Gabon: Selected Issues
Author: International Monetary Fund. African Dept.
Publication Date:
18 Mar 2016
eISBN:
9781475542141
ISBN:
9781475542141
Language:
English
Keywords:
ISCR; CR; price; GDP; economic activity; oil-price decline; oil-price slump; oil-price movement; GDP growth; CEMAC country; Oil prices; Oil; Oil exports
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This paper discusses impact of the falling oil prices on the Gabon's economy. With oil accounting for roughly 40 percent of its GDP, 45 percent of its government revenues, and nearly 85 percent of its exports in 2014, Gabon's economic growth prospects depend on how it copes with the recent oil-price slumps. Economic performance during major oil-price declines clearly illustrates the vulnerability of Gabon and other oil-dependent countries in sub-Saharan Africa. The recent oil-price slump is bound to generate a major deceleration of Gabon's non-oil economy. Given the strength of the government transmission channel, the authorities should support economic activity (through productive spending) while ensuring fiscal sustainability.

Abstract

This paper discusses impact of the falling oil prices on the Gabon's economy. With oil accounting for roughly 40 percent of its GDP, 45 percent of its government revenues, and nearly 85 percent of its exports in 2014, Gabon's economic growth prospects depend on how it copes with the recent oil-price slumps. Economic performance during major oil-price declines clearly illustrates the vulnerability of Gabon and other oil-dependent countries in sub-Saharan Africa. The recent oil-price slump is bound to generate a major deceleration of Gabon's non-oil economy. Given the strength of the government transmission channel, the authorities should support economic activity (through productive spending) while ensuring fiscal sustainability.

Economic Impact of the Oil-Price Slump1

With oil accounting for roughly 40 percent of its GDP, 45 percent of its government revenues, and nearly 85 percent of its exports in 2014, Gabon’s economic growth prospects depend on how it copes with the recent oil-price slumps. Past major oil-price declines caused a contraction in non-oil economic activity. Statistical analysis (including regression analysis) indicates that a major deceleration of Gabon’s non-oil economy is likely, albeit at a slower pace than in the past.

A. Oil-Price Shocks in Sub-Saharan Africa

1. Economic performance during major oil-price declines clearly illustrates the vulnerability of Gabon and other oil-dependent countries in Sub-Saharan Africa (SSA). The impact was more evident during the collapse in oil prices in 1986 (IMF, 2015). Following an oil-price fall of about 66 percent, average growth in real GDP in SSA oil exporting countries contracted 14 percentage points from 1985 to 1987 (from very high growth prior to the collapse in the oil price). In 1998, the 55 percent decline in oil prices was followed by a reduction of 4 percentage points in real GDP growth from 1997 to 1999. In 2008, a short-lived 43 percent reduction in oil prices in 2008 was accompanied by a 3 percentage point deceleration in real GDP growth between 2007 and 2009.

2. While countries were arguably better prepared to withstand the 2008 oil-price slump, growth decelerated significantly as they simultaneously faced the Great Recession. In 2008, SSA countries (including oil exporting countries) had more solid fiscal positions than during previous slumps and some had benefited from debt relief or favorable debt restructuring arrangements, With larger fiscal space they were able to provide fiscal impulse to face the contractionary impact of the oil-price decline. In addition, monetary policy frameworks were better designed to avoid ramping up inflation. Some countries implemented more flexible exchange rate policies than in the past, others had increased access to global financing (which had a relatively low cost as a result of expansionary monetary policies in advanced economies), and civil unrest was less common in the region. In contrast, oil exporting countries also had to face the major contraction in world demand during the Great Recession.

B. The Impact on Oil-rich CEMAC

3. The impact of oil-price slumps on non-oil economic activity in CEMAC countries has been substantial. While oil production in CEMAC countries does not immediately react to price declines as production plans are not modified in the short run, the non-oil economies of these countries are considerably affected by drastic changes in the oil price. Figure 1 shows that in the 1998 and 2008 episodes of sharp declines in the oil price, non-oil real GDP growth also decelerated rapidly and actually became negative in the aftermath of the 1998 oil-price decline. Nevertheless, non oil economic activity clearly accelerated in periods of rapid increase of the oil price, such as 2000–02, 2007–08, and 2010–12.

