## wp17120

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### I. INTRODUCTION: ENERGY TRANSITIONS
- Historical context and thesis:
  - The “peak oil” hypothesis (Hubbert 1956) predicted the imminent demise of oil as the world’s main energy source; subsequent extraction advances and reserve discoveries challenged that view.
  - Quote: “The stone age came to an end not for a lack of stones, and the oil age will end, but not for a lack of oil.” (Sheikh Zaki Yamani)
  - Analogy: past demand-driven switches (wood → coal → oil) suggest potential demand-driven abandonment of oil.
- Historical U.S. fuel transitions (shares and durations):
  - Coal replaced wood roughly between 1850 and 1895: wood share fell from about 90 to 30 percent; coal rose from 9 to 65 percent.
  - Oil and gas replaced coal between roughly 1910 and 1955: coal share declined from 77 to 28 percent; combined oil and gas increased from 9 to 65 percent.
- Authors’ projection:
  - Switch away from oil could happen in the next 10 to 25 years as electric cars replace motor vehicles.
  - Fast adoption scenario: oil prices could converge to the level of coal prices, about $15 per barrel in 2015 prices by the early 2040s.
  - Slow adoption scenario: convergence could take another 10 to 20 years.
- Evidence cited for ongoing transition:
  - Cost declines of 50 percent or better in photovoltaics, wind power, and battery production since 2008.
  - Oil use per unit of global GDP has fallen by 40 percent, essentially linearly, since 1980 (IMF 2016).
  - IEA 2040 projection: oil 26 percent, coal 25 percent, natural gas 24 percent, renewable energy 19 percent of global energy.
- Historical transition durations cited:
  - Fouquet (2010): around 50 years (UK).
  - Wilson and Grubler (2011): global changes require 80-130 years.
  - Vaclav Smil (Lacey 2010): 50-70 years.
  - Grubler (1990): consistent 55-year intervals in U.S. infrastructure development.

### II. TRANSPORTATION REVOLUTION AND THE RETURN OF THE ELECTRIC CAR
- Transportation’s share of oil demand:
  - 57 percent of global oil demand from transportation (76 percent in the U.S. in 2014).
  - Road transportation accounts for 44 percent of oil use.
  - OPEC breakdown (World Oil Outlook 2015): petrochemicals 11 percent, industry 15 percent, residential/commercial/agriculture 10 percent, electricity generation 7 percent, rail/shipping/aviation 13 percent (included in transportation).
- Historical parallels and adoption patterns:
  - In 1900, electric cars were one-third of U.S. automobile stock; by 1935 electric cars had essentially disappeared.
  - Cart horse example: ownership fell by a factor of 10 in 15 years (1915–1930).
  - Early-stage EV penetration in the U.S. follows the motor vehicle adoption trajectory closely.
- Forecasts and scenario estimates cited:
  - OPEC 2015 WOO: 6 percent alternative fuel cars worldwide by 2040 (revised in 2016 WOO to 22 percent).
  - Bloomberg New Energy Finance (BNEF): 7.4 million electric vehicles by 2020; 25 percent of all cars by 2040.
  - BNP Paribas: 25 percent displacement by 2030.
  - Carbon Tracker and the Grantham Institute (2017): 19 percent EV share by 2030 and 55 percent by 2040 (“Weak_EV” scenario).
  - Becker et al. (2009): diffusion-model estimate (text truncated in source).

### FORECASTING APPROACHES, VALIDATION, AND SCENARIOS
- Forecasting approaches and validation:
  - Approaches: extrapolation from horse-car transition, Bass Diffusion Model, assessment of adoption hurdles (affordability).
  - Validation: horse-car extrapolation matches EV adoption data between 2011 and 2015; average annual growth rate of EV ownership was 120 percent between 2011 and 2015.
- Method I — Fast adoption scenario (horse-displacement analogy):
  - Historical pattern applied: horse ownership fell ~30 percent 1905–1915 and 90 percent 1915–1930.
  - Projection (one-to-one MV → EV displacement starting in 2017):
    - Projected average annual growth rate of EV ownership per 1000 people: about 70 percent for the first ten years; about 8 percent for the following fifteen years.
    - Equivalent average annual growth over 25 years: about 30 percent.
  - MV displacement implications:
    - 30 percent displacement by the late 2020s.
    - 93 percent displacement by early 2040s.
  - Alternative rapid note:
    - Reaching EV price threshold around $35,000 in 2018 could yield 90 percent displacement between 2018 and early 2030s; EVs would grow at an average annual growth rate of 53 percent over 15 years in that rapid case.
- Method II — Slow adoption scenario (early-20th-century MV growth analogy):
  - Projection parameters: average annual EV ownership growth of 24 percent over 25 years; implied average annual decline in MV ownership: 2 percent.
  - MV displacement implications:
    - 5 percent displacement by the late 2020s.
    - 36 percent displacement by early 2040s.
  - Comparison: Method II yields slower displacement rates closer to most other studies.
- Bass Diffusion Model estimates:
  - Specification: F(t) cumulative fraction; adopters split into innovators (p) and imitators (q).
  - Empirical OLS estimates on annual U.S. EV market data:
    - p ≈ 0.000017.
    - q = 0.44.
    - 95 percent confidence interval for q: 0.34-0.53.
  - Model implications using point estimates and 2015 starting data:
    - By early 2040s, EVs represent about 90 percent of vehicle stock (aligned with Method I).
    - Sensitivity: q = 0.34 projects EV share ≈ 44 percent by early 2040s and 90 percent saturation around 2050.
  - Comparative literature: Becker et al. (2009) and Davidson et al. (2013) use p between 0.01 and 0.02 and q of 0.4; Jensen et al. (2014) (Norwegian monthly data): p = 0.002 and q = 0.23.

