Statistical measurement of illicit financial flows

SDG indicators

SDG target 16.4: By 2030, significantly reduce illicit financial and arms flows, strengthen the recovery and return of stolen assets and combat all forms of organized crime
SDG indicator 16.4.1: Total value of inward and outward illicit financial flows (in current United States dollars) (Tier II)

The COVID-19 pandemic, the war in Ukraine and the increasing costs of climate change and environmental challenges have had a particularly devastating impact on developing economies highlighting the critical need for addressing the financing gap. The ability to achieve the SDGs remains fragile when IFFs continue to drain resources that would be needed to fulfil human rights and pursue sustainable development. Domestic resource mobilization, assets recovery and curbing IFFs is more critical than ever. Governments’ capacity to raise resources through return of assets will be fundamental to rescue the 2030 Agenda.

The 2030 Agenda identifies the reduction of IFFs as a priority area, as reflected in target 16.4: “by 2030, significantly reduce illicit financial flows and arms flows, strengthen the recovery and return of stolen assets and combat all forms of organised crime”. This target is critical for financing efforts to achieve SDGs. IFFs were also identified as a global priority in the Addis Ababa Action Agenda -—
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on financing for development which calls for a redoubling of efforts to substantially reduce IFFs, with a view to eventually eliminating them.

Research shows that IFFs weaken state institutions by encouraging corruption and undermine the rule of law and the functioning of the criminal justice systems. The impacts lead to particularly dire effects for the most vulnerable. UNCTAD’s Economic Development in Africa Report -—
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found that some countries with high IFFs spend on average 25 per cent less on health and 58 per cent less on education compared with countries with low IFFs. By eroding the tax base and discouraging public and private investment, they hamper structural transformation, economic growth and sustainable development.

Regardless of its importance, data on indicator 16.4.1, “total value of inward and outward illicit financial flows”, are not yet reported as part of the SDG indicator framework -—
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. The world needs comparable and reliable statistics on IFFs to shed light on the activities, sectors and channels most prone to illicit finance, pointing to where actions should be undertaken as a priority to curb these flows.

After intensive global efforts by UNCTAD, UNODC and experts from member States and international organizations, globally agreed concepts for measuring IFFs as SDG indicator 16.4.1 now exist and were adopted by all member States represented at the IAEG-SDGs, and the United Nations Statistical Commission, as well as endorsed at the political level by the FACTI panel -—
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and the Cluster V of United Nations Regional Commissions on Financing for Development in the Era of COVID-19 -—
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. Selected methods to measure different types of IFFs have been pilot tested between 2018 and 2022 by 22 countries in Africa, Asia and Latin America, contributing towards refining global methods to measure IFFs and report on SDG 16.4.1.

Globally agreed concepts for SDG indicator 16.4.1 on illicit financial flows

UNCTAD and UNODC, as custodians of SDG indicator 16.4.1 assigned by the General Assembly, lead global methodological work to develop statistical definitions and methods to measure IFFs to support member States in monitoring progress towards target 16.4. In line with the General Assembly resolution -—
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1 to ensure engagement with national statistical authorities, UNCTAD and UNODC established a Task Force on the Statistical Measurement of IFFs in January 2019 2, involving experts from national statistical offices, financial intelligence units, tax authorities, academia, non-governmental organisations, international organisations and other IFF experts.

As a result of this work, and for the purpose of the SDG indicator, there is a globally agreed definition of IFFs which are defined as financial flows that are illicit in origin, transfer or use, that reflect an exchange of value, and cross country borders.3

The IAEG-SDG, as designated by the United Nations Statistical Commission, endorsed these concepts in a methodological proposal in October 2019 and reclassified indicator 16.4.1 from tier 3 to tier 2, meaning that the indicator is conceptually clear and based on internationally established standards, while data are not yet available from countries.

The -—
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Conceptual Framework for the Statistical Measurement of Illicit Financial Flows reflects the approved concepts and standards, and the Framework was endorsed by the member States and international organizations at the 53rd Session of the United Nations Statistical Commission -—
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in March 2022.

