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Domestic impact of production cuts in OPEC countries:
The cases of Nigeria and Venezuela
Ramón Key and Claudina Villarroel
Universidad Central de Venezuela
Ecomod Conference
Bali, Indonesia
2014
Abstract
In this century, the oil market has seen the active role of OPEC to stabilize the market
when prices show strong downward trends. Although the literature on the behavior
of OPEC shows no consensus on the model that best characterizes this organization,
there is strong evidence that the production quotas are an important determinant of
production of OPEC countries. Kaufmann et al (2004 and 2006) and Brémond et al
(2012) concluded that the organization exerts market power and can alter the
formation of prices at least in the short term. In the short term there are risks to both
supply (increased production of raw shale) and demand (financial instability) that can
lead to further production cuts by OPEC. This paper aims to quantify the domestic
costs of such cuts for Nigeria and Venezuela. Using a computable general equilibrium
model is measure the domestic impacts of these oil production cuts in Venezuela and
Nigeria, countries that show relative degree of diversification in their economies
compared to most other OPEC countries are measured. The economics costs
associated with production cuts in terms of contraction of total activity,
unemployment and inflation account for the observed decrease in level of compliance
of OPEC´s cuts in these two countries.
Keywords: computable general equilibrium models, OPEC, oil prices, oil production,
Venezuela, Nigeria.
2
1. Introduction
OPEC claims that the aim of this organization is to coordinate and unify the petroleum
policies among its member countries to ensure a safe and stable supply of income to its
members. One way to achieve their goals is through agreements allocating production
quotas. In an extensive literature review conducted by Al-Qahtani, Balestreri and Dahl
(2008) on the behavior of OPEC these authors conclude that there is no consensus about
the model that best characterize the behavior of this organization. However, they also
point out the existence of empirical studies developed from the seminal work of Griffin
(1985) as Kaufmann et al (2004, 2008) showing that production quotas are an important
determinant of production in OPEC countries. These empirical works imply that this
organization exerts market power and can alter the formation of prices. In a more recent
study conducted by Brémond et al (2012) the authors wonder if OPEC acts as a cartel and
evaluate the degree of coordination of production between member countries. They
conclude that OPEC behavior evolves over time. That is, the organization acts as a cartel
when facing significant shocks (affecting residual demand) setting oil production quotas.
But once this stage is complete and the short-term crisis is overcome, the organization
acts as a price taker agent.
In this century, the oil market players have seen the active role of OPEC in its effort to
stabilize the market when prices show a pronounced downward trend. Section 2 discusses
in detail the role of OPEC to stabilize the market in this century; particularly three periods
are analyzed. Such periods are February 2001-January 2002, November 2006 - February
3
2007 and October 2008 - January 2009 where explicit or implicit cuts are made. The
approach used in this section is purely descriptive and seeks to determine the
circumstances that led OPEC to act in the short term. The purpose is to determine for each
of these events the magnitude of the cuts involved, the level of compliance with
agreements (particularly Venezuela and Nigeria), and the eventual recovery in prices over
time. Regarding the level of compliance with agreements of production cuts it is noted
that Nigeria generally has a relatively low level of compliance (ranging between 30% -
43%) in relation to Venezuela (ranging between 45% - 87 %) and the rest of OPEC
countries (ranging between 60% - 78%). It is noteworthy that during the first two events
of production cuts, Venezuela stands out by exhibiting a level of compliance well above
the average of the OPEC countries. Only during the most recent episode of production
cuts, the country shows a level of compliance below the average of OPEC. It is argued in
the paper that the relatively low compliance rates in Nigeria and decreasing compliance
rates in Venezuela are due to the economic costs associated with such oil production cuts.
In section 3 are analyzed the existence of risks of both supply and demand than can lead
to further production cuts by OPEC in the short term (2014-2015). The purpose of this
section is to highlight the validity and relevance of the topic of production cuts. In 2013
and 2014, the fall in the average price of the OPEC basket was 8% and 9% respectively,
reaching in 2014 an average of $ 105 / Bl ($ 95 / barrel for WTI ). Because of this drop in
prices, and the reasons behind them, are not discarded in the near future new OPEC
interventions in the market; in particular further cuts are not ruled out in the current
production levels of OPEC. On the one hand, there is evidence that the production of non-
4
OPEC countries has been increasing over the growth in total oil demand (for the
emergence of shale oil production, a supply shock). On the other hand, risk situations for
global financial stability (IMF, 2013) that threaten the future growth of oil demand
(potential negative demand shocks) are maintained.
When considering the impact of production cuts in the domestic economies of the OPEC
countries, the cases of Nigeria and Venezuela are of particular interest because their
economies show a relative degree of diversification compared to most other OPEC
countries. Various indicators that reflect the degree of economic diversification in these
two countries are presented in Section 4. Further comparative indicators of the economy
of these two countries are presented in this section.
In order to measure the impact of production cuts in Nigeria and Venezuela is used for
each country a computable general equilibrium model. The structure of the proposed
model is developed in Section 5. The social accounting matrix for each country
corresponds to the year 2006. In the case of Venezuela the information comes mainly
from the Central Bank of Venezuela. In the case of Nigeria the information comes from the
International Food Policy Research Institute (IFPRI), M. Nwafor, X. Diao and Alpuerto V.
(2006). The model used in this work is a standard general equilibrium model in the sense
that define N. Hosoe, K. and Hashimoto Gasawa H. (2010), Lofgren H., RL Harris and S.
Robinson (2002), Burfisher M. (2011), Bayar A. (2013). The model structure used in this
work is adapted from other standard general equilibrium models used by the authors in
previous works on Venezuela. The model presented in this paper includes 10 activities:
5
agriculture, oil and refining, mining, manufacturing, electricity, construction, trade,
transport and communications, financial services, other services.
In addition to the issues of the number of activities, other modifications made to previous
work includes the changes in the boundary conditions related to household savings, the
inclusion of income equations and savings for businesses, including interagency transfers
beyond those made by the government to households, and the modification of the
external sector block to deal with cases of non-exportable or importable goods.
In section 6 are presented the effects of production cuts in the two countries. Section 7
present final conclusions.
2. Circumstances of OPEC production cuts in this century and
percentages of compliance
There is empirical evidence on the impact of OPEC at least in the short term. Kaufmann et
al (2004, 2008) shows that production quotas are an important determinant of production
of OPEC countries. Bremond et al (2012) conclude that OPEC behavior evolves over time.
It behaves as a cartel when it faces significant shocks (supply or demand) which merit
setting quotas. But these authors also note that once this stage is completed short-term,
the organization acts as a price taker agent.
This section discusses three recent periods where OPEC made use of explicit or implicit
mechanisms of production cuts. Excluded from this analysis is the period 2003 - 2005
because there are several reasons recommending it. The first is that although quota
allocations were recorded, in most cases, it was about expanding OPEC production. The
6
second is that the quota allocated to Venezuela was above its production, this as a result
of the oil strike started in late 2002 whose consequences were felt during the following
months.
In this section the purpose is to determine for each of the three major events of OPEC
intervention the magnitude of the cuts involved, the level of compliance with agreements
(particularly Venezuela and Nigeria), and the eventual recovery in prices over time.
February 2001 - January 2002:
In previous dates, 3 months before, WTI prices had reflected a fall of 28.8% when taking
the variation between the maximum and minimum prices. The fall in prices was motivated
by increasing concerns about the weakening conditions in the U.S. economy. In this period
the U.S. economy goes into recession and it spreads to the rest of the industrialized
countries and the group of emerging countries.
In response to this decline in prices, OPEC called progressive implicit cuts on the
production of member countries (excluding Iraq). Initially the cuts announced by the
organization were 4.7% for total OPEC, Venezuela 4.1%, and Nigeria 3.4%. Subsequently it
was followed by three additional cuts. We refer these production cuts as implicit because
what actually occurred was the capping of total production. Thus implicit cut is
determined by comparing the respective production allocations against the prevailing
production in January 2001.
It is noted that the recovery in prices due to the action of the cuts will not occur
immediately. In fact, during the period in which they carry out these cuts, the average
7
prices descended 18.1% from the prevailing average of three-months-prior to the cuts.
After six (6) months from the cuts, the average prices during that period were 0.4% higher
than those prevailing during the execution of production cuts. However prices were 18.5%
below the average prices prevailing three-months-prior to the action taken by OPEC. After
one (1) year, the average prices during that period were 8.5% higher than those prevailing
during the cuts. However prices were 11.5% below the average prices prevailing three-
months-prior to the action taken by OPEC. In general, these results in prices, in the
presence of demand shocks, are consistent with oligopoly models leader-follower type
where the leader is OPEC and the followers are the non-OPEC producer. See Nicholson
(2005), Call and Hollahan (1985). Although OPEC reduced production to achieve a new
optimal price, it will never be the same to the initially prevailed (unless the initial demand
shock is reversed).
Table 2.1 shows Information to help visualize the evolution of prices comparing it to
different time reference points. Horizontally, are identified sub-reference periods ranging
from three-months-before the cuts up to 1-year-after the cuts. To facilitate cross-time
referencing, vertically are also identified in the last two columns two sub-time periods.
