Internet Survey Results on the Effects of Fuel Economy Labels on 

Understanding and Selection 

Prepared by 

PRR Inc. 

November 2010 

 
 

1 

Internet Survey Results on the Effects of Fuel Economy Labels on 

Understanding and Selection 

Summary 

This report presents the results of a survey conducted on three fuel economy label designs proposed by

the U.S. Environmental Protection Agency and the National Highway Traffic Safety Administration.1 

Each respondent saw only one label design and was asked to compare conventional and advanced 

technology vehicles based on the information in the presented labels. 

The “understanding” questions asked respondents to identify the “better” vehicle for specified trips. 

Overall, the differences between the three label designs with respect to understandability are small. 

 The “selection” questions asked respondents to identify which vehicle s/he preferred to buy, if vehicles 

were identical except for the information on the labels. Overall, the vehicle selection differences

between the three label designs are small. 

Methodology 

Survey question development and pretesting 

The survey questions were developed by PRR, Inc. and the EPA, with input from NHTSA (National 

Highway Traffic Safety Administration) and OMB (Office of Management and Budget).2 The survey 

questions were pretested in seven cognitive interviews. 

A total of six different versions of the survey were used. These six versions differed only in regard to: 

• Which of the three label designs was presented in the survey 

• The order in which the labels were presented in the survey questions (to control for stimulus 

order effects) 

Sampling and survey implementation 

Two sources of new vehicle buyers were used: 

• those who requested a price quote from a dealer (Autobytel, http://www.autobytel.com ) and 

who indicated that they had purchased a new vehicle (120,000 contacted; response rate < 1%)) 

 

1

 Environmental Protection Agency and Department of Transportation, “Revisions and Additions to Motor Vehicle 

Fuel Economy Labe; Proposed Rule,” Federal Register 75(184) (September 23, 2010): 58078-58202. 

2

 Drafts of the survey were reviewed by Dr. Clay Voorhees of Michigan State University and Dr. Randall Pozdena of 

ECONorthwest, former vice president of the Federal Reserve Bank of San Francisco. 
 

2 

• the e-RewardsTM panel3

 of new vehicle buyers (12,025 contacted; response rate about 25%) 

The survey was conducted September 8-22, 2010. 

Data Management and Analysis 

The data from all versions of the survey were merged into one database for analysis purposes. Those 

who indicated that they had not purchased a vehicle were dropped from the final database. In addition, 

the time that it took respondents to complete the survey was calculated. Any respondent who 

completed the survey in less than five minutes was considered to have “blown through” the survey (i.e., 

could not have read/considered the questions carefully enough to provide valid information) and was 

dropped. Finally, response range and logic checks were performed in order to identify any miscoded 

variables. The final data set for this analysis (n = 3,169) consists of respondents overwhelmingly from 

the e-Rewards panel, but it includes some respondents from Autobytel.4 PRR, Inc., conducted the data 

analysis, with assistance from ECONorthwest. 

A comparison of respondent demographics across the six versions of the survey indicated no statistically 

significant differences, except that age for those who viewed the Label 3 design was slightly older than 

those who viewed the other two label designs. Respondents came from all fifty states and the District of 

Columbia. 

The key questions on the survey examined people’s “understanding” of the labels and the variation in 

“selection” between vehicles when people saw different label designs. For both these kinds of 

questions, respondents were shown labels of the same design but for different hypothetical vehicles 

(different technology, fuel economy, costs, etc.). In the “understanding” questions, respondents were

asked which vehicle was “better” for a specified distance. The “selection” questions asked which vehicle 

the respondent would prefer to buy if all vehicle characteristics other than those on the label were the 

same. This memo provides the results of these questions. 

 

3

 The e-Rewards panel (part of ResearchNowTM http://www.researchnow.com/ ) is among the most highly rated of 

such online survey panels, and has a global automotive panel of over 1.5 million panelists. Respondents are paid a 

small fee ($1.25) for completing surveys. A number of government projects have used e-Rewards panelists, 

including but not limited to surveys conducted for the United States Department of Homeland Security and the 

United States Department of Defense. 

4

 The responses include 191 people who self-identified as intending to buy a new vehicle, rather than having 

bought a new vehicle. These people came from the Autobytel database, as there were no “intenders” in the eRewards panel. Because intenders were found to be demographically different from buyers (e.g., more male, 

older, less wealthy), the intenders were excluded from the analyses presented here. Including intenders might 

affect the results, without sufficient numbers of them to identify what effects are associated with intenders vs. 

buyers, or to separate the demographic effects from differences in preference between intenders and buyers. The 

results presented here thus reflect the preferences only of buyers. Due to omission of an identifier in the eRewards panel responses, the buyers from the Autobytel panel cannot be distinguished from the e-Rewards 

panelists. They are likely to be a small enough number that they will not significantly affect the results. 
 

3 

The labels presented in the survey are based on hypothetical vehicles and are not intended to reflect the 

performance of any specific vehicles. The results of these surveys are not intended to be representative 

of any larger group of new vehicle buyers and reflect only the experiences of those who completed the 

survey. 
 

