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Energy prices and business cycles: Lessons from a simulated small open economy model
Torsten Schmidt, RWI Essen*
Tobias Zimmermann, RWI Essen*
Preliminary Version, October 2008
Abstract
Despite energy price hikes in recent years growth rates turned out to be high in
most industrialised countries. Given the well-known adverse effects of energy
price shocks in the 1970s and 1980s, this may be puzzling. This study investigates
if a reduction in the energy cost share or different sources of energy price hikes
can explain this puzzle. By adding an exogenous two variable VAR to a new open
economy model for Germany, it is considered that energy prices and the global
economy are independent from domestic variables but influence each other. We
show that calibrating the energy cost share to data averages is not sensible. Instead
long run fluctuations in important observable structural parameters and VAR
coefficients change the calibration of the model each period. By shocking the
model by an increase in energy prices (global output), the effects of supply-driven
(demand-driven) energy price increase are simulated. The results point out that the
effects of recent energy price hikes have only been different, because they were
demand-driven. Therefore, supply-driven energy price increases are still an important source of business cycle fluctuations.
JEL Classification: E31, E32, F41
Keywords: Energy prices, new Keynesian open economy model
*
*
Hohenzollernstraße 1-3, 45128 Essen. E-Mail: [email protected].
Hohenzollernstraße 1-3, 45128 Essen. E-Mail: [email protected].
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1.
Introduction
Energy prices have risen dramatically since 2004 while economic growth remains
relatively high in most energy importing countries. This suggests that the current
effects of energy price hikes are different from the seventies and early eighties. In
general, there are two categories of explanations. First, the difference can be
caused by a change in the economic structure, in particular a reduction of the energy cost share. In this case, the effects of supply-driven energy price shocks were
reduced permanently. Second, recent energy price increases are likely to be demand-driven to a large extent, i.e. triggered by a soaring world economy. Thus,
the favourable stance of the world economy might have compensated the adverse
effects of more costly energy.
By simulating a new open economy (NOE) model for the German economy, we
analyse these two explanations more elaborately. In the model the size of the energy cost share determines the strength of adverse supply effects of energy price
hikes. Due to the importance of this variable for our simulations we extract the
underlying trend of this and other important variables and use them to change the
calibration of the model for each period. Moreover, energy price and global economy shocks are supposed to be related. We account for this co-movement by adding an two variable VAR for energy prices and global GDP to the NOE model.
Changes in the persistency and the relation between shocks are captured by varying the relevant parameters each period according to 40 period rolling window
estimates.
Two different types of energy price shocks are performed each period: supplydriven energy price shocks – simulated by an innovation to energy prices, and
demand-driven energy price movements – simulated by an innovation to global
output. The results of our simulations suggest that, energy prices are still an important source for business cycles in Germany. Except for the nineties, energy
price hikes still have substantial negative effects if they were supply-driven;
hence, the source of the shock matters a lot. Then, only the simulated responses to
a global economy shock resemble the evolution of the energy price and important
domestic variables during the recent energy price shock episode. Consequently,
the effects of recent energy price hikes have only been moderate, because they
were demand-driven to a large extent.
Our results contribute to the ongoing discussion whether the effects of oil price
shocks have changed since the early seventies. In favour of non-fundamental
changes Hamilton (1996) stresses that the effects of energy price increases are still
the same as in the seventies if one concentrates on strong oil price increases. In
line with our approach, Kilian (2006) claims that the energy price shocks in the
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seventies and early eighties were exogenous supply shocks caused by political
events while the recent energy price hike was caused by excess demand, in particular related to increasing economic activity in transition economies like China
and India. In contrast, other authors argue that the energy intensity of production
has been reduced by industrial countries since the seventies (e.g. Blanchard, Gali
2007; Sanchez 2008). With the experience of the energy price shocks, firms increased their energy efficiency of production. Moreover, a trend towards more
flexible real wages lead to smaller responses of real output and inflation after an
energy price shock. Finally, stagflation in the U.S. during the seventies and early
eighties was mainly caused by monetary policy (Barsky, Kilian 2001; Bernake,
Gertler, Watson 1996). In this case, the political events in the Middle East only
amplified the economic downturn.
The outline of the paper is as follows: in the next section we describe some stylized facts concerning important economic variables. In section three we describe
the model, the calibration and the solution methodology. Section four presents the
simulation results. Section five summarizes and concludes.
