RICE UNIVERSITY National Oil Company Efficiency: Theory and Evidence Stacy Eller Peter Hartley Kenneth B Medlock III James A. Baker III Institute for Public Policy RICE UNIVERSITY 1 RICE UNIVERSITY Theoretical Model 2 Economic model precepts RICE UNIVERSITY n Intertemporal, optimizing model of a National Oil Company (NOC) n Contrast a NOC to a shareholder­owned firm n Capture systematic effects from the NOC institutional arrangement n Weaker monitoring of a NOC and differing political goals imply that in addition to commercial returns NOC management choices will reflect: u Increased employment in the firm of labor or other domestic inputs u Domestic consumer surplus from oil product sales u Pressure to increase current relative to future revenue – a high discount rate n Without these concerns, the NOC optimization problem approaches that of a private monopoly firm n In the efficient case: u Domestic oil consumers are neither taxed nor subsidized relative to other constituents, and u Domestic consumer surplus is weighed identically to NOC profits 3 NOC versus efficient case: output, inputs, cash flow RICE n Output shifted forward, lower reserves & cash flow, higher employment UNIVERSITY Output Reserves 0.40 1.20 NOC output NOC reserves 0.35 Efficient output Efficient reserves 1.00 0.30 0.80 0.25 0.20 0.60 0.15 0.40 0.10 0.20 0.05 0.00 0.00 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Years Years Employment Cash Flow 4.00 0.25 NOC employment NOC cash flow 3.50 0.20 Efficient cash Efficient employment flow 3.00 0.15 2.50 0.10 2.00 0.05 1.50 0.00 1.00 ­0.05 0.50 ­0.10 0.00 ­0.15 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Years Years 4 Effect of excess emphasis on current revenue RICE n Output & cash flow shifted forward, reduced investment in reserves, UNIVERSITY increased employment except in the long term Change in output Change in reserves 0.025 0.01 0.020 0.00 v = 0.05 r v = 0.05 0.015 r v = 0.1 ­0.01 r v = 0.1 0.010 r ­0.02 0.005 ­0.03 0.000 ­0.04 ­0.005 ­0.05 ­0.010 ­0.015 ­0.06 ­0.020 ­0.07 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Years Years Change in employment Change in cash flow 0.7 0.010 0.6 v = 0.05 0.005 r v = 0.05 r v = 0.1 0.5 r v = 0.1 r 0.000 0.4 0.3 ­0.005 0.2 ­0.010 0.1 ­0.015 0.0 ­0.1 ­0.020 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Years Years 5 Effect of increasing the employment incentive RICE n Output & cash flow shifted forward, reduced investment in reserves, UNIVERSITY increased employment except in the long term Change in output Change in reserves 0.012 0.005 v = 0.1w 0.010 0.000 L 0.008 ­0.005 vL = 0.2w 0.006 ­0.010 0.004 v = 0.1w ­0.015 L 0.002 v = 0.2w ­0.020 L 0.000 ­0.025 ­0.002 ­0.030 ­0.004 ­0.035 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Years Years Change in employment Change in cash flow 0.35 0.006 0.30 0.004 v = 0.1w v = 0.1w 0.25 L L v = 0.2w vL = 0.2w 0.002 L 0.20 0.15 0.000 0.10 ­0.002 0.05 ­0.004 0.00 ­0.05 ­0.006 0 5 10 15 20 25 30 0 5 10 15 20 25 30 6 Years Years NOC versus efficient domestic consumption RICE UNIVERSITY n The subsidy raises domestic consumption for the NOC n Increasing the domestic subsidy also shifts employment forward relative to the efficient case, but