Figure 1.
Figure 1.

CEMAC: Oil Prices, non-oil real GDP, 1990–2014

(Percent and indices)

Citation: IMF Staff Country Reports 2016, 087; 10.5089/9781475542141.002.A001

Sources: World Economic Outlook (WEO) database and IMF Staff calculations.

4. Volatility in government spending related to oil-price fluctuations have been a major transmission channel in CEMAC countries. Governments in most oil producing countries in CEMAC are highly dependent on oil-related revenue and, in the absence of effective smoothing mechanisms, their spending is highly correlated to oil-price movements, as seen in Figure 3 (left chart). In turn, with oil revenues increasing the relative size of government spending, fluctuations in the latter are strongly associated with non-oil GDP growth (right chart in Figure 3). This implies a significant transmission channel that links oil-price fluctuations to non-oil economic activity.

Figure 2.
Figure 2.

CEMAC: Government Expenditure, Oil Price, and Non-oil GDP Growth 2000–14

(Percent)

Citation: IMF Staff Country Reports 2016, 087; 10.5089/9781475542141.002.A001

Sources: World Economic Outlook (WEO) database and IMF Staff calculations.
Figure 3.
Figure 3.

CEMAC: GDP Growth During Oil-Price Shock Episodes

Citation: IMF Staff Country Reports 2016, 087; 10.5089/9781475542141.002.A001

Sources: World Economic Outlook (WEO) database and IMF Staff calculations.

C. Oil-Price Shocks in Gabon

5. The impact of oil-price fluctuations on Gabon has been particularly strong in the past. Figure 3 shows the evolution of non-oil real GDP growth on CEMAC countries during the 1998 and 2008 oil-price downside shocks. After the 1998 episode, Gabon suffered the strongest deceleration among the CEMAC oil-exporting countries in that period, with non-oil GDP growth contracting by 11 percent in 1999. Again, following the 2008 Gabon non-oil economic activity experienced the largest contraction among CEMAC oil exporting countries of -3.3 percent in 2009.

6. The latest economic statistics also indicate a major impact of the 2014-15 oil-price slumps on Gabonese non-oil economic activity. Following the 32 percent decline in oil exports (in CFAF terms) between 2014 and 2015 several large non-oil sectors indicate a significant contraction in aggregate demand. Statistics up to September 2015 show year-on-year nominal contractions on, construction and public works (-27.3 percent), commerce (-3.7 percent), hotel/lodging (-30.2 percent), and other service categories. Declining broad money and credit to the private sector also indicate weakening economic activity.

D. Assessing Potential Impact on Gabon

7. Econometric analysis for CEMAC countries finds a significant link between oil-price fluctuations and non-oil economic activity, and implies the current slump could have a major impact on Gabon (IMF, 2015b). Panel regressions including oil exporting CEMAC countries find a significant impact of oil-price changes on non-oil GDP growth the year of the downside shock and two years after (Table 1).

Table 1.

CEMAC: Oil Shock Impact on Selected Variables1/

article image
* p<0.10, ** p<0.05, *** p<0.01 Standard errors in parenthesis

Arellano-Bond linear dynamic panel-data estimation

8. The regressions have the following general specification:

Yi,t=β1*Yi,t−1+β2*WDi,t+β3*OSi,t+εi,t

There are three sets of dependent variables (Y): real GDP growth, real non-oil GDP growth, and real government spending growth. OS is the oil (downside) shock defined as the percentage change in international oil price multiplied by the share of oil exports in GDP, where the latter is the moving average of its values in the preceding three years (a similar variable is used in IMF (2012)). WD is changes in the world demand.

