metadata: authors: 0: author: Maruyama Rentschler,Jun Erik
1: author: Hosoe,Nobuhiro
count: Nigeria
docna: 0: docna: Illicit Schemes : Fossil Fuel Subsidy
            Reforms and the Role of Tax Evasion and Smuggling
docty: Policy Research Working Paper
subtopic: Social Conflict and Violence,Tax Law,Economic Assistance,Access of Poor to Social Services,Disability,Services & Transfers to Poor,Energy and Environment,Energy and Mining,Energy Demand,Energy Policies & Economics
teratopic: Social Development,Law and Development,Macroeconomics and Economic Growth,Social Protections and Labor,Poverty Reduction,Energy
abstracts: cdata!: This study develops a computable general
            equilibrium model for Nigeria, which accounts for
            informality, tax evasion, and fuel smuggling. By studying
            the impact of fuel subsidy reform on consumption, tax
            incidence, and fiscal efficiency, it shows that the presence
            of illicit activities substantially strengthens the argument
            in favour of subsidy reform: First, fuel subsidy reform can
            shift the tax base to energy goods, which are less prone to
            tax evasion losses than for instance labour. Second, by
            reducing price differentials with neighbouring countries,
            subsidy reform reduces incentives for fuel smuggling.
            Overall, the results show that considering illicit
            activities reduces the welfare losses of fuel subsidy reform
            by at least 40 percent. In addition, fuel subsidy reductions
            (and by extension energy tax increases) have a strong
            progressive distributional impact. The findings hold under
            different revenue redistribution mechanisms, in particular
            uniform cash transfers and the reduction of pre-existing
            labour taxes.
geo_reg_key: 1927320,517191
repnme: repnme: Illicit Schemes : Fossil Fuel Subsidy
            Reforms and the Role of Tax Evasion and Smuggling
display_title: Illicit Schemes : Fossil Fuel
            Subsidy Reforms and the Role of Tax Evasion and Smuggling
listing_relative_url: /research/2022/01/33709135/illicit-schemes-fossil-fuel-subsidy-reforms-role-tax-evasion-smuggling
topicv3: Energy and Extractives m1326595 507,Fuel Subsidies m1327095 1628,Cash Transfers m1327437 1608,Tax Crime m1327485 2075,Counterfeit Goods m1327550 2454
publishtoextweb_dt: 2022-01-20T00:00:00Z
dois: 10.1596/1813-9450-9907
historic_topic: Social Development,Law and Development,Macroeconomics and Economic Growth,Social Protections and Labor,Poverty Reduction,Energy
origu: Off of Sr VP Dev Econ/Chief Econ (DECVP)
no_of_pages: 48
author_keys: 0: author_key: 1217979
1: author_key: 867222
model_extractions: Policy Research Working Paper 9907

# Illicit Schemes

Fossil Fuel Subsidy Reforms and the Role of Tax Evasion and Smuggling _Jun Rentschler Nobuhiro Hosoe_ Urban, Disaster Risk Management, Resilience and Land Global Practice January 2022
Policy Research Working Paper 9907

# **Abstract**

This study develops a computable general equilibrium model for Nigeria, which accounts for informality, tax evasion, and fuel smuggling. By studying the impact of fuel subsidy reform on consumption, tax incidence, and fiscal efficiency, it shows that the presence of illicit activities substantially strengthens the argument in favour of subsidy reform: First, fuel subsidy reform can shift the tax base to energy goods, which are less prone to tax evasion losses than for instance labour. Second, by reducing price differentials with neighbouring countries, subsidy reform reduces incentives for fuel smuggling. Overall, the results show that considering illicit activities reduces the welfare losses of fuel subsidy reform by at least 40 percent. In addition, fuel subsidy reductions (and by extension energy tax increases) have a strong progressive distributional impact. The findings hold under different revenue redistribution mechanisms, in particular uniform cash transfers and the reduction of pre-existing labour taxes.

This paper is a product of the Urban, Disaster Risk Management, Resilience and Land Global Practice. It is part of a larger effort by the World Bank to provide open access to its research and make a contribution to development policy discussions around the world. Policy Research Working Papers are also posted on the Web at http://www.worldbank.org/prwp. The authors may be contacted at jrentschler@worldbank.org.

_The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent._ Produced by the Research Support Team
# Illicit schemes: Fossil fuel subsidy reforms and the role of tax evasion and smuggling

## Jun Rentschler<sup>1, 2, 3</sup> , Nobuhiro Hosoe<sup>3</sup>

> _1The World Bank, Office of the Chief Economist for Sustainable Development, USA_

> _2University College London, Institute for Sustainable Resources, UK_

> _3National Graduate Institute for Policy Studies, Japan_

_Keywords:_ Fossil fuel subsidies, tax evasion, smuggling _JEL classification:_ C68, O13, Q58, H23

**Acknowledgements:** The authors would like to thank Raimund Bleischwitz, Richard Damania, Paul Ekins, Florian Flachenecker, Michael Grubb, St ́ephane Hallegatte, Dirk Heine, Masami Kojima, Samer Matta, Victor Nechifor, Lars Nesheim, Gregor Schwerhoff, and Adrien Vogt-Schilb for helpful comments and discussions on previous versions of this paper. JR is grateful to the National Graduate Institute for Policy Studies in Tokyo for hosting him as a Visiting Researcher for the purpose and duration of this study. The authors gratefully acknowledge that this work was supported by a JSPS KAKENHI Grant (No. 16K03613). Listed affiliations include former ones that were active while the study was being conducted.

> _∗_ Corresponding author: jrentschler@worldbank.org
# **1. Introduction**

Global subsidies to fossil fuel consumption amounted to $493 bn in 2014 (IEA, 2015) – i.e. exceeding the climate finance commitment of $100 bn agreed under the Paris Agreement by a factor five. As the IMF (2013) outlines, the true economic and societal cost is bound to be far higher than this figure, since fossil fuel subsidies (FFS) cause countless adverse effects, including the lock-in of inefficient technology and behaviour, crowding out of funds for public spending such as education and health care, erosion of competitiveness, exacerbating environmental pressures, and regressive wealth transfer to the rich (Rentschler and Bazilian, 2016; Coady et al., 2017). In addition to these adverse effects, FFS are also frequently argued to be associated with illicit activities, including corruption, fuel smuggling, and tax evasion. However, no systematic study exists exploring the role of such activities in determining the outcomes FFS reforms.