2. Basic facts
In this section we identify important energy price shocks and characterise the
evolution of important macroeconomic variables during these episodes. It is
shown that real variables evolve quite differently, whereas the magnitudes of the
price increases are quite similar.
Figure 1 visualises the developments of nominal and real prices of imported energy sources. The price series is the price index of imported energy provided by
the Federal Statistical Office. Since 1970 there are four big jumps in real energy
prices. The first jump in the energy price index occurred in 1974 from 40 to 140.
The second increase from 80 to 160 started in 1979. The increase of energy prices
after 1999, also proceeded in two steps. In the first step energy prices jumped from
40 to 100 and moderated to 90 in 2002. The second increase started in 2004 and
reached in 2007 the level of 1981.
4
Figure 1. Energy shock episodes
240
200
160
120
80
40
0
1970
1975
1980
1985
1990
1995
2000
2005
Real pric e of im ported energy
Nom inal pric e of im ported energy
Notes: To get the real series the nominal price index of imported
energy (2000 = 100) is deflated by the GDP-deflator. – Source: Federal Statistical Office.
The movements of the price for imported energy sources during the four previously defined episodes are characterized in table 1. The last two columns show the
change of the nominal and the real energy price index, respectively. During the
first energy shock episode the real energy price increased by more than 130% and
nearly doubled again between 1978:Q4 and 1981:Q3. Though the recent shock
episodes show slight differences according to these numbers, it is unlikely that
these differences are sufficient to explain the different effects on energy importing
economies.
Table 1. Energy shock episodes
run-up period
change in %
(nominal)
change in %
(real)
Shock 1
1973:Q3-1974:Q1
135
132
Shock 2
1978:Q4-1981:Q3
107
94
Shock 3
1999:Q1-2000:Q4
105
106
Shock 4
2004:Q1-2006:Q3
50
48
5
Table 2 reports the development of important macroeconomic variables during the
episodes of substantial energy price increases. Here, growth rates are added eight
quarters subsequently to the quarter in which the energy price starts to rise. Then
the cumulated growth rates of the previous eight quarters are deducted. Inflation
and interest rates are averaged over these periods.
It is shown that the first two energy price shock episodes were accompanied by a
substantial loss in GDP, while in the third and fourth episode there was a gain
instead. Except for the first episode, when there was a loss, exports increased
faster in periods of energy price shocks. However, the gains in exports were substantially higher in the recent two episodes than previously. There is also a slight
change in the effects on inflation. During the first two energy price shocks inflation increased about 2.6 percentage points, while the inflation rate has increased
moderately (by 1.4 percentage points) during the recent energy price shocks. It is
therefore not surprising that the interest rate increased to a lesser extent during the
more recent energy price shocks. However, table 2 shows that monetary policy has
even lowered interest rates during the first energy shock episode and was all the
more restrictive afterwards. The reaction with regard to the recent shocks seems to
be more consistent.
Table 2: Changes in selected macroeconomic variables during energy shock episodes
Shock 1
Shock 2
Shock 3
Shock 4
GDP
-7.4
-1.2
2.9
0.7
Exports
-10.6
3.4
31.3
8.9
Inflation
-0.3
5.5
1.3
1.5
Interest rate
-2.5
1.5
0.7
0.5
3. Model simulations
To investigate the reasons why similar increases in energy prices have quite different effects on the German economy, a new open economy- (NOE-) model in
style of McCallum and Nelson (1999) is used. Like Kamps and Pierdzioch (2002)
the model considers that energy is not only used for productive purposes, but is
also consumed. According to the model, Germany is treated as a small open economy, i.e. the stance of the global economy and the real price of imported energy
sources are modelled as exogenous shocks. By using a structural model, the effects of a lower energy cost share can be identified. However, after presenting the
model setup, we show that the energy cost share in Germany exhibits long-run
fluctuations, including a trend reversal, which are commonly not classified as
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cyclical. The same is true for the relation between energy prices and world GDP
growth. To capture these trends, a time-varying calibration of the models is proposed. According to this concept, the effects of both shocks have to be calculated
separately for each period.
3.1 Model setup
In this section we describe the NOE-model. Since the derivation of the model is
well documented in the literature, only a brief description of the model is given. In
the following lower case letters denote logarithms of the corresponding upper-case
variables.
Aggregate supply
In the model energy is utilized to produce domestic output according to a CESproduction function:
1
υ1 υ
Yt = ⎡⎢α1 N tυ1 + (1 − α1 ) ( EtY ) ⎤⎥ 1 .