8
Value Date
Change in
%, between
extreme
values
Change in
%,
compared to
3 months
before cuts
Change in
%,
compared to
period of
production
cuts
3 months before (Nov 2000 - Jan 2001)
Max 36,2 nov 27, 2000
Min 25,8 dec 28, 2000 -28,8%
average 30,9
Period of Production Cuts (Feb 2001 - Jan 2002)
Max 31,6 feb 08, 2001
Min 17,5 nov 19, 2001 -44,6%
average 25,2 -18,5%
3 months after (Feb 2002 - Apr 2002)
Max 27,8 apr 02, 2002 40,5%
Min 19,8 feb 07, 2002
average 23,9 -22,4% -4,8%
6 months after (Feb 2002 - Jul 2002)
Max 29,2 may 15, 2002 47,7%
Min 19,8 feb 07, 2002
average 25,3 -18,1% 0,4%
1 year after (feb 2002 - ene 2003)
Max 35,0 Jan 24, 2003 77,1%
Min 19,8 feb 07, 2002
promedio 27,3 -11,5% 8,5%
Table 2.1 Oil production cuts: Feb. 2001 – Jan. 2002 Oil price behavior WTI $/Bl
Source: own calculations based on WTI daily information reported by EIA-DOE
(http://eia.gov).
Table 2.2 gives information on the percentage of compliance with the cuts announced by
OPEC. The information considered as relevant is the one at the end of the period, as it
collects cumulative effects of prior actions by OPEC, avoiding volatility in the data. In the
case of Venezuela, the level of compliance was 88% while Nigeria was 43%. It is
noteworthy that during this period the average compliance of other OPEC countries was
78%. Venezuela thus exhibits a higher than average level compared to other OPEC
9
Venezuela Nigeria Venezuela Nigeria Venezuela Nigeria Venezuela Nigeria Venezuela Nigeria
2001
January 3027 2147
February 2957 2118 2902 2075 -4,1% -3,4% -2,3% -1,4% 56,0% 40,3%
March 2953 2127 -2,4% -0,9%
April 2867 2058 2786 1993 -8,0% -7,2% -5,3% -4,1% 66,4% 57,8%
May 2834 2027 -6,4% -5,6%
June 2833 2064 -6,4% -3,9%
July 2847 2018 -5,9% -6,0%
August 2839 2070 -6,2% -3,6%
September 2713 2175 2670 1911 -11,8% -11,0% -10,4% 1,3% 88,0% -11,9%
October 2707 2145 -10,6% -0,1%
November 2704 2086 -10,7% -2,8%
December 2698 2080 -10,9% -3,1%
2002
January 2561 1992 2497 1787 -17,5% -16,8% -15,4% -7,2% 87,9% 43,1%
Compliance of OPEC
cuts %
Production Production Allocation
according to OPEC
Cuts asked from
OPEC %
Effective Production
Cuts %
countries, even higher than the level of compliance of Saudi Arabia, UAE, Qatar and
Kuwait.
Table 2.2 Oil production cuts: Feb. 2001 – Jan. 2002 % compliance
Fuente: Own calculations based on OPEC (Market Indicators http://opec.org).
November 2006 - February 2007:
This time it was a collapse of prices driven by inventory accumulation, growth
expectations for non-OPEC supply, with high winter temperatures and lower growth in
global oil demand by the decline of the residential construction sector in the U.S. (see oil
market report November, OPEC_b.2006). Moreover, the bimonthly bulletin of OPEC
corresponding to November and December added as an additional factor in the drop in
prices the relaxation in geopolitical pressures in the Middle East (OPEC Bulletin, 2006). As
result, collapse in prices is manifested in a fall of 26.4% when taking the variations
between the high and low prices recorded three months before the actions by OPEC.
10
Value Date
Change in
%, between
extreme
values
Change in
%,
compared to
3 months
before cuts
Change in
%,
compared to
period of
production
cuts
3 months before (Aug 2000 - Oct 2001)
Max 77,1 aug 07, 2006
Min 56,7 oct 23, 2006 -26,4%
average 65,4
Period of Production Cuts (Nov 2006 - Feb 2007)
Max 63,4 dic 01, 2006
Min 50,5 jan 18, 2007 -20,4%
average 58,6 -10,3%
3 months after (Mar 2007 - May 2007)
Max 66,5 feb 28, 2008 17,8%
Min 56,4 mar 20, 2007
average 62,6 -4,3% 6,7%
6 months after (Mar 2007 - Aug 2007)
Max 78,2 jul 31, 2007 38,6%
Min 56,4 mar 20, 2007
average 67,0 2,4% 14,2%
1 year after (Mar 2007 - Feb 2008)
Max 102,6 jan 28, 2008 81,9%
Min 56,4 mar 20, 2007
average 78,3 19,8% 33,6%
Table 2.3 Oil production cuts: Nov. 2006 – Feb. 2007 Oil behavior WTI $/Bl
Source: own calculations based on WTI daily information reported by EIA-DOE
(http://eia.gov).
During this period occur two explicit cuts for OPEC countries (excluding Iraq and Angola).
In November 2006, a reduction of 1,200 thousand barrels per day to the total OPEC is
announced. In February of the following year a further cut of 500 thousand barrels per day
is announced. In the case of Venezuela the cumulative production cut was 7.7% while in
Nigeria was 6.3%. This time the nature of the shocks show evidence of greater temporality
as prices recover relatively fast. After three months from the cuts, the average prices for
11
Venezuela Nigeria Venezuela Nigeria Venezuela Nigeria Venezuela Nigeria Venezuela Nigeria
2006
October 2523 2249
November 2458 2236 138 100 -5,5% -4,4% -2,6% -0,6% 47,1% 13,0%
December 2474 2259 -1,9% 0,4%
2007
January 2424 2215 -3,9% -1,5%
February 2394 2207 57 42 -7,7% -6,3% -5,1% -1,9% 66,2% 29,6%
Production Production
Allocation according
to OPEC
Cuts asked from
OPEC %
Effective Production
Cuts % Compliance of OPEC
cuts %
the period were 7% higher than those prevailing during the cuts. Six (6) months from the
cuts, the average prices for the period were 14% higher than those prevailing during the
cuts and 2% above the average price prior to the action taken by OPEC. After one (1) year,
prices had recovered an average of 20% over the average prices prevailing three (3)
months prior to the action taken by OPEC.
This time the level of compliance of Venezuela is 66.2% while Nigeria exhibits a 29.6% of
compliance. As in previous case, Venezuela exhibits a level of performance above the
average of the other OPEC countries this being 60.3%. However, Nigeria consistently
exhibits a level of compliance that is about half of the remaining of OPEC countries.
Table 2.4 Oil production cuts: Nov. 2006 – Feb. 2007 % compliance
Fuente: Own calculations based on OPEC (Market Indicators http://opec.org).
October 2008 - January 2009:
During this period three cuts that are a combination of implicit and explicit cuts occur. A
cumulative cut of 14.5% was recorded for both countries. This time only the cuts in
November 2008 are explicit for each member country.
12
In previous dates, three months before, the price of WTI fell 37% from $/Bl 145 on July 14
to $/Bl 91.5 on September 16 in the year 2008. The origins of this price collapse were a
global financial collapse following the bankruptcy of Lehman Brother that weakened the
global macroeconomic performance and consequently affected the demand for crude oil.
During the period in which it is carried out the cuts, average prices fall even further (54%)
over the prevailing average three-months-before the cuts. Even the prices record levels
around $/Bl 30 (23 December 2008). In this case there is a gradual recovery episode rates.
However, to this date the prices have not recovered to pre-shock levels.
After three (3) months from the cuts, the average prices was 16% lower than those
prevailing during the cuts and 61% below the average prices prevailing before the actions
taken by OPEC. After six (6) months, the average prices were 1% higher than the average
during cuts and 53% below the average prices prevailing before the actions taken by
OPEC. After one (1) year, prices had recovered on average 19% from the average
prevailing during the OPEC cuts. However, prices were on average 45% below the prices
before the actions taken by OPEC. Note that even in the current date WTI prices are 34%
below the peak reached of $/bl 145.
Venezuela has a level of compliance with production cuts of 45% while for Nigeria the
compliance level was 35%. Highlights at this time that of three episodes discussed for the
first time Venezuela registers a level below that of the other OPEC countries (67%)
compliance.
13
Value Date
Change in
%, between
extreme
values
Change in
%,
compared to
3 months
before cuts
Change in
%,
compared to
period of
production
cuts
3 months before (Jul 2008 - Sep 2006)
Max 145,3 jul 14, 2008
Min 91,5 sep 16, 2008 -37,0%
average 118,3
Period of Production Cuts (Oct 2008 - Jan 2009)
Max 98,2 oct01, 2008
Min 30,3 feb 12, 2009 -69,2%
average 54,6 -53,8%
3 months after (Feb 2009 - Apr 2009)
Max 53,9 mar 26, 2009 58,3%
Min 34,0 feb 12, 2009
average 45,8 -61,3% -16,2%
6 months after (Feb 2009 - Jul 2009)
Max 72,7 jun 11, 2009 113,6%
Min 34,0 feb 12, 2009
average 55,3 -53,3% 1,2%
1 year after (feb 2002 - ene 2003)
Max 83,1 jan 06, 2010 144,3%
Min 34,0 feb 12, 2009
promedio 64,8 -45,2% 18,6%
Tabla 2.5 Oil production cuts: Oct. 2008 – Ene. 2009 Oil price behavior WTI $/Bl
Source: own calculations based on WTI daily information reported by EIA-DOE
(http://eia.gov).
Of the three episodes of production cuts discussed in this section are set the following
observations:
i. The OPEC action is triggered by the empirical observation of a variation
between the maximum and minimum values of price greater than 25%.
ii. The adjustment process of OPEC production to demand shocks is in most cases
a continuous action, ie involving more than one time adjustment in production.