For comparability and timeliness, statistics cannot be based on legality as country laws on crime differ and some activities may be declared illegal only afterwards as part of investigations. Therefore, the scope of IFFs is defined based on a typology of activities that may generate IFFs. The Framework identifies four main types of such activities (1) illicit tax and commercial practices, (2) illegal markets, (3) corruption and (4) exploitation-type and terrorism financing (see Figure 1).

Figure 1. Categories of activities that may generate IFFs

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According to this typology, the four main categories of IFFs are described as follows:

  1. Illicit tax and commercial IFFs. This category includes illicit practices by legal entities as well as arrangements and individuals with the objective of concealing revenues, reducing tax burden, evading controls and regulations and other purposes. This category can be divided into two components:
    • IFFs from illegal commercial and tax practices. These include illegal practices such as tariff, duty and revenue offences, tax evasion, corporate offences, market manipulation and other selected practices. Some activities that are non-observed, hidden or part of the so-called shadow economy, the underground economy or the informal economy may also generate IFFs. Related activities included in the ICCS comprise tax evasion, tariff, duty and revenue offences, competition offences, import/export offences, acts against trade regulations, restrictions or embargoes and investment or stack/shares offences.
    • IFFs from aggressive tax avoidance. Illicit flows can also be generated from legal economic activities through what is sometimes called harmful or aggressive tax avoidance (see box 1 for more detail on the distinction between legal and illegal illicit flows). Aggressive tax avoidance can take place through a variety of forms, such as manipulation of transfer pricing, strategic location of debt and intellectual property, tax treaty shopping, and the use of hybrid instruments and entities. For the purposes of the measurement of the indicator, these flows need to be carefully considered, as they generally arise from licit business transactions and only the illicit part of the cross-border flows belongs to the scope of IFFs.
  2. IFFs from illegal markets. These include trade in illicit goods and services, when the money flows generated cross country borders. Such processes often involve a degree of criminal organisation aimed at creating profit. They include any type of illegal trafficking of goods, such as drugs and firearms, or services, such as smuggling of migrants. IFFs are generated by the flows related to international trade of illicit goods and services, as well as by cross-border flows from managing the illicit income from such activities.
  3. IFFs from corruption. The United Nations Convention against Corruption -—
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    defines acts considered as corruption, which are consistently defined in the ICCS. These include bribery, embezzlement, abuse of functions, trading in influence, illicit enrichment and other acts. When the economic returns from these acts directly or indirectly generate cross-border flows, they are considered IFFs.
  4. IFFs from exploitation-type activities and financing of crime and terrorism. Exploitation-type activities are illegal activities that entail a forced and/or involuntary transfer of economic resources between two actors. Examples include slavery and exploitation, extortion, trafficking in persons, and kidnapping. In addition, terrorism financing and financing of crime are illicit, voluntary transfers of funds between two actors with the purpose of funding criminal or terrorist actions. When the related financial flows cross country borders, they constitute IFFs.
Box 1: Aggressive tax avoidance and IFFs

A specific conceptual challenge is to specify what kinds of activities should be designated as illicit or licit. It is noteworthy that SDG target 16.4 refers to ‘illicit’ instead of ‘illegal’ financial flows. Aggressive tax avoidance, including by MNEs, although usually legal, can drain resources and be considered illicit.

The inclusion of tax avoidance in the definition of IFFs creates some challenges, as it blurs the line between legal and illegal activities. Noting that the boundary between legal and illegal tax practices may be unclear, the -—
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described the continuum of activities from legal tax planning to illegal tax evasion (see Figure 2). In this context, aggressive tax planning is described as “taking advantage of the technicalities of a tax system or of mismatches between two or more tax systems for the purpose of reducing tax liability.”

Figure 2. Boundaries of aggressive tax planning

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IFFs stemming from aggressive tax avoidance are considered in detail by -—
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, and can include BEPS through interest payments, strategic location of intangible assets, abuse of tax treaties, artificial avoidance of permanent establishment and transfer pricing manipulation. The BEPS package, released in 2015 by OECD and G20 countries, delivers guidance for governments to close gaps in existing international rules that allow corporate profits to be artificially shifted to low-tax jurisdictions where companies have little or no economic activity. Work to address outstanding BEPS issues by the Inclusive Framework is ongoing -—
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As part of the OECD Inclusive Framework on BEPS, progress has also been made in improving data availability to support the measurement of MNEs tax avoidance. Country-by-country reporting statistics are released publicly in an aggregated and anonymised form and can be analysed at the microdata level by country authorities.

