Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
Oil Related Shocks and Macroeconomic Adjustment
under Different Nominal Exchange Rate Policy: The
Case of the Libyan Economy
Issa Ali and Charles Harvie
This paper analyses the dynamic macroeconomic
adjustment processes arising from oil production
rehabilitation for a small open economy such as that of
Libya, operating under different nominal exchange rate
regimes with different degrees of capital mobility. The paper
utilises a general dynamic macroeconomic framework to
identify whether adverse Dutch disease consequences
arising from oil production recovery upon the non-oil trade
balance could be alleviated by adopting an alternative
nominal exchange rate policy. The model utilised in this
paper is likely to be of interest to other oil-exporting
developing economies with similar features. In particular, the
model is also capable of incorporating different degrees of
international capital mobility, along with the adoption of
either a fixed or flexible nominal exchange rate regime. The
results from this paper suggest that the impact on the
competitiveness of non-oil exports from oil related shocks
can be mitigated with a flexible nominal exchange rate
system as the real exchange rate only slightly appreciates
throughout the adjustment path. Thus, Dutch disease effects
in the Libyan economy during its current period of oil
production rehabilitation can be potentially reduced by
moving from a fixed to more flexible exchange rate regime.
In addition, the flexible nominal exchange rate benefits the
private sector and offers larger benefits to non-oil
production, arising from a larger accumulation of public
physical capital stock, human capital stock, imported capital
stock, and private capital stock.
JEL classification: E27, E60, Q33, Q43, Q48.
Key words: Oil shocks, dynamic macroeconomic model, Dutch disease
effects, fixed flexible exchange rate regime.
1. Introduction
Libya is a country heavily dependent on its oil sector since the 1960s,and
having recently experienced a considerable increase in oil revenue as a result
of increased oil prices particularly after 2000 and oil production rehabilitation
since 2011. Like many natural resource-rich developing countries, however,
the country has suffered from widespread corruption, including that related to
__________________________________________
Issa Ali, School of Economics, University of Benghazi, Benghazi, Libya, Tel: +218 91935702,
Email: isa350@uow.edu.au
Charles Harvie, School of Economics, University of Wollongong, Wollongong, NSW 2522,
Australia, Tel: +61 2 42 213702, Fax: +61 2 42 213725, E-mail: charvie@uow.edu.au
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Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
old oil production contracts and a cumbersome bureaucracy, which has
resulted in misuse of oil revenues and poor economic performance. By 2011,
the country experienced a civil war and political turmoil for a period of eight
months (Ali and Harvie, 2013). The civil war, in conjunction with international
sanctions imposed by the United Nations, adversely affected the domestic
economy, in particular the oil sector, and upward pressure on oil prices
occurred and oil related infrastructure was devastated. According to the IMF
annual report (2012), GDP considerably contracted and crude oil production
was almost halted in July 2011. Moreover, non-oil economic activity was
mainly influenced by the destruction of infrastructure and production facilities,
the departure of foreign workers, interruptions to the functioning of the
banking system, and limited access to foreign exchange (IMF, 2012). Since
the end of the Libyan revolution in late 2011, Libyan oil production has been
rehabilitating, registering about 1.2 million barrels per day (bpd)by February
2012. As the restoration of oil production continues, with the aim of reaching
the pre-revolutionary level of 1.7 million bpd, significant revenue will be
generated to the domestic economy1 and downward pressure might be placed
on global oil prices. If used effectively such windfall revenue will play a critical
role in the future prosperity of Libya and challenge the idea of a ―resource
curse‖2, alternatively it could cause adverse effects arising from so called
―Dutch disease‖3 consequences. Therefore, evaluating the impact of windfall
revenue arising from oil production recovery is of considerable contemporary
importance not only to the Libyan economy but also European nations that
are the predominant source of demand for Libyan oil as well as other key
regional trading partners.
This paper is concerned with analysing the dynamic macroeconomic
adjustment processes arising from oil production recovery for a small open
economy such as that of Libya, where the role of government is pivotal in the
recycling of oil revenues, operating under different nominal exchange rate
regimes. The paper extends upon the contribution of Ali and Harvie (2013) by
identifying whether the consequences of an oil production recovery (or boom)
upon key macroeconomic variables could be alleviated or improved upon
depending upon which nominal exchange rate policy (fixed or flexible) is in
place as well as the degree of capital account liberalisation4.That is, in order
to mitigate the adverse effects of an oil boom upon, say, the non-oil trade
balance, moving from a fixed to a flexible nominal exchange rate policy,
combined with perfect capital mobility, might produce improved
1
Mainly to government as the oil sector is predominantly state owned.
For an exhaustive review of the resource curse literature see Auty (1993, 2001),Auty and Mikesell
(1998), Brückner(2010), Cai (2009), Manzano and Rigobon (2001), Mikesell (1997), Neumayer
(2004), Rodríguez and Sachs (1999), Ross (1999), Sachs and Warner (1995, 2001), Sala-i-Martin and
Subramanian (2003), Stevens (2003), Stijns (2001a, 2001b) and van der Ploeg and Poelhekke (2009).
3
A term first coined by the Economist in 1977. This is an approach to explaining the resource curse
emphasising the declining competitiveness and productivity of the manufacturing and other tradable
sectors arising from an appreciation of the real exchange rate in the wake of a resource boom. See
Brahmbhatt et al. (2010) for an extensive review of Dutch disease theory and empirical evidence.
2
4
See Taş and Togay (2010) for a study of the case of optimal monetary policy in the post war oil
producing economy of Iraq.
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Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
macroeconomic outcomes. Under a flexible nominal exchange rate regime,
for example, the exchange rate is capable of adjusting so that capital flows
will have no effect upon foreign exchange reserves. As a result the nominal
exchange rate is endogenous, and growth of the money stock is exogenous.