14
Venezuela Nigeria Venezuela Nigeria Venezuela Nigeria Venezuela Nigeria Venezuela Nigeria
2008
Septiembre 2350 1992
Octubre 2321 1967 19 16 * -0,8% -0,8% -1,2% -1,3% 153% 154%
Noviembre 2301 1913 129 113 -6,3% -6,5% -2,1% -2,7% 33% 42%
Diciembre 2275 1914 -3,2% 0,1%
2009
Enero 2196 1891 192 159 * -14,5% -14,5% -6,6% -5,1% 45% 35%
Production Production Allocation
according to OPEC
Cuts asked from
OPEC %
Effective Production
Cuts % Compliance of OPEC
cuts %
The cumulative adjustments analyzed involved substantial reductions in the
range of 6% - 18%.
iii. Regarding the level of compliance with agreements of production cuts it is
noted that Nigeria generally has a relatively low level of compliance (ranging
between 30% - 43%) in relation to Venezuela (ranging between 45% - 87 %)
and the rest of OPEC countries (ranging between 60% - 78%). It is noteworthy
that during the first two events of production cuts, Venezuela stands out by
exhibiting a level of compliance well above the average of the OPEC countries.
Only during the most recent episode of production cuts, the country shows a
level of compliance below the average of OPEC.
Table 2.6 Oil production cuts: Oct. 2006 – Ene. 2009 % compliance
Fuente: Own calculations based on OPEC (Market Indicators http://opec.org).
15
3. Measuring the risk of new production cuts in the short-term
Since the last cuts ended in 2009, the OPEC basket price has shown relative stability. A
progressive decrease in the standard deviation is shown in Table 3.1. In 2009 the standard
deviation was 20%. By 2013 the standard deviation was 3.4% and for 2014 it was 1.2%.
Despite this relative price stability during the years 2013 and 2014 the average price of the
OPEC basket has slipped down 8% and 9% respectively, reaching in 2014 (end of April) an
average of $ 105 / Bl ($ 95 / Bl for WTI). Because of this drop in prices, and the reasons
behind them, are not discarded in the near future new market interventions by OPEC.
On one hand there is evidence that the production of non-OPEC countries has been
increasing above the growth in total oil demand (positive supply shocks). On the other
hand, risk situations still present for global financial stability (identified by the IMF itself)
that threaten also the future growth of oil demand.
Regarding oil supply by non-OPEC, it is outstanding the sustained growth experienced oil
production from North America, growing on average 6.2% per year during the period
2010-2014. In this growth the role of U.S. production has been crucial, growing an
average 8.7% per year (This according to figures reported by both the International Energy
Agency and OPEC). The driving force behind the increase in supply from North America is
technology. In the case of the U.S., the application of recent technological developments
has significantly increased the production of shale oil.
16
Maximum
Price
Minimum
Price
Average
Price
% Change
Average
% Standard
Deviation
2009 77,9 38,1 61,1 20,7%
2010 77,4 66,8 77,4 26,8% 6,9%
2011 120,9 89,81 107,5 38,8% 6,1%
2012 124,6 88,7 124,6 16,0% 6,4%
2013 114,9 96,4 114,9 -7,8% 3,4%
2014* 107,8 101,6 104,6 -9,0% 1,2%
2010 2011 2012 2013 2014 2015 Change 2015/2013
% Change Mill. Barrels
Crude oil Demand 87,3 88,1 89,0 90,0 91,2 92,5 1,4% 2,5
Total Supply Excluding OPEC´s crude oil 57,3 57,8 58,4 60,0 61,5 63,5 2,9% 3,5
Demand of OPEC´s Crude Oil 30,0 30,3 30,6 30,0 29,7 29,0 -1,7% -1,0
OPEC´s crude oil production 29,2 29,8 31,1 30,2
Balance (Inventories) -0,8 -0,5 0,5 0,2
The expected oil market balance for the years 2014 and 2015 are presented in Table 3.2.
The balance of 2014 is a short-term estimation according to the Monthly Oil Market
Report (OPEC, April 2014). The 2015 balance is based on the initial balance of 2014 and
growth rates for demand and non-OPEC supply according to the publication World Oil
Outlook (OPEC, 2013). According to these balances which assumes a global economic
growth of 3.4% is expected a decrease in demand for OPEC crude oil up to 1 MBD by 2015
from reached levels in 2013.
Table 3.1
OPEC barquet 2010 -2015, $/Bl
*Up to April 2014. Source: based on OPEC data
Table 3.2 Oil Market Balance (million barrels per day)
Source: based on OPEC, Monthly Oil Market Report and World Oil Outlook 2013
17
When adding up the effects of global economic growth risks (low growth demand), and
the effects of oil production risk in North America (increased oil production), the demand
for OPEC crude oil could be further reduced. Consider for instance the global economic
growth; the International Monetary Fund indicates the presence of risks in the transition
on the path to greater global financial stability. In particular it pointed out first, the
presence or absence of a gradual transition of the U.S. monetary policy of prolonged
flexible and accommodative policy for economic recovery towards normalization of
monetary conditions; second, it pointed out the presence of more volatile external
conditions and higher risk premiums for emerging countries (IMF, 2013).
Consider for instance the oil production in the region of North America; according to OPEC
long-term view (OPEC, 2013) shale oil will play a key role until 2020, expecting production
reaching 5 MBD in 2017. According this vision, shale oil in North America will influence
deeply the oil market balances in the short term.
Now let´s consider the short-term effects of both a decline in global economic growth and
an increase in the expected growth of oil supply in North America. Analyzing the effects of
a decline in global economic growth, let´s start saying that during the period 1990 - 2013
the standard deviation for this variable was 1.27%. Considering the production of crude oil
in North America, the standard deviation in the period 2009 - 2013 was 1.4 MBD. A ½
standard deviation decline in economic growth in the short term (holding constant
demand elasticity with respect to overall GDP growth around 0.418) demand for OPEC
crude would decrease 0.5 thousand barrels per day. A ½ standard deviation increase in oil
18
production in North America would reduce the residual crude oil demand for OPEC crude
oil by 0.7 MBD.
By introducing these two risk elements, the demand for OPEC crude could be reduced by
1.2 MBD; which should the added to the reduction already expected of 1.0 MBD in the
initial market balance shown in table 3.2. Therefore in the short term it is likely to expect
the presence of further cuts coming from OPEC. For all these reasons, the issue of
production cuts in producing countries of OPEC and its domestic effects in their
economies becomes relevant one more time in the short term. In this paper the effects of
production cuts on Nigeria and Venezuela, founding members of OPEC countries are
analyzed. These two countries together account for 15% of OPEC production (6% Nigeria,
Venezuela 9%) and 28% of proven oil reserves within this organization (3% and 25%
respectively).
4. The economies of Nigeria and Venezuela
The cases of Nigeria and Venezuela are of particular interest because their economies
show a relative degree of diversification compared to other OPEC countries. A comparable
indicator of the economic diversification in a country is the standard deviation of the
weights of value added of all economic activities. Table 4.1 displays information from the
World Bank (2014, http://datos.bancomundial.org/indicador) identifying four economic
activities: agriculture, manufacturing, other industries, and services; showing weights of
each activity in the total value added of each country. The last column in such table shows
the standard deviation respect to an average participation of 25% for each sector.
19
Countries that show lower standard deviation exhibit a higher degree of economic
diversification. According to this indicator, Indonesia is the country that exhibits the
greater degree of economic diversification in OPEC countries, followed by Nigeria, Iran
and Venezuela. Note that since 2008 Indonesia does not belong to OPEC.
In Nigeria, the agricultural sector in the country is undoubtedly the relatively more
developed sector within OPEC reaching 33% of the aggregate value, followed by Iran with
10%. In the case of Venezuela, the manufacturing sector was the most developed
(relatively) within OPEC reaching 14% of the value added, followed by Ecuador 12% and
Iran 11%. As reference, Indonesia exhibits a relative weight of 14% in agriculture and 24%
in the manufacturing sector.
Now let´s consider macroeconomic information of Venezuela and Nigeria for the years 2006
(the year available for the social accounting matrices for each country) and 2012 (latest
year available, according to information reported by the statistical yearbook OPEC).
By 2006 both economies show a strong external position with a current account surplus of over 20
billion dollars (Nigeria 23 bill. dollars, Venezuela 27 bill. dollars). During 2006 Venezuela grew at a
rate of 10% with 10% unemployment and 14% inflation; while Nigeria grew at a lower rate of 6% ,
unemployment rate at 12% and an inflation rate of 8%. Regarding fiscal accounts, the information
for this year reveals a general government surplus of 9% of GDP in financing needs in Nigeria,
while in Venezuela a slight deficit below 2% was recorded.
20
Most recent
available
informationAgriculture Manufacturing
Other
IndustriesServices
Standard
Deviation
Algeria 2012 9,3 0,0 48,5 42,2 23,9
Angola 2012 10,0 6,3 53,3 30,3 21,6
Ecuador 2012 9,9 12,3 24,6 53,3 19,9
Indonesia 2012 14,4 23,9 23,0 38,6 10,0
Iran 2007 10,2 10,6 33,9 45,3 17,5
Irak none - - - - -
Kuwait 2003 0,5 2,3 48,7 48,5 27,3
Libya 2008 1,9 4,5 73,7 19,9 33,4
Nigeria 2012 33,1 1,9 38,7 26,3 16,2
Qatar none - - - - -
Saudi Arabia 2012 2,2 10,1 52,5 35,2 23,1
United Arab Emirates 2012 0,7 9,0 51,5 38,8 24,1
Venezuela 2010 5,8 13,9 38,2 42,1 17,9
Table 4.1 Economic diversification in OPEC countries Percentage of total value added
Source: own calculations based on World Bank Database.