An important distinction is made to avoid double counting and link to the SNA between two different stages leading to IFFs: 4

  1. IFFs linked to income generation, as the set of cross-border transactions that are performed in the context of the production of illicit goods and services or the set of cross-border operations that directly generate illicit income for an actor during a non-productive illicit activity. Inward or outward IFFs occur when the operation in question is performed across a border.
  2. IFFs linked to income management, as the set of cross-border transactions finalised to use the (illicit) income for investment in (legal or illicit) financial and non-financial assets or for consuming (legal or illegal) goods and services. If spent abroad, the operation is an outward IFF. If stemming from illicit activity outside a jurisdiction but is spent in the domestic jurisdiction, an inward IFF is generated.

IFFs need to be classified using a discrete, exhaustive and mutually exclusive statistical classification aligned with existing statistical frameworks and principles -—
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. The ICCS -—
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is a good point of departure for identifying the activities that could generate IFFs. Table 1 provides examples of some activities generating IFFs that are linked directly to the ICCS.

Table 1. Examples of activities generating IFFs from crime, by ICCS categories
Categories of IFFsExamples
Tax and commercial practices08041 Tariff, taxation, duty and revenue offences
08042 Corporate offences including competition and import/export offences; acts against trade regulations
08045 Market manipulation or insider trading, price fixing
Exploitation-type activities and terrorism financing (parts of sections 02, 04, 09)020221 Kidnapping
0203 Slavery and exploitation
0204 Trafficking in persons
0302 Sexual exploitation
02051 Extortion
0401 Robbery
0501 Burglary
0502 Theft
09062 Financing of terrorism
Illegal marketsICCS includes a long list of activities, including for example drug trafficking (060132), firearm trafficking (090121), illegal mining (10043), smuggling of migrants (08051), smuggling of goods (08044), wildlife trafficking (100312)
Corruption (section 0703)07031 Bribery
07032 Embezzlement
07033 Abuse of functions
07034 Trading in influence
07035 Illicit enrichment
07039 Other acts of corruption

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Note: This list is only intended to provide some examples and it is not exhaustive.

The ICCS does not cover all tax and commercial activities that may generate IFFs, for instance IFFs related to aggressive tax avoidance. Therefore, the classification of IFFs needs to be wider. A more exhaustive classification is being developed, where each activity is being analysed considering three aspects:

  • Change in income: whether the activity is economic (directly or indirectly generating a change of income) or non-economic;
  • Direct or indirect flows: activity generating a change of income with or without direct exchange of resources;
  • Productive or non-productive activities: falling within or outside the production boundary as defined in the SNA.

Such taxonomy (see Figure 3) allows for addressing not only whether each activity generates IFFs, but also which part, i.e., income generation or income management, thus guiding IFF measurement.

Figure 3. The decision tree for IFF taxonomy

Source: UNCTAD.

UNCTAD and UNODC refining global statistical methodologies with member States

IFFs are deliberately hidden and, as they take many forms and use varying channels, their measurement is challenging both conceptually and in practice. UNCTAD and UNODC, therefore, provide different methods for the measurement of different types of IFFs. The measurement challenges also differ across countries, depending on main types of IFFs affecting the country, data availability, mandates of national institutions, statistical capacity and national policy priorities. Thus, a suite of methods is suggested for selection allowing country-specific solutions and the flexible application of the most suitable methods in each country.

In May 2021, -—
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Methodological Guidelines to Measure Tax and Commercial IFFs were published for pilot testing. They identify a suite of methods for the measurement of the main types of tax and commercial IFFs for pilot testing (see table 2). The guidelines put preference on bottom-up and direct measurement of IFFs based on using all microdata available for national authorities.5

Table 2. Activities that may generate tax and commercial IFFs and types of flows
CategoriesActivities Flows
A. IFFs from illegal commercial and tax activitiesA1 Acts against public revenue provisions [08041]

A2 Acts against commercial or financial regulations [08042]

A3 Market manipulations or insider trading [08045]

A4 Acts of commercial fraud [07019]