### DISAPPEARING HURDLES TO EV ADOPTION — COST, BATTERIES, INFRASTRUCTURE, RANGE, MANUFACTURER COMMITMENTS
- Price and affordability:
  - Ford Model T Runabout relative price fell from about $137,000 in 1910 to about $33,030 in 1917 (2015 GDP-per-capita-indexed dollars).
  - Tesla Model 3 announced price: $35,000 (2018).
  - Average price of a new car in the U.S. in 2015: $33,500.
  - Conclusion: Tesla Model 3 price at $35,000 is at the threshold price of the Ford Model T where adoption accelerated.
- Battery cost trends and materials:
  - Li-ion battery costs fell from $1000/kWh in 2007 to $410/kWh in 2014 (≈ 14 percent per year).
  - Market leaders (Tesla and Nissan) already in the $300/kWh range (as of source).
  - Plausible targets:
    - Li-ion batteries at $150/kWh by 2025 described as a serious possibility.
    - U.S. Department of Energy reported $268/kWh for plug-in hybrid batteries in 2015 and targeting $125/kWh by 2022.
  - Lithium reserves and potential EV production:
    - Economically recoverable lithium reserves: 13 million tons → about 800 million EVs (with average lithium per EV battery pack of 16 kilograms).
    - Current world reserves over 39 million tons → about 2.4 billion EVs potentially producible.
  - Research: sodium-based battery technology announced (UT News 2017) as potential alternative.
- Lifetime cost competitiveness and operating costs:
  - IEA estimate: lifetime cost competitiveness already achieved (citation in document).
  - BNEF prediction: cost competitiveness for battery EVs by 2022.
  - Cambridge Econometrics prediction: cost competitiveness by 2025.
  - Fuel-cost comparison (2015 basis):
    - Average EV about 2.7 times cheaper to fuel than average motor vehicle.
    - Equivalent efficiency: EVs ~67 mpg equivalent; average motor vehicles ~25 mpg.
    - Tesla mpg equivalent ≈ 90.
  - Maintenance: EV maintenance described as 10 to 100 times cheaper than for MVs (Seba 2016).
- Infrastructure and range:
  - Early motor-vehicle growth occurred despite lack of roads and petrol distribution; infrastructure followed adoption.
  - Driving-pattern evidence: Needell et al. (2016) suggests nearly 87 percent of daily trips in the U.S. are short enough for existing EVs; 60 percent of gasoline consumption could be theoretically replaced in 2016 without further EV range improvements.
  - Range-anxiety characterized as largely psychological.
- Manufacturer commitments:
  - Honda aim: PHEVs and battery EVs to make up 2/3 of global sales by 2030.
  - Volkswagen pledge: 25 percent of global sales (pledge quoted in source).

### ELECTRICITY DEMAND FROM EVS, RENEWABLES EXPANSION, AND STORAGE
- Electricity requirement estimates:
  - 0.3 miles per kWh for the Nissan Leaf; equivalently 0.3 kWh/mile (Trancik et al. (2016)).
  - 15,000 miles/year at 0.3 kWh/mile → 4,500 kWh/year/vehicle (Covert, Greenstone, and Knittel (2016)).
  - 100 million EVs → 450 TWh (1 TWh = 1 billion kWh).
  - U.S. generated about 4,000 TWh in 2015; powering 100 million EVs → ≈ 11 percent increase in U.S. electricity production (2015 baseline).
  - Converting entire 2015 U.S. motor-vehicle stock (≈ 253 million vehicles) to EVs → ≈ 30 percent increase in production.
  - If extra electricity generated by oil: would require 5.4 million barrels per day (mbd); 9 mbd used to produce gasoline in 2015 → net decrease 3.6 mbd.
- Renewables growth and cost trends:
  - In 2015, total global renewable power capacity (inclusive of hydropower) outstripped coal-fired power capacity.
  - Renewables projected to make up 28 percent of global power generation by 2021.
  - Unsubsidized solar and wind already competitive in 30 countries; projected to become cheaper than coal and natural gas in over 60 percent of the world in the next few years.
  - Solar costs projected to fall 60 percent by 2040; wind costs projected to fall 40 percent; BNEF projects 60 percent of global power capacity in 2040 as non-fossil fuel.
  - Photovoltaics’ levelized cost of energy fallen 80 percent since 2009; wind fallen approximately 60 percent.
  - MIT: 65 percent of utility-scale solar costs are non-module related.
  - McKinsey projects stationary storage prices halved by 2020, at roughly $200/kWh.
  - Intermittency can be addressed via storage, demand-response, interconnected grids, and complementary natural gas plants.
- Country-level examples:
  - Germany >35 percent electricity from (non-hydro) renewables.
  - UK, France, Italy >19 percent.
  - G-20 derived 8 percent of its electricity from renewables in 2015 (about 70 percent increase since 2010).
  - Uruguay: 55 percent of total primary energy and 95 percent of electricity from renewables (including hydropower).
  - China: nearly half of global wind and a third of renewables capacity growth in 2015; largest EV market in 2015.
  - India targets roughly 50 and 100 GW additional wind and solar by 2022; plans to add 6-7 million hybrid and electric vehicles per year by 2020; passenger vehicle ownership in India is 2 percent; total energy use set to double by 2040.

### OIL MARKET, PROJECTED DEMAND SHIFTS, AND PRICE CONVERGENCE SCENARIOS
- OECD transport demand reductions (Method I vs Method II):
  - Method I (fast): OECD transport-sector oil demand decrease of about 6 mbd by late 2020s and a further decrease of 15 mbd by early 2040s → implied total drop in oil demand from transportation in advanced countries by early 2040s: about 21 mbd.
  - Method II (slow): slight increase of about 1 mbd by late 2020s and then a fall of 6 mbd by early 2040s → implied total drop by early 2040s: about 5 mbd.
- Non-OECD projections and elasticity considerations:
  - US EIA (2016) and OPEC (2016) project about 24 percent increase in oil demand in non-OECD countries between 2015 and 2025, 35 percent over 2015-2030, and 54 percent over 2015-2040.
  - Using IMF (2011) median long-term oil demand income elasticity of 0.4, required annual GDP per capita growth in non-OECD countries to sustain those oil demand increases: 4.3 percent over 2015-2030 and 3.5 percent over 2015-2040.
  - Historical per-capita growth 1980-2005: China 5.7 percent; India 3.5 percent.
  - Authors argue sustained high growth would itself induce rapid adoption of EVs/renewables in non-OECD countries, undermining assumptions of continued motor-vehicle dominance there.
- Global long-run demand and price outcomes:
  - Conservative scenario with 10-year adoption lag for non-OECD: initial 24 percent increase in non-OECD total oil demand (about 47 mbd to 58 mbd) over first ten years after 2017; subsequent fast adoption (Method I) implies a drop in oil demand for transportation of 7 mbd by early 2040s relative to 2015.
  - Long run (late 2020s to early 2040s):
    - Fast adoption scenario: global oil demand would fall about 28 mbd.
    - Slow-adoption scenario: global oil demand would fall about 1 mbd.
  - External projections: Carbon Tracker/Grantham Institute ~16 mbd displacement; BNEF ~13 mbd displacement globally by 2040.
  - If oil loses primary road-transport role, oil price should eventually converge to about 15 dollars per barrel in 2015 prices; timing: early 2040s in fast adoption, delayed by 10-20 years in slow adoption.
- Energy equivalences:
  - One barrel of crude oil = 5.729 million BTU.