Against this background, this study develops a dedicated computable general equilibrium (CGE) model to study FFS reform, calibrated to reflect the characteristics of Nigeria. It introduces several innovative model features, including a large informal sector, evasion of labour and production taxes, and fuel smuggling. More specifically, this study addresses the following interrelated questions: (i) What are the effects of FFS reform on key economic parameters, including income distribution, consumption, and output? (ii) How do effects differ when illicit market activities are taken into account, in particular tax evasion and rampant fuel smuggling? (iii) How do effects differ when FFS are not only removed, but replaced by fuel taxes? (iv) How do different methods of revenue re-distribution affect households?

Drawing on the environmental and carbon tax literature (in particular the “double dividend” field), this study also considers the role of labour tax reductions as a way of re-distributing FFS reform revenues. This is in addition to considering cash transfers, which the existing literature on FFS reforms has focused on predominantly. Conceptually, these two approaches have different advantages: Reducing FFS and redistributing revenues using cash transfers has a strong progressive distributional effect. Reducing FFS and redistributing revenues by cutting labour taxes increases fiscal and economic efficiency, as distortive preexisting taxes are reduced.

By introducing the novel model features on fuel smuggling and tax evasion, this study is able to analyse additional perspectives on these arguments:

- _Fuel smuggling:_ FFS cause rampant fuel smuggling to neighbouring countries, meaning that a significant fraction of FFS benefits leaks out of the country. Replacing FFS with cash transfers is not only progressive, but terminates smuggling; i.e. the government can disburse the same aggregate benefit to the population at a lower cost.

- _Tax evasion:_ Labour taxes not only distort incentives to work, but are associated with high evasion rates and incentivise informal economic activity. Reducing FFS and using revenues to lower labour tax rates not only mitigates labour market distortions, but reduces overall tax evasion; i.e. the government can earn the same level of tax revenues, while charging lower tax rates.

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Overall, this study finds that replacing FFS with cash transfers results in substantial progressive redistribution. While the top income quintile incurs a reduction in consumption, all other income quintiles gain, with the poorest income quintile benefitting from the largest relative consumption increase. Moreover, using revenues from FFS reform to cut labour taxes results in an improvement of fiscal efficiency. Crucially, this study finds that taking into account illicit activities can lower the social welfare costs of FFS reform by up to 40% in Nigeria. Moreover, by going beyond FFS reform and also considering the introduction of fuel taxes, this study finds that the above mentioned benefits can be extended further: A revenue neutral shift of the tax base from income to fuel taxes can significantly reduce illicit activities and their associated welfare costs. However, this move may also incentivise a reversal of the fuel smuggling direction from out- to inbound.

The remainder of this paper is organised as follows: Section 2 discusses the relation of this study to prior literature on FFS, environmental tax reform, tax evasion, and smuggling. Section 3 provides a brief conceptual outline of the social welfare implications of tax evasion and fuel smuggling. Section 4 provides information on the Nigerian FFS scheme. Section 5 offers a detailed account of the CGE model set-up. Section 6 outlines data sources, while Section 7 outlines the simulation scenarios considered in this study, and the measures used for evaluating social welfare and fiscal efficiency. Section 8 presents the results, and Section 9 concludes.

# **2. Relation to prior literature**

# _2.1. Fossil fuel subsidies_

Often used as a political tool, FFS have been justified by objectives such as alleviating poverty, redistributing natural resource revenues to citizens, moderating energy price shocks, and promoting industrialization and economic development (Strand, 2013; Kojima, 2016; Yau and Chen, 2021).

However, numerous case studies have helped to document that FFS are a very ineffective way of achieving these objectives, and cause a wide range of adverse side effects pertaining to all dimensions of sustainable development: economic, social, and environmental (Rentschler and Bazilian, 2016). These side effects include economic and technological inefficiency, fiscal imbalances, crowding out of public funds for innovation and social services, pollution, climate change, fuel smuggling, and corruption (IMF, 2013; Coady, Parry, Sears and Shang, 2015; Coady, Flamini and Sears, 2015; ADB, 2015).

In addition to the fiscal pressure they place on national budgets, FFS are also particularly problematic because of their highly regressive nature. In reviewing FFS schemes in a range of developing countries, Arze del Granado et al. (2012) found that the top income quintile receives on average six times more in absolute subsidy benefits than the poorest income quintile. In this way, FFS continuously reinforce and exacerbate existing patterns of income and wealth inequality. A comprehensive overview of FFS definitions, adverse side effects, reform progress and barriers is provided by Rentschler and Bazilian (2016).

In light of mounting evidence in favour of FFS reform, a key question for policy makers has been _how_ to design and implement reforms in a way that ensures 3
public support for reform and protects livelihoods of vulnerable households. In this context, ex-ante simulations of FFS reforms have been particularly important in understanding the potential socio-economic consequences of reforms. This in turn has been critical for designing effective social protection and compensation measures alongside FFS reforms. Broadly speaking, such studies on FFS removal have used either econometric approaches or general equilibrium models.

# _2.2. Fossil fuel subsidy reform simulations_

Econometric reform simulations typically focus on changes in household consumption, and are useful for understanding the welfare and distribution effects of FFS reform (Verme and El-Massnaoui, 2015; Rentschler, 2016). Various empirical ex-ante impact assessments of FFS reforms have provided detailed assessments of the welfare impacts of FFS reforms, and highlight the need to provide adequate social protection (e.g., in the form of cash compensation) along with FFS reform (Coady et al., 2010; Zhang, 2011; Anand et al., 2013; Araar et al., 2015; Bah and Saari, 2020)<sup>1</sup> .

Both the IMF and World Bank provide analytical toolkits for the empirical simulation of FFS reforms using household expenditure surveys and input-output models (Verme and El-Massnaoui, 2015; IMF, 2016). The approach taken by these models enables swift and consistent analyses with relatively few data requirements (Rentschler, 2016).

