The relationship between oil price fluctuation and vietnams macro economy

INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM VIETNAM - NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE RELATIONSHIP BETWEEN OIL PRICE FLUCTUATION AND VIETNAM'S MACRO-ECONOMY • • BY LE THUANBINH MASTER OF ARTS IN DEVELOPMENT ECONOMICS HO CHI MINH CITY, June 2011 UNIVERSITY OF ECONOMICS HO CHI MINH CITY VIETNAM INSTITUTE OF SOCIAL STUDIES THE HAGUE THE NETHERLANDS VIETNAM -NETHERLANDS PROGRAMME FOR M.A IN DEVELOPMENT ECONOMICS THE RELATIONSHIP BETWEEN OIL PRICE FLUCTUATION AND VIETNAM'S MACRO-ECONOMY A thesis submitted in partial fulfilment of the requirements for the degree of MASTER OF ARTS IN DEVELOPMENT ECONOMICS By LETHUANBINH Academic Supervisor: DR DINH CONG KHAI HO 'CHI MINH CITY, June 2011 ACKNOWLEDGEMENT First of all, I would like to express my deep gratitude to my supervisor, Dr Dinh Cong Khai, for his encouragement and willing supports during the thesis writing process I would like to give thanks to Mr Phung Thanh Binh, who had provided sources of data and instructed econometric techniques for my thesis I wish to express my gracefulness to the Vietnam-Netherlands Programme for M.A in Development Economics which provides us chance to access the best conditions for our study I am in debt of all staffs of the Programme for their devoted supports during the time I studied there I am graceful to all professors who devoted their enthusiasm and knowledge on · lectures from which we have benefited greatly What I have learned from these lectures not only help me have basic knowledge for doing this thesis but also provide • me profound understanding on economics particularly and life generally I owe many friends a debt of gratitude for all their encouragement I am graceful to all my classmates for their co-operations during the course Last but not least, I am greatly indebted my family My parents, especially my Mom always encourage me and save all their love to me unconditionally CERTIFICATION I certify that the substance of this thesis has not been submitted for any degree and is not being currently submitted for any other degree This thesis is the result of my own independent work with the guidance of the supervisor, except where otherwise stated Other sources are acknowledged by explicit references LE THUAN BINH June,2011 ABSTRACT The impact of oil price shocks on the macro-economy has received a great deal of attention since the 1970s Many empirical studies found a significant positive effect between oil price shocks and consumer price index (CPI), and this higher CPI will retard GDP A key feature of this paper investigates the relationship between the world oil price and Vietnam's macro-economy based on monthly time series dataset from 2001 Q to 2009Q4 , using the method of multivariate vector autoregression (VAR) The findings show that the world oil price affects the economic growth and inflation of Vietnam significantly The results of the Granger causality test, impulse response functions, and variance decomposition analysis all showed that an increase in oil price will cause positive relationship to consumer price index, and this higher consumer price index causes negative affect on GDP • TABLE OF CONTENTS CHAPTER I: INTRODUCTION 1.1 Problem Statement 1.2 Research Objectives 1.3 Research Questions 1.4 Research Methodology 1.5 Thesis Structure CHAPTER II: LITERATURE REVIEW 2.1 The relationship between oil price and inflation 2.2 The relationship between oil price and industrial