Domestic impact of production cuts in OPEC countries: The ... Key and Villarroel_Bali 111020… ·...

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

http://eia.gov/

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.

http://opec.org/

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


(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

http://eia.gov/

11


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 %


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


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.

http://opec.org/

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


(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.

http://eia.gov/

14


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 %


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


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.

http://datos.bancomundial.org/indicador

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%


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.



42

Table 6.3

Results of oil production cuts of 10%: Venezuela


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%


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.



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

8. References

- Al-Qatani A., Balistreri E., Dahl C.(2008). Literature Review on oil market modelling and OPEC´s Behavior. Colorado School of Mines. Mimeo. (www.cepe.ethz.ch/education/EnergyPolicy/LitReviewOPEC.pdf)

- Bayar A. (2013). Ecomod Summer School, instructional material. Brussels, Belgium.

- Breisinger C., Thomas M., Thurlow J. (2009). Social Accounting Matrices and multiplier Analysis. International Food Policy Research Institute (IFPRI).

- Bremónd V. et al.(2012). “Does still OPEC exist as a Cartel? An Empirical investigation. Energy Economics, 34(1): 125-131.

- Brooke A., Kendrick D., Meeraus A. (1992). GAMS: A User´s Guide, Release 2.25.

Scientific Press.

- Burfisher M.E. (2011). Introduction to Computable General Equilibrium Models. Cambridge University Press.

- Call S.T., Holahan W.L.(1985). Microeconomía, Grupo Editorial Iberoamericana, Mexico DF, Mexico.

- De Santis R.A. (2003). “Crude Oil Price Fluctiations and Saudi Arabia´s behavior”. Energy Economics, 25: 155-173.

- Fargeix A., Sadoulet E. (1990). A Financial Computable General Equilibrium Model for the Analysis of Ecuador´s Stabilization Programs, Working Paper No 10, OECD Development Center.

- Griffin J.(1985). “OPEC Behavior: A Test of Alternative Hypothesis”. American Economic Review, 75(5): 954-963.

- Hosoe N., Gasawa K., Hashimoto H. (2010). Textbook of Computable General

Equilibrium Modeling, Programming and Simulations. Palgrave-Macmillan.

- IMF (2013). Global Financial Stability Report: transition challenges to stability, Octubre, Washington DC.

- IMF (2014). World Economic Outlook Database, Abril, Washington DC.

http://www.cepe.ethz.ch/education/EnergyPolicy/LitReviewOPEC.pdf

47

- Kaufmann R. et al.(2004). “Does OPEC Matter? An Econometric Analysis of Oil Prices”. The Energy Journal, 25(4): 67-90.

- Kaufmann R. et al.(2008). “Determinants of OPEC production: Implications for OPEC behavior”. Energy Economics, 30(2): 333-351.

- Key R., Bayar A. (2011). Impacto Macroeconómico del Plan Siembra Petrolera:

Resultados de Modelo de Equilibrio General Computable Dinámico de la Economía Venezolana. Mimeo.

- Lofgren H., Harris R.L. y Robinson S. (2002). A Standard Computable General

Equilibrium (CGE) Model in GAMS. International Food Policy Research Institute (IFPRI).

- Nicholson W. (2005). Microeconomic Theory: Basic Principles and Extensions, 9th ed. Willard, Ohio: RR Donnelly.

- Nwafor M., Diao X., Alpuero V.(2010). A 2006 Social Accounting Matrix for Nigeria:

Methodology and Results. International Food Policy Research Institute (IFPRI).

- OPEC (2013). World Oil Outlook. OPEC Secretariat, Viena, Autria.

- _____ (2010). Long-Term Strategy. OPEC Secretariat, Viena, Austria.

- _____ (2006). OPEC Bulletin. Vol. XXXVII, No 6, Noviembre/Diciembre.

- _____a. Market Indicators. www.OPEC.org. Varios años.

- _____b. Monthly oil Market Report. www.OPEC.org. Varios años.

- Pedagua L., Saéz F., Velazquez A. (2012). “Simulación de un Modelo de equilibrio general computable para Venezuela”. El Trimestre Económico, Vol. LXXIX (2), Num. 314, abril – junio de 2012, pp.415-448.

- Soumaila I. (2008). A General Equilibrium Analysis of Potential Use of Natural Resources Revenue in Niger. Doctoral Dissertation. Oklahoma State University.

- Worl Bank (2014). Economic Data base Indicators.

(http://datos.bancomundial.org/indicador). April 2014.

http://www.opec.org/

http://www.opec.org/

http://datos.bancomundial.org/indicador

Domestic impact of production cuts in OPEC countries: The ... Key and Villarroel_Bali 111020… ·...

Documents

Transcript of Domestic impact of production cuts in OPEC countries: The ... Key and Villarroel_Bali 111020… ·...