⎣
⎦
N t and EtY represent labour input or energy input, respectively. It is assumed that
under price flexibility labour input equals one for all t . Therefore, energy input
y
under price flexibility, et , is determined by potential output, y t , and energy
prices, pte :
y
et = y t −
1
pe .
1 − υ1 t
Output under price flexibility is:
y t = (1 − α1 ) ( eYSS ) et .
υ1
y
The parameter eYSS represents the energy cost share of production in the steady
y
state. By combining both relations, et can be eliminated.
(1 − α1 ) ( eYSS )
υ1
yt = −
υ
(1 − υ1 ) ⎡⎢⎣1 − (1 − α1 ) ( eYSS ) 1 ⎤⎥⎦
p te
(1)
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Output under flexible prices, y t , negatively depends on real energy prices measured in domestic currency. Since the model abstracts from all imports besides
energy and the real energy price is directly measured in Euro, the real exchange
rate does not appear explicitly in equation (1).
Because of certain monopoly power each firm treats the price of its good as a
choice variable while the aggregate and foreign price level are taken as given.
After setting the profit-maximizing price each firm produces whatever quantity of
output is demanded. It is assumed that firms behave according to a price adjustment mechanism similar to the one introduced in Fuhrer and Moore (1995). This
approach rationalizes a reasonable degree of inertia in inflation dynamics. More
precisely, it claims that inflation, measured as the change of the price index of
domestically produced goods, is a function of the output gap, y%t , and of the
weighted average of lagged and expected inflation
Δptc = 0.5 ( Δptc−1 + Δptc+1 ) + Ψ y%t .
(2)
Here, Ψ is a parameter depending on the degree of price stickiness in the economy. The stickier prices, the flatter the Phillips curve.
The output gap
y% t = yt − y t
(3)
is characterized as the difference between actual output, yt , and the amount of
production that would prevail under flexible prices.
Aggregate demand and monetary policy
In this model energy prices affect total consumption, cxt in two ways since in case
of an energy price hike both, the production of domestically produced goods, and
the consumption of energy become more expensive. Optimal consumption is derived from households, maximizing their expected lifetime utility with respect to
total consumption, real money balances, and domestic and foreign bonds. Preferences include habit formation, using a special case of the functional form proposed by Carrol et al. (1995). By combining the first order conditions with regard
to consumption and bonds, the expectational difference equation for the change in
consumption ( Δcxt ) with respect to expected future consumption, expected price
level ( ptcx+1 ) , and the nominal interest rate ( Rt ) is:
β g1 Et Δcxt + 2 + g 2 Et Δcxt +1 + g3 Et Δptcx+1 = g1Δcxt + g3 Rt
(4)
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where β is a discount factor, and g1 to g3 depend on β , risk aversion and
habit persistence. 1 Total consumption, cxt , is the sum of domestic consumption,
ct , and imported energy, which leads to the following linear approximated identities for the consumer price level, ptcx :
ptcx = α ptc + (1 − α ) pte
(5)
where 1 − α stands for the average share of energy imports in total consumption,
ptc is the price level for domestic consumption and pte the price level for imported
energy.
The following relation determines the demand for domestically produced consumption in dependence of the relative domestic price level
ct = cxt − ( ptc − ptcx ) .
(6)
Monetary policy sets the nominal interest rate, Rt , according to a Taylor rule,
which entails a reasonable degree of interest rate smoothing.
(
)
Rt = μ0 + (1 − μ3 ) ⎡ Δpt cx + μ1 Δpt cx − π + μ 2 y% t ⎤ + μ3 Rt −1
⎣
⎦
(7)
Here, π represents the inflation objective of the central bank.
Open economy elements and goods market equilibrium
The world demand shock enters the model through the export equation:
ext = byt* + η qt .
(8)
Exports, ext , positively depend on global output, yt* , and the real exchange rate,
qt . b and η are the income and exchange rate elasticity. The real exchange is the
sum of the nominal exchange rate, st , and the difference between foreign and
domestic price levels:
1
The exact definitions and calibrated values of all parameters of
the model and can be found in the appendix.
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qt = st + ptcx − ptcx .
*
(9)
Additionally, the uncovered interest parity is assumed to hold:
Rt = Rt* + Et Δst +1 + κ t .
