Figure S1. Log (rig activity) and log(real oil price). US
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1 Figure S1. Log (rig activity) and log(real oil price). US log (rig activity) log (real oilprice)
2 Figure S. Log (rig activity) and log(real oil price). Canada 5 log (rig activity) log (real oilprice)
3 Figure S3. Log (rig activity) and log(real oil price). Europe 4 log (rig activity) log (real oilprice)
4 Figure S4. Log (rig activity) and log(real oil price). Latin America 5 4 log (real activity) log (real oilprice)
5 Figure S5. Log (rig activity) and log(real oil price). Latin America without OPEC 5 log (rig activity) log (real oilprice)
6 Figure S6. Log (rig activity) and log(real oil price). Asia Pacific 5 log (rig activity) log (real oilprice)
7 Figure S7. Log (rig activity) and log(real oil price). Middle East without OPEC log (rig activity) log (real oilprice)
8 Figure S8. Log (rig activity) and log(real oil price). Africa 4 log (rig activity) log (real oilprice)
9 Figure S9. Log (rig activity) and log(real oil price). Africa without OPEC 3 log (rig activity) log (real oilprice)
10 Selected references related to the econometric part of the paper Bowman, K.O., Shenton, L.R., Omnibus test contours for departures from normality based on b 1 and b. Biometrika 6, Dezhbakhsh, H., The inappropriate use of serial correlation tests in dynamic linear models. Review of Economics and Statistics 7, Doornik, J.A., Hansen, H., An omnibus test of univariate and multivariate normality. Discussion paper. Nuffield College, Oxford. Harvey, A.C., Henry, S.G.B., Peters, S., Wren-Lewis, S., Stochastic trends in dynamic regression models: an application to the employment-output equation. Economic Journal 96, Harvey, A.C., Forecasting, structural time series models and the Kalman filter. Cambridge University Press, Cambridge. Hunt, L.C., Ninomiya, Y., 003. Unravelling trends and seasonality: a structural time series analysis of transport oil demand in the UK and Japan. Energy Journal 4 (3), Koopman, S.J., Harvey, A.C., Doornik, J.A., Shephard, N., Stamp: structural time series analyser, modeller and predictor. Timberlake Consultants Ltd., London. 10
11 Modeling framework ()B(L)yt = C(L)xt + kmt +µ t + s t +ε t, i (3)B(L) 1 b L p = i1 = q i (4)C(L) = cil. i= 0 (5) µ t = µ t 1+ β t 1+η t (6) β t = β t 1+ν t i 11 (7) s j= 0 t j = ξ t ( ) / (8) εt, ηt, νt, ξt ~ NIID(0,diag σεε, σηη, σνν, σ ξξ ) t. 11
12 j1 {j} (9) x t = (1/ j) x i= 0 t i (10) B(L)y = D(L)x + km +µ + s +ε, {j} t t t t t t r i (11) D(L) = d il, i= 0 1
13 State space form (1) B(L)y = D(L)x + km + Az +ε, {j} t t t t t (13) z t = Vz t 1+ς t, [ ] / z = µ, β, s, s, s t t t t t 1 t (14) V = , 13
14 ˆ (15)AIC= log( σ ) + (/T)(nk + nh + n z) ˆ (16)BIC = log( σ ) + (log(t)/ T)(n k + nh + n z), 14
15 The regions, for which we consider econometric modeling, consist of the following countries (an asterisk* refers to OPEC countries): United States Canada Europe: Denmark, France, Germany, Netherlands, Hungary, Italy, Norway, Poland, Romania, Turkey, United Kingdom, Yugoslavia, "others". Non-OPEC Middle East: Egypt, Oman, Pakistan, Sudan, Syria, Yemen, "others". Latin America: Argentina, Bolivia, Brazil, Chile, Colombia, Ecuador, Mexico, Peru, Trinidad, Venezuela*. Africa: Algeria*, Angola, Congo, Gabon*, Libya*, Nigeria*, South Africa, Tunisia, "others". Asia Pacific: Australia, Brunei, India, Indonesia*, Japan, Malaysia, Myanmar, New Zealand, Offshore China, Papua New Guinea, Philippines, Taiwan, Thailand, Vietnam, "others". 15