production • 2.3 Six oil shocks in history 2.3 Crude oil price in the Middle East in period 1973-1975 2.3.2 Iranian revolution and oil price fluctuation in 1979 2.3.3 The severe fall of oil price in 1980s 2.3.4 Oil price shock in 1990 2.3.5 The downtrend of oil price in 2001 2.3.6 The tremendous oil price shock in 2007-2008 2.4 How higher oil prices affect the global economy 10 2.4.1 Quantifying the impact of oil price in OECD countries 11 2.4.2 Quantifying the impact of oil price in developing countries 13 2.5 Why oil seems to be a matter to the macro-economy 15 2.6 Empirical studies 19 CHAPTER III: RESEARCH METHODOLOGY 3.1 Methodology- Econometric techniques 27 3.1.1 Stationary and Unit-root tests 27 3.1.2 Granger Causality Test 28 3.1.3 Impulse response functions 30 3.1.4 Variance decomposition 31 3.2 Model Specifications 31 3.3 Variable Introduction and Data Description 31 CHAPTER IV: RESEARCH RESULTS 4.1 Unit Root Tests 33 4.2 Granger Causality Tests 36 4.3 Impulse Response Functions ~ 37 4.4 Variance Decomposition 38 CHAPTER IV: CONSLUSION 5.1 Conclusion 39 5.2 Policy Recommendation 40 5.3 Suggestion for Fmiher Study 41 REFERENCES i-v APPENDICES a-1 APPENDIX a APPENDIX d APPENDIX - i APPENDIX j APPENDIX k LIST OF FIGURES Figure 1.1: Relationship between oil price and CPI in Vietnam from 1998-2009 Figure 4.2: The relationships of variables LIST OF TABLES Table 2.4.1: OECD macroeconomic indicators in sustained higher oil price case with oil price assumed to be $10 per barrel higher than in base case Table 2.4.2: Oil-importing developing countries macroeconomic indicators in sustained higher oil price case after one year Table 2.5.1: The coincidence of oil dates and recessions after 1972 Table 2.5.2: Growth in Total Factor Productivity and the Real Price of Oil Imports Table 2.6: Summarization of the impact of oil price on economy Table 4.1.1: Stationary test for variables in level Table 4.1.2: Stationary test for variables ofCPI, IP, OP, and Ms in first difference Table 4.1.3: Stationary test for variable of IP in second difference CHAPTER I: INTRODUCTION 1.1 Problem statement: In most of countries all over the world, oil industry plays critical roles in industrial, economic and social activities The relationship between oil price and levels of economy activities has been the topic for discussion, because the oil price increases are absolutely different from increases in prices of other goods The first reason is that oil price usually increases sharply or keeps sustainable, not typically of other goods and services The second one is that demand for oil is fairly inelasticity; due to oil is the input of almost industries' output The third one is that oil price fluctuations seem to be dependent on the exogenous factors such as revolutions in the Middle East Finally, oil price fluctuations have been affected by abnormal economic change, and the consequences ofhigher price are recession, high unemployment, and inflation Hamilton ( 1983) and Mork ( 1989), who are pioneers, researched the impact of oil price shocks on economic activity They found that GDP is negatively affected by oil price shock and this was used as evidence that oil shocks are related to economic recessions Brown (2004), Schneider (2004), Lardic and Mignon (2006), Sill (2007) found that the supply effect to demand effect and the terms of trade effect is altered variously in terms of the transmission mechanisms of oil shocks to economy On the supply side, a reduction in inputs for production occurs in case