(10)
Here, Rt and Rt* represent the domestic and foreign nominal interest rates which
are defined as the sum of real interest rates, rt , and expected inflation
( Rt = rt + E Δpt +1 and Rt* = rt* + E Δpt*+1 ). The variable st stands for the nominal
exchange rate. In this model the foreign variables are treated as exogenous. To
close the model, we follow Schmitt-Grohe and Uribe (2003) by modelling the risk
premium, κ t , as a function of the ratio of the nominal value of foreign bonds ( bt* )
and domestic nominal output ( yt ) :
κ t = ϕ ( st + bt* − ptY − yt ) .
(11)
Since capital accumulation is ignored, total domestic production is spent solely for
domestic consumption and exports.
yt = (1 − ex SS ) ct + ex SS ext .
(12)
The parameter ex SS denotes the export share in the steady state.
Equations (1) – (12) establish a system of 12 difference equations in the endogenous variables ext , ct , cxt , κ t , ptc , ptcx , qt , Rt , st , yt , y% t , yt . In addition we
treat the energy price and all foreign variables as exogenous.
3.2. Time varying calibration
In this section the calibration of the model is discussed. The most important measure to assess the supply side effects of energy price hikes is the energy cost share,
eYSS , (figure 2). Several papers (e.g. Blanchard, Gali 2007; Schmidt,
Zimmermann 2005, 2007; Sanchez 2008) distinguish two sub-periods to investigate the effects of price shocks in more and less energy intensive times. Obviously, the calibration of a low energy intensive era from the end of the eighties up
to now seems not to be suitable any more. Even if the amount of energy (in physical units) in relation to GDP has remained lower than in the 70s and 80s, the ongo-
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ing upward trend in energy prices since 2002 has pushed the energy cost share
near to its previous peak in 1981.
Figure 2. Energy usage and energy imports in proportion to GDP
120
100
80
6%
5%
60
4%
40
3%
2%
1%
0%
1970
1975
1980
1985
1990
1995
2000
2005
Energy usage (right axis)
Energy imports (left axis)
Notes: To calculate energy usage in proportion to GDP, nominal energy
imports are deflated by the price index for imported energy and divided by real GDP. Since the level of this measure is arbitrary 1970
is set to 100. – Source: Federal Statistical Office.
Therefore, a calibration on the basis of sample averages seems not to be convenient to capture cost trends adequately. Instead, the HP-filter is used to identify
trends in the energy cost share which changes the calibration of the model for each
quarter of our sample. Thus, long-run fluctuations which are commonly not classified as cyclical are employed for calibration purposes while the remaining fluctuations of the energy prices are interpreted as shocks.2 The identified cost trend sug2
To calculate the share of imported energy in total consumption,
α , we assume that 70 percent of the imported energy is spent for
production while 30 percent are consumed by private households. This
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gests that the cost burden for the German economy, since 2005 is nearly as large
as during the eighties. The same filter is applied to calibrate the export share,
ex SS , which is an indicator of openness and therefore crucially determines the
response of the domestic economy to world GDP shocks. This parameter shows an
upward trend that has become steeper after 1995. 3
As mentioned above energy prices and the global economic activity are assumed
to be not influenced by the German economy but linked. To capture these interactions a VAR(1) which contains the real energy prices and a measure of global
output is estimated.
E
E
⎡ ptIM ⎤
⎡ p IM ⎤ ⎡ε tIM ⎤
⎢ * ⎥ = Γ1 ⎢ t *−1 ⎥ + ⎢ Y * ⎥
⎣⎢ yt −1 ⎦⎥ ⎣⎢ ε t ⎥⎦
⎣⎢ yt ⎦⎥
E
(18)
Both time series are HP-filtered before estimation. Thereby, long-run trends in
energy prices are already considered by calibration, the remaining fluctuations are
interpreted as shocks. Moreover, it is supposed that the relationship between the
exogenous variables may have changed. By estimating a rolling window scheme
of 40 quarters over the period from 1970:Q1 to 2007:Q4, trends in the relationship
between, and the persistency of exogenous shocks are captured.
The other parameters of the model are largely set to the same values as in the
studies of McCallum and Nelson (1999) and Kamps and Pierdzioch (2002).4
However, by setting the parameter υ1 close to zero a very simple approach is
chosen concerning production. Thus, the production function can be interpreted as
Cobb Douglas and α1 stands for the non-energy cost share in domestic production. The supply side of our economy resembles the approach that has been taken
in Kim and Loungani (1991) as well as Schmidt and Zimmermann (2007). Concerning preferences we also differ from the benchmark calibration in McCallum
and Nelson (1999) by assigning σ the conventional value of 1. The coefficient of
the risk premium equation, ϕ , is set to -0.02 (Ambler et al. 2004).