16 Oil prices used for different regions: United States: Canada: Europe: Latin America: "United States West Texas Intermediate" "United States West Texas Intermediate" "Brent Blend" "United States West Texas Intermediate" Latin America without OPEC: "United States West Texas Intermediate" Asia Pacific: Middle-East without OPEC: Africa: Africa without OPEC: "Dubai" "Dubai" "Nigeria" "Nigeria" 16
17 Table A1. Ranking of simplified versions of models M 3, M 6, M 1 and M 4 according to Akaike's information (AIC) and the Bayesian information criterion (BIC) ab Region: Inform. M 3 M 6 M 1 M 4 criterion US AIC BIC Canada AIC 1 3 BIC 1 3 Europe AIC BIC Latin America AIC BIC Latin America without OPEC AIC BIC Asia Pacific AIC 1 BIC 1 Middle East without OPEC AIC BIC Africa AIC BIC Africa without OPEC AIC BIC a Lowest number indicates best model. 17
18 Table 1. Characteristic features of the preferred model for the different regions Region Smoothing over number of months Trend specification: restrictions Specification of seasonality: restrictions Dummy variable US 1 β t = 0 t σ ξξ = 0 DI00.1 Canada 3 σ νν = 0 None None Europe 6 β t = 0 t s t = 0 t DI99.10 Latin America 3 µ t = µ t s t = 0 t DI0.4 Latin America 1 β t = 0 t s t = 0 t None without OPEC Asia Pacific 4 β t = 0 t s t = 0 t None Middle East 4 β t = 0 t s t = 0 t DS06.1 without OPEC Africa 4 β t = 0 t s t = 0 t DS0. Africa without 1 β t = 0 t σ ξξ = 0 None OPEC 18
19 List of dummy variables: USA: D00.1 Impulse dummy: Insecurity surrounding the new millennium Europe: D99.10 Impulse dummy: No substantial interpretation Latin America: D0.4 Impulse dummy: Coup d'état against president Hugo Chavez Middle East without OPEC: DS06.1 Step dummy related to the civil war in Sudan Africa: DS0.. Redefinition of variables related to Algeria and Libya 19
20 Table. Overview of different diagnostics and fit measures Statistic/ Fit Explanation Distribution meas. NORM-DH The Doornik and Hansen (1994) adjusted version of the Bowman-Shenton (1975) test statistic for normality. HET A test statistic for heteroskedasticity, cf. Koopman et al. (000, p. 183) BJ-Q The Box-Ljung Q- statistic of residual autocorrelation, cf. Koopman et al. (000, p. 18) χ -distributed with degrees of freedom F-distributed with h degrees of freedom in both the numerator and denominator, where h corresponds to about one third of the standardized one-stepahead prediction errors χ -distributed with P-n h +1 degrees of freedom, where P denotes the number of autocorrelations and n h the number of estimated hyperparameters (variances) 0
21 Table (continued) NORM-BS- The Bowman-Shenton IRR (1975) statistic for normality of the auxiliary residuals related to the genuine NORM-DH- IRR NORM-BS- LEV NORM-BS- LEV error term The Doornik-Hansen (1994) statistic for normality of the auxiliary residuals related to the genuine error. The Bowman-Shenton (1975) statistic for normality of the auxiliary residuals related to the innovations in the stochastic trend component The Doornik-Hansen (1994) statistic for normality of the auxiliary residuals related to the innovations in the stochastic trend component χ -distributed with degrees of freedom χ -distributed with degrees of freedom χ -distributed with degrees of freedom χ -distributed with degrees of freedom 1
22 Table (continued). R Coefficent of determination, cf. Koopman et al. (000, p. 179) R D R S Coefficent of determination, taking into account trend movement in the modeled variable, cf. Koopman et al. (000, p. 179) Coefficent of determination, taking into account trend movement and seasonal fluctuations in the modeled variable, cf. Koopman et al. (000, p. 180)
