Non-representative sampled networks: Estimation of network structural properties by weighting

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23330%2F24%3A43971884" target="_blank" >RIV/49777513:23330/24:43971884 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S0304407624000356" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0304407624000356</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.jeconom.2024.105689" target="_blank" >10.1016/j.jeconom.2024.105689</a>

Result language

angličtina

Original language name

Non-representative sampled networks: Estimation of network structural properties by weighting

Original language description

This paper analyzes statistical issues arising from non-representative samples of a network. Sampled network data could systematically bias the network properties and generate non-classical measurement error problems. Apart from the sampling rate and the elicitation procedure, the biases on network structural measures depend non-trivially on which subpopulations of nodes are missing with higher probability. We propose a methodology, adapting weighted estimators to networked contexts, which enables researchers to recover several network-level statistics and reduce the biases in the estimated network effects. The proposed weighted estimators are consistent and asymptotically normally distributed and have good performance in finite samples. Notably, our approach does not require users to assume any network formation model and is straightforward to implement.

Czech name

—

Czech description

—

Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

50401 - Sociology

Project

<a href="/en/project/GA21-22796S" target="_blank" >GA21-22796S: Network diffusion and social cohesion: the role of the clustering coefficient</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Journal of Econometrics

ISSN

0304-4076

e-ISSN

1872-6895

Volume of the periodical

240

Issue of the periodical within the volume

1

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

20

Pages from-to

1-20

UT code for WoS article

001181492300001

EID of the result in the Scopus database

2-s2.0-85185460966