4 

Topline ‘Understanding’ Question Results 

Respondents’ understanding of the labels was tested by showing them a series of label pairs for 

hypothetical vehicles (see Appendix 1, Understanding Questions (UQ) 1-6). In each pair, respondents 

were asked to identify which vehicle was better to use for trips of specified distances. “Better” was 

chosen as the comparison word, rather than “more fuel-efficient” or “less costly,” to allow respondents 

to decide on their own what information on the label they would use. Answers may therefore reflect 

individuals’ idiosyncratic attitudes and assumptions; as a result, “incorrect” answers may result for 

reasons other than the information on the labels. Because those idiosyncrasies are expected to be 

distributed randomly across the label designs, differences in responses across label designs are expected 

to be due to the label designs. EPA has chosen to define the objectively “better” answers to these 

questions based on fuel cost, fuel economy, GHG emissions, and vehicle range and will identify this as 

the “correct” answer for purposes of the discussion below. Responses of “Both are equally good” are 

included in the “incorrect” answers. 

Below we have presented the results from each label pair, preceded by a brief description of some of 

the key metrics shown on each label. Two questions were asked for each label pair: which was “better” 

for a short distance (20-30 miles), and which was “better” for a long distance (120 miles). 

The results indicate large differences in the proportion of “correct” answers from question to question, 

as either the driving distance or the vehicle technologies changed. Limited understanding of advanced

technology vehicles may contribute to incorrect responses to these questions. The differences in 

“correct” answers across label designs in response to any individual question are much smaller than the 

differences from question to question. 

Pair #1

Key Metrics:

• Vehicle A: Gasoline, 30 mpg, $1400 annual fuel cost 

• Vehicle B: Electric, range 100 miles, 98 mpge, $616 annual fuel cost 

Understanding Q. 1: Which vehicle is better for a round-trip of 30 miles? 

Q: Which vehicle is better for a round-trip of 30 miles? * Label Type Crosstabulation

177 89 96 362

20.0% 11.6% 9.1% 13.4%

622 602 873 2097

70.1% 78.4% 83.1% 77.5%

88 77 81 246

9.9% 10.0% 7.7% 9.1%

887 768 1050 2705

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Both are equally good

Which vehicle is better

for a round-trip of 30

miles?

Total

Label 1 Label 2 Label 3

Label Type

Total
 

5 

The “correct” answer is B, due to the higher efficiency and lower operating costs of the electric vehicle. 

In this comparison, regardless of label design, respondents gave a high proportion of “correct ” answers. 

Average “correct” response was 77.5%, with the proportion of “correct” responses across label designs 

varying from 70% to 83%.5

Understanding Q. 2: Which vehicle is better for a round-trip of 120 miles? 

The “correct ” answer is A, because the range for the electric vehicle is less than the trip distance. 

In this comparison, all three labels produced a large proportion of “incorrect ” answers compared to the 

answers for the 30-mile range. Average “correct” response is 50.5%, with the proportion of “correct” 

responses across label designs varying from 48% to 52%.6

Pair #2

Key Metrics:

• Vehicle A: Extended-range electric (EREV): 

o All-electric: range 30 miles, 90 mpge, $672 annual fuel cost 

o Extended range: 32 mpg, $1,313 annual fuel cost 

• Vehicle B: Plug-in hybrid electric (PHEV): 

o Blended: range 30 miles, 65 mpge, $734 annual fuel cost 

o Extended range: 54 mpg, $778 annual fuel cost 

Understanding Q. 3: Which vehicle is better for a round-trip of 20 miles? 

 

5

 Statistically significant: Cramer’s V = .132, p = .000 

6

 Statistically not significant: Cramer’s V = .037, p = .154 

Q: Which vehicle is better for a round-trip of 120 miles? * Label Type Crosstabulation

468 402 512 1382

51.5% 52.4% 48.2% 50.5%

378 308 483 1169

41.6% 40.2% 45.5% 42.7%

62 57 67 186

6.8% 7.4% 6.3% 6.8%

908 767 1062 2737

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Both are equally good

Which vehicle is better

for a round-trip of 120

miles?

Total

Label 1 Label 2 Label 3

Label Type

Total
 

6 

The agencies identified the “correct ” answer as A since both vehicles will operate in the mode using 

electricity, and the EREV is more fuel-efficient and less costly to operate in that range. 

In this comparison, all three labels produced a large proportion of “incorrect” answers. Average 

“correct” response is 45.5%, with the proportion of “correct” responses across label designs varying 

from 39% to 52%.7

 

Understanding Q. 4: Which vehicle is better for a round-trip of 120 miles? 

The “correct” answer is B, based on a weighted average of fuel costs for the two modes that would be 

used over the distance. The PHEV’s gasoline mode is sufficiently more efficient than that for the EREV to 

outweigh the higher efficiency of the EREV for the mode using electricity. 