Therefore, domestic inflation will only be temporarily influenced by the
difference between non-oil output supply and demand.
The remainder of this paper proceeds as follows. Section 2 outlines the
theoretical framework adopted and model equations for the case where a
fixed exchange rate is adopted and the case where a flexible exchange rate is
adopted. The model also allows for varying degrees of capital mobility. In
section 3 simulation outcomes from the model for the case of an oil production
shock under a fixed and flexible exchange rate regime are compared and
contrasted. Section 4 provides concluding remarks.
2. Theoretical Framework: The Model
The dynamic macroeconomic model utilised in this paper has its foundation in
the contributions of Dornbusch (1976), Buiter and Miller (1981), Eastwood and
Venables (1982), Buiter and Purvis (1982), Neary and Van Wijnbergen
(1984), Harvie and Gower (1993), Harvie and Thaha (1993), and, more
recently and importantly, Cox and Harvie (C-H henceforth) (2010) for the case
of a flexible exchange rate in the context of advanced resource-abundant
economies, and Ali and Harvie (A-H henceforth) (2013) for the case of a fixed
exchange rate in the context of a developing resource-abundant country. In
particular, The C-H model and the A-H model are dynamic general equilibrium
models focusing on the long run nature of the adjustment process. An
important feature of the C-H model is the role of financial markets in
transmitting the effects of oil related shocks to the rest of the economy. The AH model assumes, however, that such a transmission mechanism is not
applicable for an oil producing developing economy such as that of Libya,
where financial markets are unsophisticated, tightly controlled and the
economy is operating with a fixed exchange rate regime and controls over
international capital flows.
Like the A-H model the general means by which oil related shocks transmit
their impact to the rest of the economy is via a number of common oil related
effects. First, increased oil sector production (revenue) will generate
increased revenue for the government (revenue effect). Second, increased
government consumption and development expenditure from oil revenue will
generate a spending effect. Third, increased oil exports will lead to an
accumulation of foreign asset stocks through improved trade and current
account balances (trade or current account effect). Fourth, increased future oil
income can also contribute to an increase in permanent income (wealth
effect) for both the government and the private sector which can further
influence spending. In the context of Libya the bulk of this wealth effect will
primarily accrue to the government. Fifth, the extra spending generated by the
spending and wealth effects increase the demand for non oil output relative to
its available supply. This can push up domestic prices and, with a fixed
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Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
nominal exchange rate, result in an effective appreciation of the real
exchange rate (exchange rate effect) and loss of competitiveness for the non
oil sector. Furthermore, like the A-H model this paper will capture other longrun effects, including human capital stock accumulation (a Labor productivity
effect) and imported capital stock accumulation via capital imports (a
technology effect), emphasising the supply side in a dynamic modelling
context. These effects will expand the long run productive capacity and
efficiency of the non oil sector.
The Ali and Harvie (2013) study evaluates by means of numerical simulation
the effects of additional oil revenue, arising from oil related shocks, upon key
macroeconomic variables, including the real exchange rate, non-oil trade
balance foreign asset stocks, human capital stock, physical capital stock,
imported capital stock and non-oil output supply. The important results
observed are that the country‘s oil sector recovery will potentially result in an
increase in private capital stock and private sector wealth, real income,
domestic physical capital stock, human capital stock, imported capital stock
and non-oil supply (and demand). Dutch disease effects are likely to be
confined to the non-oil trade balance during the adjustment process towards
long run steady state. That is, a recovery of the oil sector also has the
potential to deteriorate the non-oil trade balance through a loss of
competitiveness from a real exchange rate appreciation. Nevertheless,
despite the loss of competitiveness of the non-oil tradable sector, non-oil
output supply increases throughout the early periods of adjustment. This is
attributable to the fact that the Dutch disease effect upon non-oil output can
be mitigated by government development spending on physical, human and
imported capital stocks (Ali and Harvie, 2013; Cox and Harvie, 2010). In the
context of the Libyan economy5, this confirms the essential role that the
government, which owns the oil sector, must play in enhancing the positive
consequences and/or minimising the adverse effects of the oil sector recovery
upon the non oil sector. The government could improve productivity and
increase the availability and type of capital available for the non-oil sector by
increasing or changing the composition of government investment
expenditure on infrastructure, human capital formation and technology
acquisition in this sector. This will eventually improve the non-oil sector‘s
competitiveness.
The model utilised in this paper is basically the same as that extensively
discussed by Ali and Harvie (2013) with a minor, but important, change. The
equations of the model are amended to incorporate movement from a fixed to
flexible nominal exchange rate regime combined with perfect capital mobility.
A brief discussion of the model is now presented6. Equilibrium in the model
depends upon equilibrium in the product market, assets market and foreign
trade sector. The product market is discussed first.
5
6
As well as for other developing countries with similar characteristics.
For more discussion of the model see Ali and Harvie (2013).
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Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
Product Market
Equations 1 to 18 describe the product market. Equation 1 describes the total
demand for non-oil output ( No d ). It is a log linear approximation of total
spending in the form of private consumption spending ( c p ), private investment
spending ( i p ), government spending ( g ) and the non-oil trade balance
consisting of non-oil exports ( x n ) and non-oil imports ( m n ). The parameters (
 i ) represent the elasticities of spending in each category. The parameters
are based on the contribution of a dollar spent on private consumption and
investment, total government spending, non-oil exports and non-oil imports to
the demand for non non-oil output. In line with the C-H model the parameters
are set to 1 indicating that a dollar spent in any of these components
contributes equally to non oil product demand.