However, as Plante (2014) points out, these models also strongly simplify complex interactions, as they overlook the fiscal policy and general equilibrium perspective on subsidies: These models focus exclusively on the fact that the removal of FFS leads to energy price shocks, which in turn reduce purchasing power and aggregate consumption of households. Thus, FFS removal necessarily and exclusively has negative consequences, while benefits such as reduced deadweight losses or increased economic efficiency are not taken into account. Similarly, general equilibrium effects on key macro-economic parameters cannot be captured in models based on household surveys, including changes in government expenditure, output, and tax revenues.

To address the above mentioned shortcomings, Plante (2014) developed a general equilibrium model aimed at capturing the fiscal policy aspect of FFS reform. It is a standard small open economy model with two sectors, and a single representative household. FFS reductions are balanced in the government’s budget constraint through tax adjustments or lump-sum cash transfer provision. Using this model, it is shown that FFS cause distortions of relative prices, which are identified as the main reason for substantial aggregate welfare losses. Moreover, FFS are shown to aggravate fiscal imbalances, crowd out non-energy consumption, and cause inefficient allocation of labour across sectors, regardless of whether the country is an oil importer or exporter (Plante, 2014).

Several general equilibrium models have followed: Durand-Lasserve et al. (2015) offer an analysis for Indonesia based on the OECD’s ENV-Linkages model, a

> 1For additional empirical impact assessments of FFS reforms, see Jiang et al. (2015) and Ouyang and Lin (2014) for China, and Solaymani and Kari (2014) for Malaysia.

4
global CGE model. This study focusses in particular on distributional effects of FFS reform, considering redistribution of reform revenues through cash transfers or food subsidies. Siddig et al. (2014) use the CGE model by the Global Trade Analysis Project (GTAP) to analyse subsidy reform in Nigeria. They distinguish 12 households, each representing a region rather than an income group. Using this set-up they consider the impact of FFS reform on several standard macro-economic parameters, such as consumption and GDP. For Pakistan, Feltenstein and Datta (2020) assess electricity subsidy reform and revenue redistribution through targeted transfers, and find increases in the real incomes of poor households. Shehabi (2020) develops a general equilibrium model for Kuwait featuring an oligopolistic industrial structure and studies how subsidy reform affects sectoral diversification.

While the above mentioned models differ in the complexity of their modeling set-ups, they coincide in their focus on standard macro-economic parameters, in particular output, consumption, trade and fiscal balances, and income distribution. They do not consider illicit activities in any way.

# _2.3. The double dividend_

There is a prominent strand in this literature suggesting that there is a “double dividend” – i.e., that if environmental taxes are increased, but other distortionary taxes are reduced (while maintaining revenue neutrality), then not only can environmental benefits be reaped, but also fiscal efficiency can be increased (Goulder, 1995 _a_ ; Fullerton and Metcalf, 1997; Bovenberg, 1999). However, Parry and Williams (2010) also show that there is a considerable trade-off between efficiency and distributional effects. That is, income tax reductions are economically efficient, but regressive, while cash transfers are progressive, but less efficient.

Since FFS are (at least theoretically) equivalent to a negative carbon tax, the double dividend argument deserves thorough consideration in the context of FFS reforms. Especially given the significant economic efficiency costs of labour and consumption taxes (Bovenberg and Goulder, 1996; Parry, 1997; Goulder, 1995 _b_ ), there may be a rationale for using FFS reform revenues to reduce these taxes. However, instead of reducing pre-existing taxes, past reforms and associated analyses have focused almost exclusively on cash transfers for revenue redistribution.

# _2.4. Tax evasion and smuggling_

More recent studies have contributed an additional perspective, which strengthens the double dividend argument. Liu (2013) observes that energy (or carbon) taxes are more difficult to evade than labour or income taxes. Using a simple CGE model, the author shows that a revenue neutral shift from labour to carbon taxes can substantially reduce tax evasion and the welfare cost of climate change mitigation policy<sup>2</sup> . Especially when pre-existing tax evasion is high, this argument can significantly strengthen both the environmental and fiscal cases for carbon taxes (Liu, 2013; Bento et al., 2013; Carson et al., 2014).

> 2Liu (2013) shows that costs can be lowered by 89% in China and 97% in India.

5
Even though tax evasion tends to be particularly high in developing countries – large informal sectors are symptomatic of this – the “tax evasion effect” has not been studied in the context of FFS reform. Similarly, despite being a frequently cited side-effect of fossil fuel subsidies, smuggling has also received little attention from researchers. As subsidised fuels are smuggled out of a country, the government is directly subsidising fuel consumption in neighbouring countries; in other words public funds intended for domestic beneficiaries are continuously leaking out of the country (ADB, 2015). A study by Mlachila et al. (2016) is likely to be the ony one that systematically analyses the magnitude and implications of fuel subsidies on smuggling activities. They show that fuel smuggling can severely undermine the effectiveness of fuel price adjustment mechanisms and energy tax collection, when neighbouring countries subsidise their domestic fuel consumption.

The model presented in this study contributes to the literature on FFS reform and the double dividend, by providing a systematic account of tax evasion, the informal sector, and fuel smuggling in the case of Nigeria. These issues are of great significance in developing countries, especially when considering that the informal economy in Nigeria is estimated at 50% of GDP, and that 85% of fuel consumed in Benin is smuggled from (and thus subsidised by) Nigeria (Mlachila et al., 2016; Hassan and Schneider, 2016).

# **3. The societal cost of illicit activities**

This section provides conceptual detail on the argument underlying this paper. More specifically, it briefly discusses the welfare costs associated with tax evasion and smuggling activities.

A key assumption by Liu (2013) is that tax evasion (and legal tax avoidance) activities incur real costs. The reason for this is that tax evasion efforts require real resources, and thus compete for production factors with real productive activities (ADB, 2015). Bribes paid to tax officials, the employment of tax lawyers and advisors, labour hours spent on avoiding tax audits, or the complex shifting of profits between international subsidiaries are examples of costly tax avoidance or evasion activities. In addition, taxes may reduce economic efficiency by distorting business decisions and production processes. In practice, the increased need for fiscal audits and monitoring may also impose a costly burden on authorities. Overall, tax evasion imposes real costs on society, not only because productive resources are allocated to unproductive evasion activity, but also because of foregone tax revenues.

