Analyzing the Macroeconomic Effects of Oil Price Changes in t he Philippines

1. Analyzing the Macroeconomic Effects of Oil Price Changes in the Philippines Emmanuel Barnedo Presentor

2. Outline • Introduction • Methodology • Conceptual Framework • Analytical Framework • Results and Discussion • Summary and Conclusion • Policy Implications • Limitations of the Study

3. INTRODUCTION “Crude oil and various petroleum product are crucial in literally fueling the economy of a nation… If blood is the lifeline of our body, then oil is the lifeline of the economy…” -Anakpawis Rep. Crispin Beltran (2008)

5. During the oil crises in the 1970s, many countries, experienced recession (Lee and Chui, 2009; Barsky and Kilian, 2001). • In the 2000s, the Philippines proved once more that it was indeed vulnerable to the sustained increase in oil prices. • The real Gross Domestic Product (GDP) had declined considerably in 2007 until 2009 where oil prices had reached its peak in 2008.

6. Objective(s) of the Study The main objective of this study is to analyze how changes in oil prices affect crude oil consumption and some key macroeconomic indicators in the Philippines.

7. Objective(s) of the Study • Specifically, the study aimed to accomplish the following: • To determine the effects of world and local oil price changes in oil consumption and key macroeconomic indicators, such as inflation rate, investment, employment and real Gross Domestic Product; • To examine the time of disruption brought about by the world and local oil price oil price shocks;

8. Objective(s) of the Study • Specifically, the study aimed to accomplish the following: (cont…) • To compare the effects of these shocks in terms of the pattern of disruption on the domestic oil consumption and the key macroeconomic indicators; and • Lastly, to provide policy implications to lessen the impact of oil price changes.

9. Methodology Conceptual Framework Test of Stationarity Vector Autoregressive (VAR) Model Impulse Response Model Sources of Data

10. Conceptual framework

11. Let: • World oil price changes be D.DBOIL; • Local oil price changes be D.DSOIL; • inflation be INF; • total oil consumption PPS; • investment be FCF; • total employment be EMP; and • Gross Domestic Product be GDP.

12. Test of Stationarity • The Augmented Dickey Fuller (ADF) test is used. • is the differencing operator; is the white error term; and and are the coefficients of the one period lagged value and , respectively, where (are higher order autocorrelation) such that n is the optimum lag length determined using sequential search method.

13. Test of Stationarity Null Hypothesis: = 1 ( is non-stationary or there is a unit root) Alternative Hypothesis: ≠ 1 ( is stationary or there is no unit root) • It follows the same asymptotic distribution as the Dickey-Fuller test so the same critical values can be used. • Thus, if the computed absolute value of the tau statistic (|τ|) exceeds the Mackinnon critical tau values, reject the null hypothesis that = 1, the series is stationary. Otherwise, fail to reject the null hypothesis, in such case, the series is non-stationary (Gujarati, 2004).

14. Test of Stationarity • The augmented Dickey-Fuller tests for the variables under study are: • If the variable is found to be nonstationary in level form, it must be stationarized thru differencing/detrending.

15. Vector Autoregressive (VAR) Model • The first VAR model used in the study with p-lag is given by: Where: ,,, ) denotes (nx1) vector of (stationary/stationarized) time variables series ; is (nx1) vector of drift terms, is (nxn) coefficient matrix andis (nx1) vector of white noise error term; and t=1,2,…,T; p=maximum no. of lags *No. of lags were determined using AkaikeInformation Criterion -A second VAR model was similarly specified for the local oil price changes by replacing the world oil price changes () with local oil price changes ()

16. Vector Autoregressive (VAR) Model VAR Model with world oil price changes d.

17. Impulse Response Function • It traces the responsiveness of the dependent variable in the VAR system to a unit shock in error terms over time. • But the error term must be nonautocorrelated (and normally distributed) so that shocks can be represented independently. Thus, non-autocorrelation and normality of the distribution must be ensured first.