In this comparison, all three labels produced a majority of “correct ” answers. Average “correct” 

response is 55.5%, with the proportion of “correct” responses across label designs varying from 53% to

60%.8 

Pair #3

Key Metrics

• Vehicle A: Extended-range electric (EREV): 

 

7

 Statistically significant: Cramer’s V = .104, p = .000 

8

 Statistically significant: Cramer’s V = .062, p = .005 

Q: Which vehicle is better for a round-trip of 20 miles? * Label Type Crosstabulation

354 395 488 1237

38.9% 52.1% 46.3% 45.5%

322 202 290 814

35.4% 26.6% 27.5% 29.9%

233 161 275 669

25.6% 21.2% 26.1% 24.6%

909 758 1053 2720

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Both are equally good

Which vehicle is better

for a round-trip of 20

miles?

Total

Label 1 Label 2 Label 3

Label Type

Total

Q: Which vehicle is better for a round-trip of 120 miles? * Label Type Crosstabulation

223 176 314 713

25.0% 23.2% 30.0% 26.4%

470 457 570 1497

52.6% 60.3% 54.4% 55.5%

200 125 164 489

22.4% 16.5% 15.6% 18.1%

893 758 1048 2699

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Both are equally good

Which vehicle is better

for a round-trip of 120

miles?

Total

Label 1 Label 2 Label 3

Label Type

Total
 

7 

o All-electric: range 40 miles, 90 mpge, $672 annual fuel cost 

o Extended range: 54 mpg, $778 annual fuel cost 

• Vehicle B: Electric, range 90 miles, 119 mpge, $508 annual fuel cost 

Understanding Q. 5: Which vehicle is better for a round-trip of 30 miles? 

The “correct ” answer is B, due to the greater efficiency and lower operating cost for the electric 

vehicle. 

In this comparison, all three labels produced a solid majority of “correct ” answers. Average “correct” 

response is 61%, with the proportion of “correct” responses across label designs varying from 57% to 

65%.9 

Understanding Q. 6: Which vehicle is better for a round-trip of 120 miles? 

The “correct ” answer is A, because the range for the electric vehicle is shorter than the trip length. 

In this comparison, all three labels produced a large proportion of “incorrect ” answers. Average 

“correct” response is 49%, with the proportion of “correct” responses across label designs varying from 

45% to 54%.10 

 

9

 Statistically significant: Cramer’s V = .064, p = .004 

10 Statistically significant: Cramer’s V = .074, p = .001 

Q: Which vehicle is better for a round-trip of 30 miles? * Label Type Crosstabulation

190 125 206 521

20.9% 16.4% 19.8% 19.2%

521 497 623 1641

57.4% 65.3% 59.8% 60.6%

196 139 213 548

21.6% 18.3% 20.4% 20.2%

907 761 1042 2710

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Both are equally good

Which vehicle is better

for a round-trip of 30

miles?

Total

Label 1 Label 2 Label 3

Label Type

Total

Q: Which vehicle is better for a round-trip of 120 miles? * Label Type Crosstabulation

429 411 469 1309

48.2% 54.2% 45.1% 48.7%

329 272 477 1078

37.0% 35.9% 45.9% 40.1%

132 75 94 301

14.8% 9.9% 9.0% 11.2%

890 758 1040 2688

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Both are equally good

Which vehicle is better

for a round-trip of 120

miles?

Total

Label 1 Label 2 Label 3

Label Type

Total
 

8 

What parts of the label did respondents use? 

Respondents were then asked what parts of the label they had used in making their choices. Based on 

the table below, the following three metrics were used most often: 

• Fuel economy (especially on labels 3 and 2) 

• Vehicle range (especially on labels 2 and 3) 

• Gasoline and/or electricity consumption (similarly on all labels) 

Regression results (presented in Appendix 2) provide these additional observations. 

Explanatory variables that tended to increase the likelihood of identifying the “correct” answer include: 

 Fewer than 5 licensed drivers in the household 

 Being male 

 Not being the fastest adopter of new technology 

More education 

Having 5 or more household vehicles 

 

These results, with the exception of “Male,” are inconsistent across the regression results: that is, they 

are not statistically significantly different from zero for all the questions. 

The classes of vehicles people considered buying appear to have some explanatory power as well. For 

instance, people who considered purchasing compact cars appear to have a higher likelihood of 

answering “correctly.” These vehicle class variables may be serving as proxies for some personal 

characteristics not picked up in the other demographic variables. 

Q: What label information did you use in deciding which vehicle you would purchase in the previous questions?

(Multiple responses allowed; Percents add up to more than 100%)

416 38.6% 338 38.7% 481 42.7%

220 20.4% 291 33.3% 307 27.2%

88 8.2% 86 9.8% 144 12.8%

464 43.0% 490 56.1% 651 57.8%

172 16.0% 144 16.5% 176 15.6%

553 53.1% 551 63.0% 769 68.2%

Gasoline and/or electricity consumption

Gasoline and/or electricity cost

Environmental impact

Vehicle range

Rating information

Fuel economy

Count %

Label Type 1

Count %

Label Type 2

Count %

Label Type 3
 

9 

Topline ‘Selection’ Question Results 

To test whether the labels produced variation in people’s selections of vehicle purchases, respondents 

saw pairs of labels for hypothetical vehicles (see Appendix 1, Selection Questions (SQ) 1-4). They were 

asked: 

Assuming the same make and model of vehicle for both labels above and assuming that both 

vehicles met all your other requirements (including size, reliability, comfort, performance, 

appearance, and safety) and are identical in purchase price, which vehicle would you purchase 

when you consider your typical travel pattern? 