### ECONOMIC, INDUSTRIAL, AND POLICY IMPLICATIONS
- Macroeconomic and fiscal consequences:
  - Substantial drop in oil revenues would affect macroeconomic stability and fiscal sustainability of oil-exporting countries.
  - Policy prescription for oil-exporting economies: diversification away from oil is crucial; investment in renewables and alternatives to motor vehicles recommended as natural hedges.
  - For oil-importing countries: low oil prices reduce current-account pressure but necessitate tax-policy shifts away from fuel taxes toward other forms of taxation.
- Industrial and labor market effects:
  - EV transition disrupts auto industry: EVs require far fewer parts and less maintenance, shorten value chains, and could enable on-shoring in advanced economies.
  - Tens of thousands of jobs could transition into new sectors: power charging networks, battery production, autonomous driving, etc.
- Climate policy and coordinated action:
  - Under the fast adoption scenario, EV replacement pace could meet conditions to keep global temperature rise below 2°C.
  - Strong rationale for coordinated government intervention to accelerate the transportation transition to combat climate change.
- Caveats and countervailing factors:
  - “Sailing-ship” effect: lower oil prices could briefly sustain fossil-fuel dominance; EV sales declined slightly with the 2014-2016 fall in oil price, but EV producers have cut costs faster.
  - Even if all extra electricity for EVs were generated from oil, the U.S. would still see a net decline in oil demand under current technology assumptions.
  - Alternative transport technologies (e.g., hydrogen) could emerge but would not materially alter conclusions about oil losing its exclusive role.

### KEY STATISTICS, FINDINGS, AND EXACT FIGURES
- Nissan Leaf efficiency and fuel price:
  - 0.3 miles per kWh for the Nissan Leaf.
  - 0.3 kWh/mile (Trancik et al. (2016)).
  - Average retail gasoline price: $2.40 per gallon.
- Vehicle prices and models:
  - Mainstream EVs priced in the $25-$35 thousand range; GM’s Bolt about $37,000.
- Autonomous vehicle example:
  - Manhattan: more than 13,000 yellow cabs → 9,000 self-driving vehicles (about 30 percent decline); cost per mile $4 → $0.5.
- EV electricity demand and U.S. baseline:
  - 15,000 miles/year; 4,500 kWh/year/vehicle.
  - 100 million EVs → 450 TWh.
  - U.S. electricity generation in 2015 ≈ 4,000 TWh.
  - 100 million EVs → ≈ 11 percent increase in U.S. electricity production (2015 baseline).
  - All U.S. motor vehicles in 2015 (≈ 253 million) → ≈ 30 percent increase in electricity production.
  - If extra electricity from oil: 5.4 million barrels per day required; 9 mbd used to produce gasoline in 2015 → net decrease 3.6 mbd.
- Renewables and costs:
  - Renewables projected to make up 28 percent of global power generation by 2021.
  - Photovoltaics’ levelized cost of energy fallen 80 percent since 2009.
  - Wind levelized cost fallen approximately 60 percent.
  - MIT: 65 percent of utility-scale solar costs are non-module related.
  - McKinsey stationary storage price projection: $200/kWh by 2020.
  - Germany >35 percent electricity from (non-hydro) renewables; UK/France/Italy >19 percent.
  - G-20: 8 percent electricity from renewables in 2015 (≈ 70 percent increase since 2010).
  - Uruguay: 55 percent total primary energy from renewables; 95 percent of electricity from renewables.
  - China: nearly half of global wind and a third of renewables capacity growth in 2015.
  - India targets roughly 50 and 100 GW additional wind and solar capacity by 2022; plans to add 6-7 million hybrid/electric vehicles per year by 2020; passenger vehicle ownership 2 percent; total energy use set to double by 2040.
- Oil demand projections and elasticities:
  - OECD transport-sector oil demand (Method I): decrease about 6 mbd by late 2020s and further 15 mbd by early 2040s → total drop about 21 mbd by early 2040s.
  - Method II: slight increase of about 1 mbd by late 2020s and fall of 6 mbd by early 2040s → total drop about 5 mbd.
  - Non-OECD projections (US EIA and OPEC): 24 percent increase 2015-2025; 35 percent 2015-2030; 54 percent 2015-2040.
  - IMF (2011) median long-term oil demand income elasticity for non-advanced economies: 0.4.
  - Required annual GDP per capita growth in non-OECD to sustain projections: 4.3 percent over 2015-2030 and 3.5 percent over 2015-2040.
  - Historical per-capita growth 1980-2005: China 5.7 percent; India 3.5 percent.
  - Long-run global oil demand change: fall about 28 mbd (fast adoption) or about 1 mbd (slow adoption) by early 2040s.
  - External comparative projections: Carbon Tracker/Grantham Institute ~16 mbd; BNEF ~13 mbd displacement by 2040.
  - Projected long-run oil price convergence: about 15 dollars per barrel in 2015 prices.
- Units and equivalences:
  - 1 TWh = 1 billion kWh.
  - One barrel of crude oil = 5.729 million BTU.

*Source — wp17120 - References (IMF working paper content provided).*

### References .............................................................................................................

### wp17120 - References

### I. INTRODUCTION: ENERGY TRANSITIONS
- Historical context and thesis:
  - The “peak oil” hypothesis (Hubbert 1956) predicted the imminent demise of oil as the world’s main energy source, but advances in extraction and reserve discoveries have challenged that view.
  - Quote: “The stone age came to an end not for a lack of stones, and the oil age will end, but not for a lack of oil.” (Sheikh Zaki Yamani)
  - Analogy: Past demand-driven switches (wood → coal → oil) suggest a similar potential demand-driven abandonment of oil.
- U.S. historical fuel transitions:
  - Coal replaced wood roughly between 1850 and 1895: wood share fell from about 90 to 30 percent; coal rose from 9 to 65 percent.
  - Oil and gas replaced coal between roughly 1910 and 1955: coal share declined from 77 to 28 percent; combined oil and gas increased from 9 to 65 percent.
- Projection for next transition:
  - Authors' projection: switch away from oil could happen in the next 10 to 25 years as electric cars replace motor vehicles, with oil losing its role as the main fuel for transportation.
  - Price implications: In the fast adoption scenario, oil prices could converge to the level of coal prices, about $15 per barrel in 2015 prices by the early 2040s. In the slow adoption scenario, convergence could take another 10 to 20 years.
- Evidence of an ongoing transition:
  - Cost declines of 50 percent or better in photovoltaics, wind power, and battery production since 2008.
  - Oil use per unit of global GDP has fallen by 40 percent, essentially linearly, since 1980 (IMF 2016).
  - IEA (OECD/IEA World Energy Outlook 2015) projection for 2040: oil 26 percent, coal 25 percent, natural gas 24 percent, renewable energy 19 percent of global energy.
- Historical durations of transitions cited:
  - Fouquet (2010): around 50 years for energy transitions in the United Kingdom.
  - Wilson and Grubler (2011): global changes require 80-130 years.
  - Vaclav Smil: 50-70 years (Lacey 2010).
  - Grubler (1990): consistent 55-year intervals between development of canal, railway, and surfaced road networks in the United States.
- Notes on adoption dynamics:
  - Natural gas, petroleum, and renewable energy have grown at almost the same exponential rate from comparable starting positions (see Figure 2).
  - Nakicenovic et al. (1999) summary of technological transition process: successful learning curve (learning-by-doing and economies of scale) leads to declining costs; logistic diffusion model and network effects drive adoption and “lock-in.”
- Definitions/notes:
  - “Renewables” data in this paper include only solar, wind, biofuel (excluding wood), and geothermal energy.
  - Figure 1 source: U.S. Energy Information Administration (EIA), (2012) and U.S. EIA Open Data.
  - Figure 2 note: Y-axis plotted on a logarithmic scale; renewables on right-hand axis. Source: U.S. EIA (2012) and U.S. EIA Open Data.
  - Year 0 baseline in Figure 2: GAS AT 1.4%, PETROL AT 1.9%, RENEWABLES AT 1.1% OF PRIMARY ENERGY USE.

