## insea2023003

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---

### Scope of GovTech
- Definition and goals:
  - GovTech: use of technology to modernize and transform government operations, decision-making, and service delivery to improve government services, transparency, efficiencies, agility with fit-to-purpose technology, and citizen engagement (Amaglobeli and others 2023b).
  - Strategies: automating operations and government services; making more data and digital services available across government agencies and to the private sector; adopting agile approaches, startups and open source, promoting innovation, and sharing anonymized data via application programming interfaces.
- Components and examples:
  - Enabling digital public infrastructure: cloud, digital payment, digital identification, code repositories.
  - Internal systems: digitalization of revenue administration, expenditure policies, public financial management, data sharing between administrations.
  - Government–user interfaces: online immigration applications and fiscal declarations, centralized medical records, online voting, budget monitoring.
  - Notable applications: AI answering citizens’ queries; registries for securing voting and procurement; tax collection and fraud detection; AI-powered chatbots or virtual assistants (Androutsopoulou and others 2019; Gomes de Sousa and others 2019; Hjálmarsson and others 2018; Engin and Treleaven 2019).

### Impact on Policies
- Mechanisms for efficiency gains:
  - Automation, integration, and better information for citizens and businesses.
  - Example: Action Publique 2022 automated France’s 250 most frequent administrative procedures.
- Trade-offs and risks:
  - Digitalization creates new state responsibilities (supply digital public infrastructure, improve digital literacy).
  - Risk of widening the digital divide (Sanders and Scanlon 2021).
  - Integration reduces redundancies but raises sensitivity concerns for health, tax, assets, and financial data and necessitates careful tracking of access and accountability.
  - Transparency is not automatic; digitalization can enable an “open-book” model but may not increase transparency in all contexts (Margetts 2006; Bannister and Connolly 2011).

### Impact on Politics and Legitimacy
- Accountability and trust:
  - GovTech changes mechanisms of accountability through increased information availability and by expanding state control and repression capabilities; may reduce trust and policy effectiveness if perceived as authoritarian (Poortinga and Pidgeon 2003; Wong and Jensen 2020).
  - Delegation to private providers blurs accountability and responsibility for service failures (example: Dutch government resignation January 2021 over machine learning childcare benefits fraud; Hadwick and Lan 2021).
- Market incentives vs. public interest:
  - Private firms are profit-driven, possess superior technical information, and may steer GovTech toward services that entrench market power or reduce fiscal pressure; state uses fiscal policy and regulation to aim for “second-best” supply under imperfect information.
  - Delegation can inflate adaptation costs and discourage necessary demand for service changes (Gagnepain, Ivaldi, and Martimort 2013; Hellman 2006).

### Challenges in Regulating GovTech
- Institutional capacity and regulatory capture:
  - Positive relationship between number of telecom operators (adjusted for population) and political stability and other Worldwide Governance Indicators; indicates competition increases with institutional strength.
  - Private companies tend to obtain concessions via regulatory capture: campaign financing, lobbying, revolving door, corruption.
- Market structure concerns:
  - Sources of market power: regulation favoring incumbents; large upfront investments or economies of scale; irreproducibility due to exclusive access to administrative data.
  - Economies of scale: large fixed costs (4G coverage, school connectivity, procurement of lithium and rare earths) reduce scope for competition; regulation should enforce competition or contestability.
  - Algorithm training and data create high entry barriers; markets may become noncontestable (Kang and Miller 2022).
- Personal data issues:
  - Incumbent advantage arises from access to sensitive administrative data and trade secrets; first-mover advantage hard to regulate (Simon and Sichelman 2017; Fromer 2019; Levine and Sichelman 2019).
  - GDPR (Council Regulation 2016/679) and equivalents constrain businesses but not states in some respects; allocation of property and usage rights over personal data remains unresolved and raises privacy and human-rights concerns.
  - Individual control over data does not necessarily enable algorithmic competition; administrations must remain in control of data and build in-house knowledge to keep markets contestable.