Well established estimates of the coefficients of a Taylor rule for Germany can be
found in the paper of Clarida et al. (1998). The point estimates for the parameters
distribution is a very rough estimate based on information from the
Arbeitsgemeinschaft Energiebilanzen.
3
Note that the corresponding parameter c SS is not calculated on
the basis of the data. Since the model abstracts from saving and
capital accumulation all output beside exports is spent for consumption purposes. c SS is therefore simply 1 − ex SS .
4
A table which entails all parameter values can be found in the
appendix.
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μ1 and μ 2 are 0.31 and 0.25, respectively. Faust et al. (2001) find similar values
for these coefficients, albeit for slightly diverging periods. All of the mentioned
papers suggest a distinctive tendency to smooth interest rates over time. For instance, according to Clarida et al. (1998), the point estimate of the relevant coefficient is equal to 0.91.
4. Simulation Results
In this section impulse response functions, showing the reaction of endogenous
variables to energy price and global economy shocks, are presented. Due to the
time varying calibration proposed above, the responses to shocks are calculated at
each point in time.
In the first simulation, only long-run movements of the energy cost and the export
share are applied whereas shocks remain unchanged. In this case, shocks are assumed to be independent AR(1)-process, that are estimated over the whole sample. The effects of energy price shocks on the German economy are plotted in
figure 3. The period at which the initial impulse of a one percent increase in energy prices hits the German economy is depicted on the x-axis. The z-axis represents the number of periods after the initial shock impulse. The vertical axis shows
the amount of reaction. Impulse response functions are calculated from 1971:Q1
to 2006:Q4. It is demonstrated that supply side effects of energy price shocks were
negligible only in the nineties. At the end of the simulation sample (2006:Q4), the
reaction of GDP amounts to over 70% of the maximum effect which is computed
for 1982. The same is also true for exports, the price level, and the reaction of the
monetary authority. Note that the final simulation starts at the end of 2006 and
therefore shows what will happen, when energy prices start to rise from the level
of 2006.To answer the question whether energy price shocks have changed it is
suggestive to compare the effects at the beginning of the defined energy shock
episodes. The magnitude of the reaction in 2004:Q1 is roughly 1/3 larger than in
1973:Q1 and 1/3 lower than in 1980:Q1. The current trend in the energy cost share
therefore suggests that the recent energy price shock should have had effects similar to earlier shock episodes. The German economy has not reduced the energy
intensity of production or the energy usage for consumption purposes sufficiently
to prevent a trend reversal of the energy cost share. Consequently, energy importing countries have not become immune to supply side-driven energy price hikes.
13
Figure 3. Impulse response functions of the NOE-model to a one unit energy
price shock, constant shock coefficients
x 10
Output
-3
x 10
-2
-4
-6
-8
-10
-12
-5
-10
-15
20
15
10
5
1980
1990
2000
20
Consumer price level
15
x 10
10
-3
5
1980
1990
2000
Interest rate
3
0.025
0.02
0.015
0.01
20
Exports
-3
2
1
15
10
5
1980
1990
2000
20
15
10
5
1980
1990
2000
So far we have shown that the energy cost share is not able to explain why the
effects of energy price shocks where severe in the seventies and early eighties, but
have only negligible effects or are even accompanied with exceptional high
growth rates nowadays. For a small export-oriented country like Germany the
source of the shock matters a lot. On the one hand, the negative effects of higher
energy prices can be compensated when they are accompanied or even triggered
by a soaring world economy. On the other hand, the negative effects of higher
energy prices can be aggravated when they are accompanied by a global recession.
In the following simulations the energy prices and global output evolve independently from the German economy, but are allowed be interrelated. Trends in the
behaviour of the exogenous shocks are employed in a two variable VAR. Since
the coefficients are estimated in a 40 periods rolling window scheme, the first
(latest) impulse response functions are available for 1975:1 (2002:Q4). Thus, the
simulations can not ultimately answer the question what will happen if energy
prices rise again in the current situation. However, simulating shocks at the beginning of 2003 should reasonably explain the evolution of macroeconomic variables
during the latest run-up period (2004:Q1-2006:Q3).
