Relative Efficiency and Performance in the Integrated Oil and Gas Industry

Relative Efficiency and Performance in the Integrated Oil and Gas Industry Roberto Pougy Ferreira da Cunha Edmar Luiz Fagundes de Almeida, PhD Mariana Iooty de Paiva Dias, PhD Energy Economics Group, Institute of Economics, Federal University of Rio de Janeiro Avenida Pasteur 250, Sala 123 Urca, 22295-900 - Rio de Janeiro, RJ Brazil Phone: +55 21 3873-5269, Fax: +55 21 2541-8148, robertocunha@ie.ufrj.br

Introduction The integrated oil and industry International oil & gas industry constitute a peculiar study case for Industrial Organization Five main reasons: Oil is the most widely consumed energy source in the world (about 40% of the total) Entire industrial sectors depend fundamentally on this resource Economies of many countries influenced by its price dynamics and physical availability Trading values of other sources of energy directly correlated to the price of oil Oil represents a political factor of primary importance in international relations Source: Clô (2000)

Introduction The integrated oil and industry General basic economic conditions affecting oil supply Ultra-high capital intensity and risk environment High scale and scope economies Vertically integrated companies Increasing plant specificities Industry can be divided into NOCs and IOCs NOCs of several types, generally with legal protections over national oil reserves IOCs said to detain best technologies, being the ones capable of exploring complex projects Integrated IOCs can be divided into majors and super majors Formerly referred to as seven sisters Currently the super majors are BP, Chevron, ConocoPhillips, ExxonMobil, RD Shell and Total

Introduction The integrated oil and industry Source: BP Statistical Review 2008

Motivations The 2003-2007 period Rapidly increasing prices, culminating in a huge drop during the 2008 financial markets crisis Large profits margins registered for the period In this historical context: Do super majors display similar productivity levels in average? Are the ones with higher productivity levels attaining highest performance indicators? How do oil companies respond to raising oil prices efficiency-wise? Did their productivity vary due to high oil prices? Constantly increasing prices would have eased pressures for productive efficiency? Hypothesis: efficiency, in terms of productivity, is a weak determinant of overall performance

Proposed Plan of Action In order to test our hypothesis we will 1. Model production spaces for the upstream and downstream segments 2. Gather data on inputs and outputs quantities for the period 3. Gather data and apply Data Envelopment Analysis for efficiency assessment 4. Use Malmquist Indexes to assess changes in productivities 5. Analyze the correlation between relative efficiency and performance Sources: Ramos-Real et al (2008), Hawdon (2003)

Presentation Summary 1.Introduction The integrated oil and gas industry 2.Data and model choice 3.Results 4.Conclusions

Exploration DEA Data and Model Choice Exploration segment model Input: Year's number of completed exploratory drillings Outputs: Year's number of completed productive exploratory wells Increase in proved reserves due to extensions and discoveries (MMbbls) Output oriented Variable returns to scale (VRS) Firm 2007 2006 2005 2004 2003 BP 10,65 2,91 3,31 10,59 35,61 Chevron 0,65 1,73 2,56 2,05 3,37 ConocoPhillips 2,79 2,57 2,40 2,07 1,54 ExxonMobil 5,09 5,64 5,11 4,69 9,56 RD Shell 1,31 2,14 7,04 2,82 7,76 Total 3,91 5,57 2,86 19,84 29,53 Millions of barrels added to reserves per drilled well Firm 2007 2006 2005 2004 2003 BP 0,70 0,60 0,68 0,63 0,69 Chevron 0,76 0,71 0,74 0,70 0,68 ConocoPhillips 0,81 0,66 0,73 0,69 0,72 ExxonMobil 0,54 0,64 0,65 0,58 0,58 RD Shell 0,79 0,79 0,69 0,62 0,65 Total 0,58 0,58 0,56 0,64 0,65 Success rate in well drilling activities