Analogously, fuel smuggling activities also represent a loss to society. Fuel subsidies that are intended for the benefit of a country’s own citizens are smuggled abroad; in other words, the government is directly subsidising the fuel consumption by foreign consumers. In addition, the smuggling activity itself incurs real economic costs, as significant resources are used on transporting fuel, and avoiding and bribing border and customs controls (Mlachila et al., 2016).

A key argument considered in this study is that reducing FFS and using revenues to cut distortionary labour taxes can be welfare-enhancing, since welfare losses associated with smuggling and tax evasion are also reduced. In line with Parry 6
and Williams (2010), this study contrasts such labour tax cuts with other ways of recycling reform revenues: increasing public expenditure, or the provision of uniform lump-sum transfers to citizens.

# **4. Background: Fuel subsidies in Nigeria**

As a developing country with substantial fossil resource wealth and a mixed track record of fiscal prudence and transparency, Nigeria is a frequently cited case for studying FFS and natural resource management (Rentschler, 2016). Nigeria is the fifth largest oil exporter in the world (World Bank, 2015; IMF, 2013). Yet, only 55% of Nigerians have access to electricity (34% in rural areas); annual per capita electricity consumption in 2012 was 155 kWh (compared to 4,405 kWh in South Africa). Chronic underinvestment and corruption in the electricity sector mean that the average Nigerian enterprise experiences over 36 power outages a month. Problems also plague the country’s four national oil refineries, which operate at just 20% to 30% capacity. While over 70% of fuel consumption is met by imports, shortages are endemic (World Bank, 2015; IMF, 2013).

Through the Petroleum Products Pricing Regulatory Agency, Nigeria maintains artificially low fuel prices, specifically petrol. The gap between fuel import costs and regulated prices are financed through the Petroleum Support Fund, which administers fuel subsidies<sup>3</sup> . Nigeria does not provide significant subsidies to fuels other than petrol.

At about 3% of GDP in 2011 subsidies are a significant expense for the government, and fail to reach Nigerians in more than one sense (NEITI, 2013; IMF, 2013; Soile and Mu, 2015): As with all FFS schemes, the direct financial benefits to households are concentrated on the rich, thus failing to benefit the absolute poor (who constitute 61% of the population<sup>4</sup> ). In addition, a complex and opaque system of intermediary dealers and political influence means that, instead of lowering the market price, subsidies are often privately appropriated before the fuel reaches the market. Finally, rampant fuel smuggling means subsidy benefits are leaking out of the country.

Facing mounting fiscal pressures and recognising the inefficiencies of its subsidy scheme, Nigeria attempted a radical subsidy reform in 2012. While the need for such reform was pressing, the government failed to garner sufficient public support for its reform efforts. Public opposition to the reform had two key reasons in particular: (i) A lack of credibility and transparency with respect to the handling of reform revenues, and (ii) inadequate plans for compensation and social protection, resulting from a poor understanding of the needs and vulnerability of affected consumers. Subsidy removal was met with extensive

> 3The Petroleum Support Fund is managed by the Petroleum Products Pricing Regulatory Agency, and receives a set allocation in the federal budget. Contributions to the fund are made by the federal, state, and local governments. Moreover, the fund is supplemented by subsidy “surpluses”, which essentially occur when international market prices exceed the government-set fuel price (GSI, 2012).

> 4This figure is based on the national absolute poverty definition, using an absolute poverty line of N54,401 (National Bureau of Statistics, 2010)

7
strikes and violent public protests, and prompted the government to swiftly reintroduce subsidies (Bazilian and Onyeji, 2012; Siddig et al., 2014).

# **5. Set-up of the illicit activities model**

The basic structure of this model builds on Hosoe et al. (2010), who offer a small open economy CGE model featuring a representative household, two sectors, and a government. The model developed for the purpose of this study is a static small open economy model, featuring multiple representative households (representing five income quintiles), firms, and a government. The government collects taxes on production, factor usage, and imports, as well as direct taxes on households, and disburses FFS.

Moreover, the model adds several non-standard features: A small group of households is modeled to engage in fuel smuggling activities. The profits of smuggling depend on the price differential between the domestic and international price of fuel, which is determined through the level of subsidies paid. The model also allows for the evasion of production and factor taxes. In order to represent different policy options for using reform revenues, the model considers (1) government expenditure, (2) direct cash transfers, and (3) reductions of pre-existing taxes, such as labour or production taxes.

# _5.1. Tax evasion: Representation in the model_

In this model it is assumed that firms choose to evade taxes on different factors and on production, while incurring a real cost of evasion. Formally, factor taxes _τh,j_<sup>_f_onfactor</sup><sup>_h_andsector</sup><sup>_j_areevadedattherate</sup><sup>_ef_</sup> _h,j_<sup>.Similarly,production</sup> taxes _τj_<sup>_z_are evaded at the rate</sup><sup>_ez_</sup> _j_<sup>.In line with Liu (2013), tax evasion activities</sup> incur real costs _F_<sup>_loss_</sup> and _X_<sup>_loss_</sup> : _h,j j_ This setting implies that the cost of tax evasion is measured as a share _c_ ( _e_ ) of either factor inputs _Fh,j_ (in the case of factor tax evasion) or production _Zj_ (for production tax evasion). Parameters _A_<sup>_f_</sup> _h,j_<sup>,</sup><sup>_Az_</sup> _j_<sup>,</sup><sup>_N_</sup> _h,j_<sup>_f_,and</sup><sup>_N_</sup> _j_<sup>_z_characterisethe</sup> cost function and are determined during calibration. The total net benefit to firm _j_ from evading factor taxes is<sup>�</sup> _h_<sup>_Fh,j_(</sup><sup>_τ f_</sup> _h,j_<sup>_ef_</sup> _h,j_<sup>_p_</sup> _h_<sup>_f−c_(</sup><sup>_ef_</sup> _h,j_<sup>)).</sup> Evasion losses reflect the extra (unproductive) “self-input” due to evasion efforts. Specifically, if a firm engages in evasion activities, a share of its resources will be directed towards this evasion activity rather than production (e.g. labour hours). This unproductive evasion activity means that fewer resources are available for producing output, thus resulting in the output loss _Xj_<sup>_loss_</sup> .

