metadata: authors: 0: author: Campagne,Benoit Philippe Marcel
1: author: Kitzmuller,Markus
2: author: Tordo,Silvana
count: Chad
docna: 0: docna: Designing Oil Revenue Management Mechanisms
            : An Application to Chad
docty: Policy Research Working Paper
subtopic: Energy Policies & Economics,Public Finance Decentralization and
            Poverty Reduction,Public Sector Economics,Public Financial Management,Macroeconomic Management,Financial Sector Policy
teratopic: Energy,Public Sector Development,Macroeconomics and Economic Growth
abstracts: cdata!: Oil resources usually play a significant
            role in oil-rich countries, in gross domestic product and
            government revenues. High dependence of government revenues
            on oil can contribute to severe recession following an
            adverse commodity price shock, such as in 2014. This paper
            examines the extent to which a fiscal rule or stabilization
            fund could translate into a less pro-cyclical fiscal policy,
            with the government saving part of its oil revenues during
            periods of high prices and drawing down on the savings
            during difficult periods. Using the macro-structural model
            MFMod, the paper presents, evaluates, and discusses the
            strengths and weaknesses of different oil revenue management
            mechanisms applied to the specific case of Chad. The
            scenarios demonstrate that a well-designed management rule
            can successfully insulate the public budget from the oil
            price cycle, resulting in a significant reduction in the
            volatility of the economy.
geo_reg_key: 517196,517191
repnme: repnme: Designing Oil Revenue Management Mechanisms
            : An Application to Chad
display_title: Designing Oil Revenue Management
            Mechanisms : An Application to Chad
listing_relative_url: /research/2020/09/32414586/designing-oil-revenue-management-mechanisms-application-chad
topicv3: Natural Resources Revenue Management
            m1325608 2275,Public Finance Management m1326316 716,Financial Sector Development m1327681 1920,MFMod m1504542 3120,Coronavirus (COVID-19) m1939478 4828
publishtoextweb_dt: 2020-09-17T00:00:00Z
historic_topic: Energy,Public Sector Development,Macroeconomics and Economic Growth
origu: EFI-MTI-Global Macro and Debt (EMFMD)
no_of_pages: 44
author_keys: 0: author_key: 1684334
1: author_key: 1175222
2: author_key: 672073
model_extractions: Policy Research Working Paper 9402 Designing Oil Revenue Management Mechanisms An Application to Chad _Benoît Campagne Markus Kitzmuller Silvana Tordo_ Macroeconomics, Trade and Investment Global Practice September 2020
Policy Research Working Paper 9402

# **Abstract**

Oil resources usually play a significant role in oil-rich countries, in gross domestic product and government revenues. High dependence of government revenues on oil can contribute to severe recession following an adverse commodity price shock, such as in 2014. This paper examines the extent to which a fiscal rule or stabilization fund could translate into a less pro-cyclical fiscal policy, with the government saving part of its oil revenues during periods of high prices and drawing down on the savings during difficult periods. Using the macro-structural model MFMod, the paper presents, evaluates, and discusses the strengths and weaknesses of different oil revenue management mechanisms applied to the specific case of Chad. The scenarios demonstrate that a well-designed management rule can successfully insulate the public budget from the oil price cycle, resulting in a significant reduction in the volatility of the economy.

This paper is a product of the Macroeconomics, Trade and Investment 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 bcampagne@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
# **Designing Oil Revenue Management Mechanisms: An Application to Chad**

Benoît Campagne, Markus Kitzmuller, Silvana Tordo

**JEL Codes:** C50, E62, Q32

**Keywords:** economic modeling, fiscal rule, oil revenue management, Chad

**Disclaimer:** This analysis was written and finalized in 2019 prior to the COVID-19 crisis. Although, the baseline assumptions on the trajectory of the Chadian economy have crucially changed since then, the analytical results presented in this paper on the relative performance of different oil revenue management rules still hold.

**Acknowledgments:** the authors would like to thank Ana Maria Jul, Fulbert Tchana Tchana, Olanrewaju Malik Kassim, Lars Moller as well as the IMF Chad and fiscal team for the fruitful discussions that benefited this analysis.
# Contents

|**1.**|**Introduction ...............................................................................................................................3**|
|---|---|
|**2.**|**The macro-econometric model MFMod-TCD ...............................................................................6**|
|**3.**|**Baseline scenario and “business as usual” behavior of the Chadian economy ...............................8**|
|i.|Oil sector and price modelling .......................................................................................................... 8|
|ii.|<br>Modelling the « standard » behavior of the public expenditures .................................................. 11|
|iii|.<br>Baseline scenario ............................................................................................................................ 14|
|**4.**|**Outturns under alternative revenue management rules ............................................................ 17**|
|i.|The CEMAC fiscal framework .......................................................................................................... 17|
|ii.|<br>Price smoothing mechanism ........................................................................................................... 22|
|iii|.<br>CEMAC+ rule ................................................................................................................................... 24|
|iv|.<br>Comparison of outcomes ................................................................................................................ 32|
|**5.**|**Conclusion ................................................................................................................................ 34**|
|Refe|rences**....................................................................................................................................... 36**|
|App|endix**......................................................................................................................................... 37**|
|A.|<br>Baseline response of the Chadian economy to an oil price shock .................................................. 37|
|B.|<br>Functioning of the implemented oil revenue management ........................................................... 40|

2
# 1. Introduction

In many resource-rich economies (see Herrera et al. 2019), procyclical fiscal policy, high dependence on the resource sector and the absence of oil revenue management mechanism left countries vulnerable to volatility and exogenous commodity price shocks. Indeed, low savings rates and boom-bust cycles have plagued economic development in a wide range of resource-rich developing countries (IMF, 2012).

