Proceedings of 11th International Business and Social Science Research Conference
8 - 9 January, 2015, Crowne Plaza Hotel, Dubai, UAE. ISBN: 978-1-922069-70-2
Does Oil Price Change Impact on Stock Market Return in an
Emerging Economy? Evidence from Nigeria
Alex. E. Osuala1 and Ebieri Jones2
The study examines empirically the long held theory that crude oil price change
negatively impacts on stock market return. Using monthly data covering the period
1985 to 2011- resulting in 324 data points, the study examines this theory in the
context of Nigeria. The study finds a significantly positive relationship between oil
price and stock market return both on the short-run and the long-run, and that the
direction of relationship is from oil price to market return, and finds no reverse
causation. The study therefore recommends a strong effort towards diversification of
the Nigerian economy in order to avoid the detrimental effect of fall in oil price in the
international market.
Keywords: Oil Price Shock, Stock Market Return, Co-Integration.
1.0 Introduction
Crude oil occupies a very important place in the global economy. Given this fact, oil price
change in the international market remains a significant determinant of global economic
performance. Overall, an oil price increase leads to a transfer of income from importing to
exporting countries through a shift in the terms of trade. The magnitude of the direct effect
of a given price increase depends on the share of the cost of oil in national income, the
degree of dependence of the country in question on imported oil and their ability to reduce
consumption and switch away from oil (Majidi, 2006). Naturally, the bigger the oil-price
increase and the longer the oil shock, the bigger the macroeconomic impact.
Several different and joint factors could lead to “oil price shock” in the global economy,
often arising from developments in the exporting countries. Thus in 1973 following the
Arab-Israeli War, the world experienced its first major “oil shock”. The second major “oil
shock” took place in 1979 as a result of the fall of Shah of Iran from power. According to
Verleger (2000), “it can be argued that a third major „oil shock‟ began in 1999 and is now
gaining momentum”. Olomola and Adejumo (2006) noted that persistent oil shocks could
have severe macroeconomic implications with challenges for policy making-fiscal or
monetary- in both the oil importing and oil exporting countries.
For net oil-exporting countries like Nigeria, a price increase directly increases real
national income through higher export earnings, though part of this gain would be later
offset by losses from lower demand for exports generally due to the economic recession
suffered by trading partners.
Expectedly, the increase in real national income resulting from oil price increase will boost
the purchasing power of the economy, promote industrial growth and encourage
investment in the national economy. Consequently corporate firms will experience good
time, with positive implication on stock prices and dividend pay-out to investors
_______________________________________________________________________
1
Alex. E. Osuala (PhD), Department of Banking and Finance, College of Management Sciences, Michael
Okpara University of Agriculture, Umudike, Nigeria.
Email: Osuala.alex@mouau.edu.ng; Tel:
2348030606878.
2
Ebieri Jones, Department of Accounting, College of Management Sciences, Michael Okpara University of
Agriculture, Umudike, Nigeria. Email: ebierijones@yahoo.co.uk.
Proceedings of 11th International Business and Social Science Research Conference
8 - 9 January, 2015, Crowne Plaza Hotel, Dubai, UAE. ISBN: 978-1-922069-70-2
(Asaolu and Ilo, 2012). Given the above scenario, it is believed that the performance of listed
firms in an oil-exporting country like Nigeria will invariably be reasonably dependent on oil price
changes in the global oil market.
In the same vein, an oil price decrease will have a shrinking effect on the purchasing power of the
country, retard industrial growth and discourage investment in the national economy. Thus, there
has been concern in the country about the drop in crude oil prices especially over the last several
weeks. From a figure of $104 per barrel on August 1, 2014, the OPEC basket of prices collapsed to
about $82 per barrel on October 28, 2014. The drop of over $20 per barrel in the three months
between August and October has raised justifiable fear given our overwhelming dependence on oil
and gas exports for over 90 per cent of our country‟s foreign exchange earnings.
Commenting on the oil price shock, the Finance Minister and Coordinating Minister for the
Economy, Dr. (Mrs) Ngozi Okonjo-Iweala told the Senate committee on the Medium Term
Economic Framework (MTEF) on Monday, October 27 that the Nigerian economy was facing
some challenge on account of the oil price drop. She stated that The Excess Crude Account created
to cushion the economy at difficult times like this had been depleted to the tune of $4.1 billion,
down from $9 billion (Vanguard, 2014).