of increased oil prices and this leads to higher production costs, and it results a slowdown of productivity and output On the demand side, the oil price increasing puts prices of other goods in higher level, and it makes people more consider with their consumptions; so demand falls On the terms of trade side, the worsening trade conditions have to be faced with fallen demand in oilimporting countries and this result in wealth transfer from oil-importing to oilexporting countries Jimenez-Rodriguez and Sanchez (2005) found that larger impact on gross domestic product (GDP) is caused by an increase in oil price than a fall in oil price in the study on selected OECD countries Their study shows the United Kingdom's GDP is negatively impacted by an increase in oil price in the oil exporting countries, while the oil importing countries except for Japan has the same result A negative relationship between oil price and economic growth is also found in the research of Kim and Willett (2000), who examined the relationship between oil prices and economic growth for various panels of OECD countries The same result also was pointed out by Glasure and Lee (2002) in their study on Korea Therefore, it is important to understand ·impact of oil price on GOP in Vietnam for purpose of stabilizing Vietnamese economic development Last but not least, an increase in oil price seems to lead the higher inflation In fact, there are a lot of empirical evidences attempted to examine the positive relationship between oil price and inflation By applying vector auto-regressions (VARs ), Burbidge and Harrison (1984) estimated the impact of oil prices in Canada, Japan, West Germany, the UK and the USA on consumer price index with data from 1961 to 1982 They found that consumer price index and oil price have positive relationship in Germany and Japan, and larger effect in the UK By using Phillips curve framework, Hooker ( 1999) prove that inflation is affected by oil price changes only through their direct share in a price index, with little or no pass-through into core measures, while oil shocks played decisive role to core inflation before 1980 Blanchard and Gali (2007) used VAR model to similarly found that most rich countries had suffered strong impact by oil price rises over 1970-1983, but very little effect on inflation in West Germany and in Japan With the advent of the policy of reform, Vietnamese economy has taken off since 1986 Vietnam has been able to achieve a consistently high level of GDP on average Hooker, M.A.,(1996) This is what happened to the oil price-macroeconomy relationship Journal ofMonetary Economics 38, pp 215-220 Hooker, M.A.,(l997) Exploring the Robustness of the Oil Price-Macroeconomy relationship Federal Reserve Board Working Paper 1997-56 Huntington, H.G.,(l998).Crude Oil Prices and U.S Economic Performance: Where Does the Asymmetry Reside? The Energy Journal19(4): 107-132 IMF, 1996, World Economic Outlook IMF,1996, Vietnam The Transition to Market Economy Jackson,J.D and Smyth,D.J., (1985) Specifying Differential Cyclical Response in Economic Time Series Economic Modelling (1985), pp 149-161 Jimenez-Rodriguez, R., Sanchez, M., (2005) Oil price shocks and real GDP growth: empirical evidence for some OECD countries Applied Economics 37, 201-228 Katsuya,I., (2008) Oil price and Russian economy: A VEC model approach International Research Journal of Finance and Economics- Issue 17 (2008) Kim, S., Willett, T.D., (2000) Is the negative correlation between inflation and economic growth? An