For resource-rich economies, the exhaustible character of the resource and capacity constraints that restrict the speed with which investments can be efficiently made and absorbed give rise to difficult intertemporal trade-offs in deciding how much of the wealth and revenues generated today should be consumed and invested today _versus_ saved and invested or consumed tomorrow. The decisions made have implications for intergenerational equity, as well as fiscal and external sustainability. Especially in resource-rich developing countries, the volatility and disproportionate size of revenues compared with other sectors of the economy may imply different short and medium-term trade-offs and additional precautionary savings.

Carneiro and Kouame (2019) argue that the use of fiscal rules in resource-rich countries has been associated with better fiscal/debt outcomes in the countries that have adopted them. Countries that have adopted fiscal rules experience a lower procyclical bias in fiscal policy as well as a positive effect on the risk premia of their sovereign bonds. Yet, the design of fiscal rules is crucial in order to obtain concrete, sustainable and efficient benefits. The fiscal rule that works for one country may well not be appropriate for another.

A consensus in the literature (notably, see <mark>Kopits and Symansky, 1998)</mark> shows that a good fiscal rule is ( _i_ ) **simple:** characterized by clearly stated, transparent and with realistic targets; ( _ii_ ) **flexible:** allowing for course correction with clear escape clauses and, for resource-rich countries, allows for cyclical adjustments to the business cycle (or booms and busts); and ( _iii_ ) **enforceable:** with clear and credible mechanisms to monitor and oversee the implementation of the rule.

In addition, the literature is clear that an optimal resource management system allows current spending to be increased in a sustainable way, while scaling up investment in a way that can sustain a higher public capital stock (IMF, 2012). Precisely what that optimal system might be is less clear, different management frameworks and rules have been proposed. These include:

- **Non-resource primary balance rules or expenditure growth rules** that aim to limit the procyclicality of expenditures, by setting a limit or a constraint to the growth of government spending (in nominal or real terms, or as a percent of non-resource GDP). When resource revenues are large (i.e. in “good” times), the cap set to expenditure growth forbids the government to immediately spent all available resource revenues and _de facto_ forces the intertemporal transfer of some of those revenues to future periods.

- **The Hartwick rule** which earmarks all revenues stemming from the exploitation of a depletable asset for the financing of capital expenditures only, which will generate returns in the future. This rule forbids the government to finance recurrent and therefore non-productive expenditures using a transient stream of revenue.

- **Permanent income hypothesis rules** that impose that the resource-funded consumption level should not exceed the (implicit) return on the net present value of future natural resource revenue. During the extraction phase, most of the revenues are saved to build up non-resource

3
capital, in order for the return on these assets to compensate for the fall in revenue after extraction has ended.

All of these fiscal frameworks for resource-rich countries share a common characteristic: they focus on constraining public expenditures to prevent governments from overspending resource revenues on nonproductive expenditures. This approach naturally derives from a long-term view on how to convert depletable resources into long-term non-resource capital capable of generating revenues after the resource is depleted.

Although theoretically desirable, constraining expenditures, and in particular earmarking revenues to non-recurring expenditures, is a politically sensitive topic and might be unfeasible in some contexts, for instance where urgent and unavoidable security-related expenditures are a recurring competitor for funding.

A second option is to focus on the revenue side and attempt to decouple revenues as much as possible from the commodity cycle, leaving full freedom to the government for the allocation of expenditures. This corresponds to addressing the inherent volatility of resource revenues and their impact on budget planning at the source/intake <mark>. Cangiano et al. (2013)</mark> argue that volatility should be accommodated through strengthened public financial management practices such as the implementation of multiannual budgets or the design of long-term strategy plans. Yet, such plans require both a strong institutional capacity and a strong commitment capacity to elaborated plans that might not be feasible in low-income countries. Alternatively, volatility can be addressed directly at the source either by the creation of natural resource funds, in most cases for stabilization and saving purposes, or by market-based financial insurances (like the large hedging program set in place in Mexico, see Arezki et al., 2012). The latter option however can prove costly and again requires strong institutional capacities to supervise and manage sophisticated financial instruments. <mark>Cangiano et al. stress that in countries lacking</mark> strong budget planning systems, reliable internal controls and expenditure tracking systems (and most generally in institutionally fragile states), the creation of special natural resource funds can be adequate.

# **An application to the case of Chad**

In Chad, the oil sector represents around 15% of real GDP, 85 % of exports and 40 % of public revenues in 2018. During the last 15 years, Chad did not manage to successfully exploit its oil dividend to foster longterm growth and the low diversification of the economy outside of the oil sector has actually been identified as one of the structural constraints weighting on Chad’s growth potential (Kitzmuller et al. 2018). Funding available for crucial structural reforms is repeatedly destabilized by volatile oil prices, unexpected oil-production shortages and competing priorities, notably those related to security.

The economy’s dependency on the oil sector was strongly illustrated in the aftermath of the 2014 commodity price shock. The large loss in oil revenues for the government forced important budget cuts notably in social and capital expenditures with important spillovers to the real sphere. GDP declined by 6% in 2016, the budget deficit rose to 5% of GDP and public debt rose from 40% of GDP in 2014 to 55% in 2016.

Prior to the COVID-19 outbreak, Chad had been gradually recovering from this severe recession and the country was pursuing a gradual fiscal consolidation in line with an IMF program that granted access to US$310.8 million in credits. Despite a tight spending envelope and improvements in the mobilization of non-oil revenues, the fiscal balance in the medium-term will still be driven largely by oil revenues. Oil revenues are projected to represent about 7 % of non-oil GDP over the medium term, partly reflecting 4
expected increases in oil production as new extraction technologies are implemented and new fields start to produce. Production volumes are expected to reach a peak in 2023 and stagnate afterwards.

The 2018 restructuring agreement with an international commercial creditor - Glencore – markedly improved Chad’s liquidity position and restored debt sustainability. The agreement included a significant maturity extension, a large reduction in restructuring fees, a lower interest rate and contingency mechanisms that allow for reduced external debt service to Glencore when oil prices are lower. Since 2016, public debt dropped from 55 % of GDP to 48 % in 2018 and was estimated to be about 44 % of GDP at the end of 2019. While Chad’s debt is less vulnerable to oil price fluctuations now and appears to be on a sustainable path, the risk of external and overall debt distress remains high. The COVID-19 crisis is expected to exacerbate these sensitivities with the Brent oil price having fallen to 40 dollars per barrel in June 2020 and the Chadian economy projected to contract by 5.7 percent in 2020.