18. Impulse Response Function • The impulse response functions for this study are given as follows: • The effects of such shock upon the VAR model over time are graphed up to (k-1) lags with its confidence band. • A second set of IRFs was also specified for local oil price changes whose error terms were represented by , , , , .

19. Nature and Sources of Data • The study covered the period 1991Q1- 2010Q4. The variables included in the study were: • oil prices of Dubai Fateh (DBOIL) - IMF • pump prices for diesel oil (DSOIL) - DOE • inflation rate (INF) - NSO • petroleum products sales (PPS) - DOE • fixed capital formation (FCF) - NSCB • total employed people (EMP) - NSO • Gross Domestic Product (GDP) - NSCB

20. Nature and Sources of Data • There were some adjustments and estimations made, such as: • oil prices of Dubai Fateh (DBOIL);and • quarterly data for petroleum product sales

21. Results and Discussion

22. Stationarity of the Variables • There were some adjustments and estimations made, such as: • oil prices of Dubai Fateh (DBOIL); • the first difference () of DBOIL and DSLOIL was taken/used to represent change in world oil price (D.DBOIL) and local oil price (D.DSLOIL); and • quarterly data for petroleum product sales a Optimal lag length was determined through sequential search method. * represents significant at 5% level.

23. Stationarity of the Variables a Optimal lag length was determined through sequential search method. b Adjusted using first difference () to represent . c Adjusted using fourth seasonal differencing (). d Adjusted using detrending approach. * represents significant at 5% level.

24. VAR Models for Oil Price Changes • According to the Akaike Information Criterion (AIC), the optimal lag length for the first VAR model was three (3) while the second was two.

25. Impulse Response of Inflation Effect(s) of World Oil Price Shock Effect(s) of Local Oil Price Shock • The initial reaction of inflation was positive that may be attributed to the direct and indirect effect(s) of an oil price shock.

26. Impulse Response of Petroleum Product SAles Effect(s) of World Oil Price Shock Effect(s) of Local Oil Price Shock • Crude oil was said to be relatively inelastic. However, the significant decline in oil consumption also signalled that it was becoming less inelastic over time

27. Impulse Response of fixed capital formation Effect(s) of World Oil Price Shock Effect(s) of Local Oil Price Shock • The initial increase in investment on energy-efficient capital may be relatively higher compared to the decrease (or postponement) in the investment on other capital.

28. Impulse Response of Employment Effect(s) of World Oil Price Shock Effect(s) of Local Oil Price Shock The slow recovery of employment may be attributed to: (1) the industry-specific skills of labor (Loungani 1986) and (2) increase in investment .

29. Impulse Response of Gross Domestic Product Effect(s) of World Oil Price Shock Effect(s) of Local Oil Price Shock The increase in GDP may be attributed to the increase in investment. Such increase may have reduce the negative impact on energy-intensive sectors, such as transport

30. Conclusion Conclusion Policy Implication(s) Limitation(s) of the Study

31. Summary of the IRFs • A- Initial Response to the Oil Price Shock (the same for both) • B- Second Response to the Oil Price Shock (the same for both) • C- Magnitude of the Initial response (Max Value) (World Oil Price Changes) • D- Magnitude of the Second Response (Max Value) (World Oil Price Changes) • E- Length of Disruption of the World Oil Price Shock • F- Magnitude of the Initial response (Max Value) (Local Oil Price Changes) • G- Magnitude of the Second Response (Max Value) (Local Oil Price Changes) • H- Length of Disruption of the Local Oil Price Shock

32. Policy Implication(s) • Although oil price shocks were found to be disruptive, regulating the oil downstream industry could create more distortions. • Since the said shock is temporary, the government can implement short-term intervention, catered specifically to particular sector.

33. Policy implications As a long term solution, the government should promote the investment on energy-efficient technology/capital and the production of indigenous energy sources.

34. Limitations Non-availability of quarterly data for oil consumption The use of diesel oil price

35. End of presentation Thank you very much!