Production DEA Data and Model Choice Production segment model Inputs: Proved reserves at previous year-end (MMbbls) Year's total net productive oil wells Outputs: Year's total oil production (MMbbls) Output oriented Variable returns to scale (VRS) Firm 2007 2006 2005 2004 2003 BP 0,09 0,09 0,09 0,09 0,08 Chevron 0,08 0,08 0,08 0,07 0,08 ConocoPhillips 0,08 0,08 0,08 0,07 0,07 ExxonMobil 0,10 0,11 0,09 0,08 0,08 RD Shell 0,16 0,15 0,15 0,14 0,13 Total 0,09 0,08 0,08 0,08 0,08 % of Previous Year-end Proved Reserves Produced Firm 2007 2006 2005 2004 2003 BP 64,16 65,94 60,44 59,29 54,21 Chevron 14,53 14,58 13,47 16,12 15,94 ConocoPhillips 66,14 66,65 70,70 58,99 43,85 ExxonMobil 47,58 48,48 44,54 41,14 38,02 RD Shell 60,99 64,44 65,97 72,95 78,35 Total 437,3 417,5 439,5 492,9 474,5 Thousands of Barrels Produced per Well

Refining DEA Data and Model Choice Refining segment model Inputs: Refining Capacity (Mb/d) Refining Throughputs (Mb/d) Outputs: Refined Product Sales Volume (Mb/d) Output oriented Variable returns to scale (VRS) Firm 2007 2006 2005 2004 2003 BP 1,37 1,37 1,39 1,23 1,16 Chevron 1,65 1,63 1,70 1,75 1,73 ConocoPhillips 1,25 1,23 1,27 1,23 1,21 ExxonMobil 1,13 1,13 1,17 1,17 1,15 RD Shell 0,98 0,99 1,03 1,01 0,99 Total 0,90 0,89 0,87 0,91 0,90 Refined Products Sales / Refining Capacity Firm 2007 2006 2005 2004 2003 BP 1,79 1,76 1,64 1,34 1,28 Chevron 1,90 1,82 1,98 1,98 1,88 ConocoPhillips 1,31 1,34 1,39 1,29 1,26 ExxonMobil 1,27 1,29 1,31 1,31 1,32 RD Shell 1,10 1,11 1,11 1,09 1,08 Total 1,01 0,98 0,98 0,98 0,98 Refined Product Sales / Refinery Throughput

Performance Indicators Return over Assets (RoA), 03-07 Equal to year s net income over year s total assets Measures the ratio of a company s profit by its ability to create them Ideal to compare company s within the same industry Profit Margin (PM), 03-07 Equal to year s net income over year s total revenue Measures the relative capacity of minimizing total costs Return over Equity (RoE), 03-07 Equal to year s net income over year s total equity Normalizes year s profits by a measure of a company s value

Financial DEA Data and Model Choice Financial performance model Inputs: Total assets (US$) Total revenue (US$) Outputs: Net income (US$) Output oriented Variable returns to scale (VRS) Firm 2007 2006 2005 2004 2003 BP 0,09 0,10 0,11 0,09 0,07 Chevron 0,13 0,13 0,11 0,14 0,09 ConocoPhillips 0,07 0,09 0,13 0,09 0,06 ExxonMobil 0,17 0,18 0,17 0,19 0,15 RD Shell 0,12 0,11 0,12 0,10 0,07 Total 0,12 0,12 0,12 0,11 0,09 Return over Assets Firm 2007 2006 2005 2004 2003 BP 0,07 0,08 0,09 0,07 0,06 Chevron 0,08 0,08 0,07 0,09 0,06 ConocoPhillips 0,06 0,08 0,07 0,06 0,05 ExxonMobil 0,10 0,10 0,10 0,12 0,10 RD Shell 0,09 0,08 0,09 0,07 0,06 Total 0,09 0,08 0,09 0,08 0,07 Profit Margin

Presentation Summary 1.Introduction The integrated oil and gas industry 2.Data and model choice 3.Results 4.Conclusions

Exploration Segment Firm CRS te VRS te Eff Chg Tech Chg TFP Chg BP 1 1 1 0.96 0.96 Chevron 0.948 0.955 0.998 1.025 1.023 ConocoPhillips 1 1 1 1.03 1.03 ExxonMobil 0.809 1 0.971 1.022 0.993 RD Shell 0.906 0.908 1.018 0.983 1.001 Total 0.965 1 0.934 0.854 0.798 mean 0.938 0.977 0.987 0.977 0.964 Time Period 2003-2007 Inputs Year's Number of Completed Exploratory Wells Drillings Outputs Year's Number of Completed Productive Exploratory Wells Increase in Proved Reserves due to Extensions and Discoveries Orientation Input Oriented Scale VRS