8
Moreover, the marginal costs of evading taxes can be expressed as Since these marginal costs are increasing in _e_<sup>_f_</sup> _h,j_<sup>or</sup><sup>_ez_</sup> _j_<sup>, firms choose evasion rates</sup> and factor input quantities as to maximise profits (Section 5.3).

# _5.2. Smuggling: Representation in the model_

In practice, fuel subsidies often incentivise smuggling, as subsidised domestic fuel prices are significantly lower than in neighbouring countries, where fuel prices are unregulated. This price gap presents a lucrative opportunity for smugglers, who buy fuel at the subsidised domestic price and sell it abroad at the unregulated market price. However, in doing so smugglers are likely to incur real costs, e.g. in the form of bribes or transport costs (Mlachila et al., 2016).

For the sake of consistency, this model not only allows such _outbound_ smuggling (smuggling “exports”); it also considers the possibility of _inbound_ smuggling (“imports”), which may occur by the same logic when domestic fuel subsidies are removed and fuel taxes imposed.

In this model, smugglers are assumed to choose the ( _outbound_ ) smuggling quantity _Ej_<sup>_SM_</sup> (“exports”) as to maximise their profit. They purchase fuel for smuggling in the domestic market at the subsidised price (1 _− s_<sup>_e_</sup> _j_<sup>)</sup><sup>_pq_</sup> _j_<sup>(where</sup><sup>_se_</sup> _j_<sup>isthe</sup> subsidisation rate), and sell it abroad at the export price _p_<sup>_e_</sup> _j_<sup>.In addition,smug-</sup> glers incur smuggling costs _Ej_<sup>_loss_</sup> , e.g. transportation costs. Analogously, they may also choose to conduct _inbound_ smuggling _Mj_<sup>_SM_</sup> (“imports”). In this case they will purchase fuel abroad at the import price _p_<sup>_m_</sup> _j_<sup>, and sell it domestically at</sup> the composite good price _p_<sup>_q_</sup> _j_<sup>,whichissubsidised(ortaxed)attherate(1</sup><sup>_−se_</sup> _j_<sup>).</sup> Thus, the smugglers optimisation problem is given by _Ej_<sup>_SM_</sup> (or _Mj_<sup>_SM_</sup> ) denotes the smuggled quantity from sector _j_ , while the total cost of smuggling is denoted by _Ej_<sup>_loss_</sup> (or _Mj_<sup>_loss_</sup> ) expressed as a share of the total smuggled quantity. The shape of the cost function is characterised by parameters _A_<sup>_SM_</sup> _j_ and _r_ , both of which are determined during calibration<sup>5</sup> .

> 5A sensitivity analysis for these parameters is provided in Appendix C.

9
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_Xi,j_ (priced at _p_<sup>_q_</sup> _i_<sup>)andofthecompositefactor</sup><sup>_Yj_(pricedat</sup><sup>_py_</sup> _j_<sup>)intooutput</sup><sup>_Zj_</sup> (priced at _p_<sup>_z_</sup> _j_<sup>).Equations12and13representthetechnologicalconstraintsin</sup> the first and second production stage in the form of Cobb-Douglas and Leontief production functions. Equations 14 represent the optimal evasion rates for factor ( _e_<sup>_f_</sup> _h,j_<sup>) and production taxes (</sup><sup>_e_</sup> _j_<sup>_z_), which are increasing in their corresponding tax</sup> rates _τ_ .

Production factor _h_ is priced at _p_<sup>_f_</sup> _h_<sup>,andtheArmingtoncompositegood</sup><sup>_Qi_is</sup> priced at _p_<sup>_q_</sup> _i_<sup>.Thecompositefactor</sup><sup>_Yj_isproducedinthefirstproductionstage,</sup> and is priced at _p_<sup>_y_</sup> _j_<sup>.</sup><sup>_βh,j_isthe elasticity parameter in the first-stage production</sup> function, and _bj_ an efficiency parameter. Moreover, _axi,j_ (or _ayj_ ) is the input requirement coefficient of the _i_ -th intermediate input (or _j_ -th composite factor) for one unit of the output _j_ .

# _5.4. Government_

The government in this model takes the role of levying taxes, consuming goods, and providing subsidies and direct cash transfers. Formally, government consumption _Xi_<sup>_g_isasumofitsrevenuesfromdifferenttaxsources,netofsubsidy</sup> payments ( _Sf_<sup>_e_)andcashtransfers(</sup><sup>_Cttax_</sup> _l_ ): where the share of the _i_ -th good in government expenditure is denoted _μi_ . Direct taxes _Tl_<sup>_d_areleviedonthefactorendowment</sup><sup>_FFh,l_ofhousehold</sup><sup>_l_attherate</sup> _τl_<sup>_d_.</sup> Factor taxes _Th,j_<sup>_f_areleviedonfirms’factorinputsattherate</sup><sup>_τ f_</sup> _h,j_<sup>andare</sup> subject to evasion.

Production taxes _Tj_<sup>_z_areleviedonoutput</sup><sup>_Zj_byfirm</sup><sup>_j_attheeffectivetaxrate</sup> (1 _− e_<sup>_z_</sup> _j_<sup>)</sup><sup>_τ z_</sup> _j_<sup>afterevasion.</sup> Import taxes are levied on imports _Mj_ at the rate _τj_<sup>_m_.</sup> Besides public expenditure on goods ( _Xi_<sup>_g_), the government also provides energy</sup> 11
(sy) ~~—(~~ x ) (Xs yy Y EY > y )

>
for the evasion of production taxes, and for factor tax evasion. The benefits of tax evasion are distributed across households according to redistribution rules _Rl_<sup>_z_and</sup><sup>_R_</sup> _l_<sup>_f_.Thenumericalvaluesof</sup> these parameters are chosen to reflect the distribution of consumption and factor endowments.