analysis of the effect of the oil supply shocks Applied Economics Letters 7, 141-14 Komain, J.,(2006).The impact of international oil prices on industrial production: The case a/Thailand NIDA Economic Review, Vol.1, No.2 Lardic, S., Mignon, V.,(2006) The impact of oil prices on GDP in European countries: an empirical investigation based on asymmetric co-integration Energy Policy 34, 3910-3915 Lee, K., Ni, S., Raati, R.A., (1995) Oil shocks and the macro-economy: the role of price variability The Energy Journal16, 39-56 Lilien, D., (1982) Sectoral Shifts and Cyclical Unemployment Journal of Political Economy 90 (1982),777-793 iii Limin, D., Yanan, H., Chu, W (2010) The relationship between oil price shocks and China's macro-economy Energy Policy 38 (2010), pp 4142-4151 Loungani, P (1986) Oil price shocks and the dispersion hypothesis Rev Economic Statistics 683, pp 536-539 Mankiw, N Gregory (2002), Macroeconomics (5th ed.) Mohammad, R.F., Gunther,M.,(2007) The effect of oil price shocks on the Iranian economy Energy Economics 31 (2009), pp 134-151 Mork, K.A., (1989).0il shocks and the macro-economy when prices go up and down: an extension ofHamilton's results Journal ofPolitical Economy 97, pp 740-744 Mork, K.A., Olsen, 0., Mysen, H.T., (1994) Macroeconomic responses to oil price increases and decreases in seven OECD countries Energy Journal 15, 19-35 Moses Kiptui (2009) Oil price pass-through into inflation in Kenya Kenya school of monetary studies research centre Working paper Nagy, Eltony M., Al-A wadi, I'vL (2000) Oil price fluctuation and their impact on the macroeconomic variables of Kuwait: a case study using a VAR model International Journal of Energy Research (200 1) Ramon, C.R, Gabriel, P.Q.,(2005) The effect of oil price on industrial production and on stock exchange The paper 05118 Rasche, R.H and Tatom, J.A.,(l981).Energy price shocks, aggregate supply and monetary policy: The theory and International Evidence Carnegie - Rochester Conference Series on Public Policy, 14, pp 125-142 Rotemberg, J.J and Woodford, M., (1996) Imperfect Competition and the Effects of Energy Price Increases on Economic Activity Journal of Money, Credit, and Banking Volume 28, Issue 4, Part Nov., 550-577 Schneider, M., (2004).The impact of oil price changes on growth and inflation Monetary Policy and the Economy Q2/04 Sill, K., (2007).The macroeconomics of oil shocks Business Review Q1 (2007), 21-31 iv Smyth, D.J, (1993) Energy Prices and the Aggregate Production Function Energy Economics 15 (1993), pp 105-110 Taylor, John B Low inflation, pass-through, and the pricing power of firms WB, 1994, Vietnam Financial Sector Review WB, 1994, Vietnam Public Sector Management and Private Sector Incentives WB, 1995, Vietnam An Economic Report on Industrialization and Industrial Policy WB, 1996, Vietnam Fiscal Decentralization and The Delivery ofRural Services Weiqi, T., Libo, W., Zhongxiang, Z (2009) Oil price shocks and their short- and long- term effect on the Chinese economy Energy Economics 32 (2010), S3-S14 v APPENDIX DATASET INo • lndustriaiJUOduction Mouth 17345.8 2001 M1 I 2001 M2 35670.4 54253 2001 M3 73514.9 2001 M4 2001 M5 93099.7 113337 2001 M6 ' 133646 2001 M7 2001 M8 154368 175288 2001 M9 188000 10 2001 M1 C 11 2001 M11 207984 228182 12 2001 M1 21126 13 2002M1 38890 14 2002M2 60733 15 2002M3 16 2002M4 82739 105059 17 2002M5 125958 18 2002M6 149217 19 2002M7 20 2002MB 172855 "1 96562 21 2002M9 2002M1 C 218390 22 238744 23 2002M·11 24 2002M1L 260202 25 2003M1 25673 26 2003M2 48117 27 2003M3 71941 ! 