A N E MPIRICAL A NALYSIS OF P ASS -T HROUGH OF O IL P RICES TO I NFLATION : E VIDENCE FROM N IGERIA. * AUWAL, Umar Department of Economics, Ahmadu Bello University, Nigeria – West Africa , +234(0)

O RGANIZATION 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 ( p). p 3

I NTRODUCTION ( 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 O BJECTIVES OF THE STUDY : There have been many papers that have examined pass- through 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. The objective of this paper is to empirically analyze the pass- through 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. Received KnowledgeObjective(s) 5

3.0 D ATA SOURCE AND M ETHODOLOGY Monthly data :2003: :10 Type : Crude Oil Prices, Exchange rates and Inflation Source: Central Bank of Nigeria’s website – Data and Statistics division OLS, VAR-VECM and Granger Causality model were employed to analyze the data. Data SourceModels employed 6

TREND ANALYSIS 7

8

9

10

ModelModel Specification OLS, VAR-VECM 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). Where Inf t is Inflation rate for period t. OP t is Crude Oil Price for period t, and EX t is exchange rates for period t. To get the best result, the equation must be in log for all variables. Pre – estimation tests conducted Lag selection criteria, Johansen test of Co-integration, System equation estimation 4.0 Models Specification 11

12 ADF – TEST VariableOrder of IntegrationCritical Values Computed Values Crude Oil Price I(1) (1%) (5%) (10% Exchange Rate I(1) (1% ) (5% ) (10% ) Inflation Rate I(1) ( 1%) (5%) (10% Unit Root Test

6.0 MODEL PRESENTATION, ESTIMATION & ANALYSIS OF THE RESULTS : 13

O RDINARY L EAST S QUARES O UTPUT 14 Dependent Variable: INF Method: Least Squares Date: 04/22/13 Time: 16:38 Sample (adjusted): 2003M M09 Included observations: 117 after adjustments VariableCoefficientStd. Errort-StatisticProb. OP EX C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter F-statistic Durbin-Watson stat Prob(F-statistic)

G RANGER CAUSALITY TEST Pairwise Granger Causality Tests Date: 04/22/13 Time: 17:31 Sample: 2003M M12 Lags: 2 Null Hypothesis:ObsF-StatisticProb. EX does not Granger Cause OP OP does not Granger Cause EX INF does not Granger Cause OP OP does not Granger Cause INF INF does not Granger Cause EX EX does not Granger Cause INF

C O - INTEGRATION – OIL PRICE TO INFLATION 16 Date: 04/22/13 Time: 16:30 Sample (adjusted): 2003M M09 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 Trace0.05 No. of CE(s)EigenvalueStatisticCritical ValueProb.** None * At most 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

VECM ESTIMATES Error Correction:D(INF)D(OP) CointEq ( ) ( ) [ ][ ] D(INF(-1)) ( ) ( ) [ ][ ] D(INF(-2)) ( ) ( ) [ ][ ] D(OP(-1)) ( ) ( ) [ ][ ] D(OP(-2)) ( ) ( ) [ ][ ] C ( ) ( ) [ ][ ] 17

VECM OUTPUT – SYSTEM EQUATION 18 Dependent Variable: D(INF) Method: Least Squares Date: 04/22/13 Time: 16:32 Sample (adjusted): 2003M M09 Included observations: 114 after adjustments D(INF) = C(1)*( INF(-1) *OP(-1) ) + C(2)*D(INF(-1)) + C(3)*D(INF(-2)) + C(4)*D(OP(-1)) + C(5)*D(OP(-2)) + C(6) CoefficientStd. Errort-StatisticProb. C(1) C(2) C(3) C(4) C(5) C(6) R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Hannan-Quinn criter F-statistic Durbin-Watson stat

C OEFFICIENT TEST – WALD TEST APPROACH Wald Test: Equation: EQN Test StatisticValuedfProbability F-statistic (5, 108) Chi-square Null Hypothesis: C(1)=C(2)=C(3)=C(4)=C(5)=0 Null Hypothesis Summary: Normalized Restriction (= 0)ValueStd. Err. C(1) C(2) C(3) C(4) C(5) Restrictions are linear in coefficients. 19

7.0 S UMMARY 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. 20

T HANK Y OU FOR Y OUR A TTENTION 21