A5 Other illegal commercial and tax acts [08049+]
F1 Transfer of wealth to evade taxes, i.e., flows related to undeclared offshore wealth
  • Outright undeclared (concealed e.g., in secrecy jurisdictions)
  • Undeclared via instruments (Phantom corporations or shell companies, tax havens)

F2 Misinvoicing
  • Under/over pricing
  • Multiple invoicing
  • Over/under reporting of quantities
  • Misclassification of tariff categories
B. IFFs from aggressive tax avoidanceB1 Acts departing from the arm’s length principle

B2 Acts related to strategic location of debt, assets, risks, or other corporate activities

B3 Other acts of aggressive tax avoidance
F3 Transfer mispricing

F4 Debt shifting
  • Intracompany loans
  • Interest payments

F5 Assets and intellectual property shifting
  • Strategic location of intellectual property
  • Strategic location of other assets
  • Cost-sharing agreements
  • Royalty payments

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Note: Activities in category A are based on level-3 categories of the ICCS (with corresponding codes in brackets).

The Methodological Guidelines are aimed at statistical and other national authorities with a mandate to collect and access detailed data. Microdata available to national authorities enable the compilation of more reliable estimates. However, simpler methods are proposed in parallel with more sophisticated methods to enable IFFs’ estimation also where less data are available. The UNCTAD guidelines provide two methods for each of the three main types of tax and commercial IFFs:

  1. Trade misinvoicing by entities (flow F2, table 2)
    • Method #1 - Partner Country Method Plus
    • Method #2 - Price Filter Method Plus
  2. Aggressive tax avoidance or profit shifting by MNEs (flows F3-F5, table 2)
    • Method #3 - Global distribution of MNEs’ profits and corporate taxes
    • Method #4 - MNE vs comparable non-MNE profit shifting
  3. Transfer of wealth to evade taxes by individuals (flow F1, table 2)
    • Method #5 - Flows of undeclared offshore assets indicator
    • Method #6 - Flows of offshore financial wealth by country

The above methods are tier classified, allowing member States to exercise flexibility and select a feasible method. A three-tier classification is proposed, with tier 1 as the preferred method based on the soundness of methodology, data requirements, and expected quality of estimates. Tier 2 is proposed as a fallback option if tier 1 method cannot be applied. If neither are applicable, a tier 3 method could be used.

UNODC has developed and continues to enhance methods to address IFFs from criminal activities, such as smuggling of migrants, drugs trafficking, illegal mining, wildlife trafficking, and corruption, providing guidance and expert support to national authorities undertaking measurement.

The approach taken by UNCTAD and UNODC considers the multi-dimensional nature of IFFs, identifies the main types of IFFs to be measured and lays out a framework in line with existing statistical definitions, classifications and methodologies, in particular with the SNA and BoP.

Work continues to develop a comprehensive classification of IFFs and design methods to aggregate various types of IFFs into a single indicator on IFFs, towards measuring and reporting on SDG indicator 16.4.1.

Granular data held by government agencies needed for reliable measures of IFFs

National statistical systems already have some of the data needed for the measurement of IFFs, but these data are scattered across a range of authorities and domains. For instance, existing national accounts and balance of payments statistics include estimates of illegal economic activities and the non-observed economy; they provide a good starting point for the measurement of IFFs.

Relevant data may be held by the police and ministries and councils of justice, financial intelligence units and other government agencies collecting information on seizures and criminal offences. In addition, tax authorities collect relevant data for assessing the tax gap, and they exchange country-by-country reporting data on multinational enterprises. Customs’ data and statistics on international trade in goods and services provide useful information on commercial IFFs.

Over 60 per cent of national statistical offices collate relevant data on underground, illegal and informal activities using surveys, administrative sources, mirror statistics, international studies and expert assessment -—
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. While these activities are largely domestic, many of them also generate cross-border flows. There are also systematic data collections on crime and related IFFs; UNODC, for instance, compiles statistics on drugs as reported directly by countries, including detailed data on demand, supply, prices, drug characteristics, seizure data, etc.

Compiling statistics on IFFs requires access to many data sources held by different authorities. Central banks, customs, tax authorities and national statistical offices often have the strongest mandate to collect and access such data. Several global databases also contain relevant data for the compilation of IFF estimates, for instance the OECD country-by-country reporting data, UNCTAD Global Transport Costs Dataset for International Trade, the United Nations Comtrade database and the locational banking statistics by the Bank of International Settlements.