By 2012, conditions in Nigeria are very similar to those of 2006. Robust external position
with a current account surplus of 22 billion dollars, net financing needs of central
government less than 1%, economic growth of 6.6 % and annual inflation of 12%. In terms
of unemployment, the last figure reported by the IMF and corresponding to the official
figures reported by the national statistics agency shows that this rose to 24%. However,
according to estimates by the World Bank according to the methodology of the
International Labor Organization, this is at 7.5%. For Venezuela, the picture presented in
2012 is quite different. The current account surplus is reduced by almost two thirds,
reaching 11 billion dollars. The financing needs of the government reach 17% of GDP
according to the IMF. Despite these imbalances, economic activity reported a growth of
5.6% with an inflation rate of 21% and an unemployment rate of 7.8%.
21
Variables Units
2006 2012 2006 2012
Population million people 134,4 167,7 27,0 29,5
Land area thousandsquare Km 924 924 916 916
Proven crude oil reserves billion barrels 36,2 37,1 87,0 297,7
Refining capacity thousand barrels /day 445 445 1040 1524
GDP at market prices billion $ 115,4 257,4 182,1 383,4
GDP Per Capita $ 858 1535 6735 12956
GDP growth % 6,2 6,6 9,9 5,6
Inflation % 8,2 12,2 13,7 21,1
Unemployment rate % 12,3 23,9 10,0 7,8
Exports values billion $ 52,8 142,5 65,2 97,3
Imports values billion $ 27,4 35,7 32,2 59,3
Current account billion $ 23,2 23,4 27,2 11,0
current account % gdp 36,8 7,7 14,4 2,9
Exchange rate local currency/$ 128,7 156,8 2,1 4,3
General Government, Net
borrowing/lending % gdp 8,94 -0,03 -1,61 -16,60
Crude oil production thosand barrels/day 2234 1954 3107 2804
Crude oil demand thosand barrels/day 256 344 532 786
Crude oil exports thosand barreles/day 2248 2368 1735 1725
Refining products exports thosand barreles/day 50,3 8,2 529,9 675,1
Value of Oil Exports billion $ 48,4 94,6 52,5 93,6
Nigeria Venezuela
Table 4.2 Economic indicators of Nigeria and Venezuela
Sources: OPEC Bulletin (2006, 2012), IMF Data Base (World Economic Outlook Database,
April 2014).
22
5. A CGE framework for measuring domestic effects of oil production
cuts
To measure the impact of production cuts in Nigeria and Venezuela is develop a CGE
model for each country. The social accounting matrix for each country corresponds to the
year 2006. In the case of Venezuela, the information comes from primarily from the
Central Bank. In the case of Nigeria the information comes from the International Food
Policy Research Institute (IFPRI), M. Nwafor, X. Diao and Alpuerto V. (2006).
The model developed in this work is a standard CGE model in the sense that define N.
Hosoe, K. and Hashimoto Gasawa H. (2010) and H. Lofgren, Harris RL and S. Robinson
(2002). The model includes 10 activities: agriculture, oil and refining, mining,
manufacturing, electricity, construction, trade, transport and communications, financial
services, and other services. The model used here is similar in structure to other models
used by the authors in previous work on Venezuela. Changes to other previous models
include modifying the boundary conditions related to household savings to deal with
negative savings, the inclusion of income and saving equations for companies, full details
of institutional transfers, and the modification of the external sector block to deal with
cases of non-exportable or importable goods.
Following Lofgren H., Harris R.L. and Robinson S. (2002), the equations related to import
demand, demand for domestic goods, and the Armington zero profit condition of the
Armington are restricted to importable activities while incorporating a new equation
matching domestic production that goes to the domestic market with sales of the
23
compound good in the case of non-importable goods. The equations related to the supply
of exports, the supply of domestic goods, and the zero profit condition for sale between
the two markets is restricted to the sub-set of activities whose goods are exportable while
incorporating a new equation that equals domestic production to production destined for
the domestic market for non-tradable good.
The following are general details of the proposed model for both countries.
Firms
The production function used in this model is multilevel where the value added and
intermediate inputs are combined in fixed proportion through a Leontief production
function. Moreover, at another level, we there is capital-labor substitution through a
function with constant elasticity of substitution (CES).
The optimizing behavior of the company in general is summarized by the factor demands
and the profit equation:
5.1 𝐾𝑖 = (𝑋𝐷𝑖
𝑎𝐹𝑖) (
𝛾𝐹𝑖
𝑃𝐾𝑖)
𝜎𝐹𝑖
(𝛾𝐹𝑖𝜎𝐹𝑖𝑃𝐾𝑖
1−𝜎𝐹𝑖 + (1 − 𝛾𝐹𝑖)𝜎𝐹𝑖𝑃𝐿1−𝜎𝐹𝑖)
𝜎𝐹𝑖1−𝜎𝐹𝑖
5.2 𝐿𝑖
= (𝑋𝐷𝑖
𝑎𝐹𝑖) (
1 − 𝛾𝐹𝑖
𝑃𝐿)
𝜎𝐹𝑖
(𝛾𝐹𝑖𝜎𝐹𝑖𝑃𝐾𝑖
1−𝜎𝐹𝑖 + (1 − 𝛾𝐹𝑖)𝜎𝐹𝑖𝑃𝐿1−𝜎𝐹𝑖)
𝜎𝐹𝑖1−𝜎𝐹𝑖
5.3 𝑃𝐷𝑖 . 𝑋𝐷𝑖 = 𝑃𝐾𝑖. 𝐾𝑖 + 𝑃𝐿. 𝐿𝑖 + ∑(𝑃𝐷𝑗 . 𝑖𝑜𝑗𝑖). 𝑋𝐷𝑖
𝑗
24
Consider this set of equations by replacing 𝑃𝐿 by 𝑃𝐿 ∗ (1 + 𝑡𝑙𝑖) and 𝑃𝐾𝑖 by 𝑃𝐾𝑖 ∗ (1 +
𝑡𝑘𝑖) to incorporate taxes on both factors of production.
Where:
Ki: capital demand
Li: labor demand
PDi: price of goods produced domestically
PKi: capital price
PL: labor price
XDi: gross production
ioij: input matrix
𝛾𝐹𝑖: distribution parameter of the CES production function
𝜎𝐹𝑖: capital-labor elasticity of substitution
aFi: eficiency parameter in the CES production function
Income and savings of the firms:
5.4 𝐾𝐹 = ∑ 𝑃𝐾𝑖 ∗ 𝐾𝑖𝑖
5.5 Yfirm = ShK_f*KF + tr_firm_row*er
5.6 Sfirm = (1-tyfirm)*Yfirm - tr_hog_firm - tr_gov_firm - tr_row_firm
Where:
KF: capital remuneration
Yfirm: income of the firm
Sfirm: saving of the firm
Sh_K_f: share of firms in capital remuneration
tr_fim_row: transfers to firms from rest of the world
25
tr_hog_firm: transfers to households from firms
tr_row_firm: transfers to resto of the world from firms
er: Exchange rate
tyfirm: corporate income tax
Households
Income and saving of households:
5.7 Y = ShK_h*KF + PL*(LS - UNEMP) + TRF + tr_hog_firm + tr_hog_row*er
Where:
Y: income of the households
ShK_h: share of hoseholds in capital remuneration
LS: labor supply
UNEMP: unemployed
TRF: tranfers from the government to households
tr_hog_firm: transfers to the households by firms
tr_hog_row: trasnfers to households by rest of the world
Saving and expenditures of the households:
5.8 SH = mps*(Y - ty*Y)
5.9 CBUD = (1-ty)*Y - SH - tr_row_hog
Where:
SH: savings of the households
CBUD: expenditure of the household
mps: marginal propensity to save
ty: income tax
tr_row_hog: transfers to the rest of the world by households
26
Consumption equations:
5.10 (1 + 𝑡𝑐𝑖). 𝑃𝑖 . 𝐶𝑖 =
(1 + 𝑡𝑐𝑖). 𝑃𝑖 . 𝜇𝐻𝐿𝐸𝑆𝑖 + 𝛼𝐻𝐿𝐸𝑆𝑖. (𝐶𝐵𝑈𝐷 − ∑ 𝜇𝐻𝐿𝐸𝑆𝑗. (1 + 𝑡𝑐𝑗 𝑗). 𝑃𝑗)
where:
Ci: consumption
Pi: Price of the domestic good
tci: consumption tax
𝛼𝐻𝐿𝐸𝑆𝑖: exponent of utility function
𝜇𝐻𝐿𝐸𝑆𝑖: consumo de subsistencia
Government
5.11 𝑇𝑎𝑥𝑟 = 𝑡𝑦. 𝑌 + 𝑡𝑦𝑓𝑖𝑟𝑚 ∗ 𝑌𝑓𝑖𝑟𝑚 + ∑ (𝑡𝑐𝑖. 𝐶𝑖. 𝑃𝑖𝑖 + 𝑡𝑖𝑖. 𝐼𝑖 . 𝑃𝑖 + 𝑡𝑘𝑖 . 𝐾𝑖. 𝑃𝐾 +
𝑡𝑙𝑖. 𝐿𝑖. 𝑃𝐿 + 𝑡𝑚𝑖 . 𝑀𝑖 . 𝑃𝑊𝑀𝑍𝑖 . 𝐸𝑅)
Where:
Taxr: tax collection
tmi: tarif rate
Mi: imports
Ti: sale tax on investment goods
PWMZi: international price of imported goods
5.12 TRF = trep*PL*UNEMP + TRO*PCINDEX
Where:
TRF: transfers from government to households
Trep: transfer rate by unemployment
TRO: other transfers
PCINDEX: índix price
27
Consumption of the government:
5.13 𝑃𝑖 . 𝐶𝐺𝑖 = 𝛼𝐶𝐺𝑖. (
𝑇𝑎𝑥𝑟 + 𝑆ℎ𝐾𝑔 ∗ 𝑃𝐾 ∗ 𝐾𝑆 − 𝑆𝐺 ∗ 𝑃𝐶𝐼𝑁𝐷𝐸𝑋 +
𝑡𝑟𝑔𝑜𝑣𝑓𝑖𝑟𝑚+ 𝑡𝑟𝑔𝑜𝑣𝑟𝑜𝑤
∗ 𝑒𝑟 − 𝑡𝑟𝑟𝑜𝑤𝑔𝑜𝑣− 𝑇𝑅𝐹
)
Where:
𝛼𝐶𝐺𝑖: share of expenditure
ShK_g: share participation of the government in capital remuneration
tr_gov_firm: transfers to the government by firms
tr_gov_row: transfers to the government by rest of the world
SG: savings of the government
External Sector
The specification of the external sector is based on the assumption of small country, which
means that the countries are price taker in both import and export markets. For both
imports and exports it is assumed the Armington assumption, ie the imperfect
substitution between goods produced domestically (sold domestically) and those
imported (exported).