All in all, given the significant role of oil in GDP and government revenues in Chad, and its weak institutional framework, it would therefore seem that Chad could be a strong candidate for a saving fundbased fiscal rule that allows to save part of oil revenues in the good days and to draw on them in difficult times (countercyclically). The absence of a functional fiscal rule or stabilization fund was particularly felt during the fall in commodity prices in 2014 (not that some attempts with no success where made in the past, see Box 1). With no fiscal buffers available, the resulting recession and shortfall in revenues put severe strains on public finances, ultimately rendering the government illiquid and public debt unsustainable.

# **Box 1: Chad’s history with resource-revenue management**

Past attempts in Chad at managing oil revenues failed to deliver fiscal stability. In 1999, at the outset of the Chad-Cameroon pipeline project, an oil revenue management law was designed. The independent oil revenue control (Collège de Contrôle et Surveillance des Revenus Petroliers, CCSRP) was tasked with monitoring of expenditures financed by oil revenues. The mechanism was built around expected direct oil revenue, namely royalties from the sale of oil, and dividends from the government’s participation in the two transportation companies (Chad Oil Transportation Company - TOTCO and Cameroon Oil Transportation Company - COTCO) that own and manage the Chad-Cameroon pipeline. In 2007, indirect oil revenue from resource rent tax and corporate rent tax were added to the scope of application of the oil revenue management law and the role of the CCSRP was expanded accordingly. In 2014, triggered by the tightening fiscal space, a new revenue management law was enacted, but without any stabilization or saving function, the law simply became an earmarking mechanism to channel oil revenue to a list of priority sectors. In September 2018, the CCRSP was dissolved.

The remainder of this paper therefore explores the extent to which alternative revenue management frameworks on the revenue side would succeed in supporting countercyclical expenditure policies in the face of oil price and production volatility in the particular case of Chad. Frameworks will be evaluated on the extent to which boom-bust cycles emanating from resource revenues are minimized and the consequences that this has in yielding a more or less smooth path for consumption. The analysis will focus on the capacity of those mechanisms to reduce the volatility of public expenditures (and hence of growth) both from of deterministic perspective in face of determined oil price trajectories, and from a stochastic perspective in face of volatile and unpredictable oil price paths.

The following section 2 gives a presentation of the macro-structural model MFMod-TCD used for the analysis. Section 3 describes the key assumptions used in the simulations, while Section 4 present the alternative fiscal mechanisms examined and the results of simulations. Section 5 concludes.

5
# 2. The macro-econometric model MFMod-TCD

In order to design and assess alternative oil revenue management mechanisms, this paper uses the macrostructural model The Macroeconomic and Fiscal Model for Chad (MFMod-TCD). MFMod-TCD is a countryspecific structural econometric model of the Chadian economy, derived from the MFMod model framework of the World Bank (see Burns et al., 2019). It corresponds to a standard macro-structural, with significant customizations to reflect the special characteristics of the Chadian economy.

Structural macro-econometric models are important tools for forecasting and policy analysis due to their ability to incorporate a detailed mix of judgement and the rich set of transmission channels they embody, which allows policy impacts on the broader economy to be followed at a deeper level of disaggregation than in other macroeconomic models, notably DSGE-type of models (Blanchard, 2018). MFMod-TCD is well suited to the present study. It incorporates the necessary flexibility to model alternative and complex oil revenue management mechanisms while accounting for the distinctive features of the Chadian economy, including: very specific debt-repayment rules for its restructured debt that imply a highly nonlinear repayment mechanism; a country-specific government behavior that reflects national priorities; and a highly constrained fiscal space.

Most importantly, MFMod-TCD includes a detailed and internally consistent description of both national income and fiscal accounts, with public expenditures affecting the real sphere of the economy, which in turn has an impact on both revenues and debt for the government. Those linkages are essential to assess the performance of a revenue management mechanism. In contrast, a pure fiscal-focused model would omit key components of fiscal sustainability, such as the direct relationship between savings from oil revenues on capital accumulation and the country’s sustainable growth path. The presence of such feedbacks in MFM-TCD allows the model to capture the trade-offs between lower volatility of public revenues and medium-term growth.

## **Model characteristics**

In the MFMod framework, country-specific models are designed to reproduce the flow of funds across the whole economy by mapping out the main identities of the national accounts, balance of payments, labor markets and financial sectors (Burns et al., 2019 provides a detailed description of the model structure and equations). Structural relationships are consistent with both economic theory and the observed dynamics of the economy. The short-run dynamics are data-driven, with estimated parameters reflecting the actual behavior of the economy. Most equations are estimated using error-correcting models and parameters were estimated using, or calibrated to, Chadian data. In the MFMod framework, the overall equilibrium growth path of the economy is determined by potential output, which is calculated using the production-function methodology which is a function of total factor productivity, the level of capital and labor. Deviations from equilibrium, as well as convergence to equilibrium, are determined by the historical behavior of the Chadian economy.

The data used in MFMod-TCD were obtained from the World Bank WDI database for national accounts data, the IMF for fiscal and balance of payments data and the ILO for labor market data. Detailed data on the fiscal accounts were sourced from the Ministry of Finance, and include:

- Oil revenues, grants and other non-oil-related revenues.

- Expenditures on goods and services, public wages and compensations of employees, interest payments, transfers and capital expenditures.