However, the present study examines the casual relationship between oil price changes and Nigeria
stock market return. Asaolu and Ilo (2012) assumed implicitly that oil price change is responsible
for the performance of the Nigeria stock market return. There is need to empirically verify this
assertion and also confirm the claimed inverse relationship existing between market return and oil
price change. Furthermore, the study investigates the existence of long-run relationship between
the two variables over a longer period of time (1985-2011) using monthly data, than were done in
the previous studies.
1.1 Some Conceptual Issues
Often times, oil price stock is used interchangeably with oil price change which refers to change in
crude oil prices. However, it will be needful to describe with some precision the meaning of the
term “oil shock “and hence highlight the major difference it has with oil price change. According
to Verleger (2000), oil stock can be defined for economic purposes, as an increase in oil prices
large enough to cause a worldwide recession or a significant decline in global economic activity.
”significant” decline on the other land is defined as a reduction in the growth of real GDP below
projected rates by two to three percentage points . However in this study, oil stock has been used
Proceedings of 11th International Business and Social Science Research Conference
8 - 9 January, 2015, Crowne Plaza Hotel, Dubai, UAE. ISBN: 978-1-922069-70-2
interchangeably with oil price changes to mean a significant change in oil price -either an upward
change or downward change.
2.0
REVIEW OF RELATED EMPIRICAL LITERATURE
There are rather few studies on the impact of oil price change on stock market return. The bulk of
the available work have focused essentially on the impact of oil price shocks on the level of output,
majority of them suggesting that rising oil prices
reduced output and
increased inflation
(especially between the 1970s and early 1980s), and falling oil prices boosted output and lowered
inflation (Hamilton 1996; Daniel 1997 Cashin, Liang and Mcdermoth,2000). It is also a common
knowledge that most of the work were based on developed economies focussing on the burden of
such price increase on the oil importing nations. Others such as Bernanke , Gertler and Watson
(1997) analysed the monetary policy response to oil price shocks.
On the Nigeria scene, Olomola and Adejumio (2006) examine the effect of oil price shock on
output, inflation, the real exchange rate and the money supply using quarterly data from 19702003. Employing the VAR method for their study, they opine that contrary to previous empirical
findings in other countries, oil price shock does not affect output and inflation in Nigeria. They
observe however that oil price shocks do significantly influence the real exchange rates. The
implication of this, according to them, is that a high real oil price change may give rise to wealth
effect that appreciates the real exchanges rates. It was Asaolu and ilo (2012) that pointedly
examined the impact of world crude oil price on stock market return using the co-integration and
vector error correction (VEC) approach for 1984-2007. They found a long-run equilibrium
relationship between the Nigerian stock market return and oil price. However, they observed that
contrary to expectation, Nigeria, an oil expecting country still experiences the golden rule-„oil up,
stock down‟ which according to them should be applicable to oil-importing countries. They
conclude that the development could be an indication of the country‟s failure to translate its huge
foreign exchange earnings from oil into an improved industrial sector productivity; or it could be
as noted by Verleger (2000 ) that monetization of oil revenue has been a major factor in liquidity
management as its creates adverse effects on the three key macroeconomic price – interest rate,
exchange rate and inflation rate, when it is unchecked.
Proceedings of 11th International Business and Social Science Research Conference
8 - 9 January, 2015, Crowne Plaza Hotel, Dubai, UAE. ISBN: 978-1-922069-70-2
3.0
METHODLOGY
We use monthly data collected from the Central Bank of Nigeria (CBN) statistical bulletin volume
22, CBN website, and the International Energy Association (IEA).Our sample covers the period
from January 1985 to December 2012 giving us a total of 336 data points. The data on Nigeria
stock market return proxied by the stock market capitalization and the monthly exchange rate
were obtained from the CBN statistical bulletin while the monthly data on dollar price of oil was
collected from IEA. The method of analysis is simple regression analysis. Our analytical model
mimics Asaolu and Ilo (2012) but with some modifications Contrary to Asaolu and Ilo‟s work,
this study regresses market capitalization (MC) which is our proxy for stock market return on
dollar price of oil (DPO) only. The other explanatory variables included by them namely Gross
Domestic Product (GDP) and exchange rate were dropped since the study is not on the direct
impact of economic growth on the stock market. The exchange rate was rather used to multiply
the DPO because oil price is in dollar and there in need to relate the value to our national currency,
naira.