The export supply functions and supply of products to the domestic market and the
condition of "zero profit" for the activities of local and foreign sales are:
5.14 𝐸𝑒 = (𝛾𝑇𝑒)𝜎𝑇𝑒 . 𝑃𝐸𝑒−𝜎𝑇𝑒 . [𝛾𝑇𝑒
𝜎𝑇𝑒 . 𝑃𝐸𝑒1−𝜎𝑇𝑒 + (1 −
𝛾𝑇𝑒)𝜎𝑇𝑒 . 𝑃𝐷𝐷𝑒1−𝜎𝑇𝑒]
𝜎𝑇𝑒1−𝜎𝑇𝑒 . (
𝑋𝑒
𝑎𝑇𝑒)
5.15 𝑋𝐷𝐷𝑒 = (1 − 𝛾𝑇𝑒)𝜎𝑇𝑒 . 𝑃𝐷𝐷𝑒−𝜎𝑇𝑒 . [𝛾𝑇𝑒
𝜎𝑇𝑒 . 𝑃𝐸𝑒1−𝜎𝑇𝑒 + (1 −
𝛾𝑇𝑒)𝜎𝑇𝑒 . 𝑃𝐷𝐷𝑒1−𝜎𝑇𝑒]
𝜎𝑇𝑒1−𝜎𝑇𝑒 (
𝑋𝑒
𝛼𝑇𝑒)
Where:
28
ce: subset of export activities (𝑐𝑒 ∈ 𝑖)
𝜎𝑇𝑖: elasticity of transformation in the CET function
𝛾𝑇𝑖: distribution parameter according to market destination of goods
𝑎𝑇𝑖: scale parameter in the CET function
5.16 𝑋𝐷𝑛𝑒∈𝑖 = 𝑋𝐷𝐷𝑛𝑒
5.17 𝑃𝐷𝑖 . 𝑋𝐷𝑖 = 𝑃𝐸𝑒 . 𝐸𝑒 + 𝑃𝐷𝐷𝑖 . 𝑋𝐷𝐷𝑖
Where:
ne: sub-set of non-export activities ( 𝑛𝑒 ∈ 𝑖 )
The import demand functions, demand for domestically produced goods and the
condition of "zero profit" for the activity of local and foreign purchases are:
5.18 𝑀𝑚 = (𝛾𝐴𝑚)𝜎𝐴𝑚 . 𝑃𝑀𝑚−𝜎𝐴𝑚 . [𝛾𝐴𝑚
𝜎𝐴𝑚 . 𝑃𝑀𝑚1−𝜎𝑎𝐴𝑚 + (1 −
𝛾𝐴𝑚)𝜎𝐴𝑚 . 𝑃𝐷𝐷𝑚1−𝜎𝐴𝑚]
𝜎𝐴𝑚1−𝜎𝐴𝑚 . (
𝑋𝑚
𝛼𝐴𝑚)
5.19
𝑋𝐷𝐷𝑚 =
(1 − 𝛾𝐴𝑚)𝜎𝐴𝑚 . 𝑃𝐷𝐷𝑚−𝜎𝐴𝑚 . [𝛾𝐴𝑚
𝜎𝐴𝑚 . 𝑃𝐸𝑚1−𝜎𝐴𝑚 + (1 − 𝛾𝐴𝑚)𝜎𝐴𝑚 . 𝑃𝐷𝐷𝑚
1−𝜎𝐴𝑚]𝜎𝐴𝑚
1−𝜎𝐴𝑚 . (𝑋𝑚
𝛼𝐴𝑚)
5.20 𝑋𝑛𝑚∈𝑖 = 𝑋𝐷𝐷𝑛𝑚
5.21 𝑃𝑖 . 𝑋𝑖 = 𝑃𝑀𝑚. 𝑀𝑚 + 𝑃𝐷𝐷𝑖 . 𝑋𝐷𝐷𝑖
Where:
nm: subset of non import sectors ( 𝑛𝑚 ∈ 𝑖 )
The price of imports and exports:
5.22 𝑃𝑀𝑖 = 𝐸𝑅. 𝑃𝑊𝑀𝑍𝑖 . (1 + 𝑡𝑚𝑖).
5.23 𝑃𝐸𝑖 = 𝐸𝑅. 𝑃𝑊𝐸𝑍𝑖.
29
Where PMi and PEi are the price of imports and exports. PWMZi y PWEZi are international
prices.
The commercial balance:
5.24
∑ 𝑃𝑊𝑀𝑍𝑖 . 𝑀𝑖 +𝑡𝑟𝑟𝑜𝑤ℎ𝑜𝑔
𝑒𝑟+
𝑡𝑟𝑟𝑜𝑤𝑓𝑖𝑟𝑚
𝑒𝑟+
𝑡𝑟𝑟𝑜𝑤𝑔𝑜𝑣
𝑒𝑟𝑖
= ∑ 𝑃𝑊𝐸𝑍𝑖
𝑖
. 𝐸𝑖 + 𝑆𝐹 + 𝑡𝑟ℎ𝑜𝑔𝑟𝑜𝑤+ 𝑡𝑟𝑔𝑜𝑣𝑟𝑜𝑤
+ 𝑡𝑟𝑓𝑖𝑟𝑚𝑟𝑜𝑤
Where:
SF is foreign services.
Saving and Investment
The total savings in the economy is the sum of saving by households, businesses,
government savings and foreign savings.
5.25 𝑆 = 𝑆𝐻 + 𝑆𝐺 ∗ 𝑃𝐶𝐼𝑁𝐷𝐸𝑋 + 𝑆𝐹 ∗ 𝐸𝑅 + 𝑆𝑓𝑖𝑟𝑚
Las demandas de bienes de inversión:
The demands for investment goods:
5.26 (1 + 𝑡𝑖𝑖) ∗ 𝑃𝑖. 𝐼𝑖 = 𝛼𝐼𝑖 . 𝑆
Wage Curve and Unemployment
To make endogenous the unemployment rate is used a type of Phillips curve showing a
relationship between the rate of change in the real wage and the rate of change of the
unemployment rate. Consequently, the ratio of the Phillips curve:
5.27
30
(𝑃𝐿
𝑃𝐶𝐼𝑁𝐷𝐸𝑋⁄
𝑃𝐿𝑍𝑃𝐶𝐼𝑁𝐷𝐸𝑋𝑍⁄
− 1) = 𝑝ℎ𝑖𝑙𝑙𝑖𝑝𝑠 ∗ (𝑈𝑁𝐸𝑀𝑃
𝐿𝑆⁄
𝑈𝑁𝐸𝑀𝑃𝑍𝐿𝑆𝑍⁄
− 1)
Where:
UNEMPZ: initial unemployment
LSZ: initial labor supply
PCINDEX: Laspeyres consumer Price index.
5.28
𝑃𝐶𝐼𝑁𝐷𝐸𝑋 =∑ 𝑃𝑖. (1 + 𝑡𝑐𝑖) ∗ 𝐶𝑍𝑖𝑖
∑ 𝑃𝑍𝑖 . (1 + 𝑡𝑐𝑧𝑖) ∗ 𝐶𝑍𝑖𝑖
Markets Equilibrium
Simultaneous equilibrium conditions of the markets are reflected in the following
expressions.
Equilibrium in the goods market:
5.29
𝑋𝑖 = ∑ 𝐶ℎ,𝑖
ℎ
+ 𝐼𝑖 + 𝐶𝐺𝑖 + ∑ 𝑖𝑜𝑖𝑗
𝑗
𝑋𝐷𝑗
Regarding factor markets, the equilibrium condition for capital market is not needed
because capital is activity-specific and fixed. Labor market equation is drop according to
Walras´s Law. If all N-1 markets all in equilibrium, then the N market is also in equilibrium.
In any case the satisfaction of Walras´ Law is tested empirically in the initial equilibrium
solutions and in the equilibrium solution of after simulations.
Model Clousure
31
In the model used in this work a closure is chosen with the following characteristics:
Factors of Production: Labor supply and the capital stock is given. Capital factor fixed and
activity-specific.
5.30 𝐿𝑆 = 𝐿𝑆̅̅ ̅
5.31 𝐾𝑖 = �̅�𝑖
Savings-Investment: Capital formation is endogenous, determined by the overall level of
savings in the economy.
External Sector: there are considered alternative closures, real exchange rate endogenous
(exogenous foreign savings) vs exogenous real exchange rate (endogenous foreign
savings).
If real exchange rate is endogenous:
5.32a 𝑆𝐹 = 𝑆𝐹̅̅̅̅
If real exchange rate is exogenous:
5.32b 𝐸 = �̅�
Savings of the Government is fixed:
5.33 𝑆𝐺 = 𝑆𝐺̅̅̅̅
The numeraire is the labor price:
5.34 PL=1
Except for government transfers to households, the rest of the inter-institutional transfers
are exogenous.