 Because driving patterns of respondents were distributed randomly across the label designs, 

differences in responses across label designs are expected to be due to the label designs. In these 

questions there is no correct answer. Respondents identify their preferred vehicles based on their own 

decision factors. 

In all four comparisons, the majority of respondents selected the vehicle with projected higher fuel cost 

savings or lower fuel costs. Those who saw either Label 1 or (in 2 of the 4 regressions) Label 3 chose the 

vehicle with lower projected fuel costs and higher fuel savings more often than those who saw Label 2.

Regression results in Appendix 2 show that, in 3 of the 4 comparisons, respondents who drove fewer 

miles per day had a greater tendency to select the vehicle with a lower-cost short range. This result

suggests that people did think about daily driving patterns when making their choices. 

Below we have presented the results from each label pair, preceded by a brief description of some of 

the key metrics shown on each label. 

Pair #1

• Vehicle A: Gasoline, 46 mpg, $913 annual fuel cost

• Vehicle B: Extended-range electric: 

o All-electric: range 20 miles, 98 mpge, $618 annual fuel cost 

o Extended range: 28 mpg, $1,500 annual fuel cost 

Selection Q. 1: 

Q: Assuming the same make and model of vehicle for both labels above and assuming that both vehicles met all your

other requirements (including size, reliability, comfort, performance, appearance, and safety) and are identical in purchase

price, which vehicle would you purchase when you consider your typical travel pattern? * Label Type Crosstabulation

631 434 637 1702

69.8% 57.9% 61.8% 63.4%

157 224 258 639

17.4% 29.9% 25.0% 23.8%

116 91 135 342

12.8% 12.1% 13.1% 12.7%

904 749 1030 2683

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Equally likely to

purchase either vehicle

Which vehicle would you

purchase when you

consider your typical

travel pattern?

Total

Label 1 Label 2 Label 3

Label Type

Total
 

10 

In this comparison, regardless of label design, most respondents chose the conventional gasoline engine 

vehicle. Average proportion choosing the gasoline vehicle is 63%, with the proportion choosing the 

gasoline vehicle across label designs varying from 58% to 70%.11

 

Regression results for this comparison (see Appendix 2) suggest the following factors tend to increase

the likelihood of choosing the gasoline vehicle: 

 A larger share of highway driving 

 Being slow to adopt new technologies 

Pair #2

• Vehicle A: Gasoline, 28 mpg, $1,500 annual fuel cost 

• Vehicle B: Electric, range 85 miles, 123 mpge, $490 annual fuel cost 

Selection Q. 2: 

In this comparison, regardless of label design, most respondents chose the electric vehicle. Average 

proportion choosing the electric vehicle is 65%, with the proportion choosing the electric vehicle across 

label designs varying from 60% to 68%.12 

Regression results for this comparison (see Appendix 2) suggest the following factors tend to increase

the likelihood of choosing the electric vehicle: 

 Being under age 65 

 Driving less than 70 miles on a daily basis 

 Ranking the fuel economy label very highly in the decision process 

Pair #3

• Vehicle A: Extended-range electric (EREV): 

o All-electric: range 32 miles, 89 mpge, $679 annual fuel cost 

o Extended range: 31 mpg, $1,355 annual fuel cost 

• Vehicle B: Electric, range 80 miles, 121 mpge, $501 annual fuel cost 

 

11 Statistically significant: Cramer’s V = .084, p = .000 

12 Statistically significant: Cramer’s V = .050, p = .009 

Q Assuming the same make and model of vehicle for both labels above and assuming that both vehicles met all your

other requirements (including size, reliability, comfort, performance, appearance, and safety) and are identical in purchase

price, which vehicle would you purchase when you consider your typical travel pattern? * Label Type Crosstabulation

229 234 267 730

25.3% 31.4% 25.9% 27.2%

612 446 690 1748

67.7% 59.8% 67.0% 65.2%

63 66 73 202

7.0% 8.8% 7.1% 7.5%

904 746 1030 2680

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Equally likely to

purchase either vehicle

Which vehicle would you

purchase when you

consider your typical

travel pattern?

