The influence of “Dutch disease” on the Libya’s economy

The GDP per capital of Libya soared by 676% in the 1960s and a further 480% in the 1970s. However such fantastic growth rates proved unsustainable in the face of global oil recession and international sanctions. Consequently the GDP per capital shrank by 42% in the 1980s. Successful diversification and integration into the international community helped current GDP per capita to cut further deterioration to just 3.2% in the 1990s. Libya is an OPEC member and holds the largest proven oil reserves in Africa (followed by Nigeria and Algeria), 41.5 Gbbl (6.60×109 m3) as of January 2007, up from 39.1 Gbbl (6.22×109 m3) in 2006. About 80% of Libya’s proven oil reserves are located in the Sirte Basin, which is responsible for 90% of the country’s oil output. The state-owned National Oil Corporation (NOC) dominates Libya's oil industry, along with smaller subsidiaries, which combined account for around 50% of the country's oil output. Among NOC's subsidiaries, the largest oil producer is the Waha Oil Company (WOC), followed by the Agoco, Zueitina Oil Company (ZOC), and Sirte Oil Company (SOC). Oil resources, which account for approximately 95% of export earnings, 75% of government receipts, and over 50% of GDP. Oil revenues constitute the principal foreign exchange source.

At 2.6% per year on average, real GDP growth was modest and volatile during the 1990s. Libya's GDP grew in 2001 due to high oil prices, the end of a long cyclical drought, and increased foreign direct investment following the suspension of UN sanctions in 1999. Real GDP growth has been boosted by high oil revenues, reaching 4.6% in 2004 and 3.5% in 2005. Despite efforts to diversify the economy and encourage private sector participation, extensive controls of prices, credit, trade, and foreign exchange constrain growth.

The NOC hopes to raise oil production from 1.80 million bpd in 2006 to 2 million bpd by 2008. FDI into the oil sector is likely, which is attractive due to its low cost of oil recovery, high oil quality, and proximity to European markets. Most Libyan oil is sold on a term basis, including to the country's Oilinvest marketing network in Europe; to companies like Agip, OMV, Repsol YPF, Tupras, CEPSA, and Total; and small volumes to Asian and South African companies.1 Here come “Dutch disease” phenomena, explaining the relationship between resource production “boom” and significant decline in other spheres, especially in manufacturing.

Many scientists have analyzed the influence of oil prices fluctuations on Gross domestic product of Libya and Dutch disease phenomena. Journalist Benoit Fauconr in his article Libya Won’t Freeze Oil Production, published in Wall Street journal in 2016 proved the fact that Libya was affected by Dutch disease through the oil price shock and its correlation with the exchange rate.2

In this scientific research we examined the economic model, which describes, how GDP is affected by General government revenue, exports (taking into account, that in Libya export mainly represented by Hydrocarbon sector i.e. oil, gas and refined products, and their relation with the exchange rate, in terms of Dutch disease.

In order to analyze model 4 exogenous (independent) variables were taken: real oil prices, relation of USD/LYD, total exports and total imports; and 2 endogenous (dependent) variables – GDP and General government revenue. Model has following specification:

ГGDPt = С(1) + С(2) * GGRt + G(3) * ROPt + G(4) * OERt + £t{ GGRt = C(5) + G(6) * GDPt + C(7) * Ext + C(8) * Imt + st

Where GDP_t - Gross Domestic Product at market prices (current bln US$), GGR_t -General government revenue bln US$, ROP2_t - Real oil prices (USD per barrel), OER3_t - Official exchange rate (LYD per US$, period average), Ex_t -Exports of goods and services (constant 2010 bln US$), Im_t -Imports of goods and services (current 2010 bln US$). Data collected for the period from 1997 to 2015 from the open and reliable resources.

Estimation was made using Two-Stage Least Squares method and following results were obtained:

Estimation Method: Two-Stage Least Squares

Sample: 1997 2015

Included observations: 19

Total system (balanced) observations 38

	Coefficient	Std. Error	t-Statistic	Prob.
C(1)	21.85113	2.932730	7.450782	0.0000
C(2)	1.105023	0.071884	15.37242	0.0000
C(3)	0.078962	0.042527	1.856755	0.0732
C(4)	-6.977139	3.273978	-2.131089	0.0414
C(5)	-6.503235	2.397482	-2.712527	0.0109
C(6)	0.457867	0.114617	3.994753	0.0004
C(7)	0.471340	0.117798	4.001254	0.0004
C(8)	-0.116707	0.051061	-2.285625	0.0295

Determinant residual covariance    22.12389

Equation: GDPt=C(1)+C(2)*GGRt+C(3)*ROPt+C(4)*OERt

Instruments: ROPt OERt Ext Imt C

Observations: 19

R-squared	0.970287	Mean dependent var	47.01785
Adjusted R-squared	0.964344	S.D. dependent var	20.45989
S.E. of regression	3.863392	Sum squared resid	223.8869
Durbin-Watson stat	1.166175

Equation: GGRt=C(5)+C(6)*GDPt+C(7)*Ext+C(8)*Imt Instruments: ROPt OERt Ext Imt C

Observations: 19

R-squared	0.987265	Mean dependent var	25.53691
Adjusted R-squared	0.984718	S.D. dependent var	17.56264
S.E. of regression	2.171123	Sum squared resid	70.70663
Durbin-Watson stat	1.940193

Value of the multiple coefficient of determination R2=0,97 shows that 97 % of total deviation of GDP is explained by the variation of general government revenue, oil prices and in relation of USD/LYD. Such a high value of the R2 is quite good it is close to 1 (maximumR2 = 1). This means that selected factors influence the given model significantly.3 DW test was passed successfully and this means that no autocorrelation detected, F-test was passed as well.

Conclusion

Nowadays, research on the “Dutch disease” problem become especially relevant due to interesting economic trends arising on the world market. Libya as a huge oil-exporter needs a lot of attention in terms of high volatility. For oilproducing country it is a real struggle to face the “Dutch disease” phenomena in conditions of world economic crises. It was mentioned previously, that any market volatility could provoke economic misbalances.

After model’ analysis, based on economic data for the period 1997-2015, we are able to make following conclusions: model used, could possibly be used to estimate influence of used factors on gross domestic product, how changes are determined by general government revenue, oil prices and net exports as well as exchange rate, in terms of “Dutch disease”. Libyan economy relies heavily on hydrocarbon sector and depends on exports volume. There are several common methods .

«Экономика и социум» №2(33) 2017