6
<!-- Start of picture text --> i<br>—Goods and services<br>0.8<br>a~S Wagescompensations and<br>0.4 XX<br>YY —Transfers<br>—Capital expenditures<br>-0.2<br>2019 2021 2023 2025 2027 2029<br><!-- End of picture text -->
3. Baseline scenario and “business as usual” behavior of the Chadian economy A baseline scenario was generated as a point of reference from which to compare the impact of different mechanisms under alternative oil price trajectories. This baseline reflects the historical behavior of the economy, and notably of the Chadian government, in the absence of any revenue management mechanism. The baseline and analysis reported here was generated prior to the onset of the COVID-19 outbreak so that it can be interpreted as a no-COVID counterfactual. The model could also be used to explore the impacts of COVID on the Chadian economy, but that would be the subject of a separate paper.

Box 2 outlines the assumptions regarding productivity, population growth and labor market behavior that are central to the long-run growth path of the Chadian economy incorporated in MFMod-TCD. In addition to these critical assumptions for the baseline include those for the baseline behavior of the government, the oil sector and the composition of spending in the “business-as-usual” .

## **Box 2: Structural growth assumptions**

Central to the definition of the steady state of the model, the following structural global assumptions are made:

- Total factor productivity is set to grow exogenously at 1.1 % -- its average growth rate over the period 2007-2017.

- Working age population grows at 3.5 %, in line with the UN Population Division growth projection over the period 2020-2030.

- Inflation expectations are set to the BEAC inflation target of 3 %. In addition, in order for a balanced growth path to exist, in the global world commodity prices are also assumed to grow at the same pace.

- Real global growth is set to 3.9 % corresponding to the average forecast of the World Bank for 2019-2021.

- As a member of the CEMAC monetary union, the EUR/CFAF exchange rate is held constant, while the EUR/USD exchange rate is held constant in both real and nominal terms.

# i. Oil sector and price modeling

As a main driver of the Chadian economy and the focus of the revenue management mechanism, assumptions pertaining to oil are crucial for the quantitative simulation results.

## **Baseline oil production and price forecast**

First, in line with IMF forecasts, the following assumptions are made concerning the output of the oil sector (also see Figure 2):

- Up until 2023, oil production is aligned with the forecast in the IMF’s medium-term fiscal framework (IMF, 2019, Fourth Review of the Extended Credit Facility). After 2023, production is assumed to be constant, reflecting a balance between reducing oil reserves and additional light crude oil production expected to come on stream.

8
<!-- Start of picture text --> 250<br>200<br>150<br>100<br>50<br>2010 2012 2014 2016 2018 2020 2022 2024<br>—— Oil.. production.. (1000's bbl/day)<br><!-- End of picture text --> <!-- Start of picture text --> USD/bbI 250<br>120 11<br>ioreca:ioreca:ii<br>110 10 200<br>100 9<br>90 8 150<br>80 7<br>100<br>70 6<br>60 5 50<br>50 4<br>30 2 2010 2012 2014 2016 2018 2020 2022 2024<br>2010 2012 2014ll2016Discount;ll2016Discount;2016Discount;Discount;; 2018 2020(RHS)2022(RHS)2022 Brent = 2024 2026 2028 2030 —— Oil.. production.. (1000's bbl/day)<br>120 140<br>120<br>100<br>100<br>60 60<br>40<br>40<br>20<br>20 0<br>2000 2004 2008 2012 2016 2000 2004 2008 2012 2016<br><!-- End of picture text --> <!-- Start of picture text --> USD/bbI<br>120 11<br>ioreca:ioreca:ii<br>110 10<br>100 9<br>90 8<br>80 7<br>70 6<br>60 5<br>50 4<br>30 2<br>2010 2012 2018 2022 2024 2026 2028 2030<br>2014ll2016Discount;ll2016Discount;2016Discount;Discount;; 2020(RHS)2022(RHS)2022 Brent =<br><!-- End of picture text -->
discontinuities in the empirical distribution of month-to-month changes in oil prices, the data generating process is obtained by fitting a known distribution over this empirical distribution. This distribution will then be used to draw alternative series of price changes over the simulation period.

Due to the strong kurtosis of the empirical distribution (see Figure 4), fitting a normal distribution would be inappropriate (a Jarque-Bera test suggests a full rejection of the null hypothesis of a normal distribution). A Student distribution provides a much better approximation of the empirical distribution. including its fat-tail property.