### II. TRANSPORTATION REVOLUTION AND THE RETURN OF THE ELECTRIC CAR
- Transportation as the critical component of oil demand:
  - 57 percent of global oil demand comes from transportation (76 percent in the U.S. in 2014, Figure 3).
  - Road transportation alone accounts for 44 percent of oil use.
  - OPEC categorization (World Oil Outlook 2015): petrochemicals 11 percent, industry 15 percent, residential/commercial/agriculture 10 percent, electricity generation 7 percent, rail/shipping/aviation 13 percent (included in transportation).
- Historical parallel: horse vs. car and early electric vehicles:
  - In 1900, electric cars were one-third of the total automobile stock in the United States.
  - By 1912, the Ford Model T retailed at about 40 percent of the electric car’s price, contributing to the decline of electric cars; electric cars had essentially disappeared by 1935 (Matulka 2014).
- Adoption patterns and potential speed of EV diffusion:
  - Early-stage penetration of electric cars in the U.S. follows the motor vehicle adoption trajectory closely (see Figure 4).
  - Cart horse example: from 1915 to 1930, cart horse ownership fell by a factor of 10 in 15 years—illustrating how rapid modal shifts can be.
  - Coal a century ago: only 20 percent reliant on the transport sector (De Stercke 2014), whereas oil today is far more transportation-dependent.
- Forecasts and scenario estimates cited:
  - OPEC 2015 WOO: 6 percent alternative fuel cars worldwide by 2040 (later revised in 2016 WOO to 22 percent).
  - Bloomberg New Energy Finance (BNEF): 7.4 million electric vehicles by 2020, representing 25 percent of all cars by 2040.
  - BNP Paribas: 25 percent displacement by 2030.
  - Carbon Tracker and the Grantham Institute (2017): 19 percent share of electric vehicles by 2030 and 55 percent by 2040 (“Weak_EV” scenario).
  - Becker et al. (2009) diffusion-model estimate: EVs represent about a quarter of total vehicle stock by (text truncated in source).
- Data and figure sources:
  - Figure 3 source: International Institute for Applied Systems Analysis (De Stercke 2014).
  - Figure 4 source: OECD/IEA (2016) and U.S. Federal Highway Administration (FHWA), various years.

*Italicized: Source — wp17120 - References (IMF working paper content provided).*

### 2030. When explained explicitly, most projections use the data available on EV adoption and

### wp17120 - 2030. When explained explicitly, most projections use the data available on EV adoption and

### Forecasting approaches and validation
- Approaches used:
  - Extrapolation from the horse-car transition pattern (early 20th century).
  - Diffusion model widely used in management science (Bass Diffusion Model).
  - Assessment of adoption hurdles, especially affordability of EVs versus motor vehicles (MVs).
- Validation:
  - Extrapolation from the horse-car transition matches EV adoption data between 2011 and 2015.
  - Between 2011 and 2015, the average annual growth rate of EV ownership was 120 percent.

### Method I — Fast adoption scenario (horse-displacement analogy)
- Historical pattern applied:
  - Between 1905 and 1915, ownership of horses per thousand people fell by about 30 percent.
  - Between 1915 and 1930, horse ownership fell by 90 percent.
- Projection (one-to-one displacement of MV by EV starting in 2017):
  - Projected average annual growth rate of EV ownership per 1000 people:
    - About 70 percent for the first ten years.
    - About 8 percent for the following fifteen years.
  - Equivalent average annual growth over 25 years: about 30 percent.
- Implications for MV displacement (shares of total vehicles):
  - 30 percent displacement by the late 2020s.
  - 93 percent displacement by early 2040s.
- Alternative rapid scenario note:
  - Reaching EV price threshold of around $35,000 in 2018 could trigger a motor vehicle displacement rate similar to that of horses starting in 1915, yielding:
    - 90 percent displacement between 2018 and early 2030s.
    - EVs would grow at an average annual growth rate of 53 percent over 15 years in that rapid case.

### Method II — Slow adoption scenario (early-20th-century MV growth analogy)
- Projection parameters:
  - Average annual growth rate of EV ownership of 24 percent over 25 years.
  - Implied average annual rate of decline in motor vehicle ownership: 2 percent.
- Implications for MV displacement (shares of total vehicles):
  - 5 percent displacement by the late 2020s.
  - 36 percent displacement by early 2040s.
- Comparison:
  - Method II yields slower displacement rates closer to most other studies.

### Bass Diffusion Model estimates
- Model specification summary:
  - F(t) is cumulative fraction of potential market achieved; adopters classified as innovators (p) and imitators (q).
- Empirical estimates (OLS on annual U.S. EV market data):
  - p (intercept) ≈ 0.000017.
  - q (slope) = 0.44.
  - 95 percent confidence interval for q: 0.34-0.53.
- Model implications using point estimates and 2015 starting data:
  - By early 2040s, EVs would represent about 90 percent of vehicles’ stock (aligned with Method I).
- Sensitivity:
  - Using q = 0.34 (lower bound of CI) projects EV share ≈ 44 percent by early 2040s (close to Method II).
  - With q = 0.34, the market would reach 90 percent saturation around 2050.
- Comparative literature references (estimates quoted in source):
  - Becker et. al. (2009) and Davidson et. al. (2013) use p between 0.01 and 0.02 and q of 0.4.
  - Jensen et. al. (2014) (Norwegian monthly data): p = 0.002 and q = 0.23.