9. he magnitude of the coefficients implies a major impact of the current oil-price collapse on non-oil economic activity in Gabon and highlights the importance of government spending as a transmission channel. According to these estimates, the evolution in oil prices (in CFAF terms) experienced between 2014 and 2015 and projected in the IMF World Economic Outlook for the medium run could lower non-oil GDP growth in Gabon by almost nine percentage points in 2016 (see Figure 4) with respect to potential growth. On the other hand, the high significance of government spending as a transmission channel implies that the economic impact of the oil-price slump could be significantly lowered by countercyclical fiscal policy, such as the one being implemented by the authorities.

Figure 4.
Figure 4.

Impulse Response of Gabon’s Non-Oil GDP Growth

Citation: IMF Staff Country Reports 2016, 087; 10.5089/9781475542141.002.A001

E. Structural Mitigating Factors

10. Going forward, the impact of the oil-price decline and secularly declining oil production could be mitigated by a number of structural factors. Secularly declining oil production could be at least partly offset thanks to the discovery of new wells and performance improvements. The most important offsetting factor would be effective progress in implementing the government’s diversification plan (Plan Stratégique Gabon Emergent, PSGE). The PSGE seeks to develop important sector in which Gabon has evident comparative advantages (for example, mining, agriculture, forestry, fisheries, and eco-tourism.)

11. There has been significant progress lately in supporting the diversification plan as mentioned in the staff report. The authorities are rehabilitating a Trans-gabonais railway line so as to transport wood-related and mineral exports. Olam International (a Singaporean multinational) is developing one of the largest agri-business investments currently underway in sub-Saharan Africa (using 300,000 hectares, of which 46,000 hectares is already under cultivation for oil palm and 7,500 hectares planted for rubber). Olam is also developing Special Economic Zone and port capacity. Also important is the recent creation of an investment promotion agency with support from the World Bank Group.

F. Conclusion

12. The recent oil-price slump is bound to generate a major deceleration of Gabon’s non-oil economy. The experience of previous oil-price collapses on SSA oil producers and on CEMAC countries including Gabon all point to a major reduction in non-oil GDP growth as a result of the recent decline in oil prices. Econometric estimates suggest that non-oil output will be much lower than under a no-oil price slump scenario.

13. Given the strength of the government transmission channel, the authorities should support economic activity (through productive spending) while ensuring fiscal sustainability. During the current episode the Gabonese government is in a better position to avoid procyclical fiscal policy since it has lower debt levels and higher access to global financial markets before this shock than in previous episodes. It should also carefully monitor the evolution of sectors that could amplify the impact of the oil-price slump such as the financial sector. The next Selected Issues Paper focuses on this issue. Success in accumulating the government’s stabilization fund in the future and in implementing the authorities’ diversification plan will be key to minimize the potential impact of oil price fluctuations in the medium to long run.

References

  • International Monetary Fund, April 2012, “Commodity price swings and commodity exporters,” World Economic Outlook, Chapter 4.

  • International Monetary Fund, April 2015a, “Navigating headwinds,” Regional Economic Outlook—Sub-Saharan Africa, Chapter 1.

  • International Monetary Fund, April 2015b, “The Impact of Oil Prices on Non-oil Growth,” CEMAC: Selected Issues Paper, pages 44–58.

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  • International Monetary Fund, April 2015c, “Uneven Growth: Short- and Long-Term Factors,” World Economic Outlook, Statistical Appendix.

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1

Prepared by Gonzalo Salinas.

Appendix I. Panel Analysis of the Impact and Magnitude of Oil-Price Shocks

1. The initial descriptive analysis of Sections D and C is complemented by a panel analysis of the link between NPLs and oil-price changes across oil exporters. The effect of price shocks is analyzed after controlling for both macroeconomic and financial development variables.1 The regressions are performed on oil-exporting countries using the following dynamic panel specification:

Yi,t=α+βYi,t−1+γOSit+Xi,t′δ+vi,t(1)

where i is the country index and t is the period index; Yi, t represents a proxy of financial stability; OSit is the variable measuring the oil-price shock; Xi,t represents the set of macroeconomic and financial sector variables; while vi,t, the disturbance term, is the sum of three orthogonal components: an economy-specific fixed effect ni, period fixed effects ut, and idiosyncratic shocks, ξi,t (vi,t = ni+ut+ξi,t)