<!-- Start of picture text --> Figure 4: density of the month-to-month change in the price of the Brent oil<br>in USD for 2000-2018<br>.12 Histogram<br>Student's t<br>.10 Normal<br>Mean: 0.135<br>.08<br>Median: 0.859<br>.06 Std. Dev.: 5.620<br>Skewness: -1.174<br>.04<br>Kurtosis: 5.984<br>.02<br>.00<br>-30 -20 -10 0 10 20 30<br>Density<br><!-- End of picture text --> Overall, the data generating process for the monthly price of oil that will be used in the following sections will assume that the price of the Brent oil follows a random walk with a deterministic drift: o o (1 + d d avec εt ~ σ ∗T(ν) oo oo The d d is calibrated to the long-term growth of nominal oil prices forecast by the World Bank of 0.74% tt tt−1 tt tt PP = PP tt ) + εε per year. The innovation of the process is assumed to be of mean zero (as opposed to the positive mean tt observed over the period) and to follow a Student distribution calibrated over the period 2000-2018. The tt best fitted distribution is obtained for and . The monthly price trajectories are then averaged to obtain annual price trajectories. With this data generating process, alternative oil price scenarios lead to the simulated distribution presented in Figure 5. σσ= 4 νν= 5 10
<!-- Start of picture text --> 140<br>120<br>100<br>80<br>ine<br>60<br>40<br>20<br>2020 2022 2024 2026 2028 2030<br>90% 70%<br>mmm 40% mm 20%<br><!-- End of picture text -->
<!-- Start of picture text --> —_—_ «(Rev )<br><!-- End of picture text --> <!-- Start of picture text --> 100<br>50<br>0<br>-50<br>-100<br>SLOYBH QDQD PH&DWWS’ LHDS’Vv LPoYnw® HPoYr—®e LHoYOM LH’ccMG HYYdA nO<br>—Total revenues<br>—Total revenues less wages and interest payments<br>— Goods and services<br>—transfers<br><!-- End of picture text --> <!-- Start of picture text --> 80<br>60<br>40<br>20<br>0<br>-20<br>-40<br>60<br>SH QD ODO WS VY wD ® Mm © AN %<br>a o> “” “SY “ “” ” “SY “SY a a<br>—Total revenues ——Wages and compensations<br><!-- End of picture text -->
<!-- Start of picture text --> % of GDP<br>25<br>20<br>15<br>10<br>5<br>0<br>2002 2004 2006 2008 2010 2012 2014 2016 2018<br>—lInelastic expenditures ——Elastic expenditures<br><!-- End of picture text -->
<!-- Start of picture text --> 50<br>0<br>-50<br>-100<br>-150<br>-200<br>Borrowing limit improves<br>-250<br>2019 2021 2023 2025 2027 2029<br>—— Borrowing limit (excl. Glencore amortization)<br>—— Borrowing limit<br><!-- End of picture text -->
<!-- Start of picture text --> 6<br>-2<br>-4<br>-6<br>-8<br>2016 2018 2020 2022 2024 2026 2028 2030<br>60<br>50<br>40<br>30<br>20<br>10<br>0<br>2016 2018 2020 2022 2024 2026 2028 2030<br><!-- End of picture text --> <!-- Start of picture text --> 3<br>“1<br>-2<br>-3<br>2016 2018 2020 2022 2024 2026 2028 2030<br><!-- End of picture text --> <!-- Start of picture text --> 8<br>?<br>6<br>5<br>4<br>3<br>2<br>1<br>fe)<br>2016 2018 2020 2022 2024 2026 2028 2030<br><!-- End of picture text --> <!-- Start of picture text --> 400<br>300<br>200<br>100<br>0<br>-100<br>-200<br>2016 2018 2020 2022 2024 2026 2028 2030<br>——Budget balance<br>—Budget constraint (excl. Glencore)<br>——Budget constraint<br><!-- End of picture text -->
# **Simulations of alternative oil trajectories under the historical fiscal reaction functions**

Assuming the expenditure functions laid out in the preceding section, and a range of possible outcomes for oil prices (drawn from the historical behavior of oil prices), economic outcomes are more volatile than suggested by the baseline scenario (see Figure 11). These scenarios are generated by running 5,000 simulations each drawing an oil price trajectory from the oil-price probability distribution each year. In 4,500 (90%) of these scenarios oil revenues lie between 3 % and 12 % of GDP in 2023 (the frontier defined by the light blue part of the distribution). There is a 70% probability of revenues ranging between 5 and 11 percent of GDP (area bound by the darker blue shading), and a 60 percent chance of revenues ranging between 7 and 10 percent of GDP –a significant level of uncertainty. Even the darkest blue area, which accounts for only 20 percent of cases, spans a relatively wide range of between 7 to 9 percent of GDP. After 2023, both the median revenue as a percent of GDP and the range of possible outcomes are expected to decline as the economy diversifies away from oil, due to faster growth in the non-oil economy. Despite the declining trend, oil plays a crucial role in the Chadian economy and will continue to do so in the near future.

In this “business-as-usual” scenario, the procyclical spending behavior described in the previous section reduces the volatility of the fiscal balance (deficit/surplus), but contributes to the volatility of GDP – especially in the early years where the debt repayments required under the Glencore deal constrains the total spending of the government.

Depending on oil prices observed, GDP growth outcomes could vary by as much as 4 percentage points during the period 2020-2025, and up to 2 p.p. in the longer term.

16
<!-- Start of picture text --> 9 13<br>12<br>8 ci<br>7 10<br>9<br>68<br>7<br>5<br>6<br>45<br>4<br>33<br>2<br>;<br>1<br>1f)<br>2019 2021 2023 2025 2027 2029 2019 2021 2023 2025 2027 2029<br>90% m70% m40% m20% 90% m70% m40% 20%<br>8 50<br>7 45<br>6<br>40<br>5<br>4 35<br>3 30<br>2 25<br>1<br>20<br>0<br>15<br>4<br>-2 10<br>2019 2021 2023 2025 2027 2029 2019 2021 2023 2025 2027 2029<br>90% m70% m40% m20% 90% m70% m40% m20%<br><!-- End of picture text -->
importance of oil revenues for the CEMAC members. As a legally binding framework for the Chadian government designed to address the question of commodity-linked revenue management, it is natural to start with the examination of the extent to which this rule reduces Chad’s vulnerability to oil price volatility.

**Definition** The CEMAC rule imposes that the Reference Budget Balance ( ) should be above -1.5 % of GDP. The reference budget balance is defined as follows: RRB

= − ∗( + + ~~)~~ GDPt 3 GDPt−1 GDPt−2 GDPt−3 Where is the overall budget balance, are financial savings from oil revenues, and total collected oil revenues in year . tt tt tt OOBB FFSSOORR OORR In practice, the financial savings from oil revenues corresponds to the deviation (measured as a % of GDP) tt In practice, the financial savings from oil revenues corresponds to the deviation (measured as a % of GDP) of oil revenues from its (3-year) trend. Effectively the rule requires a government to save “surprise” or “excess” revenues (revenues that exceed the backward looking 3-year moving average of oil revenues). In this setting, the reference budget balance is the balance calculated based on the 3-year average of oil revenues, whereas the overall balance is the actual revenues. If spending is not adjusted and “excess” revenues are not spent, they will correspond to savings from oil revenues for the government. Under this formulation, savings are inherently asymmetrical as negative “surprise” revenues will still automatically generate a cut in expenditure. Moreover, the rule is not binding as the framework does not require that “excess” revenues be explicitly saved. A supplementary budget can be passed authorizing their expenditure.

The CEMAC surveillance framework also includes a 70% of GDP debt ceiling over 25 years, limiting the speed of debt accumulation. In practice, this ceiling is non-binding in all simulations due to the strong downward trajectory of Chadian debt. It is therefore ignored in the following discussion.