23 Table 3. Econometric results for oilrig activity in US a Variable Estimate t-value Variance ratio, diagnostics and fit Diagnostics related to auxiliary residuals y t ση / σ NORM ε BS-IRR y t Std. error NORM- DH-IRR {1} p NORM t DH DI HET b NORM BS-IRR BJ-Q c Long-run elasticity 1.70 R s NORM- DH-IRR a Cf. Table 1 for an explanation of diagnostic tests and fit measures. Estimates of fixed seasonal effects are not reported. Estimation sample 1987M10-006M5. b The number of degrees of freedom is 74 both for the numerator and the denominator. c The number of degrees of freedom is 1. 3
24 Figure R1. Residuals. US 3 US
25 Figure TR1. Extracted stochastic trend. US 5.4 US
26 Table 4. Econometric results for oilrig activity in Canada a Variable Estimate t-value Variance ratios, diagnostics and fit Diagnostics related to auxiliary residuals {3} pt Longrun elasticity σε / σ NORMη BS-IRR σ / σ NORM- ξ η Std. error NORM-DH HET b BJ-Q c R s DH-IRR NORM- BS-IRR NORM- DH-IRR a Cf. Table 1 for an explanation of diagnostic tests and fit measures. Estimate of linear deterministic trend is not reported. Estimation sample 1998M3-006M5. b The number of degrees of freedom is 8 both for the numerator and the denominator. c The number of degrees of freedom is 6. 6
27 Figure R. Residuals. Canada Canada
28 Figure TR. Extracted stochastic trend. Canada Canada
29 Figure Seas1. Extracted seasonal component. Canada Canada
30 Table 5. Econometric results for oilrig activity in Europe a Variable Estimate t-value Variance ratio, diagnostics and fit Diagnostics related to auxiliary residuals y t ση / σ NORM ε BS-IRR (pvalue) y t Std. error NORM- DH- IRR (pvalue) {6} pt NORM-DH DI99.10 Longrun elasticity HET b BJ-Q c R NORM- BS-IRR (pvalue) NORM- DH- IRR (pvalue) a Cf. Table 1 for an explanation of diagnostic tests and fit measures. Estimation sample 1995M3-006M5. b The number of degrees of freedom is 44 both for the numerator and the denominator. c The number of degrees of freedom is 9. 30
31 Figure R3. Residuals. Europe Europe
32 Figure TR3. Extracted stochastic trend. Europe 1.5 Europe
33 Table 6. Econometric results for oilrig activity in Latin America a Variable Estimate t-value Variance ratio, diagnostics and fit y t Std. error NORM- BS-IRR {3} pt {3} pt DI0.4 Longrun elasticity NORM-DH HETb BJ-Q c R d Diagnostics related to auxiliary residuals NORM- DH-IRR a Cf. Table 1 for an explanation of diagnostic tests and fit measures. Effect of linear deterministic trend is not reported. Estimation sample 1995M-006M5. b The number of degrees of freedom is 44 both for the numerator and the denominator. c The number of degrees of freedom is
34 Figure R4. Residuals. Latin America.5.0 Residual LRIGA4 Latin America
35 Table 7. Econometric results for oilrig activity in Latin America without OPEC a Variable Estimate t-value Variance ratio, diagnostics and fit Diagnostics related to auxiliary residuals {1} pt σε / σ NORM η BS-IRR Std. error NORM DH-IRR NORM-DH HET b BJ-Q c NORM- BS-IRR NORM- DH-IRR Long-run R elasticity a Cf. Table 1 for an explanation of diagnostic tests and fit measures. Estimation sample 1995M1-006M5. b The number of degrees of freedom is 45 both for the numerator and the denominator. c The number of degrees of freedom is 9. 35
36 Figure R5. Residuals. Latin America without OPEC 3 Latin America without OPEC
37 Figure TR4. Extracted stochastic trend. Latin America without OPEC Latin America without OPEC