28 2003M4 97443 29 2003M5 122604 30 2003M6 "148340 31 2003M7 17 4633 32 2003MB 199497 33 2003M9 227117 34 2003M1 255070 35 2003M11 274472 2003M1 ') 36 302990 CPI OiiJ>rice 80.429 25.45 80.765 27.51 80.161 24.57 79.759 25.65 79.624 28.32 79.624 27.75 79.49 24.53 79.49 25.75 79.893 25.22 79.759 20.56 79.96 18.85 80.631 18.67 81.523 19.46 83.35 20.12 82.64 23.54 82.64 25.6 82.944 25.39 83.046 24.09 82.944 25.69 83.046 26.56 83.147 28.33 83.452 27.5 83.655 24.23 83.959 28.23 84.67 31.29 86.498 32.72 85.99 30.46 85.99 24.89 85.888 25.68 85.685 27.52 85.381 28.4 85.381 29.71 85.381 26.85 85.279 29.62 85.787 28.69 86.498 29.76 a Money SliJ>I>Iy 232150.733 233986.945 238454.168 239794.083 242234.804 248973.283 254368.224 260770.094 263372.633 269137.656 275040.441 279780.711 287493.505 288557.354 289863.937 295490.683 300838.516 302679.39 307797.147 311432.82 314973.446 321402.974 324809.572 329149.785 346011.655 345353."1 08 34571"1.127 349865.988 356566.447 368462.829 371 008.494 374118.829 382188.972 387901."19 39421 9.484 411232.9~:2 Interest Rate 10.65 10.8 10.5 9.45 9.6 9 9 8.52 8.52 8.55 8.5 8.5 8.46 8.46 9.33 9.54 9.48 9.48 9.48 9.48 9.48 9.48 9.3 9.46 9.42 9.46 9.46 9.53 9.53 9.57 9.47 9.54 9.54 No 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 I 58 l 59 60 I 61 62 63 : 64 I 65 ! 66 I 67 68 69 70 71 72 ' lndustriall>roduc.1ion Month 2004M1 27281 55548 2004M2 85018 2004M3 113970 2004M4 144917 2004M5 176623 2004M6 208138 2004M7 240501 2004MB 264554 2004M9 293850 2004M1C 2004M11 321888 2004M1:; 354030 2005M1 36153 2005M2 64989 01195 2005M3 2005M4 138585 2005M5 166188 285695 2005M6 2005M7 245103 267826 2005MB 2005M9 308665 329611 2005M1 C 2005M·11 373890 2005M1 416863 2006M1 40952 2006M2 77277 '1'19689 2006M3 2006M4 162662 2006M5 198991 2006M6 241794 2006M7 284381 2006MB 318843 2006M9 365064 2006M1C 396784 2006M11 441432 2006M12 491967 CPI Oil!>rice 87 4"11 31.3 90.051 30.86 90.761 33.46 91.168 33.15 37.99 91.98 92.792 35.24 93.198 38.24 93.807 43.16 94.0'1 43.33 94.01 49.67 94.213 43.'17 94.822 37.24 95.838 44.36 98.27 45.22 98.376 53.1 98.985 52.'1 99.391 5'1.07 99.797 54.84 100.2 57.57 100.61 64:14 101.42 62.B5 101.B3 58.75 102.23 55.3:3 103.05 57.03 104.26 63.18 '1 06.5 60.19 105.99 62.12 106.19 70.12 106.8 69.75 107.21 68.56 '1 07.61 73.77 108.02 73.35 1OB.33 61.66 1OB.63 57.7 109.24 5~i.36 109.85 63.11 b Money Slii>J>Iy 428525.28 426'153.726 437 412.97 443077.338 450807 07 458866.539 469086.485 479715.898 4847 49.528 496785.12 5111 05.338 532345.9'13 537762.372 54517 4.609 553872.785 564104.844 570253.424 581505.708 5B4B46.577 602024.25B 614945.709 627321.48'1 644215.73'1 (i90652.292 717B20.298 717066.346 73956'1.694 757699.305 77097 4.513 782B71.3 792434.977 B18542.862 B24294.177 844595.281 B68772.915 922672.414 Interest Rate 9.54 9.54 9.54 9.54 9.54 9.54 9.54 9.63 9.87 '1 0.01 '1 0.1 10.25 '1 0.25 11 '11 '1 0.8 10.8 11.03 11.03 1'1.03 11.18 11.18 11.4 11.4 1'1.18 11.1'8 '1 '1.'1 B 11.18 11.18 11.18 '11.18 1'1.1B 1'1.18 1'1.18 11.18 11.18 No 7:3 74 75 76 77 78 79 80 8'1 82 83 • Month lndustriall>roduction 2007M1 49212 2007M2 84604 2007M3 129758 1771 02.6 2007M4 2007M5 225056 2007M6 275121 2007M7 325377 368375 2007MB 417959 2007M9 467723 2007M1 2007M11 5'18880 I 84 2007M1 L 574829 85 2008M1 52874 86 2008M2 106383 87 2008M3 160555 2'15544 88 2008M4 89 2008M5 270814 90 2008M6 326641 I 91 2008M7 382346 438115 i 92 2008MB 93 2008M9 493196 54 7212 94 2008M10 95 2008M11 601253 ' 96 2008M12 652766 47855 97 2009M1 '1 06067 98 2009M2 I 99 2009M3 152947 208991 