Plug-in Vehicle Deployment in California: An Economic Assessment

David Roland-Holst Department of Agricultural and Resource Economics UC Berkeley dwrh@berkeley.edu

30 October 2012 Clean Air Dialogue (CAD) Working Group, Sacramento

DOCKETEDCalifornia Energy Commission

JAN. 18 2013

TN # 69194

12-ALT-02

Roland-Holst 2

Acknowledgements •  This research was performed at the invitation of the California

Electric Transportation Coalition. We wish to thank the CARB and CalEPA staff for their data, Natural Resources Defense Council, Electric Power Research Institute and California Electric Transportation Coalition for their technical review, and Chris Yang, U.C. Davis, for data, insights and advice. We also thank the CARB and CalEPA staff for their data, and Chris Yang, U.C. Davis, for data and insights.

•  The author also wishes to thank many research assistants for dedicated support during this project: Drew Behnke, Billie Chow, Melissa Chung, Elliot Deal, Sam Heft-Neal, Shelley Jiang, Fredrick Kahrl, Mehmet Seflek, and Ryan Triolo.

•  Financial support from CalETC is gratefully acknowledged.

30 October 2012

Roland-Holst 3

Objectives

1.  Estimate direct and indirect economic impacts of Plug-in Electric Vehicle (PEV) deployment.

2.  Inform stakeholders and improve visibility for policy makers.

3.  Promote evidence based policy dialogue.

30 October 2012

Roland-Holst 4

Summary of Findings •  Light-duty vehicle electrification can be a potent catalyst

for economic growth, contributing up to 100,000 additional jobs by 2030.

•  On average, a dollar saved at the gas pump and spent on the other goods and services that households want creates 16 times more jobs.

•  Unlike the fossil fuel supply chain, the majority of new demand financed by PEV fuel cost savings goes to in-state services, a source of diverse, bedrock jobs that are less likely to be outsourced.

•  Individual Californians gain from economic growth associated with fuel cost savings due to vehicle electrification, whether they buy a new car or not. As a result of light-duty vehicle electrification, the average real wages and employment increase across the economy and incomes grow faster for low-income groups than for high-income groups.

30 October 2012

Roland-Holst 5

How we Forecast

California GE Model

Transport Sector

Electricity Sector

Technology

The Berkeley Energy and Resources (BEAR) model is being developed in four areas and implemented over two time horizons.

Components:

1. Core GE model

2. Technology module

3. Electricity generation/distribution

4. Transportation services/demand

Time frames: 1. Policy Horizon, 2010-2030 2. Strategic Adaptation Horizon, 2010-2050

30 October 2012

Roland-Holst 6

Detailed Framework National and International Initial Conditions, Trends, and External Shocks

Emission Data Engineering Estimates Adoption Research Trends in Technical Change

Prices Demand Sectoral Outputs Resource Use

Detailed State Output, Trade, Employment, Income, Consumption, Govt. Balance Sheets

Standards Trading Mechanisms Producer and Consumer Policies

Technology Policies

California GE Model

Transport Sector

Electricity Sector

Technology

LBL Energy Balances PROSYM/MARKAL/NEMS Initial Generation Data Engineering Estimates

Innovation: Production Consumer Demand

Energy Regulation RES, CHP, PV

- Data - Results - Policy Intervention

Household and Commercial Vehicle Choice/Use

Fuel efficiency Incentives and taxes

Detailed Emissions of C02 and non-C02

30 October 2012

Roland-Holst 7

PEV Deployment Scenarios

30 October 2012

Scenario Name Description

1 Baseline Assume California implements current commitments to state and post-1990 federal fuel economy standards, but continues growth at levels forecast by the Department of Finance. This is the baseline scenario.

2 PEV15 Including the Baseline scenarios, but assuming 15.4% PEV deployment in the new light-duty vehicle fleet by 2030, this would be consistent with the ZEV regulations being met by PEVs. Tax credits for PEV vehicles are phased out by 2020, and LCFS credits are awarded for pollution reduction (see section 3).