### Disappearing hurdles to EV adoption — cost, batteries, infrastructure, range, manufacturer commitments
- Price and affordability:
  - Historical: Ford Model T Runabout relative price fell from about $137,000 in 1910 to about $33,030 in 1917 (2015 GDP-per-capita-indexed dollars).
  - Tesla Model 3 announced price: $35,000 (2018).
  - Average price of a new car in the U.S. in 2015: $33,500.
  - Conclusion in source: Tesla Model 3 price at $35,000 is at the threshold price of Ford Model T where adoption accelerated.
- Battery cost trends:
  - Average vehicle Li-ion battery costs fell from $1000/kWh in 2007 to $410/kWh in 2014 (≈ 14 percent per year).
  - Market leaders (Tesla and Nissan) are already in the $300/kWh range (as of source).
  - Plausible future targets:
    - Li-ion batteries at $150/kWh by 2025 described as a serious possibility.
    - U.S. Department of Energy reported $268/kWh for plug-in hybrid batteries in 2015 and targeting $125/kWh by 2022.
  - Technological/material notes:
    - Economically recoverable lithium reserves: 13 million tons implies about 800 million EVs (with average lithium per EV battery pack of 16 kilograms).
    - Current world reserves over 39 million tons implies about 2.4 billion EVs potentially producible.
    - Research example: a sodium-based battery technology announced (UT News 2017) as a potential alternative to lithium.
- Lifetime cost competitiveness and operating costs:
  - IEA estimate: lifetime cost competitiveness already achieved (source citation in document).
  - Bloomberg New Energy Finance prediction: cost competitiveness for battery electric vehicles by 2022.
  - Cambridge Econometrics prediction: cost competitiveness by 2025.
  - Fuel cost comparison (2015 basis):
    - Average EV was about 2.7 times cheaper to fuel compared to the average motor vehicle.
    - Equivalent efficiency: EVs ~67 mpg equivalent versus average motor vehicles ~25 mpg.
    - Tesla mpg equivalent ≈ 90.
  - Maintenance cost: EV maintenance described as 10 to 100 times cheaper than for MVs (Seba 2016).
- Infrastructure and range:
  - Historical parallel: early-20th-century motor-vehicle growth occurred despite lack of roads and petrol distribution; infrastructure growth followed.
  - Driving-pattern evidence: Needell et. al. (2016) suggests nearly 87 percent of daily trips in the U.S. are short enough for existing EVs; 60 percent of gasoline consumption could be theoretically replaced in 2016 without further EV range improvements.
  - Range-anxiety characterized as largely psychological rather than technical.
- Manufacturer commitments:
  - Honda aim: PHEVs and battery EVs to make up 2/3 of global sales by 2030.
  - Volkswagen pledge: 25 percent of global sales (pledge quoted in source).

### Synthesis and overall assessment
- Methods I and II provide bounds for EV adoption; authors argue future is more likely closer to Method I than Method II because:
  - Potential market scale for EV adoption is much larger now than historical horse-to-car market.
  - Motor vehicles and EVs are closer substitutes than horses and motor vehicles were.
  - Rapid substitution analogized to smartphone adoption replacing ordinary cell phones.
  - EV price convergence to average motor vehicle price supports rapid substitution.
  - Modern automakers’ production scaling capability exceeds that of early automobile industry.
  - Environmental consciousness and climate concerns support faster adoption.
- Timing implications emphasized:
  - Depending on assumptions, large-scale motor-vehicle displacement could occur by the late 2020s through the 2030s and reach near-saturation (≈ 90 percent EV stock) by the early 2040s under faster scenarios or by around 2050 under slower diffusion assumptions.

*Source: wp17120 - 2030. When explained explicitly, most projections use the data available on EV adoption and (IMF Working Paper PDF content provided).*

### 0.3 miles per kWh for the Nissan Leaf, and an average retail gasoline price of $2.40 per gallon.

### wp17120 - 0.3 miles per kWh for the Nissan Leaf, and an average retail gasoline price of $2.40 per gallon

### EV adoption, autonomous vehicles, and diffusion speed
- EV market prices and models:
  - GM's Chevy Volt, Nissan's Leaf, Toyota's Prius Prime, and Tesla's Model 3 have prices in the $25-$35 thousand range (and GM’s Bolt is about $37,000), before tax incentives.
- Autonomous vehicle implications:
  - Ford plan to mass-produce fully self-driving cars by 2021.
  - Lyft CEO Travis Zimmer predicts self-driving cars could dominate the Lyft fleet within five years.
  - Study: Manhattan’s fleet of more than 13,000 yellow cabs could be replaced by 9,000 self-driving vehicles (about 30 percent decline), while decreasing cost per mile from $4 to $0.5.
  - Eliminating drivers would make ride-sharing cheaper than car ownership, increasing scope for electric car diffusion.
- Diffusion comparisons and historical analogies:
  - Electric cars have expanded faster in absolute terms over their first decade than motorcycles, motor cars, and electric bikes (Figure 9).
  - VCRs, cell phones, and microwaves went from 10 percent to 80 percent market penetration in the U.S. within a decade; color TVs achieved this from 1970 to 1980; refrigerators took two decades (1930-1950).
  - Fast adoption scenario for the U.S. EV market (Method I) resembles the most recent rapid technological adoptions.
- State push and sector-specific rapid transitions:
  - Brazil flex-fuel cars went from 20 percent to 90 percent of new cars sold between 2004 and 2009; by mid-2010s, 64 percent of all Brazilian cars on the road were flex-fuel.
- Nissan Leaf fuel-economy and alternate measures:
  - Content includes both "0.3 miles per kWh for the Nissan Leaf" and Trancik et. al. (2016) finding that the Nissan Leaf has a fuel economy of 0.3 kWh/mile.

### Electricity demand from EVs and renewables expansion
- Electricity requirement estimates:
  - Covert, Greenstone, and Knittel (2016) estimate that 15,000 miles/year driven by a vehicle with a fuel economy of 0.3 kWh/mile yields 4,500 kWh/year/vehicle.
  - Powering about 100 million electric vehicles would represent about 450 TWh of electricity (1 TWh = 1 billion kWh).
  - U.S. generated about 4,000 TWh of electricity in 2015; powering 100 million EVs would require increasing U.S. electricity production by about 11 percent.
  - Converting the whole U.S. motor vehicle stock in 2015 (about 253 million vehicles) to EVs would require increasing production by about 30 percent.
  - If all extra electricity were generated by oil, it would require 5.4 million barrels per day (mbd), compared to 9 mbd used to produce gasoline in 2015 — implying a net decrease of 3.6 mbd with current 2015 technology.
- Renewables growth and projections:
  - In 2015, total global renewable power capacity (inclusive of hydropower) outstripped coal-fired power capacity.
  - Renewables are projected to make up 28 percent of global power generation by 2021.
  - Unsubsidized solar and wind are already competitive in 30 countries and projected to become cheaper than coal and natural gas in over 60 percent of the world in the next few years.
  - Solar power costs projected to fall by 60 percent by 2040; wind costs projected to fall 40 percent; Bloomberg New Energy Finance projects 60 percent of global power capacity in 2040 as non-fossil fuel.
- Costs, storage, and intermittency:
  - Photovoltaics’ levelized cost of energy has fallen 80 percent since 2009.
  - Wind power’s levelized cost has fallen approximately 60 percent.
  - MIT's Energy Initiative (2015) finds 65 percent of utility-scale solar costs today are non-module related expenses.
  - McKinsey projects stationary storage prices will be halved by 2020, at roughly $200/kWh.
  - Combined with demand-response, a more interconnected grid, and complementary natural gas plants, intermittency could be effectively addressed.
- Country-level renewable adoption examples:
  - Germany generates over 35 percent of its electricity from (non-hydro) renewables; the UK, France, and Italy have reached more than 19 percent.
  - In 2015, the G-20 derived 8 percent of its electricity from renewables (about 70 percent increase since 2010).
  - Uruguay: 55 percent of total primary energy and 95 percent of electricity comes from renewables (including hydropower).
  - China accounted for nearly half of global wind and a third of renewables capacity growth in 2015 and became the world's largest market for electric vehicles in 2015.
  - India announced targets of roughly 50 and 100 GW of additional wind and solar capacity respectively by 2022, and plans to add 6-7 million hybrid and electric vehicles per year by 2020; passenger vehicle ownership in India is 2 percent of the population and total energy use is set to double by 2040.