Nod  1c p  2i p  3 g  4 ( xn  mn )
(1)
Private consumption expenditure is given by Equation 2. It depends positively
upon non-oil output supply and private sector wealth. The production of nonoil output represents income generated by the public and private sectors,
although most non-oil output is produced by the public sector in Libya7.
Equation 3 describes private sector gross investment, which equals the
change in the stock of private capital8 and is based on the partial adjustment
hypothesis. This partial adjustment arises from costs of adjusting the actual
physical capital stock ( k p ) to the desired capital stock ( k p* ). The increase in
capital from the end of the previous period to the end of the current period is
some fraction  of the divergence between the desired and actual stock of
capital. The adjustment coefficient  was selected to be 0.50, indicating
moderate adjustment of the dependent variable. The desired capital stock is
assumed to depend upon non-oil output (see Equation 4), where the
parameter  is set to be 0.8.
c p  6 Nos  7 w p
(2)
i p  k p   (k p*  k p ) (3)
k p*   Nos (4)
Total government spending ( g ) is identified by Equation 5. It depends
positively on two components of expenditure; government consumption
spending ( c g ), which is assumed to be dependent upon oil revenue as shown
in Equation 6, and government development expenditure. Government
development spending is divided into three parts; government development
spending on physical capital (for example, infrastructure) ( i g ), government
development spending on human capital (for example, education and health
7
Non-oil output can be considered as a good which can be either consumed domestically or exported,
and is an imperfect substitute for the foreign non-oil imported good.
8
A dot (.) above a variable signifies its rate of change.
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Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
care) ( i h ) and that devoted to imported capital (for example, imported foreign
technology) ( i cap ). Equation 5 parameters are based on the relative weight of
each of these spending components in total government spending. Equations
7, 8, and 9 describe government investment spending on the physical, human
and imported capital stocks, respectively, which arises from a gradual
adjustment of the actual public capital stock to their policy determined levels.
The policy determined levels are determined by oil revenue, as given by
Equations 10, 11 and 12.For adjustment equations 7, 8 and 9 the adjustment
coefficients were selected to be 0.50, indicating moderate adjustment of the
dependent variables. The parameters for Equations 6, 10, 11, and 12 were
chosen as weighted averages, indicating how the government distributes oil
revenue between desired physical capital stock, desired human capital stock,
desired imported capital stock and consumption expenditure according to its
policy priorities9. The summation of these parameters is one, as all oil
revenue goes to the government and this is totally disbursed in the previous
four ways.
g  8c g  9i s  10i h  11i cap
(5)
c g  (1  1  2  3 )(oa  po  e  p)
(6)
i s  k s   (k s  k s ) (7)
*
i h  k h   (k h  k h ) (8)
*
i cap  k cap   (k cap  k cap )
*
(9)
k s  1 (oa  po  e  p) (10)
*
k h  2 (oa  po  e  p) (11)
*
k cap  3 (oa  po  e  p)
*
(12)
Equation 13 identifies the budgetary stance, which is government expenditure
x
( g ) less tax revenues ( t ). In Libya the government issues bonds to the
central bank only, therefore Equation 13 shows that any excess of
government expenditure over tax revenue must be financed by borrowing
domestically from the Central Bank of Libya (CBL). Tax revenue is generated
from two sources, oil production and non-oil production (Equation 14).The
parameter ( 13 ) in Equation 14 is set to 0.70 as the bulk of government
revenue comes mainly from oil, with oil revenue contributing 70 percent on
average of total government revenue during the period 1970-2007.
bd  g  t x  12 (m  p) (13)
t x  13 (oa  po  e  p)  (1  13 ) Nos
(14)
The non-oil trade balance is disaggregated into non-oil exports less non-oil
imports as shown in Equation 15 and identity Equation 30. Equation 15
specifies that non-oil exports ( x n ) depend positively upon the real exchange
rate (e + p* — p) and world real income (y*) which is assumed to be
9
These can be regarded as policy determined parameters.
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Proceedings of European Business Research Conference
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exogenous. Non-oil imports is also disaggregated into non-oil consumption
imports ( mcon ) and non-oil capital imports ( i cap ). Equation 16 identifies non-oil
consumption imports, which depends negatively upon the real exchange rate
and positively on domestic real income (y). Equation 9 identifies non-oil
capital imports which are assumed to be endogenously determined, arising
from a gradual adjustment of actual imported capital spending to its policy
determined level. The parameters in behavioural Equations 15 an16 were
empirically estimated using the ARDL approach (see Table 3).
xn  14 (e  p *  p)  15 y *
(15)
mcon  16 y  17 (e  p *  p)
(16)
Real and permanent income (yp) definitions, first used by Buiter and Purvis
(1982), are given by Equations 17 and 18. Real income, as identified in
Equation 17, depends upon non-oil output ( No s ), oil production ( o a ) that is
assumed to be exogenous, the world price of oil ( po ), that is also exogenous,
the real exchange rate as emphasized here and the exogenously determined
price of non-oil imported goods ( p * ).Equation 18 represents permanent
income, which depends on exogenous permanent non-oil output ( No sp ),
exogenous permanent oil output ( o p ), the world price of oil, the real exchange
rate and price of non-oil imported goods (see Harvie, 1994). The parameters
in identities 17 and 18 are based upon the calculated share of current and
permanent oil output in total current and permanent output, respectively. It is
assumed that v , the share of current and permanent non-oil production in total
current and permanent income, is the same in real and permanent income
and constant through time (see Buiter and Purvis, 1982). The share of oil
output in domestic real income ( 1  v ) is deliberately set to be larger than its
share in domestic consumption (  2 ) resulting in the Libyan economy being a
net oil exporter in the model.
