Estimating Spillovers from Sampled Connections

Fuente: arXiv
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Main Author: Marray, Kieran
Format: Preprint
Published: 2024
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author Marray, Kieran
author_facet Marray, Kieran
contents Empirical researchers often estimate spillover effects by fitting linear or non-linear regression models to sampled network data. We show that common sampling schemes bias these estimates, potentially upwards, and derive biased-corrected estimators that researchers can construct from aggregate network statistics. Our results apply under different assumptions on the relationship between observed and unobserved links, allow researchers to bound true effect sizes, and to determine robustness to mismeasured links. As an application, we estimate the propagation of climate shocks between U.S. public firms from self-reported supply links, building a new dataset of county-level incidence of large climate shocks.
format Preprint
id arxiv_https___arxiv_org_abs_2410_17154
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Estimating Spillovers from Sampled Connections
Marray, Kieran
General Economics
Economics
Empirical researchers often estimate spillover effects by fitting linear or non-linear regression models to sampled network data. We show that common sampling schemes bias these estimates, potentially upwards, and derive biased-corrected estimators that researchers can construct from aggregate network statistics. Our results apply under different assumptions on the relationship between observed and unobserved links, allow researchers to bound true effect sizes, and to determine robustness to mismeasured links. As an application, we estimate the propagation of climate shocks between U.S. public firms from self-reported supply links, building a new dataset of county-level incidence of large climate shocks.
title Estimating Spillovers from Sampled Connections
topic General Economics
Economics
url https://arxiv.org/abs/2410.17154