Total

Label 1 Label 2 Label 3

Label Type

Total
 

11 

Selection Q. 3: 

In this comparison, there is more of an even split between the two vehicle types, with half overall 

choosing the Electric Vehicle (50%) and another 11% indicating that they would be equally likely to 

purchase either vehicle. Average proportion choosing the electric vehicle is 50%, with the proportion 

choosing the electric vehicle across label designs varying from 44% to 53%.13

 

Regression results for this comparison (see Appendix 2) suggest the following factors tend to increase

the likelihood of choosing the electric vehicle: 

 Having 1 vehicle in their household 

 Driving less than 70 miles on a typical day

Pair #4

• Vehicle A: Extended-range electric: 

o All-electric: range 30 miles, 90 mpge, $672 annual fuel cost 

o Extended range: 32 mpg, $1,313 annual fuel cost 

• Vehicle B: Plug-in hybrid electric: 

o Blended: range 30 miles, 65 mpge, $734 annual fuel cost 

o Extended range: 54 mpg, $778 annual fuel cost 

Selection Q. 4: 

 

13 Statistically significant: Cramer’s V = .069, p = .000 

Q: Assuming the same make and model of vehicle for both labels above and assuming that both vehicles met all your

other requirements (including size, reliability, comfort, performance, appearance, and safety) and are identical in purchase

price, which vehicle would you purchase when you consider your typical travel pattern? * Label Type Crosstabulation

353 334 359 1046

39.0% 45.0% 35.0% 39.1%

475 324 548 1347

52.5% 43.7% 53.4% 50.4%

77 84 120 281

8.5% 11.3% 11.7% 10.5%

905 742 1027 2674

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Equally likely to

purchase either vehicle

Which vehicle would you

purchase when you

consider your typical

travel pattern?

Total

Label 1 Label 2 Label 3

Label Type

Total

Q: Assuming the same make and model of vehicle for both labels above and assuming that both vehicles met all your

other requirements (including size, reliability, comfort, performance, appearance, and safety) and are identical in purchase

price, which vehicle would you purchase when you consider your typical travel pattern? * Label Type Crosstabulation

210 164 262 636

23.3% 22.0% 25.4% 23.7%

532 450 593 1575

59.0% 60.5% 57.5% 58.8%

160 130 177 467

17.7% 17.5% 17.2% 17.4%

902 744 1032 2678

100.0% 100.0% 100.0% 100.0%

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Count

% within Label Type

Vehicle A

Vehicle B

Equally likely to

purchase either vehicle

Which vehicle would you

purchase when you

consider your typical

travel pattern?

Total

Label 1 Label 2 Label 3

Label Type

Total
 

12 

In this comparison, regardless of label design, most respondents chose the Plug-in Hybrid Electric 

Vehicle (PHEV). Average proportion choosing the PHEV is 59%, with the proportion choosing the PHEV 

across label designs varying from 58% to 61%.14

Regression results for this comparison (see Appendix 2) suggest the following factor tends to increase

the likelihood of choosing the PHEV: 

 Higher proportion of highway miles

What parts of the label did respondents use?

Respondents were then asked what parts of the label they had used in making their purchase selections.

Based on the table below, the following four metrics were used most often: 

• Fuel economy (especially on labels 3 and 2) 

• Vehicle range (especially on labels 2 and 3) 

• Gasoline and/or electricity cost (especially for label 3 and 2) 

• Gasoline and/or electricity consumption (especially for label 3) 

 

14 Statistically not significant: Cramer’s V = .023, p = .569 

Q: What label information did you use in deciding which vehicle you would purchase in the previous questions?

(Multiple responses allowed; Percents add up to more than 100%)

418 38.8% 359 41.1% 539 47.8%

362 33.6% 411 47.0% 552 49.0%

113 10.5% 131 15.0% 238 21.1%

439 40.7% 460 52.6% 594 52.7%

210 19.5% 202 23.1% 278 24.7%

571 53.0% 563 64.4% 742 65.8%

Gasoline and/or electricity consumption

Gasoline and/or electricity cost

Environmental impact

Vehicle range

Rating information

Fuel economy

Count %

Label Type 1

Count %

Label Type 2

Count %

Label Type 3
Appendix 1 

Labels Used in the Surveys 

 
UQ1 & UQ2: 

Label Type 1 

 
Label Type 2 
 

Label Type 3 
UQ3 & UQ4: 

Label Type 1 
 

Label Type 2 
 

Label Type 3 
UQ5 & UQ6: 

Label Type 1 
 

Label Type 2 
 

Label Type 3 
SQ1: 

Label Type 1 
 

Label Type 2 
 

Label Type 3 
SQ2: 

Label Type 1 
 

Label Type 2 
 

Label Type 3 
SQ3: 

Label Type 1 
 

Label Type 2 
 

Label Type 3 
SQ4: 

Label Type 1 
Label Type 2 
Label Type 3 
Appendix 2 

Regression Results 
Fuel Economy Label Models Dammen, Pozdena 

Technical Memo ECONorthwest

 Page 1 

Fuel Economy Label Survey Choice Models 

Technical Memorandum 

Label Understanding and Vehicle Selection Models 

Interpretation of the coefficients and odds ratios from the logistic regressions ________________ 2 

Label Understanding Model Results ________________________________________________________ 5 

Vehicle Preference (Selection) Model Results _____________________________________________ 14 
Fuel Economy Label Models Dammen, Pozdena 

