Revenue Statistics in Asia and the Pacific 2026

2. Taxing Informal and Hard-to-Tax Sectors

Abstract

This Special Feature examines challenges in effective taxation of the informal and hard-to-tax sectors in selected developing economies in Asia. The informal sector has been a challenge for many countries in Asia and the Pacific. The chapter provides an overview of informal sectors in selected countries, analyses structural and institutional factors that drive informality, and discusses some measures taken to address these challenges.

Introduction

The size, nature and dynamics of the informal sector remain a key issue for policymakers in the Asia-Pacific region and beyond as they consider ways to increase public revenues. This Special Feature distinguishes between the informal and the hard-to-tax sectors, as well as between compliant and non-compliant taxpayers, to better understand the revenue potential of these groups and which policies are best suited to tap this potential, based on specific experiences from across Asia and the Pacific.

This chapter has been adapted by the Asian Development Bank (ADB) from “Taxing informal and hard-to-tax sectors”, an ADB Policy Guide led by Sandeep Bhattacharya, Principal Public Sector Economist at ADB, and written by Mazhar Waseem, Professor of Economics at the University of Manchester and consultant for ADB, and Tejaswi Velayudhan, Assistant Professor at the University of California, Irvine, and consultant for ADB.

The Special Feature is structured as follows. The first section explains the continued importance of analysing the informal and hard-to-tax sectors while the second section provides estimates of the size of the informal sector for a selection of countries in Developing Asia. The third section examines the potential revenue gains from bringing informal and hard-to-tax sectors into the tax net while the fourth section presents some of the main challenges to doing so and a fifth section present possible approaches to overcoming these challenges. A sixth section concludes.

Why the informal and hard-to-tax sectors matter for taxation in developing countries

The informal sector has been a focal concern in the efforts to improve taxation in developing countries. One reason the issue remains evergreen is that very little consensus on its definition and therefore its size and importance has been reached. This paper distinguishes between the informal and hard-to-tax (HTT) sectors and the underlying amount of their potential tax revenue.

HTT does not correspond to groups with the highest prevalence of tax evasion or the largest potential revenue gain from enforcement or base expansion. A broadly agreed-upon definition of the term is activities or groups who can very easily evade taxes or are administratively costly to tax. For example, agricultural income is considered HTT because agricultural landholdings are small. However, as Alm et al. (2005[1]) state, “there appears to be consensus also that the more sophisticated HTT activities, such as electronic commerce or multinational corporations with highly mobile capital and sophisticated transfer pricing activities, should not be considered part of the HTT.”

Similarly, informal does not always mean noncompliant and formal does not always mean compliant. A broad definition of informal seems to be activities or entities that have market value but are unregistered under any regulatory body, or registered entities that are nevertheless underreporting their activity. Table 2.1 shows the different categorisations and provides examples of their overlap with tax compliance.

Table 2.1. Categorisation of activities by formality and tax compliance status

	Formal	Informal	Hard-to-tax
Compliant	Tax-registered; reports and remits tax liability truthfully	Legally unregistered (outside of tax base), e.g. smaller than mandatory value-added tax exemption threshold	For example, agriculture, microenterprises
Noncompliant	Tax-registered but underreports tax liability or delinquent in payments	Illegally unregistered	Professional services

Source: Asian Development Bank.

Taxing the compliant forms of informality or HTT sectors requires changing the legal requirements for tax registration or changing the tax base (for example by reducing the value-added tax (VAT) registration threshold or removing an exemption for agriculture). Meanwhile, strong enforcement is a key means of reducing non-compliant forms. In both cases, policymakers should assess whether an increase in enforcement or expansion of the base would generate sufficient additional revenue to offset the associated increase in the administrative and compliance burden (Keen and Slemrod, 2017[2]).

Estimates of informal sector size in Asia and the Pacific

ADB’s study focuses on 17 developing member countries for its empirical analysis, 14 of which are included in Revenue Statistics in Asia and the Pacific.1 It shows that the informal sector corresponds to 25%-30% of GDP on average in the selected countries but constitutes a much larger share of employment: about two-thirds of employment is informal on average. These two figures can be reconciled by the fact that informal employment tends to be much less productive and therefore generates less overall economic output. The ADB further estimates that, on average, only around 40% of the labour force is registered for personal income tax (PIT) in the selected economies with available data, although there is considerable variation between them.