y  vNos  (1  v)oa  (1  v  2 ) po  (1  v)(e  w)  (1  1  2 ) p *
(17)
y  vNo  (1  v)o  (1  v  2 ) po  (1  v)(e  w)  (1  1  2 ) p *
(18)
p
sp
p
Assets Market
The asset market is encapsulated by Equations 19–21. The behavioural
Equation 19 describes the demand for real money balances (the nominal
money stock m deflated by the consumer price level p). It depends positively
upon real non-oil income ( No s ), representing a transactions demand, and
negatively upon the interest rate representing an asset demand. The interest
rate is subject to regulation by policymakers in Libya and it is no longer a
good proxy for the cost of holding money. Therefore, the rate of inflation is
utilised, besides the interest rate, as a proxy variable for the opportunity cost
of holding money in the A-H model. The nominal money supply is assumed to
be endogenous as the nominal exchange rate is fixed. The estimated
parameters of Equation 19 are shown in Table 3.
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Proceedings of European Business Research Conference
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m  p  1 Nos   2   3r
(19)
Domestic private sector real wealth (wp) is given by Equation 20 and consists
of three components. The first component is private capital stock which is
owned entirely by the private sector. The second major component is real
money balances, which consists of cash, deposits, and savings of the private
sector. The final component is permanent non-oil income equivalent to that of
permanent non-oil output10.The parameters in Equation 20 are set to 1
indicating the equal importance of each of the components to total private
sector wealth.
w p   5 k p   6 (m  p)   7 y p
(20)
Equation 21 shows the money growth equation. It indicates the assumption of
a fixed exchange rate combined with imperfect capital mobility. Since a fixed
exchange rate is assumed for the case of Libya the money supply and its
growth is endogenously determined. It depends upon exogenously
determined changes in domestic credit expansion ( dce ) and the accumulation
of foreign exchange reserves through balance of payments surpluses/deficits
( fes ) (see Harvie, 1993, and Harvie and Thaha, 1994), as shown in Equation
21* .
m  dce  fes
Equation 21*
dce is exogenously determined by government and is assumed for simplicity
to be equal to zero. Changes in foreign exchange reserves arise from
developments in the current account ( f ) and from capital flows due to
differences in the domestic and foreign nominal interest rate (r  r*) , as shown
in Equation 21** ,where  denotes the sensitivity of capital flows to interest
rate differentials, representing the degree of capital mobility. The value of
coefficient  can range from zero to infinity. The greater is  the greater is
international capital mobility, while the smaller is  the smaller is international
capital mobility (Frenkel & Rodriquez, 1982). The parameter  is chosen to be
0.2 in this base model, which is indicative of the substantial control over
capital mobility exercised by the government.
fes   (r  r*)  f
Equation 21**
By substituting Equation 21** into Equation 21* , Equation 21 is obtained.
m  dce  ( (r  r *)  f ) (21)
10
This is a proxy for the present value of the future income stream for the private sector.
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Aggregate Supply and Prices
Equations 22–24 define the price level and aggregate non-oil output supply.
Price and inflationary expectations developments are given by Equations 22,
23, and 24. Equation 22 defines the consumer price level, which is a weighted
average of nominal wages, the domestic cost of oil and the domestic cost of
the world non-oil imported good. The weights used in the consumer price
index in Equation 22 are approximated, based on Libyan data. Adjustment of
nominal wages is generated by an expectations augmented Phillips curve, as
given by Equation 23. Two possible adjustment sources are considered.
These being excess demand for non-oil goods relative to its available supply
( Nod  Nos ) , and core inflation (  ). Core Inflation depends upon
developments in the monetary growth rate (Equation 21). The estimated
parameters of Equation 23 are contained in Table 3.
p  1w  2 (e  po)  (1  1  2 )(e  p*)
(22)
w   1 ( Nod  Nos )  2 m
(23)
Aggregate non-oil output supply is endogenously determined, as given by
Equation 24. It depends positively on the public capital stock 11, human capital
stock, private capital stock, imported capital stock and employment.
Government investment is divided into three parts; capital that affects non-oil
output through physical capital stock accumulation, capital that affects non-oil
output through human capital formation and capital imports. The estimated
parameters of Equation 24 are shown in Table 3.
Nos  1k p  2 k g  3k h  4 k cap  5em
(24)
Overseas Sector
The external sector consists of the current account and the oil trade balance.
Developments in the current account are given by Equation 25a (see for
example Harvie and Gower (1993) and Harvie (1994)).
f  e  p  1T   2 (r * f  e  p)  3 (o x  po  e  p)
(25a)
where (ox) represents net exports of oil. Re-arranging Equation 25a and
expressing this in terms of changes in foreign exchange reserves, Equation
25 is obtained. This shows that changes in foreign exchange reserves, as
reflected in the current account balance ( f ), depends positively upon the
non-oil trade balance (as given by Equation 29), foreign interest income ( r * f
), net oil exports and on the real exchange rate ( e  p ). In long run steady
state the current account balance must be zero, otherwise further wealth
11
Inclusion of the public capital stock is attributed to the assumption that it is complementary to that of
the private capital stock in nature (see Aschauer, 1989a, 1989b; Morrison and Schwartz, 1996).
