Digital State Capacity

Patrick Healy, Simon D. Angus, Paul Raschky, Klaus Ackermann, Nathan Lane, Weijia Li and Cynthia Huang
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Patrick Healy: Department of Economics, Monash Business School, Monash University
Simon D. Angus: Department of Economics, Monash Business School, Monash University
Paul Raschky: Department of Econometrics and Business Statistics, Monash Business School, Monash University
Klaus Ackermann: Department of Economics, Monash Business School, Monash University
Nathan Lane: SoDa Laboratories, Monash Business School, Monash University
Weijia Li: Department of Econometrics and Business Statistics, Monash Business School, Monash University
Cynthia Huang: SoDa Laboratories, Monash Business School, Monash University

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Abstract: Digital State Capacity is the ability of governments to deploy ICT infrastructure and information systems to implement policy. This paper introduces a new measure of government ICT capacity based on an observable stock of deployable public-sector network infrastructure: public IPv4 address space held by government organisations. These address holdings are key inputs into digital administration because they support internet-facing systems, networked information exchange, and coordination across agencies and functions. The core panel covers approximately 150,000 country-entity records classified as government across more than 150 countries from 2019 to 2024 and can be disaggregated by administrative level and government function. In the 2019 to 2024 Admin-1 panel, government IP holdings are observed in 1,681 subnational regions across all years. We validate the measure at the crosscountry and subnational levels and apply it to government tasks related to corruption control and vaccination rollout. In illustrative country-year analysis, higher Digital State Capacity is associated with higher-quality governance and publicservice outcomes in the expected directions, including lower measured corruption and higher vaccination coverage. These associations are descriptive; they demonstrate the empirical relevance of the measure and are not causal estimates.

Date: 2026-08
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