3 PEV45 Same as PEV15, except PEV deployment is accelerated to 45% of the new light-duty vehicle fleet by 2030.

Roland-Holst 8

Macroeconomic Impacts

PEV15 PEV45 Real GSP 4.954 8.177 Net Job Growth 48,816 97,761

30 October 2012

Change from Baseline trend in 2030. Billions of 2012 dollars and FTE jobs.

Source: Author estimates.

Roland-Holst 9

Employment Effects

30 October 2012

Change from Baseline trend in 2030. FTE thousands.

-20 0 20 40 60 80 100 120

PEV15

PEV45

Accelerated Job Growth Slowed Job Growth Net

Source: Author estimates.

Roland-Holst 10

Retail

Priv Services

Construction

Oil&Gas

0.01

0.10

1.00

10.00

100.00

Em

ploy

mne

t Con

tent

of O

utpu

t (lo

gari

thm

ic sc

ale)

California Agriculture, Industry, and Service Sectors

Why it works The carbon fuel supply chain is among the least job-intensive in

the economy.

30 October 2012 Source: California Dept of Finance and

Employment Development Office

Roland-Holst 11

Index of Job Intensity by Sector

Sector Job Index

Agriculture 20 Construction 42 Oil & Gas 1 Vehicle Manufacturing 5 Vehicle Sales & Service 19 Wholesale & Retail Trade 29 Other Service 34

30 October 2012 Source: California State Department of Finance

and Employment Development Department

Roland-Holst 12

Employment Impacts by Sector (FTE thousands, change in 2030)

Sector PEV15 PEV45 Agriculture 0 0 Other Primary 0 0 Oil and Gas -2 -6 Electric Gen and Dist 1 3 Natural Gas Dist. 0 0 Other Utilities 0 0 Processed Food 0 0 Construction -– Residential 1 2 Construction -– NonRes 2 5 Light Industry 3 6 Heavy Industry 1 3 Machinery 0 0 Technology 2 4 Electronic Appliances 0 0 Automobiles and Parts 1 2 Trucks and Parts 0 0 Other Vehicles 0 1 Wholesale, Retail Trade 15 30 Transport Services 2 4 Other Services 23 45 Total Net Jobs 49 98 New Employment 51 104 Reduced Job Growth -2 -6

30 October 2012

Roland-Holst 13

Real Income by Household Tax Bracket

Household ZEV15 ZEV45 1 < $12k 0.2% 0.4% 2 $12-28k 0.2% 0.4% 3 $28-40k 0.2% 0.4% 4 $40-60k 0.2% 0.2% 5 $60-80k 0.2% 0.2% 6 $80-200k 0.2% 0.2% 7 $200k+ 0.1% 0.2%

Average 0.2% 0.4%

30 October 2012 Source: Author estimates.

Roland-Holst 14

Vehicle Adoption

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030

Per

cent

of F

inal

Yea

r Mar

ket S

hare

Normal

Early

Late

Source: Author assumption 30 October 2012

Roland-Holst 15

Fleet Composition

PEV$Passenger$Cars$(by$tech$type)$ $PHEV20$ $ $ 33%$PHEV40$ $ $ 33%$BEV100$ $ $ 33%$

$ $ $ $PEV$Light$Trucks$(by$tech$type)$ $ $

PHEV20$ $ $ 50%$PHEV40$ $ $ 30%$BEV100$ $ $ 20%$

Source: Author 30 October 2012

Roland-Holst 16

Vehicle Miles Traveled

0

5000

10000

15000

20000

0 5 10 15

Ann

ual d

rivi

ng (

mi/y

r/ve

hicl

e)

Vehicle age

Light trucks Cars

median: 14-yr, 186k

median: 17-yr, 234k

Source: CARB, 2008 30 October 2012

Roland-Holst 17

Vehicle Survival Rates

!"!!!!