### The oil market, projected demand shifts, and price convergence scenarios
- Historical parallels and structural points:
  - The decline of coal occurred in two stages: 1918-1944 coal fell from 73 percent to 50 percent of total primary energy use; 1945-1960 collapse in coal-powered transportation.
  - At no point historically was the price of oil cheaper than the price of coal in terms of heat content per dollar, yet oil supplanted coal for transport.
  - Coal price per barrel of oil equivalent has fluctuated narrowly at about $10-15 for a century and a half.
- Projected OECD transport demand reductions and methods:
  - By the late 2020s the stock of motor vehicle in the U.S. could decline by 24 percent (Method I); in the next 15 years the stock could fall by another 90 percent.
  - In terms of oil consumption in the transportation sector in advanced countries:
    - Decrease of about 6 mbd by late 2020s and a further decrease of 15 mbd by early 2040s under Method I.
    - Method II implies a slight increase of about 1 mbd by late 2020s and then a fall of 6 mbd by early 2040s.
  - Implied total drop in oil demand from transportation in advanced countries by early 2040s:
    - About 21 mbd under Method I.
    - About 5 mbd under Method II.
- Non-OECD projections and growth/elasticity considerations:
  - US EIA (2016) and OPEC (2016) project about 24 percent increase in oil demand in non-OECD countries between 2015 and 2025, 35 percent over 2015-2030 and 54 percent over 2015-2040.
  - Using IMF (2011) median long-term oil demand income elasticity of 0.4, the associated annual GDP per capita growth in non-OECD countries would have to be 4.3 percent over 2015-2030 and 3.5 percent over 2015-2040 to sustain those oil demand increases.
  - Historical per-capita growth 1980-2005: China 5.7 percent, India 3.5 percent.
  - Argument: sustained non-OECD growth at rates needed would likely induce rapid adoption of EVs and renewables in those countries, undermining assumptions of continued motor-vehicle dominance there.
- Global long-run demand and price outcomes:
  - Conservative scenario assuming a 10-year adoption lag for non-OECD countries: initial 24 percent increase in non-OECD total oil demand (about 47 mbd to 58 mbd) over first ten years after 2017; subsequent fast adoption (Method I) implies a drop in oil demand for transportation of 7 mbd by early 2040s relative to 2015.
  - Over the long run (late 2020s to early 2040s):
    - Fast adoption scenario: global oil demand would fall about 28 mbd.
    - Slow-adoption scenario: global oil demand would fall about 1 mbd.
  - External projections: Carbon Tracker/Grantham Institute project about 16 mbd displacement; BNEF projects about 13 mbd displacement globally by 2040.
  - If oil loses its primary role in road transport, oil price should eventually drop substantially and converge to a level around 15 dollars per barrel in 2015 prices, along with coal and natural gas; in the fast adoption scenario this could happen by the early 2040s; in the slow adoption scenario it may be delayed by ten to twenty years.
- Energy-price convergence context:
  - One barrel of crude oil = 5.729 million BTU (note from Figure 18).

### Economic, industrial, and policy implications
- Macroeconomic and fiscal consequences:
  - A substantial drop in oil revenues would have major implications on macroeconomic stability, including fiscal sustainability, of oil-exporting countries.
  - Policy prescription for oil-exporting economies: diversification away from oil is the most crucial item; investment in sectors such as renewables and alternatives to motor vehicles would be natural hedges.
  - For oil-importing countries: low oil prices reduce current-account pressure but would necessitate tax-policy shifts for countries relying heavily on fuel taxes toward other forms of taxation.
- Industrial and labor market effects:
  - Transition to EVs would disrupt the auto industry in production and maintenance: EVs require a much smaller number of parts and much less maintenance, shorten value chains, and could enable on-shoring into advanced economies.
  - Tens of thousands of jobs could transition into new sectors: power charging networks, battery production, autonomous driving, etc.
- Climate policy and coordinated action:
  - Under the fast adoption scenario, the pace at which EVs replace motor vehicles would meet the conditions to keep global temperature rise below 2°C.
  - Strong rationale for coordinated government intervention to accelerate the transportation transition to combat climate change.
- Caveats and countervailing factors:
  - “Sailing-ship” effect: lower oil prices could briefly sustain fossil-fuel dominance; EV sales declined slightly with the 2014-2016 fall in oil price, but EV producers have cut costs faster.
  - Even if all extra electricity to power EVs were generated from oil, the U.S. would still experience a net decline in oil demand under current technology assumptions.
  - Alternative transport technologies (e.g., hydrogen cars) could emerge, but would not materially alter conclusions about oil losing its exclusive role.

### Key statistics and exact figures extracted from the source
- 0.3 miles per kWh for the Nissan Leaf.
- 0.3 kWh/mile (Nissan Leaf fuel economy reported by Trancik et. al. (2016)).
- Average retail gasoline price of $2.40 per gallon.
- Vehicle prices: $25-$35 thousand range; Bolt about $37,000.
- Manhattan taxi example: more than 13,000 yellow cabs → 9,000 self-driving vehicles (about 30 percent decline); cost per mile $4 → $0.5.
- EV travel and electricity:
  - 15,000 miles/year; 4,500 kWh/year/vehicle.
  - 100 million EVs → 450 TWh.
  - U.S. electricity generation in 2015 ≈ 4,000 TWh.
  - 100 million EVs → require ≈ 11 percent increase in U.S. electricity production (2015 baseline).
  - All U.S. motor vehicles in 2015 (≈ 253 million) → require ≈ 30 percent increase in electricity production.
  - If extra electricity from oil: 5.4 million barrels per day required; 9 mbd used to produce gasoline in 2015; net decrease 3.6 mbd.
- Renewables and costs:
  - Renewables projected to make up 28 percent of global power generation by 2021.
  - Photovoltaics’ levelized cost of energy fallen 80 percent since 2009.
  - Wind levelized cost fallen approximately 60 percent.
  - MIT: 65 percent of utility-scale solar costs are non-module related.
  - McKinsey stationary storage price projection: $200/kWh by 2020.
  - Germany >35 percent electricity from (non-hydro) renewables; UK/France/Italy >19 percent.
  - G-20 8 percent electricity from renewables in 2015 (≈ 70 percent increase since 2010).
  - Uruguay: 55 percent total primary energy from renewables; 95 percent of electricity from renewables.
  - China accounted for nearly half of global wind and a third of renewables capacity growth in 2015.
  - India targets roughly 50 and 100 GW additional capacity by 2022; plans to add 6-7 million hybrid/electric vehicles per year by 2020; passenger vehicle ownership 2 percent; total energy use set to double by 2040.
- Oil demand projections and elasticities:
  - OECD transport-sector oil demand decrease: about 6 mbd by late 2020s and further 15 mbd by early 2040s (Method I).
  - Method II: slight increase of about 1 mbd by late 2020s and then fall of 6 mbd by early 2040s.
  - Implied total drop in oil demand from transportation in advanced countries by early 2040s: 21 mbd (Method I) and 5 mbd (Method II).
  - Non-OECD oil demand projections (US EIA and OPEC): 24 percent increase 2015-2025; 35 percent 2015-2030; 54 percent 2015-2040.
  - IMF (2011) median long-term oil demand income elasticity for non-advanced economies: 0.4.
  - Required annual GDP per capita growth in non-OECD countries to sustain projected oil demand: 4.3 percent over 2015-2030 and 3.5 percent over 2015-2040.
  - Historical per-capita growth 1980-2005: China 5.7 percent; India 3.5 percent.
  - Long-run global oil demand change: fall about 28 mbd (fast adoption) or about 1 mbd (slow adoption) by early 2040s.
  - External comparative projections: Carbon Tracker/Grantham Institute ~16 mbd displacement; BNEF ~13 mbd displacement by 2040.
  - Projected long-run oil price convergence point: about 15 dollars per barrel in 2015 prices.
- Energy equivalences and units:
  - 1 TWh = 1 billion kWh.
  - One barrel of crude oil = 5.729 million BTU.