Individuals who are unregistered for PIT nevertheless contribute to tax revenue through other tax instruments. The economic output of individuals is increasingly taxed through their association with firms (Slemrod and Velayudhan, 2018[3]); (Milanez, 2017[4]). Firms employing informal labour or individuals who are unregistered for PIT may be registered for and remitting a business income tax, corporate income tax (CIT) or VAT. The employees of these firms therefore contribute to tax revenue and bear the economic incidence of the tax through its impact on their employment and wages. Instead of expanding the PIT base by lowering the exemption threshold, countries may be able to raise revenue from the same sources by raising the rates or improving enforcement of other taxes.

These considerations make estimates of informality in the labour market a poor predictor of missing tax revenue. In the case of VAT, informal labour is unlikely to even be correlated with VAT evasion because wage payments do not affect the tax liability (see Box 2.1 for further examination of the relationship between informality and VAT).

Estimating the revenue potential of the informal and HTT sectors

There are various ways to measure revenue potential. Taking a tax system as given, tax gap analyses can identify evasion within a given system or instrument. These estimates capture revenue missing through evasion, avoidance and possibly exemptions. In Pakistan, the income tax gap for 2022 was estimated to be about 30% of total tax collected while the sales tax gap was estimated to be about 24% of tax collected (Government of Pakistan, 2022[5]). In Bangladesh, a World Bank report estimated the VAT gap to be about 50%-60% of revenue collected (Rinaudo, 2015[6]). These gap estimates include underreporting by existing taxpayers in addition to revenue potential from unregistered taxpayers.

Meanwhile (Waseem, 2020[7]), for example, uses changes in the income tax exemption cutoff from Pakistan to estimate that low- and middle-income self-employed taxpayers in the country underreport their income by at least 70%. In comparison, low-income employees underreport only around 1% of their income.

Random audits can reveal more nuanced information about where the revenue potential lies. (Best et al., 2021[8]) exploit a random audit programme from Pakistan to estimate that around one-third of all VAT-paying firms in the country engage in some form of tax evasion. Firms that engage in tax evasion on average evade around 40% of their tax liability, and the tax evasion rate drops with firm size.

Not only can such analysis provide estimates of the size of the problem, but they can also reveal areas of weakness and allow better targeting of resources. Currently, only Indonesia and Viet Nam produce periodic tax gap estimates for either the CIT, PIT or VAT, although other countries have produced ad hoc estimates as cited above.

Box 2.1. VAT and the informal sector

VAT has been adopted by nearly every major economy and most developing countries in Asia and the Pacific. It has matured over time in many of these contexts, increasing in sophistication of enforcement and compliance. VAT has changed the landscape of informality by:

1. raising the costs of remaining informal;

2. increasing the importance of scrutinising existing tax registers, i.e., removing fake firms from the tax register; and

3. creating capacity to tax the informal sector indirectly through the channel of input taxation.

VAT has in-built mechanisms that incentivise formalisation. An unregistered firm purchasing inputs from a VAT-registered firm faces a tax-inclusive price but cannot receive tax credits on that purchase. As a result, the evidence suggests that transacting with formal firms increases the likelihood that a firm will themselves formalise (Almunia et al., 2024[9]; Gadenne, Nandi and Rathelot, 2019[10]; De Paula and Scheinkman, 2010[11]).

Many firms that are not mandated to register nevertheless do so voluntarily. A study of VAT in the Indian state of West Bengal shows that firms that buy from or sell to VAT-registered firms are more likely to register themselves, regardless of whether they are required to (Gadenne, Nandi and Rathelot, 2019[10]). It also reveals that once a firm registers for a VAT, they are more likely to purchase inputs from other VAT-registered firms, therefore bringing more transactions into the VAT net.

Experience suggests that raising the VAT revenue threshold may be desirable from a revenue efficiency standpoint as described by (Keen and Mintz, 2004[12]). Potential revenue gains from lowering the exemption threshold must be traded off with the efficiency loss from incentivising firms to remain small and the additional compliance and administrative costs incurred. Bashir et al. (2024[13]) find that the VAT exemption threshold in Pakistan reduces revenue growth of affected firms by nearly 37%.