In addition to the five households, this model considers a smuggler who consumes the same goods as all other households, but earns income from fuel smuggling activities. Thus, the smuggler’s budget constraint prescribes that his consumption expenditure equals smuggling profits: The smuggler’s share parameter _αj_ is calibrated according to the share parameter of the 2<sup>_nd_</sup> income quintile household. This choice reflects anecdotal evidence that fuel smuggling is typically done by low income households (Mlachila et al., 2016), but the relatively small number of smugglers means that this parameter is inconsequential for overall results. Note that for consistency, the above notation allows smuggling in all sectors _j_ , yet the empirical evidence suggests that it is a relevant consideration mainly in the petrol sector.

# _5.6. Exports, imports, and the balance of payments_

For considering the implications of cross-border smuggling, the use of an open economy model is necessary. This section briefly sets out the interaction between the model economy and the rest of the world. For this purpose a small open economy set-up is used, which implies that import and export prices (denominated in foreign currency terms) are exogenously given. Formally, domestic import ( _p_<sup>_m_</sup> _i_<sup>)andexportprices(</sup><sup>_pe_</sup> _i_<sup>),arelinkedtotheircorrespondingworld</sup> prices ( _p_<sup>_W m_</sup> _i_ and _p_<sup>_W e_</sup> _i_ ) through the exchange rate _ε_ .

The balance of payments condition requires that monetary outflows (i.e. due to imports _Mi_ , and inbound smuggling _Mi_<sup>_SM_</sup> and _Mi_<sup>_loss_</sup> ) equal inflows (i.e. exports _Ei_ , “foreign savings” or the current account deficit _Ss_<sup>_f_</sup> , and gross earnings from the foreign sale of smuggled fuel _Ei_<sup>_SM_</sup> ).

Details on the substitution and transformation of traded goods are provided in Appendix A.3.

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# _5.7. Market clearing_

Two equilibrium conditions are needed to ensure the equivalence of demand and supply in goods and factor markets. For the goods market: This condition implies that the supply of the _i_ -th Armington composite good _Qi_ must equal its aggregate demand. Demand is composed of demand by households ( _Xi,l_<sup>_p_), the government (</sup><sup>_X_</sup> _i_<sup>_g_), investment (</sup><sup>_X_</sup> _i_<sup>_v_), firms (</sup><sup>_Xi,j_), and the smug-</sup> gler ( _Xi_<sup>_SM_</sup> ); in addition some of the goods are lost as inputs to tax evasion ( _Xi_<sup>_loss_</sup> ) and smuggling ( _Ei_<sup>_loss_</sup> ) activities.

For the factor market, the sum of endowments of the _h_ -th factor ( _FFh,l_ ) must equal the aggregate factor demand: Note that firms’ total factor demand is the sum of standard factor demands for production ( _Fh,j_ ) and factors used for the purpose of tax evasion activities (e.g. labour), denoted _Fh,j_<sup>_loss_.</sup>

# **6. Data**

# _6.1. Economic variables_

The baseline values for macro-economic parameters have been obtained from the GTAP 9 database – in particular, Nigeria’s social accounting matrix (SAM) for the 2011 reference year. These macro-economic parameters are the size of economic sectors (i.e. output), intermediate inputs, capital and labour inputs, taxes, government expenditure, household consumption, imports, exports, and the current account balance. Four sectors are distinguished: (i) the (subsidised) petrol sector, (ii) the (unsubsidised) energy sector, which excludes petrol, (iii) the formal (non-energy) sector, and (iv) the informal (non-energy) sector. The parameters and coefficients _αi,l_ , _βh,j_ , _bi_ , _γi_ , _μi_ , _λi_ , _θi_ , _axi,j_ , _ayj_ , _δmi_ , _δdi_ , _ξei_ , _ξdi_ , _sspl_ , and _ssg_ have been calibrated on the basis of the 2011 baseline data, and the model equations set out in Section 5.

Since the GTAP 9 SAM does not provide information on the distribution of income and consumption, aggregate household consumption figures have been split into income quintiles according to expenditure shares contained in the Harmonised Nigeria Living Standards Survey 2010. Across income quintiles, this household expenditure survey provides details on the level of spending on petrol, other energy, and non-energy consumption goods. It is thus essential for the distributional aspects considered in this study.

Data on FFS in Nigeria have been obtained from the International Energy Agency’s World Energy Outlook 2015 Fossil Fuel Subsidies database (IEA, 2015). The IEA provides an estimate of $7.1 bn of fossil fuel consumption subsidies in 2011, of which over $6.5 bn are paid to subsidise oil (primarily 14
petrol)<sup>7</sup> . This figure, in combination with the estimated size of the petrol sector, translates to a baseline subsidisation rate of 17.8%. Official (subsidized) petrol prices were set at N65/liter in 2011. This price creates incentives for a variety of illicit activities and commercial malpractice, including smuggling and black market sales which exploit local petrol shortages. As a consequence, actual petrol prices observed by households are often significantly higher than N65/liter (Kojima, 2016).<sup>8</sup> Nevertheless, observed petrol prices in Nigeria are still lower than in neighbouring countries, thus preserving an incentive for smuggling. Finally, population data has been obtained from the World Bank’s World Development Indicators database.

# _6.2. Tax evasion_

For the purpose of comparing sectors with high and low tax evasion, Liu (2013) uses the self-employment rate of an economy to approximate the size of the high-evasion sector. This approach works particularly well in developed and emerging economies, for which reasonably reliable estimates of self-employment are available from sources such as the International Labour Organization (ILO). However, the ILO’s Labour Statistics database offers no estimate of the selfemployment rate in Nigeria.

Instead of relying on uncertain alternative estimates for self-employment, this study uses the size of the informal sector as a proxy for the high-evasion sector. The advantage of this approach is that estimates of informal economic sectors exist for a wide range of countries – including developing countries. Specifically, the formal economy estimates from the GTAP 9 database are supplemented by including an informal sector, which in 2011 measured 50% of GDP according to the comprehensive analysis by Hassan and Schneider (2016).

