. We choose $r$ to maximize the rate of convergence of a Horvitz-Thompson estimator and prove that this is minimax rate-optimal. We provide weak conditions under which the estimator is asymptotically normal and propose a variance estimator.

econ.EM↗