14
The setup offers two different explanations for energy price hikes. Firstly, as before an energy price increase is modelled as an exogenous initial innovation. However, contrary to the former case this shock may be aggravated by global economic downswings. Secondly, energy prices are triggered by global output. This
variant resembles a demand-driven energy price increase. We present both simulations, in the following. Since the effects on the German economy are quite different, we can decide which of the two variants yields a plausible explanation for
different shock episodes.
Figure 4 shows what happens to important macroeconomic variables subsequent
to a one unit energy price hike when all time varying elements are included. In
contrast to the former simulations differences in the impulse functions are not only
caused by trends in structural parameter but also by a changing persistency of
energy prices themselves and changing effects on the global economy. At first, it
becomes evident that the persistency of the energy price itself was exceptionally
large in the beginning of the 80s. Then, at the same time the estimated effects on
the world economy increased. Thus, the adverse supply effects on the German
output and exports were relatively persistent and heavily aggravated by a decrease
in demand from abroad. This can be seen by comparing the magnitude of the responses to the ones which are depicted in figure 3. In consequence of the high
energy price persistency during this time, the price level effects of energy price
shocks are inimitable large from the beginning to the middle of the eighties. These
simulations are therefore useful to understand the first energy shock episodes,
because they reproduce not only the very large negative impact on domestic and
worldwide aggregates, but also a harsh monetary reaction without referring to
credibility problems. Key factors are the persistency of the energy price itself and
its strong negative impact on the world economy. The last mentioned factor heavily aggravates the pure energy price shock for export intensive countries.
15
Figure 4. Impulse response functions of the NOE-model to a one unit energy
price shock, time-varying shock coefficients
Energy price
1
0.5
0
-0.5
20 15
10 5
World economic activity
0.1
0
-0.1
-0.2
-0.3
20 15
2000
1990
10 5
1980
Output
0.02
0
-0.02
20 15
10 5
0.04
0.02
0
-0.02
-0.04
20 15
10 5
Exports
0.05
0
-0.05
-0.1
20 15
2000
1990
10 5
1980
Consumer price level
2000
1980 1990
2000
1980 1990
x 10
4
2
0
-2
-4
20 15
2000
1980 1990
-3
Interest rate
10 5
2000
1980 1990
16
Even if the effects of energy prices where strongly aggravated in the seventies and
early eighties but not in recent run-up periods, supply-driven energy price shocks
in any case cause negative effects on real and positive effects on nominal domestic
variables. Thus, these simulations are less appropriate to reproduce the very recent
facts, which suggest that energy price shocks have no substantial effects or are
even accompanied by unusual high growth rates and moderate inflationary pressure.
In a final simulation exercise, the model is shocked by the same innovation to
global output in each period. It is shown that these simulations provide a reasonable explanation of the stylized facts of the recent energy price episodes. Especially, after the end-nineties, shocks to global output are accompanied by increasing energy prices. Note that the magnitude of the innovations is chosen to cause
approximately a one unit increase in energy prices in recent shock episodes. Moreover, domestic output and exports increase and the effects on the consumer price
level are moderate, so that a minor reaction of the monetary authority succeeds.
The final simulation, starting in 2002, matches exactly what can be observed in
Germany (and in other small energy importing countries) from this point in time
on up to now: a booming world economy, rapidly increasing energy prices, an
increase in domestic output and exports, moderate inflationary pressure, and a
moderate reaction of the central bank.5 The simulation of the end-eighties and
nineties suggest that economic booms and energy prices exhibit a weak or even
negative relationship, i.e. energy prices were not demand driven during this period. Surprisingly, the simulations, which are conducted for the time before 1980,
show that according to the model the demand shock explanation is not completely
implausible for previous energy shock episodes. Contrary to recent shock episodes, the negative effects of higher energy prices which succeed economic booms
strongly overcompensate the weak positive initial effects on exports and output.
As observed in this period the effects on these variables are therefore ultimately
negative. However, there is strong evidence that energy supply was shortened
previous to the earlier shock episodes. We conclude that the supply shock explanation plays at least a dominant role in the first energy shock episodes.
5
Note, that interest rates would probably be higher, if recent financial markets turbulences have not pushed central banks to keep
interest rates constant.