This study uses a very conservative estimate of 2% for the tax evasion rate in the formal economy. For comparison, Liu (2013) uses a 5% evasion rate in a selection of 27 developed and emerging economies, based on estimates by Slemrod (2007). The Swedish National Tax Agency (2008) reports a 4.8% evasion rate for income taxes in its jurisdiction. In line with the notion of informality, this study assumes that the informal sector does not pay any taxes. Moreover, this study uses the conservative assumption by Liu (2013), that 10% of evaded taxes are spent on non-productive evasion activities (see Section 3). The net benefits of tax evasion are assumed to ultimately accrue to households; in line with the distribution shares of regular income, the top income quintile is assumed to benefit disproportionately more than lower quintiles.

Based on these numbers, the evasion parameters _A_<sup>_f_</sup> _h,j_<sup>,</sup><sup>_N_</sup> _h,j_<sup>_f_,</sup><sup>_Az_</sup> _j_<sup>,and</sup><sup>_N_</sup> _j_<sup>_z_are</sup> calibrated to characterise the evasion cost functions (Eq. 1 and 2).

> 7To make subsidy estimate comparable across countries, the IEA applies some aggregation and simplification assumptions. This results in a lower subsidy estimate than provided by the Nigeria Extractive Industries Transparency Initiative (NEITI, 2013), which estimates total subsidy payments in 2011 to be $12.4 bn. Of this sum, $7.3 bn were paid through the Petroleum Product Pricing Regulatory Agency (PPPRA) and $5.1 bn through the Nigerian National Petroleum Corporation (NNPC).

> 8The National Bureau of Statistics only reports observed petrol prices since 2014, hence we apply a 50% mark-up as a simplifying assumption for household petrol consumption.

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# _6.3. Smuggling_

This section outlines the steps taken to estimate the baseline magnitude of fuel smuggling out of Nigeria to neighbouring countries.

_The first step_ is to focus on smuggling activity from Nigeria to Benin (and from there to Togo), as detailed estimates are available from the IMF (Mlachila et al., 2016). While Togo does not share a border with Nigeria, its distance to the Nigerian border is under 120 km, and thus extensive smuggling occurs via Benin. The IEA (2016) reports total gasoline consumption for Benin (616 k tonnes) and Togo (175 k tonnes) in 2011. Mlachila et al. (2016) outline that in both Benin and Togo respectively, gasoline is sold on two separate markets: an official market for the sale of legal and regulated gasoline, as well as an informal market for the sale of gasoline smuggled from Nigeria. Mlachila et al. (2016) estimate that the informal market constituted about 85% of total gasoline consumption in Benin in 2011, and 70.7% in Togo. These figures enable the computation of the absolute size of the informal markets (in physical units), which reflects the quantity of fuel smuggled across the Benin-Nigeria border.

The revenues earned by smugglers are then estimated by multiplying the total smuggled quantity of gasoline with the respective price differential between Nigeria’s official subsidised market price and Benin’s (or Togo’s) informal market price. These informal market prices are also reported by Mlachila et al. (2016).

_The second step_ is to extrapolate the smuggling estimates for Benin (and Togo) to Nigeria’s remaining neighbouring countries Niger and Cameroon<sup>9</sup> . Using the border length between Benin and Nigeria (773 km), and by assuming that the smuggled quantity is proportional to the length of the external border, a rough estimate of total smuggling can be obtained. In other words, the longer the border between Nigeria and a neighbouring country, the more smuggling activity takes place towards this country. For instance, Nigeria shares a 773 km border with Benin and 1,497 km with Niger, thus the quantity of fuel smuggled to Niger should be roughly twice as large.

_The third step_ is to refine this extrapolation by making two further adjustments:

- _Population:_ Since the states bordering Benin are particularly populous (and states in Northern Nigeria are sparsely populated), the smuggling estimate is further adjusted proportional to the population size in Nigerian border states. This reflects the presumption that a larger population means that more smugglers are present and that more smuggling takes place. This also accounts for the fact that population densities on two sides of a border tend to be correlated; thus taking into account the number of foreign consumers demanding smuggled fuel.

- _Availability of gasoline:_ The availability of gasoline varies significantly across Nigeria, and directly affects the quantity of gasoline available for smuggling. The states bordering Benin are more developed and urbanised, and offer better access to energy goods; e.g. due to proximity to harbours,

> 9Chad shares a 89 km border with Nigeria. This implies that smuggling quantities to Chad are negligible for the purpose of this study.

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where imported gasoline is landed, and better distribution infrastructure. In more remote states gasoline tends to be less widely available and more expensive (reflecting domestic transport costs), thus reducing smugglers’ profit margins. To reflect these factors, smuggling estimates are further adjusted in line with the average per capita expenditure on gasoline in the relevant bordering states.

Based on this method a total petrol smuggling estimate of $ 641 m is obtained, about 43% of which is smuggled to Benin and Togo, 33% to Cameroon, 24% to Niger, and less than 1% to Chad. Appendix B provides further details on this estimation.

Mlachila et al. (2016) report that petrol smuggled from Nigeria is sold in Benin with an average mark-up ranging between approximately 20% and 40%. They note that informal prices in Benin are lower (i.e. the mark-up smaller) closer to the Nigerian border. This mark-up contains the cost of smuggling (including transport costs), but also profits by smugglers and middlemen. This study makes the assumption that the cost of smuggling corresponds to 10% of the smuggling value<sup>10</sup> .

# **7. Simulation scenarios and outcome variables**

# _7.1. Simulation scenarios_

The model is computed for the following scenarios.

**Scenario 1 – Baseline:** This scenario reproduces the baseline economy observed in the data. It serves as a reference point for evaluating the results in the subsequent simulation scenarios. It also enables a baseline evaluation of the regressivity of FFS.

**Scenario 2 – Uncompensated subsidy reform:** This scenario simulates an uncompensated petrol subsidy reduction and petrol tax increase (from _s_<sup>_e_</sup> _P etrol_<sup>=</sup> 0 _._ 22 to _s_<sup>_e_</sup> _P etrol_<sup>=</sup><sup>_−_0</sup><sup>_._22)11.Thegovernmentusesreformrevenuestoincrease</sup> government spending. Households receive no compensation.