A VAT can tax the informal sector indirectly. Some of the inputs informal firms use are sourced from formal firms or are imported from abroad. The VAT on these inputs – such as electricity and imported raw materials – is charged and remitted by the informal firm’s supplier at the time of supply. The informal firm, however, cannot claim any credit for the VAT paid by its suppliers and thus ends up bearing some of the incidence of the VAT. In this way, the VAT acts as a withholding tax on inputs supplied to the informal firms, taxing them indirectly (see (Waseem, 2022[14]) and (Keen, 2008[15]) for additional details of this process).

This withholding mechanism prompted some revenue authorities to use a strategy whereby imported and domestic inputs predominantly used by the informal sector are taxed at a higher than standard rate. While registered taxpayers can recover the tax through input tax credits, unregistered taxpayers cannot. This strengthens the incentives an informal firm faces to register. A similar impact can be achieved by imposing a withholding tax on imported inputs and domestic inputs supplied by the formal sector.

Informality interacts with VAT in another important way. Because under a standard VAT the tax paid at one stage is claimed as input tax in the next stage of the supply chain, the buyer has an incentive to ask for the VAT invoice from the seller, reducing the ability of the seller to misreport the transaction. This mechanism, however, breaks down when supplies to informal firms take place. Informal firms have no use for the VAT invoice and may prefer suppliers not to issue an VAT invoice in their name, as it could create a paper trail and expose them to the revenue authority. On the other hand, a VAT invoice is a check drawn on the government and being so has a market value.

This combination of incentives induces some fake firms – often called invoice mills – to enter the VAT system. The primary purpose of these firms is to purchase and sell VAT invoices rather than doing any legitimate business. Waseem (2023[16]) finds that invoice mills are a major conduit for VAT evasion in Pakistan. They are predominantly used to claim illegitimate VAT refunds on exports, with roughly 40% of the overclaimed refunds based on spurious invoices issued by invoice mills (see (Keen and Smith, 2006[17]); (Mittal, Reich and Mahajan, 2018[18]); and (Carrillo et al., 2023[19]) for more details on how invoice mills erode VAT revenues in developing countries). Invoice mills are a primary reason revenue authorities must maintain a “clean” tax register.

Challenges to taxing the informal and HTT sectors

The informal sector is characterised by cash-based transactions and limited financial documentation. Limited enforcement capacity, inadequate data systems, and higher compliance costs complicate efforts to bring these sectors under the tax net. Addressing these challenges requires a nuanced approach that balances enhanced compliance measures with inclusive policies to support formalisation, ultimately fostering a more resilient and equitable tax system while maintaining the livelihoods of those reliant on informal work. The following section focuses on some of the challenges developing economies are facing in tackling informal and HTT sectors.

Lack of reliable data to identify and track informal activities

A fundamental challenge in taxing the informal sector is a lack of reliable data to track its economic activities. Informal businesses often operate without formal registration or structured financial records, which leaves tax authorities with limited visibility of their scale, revenue streams and financial health. This absence of data not only complicates efforts to estimate potential tax bases but also hinders an authority’s ability to design effective tax policies that are appropriately tailored to informal sector characteristics. Additionally, the mobility and transitory nature of many informal enterprises make systematic tracking nearly impossible. Without robust data and effective identification mechanisms, tax authorities face significant obstacles in assessing, monitoring and collecting taxes from this sector, resulting in missed revenue opportunities and a tax system that lacks inclusiveness.

A key challenge in taxing the informal sector is that agents’ transactions do not leave any information trails. In addition, the sector is composed of numerous small firms, which obviates the possibility of using firms as tax collectors. This increases the administrative costs of collecting taxes as the government must collect taxes from many small agents with no verifiable third-party information available on the volume of the tax base involved.

In general, digital transactions – payments through a debit or a credit card – leave information trails, whereas cash transactions do not. Accordingly, information trails in an economy are proxied by the probability that a typical person in the economy owns a debit or a credit card. Some countries within the sample group, such as Indonesia, Malaysia, Sri Lanka and Viet Nam, have made impressive strides in improving access to digital payments, while others, such as Afghanistan, Bangladesh and Pakistan, still lag behind.