Technical Memo ECONorthwest

 Page 2 

Interpretation of the Coefficients and Odds Ratios from Logistic 

Regressions 

This technical memorandum presents the preliminary results of the modeling for the 

EPA/NHTSA Fuel Economy Label Design survey. From the Fuel Economy Label survey 

data, the presented results are from the discrete choice modeling of the following: 

1. Respondent label understanding responses (Understanding Questions 1-6) 

2. Respondent vehicle preference/likely to purchase (Selection Questions 1-4) 

Logit (choice) models are estimated with the binary (e.g., 0 or 1) choice variable (the 

answer to either the understanding or vehicle choice questions) on the left-hand side of 

the model. The label design indicator variables and a series of demographic and other 

respondent survey responses are on the right-hand side (RHS), as either the control or 

predictor variables. 

The logit model is the appropriate model when the variable of interest is a binary 

variable (e.g., the variable takes on values of 0 or 1). The logit model predicts the 

probability of the dependent variable taking on a value equal to 1, given the predictor 

and control variables of the model. 

The probability of the outcome, and the odds ratio of the outcome are key concepts 

for correctly interpreting the results from these models. 

For the label understanding choice models: 

 Probability is defined as the probability that the respondent selects the correct 

answer. E.g., p is the probability that the respondent answers correctly, or 

p(correct=1) 

 The ‘odds’ of a correct answer is the ratio of the probability of a correct answer 

(p), over the probability of the incorrect answer (1-p), or: p/(1-p). 

 And the log odds ratio, or “logit” is then: LN(p/(1-p)) 

 The “Both are equally good” responses to Understanding Questions 1-6 were 

categorized as “incorrect” for the label understanding modeling. 

For the vehicle likely to purchase (selection) choice models: 

 Probability is defined as the probability that the respondent selects the first 

vehicle (i.e., Vehicle A). To interpret the results from the vehicle preference 

models, it is important to consider the model results with respect to the two 

vehicles being compared and the vehicle that corresponds to Vehicle A (e.g., 

p(vehicle A=1)). 

 The “Equally likely to purchase either vehicle” responses were randomly assigned 

to Vehicle A or Vehicle B, using a uniform distribution. 

Simple Numerical Example of an Odds Ratio 

Prior to Understanding Questions 1 and 2 in the survey, respondents are shown fuel 

economy labels for a gasoline vehicle and a dual fuel electric vehicle. Understanding 
Fuel Economy Label Models Dammen, Pozdena 

Technical Memo ECONorthwest

 Page 3 

Question 1 then asks respondents which vehicle is better for a 30-mile round-trip (the 

correct answer is the dual fuel electric). 

The frequency tabulation for the answers to Understanding Question 1 is shown in Table 

1. 

Table 1 ‘Correct’ and ‘Incorrect’ Frequency Tabulation for Understanding Question 1 

Understanding 

Question 1 

Frequency 

Correct 2,097 

Incorrect 608 

Total 2,705 

From this frequency tabulation of the answers to Understanding Question 1, we can 

calculate the following: 

 The probability of the respondent selecting the correct answer is: 

p = prob(correct=1)= 2097/2705 = 0.775 

 The odds of a correct answer are: 0.775/(1-0.775) = 3.449 

 The log odds is: log(3.45) = 1.238 

The calculated log odds is the same as the estimated coefficient on the constant term 

in a model without any other predictor variables: 

Table 2 Logistic Regression Results for Understanding Question 1, Constant Term Only 

Logistic regression Number of obs = 2705 

--------------------------------------------------------------------------------------------------------- 

 Question 1 | Coef. Std. Err. z P>|z| [95% Conf. Interval] 

-------------+------------------------------------------------------------------------------------------- 

 Constant | 1.238088 .0460609 26.88 0.000 1.14781 1.328366 

--------------------------------------------------------------------------------------------------------- 

This simple numerical example of the calculation of the odds ratio and the presentation 

of the logistic regression results for a model with only a constant term are intended to 

illustrate the basic interpretation of the odds ratio.1 As predictor variables are 

introduced to the model, the interpretation of the coefficients and odds ratio does not 

change in any fundamental way. 

 

1 This exposition is based on the explanation provided at: UCLA, Academic Technology Services, Statistical Consulting 

Group. FAQ: How do I interpret odds ratios in logistic regression?

http://www.ats.ucla.edu/stat/mult_pkg/faq/general/odds_ratio.htm (accessed October 9, 2010). 
Fuel Economy Label Models Dammen, Pozdena 

Technical Memo ECONorthwest

 Page 4 

Notably, we can make the following statements about the correct interpretation of the 

logistic regression results: 

 The estimated coefficients from the models represent the rate of change in the 

log odds ratio for the change in the predictor (RHS) variable. 

 These changes are interpreted relative to the default case for dichotomous RHS 

variables; and are interpreted for a one-unit change in the RHS variable in the 

case of continuous RHS variables. 

 From the above example, we can see that the odds ratio is an easy 

mathematical transformation and more intuitive way to interpret the model 

results. 