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effects will arise requiring further macroeconomic adjustment. Equation 25 is
as in the C-H model. The estimated parameters of this equation are contained
in Table 3.
f  1 ( xn  mn )   2 r * f  3 (o x  po)  (1   2  3 )(e  p)
(25)
Equation 26 indicates that net oil exports are exogenously determined, being
dependent upon government policy towards the domestic usage or export of
oil production. The parameter in Equation 26 has been selected as 0.70,
indicating a more export oriented policy.
o x   oa
(26)
Definitions
Finally, Equations 27–30 define four variables which are used extensively
throughout this study. Equation 27 defines the real exchange rate as used in
this study, Equation 28 defines real money balances, Equation 29 defines the
non-oil trade balance, and Equation 30 defines non-oil imports.
c ew
l  m  w (28) T  xn  mn (29)
(27)
mn  mcon  i cap
(30)
2.1 Alternative Exchange Rate Policy
The above discussion has focused on an economy operating with a fixed
exchange rate regime. With a flexible nominal exchange rate some
amendments are required. Moving from a fixed to flexible nominal exchange
rate combined with perfect capital mobility requires replacement of Equation
21 by Equation 21a in the model.
e  r r*
(21a)
With a flexible nominal exchange rate regime the exchange rate is capable of
adjusting so that capital flows will have no effect upon foreign exchange
reserves. As a result the nominal exchange rate is endogenous, and growth of
the money stock is exogenous ( m  m ). Therefore, domestic inflation will only
be temporarily influenced by the difference between non-oil demand and
output supply. Equation 21a is the uncovered interest parity condition. It
encapsulates the assumption of perfect capital mobility and perfect foresight
in the foreign exchange market. It assumes that in the foreign exchange
market agents have forward looking expectations and anticipate that when the
economy is out of steady state it will ultimately converge to a new steady
state.
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3. Simulation Results Arising from Oil Production
Rehabilitation under a Fixed and Flexible Exchange Rate
Regime.
This section analyses the consequences from the adoption of alternative
exchange rate regimes upon the Libyan macro-economy for the case of oil
production rehabilitation. Two different nominal exchange rate regime
scenarios are conducted. Scenario A assumes a fixed nominal exchange rate
combined with imperfect capital mobility, whilst scenario B presumes a flexible
nominal exchange rate regime combined with perfect capital mobility. A
simulation analysis is conducted utilizing a program called ―Dynare‖, which is
designed for solving and simulating deterministic and stochastic dynamic
general equilibrium models(see Adjemian, et al. 2011).
The parameter values utilised to conduct the numerical simulation scenarios
are summarised in Table 1. It contains 19 estimated parameters for
behavioural equations 2, 15, 16, 19, 23, 24 and 25, using the ARDL
cointegration approach12, where they are significantly different from zero(see
Table 3).The remaining parameters summarised in Table 1 were chosen from
prior studies and/or calculated from available data. However, before the
behavioural equations are estimated the major structural break(s) in the
intercept and trend using the LM unit root test of Lee and Strazicich (2003,
2004)are identified and incorporated in the estimated equations. Furthermore,
testing for the existence of a long-run relationship among the variables is
conducted, where the results presented in Table 2 indicate conclusive
outcomes for the dependent variables c p , xn , mcap , m  p, w, Nos and f , as
computed F-statistics are greater than the upper bound critical values. The
exception to this result is the computed F-statistic for mcon , where the result is
inconclusive at the 95 percent level as the computed F  statistic is greater
than the lower bound but less than the upper bound; however, it is conclusive
at the 90 percent level. These results imply that the variables of interest are
bound together in a long-run relationship.
Generally, as indicated in Table 4 and Figure 1, moving from a fixed to flexible
nominal exchange rate regime brings about different outcomes during the
dynamic adjustment process, and in particular for the non-oil trade balance.
The key variables that contribute to this difference are the inflation rate and
nominal exchange rate. The results suggest that the adoption of an alternative
exchange rate policy not only leads to a reduction of Dutch disease
consequences in the early periods of adjustment, but it can also enhance the
supply of, and demand for, non-oil output.
<<Table 4>>
Simulation outcomes for foreign asset stocks, as shown in Figure 1, show that
they initially increase in both scenarios, but this is more rapid in scenario B
12
Following Pesaran et al. (2001) and Pesaran and Pesaran (2009) and without having any prior knowledge about the direction of
the relationship among the variables, the behavioural equations are expressed in the form of an unrestricted error correction
model (UECM).
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Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
signifying higher current account surpluses during the early stage of
adjustment. Foreign asset stocks decline slightly for scenario B thereafter,
before returning to long-run steady state where it has accumulated by 23
percent. This arises from an immediate increase in oil exports and surplus in
the oil trade balance and an increase in foreign interest income, which offset
the deficit in the non-oil trade balance in both scenarios. The result indicates
that a flexible nominal exchange rate combined with perfect capital mobility
produces a significant accumulation of foreign asset stocks during the early
period of adjustment. This is mainly due to the fact that the deficit in the nonoil trade balance is less in scenario B compared to that of A during the early
periods of adjustment (see Figure 1).
The price level initially increases by almost 4 percent during the adjustment
process for the fixed nominal exchange rate regime scenario (scenario A),
and remains above base line for a period of time before it achieves its longrun steady state equilibrium. The adjustment of the price level in the early
periods is essentially influenced by oil export revenue which contributes to an
accumulation of foreign asset stocks (current account effect), which in turn
affects money growth due to balance of payments surpluses and also
generates increased spending.
The result would be different with a flexible exchange rate as an increase in
oil revenue would not influence the monetary growth rate, but, rather,
appreciate the nominal and real exchange rate. This is true as the flexible
exchange rate regime allows the economy to retain control over its money
supply compared to that of a fixed exchange rate. Thus, the adjustment of the
domestic price level reflects the adjustment of the nominal exchange rate. The
price level increases by only 2 percent in scenario B in the early periods of the
adjustment process, and returns quickly to its initial value thereafter.