Measuring IFFs requires close collaboration within the national statistical system and with administrative data providers. The compilation of SDG indicator 16.4.1 is a technical, statistical activity to be based on statistical considerations only in line with the Fundamental Principles of Official Statistics -—
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. National statistical offices, as the focal point for coordinating the compilation of SDG indicators, should lead and coordinate the work to bring the necessary stakeholders together to measure IFFs.

Country pilots show that illicit financial flows can be estimated

While some elements of IFFs are more readily measurable, others are highly challenging to estimate, including bribery, abuse of functions, illicit enrichment and illicit tax practices. Country pilots are central to building the capacity to measure IFFs and testing the feasibility of measurement.

Pilot studies focus first on types of IFFs that are most prominent in a country and for which data are available. Coverage of different IFFs will be improved gradually along with data improvements. A series of pilot studies have been conducted with partners, UNODC and relevant UN Regional Commissions, in 22 countries to date, and have provided or continue to provide critical information for refining statistical methods to measure IFFs, either in terms of modifying the methodological approach (e.g., due to unreliable quantity information in trade statistics, related proposed reliability weighting procedure for Partner Country Method Plus on trade misinvoicing turned out to be unattainable in parts), or proposing alternative avenues (e.g., inspecting remittance flows), or clearly specifying national adaptations in applying methods. Further refinements are expected after current pilot testing concludes towards the end of 2022.

The first pilots carried out in Latin America between 2018 and 2020, by UNODC, show the way forward for other countries. In the first pilots, Columbia, Peru, Ecuador, and Mexico measured IFFs from selected illegal markets, such as drugs trafficking and smuggling of migrants.6 Estimates in Mexico, for instance, show that an inflow of IFFs equivalent to around $12 billion was generated annually by drug trafficking activities.7 conducted between 2015 and 2018.

Similarly, inward IFFs from cocaine trafficking were estimated for Peru ($1.48 billion annually between 2015 and 2017) and Colombia (range: $1.5 billion - $10.2 billion for 2019). Smuggling of migrants is instead estimated to have generated an annual average of $1.1 billion in inward IFFs for Mexico and $13.6 million outward IFFs for Ecuador (2016-2018 data).

Pilots also addressed the measurement of IFFs from illegal gold mining and trafficking in persons, even if data in such cases did not allow for a sufficiently robust estimate.

In 2021, eleven interested African countries joined the pilot testing of statistical methodologies to measure IFFs with UNCTAD and UNECA focusing on tax and commercial IFFs. UNCTAD and UNODC are also pilot testing IFFs’ measurement with ESCAP and six countries in Asia and the Pacific in 2021–2022, and Egypt is pursuing overall measurement of IFFs in the context of United Nations Joint Fund Support to Egypt for Integrated SDGs Financing8, in collaboration with UNCTAD on tax and commercial IFFs and with UNODC on drud-related IFFs. Map 1 shows countries that have been involved in measurement of IFFs.

Map 1. IFF pioneering and pilot studies carried out and in progress

Source: UNCTAD and UNODC

Note: Situation reflected on the map as in May 2022.

While countries are moving at a different pace, the eleven pilots in Africa will finish in June 2022; Egypt and countries in Asia are expected to produce preliminary results by autumn 2022 and finalise project activities by the end of 2022. Project activities in general start by a review of national circumstances in the form of an IFF risk assessment, followed by a mapping of relevant national stakeholders, a review of data availability and quality; and finally, the pilot calculation of IFF estimates with one or two selected methods. In order to implement the activities, countries form a national technical working group composed of key institutions possessing relevant data and mandates to measure or address IFFs. Tight collaboration among national institutions is key to getting the work done.

Selection of method(s) to measure IFFs depends on types of IFFs that prevail in a country. In the 18 pioneering countries currently measuring IFFs, trade misinvoicing and to a somewhat lesser extent multinational profit shifting are identified for measurement, with many countries focusing on their extractive industries. The choice of the method also depends on data available in the national statistical system and accessible to some members of the technical working group. Moreover, specific economic and market conditions may limit the choice of methods, e.g., specific prominent sectors (e.g., mining) being fully dominated by multinational enterprises, whereby no domestic units could be identified to use a control group.