38 Table 8. Econometric results for oilrig activity in Asia Pacific a Variable Estimate t-value Variance ratio, diagnostics and fit Diagnostics related to auxiliary residuals y t ση / σ NORM ε BS-IRR {4} pt Std. error NORM DH-IRR NORM-DH HET b BJ-Q c NORM- BS-IRR NORM- DH-IRR Long-run R elasticity a Cf. Table 1 for an explanation of diagnostic tests and fit measures. Estimation sample 1995M-006M5. b The number of degrees of freedom is 45 both for the numerator and the denominator. c The number of degrees of freedom is 9. 38
39 Figure R6. Residuals. Asia Pacific Asia Pacific
40 Figure TR5. Extracted stochastic trend. Asia Pacific Asia Pacific
41 Table 9. Econometric results for oilrig activity in Middle East without OPEC a Variable Estimate t-value Variance ratio, diagnostics and fit {4} p t σε / σ NORMη BS-IRR DS Std. error NORM- DH-IRR NORM- DH HET b BJ-Q c NORM- BS-IRR NORM- DH-IRR Diagnostics related to auxiliary residuals Long-run R elasticity a Cf. Table 1 for an explanation of diagnostic tests and fit measures. Estimation sample 1995M1-006M5. b The number of degrees of freedom is 45 both for the numerator and the denominator. c The number of degrees of freedom is 9. 41
42 Figure R7. Residuals. Middle East without OPEC 3 Middle East without OPEC
43 Figure TR6. Extracted stochastic trend. Middle East without OPEC 5.60 Middle east without OPEC
44 Table 10. Econometric results for oilrig activity in Africa a Variable Estimate t-value Variance ratio, diagnostics and fit Diagnostics related to auxiliary residuals {4} p t ση / σ NORM ε BS-IRR DS Std. error NORM DH-IRR NORM- DH HET b BJ-Q c NORM- BS-IRR NORM- DH-IRR Long-run R elasticity a Cf. Table 1 for an explanation of diagnostic tests and fit measures. Estimation sample 1995M1-006M5. b The number of degrees of freedom is 45 both for the numerator and the denominator. c The number of degrees of freedom is 9. 44
45 Figure R8. Residuals. Africa 3 Africa
46 Figure TR7. Extracted stochastic trend. Africa Africa
47 Table 11. Econometric results for oilrig activity in Africa without OPEC a Variable Estimate t-value Variance ratio and diagnostics Diagnostics related to auxiliary residuals y t ση / σ NORM ε BS-IRR {1} pt Std. error NORM- DH-IRR NORM- DH HET b BJ-Q c NORM- BS-IRR NORM- DH-IRR Long-run R elasticity s a Cf. Table 1 for an explanation of diagnostic tests and fit measures. Fixed seasonal effects are not reported. Estimation sample 1995M-006M5. b The number of degrees of freedom is 45 both for the numerator and the denominator. c The number of degrees of freedom is 9. 47
48 Figure R9. Residuals. Africa without OPEC Africa without OPEC
49 Figure TR8. Extracted stochastic trend. Africa without OPEC.6.5 Africa without OPEC
50 Table 1. Estimated long-run elasticities for different regions Region: Long-run elasticity US 1.70 Canada Europe Latin America 1.5 Latin America without OPEC 0.80 Asia Pacific Middle East without OPEC 0.60 Africa Africa without OPEC
51 Figure 3. Price elasticities for oilrig activity over different periods of time after a sustained price increase for US, Canada, Europe, Latin America and Latin America without OPEC US Europe Latin America without OPEC CAN Latin America
52 Figure 4. Price elasticities for oilrig activity over different periods of time after a sustained price increase for Asia Pacific, Middle East without OPEC, Africa, Africa without OPEC Asia Pacific Africa Middle East without OPEC Africa without OPEC
53 Further work Multivariate model with a set of regions. For instance common latent variables representing technology. Formal inference on variance of latent components. Recursive analysis (for US). Stochastic slope parameters (STAMP 7). Forecasting. 53
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