Developments in the domestic price level affect the evolution of the real
exchange rate during the adjustment process. The real exchange rate initially
appreciates throughout the adjustment path with the adoption of a fixed
nominal exchange rate regime (scenario A) by 6 percent, overshooting its
long-run steady state. Also the appreciation of the real exchange rate for
scenario A is larger and is more prolonged before it depreciates towards longrun steady state. The main reason for this being that the higher domestic price
level for scenario A, induced by money growth and the difference between
non-oil demand and non-oil supply, remains above the base line for a long
period of time before reaching its long-run steady state.
With a flexible nominal exchange rate regime the real exchange rate
appreciates by less (3 percent), induced by a smaller increase in the domestic
price level for scenario B. The price level is unaffected by money growth, but it
is, rather, influenced by developments in the nominal exchange rate.
Thereafter, the real exchange rate depreciates faster than that of scenario A
towards its initial value as the price level returns quickly to its initial value.
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Proceedings of European Business Research Conference
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Development of the non-oil trade balance is influenced by the adjustment path
of the real exchange rate in both scenarios. The non-oil trade balance
deteriorates throughout the dynamic adjustment process in both scenarios,
with a noticeably larger deterioration in scenario A where it initially
deteriorates by almost 14percent. The deterioration of the non-oil trade
balance in the case of a fixed exchange rate, scenario A, is due to a
combination of (1) increasing non-oil imports arising from an increase in real
income and (2) a decline in non-oil exports throughout the dynamic
adjustment process influenced by the initial sizeable appreciation of the real
exchange rate. On the other hand the deterioration of the non-oil trade
balance in the case of a flexible exchange rate, scenario B, is due mainly to
an increase in non-oil imports stimulated by a larger increase in real income.
Non-oil exports experience a minor decline in the early stage of adjustment in
scenario B, influenced by a smaller appreciation of the real exchange rate and
a prompt return to its base value thereafter. The smaller deterioration of the
non-oil trade balance in scenario B means that the competitiveness of non-oil
exports is superior with the flexible nominal exchange rate regime combined
with perfect capital mobility.
Non-oil production increases continuously in both scenarios throughout the
adjustment path towards long-run steady state, but it increases more in the
case of the flexible exchange rate regime (scenario B). The main contributory
factor for this difference is an increase in non-oil production in scenario B
which is stimulated by an accumulation of physical capital stock, human
capital stock, imported capital stock and private capital stock on the supply
side, but also by an improved situation for non-oil exports arising from a
smaller appreciation of the real exchange rate as compared with that of
scenario A. As can be seen from Table 4, and Figure 1, public physical capital
stock, human capital stock, imported capital stock and private capital stock
accumulate in the early periods of adjustment towards their long-run steady
state. All capital stocks accumulate more with a flexible exchange rate regime,
mainly in the early periods of adjustment. This is due to two reasons; 1) as
mentioned earlier the flexible exchange rate regime offers significant
accumulation of foreign asset stocks, particularly during the early periods of
adjustment process, which could be used for more accumulation of imported
capital stock; 2) government real oil revenue increases more under a flexible
nominal exchange rate system as the economy is insulated from inflation
arising from growth of the money supply. Therefore, the larger government
real oil revenue the larger is the accumulation of public physical capital stock
and human capital stock. This implies that the major benefits from increased
oil production are upon all capital stocks and in turn upon non-oil production
arising from scenario B (flexible exchange rate regime combined with perfect
capital mobility).
The simulation results also indicate that private real wealth increases
continuously in both scenarios throughout the adjustment path towards longrun steady state. It increases more in scenario B, where it increases by 27.5
percent compared with 25 percent in scenario A. Developments in real private
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Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
wealth are induced mainly by a significant accumulation of private capital
stock, real money balances and permanent income.
Overall, the alternative policy of a flexible nominal exchange rate regime,
combined with perfect capital mobility, offers significant accumulation of
foreign asset stocks in the early stage of adjustment13, and the
competitiveness of non-oil exports improves with a flexible nominal exchange
rate regime as the real exchange rate only slightly appreciates during the
adjustment path and returns swiftly to base line. Thus, the deterioration of the
non-oil trade balance was due to the larger increase in non-oil imports
stimulated by a larger increase in real income. Therefore, it can be argued
that Dutch disease consequences can be further minimised by moving from a
fixed to flexible exchange rate regime in conjunction with greater capital
account liberalisation. A flexible nominal exchange rate policy provides
greater benefits for non-oil production, induced on the supply side by a larger
accumulation of public physical capital stock, human capital stock, imported
capital stock, and private capital stock. It is also stimulated on the demand
side by the improved competitiveness of non-oil exports. Moreover, private
sector benefits from the flexible exchange rate regime are induced mainly by
an increase in private capital stock.
<<Figure 1>>
4. Concluding Remarks
This paper has utilised a dynamic general equilibrium macroeconomic model
for the Libyan economy, aimed at evaluating the effects of additional oil
revenue upon key macroeconomic variables under different exchange rate
regimes. The simulation scenario of a fixed exchange rate with imperfect
capital mobility indicated that a permanent oil production increase by 50
percent would potentially result in an increase in private capital stock, private
sector wealth, real income, public capital stock, human capital stock, imported
capital stock, non-oil output supply and demand. However, the oil sector
boom also has the potential to deteriorate the non-oil trade balance through a
loss of competitiveness from a real exchange rate appreciation and increasing
non-oil imports arising from an increase in real income. On the other hand, for
a flexible exchange rate regime with perfect capital mobility, outcomes also
suggest that the competitiveness of non-oil exports only slightly deteriorates
as the real exchange rate only slightly appreciates during the early part of the
adjustment process. Hence, the deterioration of the non-oil trade balance was
less and was primarily due to the larger increase in non-oil imports stimulated
by an increase in real income. The Dutch disease effects, therefore, are
potentially reduced by moving from a fixed to flexible exchange rate regime. In
addition, the flexible nominal exchange rate regime in conjunction with capital
account liberalisation offers larger benefits to non-oil production, influenced by
a larger accumulation of public physical capital stock, human capital stock,
imported capital stock, and private capital stock. All of these add to the
13
Implying that foreign exchange reserves will also be higher, facilitating the purchase of imported
capital (technology).