Preliminary results of pilot testing activities confirm the feasibility of the task, yet challenges in coordinating access and use of data, the collaboration between several entities and the estimation exercise remain. Early feedback shows that support by national consultants, training provided by international organizations and integration of national institutions into the technical working group, are crucial for compiling statistics on IFFs, all this was further complicated by the COVID-19 restrictions in 2021-2022. UNCTAD’s support to pioneering countries in measuring SDG indicator 16.4.1 is discussed in more detail in UNCTAD in Action section on IFFs.

Lastly, countries will prepare an action plan to address gaps to enable regular measurement of IFFs with national statistics. These gaps may refer to unavailability of data, poor basic statistics or lack of integration of data sources. The action plans will be important for raising awareness of decision makers on the needs for investment and support, including from national governments and donors. The feedback from pilots will help refine the Methodological Guidelines and the skills and processes established contribute to future reporting of progress towards SDG target 16.4.

The early pilots developed tools and approaches and tested first methods to measure IFFs. As a result, refined tools and methods can be made available for all interested countries to use globally. In addition, a global UN capacity development project will start in 2023, relying on methodological support, guidance and training by UNCTAD and UNODC. It will be carried out in coordination by UNECA with all UN Regional Commissions. The project will enhance the capacity of developing countries across regions to measure and curb IFFs, enhance investigative and analytical capacities and improve domestic resource mobilisation to strengthen socio-economic resilience to pursue the 2030 Agenda.

UNCTAD and UNODC invite all interested countries to test the measurement of IFFs that affect their economies the most. Estimating IFFs will not only provide clarity on the scope of IFFs, but also help improve the quality of key macroeconomic statistics, such as GDP, by improving their coverage and exhaustiveness.

The statistical Task Force will continue its work to support countries in the pilot testing of the measurement of IFFs with a view to developing a global Statistical Framework for the Measurement of Illicit Financial Flows with practical and methodological guidance in line with the Conceptual Framework. This will include a classification of activities generating IFFs, linked to the SNA and BoP concepts, and recommended methods to measure different types of IFFs in SDG indicator 16.4.1.

Further work will also aim at developing nuanced measurement of IFFs to support policy action and at the same time developing methods to aggregate estimates of different types of IFFs into one SDG indicator, e.g., to adjust for double counting. In the future, the measurement of IFFs as a satellite account taking into consideration national accounts concepts and definitions could be worth exploring.

Notes

  1. The General Assembly resolution “stresses that official statistics and data from national statistical systems constitute the basis needed for the global indicator framework, recommends that national statistical systems explore ways to integrate new data sources into their systems to satisfy new data needs of the 2030 Agenda for Sustainable Development, as appropriate, and also stresses the role of national statistical offices as the coordinator of the national statistical system” -—
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  2. The Task Force is composed of statistical experts from Brazil, Finland, Ireland, Italy, Peru, South Africa and the United Kingdom, representing national statistical offices, central banks, customs or tax authorities. The Task Force also includes experts from international organisations with recognised expertise in this field. ECLAC, ESCAP, Eurostat, IMF, OECD, UNECA, UNSD, UNCTAD and UNODC are represented.
  3. The proposed bottom-up measurement approach considers domestic illicit financial flows as part of the illegal economy. These flows would not fall under the definition of IFFs for SDG indicator 16.4.1 but are of high relevance to understanding organised cross-border illicit flows.
  4. This basic typology is coherent with the main concept of national accounts. Indeed, income generation refers to the set of operations that in national accounts relate to production account, and generation and distribution of income account, while income management refers to the set of operations that in national accounts refer to capital and use of income account.
  5. This approach is consistent with -—
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  6. Preliminary estimates of IFFs from illegal activities resulting from pilot testing in Latin America were presented at a meeting in Latin America in March 2021 -—
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    -—
    – ‒
    - –
    —-
    .
  7. Mexico-US trafficking of cocaine, methamphetamine and heroin.
  8. Under the INFF. Refer to project’s website for more information -—
    – ‒
    - –
    —-
    -—
    – ‒
    - –
    —-
    -—
    – ‒
    - –
    —-
    -—
    – ‒
    - –
    —-
    .

References

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