Prior to 2013, the CEMAC deficit rule was systematically violated with the reference deficit regularly exceeding the CEMAC target (Figure 12). Since 2013/2014, following the decline in oil prices and the large fiscal consolidation that it engendered the rule has been met (see Figure 12). Prior to 2013, the average deviation from the target was 3.3 pp of GDP. In 2018, savings from oil revenues ( ) were 2.3% of GDP. FFSSOORR 18
<!-- Start of picture text --> 6.0 fe)% of GDP<br>4.0<br>2.0<br>0.0<br>-2.0<br>-4.0<br>-6.0<br>-8.0<br>-10.0<br>2005 2007 2009 2011 2013 2015 2017<br>—— Overall budget balance<br>—— Reference budget balance<br>CEMAC target<br><!-- End of picture text --> <!-- Start of picture text --> 44<br>3 3<br>22<br>11<br>0 0<br>-1 -1<br>-2 -2<br>-3 -3<br>4 4<br>-5 -5<br>18 20 22 24 ~.2 28 = 30 18 20 22 24 26 28 = 30<br><!-- End of picture text --> <!-- Start of picture text --> 3<br>1<br>0<br>-1<br>-2<br>-3<br>4<br>-5<br>18 20 22 24 26 28 = 30<br><!-- End of picture text -->
<!-- Start of picture text --> 99<br>8 8<br>77<br>66<br>55<br>44<br>33<br>22<br>1 1<br>2019 2021 2023 2025 2027 2029 2019 2021 2023 2025 2027 2029<br>90% 70% TM40% 20% 90% 70% 40% 20%<br>88<br>7 7<br>66<br>55<br>44<br>33<br>22<br>11<br>0) 0)<br>-1 1<br>-2 -2<br>2019 2021 2023 2025 2027 2029 2019 2021 2023 2025 2027 2029<br>90% TM70% 40% 20% 90% 70% 40% 20%<br>50 50<br>45 45<br>40 40<br>35 35<br>30 30<br>25 25<br>20 20<br>15 15<br>10 10<br>55<br>))<br>2019 2021 2023 2025 2027 2029 2019 2021 2023 2025 2027 2029<br>90% 70% TM40% 20% 90% 70% TM40% 20%<br><!-- End of picture text -->
<!-- Start of picture text --> 20 0.4<br>10 wi ~ 0.3 r\<br>5 ¢ .<br>t 0.2 4 \<br>0<br>50.1 1 A<br>0.0 < . = o<br>-20 -0.1<br>2024 2025 2026 2027 2028 2029 2030 2024 2025 2026 2027 2028 2029 2030<br>1.0<br>c= © —a_, —<br>0.6 u +10 USD, Baseline<br>0.4 t =— —+20 USD, Baseline<br>0.2 l -10 USD, Baseline<br>0.0 ——— -20 USD, Baseline<br>-0.2 +10 USD, CEMAC rule<br>=— + +20 USD, CEMAC rule<br>0.4<br>06‘ ——-20-10 USD,USD, CEMACCEMAC rulerule<br>-0.8<br>-1.0<br>2024 2025 2026 2027 2028 2029 2030<br><!-- End of picture text -->
<!-- Start of picture text --> 120<br>110 r~<br>100 |e a peke<br>90 ne! 1 —MA(3,0,0)<br>80 rd \<br>70 , \<br>60 ) \ —MA(3,1,0)<br>50 ! , aVy<br>40 4 —— MA(3,0,3)<br>30 LG /<br>20 —MA\(5,0,0)<br>10<br>© VL & © OO DV nd nO nO AO AV<br>PHY HP AP Wy wh AO WP AP<br>PPP PP PPP PPP<br><!-- End of picture text -->
<!-- Start of picture text --> 20<br>15<br>10<br>06)<br>2004 2006 2008 2010 2012 2014 2016 2018<br>—— Collected Collected oil revenues<br>— Budgeted oil revenues<br><!-- End of picture text --> <!-- Start of picture text --> 20<br>15<br>10<br>6)<br>2004 2006 2008 2010 2012 2014 2016 2018<br>——Setup in 2005——Setup in 2008<br>——=Setup in 2011<br><!-- End of picture text --> <!-- Start of picture text --> 20 20<br>15 15<br>10 10<br>55<br>06)<br>2004 2006 2008 2010 2012 2014 2016 2018 2004 2006 2008 2010 2012 2014 2016 2018<br>—— Collected Collected oil revenues ——Setup in 2005——Setup in 2008<br>— Budgeted oil revenues ——=Setup in 2011<br>99<br>8 8<br>7) 7<br>66<br>55<br>44<br>33<br>22<br>11<br>2019 2021 2023 2025 2027 2029 2019 2021 2023 2025 2027 2029<br>90% m70% TM40% m20% 90% m70% m40% m20%<br><!-- End of picture text -->
<!-- Start of picture text --> 2750 14<br>2500 13<br>12<br>2250 a<br>2000 10<br>1750 9<br>1500 8<br>7<br>1250 6<br>1000 5<br>750 4<br>500 3<br>2<br>250 1<br>0 0<br>2019 2021 2023 2025 2027 2029 2019 2021 2023 2025 2027 ~ 2029<br>90% 70% m40% 20% 90% 70% m40% 20%<br><!-- End of picture text --> <!-- Start of picture text --> 14<br>13<br>12<br>a<br>10<br>9<br>8<br>7<br>6<br>5<br>4<br>3<br>2<br>1<br>0<br>2019 2021 2023 2025 2027 ~ 2029<br>90% 70% m40% 20%<br><!-- End of picture text --> <!-- Start of picture text --> — — +0.8 «(— -— oO — )<br><!-- End of picture text -->
In addition, oil savings are now explicit and saved/dissaved into a stabilization account ( F ). While savings are not bounded upwards, dissaving is limited by the amount already available into the account.