100 2009M4 265639 101 2009M5 32424£1 102 200BM6 '1 03 200BM7 382661 443042 104 2009MB 505972 105 2009M9 568960 106 2009M1C 63'1871 107 2009M11 [196577 '108 2009M1 L CPI 11 0.96 113.4 113.1 113.71 114.52 115.53 116.65 117.26 117.87 118.78 120.2 123.66 126.6 131.17 135.03 138.07 '143.45 146.5 148:12 150.46 150.76 150.46 149.34 148.33 151.14 151.4 151.24 150.78 151.45 152.27 153.07 153.43 154.39 154.95 155.81 157.96 - Oil Juice 53.68 57.78 62.09 67.48 67.6 7'1 76.68 70.8 77.02 82.7 93.34 92.11 93.66 96.81 105.1 109.95 123.24 134.05 133.B 115.08 99:16 71.4 49.75 40.3'1 43.64 43.39 46.8 50.22 57.55 68.68 64.f36 72.61 67.32 72.9 76.72 74.32 c Money supply 955584.117 988083.313 1030816.227 '1 062452.992 '1 089672.987 11'17217 911 1'1461 98.161 1159943.21 1'198195.013 '1243332.838 1274'195.033 1348243.67 1389089.735 '1376442.55 1398303.415 1381549.513 1398846.229 1404596.523 '1413228.953 1413695.791 1459808.648 14 77680.853 '1505517.627 1622129.759 1669467.676 1693324.022 '1747126.125 1800707.433 1858150 1904976.454 1950124.396 19600'1 9.388 1973969.704 200£18'18.771 2029916.£159 2045547.32 Interest Rate 11.18 11.18 1'1.18 '11.18 11.18 11.18 11.18 11.18 '11.18 11.18 1'1.18 11.'18 11.18 11.18 14.6 14.27 '16.53 Hl.1'1 20.25 20.19 19.86 18 13.26 10.98 10.08 9.39 9.15 9.15 9.6 9.96 9.96 10.26 10.35 10.46 10.46 r· APPENDIX2 UNIT ROOT TEST Null Hypothesis: I has a unit root Exogenous: Constant Lag Length: (Automatic based on SIC, MAXLAG=12) Augmented Dickey-Fuller test statistic 1% level Test critical values: 5% level 10% level t-Statistic Prob * -3.605639 -3.493747 -2.889200 -2.581596 0.0072 *MacKinnon ( 1996) one-sided p-values Augmented Dickey-Fuller Test Equation Dependent Variable: D(l) Method: Least Squares Date: 03/15/11 Time: 21: 12 Sample (adjusted): 2001M04 2009M12 Included observations: 105 after adjustments Variable Coefficient Std Error t-Statistic Prob 1(-1) D(l(-1)) D(l(-2)) -0.104064 0.428086 0.237752 1.135542 0.028862 0.094990 0.099132 0.316931 -3.605639 4.506651 2.398335 3.582925 0.0005 0.0000 0.0183 0.0005 c R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.333657 0.313865 0.649517 42.60906 -101.6391 16.85787 0.000000 Mean dependent var S.D dependentvar Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat d 0.014286 0.784125 2.012174 2.113277 2.053143 1.993797 • Null Hypothesis: D(CPI) has a unit root Exogenous: Constant Lag Length: (Automatic based on SIC, MAXLAG=12) Augmented Dicke~-Fuller test statistic Test critical values: 1% level 5% level 10% level t-Statistic Prob.* -5.104361 -3.493129 -2.888932 -2.581453 0.0000 *MacKinnon (1996) one-sided p-values Augmented Dickey-Fuller Test Equation Dependent Variable: D(CPI,2) Method: Least Squares Date: 03/15/11 Time: 21:13 Sample (adjusted}: 2001M03 2009M12 Included observations: 106 after adjustments Variable Coefficient Std Error t-Statistic Pro b D(CPI(-1)) -0.408004 0.307273 0.079932 0.104472 -5.104361 2.941194 0.0000 0.0040 c -:' R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.200335 0.192646 0.902475 84.70391 -138.5208 26.05450 0.000002 Mean dependent var S.D dependentvar Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat e 0.017138 1.004392 2.651336 2.701589 2.671704 2.190067 • Null Hypothesis: D(MS) has a unit root Exogenous: Constant Lag Length: (Automatic based on SIC, MAXLAG=12) Augmented Dickev-Fuller test statistic 1% level Test critical values: 5% level 10% level t-Statistic Prob.