14
Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
productivity of the non oil sector. In addition, the private sector benefits from
the flexible exchange rate regime, induced mainly through an increase in
private capital stock.
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Table 1. Parameters Values
1 ***
 2 ***
 3 ***
 4 ***
6 *
7 *
 ***
*
8 **
 9 **
10 **
11 **
 ***
 ***
 ***
1.0
1.0
1.0
0.75
0.6
0.3
0.5
0.8
0.4
0.3
0.15
0.15
0.5
0.5
0.5
1 **
 2 **
 3 **
12 **
13 *
14 *
15 *
16 *
17 *
v **
1 *
2 *
3 *
 5 ***
 6 ***
 7 ***
 ***
1 ***
 2 ***
1 *
2*
1 *
2 *
3 *
4 *
5 *
1 *
2 *
3 *
 ***
rs ***
0.3
0.2
0.2
1.0
0.7
0.45
0.5
0.75
0.25
0.7
0.4
0.36
0.09
1.0
1.0
1.0
0.2
0.6
0.1
0.65
0.4
0.1
0.5
0.4
0.3
0.2
0.15
0.5
0.35
0.30
0.05
* Estimated coefficients obtained using ARDL as contained in Table 3. See also Ali and Harvie
(2013).
** Calculated by the authors based on available data.
*** Cox and Harvie (2010), and Harvie and Thaha (1994).
Table 2: Testing for the Existence of a Long-Run Relationship among the
Variables*
Equation
95%
Lower
bound
7.1331
95%
Upper
bound
8.1223
90%
Lower
bound
5.9643
90%
Upper
bound
6.8483
The
computed
F-statistic
8.5036
F ( xn / (e  p *  p), y*, D78 , D2000 )
7.2027
8.0224
5.9599
6.8090
9.5687
F (mcon / y,(e  p *  p), D87 , D2003 )
6.8999
7.9831
5.7676
6.7289
6.9717
F (m  p / Nos , r ,  , D81 )
4.9827
5.9803
4.1361
5.0154
6.1426
F (w /( Nod  Nos ),  )
2.8906
4.1355
2.2636
3.3349
6.7978
F ( Nos / k p , k g , k h , em, k cap , D89 )
3.6605
5.0006
3.0991
4.2756
6.2444
F ( f / T , r * f ,(o x  po),(e  p))
4.0285
5.3829
3.3851
4.627
5.9057
F (c p / Nos , w p , D83 , D2000 )
*Critical values are obtained directly from the empirical results generated by Microfit 5.
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Table 3: Estimated Long-Run Coefficients using the ARDL technique for Equations 2, 15, 16, 19,
23, 24 and 25
n
n
n
p
p
p
p
s
s
  0   b j ct  j   c j Not  j   d j wt  j  1ct 1   2 Not 1  3wt 1   4 D83   5 D2000   t
j 1
j 0
j 0
Equation
2:The long-
c
run coefficient
estimates
based on
ARDL (3,0,0)
and selected
lag based on
AIC
Variables
No s
wp
Constant
Trend
D1983
D2000
coefficients
0.6636
0.4438
-0.6310
-0.0533
-0.1423
0.0872
t-statistics
2.9561
2.1632
-0.8602
-4.2839
-1.6100
0.9116
p
2
R = 0.74
Equation
16:The longrun coefficient
estimates
based on
ARDL (1,0,0),
and selected
lag based on
AIC
Equation
18:The longrun coefficient
estimates
based on
ARDL (1,0,0)
and selected
lag based on
AIC
D-W = 2.10
n
n
n
n
n
*
*
n
*
x   0   b j xt  j   c j  (e  p  p )t  j   d j yt  j  1xt 1   2 (e  p  p )t 1
j 1
j 0
j 0
*
 3 yt 1   4 D78   5 D2000   t
Variables
(e  p *  p)
coefficients
0.4735
t-statistics
1.4607
R2 = 0.60
D-W = 2.03
m
com
Equation
25:The longrun coefficient
estimates
based on
ARDL (1,0,1)
and selected
lag based on
AIC
D1978
D2000
5.0362
-113.30
-0.2154
-0.1012
2.0708
2.3759
-2.3044
-2.0094
-0.1869
2.0416
 4 D87   5 D2003   t
Variables
(e  p *  p)
coefficients
-0.2565
t-statistics
-2.2490
R = 0.67
run coefficient
estimates
based on
ARDL
(1,0,1,0) and
selected lag
based on AIC
Trend
n
n
n
com
*
com
*
  0   b j mt  j   c j yt  j   d j  (e  p  p )t  j  1mt 1   2 yt 1   3 (e  p  p )t 1
j 1
j 0
j 0
2
Equation
21:The long-
Constant
y*
y
Constant
Trend
D1987
D2003
0.7438
2.4202
-0.0355
0.6507
-0.6605
3.5753
1.4721
-2.0950
2.1544
-1.9677
D-W = 2.31
n
n
n
n
s
 ( m  p )   0   b j  ( m  p )t  j   c j Not  j   d j rt  j   e j  t  j  1 ( m  p )t 1
j 1
j 0
j 0
j 0
s
 2 Not 1   3rt 1   4 t 1   5 D81   t
Variables
No s
coefficients
t-statistics
R2 = 0.76
0.4102
10.1153
D-W = 2.14

r
Constant
D1987
D2003
-0.3624
-3.1979
-0.0987
-1.5171
1.3204
1.8935
-0.0738
-1.6850
-0.1166
-1.6537
n
n
n
d
s
d
s