2. The oil shock (OS) variable accommodates both the price and volume dimensions,2 and effectively captures oil-exporters’ exposure. Following the methodology in IMF (2012), the shock variable is defined as the percentage change in international oil prices multiplied by the economy’s reliance on oil, expressed as a lagged three-year moving average of net oil exports to GDP. The model is estimated using economic and financial data from the IFS database and FinStats over the period 1998–2013, and high frequency FSI data covering 2010-2015 from COBAC. Additional sources for macroeconomic and financial sector data used to control for the effect of oil-price shocks are Sahay et al. (2015), the World Development Indicators (WDI) and the World Development Outlook (WEO). The main econometric findings are robust to various dynamic panel techniques, including fixed effects and the Generalized Method of Moments (GMM) estimations.

3. The magnitude of the oil-price shock is modeled as a linear function of a set of conditioning variables. Equation (1) is augmented with cross-products of the shock OS and a set of variables suspected to influence the shock magnitude (Zi,t):

Yi,t=α+βYi,t−1+γ1OSit+γ2OSit*Zi,t+Xi,t′δ+vi,t′(2)

so that the marginal effects of the price shock is a linear function of Zi,t:

∂Yi,t∂OSit=γ1+γ2Zi,t.(3)

Thus the coefficient γ2 measures the effect of conditioning variables on the oil-price shock’s magnitude. Conditioning variables considered are real sector variables and financial and fiscal buffers variables. An estimated negative value for γ2 for equation (2) suggests an amplification effect of declining oil prices on financial stability.

References

  • Babihuga, Rita, 2007, “Macroeconomic and Financial Soundness Indicators: an Empirical Investigation” IMF Working Paper 7/115, (Washington: International Monetary Fund).

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  • De Bock, Reinout, and Alexander Demyanets, 2012, “Bank Asset Quality in Emerging Markets: Determinants and Spillovers,” IMF Working Paper 12/71, (Washington: International Monetary Fund).

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  • International Monetary Fund, 2012, “Commodity Price Swings and Commodity Exporters,” World Economic Outlook, Chapter 4, April.

  • International Monetary Fund, April 2015, “Navigating Headwinds,” Regional Economic Outlook—Sub-Saharan Africa, Chapter 1.

  • Kinda, Tidiane, Montfort Mlachila, and Rasmané Ouedraogo, 2016, “Commodity Price Shocks and Financial Sector Fragility,” IMF Working Paper 16/17, (Washington: International Monetary Fund).

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  • Marchettini, Daniela and Rodolfo Maino, 2015, “Systemic Risk Assessment in Low Income Countries: Balancing Financial Stability and Development,” IMF Working Paper 15/190, (Washington: International Monetary Fund).

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  • Sahay, Ratna, Martin Čihák, Papa N’Diaye, Adolfo Barajas, Ran Bi, Diana Ayala, Yuan Gao, Annette Kyobe, Lam Nguyen, Christian Saborowski, Katsiaryna Svirydzenka, and Seyed Reza Yousefi, 2015a, “Rethinking Financial Deepening: Stability and Growth in Emerging Markets,” IMF Staff Discussion Note 15/08, (Washington: International Monetary Fund).

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  • Sahay, Ratna, Martin Čihák, Papa N’Diaye, Adolfo Barajas, Srobona Mitra, Annette Kyobe, Yen Nian Mooi, and Seyed Reza Yousefi, 2015b, “Financial Inclusion: Can It Meet Multiple Macroeconomic Goals?” IMF Staff Discussion Note 15/17, (Washington: International Monetary Fund).

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1

Prepared by Neree Noumon. The author would like to thank Gabon authorities for the quality of the discussions on financial sectors issues. The author is also grateful to AFR’s Financial Network for their enriching comments.

2

In 2015, Trinidad and Tobago, Malaysia, China, Australia, Spain, Italy, Netherlands, United States, and North Korea were the main destinations of Gabon’s exports, with exports shares ranging from 14 percent of to 5 percent.