**Scenario 3 – Subsidy reform with cash transfers:** This scenario simulates a petrol subsidy reduction and petrol tax increase, in which reform revenues are redistributed to households uniformly in the form of direct cash transfers. Each household – no matter the income level – receives the same amount.

**Scenario 4 – Subsidy reform with labour tax reduction:** This scenario simulates a petrol subsidy reduction and petrol tax increase, in which reform

> 10The overall results of this study are not found to be influenced significantly by increasing the cost of smuggling to 20% or 30%.

> 11Note that, as mentioned previously, the baseline subsidisation rate observed in the data is _s_<sup>_e_</sup> _P etrol_<sup>=0</sup><sup>_._18.ThismeansthatthesimulationrangemainlyfocussesontheFFSreduction</sup> (0.18 to -0.22), but also provides estimates for the effects of an increase in FFS (from 0.18 to 0.22).

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revenues are used to reduce labour taxes (i.e. a double dividend style fiscal reform). Labour taxes across all sectors are reduced.

**Counter-factual scenario (Revenue neutral subsidy reform ignoring tax evasion and smuggling):** This scenario repeats the simulation of a double dividend style fiscal reform (Scenario 4), but disregards tax evasion and smuggling activities. This enables an assessment of the size of the evasion and smuggling effects on estimated reform benefits.

# _7.2. Assessing welfare effects_

# _7.2.1. Fiscal efficiency and social welfare_

As Liu (2013) shows, a “double dividend” style tax reform – i.e. using environmental tax revenue to reduce pre-existing taxes – can reduce, but not fully eliminate, the social welfare cost of environmental taxes (Bovenberg and Goulder, 1996; Goulder, 1995 _b_ ). The same welfare costs must be expected when FFS reform revenue is used to reduce pre-existing taxes (simulation scenario 4).

To confirm this, this study estimates the social welfare cost of a double dividend style FFS reform (i.e. scenario 4) by evaluating changes at the tax base<sup>12</sup> . For this purpose, this study adopts the approach taken by Williams (2002), Bento and Jacobsen (2007), and Liu (2013), who use the following expression to measure the welfare effect of a change in the environmental tax rate – in this

> 12Note that the term “welfare” here is used – in line with the literature – to refer to the fiscal efficiency benefits of subsidy reform, and thus the associated increase in societal well-being. It does not refer to household level consumption, which is covered by Section 7.2.2.

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13 case the subsidisation rate _s_<sup>_e_</sup> : _j_ Welfare impact = The first line represents the marginal change in factor tax revenues following a change in the subsidisation rate. The second line represents the marginal change in production tax revenues. The third line represents the marginal change in subsidy payments (or petrol tax receipts, in the case of a negative subsidisation rate). The fourth line represents the marginal change in real factor losses associated with factor tax evasion. Similarly, the fifth line represents the marginal change in real output losses due to production tax evasion. Lastly, lines six and seven represent the marginal change in smuggling losses associated with outbound ( _Ej_<sup>_loss_</sup> ) and inbound smuggling ( _Mj_<sup>_loss_</sup> ). Note that Liu (2013) does not consider subsidies, production tax evasion, and smuggling; likewise, this study does not consider the environmental benefits due to emission reduction.

# _7.2.2. Distribution and household welfare_

In addition, this study considers the reform’s effects on household welfare, i.e. utility. However, utility, being an ordinal measure, is not a practical measure for the purpose of quantitative policy evaluation. This is especially the case when welfare effects on heterogeneous households are to be quantified and compared.

Nevertheless, changes in utility levels can be monetised and thus consistently evaluated and compared by computing _Hicksian equivalent variations_ (Hosoe et al., 2010; Durand-Lasserve et al., 2015)<sup>14</sup> . Equivalent variation measures by how much households’ income would need to change (at original price levels) to

> 13See Liu (2013) for a full analytical derivation.

> 14For further details refer to Mas-Colell et al. (1995).

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fuel tax can extend this reduction to over 35%. In turn, households increase their formal market consumption accordingly.

In addition, by considering the role of illicit activities, this study shows that conventional analyses may be overlooking a significant part of the picture:

- Regardless of the method of revenue redistribution, reducing subsidies diminishes the incentives for fuel smuggling, and hence the welfare losses associated with it. The reduction of these welfare losses must be considered when evaluating FFS reforms.

- In the case when revenues of FFS reform are redistributed using cash transfers, avoided smuggling means that the cash transfer scheme is disbursing the same aggregate benefit to the population as in the FFS scheme, but at a lower cost.

- Reducing FFS and using revenues to lower pre-existing labour tax rates not only mitigates labour market distortions, but reduces tax evasion; i.e. the government can earn the same level of tax revenues, while charging lower tax rates.

- A conservative estimate for Nigeria is that taking into account illicit activities can lower the welfare cost of FFS reform by up to 40%. The tax evasion effect accounts for (on average) 75% of this difference, with smuggling effects accounting for the remainder.

- The above mentioned benefits of FFS removal (i.e. in terms of income distribution, consumption, fiscal efficiency) can be increased when subsidies are not only removed, but replaced by fuel taxes. Such fuel taxes may reverse the direction of smuggling activities, though this is not enough to undermine the overall benefits.

Even though tax evasion tends to be particularly high in developing countries – large informal sectors are symptomatic of this – the “tax evasion effect” has not been studied before in the context of FFS reform. Similarly, despite being a frequently cited side-effect of FFS, smuggling has also received virtually no attention in the literature so far. This study demonstrates that such illicit activities can make a significant difference to the argument in favour of FFS reform; and should be considered when designing and implementing such reforms.

Moreover, evidence from Luxembourg demonstrates significant cross-border fuel demand due to large price differentials with neighbouring countries – and thus illustrates that the relevance of such activities is by no means limited to resourcerich developing countries (IMF, 2015). A better understanding of such activities can be vital for designing functioning energy and carbon pricing schemes.

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