32
Welfare Indicators
In this paper several indicators, scalar type, are calculated once solved the model
described above. These scalars are the utility of consumers, real GDP, nominal GDP, and
the GDP deflator.
Elasticities
In Fargeix A. and E. Sadoulet (1990) on Ecuador, are considered elasticity of capital-labor
substitution of 0.8 for the agriculture, electricity, construction, and transportation. For
manufacturing, trading, services, and government services sectors are considered
elasticities of 0.90 to 0.95 and 0.7 for oil sector. The Armington elasticity of substitution
between imported goods and domestically produced goods used are located in a range of
0.6 to 0.9. The Agriculture, Electricity, Construction, Transportation, Services sectors
consider an elasticity of 0.6 while for manufacturing 0.9. The elasticity of substitution
between goods exported and produced for the domestic market are between -0.95 and -
0.6.
De Santis R. (2003) on Saudi Arabia considers elasticity of substitution between capital
and labor in a range of 1.26 to 1.68 for Manufacturing, Electricity, Gas, Construction,
Trade, Transport, Finance and Services sectors. While for Agriculture and Petroleum
sectors considered elasticity of 0.24 and 0.20 respectively. The Armington elasticity
substitution elasticity used are in the range of 4.4 to 5.6 for agriculture and
manufacturing. As for the elasticity of substitution for exports and sales to domestic
33
market he uses -1.5 for all sectors. It is argued that the values of -1.5 (considered by the
author as low) are to reflect that very little of the non-oil production is export-oriented.
Issoufou Soumaila (2003) on Republic of Niger (a close Nigeria neighbor) considers
Armington elasticity substitution of 1.5 for agriculture, mining and construction while for
manufacturing, electricity, trade and transport, Finance and Services considered an
elasticity of 2. This paper considers a Frisch parameter ranging from -4 and -5, depending
on the skill level of households. Income elasticity is considered inferior to one in the case
of agricultural commodities and mining ranging 0.4 to 0.9. For other goods the range is
between 1,119 and 1,179, the highest being related to the services sector.
Key R. and Bayar A. (2011) consider on Venezuela Armington elasticity substitution of 2
and export elasticity substitution of -2. They also consider a Frisch parameter of -1.1 and
income elasticity of 1.1.
Pedagua L. et al (2012) on Venezuela estimates econometrically export elasticity of
substitution and imports elasticity substitution for both short and long term for 30
industries. For the Armington elasticity in the short term, 25 out of 30 are statistically
significant and with the expected sign. For the long term they found 12 elasticity’s out of
30 statistically significant. On average short term elasticity is equal to 0.78 with a range
between 0.3 and 1.27, while in the long run it was 1.25 on average ranging between 0.52
and 2.35. The most sensitive imports proved to be the wood industry, goods for
construction of machinery and goods for construction of transport materials. Less
sensitive sectors were petroleum products and products for manufacture of non-metallic
34
minerals. For the export elasticity of substitution in the short run, just in 7 cases were
significant and with the expected sign. For the long term only in 4 cases were significant.
On average the short-run elasticity is -1.11 ranging from -0.69 to -1.61, while the long
term was -3.2 ranging from -2.5 to -4.3.
Simulating the Effects in Production Cuts
Considering these previous works are built 2 scenarios for Armington and Export elasticity of
substitution, one high and one low. In the high elasticity scenario is used a level of 2 for Armington
elasticity and -2 for export elasticity. In the low elasticity scenario are used an average of 0.83 for
Armington elasticity and -0.87 for export elasticity. Regarding Frisch parameter, based on per
capita income, for Venezuela is considered a value of -2 and for Nigeria a value of -4.
Concerning income elasticity it is considered a value of 1.1
35
Table 5.2
Social Accounting Matrix of Nigeria (2006) Millions of Nairas
Source: M. Nwafor, X. Diao y V. Alpuerto (2010)
AGR OIL MIN MNF ELC CNST TRD TRP FIN OTHSRV LAB CAP
AGR 3.224.609 - 175 13.779.755 - 3.899 1.493.344 92 - 76.316 - -
OIL 440.672 29.155.919 80.415 2.184.558 359.201 1.052.165 721.379 3.174.688 8.410 264.704 - -
MIN - 20.729 106.514 2.426.906 75 641.336 - - 1 8.180 - -
MNF 4.510.852 4.174.049 367.270 46.217.708 604.314 16.031.816 15.694.937 2.736.502 781.183 9.599.635 - -
ELC 107.951 440.652 55.910 2.027.761 92.022 26.244 775.884 319.747 121.502 902.858 - -
CNST 19.460 949.929 58.753 - 334.504 100.256 1.124.890 469.109 554.631 1.209.548 - -
TRD 8.630.934 1.011.008 126.051 34.392.539 212.330 4.488 1.991.437 2.645.911 139.250 1.353.665 - -
TRP 486.821 2.186.693 - 10.482.426 36.388 31.727 3.877.488 2.796.092 1.062.576 702.142 - -
FIN 361.960 4.191.221 93.889 2.125.464 162.502 172.345 1.175.164 774.390 1.684.938 2.274.536 - -
OTHSRV 495.788 2.419.576 324.376 2.979.516 327.384 1.152.833 4.736.843 2.233.490 2.890.157 5.226.831 - -
LAB 5.654.435 5.705.602 1.366.410 16.001.308 1.845.882 17.389.778 27.267.416 10.670.858 3.573.423 44.637.094 - -
CAP 8.297.623 103.873.392 2.223.692 29.158.187 1.217.011 8.149.623 10.245.931 10.078.924 2.648.830 19.093.111 - -
FIRM - - - - - - - - - - - 188.399.618
HOG - - - 134.112.206 6.580.595
GOV - - - - 6.111
txe 84.834 147.815 46.268 5.337.246 - - - - - 273 - -
txs 81.192 849.178 - 18.737.102 378.718 - 6.310.569 2.241.917 480.599 973.049 - -
txi - 52.172 174.661 - -
txl 93.496 2.716.815 281.381 2.465.878 1.309.617 3.868.776 2.085.951 2.578.715 1.378.297 12.153.190 - -
txk - - -
txy - - - - - - - - - - - -
INV - - - - - - - - - - - -
ROW 2.280.634 6.293.889 820.784 70.465.190 10.969 - 496.288 3.720.493 1.158.612 1.995.867 - -
TOTAL 34.771.261 164.136.467 6.004.060 258.781.544 6.890.917 48.799.947 77.997.521 44.440.928 16.482.409 100.470.999 134.112.206 194.986.324
FIRM HOG GOV txe txs txi txl txy INV ROW TOTAL
AGR - 13.935.619 248.527 - - - 1.915.094 93.831 34.771.261
OIL - 2.972.488 - - - - - - 1.069.894 122.651.974 164.136.467
MIN - - - - - - 248.301 2.552.018 6.004.060
MNF - 84.915.932 1.542.948 - - 57.155.373 14.449.025 258.781.544
ELC - 1.959.858 - - - - - 60.528 6.890.917
CNST - - - - - - 43.978.867 - 48.799.947
TRD - 27.245.947 - - - - - - 210.105 33.856 77.997.521
TRP - 21.388.261 66.968 - - - - 1.323.346 44.440.928
FIN - 3.460.742 - - - - - 5.258 16.482.409
OTHSRV - 29.249.773 45.421.161 - - - - - 2.796.319 216.952 100.470.999
LAB - - - - - - - - - 134.112.206
CAP - - - - - - - - - 194.986.324
FIRM - - - - - - - 626.829 189.026.447
HOG 20.975.598 20.942.688 - - - - - 182.611.087
GOV 61.940.960 - 5.616.436 30.052.324 226.833 28.932.116 29.965.586 - - 156.740.366
txe - - - - - 5.616.436
txs - - - - - - - - - 30.052.324
txi 226.833
txl - - - - - - - - - 28.932.116
txy 28.669.549 1.296.037 - - - - - - - 29.965.586
INV 77.440.340 -3.983.484 85.780.632 - - - - - -51.863.535 107.373.953
ROW - 169.914 2.737.442 - - - - 90.150.082
TOTAL 189.026.447 182.611.087 156.740.366 5.616.436 30.052.324 226.833 28.932.116 29.965.586 107.373.953 90.150.082
36
Table 5.3
Social Accounting Matrix of Venezuela (2006), thousand bolivars
Souce: based on Key and Bayar (2011).