In addition, the rule allows for an adjustment in the case of persistent negative oil revenue shocks. 100% of the revenue shortfall is covered in the first year of occurrence of a shock, 66 % in the second year, 33 % in the third and 0 % in the fourth. Any residual adjustment is absorbed by an adjustment of public expenditures.

Under this revenue management scheme oil savings are explicit and taken out of the general budget, and the reference budget balance corresponds to the budget balance computed using the budgeted oil revenues. As such, the zero-deficit target for the reference balance simply ensures that the planned budget is balanced. This ensures the _ex-ante_ compliance of the rule with the CEMAC framework.

Note that the suggested modifications to the original CEMAC rule presented above are not the only possible ones. The selected version of the rule acts as a general framework for discussion, yet multiple sophistications or adjustments can be added (see Box 3). As such changes do not alter the spirit of the rule, those additions are not discussed here.

# **Box 3: Further refining the CEMAC+ rule**

The current formulation of the rule is highly adjustable and customizable **.** The parameters and mechanisms can be adjusted according to the preference of the government choosing to implement a revenue management rule. The following parameters/lines can easily be adjusted to fit specific needs and preferences:

- **Deficit target:** the deficit target can be adjusted to allow for more stringent or looser fiscal policy.

- **Level of savings:** the strict adherence to the CEMAC rule can be loosened and tighter or stronger savings accumulation rule can be designed. This can allow the rule to better reflect political preferences and financing priorities in the economy.

- **Adjustment schedule and coverage:** the length and size of insurance coverage can be adjusted to allow for shorter/longer period of coverage with more/less gradual phasing out of the coverage.

- **Use of interest income:** interest income can be used to protect the value of the fund against inflation or can be used externally to finance investment or the general public budget.

- **Ceiling to the stabilization fund size:** the size of the fund might be constrained to a ceiling value to avoid over-accumulation of savings beyond the desired level of risk coverage.

25
<!-- Start of picture text --> 1200<br>1000<br>800<br>600<br>400<br>200<br>0<br>2005 2007 2009 2011 2013 2015 2017<br>—— Budgeted oil revenues<br>— Collected oil revenues<br><!-- End of picture text --> <!-- Start of picture text --> 35<br>30<br>25<br>20<br>15<br>10<br>5<br>0<br>2005 2007 2009 2011 2013 2015 2017<br>—— Budgeted oil revenues<br>— Collected oil revenues<br><!-- End of picture text -->
<!-- Start of picture text --> 2500<br>2000<br>1500<br>1000<br>500<br>0<br>2004 2006 2008 2010 2012 2014 2016 2018<br>Setup in 2005——Setup in 2008<br>Setup in 2011<br><!-- End of picture text -->
<!-- Start of picture text --> 6 4<br>4<br>0)<br>E<br>-4<br>-6<br>-8<br>2016 2018 2020 2022 2024 2026 2028 2030<br>60<br>50<br>40<br>30<br>20<br>10<br>)<br>2016 2018 2020 2022 2024 2026 2028 2030<br>=== CEMAC+rule<br><!-- End of picture text --> <!-- Start of picture text --> 3<br>4<br>)<br>“1<br>-2<br>3<br>2016 2018 2020 2022 2024 2026 2028 2030<br><!-- End of picture text --> <!-- Start of picture text --> 10<br>9<br>:<br>7<br>6<br>5<br>4<br>7<br>2<br>1<br>0<br>2016 2018 2020 2022 2024 2026 2028 2030<br><!-- End of picture text --> <!-- Start of picture text --> === CEMAC+rule — — Baseline<br><!-- End of picture text --> <!-- Start of picture text --> 99<br>8 8<br>7 7h<br>66<br>55<br>44<br>33<br>22<br>11<br>2019 2021 2023 2025 2027 4«2029 2019 2021 2023 2025 2027 2029<br>90% 70% 040% 20% 90% 70% 40% 20%<br><!-- End of picture text -->
<!-- Start of picture text --> pe<br>ee<br>50 8<br>45 7<br>40 6<br>35 5<br>30 4<br>25 3<br>20 2<br>15 a<br>10 0<br>5 -1<br>0 -2<br>2019 2021 2023 2025 2027 2029 2019 2021 2023 2025 2027 2029<br>90% 70% %w§40% 20% 90% 70% %W40% 20%<br>a<br>4000 20.0<br>3500 17.5<br>3000 15.0<br>2500 12.5<br>2000 10.0<br>1500 75<br>1000 5.0<br>500 2.5<br>0 0.0<br>2019 2021 2023 2025 2027 2029 2019 2021 2023 2025 2027 2029<br>90% 70% m@40% 20% 90% 70% %w§40% m20%<br><!-- End of picture text -->
<!-- Start of picture text -->
1.00 20<br>yr<br>0.75 ‘ \\\ 15 t~=—«<br>U \ é ‘<br>0.50 ‘ ‘ 10 t .<br>0.25 f poems / Nene<br>t— 2 ~Sy 5 A" agit a<br>toe? ee ss fie? \ “s<br>-0.25 5<br>-0.50 -10<br>-0.75 -15<br>-1.00 -20<br>2024 2025 2026 2027 2028 2029 2030 2024 2025 2026 2027 2028 2029 2030<br>=== +20 USD, Baseline<br>—— -20 USD, Baseline<br>=== +20 USD, CEMAC+<br>—— -20 USD, CEMAC+<br><!-- End of picture text -->