 For a given right-hand side variable, the odds ratio is the estimated effect on the 

odds ratio for the event for that predictor variable. Based on this explanation, we 

can make the following interpretations and conclusions about the coefficients 

and odds ratios: 

 An odds ratio of 1.5 is interpreted as the predictor variable being associated 

with the odds of a correct answer being 1 and 1/2 times more likely than the 

odds of the incorrect answer. 

 Negative coefficients from the model produce odds ratios of less than one, 

so a change in the right-hand side variable makes the outcome less likely to 

occur. 

Again, the coefficients from the logistic regression for dichotomous right-hand side 

variables are always interpreted relative to the default case. For example, if the 

coefficient on Male (gender) is 0.391 then using the odds ratio transformation of the 

coefficient, the odds ratio is 1.478. This indicates that the odds for a correct answer are 

147.8 percent for males than the odds for females. 

For a continuous right-hand side variable, the coefficient represented as the odds ratio 

is the effect of a 1-unit change in the variable on the difference in log odds. For 

example: for a one-unit increase in the share of miles in the city, we see a 100.7 percent 

increase in the odds of selecting the correct answer in the understanding choice 

models (or, of selecting vehicle A, in the case of the selection models). (Note than 

interpretation of negative odds ratios are conceptually slightly more complex.) 

Thus, each exponentiated coefficient is either the ratio of two odds (e.g., for 

dichotomous RHS variables); or the change in odds (continuous) for a unit increase in 

the corresponding RHS variable holding other variables at constant value(s). 

The following pages present the model estimation results for the choice models. The 

results contain both the estimated coefficient and the odds ratio. The z-statistic is 

displayed in parentheses underneath the estimated coefficient. The z-statistic indicates 

whether the estimated coefficient is statistically different from zero. 
EPA Fuel Economy Label Choice 

Models

Independent Variables Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Constant -0.048 0.953 0.247 1.280

(0.060) (0.340)

Label 1 Dummy Variable -0.709 0.492 0.183 1.201

(5.65)** (1.770)

Label 2 Dummy Variable -0.311 0.733 0.316 1.372

(2.30)* (2.91)**

City Miles Share of Miles (e.g., 1-100) -0.002 0.998 -0.004 0.996

(0.630) (1.830)

Age 18-24 -0.258 0.773 -0.610 0.543

(0.690) (1.880)

Age 25-34 -0.189 0.828 -0.238 0.788

(0.730) (1.150)

Age 35-44 -0.237 0.789 -0.090 0.914

(0.910) (0.440)

Age 45-54 -0.369 0.691 0.218 1.244

(1.500) (1.110)

Age 55-64 0.103 1.108 0.049 1.050

(0.420) (0.260)

Less than High School -0.822 0.440 -1.016 0.362

(1.030) (1.320)

High School -0.490 0.613 -0.653 0.520

(2.30)* (3.51)**

Some College -0.339 0.712 -0.219 0.803

(2.23)* (1.780)

College -0.236 0.790 0.029 1.029

(1.690) (0.260)

Household Income Less Than $15k 0.150 1.162 -0.316 0.729

(0.300) (0.680)

Household Income $15-$25k -0.714 0.490 -0.634 0.530

(1.610) (1.370)

Household Income $25-$50k 0.010 1.010 0.042 1.043

(0.040) (0.210)

Household Income $50-$75k 0.345 1.412 0.142 1.153

(1.770) (0.890)

Household Income $75-$100k 0.179 1.196 0.255 1.290

(1.090) (1.840)

Household Income $100-$125k 0.356 1.428 0.066 1.068

(2.12)* (0.480)

Household Income $125-$150k 0.393 1.481 0.195 1.215

(2.04)* (1.250)

Household Size=1 0.677 1.968 -0.458 0.633

(1.000) (0.780)

Household Size=2 -0.045 0.956 -0.357 0.700

(0.090) (0.770)

Household Size=3 0.341 1.406 -0.155 0.856

(0.720) (0.340)

Household Size=4 0.279 1.322 -0.342 0.710

(0.590) (0.750)

Household Size=5 0.356 1.428 -0.306 0.736

(0.740) (0.660)

Household Size=6 0.967 2.630 -0.410 0.664

(1.650) (0.790)

Correctly identified vehicle A, a 

gasoline vehicle, as better for 120-mile 

round-trip, compared to vehicle B, an 

electric vehicle.

Understanding Questions 1 & 2

Gasoline Vehicle Label Compared With Electric Vehicle Label

(Correct Answer=1, Incorrect Answer=0)

Correctly identified vehicle B, an 

electric vehicle as the better vehicle for 

a 30-mile round-trip, compared to 

vehicle A, a gasoline vehicle.
EPA Fuel Economy Label Choice 

Models

Independent Variables Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Correctly identified vehicle A, a 

gasoline vehicle, as better for 120-mile 

round-trip, compared to vehicle B, an 

electric vehicle.