Greater share of hard-to-tax sectors in GDP

The structure of an economy plays a critical role in determining how difficult it is to tax the formal sector. A greater share of agriculture, wholesale, and retail trade in an economy’s GDP presents a major challenge because these sectors are inherently difficult to regulate and monitor. In many developing economies, agriculture and small-scale retail activities often operate in highly decentralised, cash-based environments with minimal formal record-keeping, making it challenging to assess taxable income accurately. Furthermore, these sectors frequently consist of small, family-run enterprises and self-employed individuals who lack both the capacity and incentive to comply with tax regulations.

Wholesale and retail trade often rely on informal networks and are spread across numerous small businesses, adding to the complexity of enforcement. The seasonal and volatile nature of agricultural income also complicates efforts to tax this sector consistently and fairly. Where these HTT sectors contribute a significant portion of GDP, the inability to effectively tax them results in substantial untapped revenue potential. This structural composition of the economy thus hampers the ability of tax authorities to widen the tax base and integrate the informal sector, limiting resources for development and perpetuating fiscal constraints.

High compliance costs and complex tax systems

High compliance costs and a complex tax system may discourage small and informal businesses from entering the formal economy. Compliance with tax regulations often involves both direct costs, such as registration fees and potential penalties, and indirect costs, such as the time and resources needed to understand and adhere to complex tax rules. For many small enterprises and self-employed individuals in the informal sector, these costs can be prohibitive, especially in developing countries where administrative capacity is limited and tax systems lack transparency. Additionally, small businesses may face pressure to pay bribes to tax inspectors, further increasing the perceived costs and risks of formalisation.

This resistance perpetuates the informal sector’s size, resulting in lost revenue for governments and undermining efforts to broaden the tax base. Simplifying tax procedures and reducing compliance costs could therefore be essential steps towards incentivising formalisation and improving tax compliance.

Weak institutions

Weak institutions create significant obstacles in taxing the informal sector. When tax authorities and regulatory bodies are prone to corruption, businesses in the informal sector may find it easier and more cost-effective to pay bribes than to formalise and comply with tax regulations. This perpetuates informality and erodes trust in government institutions, as businesses perceive the tax system as unfair and untrustworthy.

Ineffective governance and poor enforcement of the rule of law also mean that tax regulations are often inconsistently applied, making compliance unpredictable and discouraging formalisation. Moreover, without robust institutional frameworks to monitor, assess and collect taxes, governments lack the necessary tools to broaden the tax base effectively. These issues create a cycle whereby weak institutions both contribute to and are reinforced by a large informal sector.

Ineffective governance and political instability contribute to an unpredictable regulatory environment, making it difficult for businesses to navigate tax obligations confidently, further disincentivising formalisation. The ADB study underscores that weak institutional frameworks characterised by high bribery, low government effectiveness, poor rule of law and political instability, pose significant challenges to taxing the informal sector. Without improvements in governance, efforts to broaden the tax base and enhance compliance will remain limited, as businesses may continue to view informal operations as a more viable and less costly option.

Strategies to tax the informal and HTT sectors

Tax administrations in Asia and the Pacific are taking various measures to overcome the major challenges in taxing the informal and HTT sectors. The following section introduces some of the strategies implemented across Asia and the Pacific, along with key considerations for policymakers.

Expanding business registration

Identifying unregistered taxpayers through physical verification is often used as a key strategy for addressing informality. Taxpayer registration is a fundamental step in the tax process, and comprehensive, accurate, and up-to-date registration information is essential for effective tax administration. On the other hand, non-compliance with mandatory registration requirements tends to be negatively correlated with firm size, indicating this measure is likely to target smaller firms, with lower revenue potential. Several studies of experiences with expanding registration show that this strategy is too costly to justify the resulting revenue gains (Gallien et al., 2023[20]).

The evidence on what works to get firms to register with the tax authority is best viewed through the lens of a trade-off between the cost of registration and the cost of remaining unregistered. The cost of registration includes a potential increase in tax liability, increase in compliance cost and potential harassment by government officials, while the cost of remaining unregistered includes a higher risk of enforcement, inability to grow, and even potentially a higher tax liability (e.g. in presumptive tax regimes). The findings suggest that efforts aimed at decreasing the non-tax cost of registration are generally unsuccessful while increasing the cost of remaining unregistered tends to be more successful.