*Source: wp17120 - 0.3 miles per kWh for the Nissan Leaf, and an average retail gasoline price of $2.40 per gallon (IMF working paper content provided).*

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### Policy, economics, and cross-cutting analyses
- Arezki, R., Z. Jakab, D. Laxton, A. Matsumoto, A. Nurbekyan, H. Wang, and J. Yao (2017). Oil prices and the global economy. IMF Working Paper WP/17/15.
- Parry, I., B. Shang, P. Wingender, N. Vernon, and T. Narasimhan (2016). Climate mitigation in China: Which policies are most effective? IMF Working Paper 16/148.
- International Monetary Fund/IMF (2016). World Economic Outlook: Too slow for too long. Washington, April.
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- Charap, J., A. Ribeiro da Silva, and P. Rodriguez (2013). Energy subsidies and energy consumption—a cross country analysis. IMF Working Paper 13/112.
- Cherif, R., F. Hasanov, and M. Zhu (2016). Breaking the oil spell: The Gulf falcons’ path to diversification. International Monetary Fund, Washington, DC.
- Cherif, R. and F. Hasanov (2015). The leap of the tiger: How Malaysia can escape the middle-income trap. IMF Working Paper WP/15/131.
- Benes, J., M. Chauvet, O. Kamenik, M. Kumhof, D. Laxton, S. Mursula, and J. Selody (2012). The future of oil: Geology versus technology. IMF Working Paper 12/109.

*Content compiled from: wp17120 - References (wp17120 - References).*

### 29. Retrieved November 20, 2016, from https://www.tesla.com/it_CH/blog/tesla-

### wp17120 - 29. Retrieved November 20, 2016, from https://www.tesla.com/it_CH/blog/tesla-

### References and cited media
- Tesla Motors sets new pricing—awardwinning Model S. Retrieved November 20, 2016, from https://www.tesla.com/it_CH/blog/tesla-motors-sets-new-pricing-awardwinning-model-s
- Tricks, H. (2016). The future of oil: breaking the habit. The Economist (Special Report), November 26. Retrieved from http://www.economist.com/news/special-report/21710628-worlds-use-oil-approaching-tipping-point-writes-henry-tricks-dont-expect
- United States Census Bureau (2000). Historical national population estimates: July 1, 1900 to July 1, 1999. [Data file]. Retrieved from https://www.census.gov/popest/data/national/totals/pre-1980/tables/popclockest.txt
- United States Census Bureau (2016). International data base. [Data file]. Retrieved from http://www.census.gov/population/international/data/worldpop/table_population.php
- United States Census Bureau (2016). Total population: All ages including armed forces overseas (POP) [Data file]. Retrieved from FRED, Federal Reserve Bank of St. Louis: https://fred.stlouisfed.org/series/POP
- United States Department of Energy, Energy Information Administration (2012). U.S. primary energy consumption estimates by source, 1775-2011 [Data file]. Retrieved from http://www.eia.gov/totalenergy/data/annual/perspectives.php
- United States Department of Energy, Energy Information Administration (2016). Monthly energy review-August 2016 [Data file]. Retrieved from http://www.eia.gov/totalenergy/data/monthly/archive/00351608.pdf
- United States Department of Energy, Energy Information Administration (2016). International Energy Outlook 2016. Retrieved October 4, 2016 from https://www.eia.gov/outlooks/ieo/pdf/0484(2016).pdf
- United States Department of Energy (2015). Revolution...now: The future arrives for five clean energy technologies—2015 update.
- United States Department of Labor, Bureau of Labor Statistics (2016). Consumer Price Index (Estimate), 1800- [Data file]. From Handbook of Labor Statistics. Retrieved from Federal Reserve Bank of Minneapolis: https://www.minneapolisfed.org/community/teaching-aids/cpi-calculator-information/consumer-price-index-1800
- United States Department of Transportation, Federal Highway Administration (2016). Highway statistics summary to 1995: Motor vehicle registrations by state, 1900-1995. Available: https://www.fhwa.dot.gov/ohim/summary95/mv200.pdf
- UT News (2017). Lithium-ion battery inventor introduces new technology for fast-charging, noncombustible batteries. University of Texas, February 28. Available: https://news.utexas.edu/2017/02/28/goodenough-introduces-new-battery-technology
- Ward, A. (2016a). Energy curbs pose a future mortal threat to oil majors. Financial Times, November 10. Retrieved from https://www.ft.com/content/6f89e2ea-948f-11e6-a1dc-bdf38d484582
- Ward, A. (2016b). Oil groups 'not investing enough' in green energy. Financial Times, November 18. Retrieved from https://www.ft.com/content/ba3719e6-ad41-11e6-ba7d-76378e4fef24
- Watts, J. (2015). Uruguay makes dramatic shift to nearly 95% electricity from clean energy. The Guardian, December 3. Retrieved October 04, 2016 from https://www.theguardian.com/environment/2015/dec/03/uruguay-makes-dramatic-shift-to-nearly-95-clean-energy
- Wilson, C., and A. Grubler (2011). Lessons from the history of technological change for clean energy scenarios and policies. Natural Resources Forum, 165-184.
- World Economic Forum (2016). Renewable infrastructure investment handbook: A guide for institutional investors. World Economic Forum, Geneva, December. Retrieved from http://www3.weforum.org/docs/WEF_Renewable_Infrastructure_Investment_Handbook.pdf