AGR OIL MIN MNF ELC CNST TRD TRP FIN OTHSRV LAB CAP
AGR 3.224.609 - 175 13.779.755 - 3.899 1.493.344 92 - 76.316 - -
OIL 440.672 29.155.919 80.415 2.184.558 359.201 1.052.165 721.379 3.174.688 8.410 264.704 - -
MIN - 20.729 106.514 2.426.906 75 641.336 - - 1 8.180 - -
MNF 4.510.852 4.174.049 367.270 46.217.708 604.314 16.031.816 15.694.937 2.736.502 781.183 9.599.635 - -
ELC 107.951 440.652 55.910 2.027.761 92.022 26.244 775.884 319.747 121.502 902.858 - -
CNST 19.460 949.929 58.753 - 334.504 100.256 1.124.890 469.109 554.631 1.209.548 - -
TRD 8.630.934 1.011.008 126.051 34.392.539 212.330 4.488 1.991.437 2.645.911 139.250 1.353.665 - -
TRP 486.821 2.186.693 - 10.482.426 36.388 31.727 3.877.488 2.796.092 1.062.576 702.142 - -
FIN 361.960 4.191.221 93.889 2.125.464 162.502 172.345 1.175.164 774.390 1.684.938 2.274.536 - -
OTHSRV 495.788 2.419.576 324.376 2.979.516 327.384 1.152.833 4.736.843 2.233.490 2.890.157 5.226.831 - -
LAB 5.654.435 5.705.602 1.366.410 16.001.308 1.845.882 17.389.778 27.267.416 10.670.858 3.573.423 44.637.094 - -
CAP 8.297.623 103.873.392 2.223.692 29.158.187 1.217.011 8.149.623 10.245.931 10.078.924 2.648.830 19.093.111 - -
FIRM - - - - - - - - - - - 188.399.618
HOG - - - 134.112.206 6.580.595
GOV - - - - 6.111
txe 84.834 147.815 46.268 5.337.246 - - - - - 273 - -
txs 81.192 849.178 - 18.737.102 378.718 - 6.310.569 2.241.917 480.599 973.049 - -
txi - 52.172 174.661 - -
txl 93.496 2.716.815 281.381 2.465.878 1.309.617 3.868.776 2.085.951 2.578.715 1.378.297 12.153.190 - -
txk - - -
txy - - - - - - - - - - - -
INV - - - - - - - - - - - -
ROW 2.280.634 6.293.889 820.784 70.465.190 10.969 - 496.288 3.720.493 1.158.612 1.995.867 - -
TOTAL 34.771.261 164.136.467 6.004.060 258.781.544 6.890.917 48.799.947 77.997.521 44.440.928 16.482.409 100.470.999 134.112.206 194.986.324
FIRM HOG GOV txe txs txi txl txy INV ROW TOTAL
AGR - 13.935.619 248.527 - - - 1.915.094 93.831 34.771.261
OIL - 2.972.488 - - - - - - 1.069.894 122.651.974 164.136.467
MIN - - - - - - 248.301 2.552.018 6.004.060
MNF - 84.915.932 1.542.948 - - 57.155.373 14.449.025 258.781.544
ELC - 1.959.858 - - - - - 60.528 6.890.917
CNST - - - - - - 43.978.867 - 48.799.947
TRD - 27.245.947 - - - - - - 210.105 33.856 77.997.521
TRP - 21.388.261 66.968 - - - - 1.323.346 44.440.928
FIN - 3.460.742 - - - - - 5.258 16.482.409
OTHSRV - 29.249.773 45.421.161 - - - - - 2.796.319 216.952 100.470.999
LAB - - - - - - - - - 134.112.206
CAP - - - - - - - - - 194.986.324
FIRM - - - - - - - 626.829 189.026.447
HOG 20.975.598 20.942.688 - - - - - 182.611.087
GOV 61.940.960 - 5.616.436 30.052.324 226.833 28.932.116 29.965.586 - - 156.740.366
txe - - - - - 5.616.436
txs - - - - - - - - - 30.052.324
txi 226.833
txl - - - - - - - - - 28.932.116
txy 28.669.549 1.296.037 - - - - - - - 29.965.586
INV 77.440.340 -3.983.484 85.780.632 - - - - - -51.863.535 107.373.953
ROW - 169.914 2.737.442 - - - - 90.150.082
TOTAL 189.026.447 182.611.087 156.740.366 5.616.436 30.052.324 226.833 28.932.116 29.965.586 107.373.953 90.150.082
37
PIB IPC Desempleo Y U TAXR ER SF
Endogenous exchange rate
Nigeria
High elasticity -4,70% 2,00% 19,60% -0,68% -10,46% -2,57% 9,48% 0,00%
Low elasticity -5,06% 2,80% 27,25% -0,30% -11,99% 0,30% 15,34% 0,00%
Venezuela
High elasticity -4,58% 2,39% 23,31% -1,07% -0,29% -1,92% 8,71% 0,00%
Low elasticity -4,74% 2,61% 25,46% -1,14% -0,61% -1,86% 9,75% 0,00%
Exogenous exchange rate
Nigeria
High elasticity -3,51% 0,15% 1,50% -0,58% -2,93% -2,43% 0,00% 47,60%
Low elasticity -3,56% 0,23% 2,29% -0,65% -3,49% -2,56% 0,00% 42,49%
Venezuela
High elasticity -3,04% 0,17% 1,65% -0,25% -0,46% -1,73% 0,00% 39,02%
Low elasticity -3,11% 0,26% 2,61% -0,29% -0,61% -1,82% 0,00% 36,56%
6. Simulation of the impact of oil production cuts
A reduction of 10% in oil production in Nigeria and Venezuela is considered. As indicated
in previous sections, the model used considers capital factor as industry-specific.
Alternative scenarios for model closure in the external sector are also considered, fixed
exchange rate (exogenous) and variable rate (endogenous). Similarly, simulations are
performed considering alternative scenarios on the elasticity of substitution for imports
and exports.
Table 6.1 Comparative Results of an oil production cut of 10%
Source: Own calculations.
In Table 6.1 the results of global variables for each country are reported. These variables
refer to GDP, inflation, unemployment, income and household utility, tax revenue, the
exchange rate and foreign savings. In general is observed for each country a fall of GDP,
rising inflation and unemployment, decreased utility and household income. It is observed
that the severity of the results depend on the type of closure model for the external
sector and the elasticity of substitution of imports and exports. In general, the results with
38
a variable rate that is depreciated with reduction in oil production reveal a further
deterioration of the variables discussed above. Similarly, the results show also further
deterioration in these variables (GDP, inflation, unemployment, income, utility) with a
lower elasticity of substitution in the external sector.
In the case of Nigeria, the reduction of global GDP would be in a range from 3.5% to 5.1%
while for Venezuela would be in a range of 3.0% to 4.7% depending as said before on the
type of model closure proposed and the value considered for the elasticity of substitution
in the external sector. As for the price increase, in the case of Nigeria would be on the
order of 0.15% to 2.8%. In the case of Venezuela the price increase would be in the range
of 0.17% to 2.6%. As for the increase in unemployment, in Nigeria it would be in the range
of 1.5% to 27%. In the case of Venezuela, it would be from 1.7% to 26%. The fall in
household income would be around 0.7%, while in Venezuela it would be in the range
from 0.3% to 1.1%.
The biggest losses in GDP, revenues and income of households and the largest increases in
prices correspond to the scenario of floating exchange rate regime and low elasticity of
substitution. The reason why is obtained less deterioration in these key variables with a
fixed exchange rate is that foreign under this scenario saving is endogenous, thus cutting
oil production results in an increase in foreign saving. As result total savings increase
which cause higher level of investment. In turn implies higher investment and an increase
in production of goods and services.
39
The costs associated with production cuts in terms of contraction of total economic
activity, unemployment and inflation account for the level of compliance in OPEC cuts in
these two countries. These results largely explain why a country like Nigeria showing
higher relative costs in terms of GDP loss, unemployment, income and consumer utility
compared to Venezuela display a level of compliance with OPEC cuts lower than
Venezuela. Moreover, these costs also help to explain why the compliance rate of
production cuts in Venezuela has declined overtime, at least en the three events consider
in section 2.
The results for both countries in variables that are sectors-specific are presented in Tables
6.3 and 6.4. The nomenclature of these variables, which were originally introduced in Section 5
are presented in Table 6.2. In both cases the results reported refer to the scenario of high
elasticity. Variables that are industry-specific are: production, domestic sales, exports and imports,
domestic and foreign prices in domestic currency.
In the case of variable exchange rate, the sectors that in common are negatively impacted
in production in both countries besides oil are: electricity, construction, trade, and other
services. The sectors are less tradable. Moreover, the sectors that are commonly
stimulated together with adjusting the exchange rate are: mining, manufacturing,
transportation. In the case of fixed exchange rate wherein increasing level of total
investment, output in the construction sector is stimulated and the manufacturing sector
as well. Now sectors which are negatively impacted are: electricity, transportation and
other services. While trade and financial sectors are stimulated in Nigeria, the opposite
40
occurs in Venezuela. While agriculture and mining sectors are stimulated in Venezuela,
the opposite happens in Nigeria.
Table 6.2 Sector-specific variables
Source: from section 5.