Presumptive taxation

Presumptive taxation, which is taxing based on easily observable characteristics such as taxing on turnover, or setting a minimum tax, is a way to generate revenue from the lower end of the taxpayer distribution while lowering the administrative and compliance burden. Registered taxpayers below a minimum size threshold are eligible for a simplified tax regime with minimal filing and recordkeeping requirements. Such instruments have small efficiency costs and do not raise much revenue but may bring non-revenue benefits of formalisation and provide a path to voluntary formalisation and growth.

Some evaluations of experiences with presumptive tax regimes suggest that they can encourage registration. A simplified regime in Georgia for firms below a given turnover threshold resulted in a one-time increase in firm registration just below that threshold (Bruhn and Loeprick, 2015[21]). The increase in registration came from an existing stock of informal firms registering rather than newly created firms or existing registered firms reporting lower turnover. However, how much these newly registered firms contribute to tax revenue could not be measured. Brazil’s SIMPLES programme2 reduced tax for some taxpayers on top of simplifying registration procedures, which encouraged formalisation but resulted in a net revenue decrease (Rocha, Ulyssea and Rachter, 2018[22]). The increased revenue from newly formal firms did not offset the decrease in revenue for already-formal firms.

While presumptive regimes can have low costs for the revenue authority and taxpayers, care must be taken to ensure that they do not simply act as a nuisance tax that raises little revenue but presents a hassle to the taxpayer. Hoy et al. (2024[23]) find that presumptive regimes do seem to add more burden on taxpayers than previously known, while bringing in very little revenue. In Kenya, many taxpayers in the presumptive regime did not know their actual tax liability even though it was theoretically simple to calculate if they knew their monthly sales. These taxpayers tended to pay the same fixed amount regardless of the actual liability even if the liability may have been lower. This suggests that even very simple regimes may be more burdensome to taxpayers than previously understood.

Presumptive and simplified tax regimes are widely prevalent and likely to remain so3. They are beneficial in the sense that they provide a path to formalisation for growing firms without an immediate, large burden in terms of compliance costs. Compared with mass registration, they are less costly for the tax authority to administer and for the taxpayer to participate in. Nevertheless, expanding presumptive regimes by requiring even smaller taxpayers or by raising the exemption threshold comes with revenue trade-offs that should be measured and considered.

Data-driven approaches to tax enforcement

Advances in technology are revolutionising the work of revenue authorities in advanced economies. These authorities are increasingly using the predictive power of big data to identify unregistered businesses, detect tax evasion, target enforcement and recover the evaded amounts. Emerging and developing economies are also transitioning to data-driven organisation. In some respects, more data are available to revenue authorities of developing economies than their counterparts in the developed world. For example, transaction-level details of all sales and purchases are now collected in many developing contexts, such as Pakistan, whereas such data are not collected in some developed countries. Data are the most important resource for tax enforcement; developing economies collect vast amounts of data from taxpayers, but they are either not utilised or utilised very inefficiently.

Data-driven enforcement combines tax and non-tax data available to revenue authorities with cutting-edge machine learning algorithms to address two critical gaps in enforcement capacity in these contexts.

Risk-based targeting: The number of taxpayers that revenue authorities can audit each year is usually very limited. It is therefore critical that these audits are targeted towards the most significant tax evaders so that their impact can be maximised. But existing evidence shows that the targeting mechanisms used in developing economies are extremely inefficient. Using data from Pakistan, (Best et al., 2021[8]) find that risk-based mechanisms used by the country do not do better than random audits in identifying the risk of tax evasion.

There are many technological and institutional reasons for developing economies’ lack of efficient targeting mechanisms. Importantly, they do not have the capacity to evaluate the objective revenue risk of each taxpayer, which requires comparing the revenue remitted by a taxpayer to the potential revenue remitted by the taxpayer in a world with no tax evasion. As a result, most still use archaic discretion-based rules to allocate audits, and where data-driven risk mechanisms are used, they do not attempt to estimate the objective risk of each taxpayer. By combining the experimental variation with data and using cutting-edge machine learning algorithms, revenue authorities can estimate the tax gap for all major taxes as well as implement the most efficient targeting mechanism for audit.