3

See Babihuga (2007) who examined 96 countries over the period 1998–2005; or De Bock and Demyanets (2012) who studied 25 emerging countries during 1996–2010.

4

In emerging markets, non-performing loans are mainly determined by GDP growth rates, exchange rates, portfolio and bank flows, and changes in terms of trade.

5

Holding sovereign wealth funds (SWF) that supplement fiscal buffers help mitigate weak fiscal buffers.

6

The minimum capital adequacy ratio required is at 8 percent and takes into consideration only credit risks. The COBAC is considering revising its capital regulation upward, so that banks can better absorb shocks.

7

Similarly, the negative effect was observed on profitability in recent months (Figure 1). The related scatter plot is not presented because of its short series and also for the sake of clarity.

8

In 2013, out of ten banks, the biggest bank in Gabon represented 43 percent and three biggest banks 65 percent of the banking sector, in terms of total assets.

9

Gabon’s fiscal balance went from a surplus of 0.3 percent of GDP in 2013 to a deficit of 4.8 percent of GDP in 2014, following the 2014 shock.

10

Banks’ claims on the central government increased by 70 percent from June 2014 to October 2015.

11

Gabon’s wage bill is unsustainable and grew from CFAF 226 billion in 2005 to CFAF 732 billion in 2015. In 2015, the wage bill accounted for 35 percent of total spending and was more important than investment spending (25 percent of total spending). Besides, the wage bill represented 53 percent of tax receipts, well above the 35 percent criteria set by the CEMAC Commission.

12

The number of civil servants significantly grew from 62594 in 2010 to 82544 employees in 2014.

13

Sustained losses lead to financial instability, depending on the intensity and duration of the oil price shock, and on prevailing policy and institutional frameworks.

14

The primary sector includes agriculture, farming, hunting, forestry and fishing.

15

This reduced credit supply is also related adverse developments and outlook in the manganese sector.

16

Short-term is used for a maturity that is less than a year; medium-term (1–5 years) and long-term (over five years).

17

To tackle limited availability of bank level data, we consider additional oil-exporting countries. Although the results of the analysis only apply to the average country in the sample, the purpose was to establish causality and identify amplifying factors.

18

Other definitions of the oil-price shock have been investigated in recent research (e.g., shock as unanticipated fall in oil prices, (see Kinda et al. (2016) for a review).

19

The instruments are validated by the Hansen test and effectively tackle endogeneity issues including that stemming from the inclusion of the lagged dependent variable at the origin of the Nickel bias (1981), whereas the Arellano–Bond supports the introduction of the lagged dependent variable.

20

Most coefficients on control variables are not significant except for FIA, which may suggest that increased access financial services could increase the vulnerabilities of banks’ assets.

21

The analysis used Sahay et al. (2015) financial development indicators. These authors define financial development as a combination of depth (size and liquidity of markets), access (ability of individuals to access financial services), and efficiency (ability of institutions to provide financial services at low cost and with sustainable revenues, and the level of activity of capital markets).

22

The focus of this section is on macroeconomic and financial factors, although institutional and governance variables are also determining (see Kinda et al. (2016)).

1

Our approach is mostly similar to the approach used in Kinda et al. (2016). The main difference lies in our focus on oil exporters and oil shocks and our definition of oil-price shock.

2

Other definitions of the oil-price shock have been investigated in recent research (e.g., shock as unanticipated fall in oil prices, (see Kinda et al. (2016) for a review).

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Cover IMF Staff Country Reports
Gabon: Selected Issues
Author: International Monetary Fund. African Dept.
Volume/Issue:
Volume 2016: Issue 087
Publisher:
International Monetary Fund
ISBN:
9781475542141
ISSN:
1934-7685
Pages:
25
DOI:
https://doi.org/10.5089/9781475542141.002

CEMAC: Oil Prices, non-oil real GDP, 1990–2014

(Percent and indices)

CEMAC: Government Expenditure, Oil Price, and Non-oil GDP Growth 2000–14

(Percent)

CEMAC: GDP Growth During Oil-Price Shock Episodes

Impulse Response of Gabon’s Non-Oil GDP Growth