### Analytical Framework: Market Power, Economies of Scale, and Data
- Market power:
  - Arises from regulatory preference for incumbents and from natural-monopoly features (large upfront investments, economies of scale).
  - Trade secrets in GovTech often equate to exclusive access to administrative data rather than unknown technical superiority.
- Economies of scale:
  - Infrastructure investments and algorithm training costs favor incumbents; social optimum requires regulation to avoid oligopolistic pricing and encourage innovation.
- Personal data and contestability:
  - Sensitive data increases incumbent entrenchment; if private providers refuse to share data with administrations, this necessitates demanding oversight of usage and storage (Thomas and others 2019).
  - National regulation has lagged technological change (Wu 2014).

### Direction of GovTech: Practical Risks and Choices
- Primary deployment risks:
  - National digital initiatives can reduce agency autonomy; risks particularly acute in low-income and fragile countries: capture by techno-savvy elites, redirected budgets, blocked organic agency growth, single points of failure, brain drain, heightened fragility.
  - Migration of services: moving services to commercial clouds may reduce corruption in some contexts but in others may enable private capture; migrations can create corruption and data-breach risks.
  - Information security: increased actors multiply cybersecurity risks; directed cyberattacks target ecosystems rather than single institutions (example: “NotPetya” in Ukraine in 2017).
- Private-sector influence:
  - Private innovators may lobby for services that build market power and reduce competition; technical change biased toward capital raises redistribution and political unrest concerns (Acemoglu 2002; Caselli 1999; Rosenberg 1969).
  - Risk of data being used for purposes beyond initial public-purpose promises, including surveillance and human-rights restrictions (Goncharenko and Khadaroo 2020; Gussarova 2021).
- Citizen-centered alternatives:
  - Collaborative design, coproduction, and technologies like blockchain could return data control to citizens; coproduction common in local smart-city projects but less so nationally (Edelmann and Mergel 2021; Cordella and Paletti 2018).

### Governance, State Capacity, and Public Legitimacy
- Delegation and legitimacy:
  - Delegation creates direct relationships between private interests and citizens, diluting state responsibility and raising legitimacy issues (Janowski, Estevez, and Baguma 2018).
  - Risk of state capacity deterioration if the state does not maintain understanding of technologies; perceived inadequate administration can erode legitimacy of fiscal policy, the welfare state, and democracy.
- Institutional framework priorities:
  - Ensure GovTech remains citizen oriented, inclusive, competitive, and preserves direct citizen–state relationships to maintain legitimacy and accountability.
  - Avoid two-tier societies by keeping analog alternatives where necessary to prevent exclusion.

### Governing Demand and Supply
- Governing demand (adoption and inclusion):
  - Encourage broad adoption while avoiding exclusion of nonadopters via citizen-oriented innovation labs, transparent governance, clear accountability for implementation flaws, “citizen service” culture centered on satisfaction and feedback, and investment in digital education for all ages.
- Governing supply (fiscal and regulatory responses):
  - Fiscal policy and regulation should adapt to digital market structures.
  - Recommendations:
    - State should tax less and arguably subsidize GovTech services it does not wish to provide itself where positive spillovers exist.
    - Favor entry and competition; tax services with negative externalities or that do not serve citizens’ interests.
    - If private provision undermines satisfactory service or undermines regulation/taxation, state should supply the service itself and prevent private entry.
    - Ensure supply of digital infrastructure and connectivity does not hinder demand for digital services.

### Concluding Remarks: Goals, Dividends, and Risks
- Digital development strategies should make connectivity accessible, affordable, open, and safe while reducing the risk of regulatory capture, inequality, and market concentration.
- Potential social dividends:
  - Increased inclusion, efficiency, and innovation across public services (health, education); reduce disparities across urban/rural, gender, and education levels.
  - Positive macroeconomic and micro-level effects and potential improvements in government legitimacy and political stability.
- Contingencies:
  - Social dividends depend on the appropriate degree of fiscal policy (investment in infrastructure and subsidies) and regulation (market structure and privacy) to foster accessibility, affordability, and safety.
- Sector scale estimate cited:
  - McKinsey estimated the sector at $400 billion in 2018 and predicted it would increase to $1 trillion by 2025 (cited in Santiso 2020).

*IMF | IMF Note NOTE/2023/003 — The Political Economy of GovTech, Arthur Silve and Mariano Moszoro, July 2023*

### References .............................................................................................................

