SearcharxivSearch

arXiv · 2605.22994

Grow and Pollute but Invest and Clean: Dynamic Associations between Parent Firm Characteristics and Facility Toxic Releases

Abstract

This paper examines how relationships between parent-firm characteristics and facility-level toxic releases evolve over time. Using 238,304 observations for 7,447 U.S. manufacturing facilities from 1992 to 2023, we link on-site releases from the Toxics Release Inventory to financial, managerial, and macroeconomic data. A time-varying mean-group estimator accommodates changes in average coefficients over time and heterogeneity across facilities. The main result is a persistent contrast between operating scale and investment-related adjustment: sales is positively associated with release growth, whereas investment intensity is negatively associated. This pattern remains in joint specifications, parsimonious models, and the main robustness exercises. Other financial and managerial associations are identified as well. These findings suggest that environmental policy evaluation may benefit from distinguishing release changes associated with production expansion from those associated with investment-related adjustment and from allowing for variation across periods and production settings. For corporate managers, the same distinction can inform how emissions considerations are incorporated into capital budgeting and production planning.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

George Kapetanios, Steven Ongena, Alexia Ventouri, Huiyan Xiao. 2026-05-21. Grow and Pollute but Invest and Clean: Dynamic Associations between Parent Firm Characteristics and Facility Toxic Releases. https://arxiv.org/abs/2605.22994

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

KEEP EXPLORING

Related papers

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

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

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