w   0   b j wt  j   c j ( No  No )t  j   d j  t  j  1wt 1   2 ( No  No )t 1   3 t 1   t
j 1
j 0
j 0
Variables
( Nod  Nos )

coefficients
0.6778
0.4109
t-statistics
1.6985
2.2924
2
R = 0.73
D-W = 2.13
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Proceedings of European Business Research Conference
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Table 3: Continued
Equation
26:The longrun coefficient
estimates
based on
ARDL
(2,0,1,2,0,0)
and selected
lag based on
AIC
Equation
27:The longrun coefficient
estimates
based on
ARDL
(2,0,2,0,0) and
selected lag
based on AIC
n
n
n
n
n
n
p
g
cap
s
s
h
No   0   b j Not  j   c j kt  j   d j kt  j   e j kt  j   f j lt  j   g j kt  j
j 1
j 0
j 0
j 0
j 0
j 0
p
g
cap
s
h
1Not 1   2 kt 1   3kt 1   4 kt 1   5lt 1   6 kt 1   7 D89   t
Variables
kp
kg
kh
k cap
em
Constant
D1996
coefficients
t-statistics
R2 = 0.87
0.0866
0.9019
D-W =
1.93
0.5061
4.2342
0.5225
2.4162
0.3105
2.0154
0.2014
2.1358
-2.4822
-2.1223
0.0416
0.3905
n
n
n
n
n
x
f   0   c j Tt  j   b j ft  j   c j r * ft  j   d j  (o  po )t  j   e j  (e  w)t  j
j 0
j 1
j 0
j 0
j 0
x
1 ft 1   2Tt 1   3r * ft 1   4 (o  po)t 1   5 (e  w)t 1   t
Variables
T
r* f
(o x  po)
(e  p)
Constant
Trend
coefficients
t-statistics
R2 = 0.86
0.1506
1.1327
D-W =
2.16
0.5175
4.1594
0.3250
2.0135
-0.3787
-1.2976
-0.9352
-1.3189
0.0058
1.8155
Table 4: Steady State Properties of the Model for Alternative Nominal Exchange
Policy Regimes (A and B)
(Percentage Deviation from Baseline)
f T c w p y No s k g k h k cap k p
Variable
Case 4*: A 23
B
-11.5
23
0.0
-10.50.0
25
23
27.5 25
16
19
*Oil production increase
20
15
10
16
11
10
11
17
20
Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
Figure 1: The effects of Oil Production Recovery upon key Macroeconomic Variables
Undera Fixed and Flexible Exchange Rate Regime
Price level
Foreign asset stocks
0.04
0.25
B
0.035
% deviation from baseline
% deviation from baseline
A
0.03
0.025
0.02
0.015
0.01
0.2
0.15
0.1
A
0.05
0.005
B
0
0
5
10
15
20
25
30
35
40
45
0
50
0
5
10
15
20
Periods
25
30
35
40
45
50
Periods
Non-oil trade balance
0.02
Real exchange rate
A
0.01
0
B
% deviation from baseline
% deviation from baseline
0
-0.01
-0.02
-0.03
-0.04
-0.05
B
-0.02
-0.04
-0.06
-0.08
-0.1
-0.12
-0.06
A
-0.07
-0.14
0
5
10
15
20
25
Periods
30
35
40
45
50
0
5
10
15
20
25
30
35
40
45
50
Periods
Non-oil imports
Non-oil exports
-3
5
0.14
x 10
0.12
% deviation from baseline
% deviation from baseline
0
0.1
0.08
0.06
0.04
0.02
-5
-10
-15
A
B
0
B
-0.02
0
5
10
15
20
25
30
35
40
45
A
-20
50
Periods
21
0
5
10
15
20
25
Periods
30
35
40
45
50
Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
Physical capital stock
0.18
0.16
0.16
0.14
0.14
% deviation from baseline
% deviation from baseline
Non-oil output supply
0.18
0.12
0.1
0.08
0.06
0.04
0.12
0.1
0.08
0.06
0.04
A
A
0.02
0.02
B
0
0
5
10
15
20
25
30
35
40
45
B
0
50
0
5
10
15
20
Periods
30
35
40
45
0.12
0.1
0.1
% deviation from baseline
0.12
0.08
0.06
0.04
A
0.02
0.08
0.06
0.04
A
0.02
B
B
0
0
5
10
15
20
25
50
Foreign capital stock
Human capital stock
% deviation from baseline
25
Periods
30
35
40
45
0
50
0
5
10
15
20
Periods
25
30
35
40
45
50
Periods
Private capital stock
Real income
0.2
0.3
0.25
% deviation from baseline
% deviation from baseline
0.15
0.1
0.05
0.2
0.15
0.1
0.05
0
A
A
0
B
B
-0.05
0
5
10
15
20
25
30
35
40
45
-0.05
50
Periods
0
5
10
15
20
25
Periods
22
30
35
40
45
50
Proceedings of European Business Research Conference
Sheraton Roma, Rome, Italy, 5 - 6 September 2013, ISBN: 978-1-922069-29-0
Real government revenue
Real private wealth
0.4
0.3
0.35
% deviation from baseline
% deviation from baseline
0.25
0.2
0.15
0.1
0.05
0.3
0.25
0.2
0.15
0.1
A
A
0
0.05
B
-0.05
0
5
10
15
20
25
30
35
40
45
B
0
50
0
5
10
15
20
25
Periods
Periods
23
30
35
40
45
50