pk Price of capital
p Price of the composite good
pd Price of domestic good
pdd Price of domestic good selling in domestic markets
pe Price of exported good in local currency
pm Price of imported good in local currency
xd Gross domestic product
xdd Domestic product selling in domestic markets
x Sells of the composite good
k Capital demand
l Labor demand
c Consumption
i Investment
e Exports
m Imports
cg Public consumption
41
Table 6.2
Results of oil production cuts of 10%: Nigeria
AGR OIL MIN MNF ELC CNST TRD TRP FIN OTHSRV
pk -1,64% -1,12% 10,98% 3,74% -7,80% -49,99% -6,13% 4,44% 17,44% -8,00%
p 0,46% 10,32% 9,43% 6,91% -1,26% -38,67% 0,86% 5,34% 5,28% 2,20%
pd -0,19% 9,59% 9,30% 2,67% -1,26% -38,67% 0,86% 4,01% 3,38% 2,20%
pdd -0,23% 11,69% 9,00% 2,21% -1,26% -38,67% 0,86% 2,90% 0,49% 2,20%
pe 9,48% 9,48% 9,48% 9,48% 9,48% 9,48% 9,48% 9,48% 9,48% 9,48%
pm 9,48% 9,48% 9,48% 9,48% 9,48% 9,48% 9,48% 9,48% 9,48% 9,48%
xd -0,70% -10,00% 0,57% 1,01% -3,22% -1,13% -4,08% 1,94% 10,62% -5,64%
xdd -0,79% -6,52% 0,02% 0,10% -3,22% -1,13% -4,08% -0,23% 4,52% -5,64%
x -2,15% -4,19% -0,76% -8,49% -3,22% -1,13% -4,08% -4,81% -4,77% -5,64%
k 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00%
l -1,15% -0,79% 7,56% 2,61% -5,53% -38,43% -4,33% 3,09% 11,91% -5,67%
c -2,28% -4,31% - -3,65% -1,89% - -2,37% -3,33% -3,32% -2,67%
i -39,47% -44,88% - -43,12% - -0,85% -39,71% - -42,24% -
e 19,47% -10,18% 0,91% 14,84% - - - 12,95% 24,05% -
m -17,61% -2,72% -0,85% -12,74% - - - -11,87% -11,94% -
cg - - - - - - - - - -6,35%
AGR OIL MIN MNF ELC CNST TRD TRP FIN OTHSRV
pk -0,66% -9,96% -0,23% 14,29% -4,46% 123,07% 6,14% -4,59% 2,57% -5,96%
p -0,13% 0,95% -0,02% 1,48% -1,43% 96,86% 0,36% -0,46% 0,22% 0,45%
pd -0,14% 0,13% -0,06% 4,25% -1,43% 96,86% 0,36% -0,63% 0,34% 0,45%
pdd -0,14% 2,52% -0,17% 4,50% -1,43% 96,86% 0,36% -0,75% 0,49% 0,45%
pe 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00%
pm 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00%
xd -0,28% -10,00% -0,01% 3,69% -1,82% 1,06% 4,00% -2,06% 1,61% -4,19%
xdd -0,28% -5,65% -0,22% 4,20% -1,82% 1,06% 4,00% -2,30% 1,91% -4,19%
x -0,30% -2,70% -0,52% 10,50% -1,82% 1,06% 4,00% -2,86% 2,47% -4,19%
k 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00%
l -0,46% -7,08% -0,16% 9,80% -3,15% 75,35% 4,26% -3,23% 1,80% -4,21%
c -0,66% -0,93% - -1,05% -0,34% - -0,78% -0,58% -0,75% -0,81%
i 99,85% 97,71% - 96,68% - 1,39% 98,88% - 99,16% -
e 0,00% -10,23% 0,12% -4,59% - - - -0,82% 0,92% -
m -0,56% -0,83% -0,56% 13,80% - - - -3,75% 2,92% -
cg - - - - - - - - - -4,94%
Source: own calculations.
Endogenous exchange rate
Exogenous exchange rate
42
Table 6.3
Results of oil production cuts of 10%: Venezuela
AGR OIL MIN MNF ELC CNST TRD TRP FIN OTHSRV
pk 0,02% -1,16% 15,45% 4,91% -2,44% -7,79% -0,35% 0,37% -5,19% -9,33%
p 1,66% 9,77% 6,33% 4,25% 0,40% 0,34% 1,11% 1,70% -0,21% -1,30%
pd 1,20% 8,99% 7,15% 2,75% 0,47% 0,34% 1,06% 1,33% -0,84% -1,47%
pdd 1,18% 9,97% 5,53% 2,13% 0,39% 0,34% 1,06% 1,05% -0,84% -1,49%
pe 8,71% 8,71% 8,71% 8,71% 8,71% 8,71% 8,71% 8,71% 8,71% 8,71%
pm 8,71% 8,71% 8,71% 8,71% 8,71% 8,71% 8,71% 8,71% 8,71% 8,71%
xd 0,01% -10,00% 4,32% 1,30% -1,24% -4,03% -0,18% 0,15% -2,41% -5,02%
xdd -0,04% -8,38% 1,19% 0,10% -1,41% -4,03% -0,19% -0,41% -2,42% -5,07%
x -0,99% -8,04% -0,31% -3,93% -1,43% -4,03% -0,29% -1,69% -3,66% -5,43%
k 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00%
l 0,02% -0,82% 10,58% 3,42% -1,72% -5,52% -0,24% 0,26% -3,66% -6,63%
c -2,74% -9,26% - -4,94% -1,64% - -2,27% -2,78% -1,10% -0,10%
i -5,32% -12,32% -9,48% -7,68% - -4,08% -4,81% - - -2,48%
e 15,41% -10,45% 7,38% 13,42% 15,62% - 15,50% 15,27% 17,30% 15,62%
m -13,42% -6,26% -4,64% -11,65% -15,93% - -13,75% -13,96% -18,82% -22,05%
cg -12,99% - - -15,15% - - - -13,02% - -10,37%
AGR OIL MIN MNF ELC CNST TRD TRP FIN OTHSRV
pk 1,11% -10,05% 0,90% 2,82% -1,48% 8,04% 0,22% -1,15% -5,78% -3,07%
p 0,39% 1,46% 0,63% 0,50% -0,13% 1,51% 0,12% -0,18% -1,13% -0,58%
pd 0,42% 0,39% 0,43% 0,69% -0,13% 1,51% 0,12% -0,19% -1,22% -0,59%
pdd 0,42% 1,74% 0,85% 0,75% -0,13% 1,51% 0,12% -0,20% -1,22% -0,59%
pe 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00%
pm 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00%
xd 0,32% -10,00% 0,27% 0,76% -0,75% 3,98% 0,11% -0,46% -2,69% -1,62%
xdd 0,32% -7,55% 1,12% 0,89% -0,76% 3,98% 0,11% -0,47% -2,69% -1,62%
x 0,38% -7,04% 1,56% 1,40% -0,76% 3,98% 0,12% -0,51% -2,86% -1,65%
k 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00% 0,00%
l 0,77% -7,15% 0,63% 1,96% -1,04% 5,56% 0,15% -0,81% -4,08% -2,16%
c -0,62% -1,57% - -0,72% -0,15% - -0,38% -0,11% 0,77% 0,26%
i 5,87% 4,76% 5,62% 5,76% - 4,71% 6,16% - - 6,91%
e -0,53% -10,69% -0,58% -0,62% -0,49% - -0,13% -0,08% -0,28% -0,45%
m 1,17% -4,30% 2,85% 2,42% -1,02% - 0,36% -0,86% -5,04% -2,79%
cg -4,37% - - -4,48% - - - -3,83% - -3,44%
Source: own calculations.
Endogenous exchange rate
Exogenous exchange rate
43
7. Conclusions and policy implications
i. There is empirical evidence on the impact of OPEC at least in the short term.
Kaufmann et al (2004, 2008) shows that production quotas are an important
determinant of production of OPEC countries. Bremond et al (2012) conclude that
OPEC behavior evolves over time. It behaves as a cartel when it faces significant
shocks (supply or demand) which merit setting quotas. But these authors also note
that once this stage is completed short-term, the organization acts as a price taker
agent.
ii. During this century the oil market have seen the active role of OPEC in its effort to
stabilize the market when prices show a pronounced downward trend. We
identify three of such periods February 2001-January 2002, November 2006 -
February 2007 and October 2008 - January 2009 where significant explicit or
implicit cuts were made.
iii. The OPEC intervention in the market is triggered by the empirical observation of a
negative variation between the maximum and minimum values of price greater
than 25%; and the clear identification of this fall with signs of weak economic
activity, accumulation of inventories, seasonal or unexpected conditions.
iv. The adjustment process of OPEC production to demand shocks is in most cases a
continuous action, ie involving more than one time adjustment in production. The
cumulative adjustments analyzed involved substantial reductions in the range of
6% - 18%.
44
v. In most cases the shocks on the residual demand for OPEC were such that after a
year the prices remained below to pre-shock conditions. On average, for the 3
cases analyzed prices remained 12% below the pre-crisis situation in spite of
OPEC actions.
vi. Regarding the level of compliance with agreements of production cuts it is noted
that Nigeria generally has a relatively low level of compliance (ranging between
30% - 43%) in relation to Venezuela (ranging between 45% - 87 %) and the rest of
OPEC countries (ranging between 60% - 78%).
vii. It is noteworthy that during the first two events of production cuts, Venezuela
stands out by exhibiting a level of compliance well above the average of the OPEC
countries. Only during the most recent episode of production cuts, the country
shows a level of compliance below the average of OPEC.
viii. By introducing risk elements of total demand and Non OPEC production, the
demand for OPEC crude could be reduced by 1.2 MBD in the short term; which
should the added to the reduction already expected of 1.0 MBD in the initial
market balance shown. Therefore in the short term it is likely to expect the
presence of further cuts coming from OPEC.
ix. To measure the impact of production cuts in Nigeria and Venezuela is develop a
CGE model for each country. To simulate the effects of a 10% cut in oil production
it is adjusted the total factor productivity coefficient in the oil sector in order to
achieve such a reduction.
x. In the case of Nigeria, the reduction of global GDP would be in a range from 3.5%
to 5.1% while for Venezuela would be in a range of 3.0% to 4.7% depending as said
45
before on the type of model closure proposed and the value considered for the
elasticity of substitution in the external sector. As for the price increases, in the
case of Nigeria would be on the order of 0.15% to 2.8%. In the case of Venezuela
the price increase would be in the range of 0.17% to 2.6%. As for the increase in
unemployment, in Nigeria it would be in the range of 1.5% to 27%. In the case of
Venezuela, it would be from 1.7% to 26%. The fall in household income would be
around 0.7%, while in Venezuela it would be in the range from 0.3% to 1.1%.
xi. The costs associated with production cuts in terms of contraction of total economic
activity, unemployment and inflation account for the level of compliance in OPEC
cuts in these two countries. These results largely explain why a country like Nigeria
showing higher relative costs in terms of GDP loss, unemployment, income and
consumer utility compared to Venezuela display a level of compliance with OPEC
cuts lower than Venezuela. Moreover, these costs also help to explain why the
compliance rate of production cuts in Venezuela has declined overtime.
xii. These results are part of a line of research aimed to quantify, characterize and
compare the impacts of domestic production cuts production of all OPEC countries.
46
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