Hence our model in given implicitly as:
MCt  f ( DPOEt ) …………………………………………………………
(1)
and explicitly as:
MCt  0  1DPOEt  ut ……………………………………………..
(2)
where MCt = Market capitalization at time, t.
DPO = dollar price of oil multiplied by exchange rate at time period, t.
B0 = the y-intercept which represents the value of MC when DPO = zero.
B1 is the slope of the regression of DPOE on MC. A prior, it is expected that B1>0.
ut is stochastic variable at time, t.
In order to examine the long-run and casual relationship between oil price change and stock
market performance, the study uses the Augumented Dickey Fuller (ADF) and Granger causality
tests. This requires a pretest for stationarity of variables to avoid spurious regression (Osuala,
Proceedings of 11th International Business and Social Science Research Conference
8 - 9 January, 2015, Crowne Plaza Hotel, Dubai, UAE. ISBN: 978-1-922069-70-2
2010). The stationarity or unit root test is done also using Augument Dickey Fuller test. The
following equation was used to check the stationarity of the time series data used in the study.
m
Yt  0  1t  Yt 1    Yt 1   t
(3)
t 1
where  t is white noise error term and
Yt 1  Yt 1  Yt 2 ; and Yt 2  Yt 2  Yt 3
These tests determine whether the estimates of ‘  ’ are equal to zero or not. Fuller (1976), as in
Osuala (2010) provided cumulative distribution of the ADF statistics by showing that if the
cumulative ratio (value) of the coefficient,  is less than the taw (  ) critical value from Fuller
table, then Y is said to be stationary. Although Harris (2003) and Shahbaz, et al, (2008) argue that
this test is not reliable for small sample data set due to its size and power properties, we think
this poses no problem in our study since our sample size is large enough, consisting of monthly
data covering a period of more than twenty six years (1985 – 2012).
The short- and long- run equilibrium solution to equation (1) above was conducted by estimating
an error correction version of the said equation after carrying out Johansen Test of Co-integration
on the time series data. More generally, the error correction model (ECM) is given as
n
n
i 1
i 1
Yt   0   yi Yt 1   xi X t 1   (Yt 1   X t 1 )  et         (4)
where  denotes the first difference operator and the quantity  (Yt 1   X t 1 ) represents the
error correction factor.
The model represented in equation 4 shows how change in Yt (MC) responds in the short-run to
changes in X t (i.e. oil price change), and to deviations from long-run equilibrium (Yt 1   X t 1 ) . The
error correction specification requires that the variables are I(I) and are co-integrated. If in
equation 4 above,   0 , there is no error correction mechanism (ECM). It is a first difference
model. et is a white noise.
The test of causality is done to confirm if DPOE granger causes MC or the other way round. If
changes in DPOE precede changes in MC, we can rule out MC causing DPOE. Using this logic,
we estimate the regression:
MCt  0    j MCt  j   c j DPOEt  j  ut
……………………………………… (5)
If past values of DPOE help to determine current values of MC, then we say DPOE granger causes MC.
Proceedings of 11th International Business and Social Science Research Conference
8 - 9 January, 2015, Crowne Plaza Hotel, Dubai, UAE. ISBN: 978-1-922069-70-2
4.0
DATA ANALYSIS AND DISCUSSION OF RESULTS
The results of the unit root test are presented in table 1 below.
TABLE 1: AUGMENTED DICKEY FULLER (ADF) UNIT ROOT TEST
VARIABLE
T-STAT AT LEVEL
-1.637887
-1.502341
MC
DPOE
P-VALUE
0.4620
0.5314
ADF STATISTICS
T-STAT AT FIRST
DIFFERENCE
P-VALUE
-5.311350
-9.220233
0.0000
0.0000
ORDER
OF
INTEGRATION
I(1)
I(1)
Since the variables are I(1), any attempt to specify the dynamic function of the variables in the
level of the series will be inappropriate and may lead to spurious regression in line with Osuala
(2010). Based on the foregoing, it became necessary to test for co-integration.
Co-integration Test
The result of the co-integration test is presented in Table 2 below.
