AN EMPIRICAL ANALYSIS OF PASS-THROUGH OF OIL
PRICES TO INFLATION: EVIDENCE FROM NIGERIA.*
AUWAL, Umar
Department of Economics,
1
Ahmadu Bello University, Nigeria – West Africa
aumar@abu.edu.ng , aumar27@yahoo.co.uk
+234 803 227 4567 , +234(0)705 727 6029
ORGANIZATION OF THE WORK
Introduction.
 Received Knowledge vs. Objective(s).
 Data Source and Estimation techniques.
 Models Specification.
 Unit Root test.
 Models Estimation, interpretation and Analysis.
 Summary and Conclusions.

2
1.0 INTRODUCTION

Oil prices have risen sharply over the last year, leading to concerns
that we could see a repeat of the 1970s, when rising oil prices were
accompanied by severe recessions and surging inflation.

The oscillation of global oil prices has always been a major
concern in market instability. This instability resulted into
inflation. Consequently, the price of oil and inflation are often
seen as being connected within a cause and effect framework. As
oil prices move up or down, inflation follows in the same
direction. The reason why this happens may be that oil is a major
input in the economy - it is used in critical activities such as
fueling transportation or goods made with petroleum products and if the costs of intermediate input rise, so should the cost of end
output
(http://www.investopedia.com/ask/answers/06/oilpricesinflation.as
p) .
3
INTRODUCTION (CONT…)






Crude Oil Prices
Period of high price strategy in the oil market
Period of substantial decrease in crude oil prices - It reached
a peak of $147 in july,2008 and decrease to $38.6 in
December, 2008 and now is below $80 (Abosedra, 2009).
Nigeria : (i)a mono-cultural economy
(ii)recognized as one of the most volatile
economies in the world
Volatility: a major constraint on development
Causes: planning more problematic and
investment more risky (Ukwu et.al, 2003)
4
2.0 OBJECTIVES OF THE STUDY:
Received Knowledge

There have been many papers
that have examined passthrough
of
oil
price
fluctuations to exchange rate
as well as some that have
examined pass-through to
domestic inflation.

Many of the recent studies
have concentrated on the
relationship
between
an
country’s characteristics and
the pass-through of oil price
fluctuations in that country.
Objective(s)

The objective of this paper is to
empirically analyze the passthrough of oil price shock to
inflation in Nigeria. Specifically
–
 It examines the historical
relationship between oil
price shocks and inflation in
light of trend analysis and
some recent research, and
 Estimate and analyzes the
impact of oil price and
exchange rates on inflation.
 it uses monthly data from
2003:01 to 2012:10.
5
3.0 DATA SOURCE AND METHODOLOGY
Data Source
Monthly data :2003:01
- 2012:10
 Type : Crude Oil
Prices, Exchange rates
and Inflation
 Source: Central Bank
of Nigeria’s website –
Data and Statistics
division

Models employed

OLS, VAR-VECM and
Granger Causality
model were employed
to analyze the data.
6
TREND ANALYSIS
7
OIL_PRICE
140
120
100
80
60
40
20
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
8
EXCHANGE_RATE
160
150
140
130
120
110
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
9
INFLATION
30
25
20
15
10
5
0
2003
2004
2005
2006
2007
2008
2009
2010
2011
2012
10
4.0 Models Specification
Model
OLS, VAR-VECM
Model Specification
This study employs OLS and VAR-VECM for empirical analysis
and only focusses on three chosen variables: Oil Price (Bonny
light, $/B), Exchange rates (N/$) and Inflation (All items – year
on change).
Inf  f (OP )
Inf  f (OP , EX )
Inf    OP  EX  
0
t
1
t
t
2
t
Where Inft is Inflation rate for period t. OPt is Crude Oil Price
for period t, and EXt is exchange rates for period t. To get the
best result, the equation must be in log for all variables.
ln Inf
Pre – estimation tests
conducted
t