### References

### Scope of GovTech
- Definition and goals:
  - GovTech: use of technology to modernize and transform government operations, decision-making, and service delivery to improve government services, transparency, efficiencies, agility with fit-to-purpose technology, and citizen engagement (Amaglobeli and others 2023b).
  - Strategies: automating operations and government services; making more data and digital services available across government agencies and to the private sector; adopting agile approaches, startups and open source, promoting innovation, and sharing anonymized data via application programming interfaces.
- Components and examples:
  - Enabling digital public infrastructure: cloud, digital payment, digital identification, code repositories.
  - Internal systems: digitalization of revenue administration, expenditure policies, public financial management, data sharing between administrations.
  - Government–user interfaces: online immigration applications and fiscal declarations, centralized medical records, online voting, budget monitoring.
  - Notable applications: AI answering citizens’ queries; registries for securing voting and procurement; tax collection and fraud detection; AI-powered chatbots or virtual assistants (Androutsopoulou and others 2019; Gomes de Sousa and others 2019; Hjálmarsson and others 2018; Engin and Treleaven 2019).

### Impact on Policies
- Mechanisms for efficiency gains:
  - Automation, integration, and better information for citizens and businesses.
  - Example: Action Publique 2022 automated France’s 250 most frequent administrative procedures.
- Trade-offs and risks:
  - Digitalization creates new state responsibilities (supply digital public infrastructure, improve digital literacy).
  - Risk of widening the digital divide (Sanders and Scanlon 2021).
  - Integration reduces redundancies but raises sensitivity concerns for health, tax, assets, and financial data and necessitates careful tracking of access and accountability.
  - Transparency is not automatic; digitalization can enable an “open-book” model but may not increase transparency in all contexts (Margetts 2006; Bannister and Connolly 2011).

### Impact on Politics and Legitimacy
- Accountability and trust:
  - GovTech changes mechanisms of accountability through increased information availability and by expanding state control and repression capabilities; may reduce trust and policy effectiveness if perceived as authoritarian (Poortinga and Pidgeon 2003; Wong and Jensen 2020).
  - Delegation to private providers blurs accountability and responsibility for service failures (example: Dutch government resignation January 2021 over machine learning childcare benefits fraud; Hadwick and Lan 2021).
- Market incentives vs. public interest:
  - Private firms are profit-driven, possess superior technical information, and may steer GovTech toward services that entrench market power or reduce fiscal pressure; state uses fiscal policy and regulation to aim for “second-best” supply under imperfect information.
  - Delegation can inflate adaptation costs and discourage necessary demand for service changes (Gagnepain, Ivaldi, and Martimort 2013; Hellman 2006).

### Challenges in Regulating GovTech
- Institutional capacity and regulatory capture:
  - Positive relationship between number of telecom operators (adjusted for population) and political stability and other Worldwide Governance Indicators; indicates competition increases with institutional strength.
  - Private companies tend to obtain concessions via regulatory capture: campaign financing, lobbying, revolving door, corruption.
- Market structure concerns:
  - Sources of market power: regulation favoring incumbents; large upfront investments or economies of scale; irreproducibility due to exclusive access to administrative data.
  - Economies of scale: large fixed costs (4G coverage, school connectivity, procurement of lithium and rare earths) reduce scope for competition; regulation should enforce competition or contestability.
  - Algorithm training and data create high entry barriers; markets may become noncontestable (Kang and Miller 2022).
- Personal data issues:
  - Incumbent advantage arises from access to sensitive administrative data and trade secrets; first-mover advantage hard to regulate (Simon and Sichelman 2017; Fromer 2019; Levine and Sichelman 2019).
  - GDPR (Council Regulation 2016/679) and equivalents constrain businesses but not states in some respects; allocation of property and usage rights over personal data remains unresolved and raises privacy and human-rights concerns.
  - Individual control over data does not necessarily enable algorithmic competition; administrations must remain in control of data and build in-house knowledge to keep markets contestable.

### Analytical Framework: Market Power, Economies of Scale, and Data
- Market power:
  - Arises from regulatory preference for incumbents and from natural-monopoly features (large upfront investments, economies of scale).
  - Trade secrets in GovTech often equate to exclusive access to administrative data rather than unknown technical superiority.
- Economies of scale:
  - Infrastructure investments and algorithm training costs favor incumbents; social optimum requires regulation to avoid oligopolistic pricing and encourage innovation.
- Personal data and contestability:
  - Sensitive data increases incumbent entrenchment; if private providers refuse to share data with administrations, this necessitates demanding oversight of usage and storage (Thomas and others 2019).
  - National regulation has lagged technological change (Wu 2014).