TABLE 2: Result of Unit Root test on the residual Generated
VARIABLE
T-STAT AT LEVEL
RES
3.205559
ADF STATISTICS
T-STAT AT FIRST
DIFFERENCE
P-VALUE
0.0206
-
P-VALUE
-
ORDER
OF
INTEGRATION
I(1)
Since the residual from the regression of MC on DPOE has no unit root, we conclude that MC and
DPOE are co-integrated. This implies that there is long-run relationship between stock market
return (proxied by market capitalization) and oil price. Hence we can move on to establish the
existence or otherwise of short-run relationship between the variables (i.e., ECM). This is done by
regressing the first difference of MC on DPOE and the lag of the residual (i.e., RES t-1). The result is
presented in table 3.
Table 3: Result of ECM
Dependent Variable: D(MC)
Method: Least Squares
Date: 11/28/14 Time: 19:43
Sample (adjusted): 2 324
Included observations: 323 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
Proceedings of 11th International Business and Social Science Research Conference
8 - 9 January, 2015, Crowne Plaza Hotel, Dubai, UAE. ISBN: 978-1-922069-70-2
D(DPOE)
RES(-1)
C
22.13884
-0.039286
14.46518
4.739383
0.017170
17.53409
4.671249
-2.288112
0.824975
0.0000
0.0228
0.4100
2
R = 0.071646; F-statistic = 12.34810; Prob( F-statistic) = 0.000007
The coefficient of the Residual is negatively signed and statistically significant at 5% level. This is
as expected; and hence we conclude that there is a short-run relationship existing between stock
market
return
and
oil
price
change.
The results reveal that for a unit increase in oil price there is a 22.14 point increase in market
return. The negative coefficient on RES(-1) ( which is the ECM) indicates that if Market return is
above its long-run relationship with oil price, it will adjust (decrease) in the short-run by 0.039
points to return to equilibrium.
Causality Test
The test of causality is done to confirm the direction of relationship between DPOE and MC.
The result of the test is presented in table 4.
Table 4: Causality Test Result
Dependent Variable: D(MC)
Method: Least Squares
Date: 11/29/14 Time: 06:33
Sample (adjusted): 3 324
Included observations: 322 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(MC(-1))
D(DPOE(-1))
RES(-1)
C
0.081838
24.50009
-0.021272
12.18380
0.055681
4.840758
0.017252
17.32192
1.469779
5.061209
-1.233016
0.703374
0.1426
0.0000
0.2185
0.4823
R-squared
0.104273
Since the coefficient on DPOEt 1 is significant at 5% level of significance, we conclude that oil price
change (DPOE) granger causes market return (MC).
Proceedings of 11th International Business and Social Science Research Conference
8 - 9 January, 2015, Crowne Plaza Hotel, Dubai, UAE. ISBN: 978-1-922069-70-2
Table 5: The Reverse Causality Test Result
Dependent Variable: D(DPOE)
Method: Least Squares
Date: 11/29/14 Time: 07:06
Sample (adjusted): 3 324
Included observations: 322 after adjustments
Variable
Coefficient
Std. Error
t-Statistic
Prob.
D(DPOE(-1))
D(MC(-1))
RES(-1)
C
0.608027
0.000613
0.000730
0.088225
0.045420
0.000522
0.000162
0.162528
13.38683
1.172905
4.509231
0.542832
0.0000
0.2417
0.0000
0.5876
R-squared
Adjusted R-squared
0.399736
0.394073
The result of the reverse causality presented in table 5 shows that MC does not granger cause
DPOE at 5% level of significance.
5.0
SUMMARY AND CONCLUSION
The study examines empirically the existence of long-run equilibrium between crude oil price
change and stock market return in the Nigerian context. Using monthly data covering the period
1985 to 2011, and analyzing the data in the co-integration and error correction model (ECM)
framework, the study finds a significantly positive relationship between oil price and stock market
return both on the short-run and the long-run, and that the direction of relationship is from oil price
to market return. It finds no reverse causation.
The study therefore concludes that oil price change is a very significant factor influencing stock
market return in Nigeria. Hence, it recommends proper harnessing of crude oil income in order to
further develop the Nigerian stock market, and a strong effort towards diversification of the
Nigerian economy in order to avoid the detrimental effects of fall in oil price in the international
market.
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Proceedings of 11th International Business and Social Science Research Conference
8 - 9 January, 2015, Crowne Plaza Hotel, Dubai, UAE. ISBN: 978-1-922069-70-2
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