17
Figure 5. Impulse response functions of the NOE-model to a global economy shock, time-varying shock coefficients
Energy price
1
0.5
0
20 15
10 5
World economic activity
0.2
0
-0.2
20 15
2000
1990
10 5
1980
Exports
Output
0.02
0
-0.02
20 15
0.1
0.05
0
-0.05
10 5
2000
1980 1990
Consumer price level
0.06
0.04
0.02
0
20 15
2000
1980 1990
10 5
2000
1980 1990
20 15
x 10
4
2
0
-2
20 15
10 5
2000
1980 1990
-3
Interest rate
10 5
2000
1980 1990
18
4. Conclusions
This paper contributes to the ongoing debate on the changing effects of energy
price shocks. We illustrate that during the recent energy price shock episodes the
inflation rate and the interest rate increased moderately compared to the seventies
and early eighties, while GDP and exports showed unaltered or even higher
growth rates following recent energy shock episodes.
We show that a permanent reduction of the energy cost share can not be a source
for the different effects of energy price hikes on the German economy. While the
energy cost share is an important factor for the effects of energy price shocks, it
increased substantially since the late nineties. This ongoing upward trend in the
energy cost share suggests that energy importing countries like Germany have
become again quite vulnerable to energy price shocks in recent times. In addition,
due to this upward trend a calibration of the energy cost share to sample averages
is not useful to asses why the adverse supply effects of energy price might change
over time. Instead we propose to indentify trends in observable structural parameters which change the calibration our model each period. Using a time varying
calibration gives us also the opportunity to consider the changing relation between
energy prices and the global economy by estimating a rolling window scheme.
Simulations with an NOE-model suggest that the source of an energy price shock
plays the major role from the perspective of a small open economy. Supply-driven
energy price shocks can explain the stylized facts of the first shock episodes very
well. Hereby, the succeeding worldwide economic downswing heavily aggravated
the pure supply side effects. Moreover, since oil price increases were exceptionally persistent, even the harsh monetary reaction in the early eighties can be explained without referring to credibility problems or other special factors. Surprisingly, also the demand shock view is not completely implausible as an explanation
for the earlier shock episodes. During these times the only weak positive effects of
shocks to global production on domestic output were strongly overcompensated
by the strong negative effects of succeeding energy price increases.
On the contrary, the supply shock simulation does not yield a convenient explanation for recent energy price shocks and their consequences while a demand-driven
energy price hike can. A world economic boom has no effects from the end of the
eighties to the new century, but large energy price increases are the consequence
afterwards. Since both shocks compensate each other, the positive reaction of
domestic production and exports match the stylized facts.
Though, the risk of an energy price induced recession seems to be limited for this
time, the outlook is therefore miscellaneous. On the one hand, if energy price
movements continue to be demand-driven for the main part, their effects will
continue to be negligible. In this case two exogenous shocks will keep on compensating each other. On the other hand, if a new supply-driven energy price hike
19
which causes a worldwide recession takes place, the effects might be even
stronger due to the larger openness of the energy importing economies.
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21
Appendix A: Parameters
Table A.1: Constant parameters
υ1
-0.001
σ
1
β
0.99
h
0.6
Ψ
0.02
b
0.33
η
0.33
ϕ
-0.02
π
0
μ0
0
μ1
0.3
μ2
0.25
μ3
0.9
g1 = h − σ h
g 2 = 1 + β h 2 − σβ h 2 − σβ h
g 3 = σ (1 − β h )
22
Appendix B: Data description
GDP: Real Gross Domestic Product. Chain index. Seasonally adjusted by official source.
National Accounts. Federal Statistical Office Germany.
Consumer price level: GDP, implicit Price Deflator. National Accounts. Federal Statistical
Office Germany.
Consumption: Real private household consumption. Chain index. Seasonally adjusted by
official source. National Accounts. Federal Statistical Office Germany.
Exports: Real exports. Chain index. Seasonally adjusted by official source. National Accounts.Federal Statistical Office Germany.
Real Energy imports: Nominal energy imports – GDP-deflated. Foreign trade statistics.
Statistical Office Germany.
Real energy price: Imported energy price index 2000 = 100 – GDP-deflated. Foreign trade
price statistics. Federal Statistical Office Germany.
Nominal interest rate: three month interbank rate. German Bundesbank.
Global GDP: Real Gross Domestic Product of Belgium, Canada, Denmark, France, Italy,
Japan, Korea, Mexico, Netherlands, Spain, Sweden, United Kingdom, USA.
OECD.