### Appendix — Data sources, variables, and units
- Fisher (1974)
  - Description: Non-farm horses and mules (proxy for transportation-horses), annual data in 5 year intervals (1900-1950).
  - Variable: Non-farm horses and mules
  - Units: Animals (millions)
- Census Bureau (2000)
  - Description: United States population estimates, July 1, 1900- July 1, 1999
  - Variable: US population, pre-1999
  - Units: Persons
- Census Bureau (2016)
  - Description: United States population estimates, including armed forces overseas
  - Variable: US population, post-1999
  - Units: Persons
- IEA Global EV Outlook (2016)
  - Description: Electric and plug-in hybrid vehicles, by country
  - Variable: Electric Cars
  - Units: Cars (thousands)
- U.S. Federal Highway Administration
  - Description: U.S. motor-vehicle registrations (including trucks and buses), annual
  - Variable: "Motor cars"
  - Units: Vehicles
- Johnston & Williamson (2016)
  - Description: US Nominal GDP per Capita, 1902-1927
  - Variable: Nominal GDP /Capita
  - Units: Nominal US Dollars
- U.S. EIA (2012)
  - Description: U.S. Primary Energy Consumption by Source, 1875-2011, annual (e.g. Annual US coal consumption, 1875-2011)
  - Units: Quadrillion BTU
- U.S. EIA Monthly Energy Review, August 2016
  - Description: U.S. Primary Energy Consumption by Source, 2012-2015, annual (e.g. Annual US coal consumption, 2012-2015)
  - Units: Quadrillion BTU
- De Stercke (2014)
  - Description: US Primary Energy Consumption by source and usage, 1900-2014 (e.g. Coal Consumption in Transportation)
  - Units: Terajoules/year
- McNerney et. al (2011)
  - Description: Nominal US coal price, weighted average of bituminous+anthracite coal for (1875-1957). Subsequently, weighted average of bituminous+subbituminous+lignite+anthracite coal for (1958-1989).
  - Variable: Nominal US Coal Price (1875-1989)
  - Units: Nominal USD/short ton
- EIA Open Data (Coal prices) (1)/ [STEO.CLEUDUS.A]
  - Description: Cost of coal delivered to US electric generating plants, (1990-2015)
  - Variable: Nominal US Coal Price (1990-2015)
  - Units: Nominal USD/million BTU
- EIA Open Data (Natural Gas prices) [NG.RNGWHHD.A]
  - Description: Henry Hub Natural Gas Spot Price, Annual (2000-2015)
  - Variable: Nominal US Natural gas price (2000-2015)
  - Units: Nominal USD/million BTU
- EIA Open Data (Crude oil prices) [PET.RWTC.A]
  - Description: Cushing, OK WTI Spot Price FOB, Annual (2000-2015)
  - Variable: Nominal US Crude Oil Price (2000-2015)
  - Units: Nominal USD/barrel
- EIA Open Data (Renewable energy consumption) [TOTAL.WYTCBUS.A,TOTAL.BMTCBUS.A,TOTAL.SOTCBUS.A,TOTAL.GETCBUS.A,TOTAL.TETCBUS.A]
  - Description: US renewable energy consumption decomposed by type (i.e. solar, wind, biofuels) (2)
  - Variable: "Renewables"
  - Units: Trillion BTU
- EIA Open Data (Petroleum consumption) [TOTAL.PAICBUS.A,TOTAL.PACCBUS.A,TOTAL.PARCBUS.A,TOTAL.PAEIBUS.A,TOTAL.TETCBUS.A]
  - Description: Petroleum consumption decomposed by sector (e.g. residential, industrial, commercial use) (1990-2015)
  - Variable: Petroleum Consumption, non-transport sector
  - Units: Thousand barrels/day
- EIA Open Data (Wood energy) [TOTAL.WDTCBUS.A]
  - Description: Annual wood energy consumption (2012-2015). Later subtracted from renewables.
  - Units: Trillion BTU
- Bureau of Labor Statistics
  - Description: Consumer price index, 1800-2015
  - Variable: US CPI (used to deflate coal prices)
  - Units: Unitless index
- BP Statistical Review of World Energy (2016), data workbook
  - Description: Oil price, combining various series. (1875-2015) (3)
  - Variable: US oil price
  - Units: Real $2015, deflated using US CPI
- IMF WEO (2016)
  - Description: US nominal GDP /Capita, 2015
  - Variable: US nominal GDP /capita (2015)
  - Units: Nominal USD, 2015
- Collins (2007)
  - Description: Nominal Price (USD) of Model T Runabout
  - Variable: Model T Runabout price
  - Units: US Dollars
- Gartner (2009), (2015)
  - Description: Global mobile phone sales to end users, (2008-2014)
  - Variable: Global mobile phone sales
  - Units: Millions of units
- Gartner (2016)
  - Description: Global smartphone phone sales to end users, (2007-2015)
  - Variable: Global smartphone sales
  - Units: Millions of units
- Ericsson (2015), (2016)
  - Description: Global smartphone subscriptions per capita (2014, 2015)
  - Variable: Global smartphone ownership
  - Units: Units per capita
- Heggestuen (2013)
  - Description: Global smartphone penetration (active devices per capita)
  - Variable: Global smartphone ownership
  - Units: Units per capita
- ["Tesla Motors sets..." (2012), Davies (2014), Quiroga (2015), Fleming & Peltz (2016), Randall (2016)]
  - Description: Retail price for Tesla Model S and Model 3 (without tax credits) culled from various news sources, for lack of an available data series.
  - Variable: Tesla Model S (and prospective Model 3) MSRP
  - Units: Nominal USD
- Bento and Wilson (2016)
  - Description: Annual data on global technological diffusion (1870-2008).
  - Variable: Consumer technologies (refrigerators, dryers, etc.) and Power capacity (Electricity from oil, hydropower, coal, etc.)
  - Units: Consumer technologies (units) and Power technologies (megawatts of installed capacity)
- Ren21 (2014), (2016)
  - Description: Global total of solar, wind, biofuel, and geothermal electricity generation capacity (2004-2015). Non-hydro renewables (2004-2015).
  - Units: Megawatts of installed capacity
- Maddison (2009)
  - Description: Global population, annual (1870-2005)
  - Units: Persons (thousands)
- Census Bureau (2016)
  - Description: Total mid-year global population, annual (2005-2015)
  - Units: Persons

### Notes on series composition and usage
- Description: where dates are given, these signify dates relevant for our use and not the full extent of the time series. For example, Fisher's non-farm horses data extends to 1850, but we use only 1900-1950.
- (2)/ We only include Solar, Wind, Biofuels (excluding Wood), and Geothermal Energy in our Renewables series.
- (3)/ Series composition: "1875-1944 US Average, 1945-1983 Arabian Light posted at Ras Tanura, 1984-2015 Brent dated."
- (1)/ EIA Open Data series are constantly updated and available for bulk download from http://www.eia.gov/opendata/. Any Open Data series used here include unique series identifiers, enabling users to find the source data. There may be slight discrepancies as data is revised over time.

*Source: wp17120 - 29. Retrieved November 20, 2016, from https://www.tesla.com/it_CH/blog/tesla-*

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_Source: https://www.imf.org/-/media/files/publications/wp/2017/wp17120.pdf_