Detection technology and recovery capacity: Detection technology refers to the probability that a typical tax audit conducted by the revenue authority would be able to detect tax evasion committed by a taxpayer. In many developing contexts, the detection technology of the revenue authority is underdeveloped and revenue authorities also struggle with recovery capacity. Recovery capacity refers to the probability that an amount detected by audit would ultimately be recovered by the revenue authority. Recent research has found that weak recovery capacity is the more significant constraint than detection technology in curtailing tax evasion in developing economies (Best et al., 2021[8]; Okunogbe, 2021[24]). Data-driven approaches can create end-to-end linkage of the audit-detection-recovery process. As a result, the government can track the outcomes of audits to their logical end, determine the quality of audit, and compensate the auditors accordingly.

Informality and tax rates

The relationship between informality and tax rates is complex. High tax rates can incentivise businesses to remain informal to avoid tax burdens, while lower tax rates may encourage formalisation by reducing the cost of compliance. However, the effectiveness of tax rate reductions in promoting formalisation depends on various factors, including enforcement mechanisms, administrative capacity and the broader regulatory environment.

Empirical evidence supporting the notion that lower tax rates can encourage formalisation is mixed. (Rocha, Ulyssea and Rachter, 2018[22]) use the SIMPLES programme from Brazil to show that reducing taxes once registration costs have already been eliminated reduces firm informality. The implied formalisation elasticity, however, is low, meaning that the programme resulted in net losses for the country in terms of tax revenues. Using the same programme, (Monteiro and Assunção, 2012[25]) find heterogeneous effects by sector. While formal licensing goes up by 13 p.p. in the retail sector, it remains unchanged in the construction, transportation, services and manufacturing sectors.

While lower tax rates may not encourage formalisation of firms, increasing the tax rate significantly can push registered firms into informality. Waseem (2018[26]) uses a tax reform enacted by Pakistan in 2009, which increased the taxation of partnership earnings substantially relative to earnings from other business forms, to show that following the tax increase nearly two-thirds of the affected firms moved into informality. The revenue loss caused by this migration was so large that by the third year after the tax increase the government was collecting less revenue than it would have expected to without the tax increase.

The complex relationship between informality and tax rates underscores the need for policymakers to exercise caution when designing tax policies aimed at addressing informality. This delicate balance requires policymakers to carefully evaluate the trade-offs and complement tax rate adjustments with measures such as simplified compliance procedures, targeted enforcement, and support for businesses transitioning to formal operations. A nuanced approach, informed by empirical evidence, is crucial to ensure that tax policies effectively reduce informality without undermining revenue goals or economic activity.

Conclusion

The informal and hard-to-tax sectors remain significant challenges for tax administrations across Asia and the Pacific. This Special Feature explains why policymakers should carefully consider the revenue implications and enforcement costs of measures targeting informality, as many informal taxpayers are small with limited revenue potential or fall below exemption thresholds. Tax administrations should adopt a more targeted approach towards registered and unregistered noncompliant taxpayers, particularly those with higher revenue potential, rather than relying on a binary distinction between the formal and informal sectors.

The chapter also highlights several structural and institutional factors associated with informality, including the share of agriculture in GDP, weak institutions, high compliance costs and limited transaction traceability. The experiences reviewed further show that strategies such as expanding taxpayer registration and presumptive taxation have produced mixed results, with varying implications for revenue collection, compliance, and formalisation.

Ultimately, country-specific contexts remain important in designing appropriate approaches to address informality and hard-to-tax sectors. ADB’s study, Taxing Informal and Hard-to-Tax Sectors, further elaborates on the analysis of informal and hard-to-tax sectors in selected economies, as well as related policy considerations and recommendations.

References

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Notes

← 1.  These 17 countries are Afghanistan, Bangladesh, Bhutan, Cambodia, the People’s Republic of China, India, Indonesia, Malaysia, Maldives, Mongolia, Myanmar, Nepal, Pakistan, the Philippines, Sri Lanka, Thailand and Viet Nam. These countries are referred to as “countries of focus” or “selected countries” in this chapter.

← 2.  The SIMPLES programme in Brazil, introduced in 1996, is a simplified tax regime designed to encourage small and micro enterprises to formalise by consolidating multiple taxes into a single, lower tax rate and streamlining compliance procedures. By reducing the administrative burden and cost of formalisation, the programme aimed to increase formal registrations among small businesses while improving tax compliance.

← 3.  Please see Mas-Montserrat et al. (2023[27]) for further analysis of the design of presumptive tax regimes globally.