<!-- Start of picture text -->
1.00 20<br>yr<br>0.75 ‘ \\\ 15 t~=—«<br>U \ é ‘<br>0.50 ‘ ‘ 10 t .<br>0.25 f poems / Nene<br>t— 2 ~Sy 5 A" agit a<br>toe? ee ss fie? \ “s<br>-0.25 5<br>-0.50 -10<br>-0.75 -15<br>-1.00 -20<br>2024 2025 2026 2027 2028 2029 2030 2024 2025 2026 2027 2028 2029 2030<br>=== +20 USD, Baseline<br>—— -20 USD, Baseline<br>=== +20 USD, CEMAC+<br>—— -20 USD, CEMAC+<br><!-- End of picture text -->
<!-- Start of picture text -->
1.00 20<br>0.75 n)| eh ll Ttprt tee 15 freewsiceacT<br>0.50 / ot / Lo tee<br>{ ma 10 y oe<br>0.25 #54 5 Ft<br>0.00 toe? ) 4 Si ue<br>-0.25 5<br>-0.50 -10<br>-0.75 -15<br>-1.00 -20<br>2024 2025 2026 2027 2028 2029 2030 2024 2025 2026 2027 2028 2029 2030<br>=-=-= +20 USD, Baseline<br>———-20 USD, Baseline<br>=== +20 USD, CEMAC+<br>=——=-20 USD, CEMAC+<br><!-- End of picture text -->
<!-- Start of picture text --> 6.5 8<br>6.0 os<br>7G<br>y<br>5.5 \ 2 “\<br>5.0 y 6 ~ \<br>\ in \\<br>45 5 \<br>4 " | f\ A s<br>4.0 QX ~ <—aie / je \ <= _—-—=Ss->=——<br>3.5 XS SeES .4 =— =<br>3.0 WSs~S" 3 esSe =——<br>~ ee<br>2.5 2<br>2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030<br>— Norule = =—CEMAC rule — Norule = =—CEMAC rule<br>=== Smoothing mechanism —— CEMAC+ === Smoothing mechanism —— CEMAC+ rule<br><!-- End of picture text -->
<!-- Start of picture text -->
1.5 1.5<br>1.0 1.0<br>. 0.0<br>nas a7 nas<br>-0.5 “For fF -0.5 ~SoS<br>\ , \ a;<br>‘ N load<br>-1.0 ay 7 -1.0 ee eee ee<br>-1.5 -1.5<br>2024 2025 2026 2027 2028 2029 2030 2024 2025 2026 2027 2028 2029 2030<br>=——= No rule, +20USD<br>= —No rule, -20 USD<br>== CEMAC rule, +20 USD<br>= + CEMAC rule, -20 USD<br>——— Smoothing mechanism, +20 USD<br>= = Smoothing mechanism, -20 USD<br>== CEMAC+ rule, +20 USD<br>=— —CEMAC+ rule, -20 USD<br><!-- End of picture text -->
# 5. Conclusion

Unexpected revenue shortfalls in resource-rich countries following adverse commodity price shocks can lead to severe fiscal and economic crisis, including illiquidity, debt distress, and severe recession. In the absence of any stabilizing revenue management mechanism in place, governments usually have no choice but to absorb the full extent of the shock through large expenditure cuts and arrears accumulation.

To avoid such costly adjustments and manage commodity price and production volatility more efficiently, the key objective for a revenue management mechanism is to introduce a countercyclical dimension into public financing. To identify and calibrate an adequate and effective resource revenue management mechanism, a macro-structural model such as MFMod allows to explore various options to stabilize public expenditure in face of revenue volatility and shocks taking into account the interactions between variables.

In the present paper, alternative oil revenue management mechanisms in the specific case of Chad were compared on five main dimensions: ( _i_ ) minimizing GDP volatility, ( _ii_ ) ensuring fiscal sustainability, ( _iii_ ) the transparency and simplicity of the rule, ( _iv_ ) the compliance with existing rules (i.e. the CEMAC macrosurveillance framework) and fiscal frameworks (the IMF Medium Term Fiscal Framework), as well as ( _v_ ) with country immediate economic and social needs.

For Chad, a smoothing mechanism alone does not significantly reduce volatility because the limited borrowing capacity of the government prevents it from using financial markets to supply savings during bad times. Introducing an explicit stabilization account with identified rules for savings/dissaving creates a pool of savings from which to draw during downturns and at the cost of slower growth in the near-term significantly reducing GDP volatility. Effectively, the revenue management mechanism acts as a commitment device that forces the government to save during good times, permitting dis-savings during bad. Both the simple price smoothing mechanism and the enhanced CEMAC framework achieve similar reduction in volatility. The CEMAC+ rule is marginally better because it is specifically tailored to Chad’s needs. It is compliant with the CEMAC macro-surveillance framework, smooths revenue volatility from both price and production shocks, and allows for a gradual adjustment in public expenditures in the context of structural changes in revenues.

Based on the present analysis and with the support of the World Bank, the Government of Chad designed and enacted in November 2019 an oil revenue management mechanism for fiscal stabilization purposes. Economic and fiscal modeling has informed the determination of fiscal policy objectives and allows to assess the strengths and weaknesses of different mechanisms under various scenarios as well as the fiscal performance of the selected mechanism in a medium term macro-fiscal framework. Although the new mechanism differs in its formulation from those presented in this paper, its core structure is deeply rooted in the conclusions of the analysis. The key objective of the new mechanism is to set aside sufficient oil revenues to cushion the fiscal impact of large, unexpected oil revenue shortfalls.<sup>2</sup> The present analysis was conducted before the COVID-19 crisis, and the reformed revenue mechanism enacted by the government was put in just before the crisis. Because the saving mechanisms had only begun, neither the CEMAC+ nor the actual system will provide much in the way of relief to the revenue falls currently being experienced by the Chadian authorities. However, over time as the economy recovers

> 2 A detailed description and illustration of the functioning of this oil revenue management mechanism is provided in appendix B.

34
and savings are accumulated, it should help arm the government with the kind of reserves that will allow it to mount a more robust response to future shocks.

All in all, an oil revenue management mechanism alone is not enough to bolster strong, sustainable and balanced growth in a resource-rich country. This is particularly true in the event of extreme price shocks such as illustrated by the COVID-related crisis, with associated loss in revenues most likely exceeding the value of any (hypothetical) stabilization account. Prudent fiscal management as well as increased economic diversification remain key elements to face crises of this magnitude.

35