  ln OP  ln EX  
0
1
t
2
t
t
Lag selection criteria, Johansen test of Co-integration, System
equation estimation
11
5.0 Unit Root Test
ADF – TEST
Variable
Crude Oil Price
Order of Integration
I(1)
Critical Values
-3.4900 (1%)
-2.8874(5%)
Computed Values
-4.672726
-2.5804 (10%
Exchange Rate
I(1)
Inflation Rate
I(1)
3.4900 (1% )
-2.8874 (5% )
-2.5804 (10% )
-3.4900 (1%)
-2.8874 (5%)
-4.329422
-4.267187
-2.5804 (10%
12
6.0 MODEL PRESENTATION, ESTIMATION
&
ANALYSIS OF THE RESULTS:
13
ORDINARY LEAST SQUARES OUTPUT
Dependent Variable: INF
Method: Least Squares
Date: 04/22/13 Time: 16:38
Sample (adjusted): 2003M01 2012M09
Included observations: 117 after adjustments
Variable
OP
EX
C
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Prob(F-statistic)
Coefficient
Std. Error
t-Statistic
-0.061926
0.111950
1.327876
0.015108
0.035382
4.604224
-4.098788
3.164009
0.288404
0.150036
0.135124
4.559316
2369.759
-342.0054
10.06164
0.000095
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
Prob.
0.0001
0.0020
0.7736
12.19744
4.902558
5.897529
5.968354
5.926283
0.244726
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GRANGER CAUSALITY TEST
Pairwise Granger Causality Tests
Date: 04/22/13 Time: 17:31
Sample: 2003M01 2012M12
Lags: 2
Null Hypothesis:
Obs
F-Statistic
Prob.
EX does not Granger Cause OP
OP does not Granger Cause EX
115
1.70448
2.61122
0.1866
0.0780
INF does not Granger Cause OP
OP does not Granger Cause INF
115
0.70705
0.52597
0.4953
0.5925
INF does not Granger Cause EX
EX does not Granger Cause INF
115
0.91917
0.47069
0.4019
0.6258
15
CO-INTEGRATION – OIL PRICE TO INFLATION
Date: 04/22/13 Time: 16:30
Sample (adjusted): 2003M04 2012M09
Included observations: 114 after adjustments
Trend assumption: Linear deterministic trend
Series: INF OP
Lags interval (in first differences): 1 to 2
Unrestricted Cointegration Rank Test (Trace)
Hypothesized
Trace
0.05
No. of CE(s)
Eigenvalue
Statistic
Critical Value
Prob.**
None *
0.107121
16.32007
15.49471
0.0375
At most 1
0.029413
3.403341
3.841466
0.0651
Trace test indicates 1 cointegrating eqn(s) at the 0.05 level
* denotes rejection of the hypothesis at the 0.05 level
**MacKinnon-Haug-Michelis (1999) p-values
16
VECM ESTIMATES
Error Correction:
D(INF)
D(OP)
CointEq1
-0.136008
(0.04255)
[-3.19644]
-0.215053
(0.12746)
[-1.68723]
D(INF(-1))
0.196687
(0.09350)
[ 2.10365]
-0.022662
(0.28008)
[-0.08091]
D(INF(-2))
0.083269
(0.09499)
[ 0.87665]
0.018721
(0.28454)
[ 0.06579]
D(OP(-1))
0.007182
(0.03169)
[ 0.22667]
0.364237
(0.09491)
[ 3.83752]
D(OP(-2))
-0.005914
(0.03196)
[-0.18506]
0.075168
(0.09573)
[ 0.78523]
C
0.036832
(0.19651)
[ 0.18743]
0.424848
(0.58866)
[ 0.72172]
17
VECM OUTPUT – SYSTEM EQUATION
Dependent Variable: D(INF)
Method: Least Squares
Date: 04/22/13 Time: 16:32
Sample (adjusted): 2003M04 2012M09
Included observations: 114 after adjustments
D(INF) = C(1)*( INF(-1) + 0.0961409050262*OP(-1) - 19.2942120304 ) +
C(2)*D(INF(-1)) + C(3)*D(INF(-2)) + C(4)*D(OP(-1)) + C(5)*D(OP(-2)) +
C(6)
C(1)
C(2)
C(3)
C(4)
C(5)
C(6)
R-squared
Adjusted R-squared
S.E. of regression
Sum squared resid
Log likelihood
F-statistic
Coefficient
Std. Error
t-Statistic
-0.136008
0.196687
0.083269
0.007182
-0.005914
0.036832
0.042550
0.093498
0.094986
0.031685
0.031956
0.196511
-3.196438
2.103650
0.876645
0.226674
-0.185056
0.187432
0.106455
0.065087
2.082755
468.4896
-242.3180
2.573369
Mean dependent var
S.D. dependent var
Akaike info criterion
Schwarz criterion
Hannan-Quinn criter.
Durbin-Watson stat
Prob.
0.0018
0.0377
0.3826
0.8211
0.8535
0.8517
0.047368
2.154033
4.356456
4.500466
4.414901
2.008545
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COEFFICIENT TEST – WALD TEST APPROACH
Wald Test:
Equation: EQN
Test Statistic
F-statistic
Chi-square
Value
df
Probability
2.573369
12.86684
(5, 108)
5
0.0306
0.0247
Value
Std. Err.
-0.136008
0.196687
0.083269
0.007182
-0.005914
0.042550
0.093498
0.094986
0.031685
0.031956
Null Hypothesis: C(1)=C(2)=C(3)=C(4)=C(5)=0
Null Hypothesis Summary:
Normalized Restriction (= 0)
C(1)
C(2)
C(3)
C(4)
C(5)
Restrictions are linear in coefficients.
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7.0 SUMMARY AND CONCLUSION






The co-integration between oil price and inflation variable
exist at 5% significant level in the long run.
For granger causality test, we found that the inflation does not
granger cause to the exchange rate but it does granger cause
to the oil price.
The oil price does granger cause to the inflation but it does
not granger cause to the exchange rate.
The exchange rate does not granger cause to both of the
variables (Inflation and Oil Price).
So, the oil crude price can give an effect on inflation. If the rate
of crude oil price changes, the inflation also changes.
The finding will contribute to Nigerian government in
making policy towards crude oil price to avoid from the
inflation.
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THANK YOU FOR YOUR ATTENTION
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