Exploration Segment

Exploration Segment

Production Segment Firm CRS te VRS te Eff Chg Tech Chg TFP Chg BP 0.656 0.877 1.026 1.002 1.028 Chevron 0.594 0.776 0.967 1.054 1.019 ConocoPhillips 0.578 1.000 1.038 1.003 1.041 ExxonMobil 0.632 0.915 1.022 1.024 1.046 RD Shell 1.000 1.000 1.000 1.027 1.027 Total 1.000 1.000 1.000 0.991 0.991 mean 0.743 0.928 1.009 1.016 1.025 Time Period 2003-2007 Inputs Year's Total Oil Production Proved Reserves at Previous Year-end Outputs Year's Total Net Productive Oil Wells Orientation Output Oriented Scale VRS

Production Segment

Refining Segment Firm CRS te VRS te Eff Chg Tech Chg TFP Chg BP 0.683 0.827 1.084 0.992 1.075 Chevron 1.000 1.000 1.000 0.996 0.996 ConocoPhillips 0.699 0.699 1.021 0.988 1.009 ExxonMobil 0.703 1.000 0.993 0.998 0.991 RD Shell 0.576 0.766 1.007 0.990 0.997 Total 0.524 0.582 1.011 0.988 0.999 mean 0.697 0.812 1.019 0.992 1.011 Time Period 2003-2007 Inputs Refined Product Sales Volume Refining Capacity Outputs Refinery Throughput Orientation Output Oriented Scale VRS

Refining Segment

Performance Assessment Firm CRS te VRS te Eff Chg Tech Chg TFP Chg BP 0.631 0.689 1.037 0.994 1.031 Chevron 0.627 1.000 1.077 1.025 1.104 ConocoPhillips 0.439 1.000 1.085 1.014 1.101 ExxonMobil 1.000 1.000 1.000 1.015 1.015 RD Shell 0.601 0.657 1.104 0.995 1.098 Total 0.654 1.000 1.068 0.998 1.066 mean 0.659 0.891 1.061 1.007 1.069 Time Period 2003-2007 Inputs Total Revenue Total Assets Outputs Net Income Orientation Output Oriented Scale VRS

Performance Assessment

Presentation Summary 1.Introduction The integrated oil and gas industry 2.Data and model choice 3.Results 4.Conclusions

Conclusions Exploration Production Performance Refining DEA Average DEA DEA DEA BP plc 1 0,656 0,683 0,780 0,631 Chevron Corporation 0,948 0,594 1 0,847 0,627 ConocoPhillips 1 0,578 0,699 0,759 0,439 Exxon Mobil Corporation 0,809 0,632 0,703 0,715 1 Royal Dutch Shell plc 0,906 1 0,576 0,827 0,601 Total S.A. 0,965 1 0,524 0,830 0,654 Correlation -0,486

Conclusions 1. Our hypothesis was apparently confirmed More efficient firms were not the most profitable ones Interesting clues are present 2. Misinterpretations Being more efficient is more costly in the integrated oil & gas industry? The return on efficiency might not be as appealing as other market strategies 3. Suggested interpretation Companies in this industry are subject to externalities such that cost minimization is a weak determinant of performance The ability to take higher risks is directly associated with the company`s size, thus dissociating performance from productive efficiency itself

Relative Efficiency and Performance in the Integrated Oil and Gas Industry Roberto Pougy Ferreira da Cunha Edmar Luiz Fagundes de Almeida, PhD Mariana Iooty de Paiva Dias, PhD Energy Economics Group, Institute of Economics, Federal University of Rio de Janeiro Avenida Pasteur 250, Sala 123 Urca, 22295-900 - Rio de Janeiro, RJ Brazil Phone: +55 21 3873-5269, Fax: +55 21 2541-8148, robertocunha@ie.ufrj.br