the effects are small 0.0112 Change in employment 0.0006 0.0111 v = 1.025 0.0004 c 0.0110 v = 1.05 0.0002 c 0.0109 0.0108 NOC domestic demand 0.0000 0.0107 Efficient domestic demand ­0.0002 0.0106 ­0.0004 0.0105 ­0.0006 0.0104 ­0.0008 0.0103 0 5 10 15 20 25 30 0 5 10 15 20 25 30 Years Years 7 RICE UNIVERSITY Empirical Analysis 8 Data and methods RICE UNIVERSITY n Sample of 80 firms over 2002­2004 (Energy Intelligence “Ranking the World’s Oil Companies”) with data on: u revenue, u reserves of natural gas and crude oil, u employment, u production of natural gas and crude oil and crude oil products, and u the government ownership share n Used both non­parametric Data Envelopment Analysis (DEA) and a parametric Stochastic Frontier Approach (SFA) n Motivated by the theoretical model we use revenue as the output measure u Political pressure is likely to force a NOC to subsidize domestic consumers u To the extent that NOC’s generate less revenue for given inputs we can conclude that their objectives differ from a private firm n Also in accordance with the theoretical model, we allow for three inputs: employees, oil reserves and natural gas reserves 9 Firms in the sample (statistics for 2004) RICE Revenue Revenue Revenue Revenue per per Gov ernment per per Gov e rnment UNIVERSITY Compan y Emp lo yee Reserves Ownership Country Compan y Emplo yee Reserves Owne rship Country $/employee $/boe % $/employee $/boe % NOCs Others Adnoc 205 0.20 100% UAE Amerada Hess 1,532 16.07 0% US CNOOC 2,656 2.97 71% China Anadarko 1,838 2.52 0% US EcoPetrol 824 2.26 100% Colombia Apache 2,019 2.71 0% US Eni 1,056 10.50 30% Italy BG 1,547 3.64 0% UK Gazprom 103 0.16 51% Russia Burlington 2,537 2.74 0% US INA 187 11.70 75% Croatia Chesapeake Energy 1,577 3.22 0% US KMG n/a n/a 100% Kazakhastan CNR 4,606 3.85 0% Canada KPC 1,650 0.34 100% Kuwait Devon 2,356 4.33 0% US MOL 635 42.37 25% Hungary Dominion 847 13.81 0% US NIOC 283 0.11 100% Iran EnCana 2,915 4.48 0% Canada NNPC 1,460 0.56 100% Nigeria EOG 1,844 2.38 0% US NorskHydro 673 11.37 44% Norway ForestOil 1,841 4.02 0% US OMV 2,214 8.90 32% Austria HuskyEnergy 2,149 9.53 0% Canada ONGC 298 2.11 84% India Imperial 2,838 35.72 0% Canada PDO 1,591 0.98 60% Oman Kerr­McGee 1,263 4.15 0% US PDVSA 1,985 0.66 100% Venezuela Lukoil 233 1.68 0% Russia Pemex 506 4.01 100% Mexico Maersk 60 2.90 0% Denmark Pertamina 453 0.73 100% Indonesia Marathon 1,757 39.14 0% US Petrobras 773 3.39 32% Brazil Murphy 1,436 21.60 0% US PetroChina 111 2.52 90% China Newfield 2,114 4.45 0% US Petroecuador 1,026 1.25 100% Ecuador Nexen 1,048 4.25 0% Canada Petronas 1,202 1.45 100% Malaysia NipponOil 2,690 131.74 0% Japan PTT 2,896 16.68 100% Thailand Noble 2,433 2.54 0% US QP 1,800 0.10 100% Qatar Novatek 220 0.21 0% Russia Rosneft 86 0.19 100% Russia Occidental 1,577 4.46 0% US SaudiAramco 2,261 0.40 100% Saudi Arabia PennWest 1,577 2.53 0% Canada Sinopec 192 19.76 57% China Petro­Canada 2,370 9.24 0% Canada Socar n/a n/a 100% Azerbaijan PetroKazakhstan 546 4.12 0% Kazakhstan Sonangol 755 1.37 100% Angola Pioneer 1,183 1.76 0% US Sonatrach 688 0.93 100% Algeria Pogo 5,088 4.38 0% US SPC 375 1.71 100% Syriac RepsolYPF 1,561 10.79 0% Spain Statoil 1,910 10.85 71% Norway Santos 