!0.20!!

!0.40!!

!0.60!!

!0.80!!

!1.00!!

!1.20!!

1! 2! 3! 4! 5! 6! 7! 8! 9! 10! 11! 12! 13! 14! 15! 16! 17! 18! 19!

Source: SHTSA, 2006 30 October 2012

Roland-Holst 18

CA Gasoline and Diesel Prices

2.00

2.50

3.00

3.50

4.00

4.50

5.00

2009

20

11 20

13 20

15 20

17 20

19 20

21 20

23 20

25 20

27 20

29 20

31 20

33 20

35

Pric

e ($

/gal

lon)

Gasoline Diesel

Source: EIA, 2012 30 October 2012

Roland-Holst 19

Baseline CA Electricity Price

10 11 12 13 14 15 16 17 18 19 20

2010

20

11 20

12 20

13 20

14 20

15 20

16 20

17 20

18 20

19 20

20 20

21 20

22 20

23 20

24 20

25 20

26 20

27 20

28 20

29 20

30

Pric

e (c

ents

/kW

h)

Year

Source: EIA, 2012 30 October 2012

Roland-Holst 20

Battery Cost Efficiency

Source: McKinsey, 2012

$0#

$200#

$400#

$600#

$800#

$1,000#

$1,200#

2012#

2013#

2014#

2015#

2016#

2017#

2018#

2019#

2020#

2021#

2022#

2023#

2024#

2025#

2026#

2027#

2028#

2029#

2030#

$/kW

h& PHEV10#

PHEV40#

BEV#

30 October 2012

Roland-Holst 21

Incremental Vehicle Costs

Source: Author estimates.

$0#

$5,000#

$10,000#

$15,000#

$20,000#

$25,000#

$30,000#

2012# 2013# 2014# 2015# 2016# 2017# 2018# 2019# 2020# 2021# 2022# 2023# 2024# 2025# 2026# 2027# 2028# 2029# 2030#

PHEV20#PC#

PHEV20#LT#

PHEV40#PC#

PHEV40#LT#

BEV#PC#

BEV#LT#

30 October 2012

Roland-Holst 22

Aggregate Incremental Cost: PEV15

Source: Author estimates. 30 October 2012

!$3,000&

!$2,000&

!$1,000&

$0&

$1,000&

$2,000&

$3,000&

$4,000&

$5,000&

$6,000&

2012&2013&2014&2015&2016&2017&2018&2019&2020&2021&2022&2023&2024&2025&2026&2027&2028&2029&2030&

Incremental&Costs&

Fuel&Cost&Savings&

Total&IncenBves&

LCFS&Credit&

Net&Savings&

Millions of 2012 dollars)

Roland-Holst 23

Aggregate Incremental Cost: PEV45

Source: Author estimates. 30 October 2012

!$3,000&

!$2,000&

!$1,000&

$0&

$1,000&

$2,000&

$3,000&

$4,000&

$5,000&

$6,000&

2012&2013&2014&2015&2016&2017&2018&2019&2020&2021&2022&2023&2024&2025&2026&2027&2028&2029&2030&

Incremental&Costs&

Fuel&Cost&Savings&

Total&IncenBves&

LCFS&Credit&

Net&Savings&

Roland-Holst 24

Conclusions

•  Vehicle fuel efficiency can be a potent catalyst for economic growth and energy security.

•  Households and enterprises spend their fuel savings on new vehicle technology and a broad range of other goods and services, stimulating net employment growth across the state economy.

•  By creating a market to incubate the next generation of fuel efficient vehicles, California can promote job growth across it’s economy while capturing national and global market opportunities for technology development.

30 October 2012

Roland-Holst 25

Recommendations

•  More extensive analysis of program design: incentive policies, vehicle adoption patterns, and welfare effects

•  More intensive analysis of likely market and technology responses

•  Assessment of other transport classes

30 October 2012

Roland-Holst 26

Discussion

30 October 2012