### Direction of GovTech: Practical Risks and Choices
- Primary deployment risks:
  - National digital initiatives can reduce agency autonomy; risks particularly acute in low-income and fragile countries: capture by techno-savvy elites, redirected budgets, blocked organic agency growth, single points of failure, brain drain, heightened fragility.
  - Migration of services: moving services to commercial clouds may reduce corruption in some contexts but in others may enable private capture; migrations can create corruption and data-breach risks.
  - Information security: increased actors multiply cybersecurity risks; directed cyberattacks target ecosystems rather than single institutions (example: “NotPetya” in Ukraine in 2017).
- Private-sector influence:
  - Private innovators may lobby for services that build market power and reduce competition; technical change biased toward capital raises redistribution and political unrest concerns (Acemoglu 2002; Caselli 1999; Rosenberg 1969).
  - Risk of data being used for purposes beyond initial public-purpose promises, including surveillance and human-rights restrictions (Goncharenko and Khadaroo 2020; Gussarova 2021).
- Citizen-centered alternatives:
  - Collaborative design, coproduction, and technologies like blockchain could return data control to citizens; coproduction common in local smart-city projects but less so nationally (Edelmann and Mergel 2021; Cordella and Paletti 2018).

### Governance, State Capacity, and Public Legitimacy
- Delegation and legitimacy:
  - Delegation creates direct relationships between private interests and citizens, diluting state responsibility and raising legitimacy issues (Janowski, Estevez, and Baguma 2018).
  - Risk of state capacity deterioration if the state does not maintain understanding of technologies; perceived inadequate administration can erode legitimacy of fiscal policy, the welfare state, and democracy.
- Institutional framework priorities:
  - Ensure GovTech remains citizen oriented, inclusive, competitive, and preserves direct citizen–state relationships to maintain legitimacy and accountability.
  - Avoid two-tier societies by keeping analog alternatives where necessary to prevent exclusion.

### Governing Demand and Supply
- Governing demand (adoption and inclusion):
  - Encourage broad adoption while avoiding exclusion of nonadopters via citizen-oriented innovation labs, transparent governance, clear accountability for implementation flaws, “citizen service” culture centered on satisfaction and feedback, and investment in digital education for all ages.
- Governing supply (fiscal and regulatory responses):
  - Fiscal policy and regulation should adapt to digital market structures.
  - Recommendations:
    - State should tax less and arguably subsidize GovTech services it does not wish to provide itself where positive spillovers exist.
    - Favor entry and competition; tax services with negative externalities or that do not serve citizens’ interests.
    - If private provision undermines satisfactory service or undermines regulation/taxation, state should supply the service itself and prevent private entry.
    - Ensure supply of digital infrastructure and connectivity does not hinder demand for digital services.

### Concluding Remarks: Goals, Dividends, and Risks
- Digital development strategies should make connectivity accessible, affordable, open, and safe while reducing the risk of regulatory capture, inequality, and market concentration.
- Potential social dividends:
  - Increased inclusion, efficiency, and innovation across public services (health, education); reduce disparities across urban/rural, gender, and education levels.
  - Positive macroeconomic and micro-level effects and potential improvements in government legitimacy and political stability.
- Contingencies:
  - Social dividends depend on the appropriate degree of fiscal policy (investment in infrastructure and subsidies) and regulation (market structure and privacy) to foster accessibility, affordability, and safety.
- Sector scale estimate cited:
  - McKinsey estimated the sector at $400 billion in 2018 and predicted it would increase to $1 trillion by 2025 (cited in Santiso 2020).

*IMF | IMF Note NOTE/2023/003 — The Political Economy of GovTech, Arthur Silve and Mariano Moszoro, July 2023*

### References

### insea2023003 - References

### References (as listed in the source)
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*The Political Economy of GovTech NOTE/2023/003*

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_Source: https://www.imf.org/-/media/files/publications/imf-notes/2023/english/insea2023003.pdf_