789 1.92 0% Australia TPAO 154 1.53 100% Turkey Sibneft 189 1.81 0% Russia Average 1,000.27 5.23 Suncor 1,447 78.50 0% Canada Surgutneftegas 121 1.01 0% Russia Major IOCs Talisman 2,207 3.26 0% Canada BP 2,788 15.68 0% UK TNK 63 1.66 0% Russia Chevron 2,606 12.78 0% US Total 1,406 14.33 0% France ConocoPhillips 3,368 14.03 0% US Unocal 1,259 4.63 0% US ExxonMobil 3,148 12.26 0% US Vintage 1,136 1.76 0% US Shell 2,418 21.67 0% Netherlands Woodside 758 2.11 0% Australia Average 2,865.48 15.28 XTO 1,437 1.94 0% US Average 1,628.94 11.24 10 Simplified representation of DEA RICE n UNIVERSITY To graph the data in two dimensions, reserves are converted to barrels of oil equivalent and normalized, along with revenue, on the number of employees n Technical inefficiency in generating revenue from these inputs can be calculated using the vertical distance of a firm from the frontier 4 NOCs Majors Others e e 3 oy l p m e r e p ) $ US 2 on i l l i m ( e u n ve 1 Re 0 0 0.2 0.4 0.6 0.8 Reserves (mmboe) per employee 11 Other variables in the analysis n RICE Vertical integration could influence estimated technical efficiency: UNIVERSITY u A vertically integrated firm captures the value added by the internal sale of crude oil to its refining unit u Without measuring capital employed in the refining, transporting and marketing, a vertically integrated firm would appear to be relatively efficient at generating revenue from employees and reserves alone n Government ownership share is a key variable for our hypothesis: u Theory implies higher government ownership should give lower efficiency at generating revenue u Excess employment should be a key mechanism for this measured technical inefficiency u Two­tier pricing is another reason a NOC may generate less revenue Venezuela 0.11 Iran 0.21 Saudi Arabia 0.64 Indonesia 0.85 Algeria 0.89 Kuwait 0.91 UAE 1.06 Oman 1.08 Syria 1.12 Malaysia 1.12 Azerbaijan 1.12 Angola 1.29 Ecuador 1.53 Nigeria 1.59 Kazakhstan 1.70 Thailand 1.72 China 1.72 Russia 1.89 Mexico 1.97 Colombia 2.04 Average pump prices 2004 US 2.10 Brazil 2.52 Canada 2.57 India 2.82 Australia 3.18 Japan 4.18 Spain 4.37 Croatia 4.49 Austria 4.75 Hungary 4.77 Turkey 4.84 France 5.05 Italy 5.37 Netherlands 5.39 Denmark 5.41 Norway 5.77 UK 5.98 ­ 1.00 2.00 3.00 4.00 5.00 6.00 7.00 12 Average DEA scores over 2002­04 P o go 1.00 Nippo nOil 1.00 RICE P TT 0.96 P etro Kaza khs tan 0.87 Exxo nMo bil 0.84 UNIVERSITY Imperial 0.81 C NR 0.77 B P 0.75 Co no co P hillips 0.71 EnC ana 0.68 Shell 0.67 C hevro n 0.67 Newfie ld 0.64 Stato il 0.63 P etro ­C anada 0.62 Sino pec 0.61 n Hus kyEnergy 0.61 Murphy 0.60 Five major IOC’s are Sunco r 0.58 C NOOC 0.57 No ble 0.56 Talis man 0.55 clustered near the frontier OMV 0.54 B urlingto n 0.53 Devo n 0.52 Maratho n 0.50 n EOG 0.49 P ennWes t 0.48 NOC’s tend to be clustered Reps o lYP F 0.46 Apache 0.46 Amerada Hes s 0.45 Occidenta l 0.44 near the bottom Che s apeake Energy 0.44 Fo res tOil 0.43 B G 0.40 To ta l 0.39 Anadarko 0.38 n XTO 0.37 NOCs average TE ≈ 0.27 SaudiAramco 0.36 KP C 0.35 Kerr­McGee 0.34 Uno c al 0.33 QP 0.32 n P DVSA 0.32 Sample average TE ≈ 0.40 Vintage 0.31 Nexen 0.31 P etro nas 0.30 P etro ecuado r 0.30 Eni 0.29 n MOL 0.29 Five major