* -2.742429 -3.494378 -2.889474 -2.581741 0.0704 *MacKinnon (1996) one-sided p-values Augmented Dickey-Fuller Test Equation Dependent Variable: D(MS,2) Method: Least Squares Date: 03/15/11 Time: 21:14 Sample (adjusted): 2001M05 2009M12 Included observations: 104 after adjustments Variable Coefficient Std Error t-Statistic Pro b D(MS(-1)) D(MS(-1 ),2) D(MS(-2),2) -0.271983 -0.398866 -0.335670 4992.203 0.099176 0.107934 0.094381 2268.906 -2.742429 -3.695458 -3.556549 2.200268 0.0072 0.0004 0.0006 0.0301 c ~ R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.363162 0.344057 15465.68 2.39E+10 -1148.754 19.00858 0.000000 Mean dependent var S.D dependentvar Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat f 137.4081 19095.71 22.16834 22.27004 22.20954 1.968332 t ~ Null Hypothesis: D(OP) has a unit root Exogenous: Constant Lag Length: (Automatic based on SIC, MAXLAG=12) Augmented Dicke:t-Fuller test statistic Test critical values: 1% level 5% level 10% level t-Statistic Prob.* -6.295805 -3.493129 -2.888932 -2.581453 0.0000 *MacKinnon (1996) one-sided p-values Augmented Dickey-Fuller Test Equation Dependent Variable: D(OP,2) Method: Least Squares Date: 03/15/11 Time: 21:16 Sample (adjusted): 2001M03 2009M12 Included observations: 106 after adjustments Variable Coefficient Std Error t-Statistic Pro b D(OP(-1)) -0.552616 0.225238 0.087775 0.540296 -6.295805 0.416878 0.0000 0.6776 c ~ R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.275953 0.268991 5.545483 3198.248 -330.9742 39.63716 0.000000 Mean dependent var S.D dependent var Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat • g -0.042080 6.486018 6.282532 6.332786 6.302900 2.051404 i ' Null Hypothesis: D(IP,2) has a unit root Exogenous: Constant Lag Length: 10 (Automatic based on SIC, MAXLAG=12) Augmented Dicke~-Fuller test statistic 1% level Test critical values: 5% level 10% level t-Statistic Prob.* -227.6262 -3.500669 -2.892200 -2.583192 0.0001 *MacKinnon (1996) one-sided p-values Augmented Dickey-Fuller Test Equation Dependent Variable: D(IP,3) Method: Least Squares Date: 03/15/11 Time: 21:20 Sample (adjusted): 2002M02 2009M12 Included observations: 95 after adjustments - Variable Coefficient Std Error t-Statistic Pro b D(IP(-1),2) D(IP(-1),3) D(IP(-2),3) D(IP(-3),3) D(IP(-4),3) D(IP(-5),3) D(IP(-6),3) D(IP(-7),3) D(IP(-8),3) D(IP(-9),3) D(IP(-10),3) -12.84979 10.83386 9.809921 8.774726 7.726456 6.666595 5.594933 4.507145 3.405422 2.284823 1.149370 -285.0006 0.056451 0.054509 0.051126 0.046650 0.041379 0.035544 0.029373 0.023028 0.016720 0.010646 0.005096 574.6675 -227.6262 198.7519 191.8772 188.0989 186.7260 187.5602 190.4775 195.7274 203.6693 214.6224 225.5575 -0.495940 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.6212 c R-squared Adjusted R-squared S.E of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.999712 0.999674 5593.260 2.60E+09 -948.1701 26172.08 0.000000 Mean dependent var S.D dependentvar Akaike info criterion Schwarz criterion Hannan-Quinn criter Durbin-Watson stat h 2411.042 309584.5 20.21411 20.53670 20.34446 2.317947 • ' APPENDIX3 GRANGER CAUSALITY TEST VAR Granger Causality/Block Exogeneity Wald Tests Date: 03/15/11 Time: 21:22 Sample: 2001M01 2009M12 Included observations: 106 Dependent variable: IP Excluded Chi-sq df Pro b CPI OP 8.929773 2.698428 2 0.0115 0.2594 All 11.25377 0.0239 Dependent variable: CPI .; Excluded Chi-sq df Pro b IP OP 29.91658 7.458926 2 0.0000 0.0240 All 34.04913 0.0000 Dependent variable: OP Excluded Chi-sq df Pro b IP CPI 5.462263 17.06214 2 0.0651 0.0002 All 22.60418 0.0002 i APPENDIX4 IMPULSE RESPOSE FUNCTIONS Response to Cholesky One S.D Innovations± S.E 100,