Data As Fiscal Infrastructure

A tax system without data is like a pilot navigating through thick cloud cover without instruments. The aircraft may be well-built, the engines may be strong, and the crew may be experienced, yet without reliable readings on altitude, direction, fuel, and weather conditions, flight becomes an exercise in uncertainty rather than control. In the same way, Nigerian states may possess tax laws, administrative structures, and enforcement agencies (IRSs), but without structured, timely, and credible data, fiscal decision-making becomes reactive, fragmented, and often inefficient.

This is the third instalment in a series on state-level taxation/tax policy. The first, published on 7th April, Rebuilding State Tax Capacity for Growth, examined the institutional and administrative foundations of tax systems in sub-national governments. The second, published on 21st April, Taxation Follows Economic Activity, extended the argument by showing that taxation is fundamentally endogenous to economic structure, industrial activity, and investment flows. This third piece builds directly on those foundations by introducing a critical missing pillar in Nigeria’s fiscal architecture: data as the operational core of modern tax systems.

Data as fiscal foundation

From a public finance perspective, taxation is not merely a legal obligation enforced by administrative machinery. It is a data-dependent coordination problem between the state and the economy. Every tax liability is ultimately a function of observable economic activity, whether consumption, income generation, property ownership, or corporate earnings. Without data, these activities remain partially invisible, inconsistently measured, and unevenly taxed.

In Nigeria’s subnational context, this problem is acute. Many states still rely on fragmented registries, outdated manual records, and incomplete taxpayer databases. As a result, fiscal authorities often operate with partial information, leading to estimation errors, revenue leakages, and inefficient enforcement allocation. A modern tax system, however, requires what institutional economists describe as state capacity in information processing. This is not limited to technology alone; it includes the ability to collect, verify, integrate, and utilize data across agencies and economic sectors.

The distinction is important. A state can digitize forms without transforming its information ecosystem. True data infrastructure connects land registries, business registrations, payroll systems, financial transactions, and consumption patterns into a coherent fiscal map. Without this integration, tax administration becomes fragmented, and compliance strategies become guesswork rather than evidence-based interventions.

Administrative reform meets reality

In the first article of this series, the emphasis was placed on administrative capacity: staffing, processes, institutional design, and enforcement systems. That analysis remains valid, but incomplete. Administrative capability without data is like an engine without a navigation system. It generates motion, but not direction.

Consider the case of Lagos State, where relatively stronger data integration across vehicle registration, land administration, and business tax systems has enabled more targeted enforcement and improved compliance efficiency. Even there, challenges remain, but the direction of reform illustrates an important principle: data reduces the cost of enforcement while increasing its precision.

Contrast this with some states, where taxpayer identification systems remain partially fragmented across local governments and state agencies. In such contexts, enforcement efforts often become broad, repetitive, and inefficient, targeting visible taxpayers while missing large segments of informal or semi-formal activity. The result is a higher administrative cost per unit of revenue collected.

This demonstrates a key public finance principle: administrative reforms yield diminishing returns when not supported by robust data systems. States may increase enforcement intensity, but without accurate information, marginal revenue gains decline over time.

Economic activity becomes visible

The second article in this series argued that taxation follows economic activity. This principle becomes operational only when economic activity is measurable. Data is what transforms economic activity from abstract theory into taxable reality.

In Kano, for example, markets such as Kurmi and Sabon Gari represent dense nodes of economic exchange. Yet without integrated transaction data, business registration linkages, and consumption tracking, a large portion of this activity remains outside formal fiscal visibility. Similarly, Kaduna’s expanding industrial clusters along the Kaduna Industrial Zone generate significant value-added activity, but incomplete data integration between corporate registries and tax authorities limits full fiscal capture. In Katsina, agricultural trade flows across rural markets remain largely undocumented, creating gaps between actual economic output and taxable capacity.

In each case, the constraint is not solely administrative inefficiency or weak enforcement. It is information asymmetry between the state and the economy. Where data systems are weak, the state underestimates its own fiscal potential and misallocates enforcement resources.

From an institutional economics perspective, this is a classic case of incomplete information reducing the efficiency of governance. Markets operate with dispersed information, but states require aggregated, structured data to intervene effectively. Without it, taxation becomes selective rather than comprehensive.

Data and fiscal efficiency

Data does not only increase revenue; it improves allocative efficiency in tax administration. A well-structured data system allows tax authorities to segment taxpayers, identify compliance risk profiles, and allocate enforcement resources where marginal returns are highest.

For example, corporate tax compliance in Kaduna can be significantly improved if data from the Corporate Affairs Commission, financial institutions, and sector regulators are integrated into a unified tax intelligence system. This allows authorities to identify discrepancies between reported income and observable economic activity. Similarly, in Kano, integrating customs-related trade data with state-level tax records can help close leakage points in commercial taxation.

The economic logic is straightforward: better data reduces information asymmetry, and reduced asymmetry improves compliance efficiency. This is a standard result in optimal tax theory, where enforcement costs decline as information quality improves.

Moreover, data enables dynamic fiscal planning. States can forecast revenue more accurately, simulate policy impacts, and assess the fiscal consequences of tax incentives or exemptions. Without data, fiscal planning becomes static and backward-looking.

From data gaps to fiscal systems

The absence of integrated data systems creates what can be described as a fiscal visibility gap. This gap manifests as underreporting, weak compliance targeting, and inefficient policy design. It also leads to misaligned incentives, where enforcement focuses on easily observable taxpayers rather than high-value but less visible economic actors.

In Kaduna, for instance, informal subcontracting within manufacturing value chains often escapes taxation due to lack of supply chain data integration. In Kano, retail and wholesale networks generate substantial turnover, but fragmented business registries limit full fiscal mapping. In Katsina, agricultural output flows through multiple informal channels before reaching markets, making income tracking difficult.

Closing these gaps requires more than digitization. It requires data architecture design, institutional coordination, and inter-agency interoperability. The state must function as an integrated information system, not a collection of isolated administrative units.

This is where systems thinking becomes critical. Tax administration is not a linear process but a networked system in which data flows determine efficiency, accuracy, and responsiveness.

Closing reflection

If taxation is to function as a developmental tool, then data must be treated as fiscal infrastructure, not an administrative accessory. Roads connect markets; data connects economic activity to the state. Without it, policy becomes speculative. With it, fiscal governance becomes precise, adaptive, and sustainable.

As the economist Herbert Simon once observed, “To design is to devise courses of action aimed at changing existing situations into preferred ones.” In fiscal systems, data is what makes such design possible.

This series continues in the next week, progressively building a coherent framework for understanding and reforming subnational taxation in Nigeria.