Understanding Questions 1 & 2

Gasoline Vehicle Label Compared With Electric Vehicle Label

(Correct Answer=1, Incorrect Answer=0)

Correctly identified vehicle B, an 

electric vehicle as the better vehicle for 

a 30-mile round-trip, compared to 

vehicle A, a gasoline vehicle.

Household Vehicles=1 -0.614 0.541 -0.279 0.757

(1.270) (0.700)

Household Vehicles=2 -0.144 0.866 -0.507 0.602

(0.540) (2.23)*

Household Vehicles=3 -0.126 0.882 -0.457 0.633

(0.480) (2.05)*

Household Vehicles=4 -0.233 0.792 -0.397 0.672

(0.840) (1.630)

Licensed Drivers in Household=1 1.512 4.536 1.423 4.150

(2.32)* (2.64)**

Licensed Drivers in Household=2 1.033 2.809 1.160 3.190

(2.57)* (3.10)**

Licensed Drivers in Household=3 0.957 2.604 1.239 3.452

(2.43)* (3.36)**

Licensed Drivers in Household=4 0.828 2.289 1.209 3.350

(2.07)* (3.21)**

Male 0.446 1.562 0.393 1.481

(3.89)** (4.24)**

Daily Miles Driven, Less than 20 0.187 1.206 -0.264 0.768

(0.520) (0.860)

Daily Miles Driven, 20-30 0.123 1.131 -0.293 0.746

(0.340) (0.950)

Daily Miles Driven, 31-40 0.099 1.104 -0.490 0.613

(0.270) (1.570)

Daily Miles Driven, 41-50 0.216 1.241 -0.092 0.912

(0.570) (0.280)

Daily Miles Driven, 51-60 0.378 1.459 -0.278 0.757

(0.960) (0.850)

Daily Miles Driven, 61-70 -0.244 0.783 -0.637 0.529

(0.590) (1.760)

Daily Miles Driven, 71-80 0.297 1.346 -0.630 0.533

(0.640) (1.660)

Daily Miles Driven, 81-90 -1.001 0.368 -0.420 0.657

(2.10)* (0.960)

Daily Miles Driven, 91-100 0.294 1.342 -0.173 0.841

(0.590) (0.430)

Importance of Fuel Economy rated 2 

(7 =very important) 0.425 1.530 -0.268 0.765

(0.830) (0.580)

Importance of Fuel Economy rated 3

(7 =very important) 0.066 1.068 -0.730 0.482

(0.140) (1.680)

Importance of Fuel Economy rated 4

(7 =very important) 0.445 1.560 -0.574 0.563

(0.980) (1.400)

Importance of Fuel Economy rated 5

(7 =very important) 0.488 1.629 -0.426 0.653

(1.070) (1.040)

Importance of Fuel Economy rated 6

(7 =very important) 0.509 1.664 -0.644 0.525

(1.100) (1.540)

Importance of Fuel Economy rated 7

(7 =very important) 0.233 1.262 -0.848 0.428

(0.490) (1.98)*
EPA Fuel Economy Label Choice 

Models

Independent Variables Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Correctly identified vehicle A, a 

gasoline vehicle, as better for 120-mile 

round-trip, compared to vehicle B, an 

electric vehicle.

Understanding Questions 1 & 2

Gasoline Vehicle Label Compared With Electric Vehicle Label

(Correct Answer=1, Incorrect Answer=0)

Correctly identified vehicle B, an 

electric vehicle as the better vehicle for 

a 30-mile round-trip, compared to 

vehicle A, a gasoline vehicle.

Importance of Fuel Economy Label=2 0.144 1.155 0.213 1.237

(0.410) (0.730)

Importance of Fuel Economy Label=3 -0.072 0.931 0.142 1.153

(0.220) (0.520)

Importance of Fuel Economy Label=4 -0.232 0.793 -0.055 0.946

(0.760) (0.210)

Importance of Fuel Economy Label=5 -0.020 0.980 0.045 1.046

(0.060) (0.170)

Importance of Fuel Economy Label=6 0.209 1.232 0.124 1.132

(0.650) (0.460)

Importance of Fuel Economy Label=7 0.277 1.319 -0.047 0.954

(0.810) (0.170)

Vehicles considered=Sports Car -0.066 0.936 -0.321 0.725

(0.400) (2.29)*

Vehicles considered=Subcompact Car -0.052 0.949 0.423 1.527

(0.220) (2.24)*

Vehicles considered=Compact Car 0.330 1.391 0.271 1.311

(2.13)* (2.20)*

Vehicles considered=Midsized Car 0.161 1.175 0.093 1.097

(1.400) (1.000)

Vehicles considered=Large Car -0.010 0.990 0.162 1.176

(0.060) (1.080)

Vehicles considered=Station Wagon -0.385 0.680 -0.274 0.760

(1.600) (1.310)

Vehicles considered=SUV 0.108 1.114 -0.078 0.925

(0.930) (0.810)

Vehicles considered=Crossover 0.038 1.039 0.417 1.517

(0.300) (3.99)**

Vehicles considered=Pickup Truck 0.004 1.004 -0.063 0.939

(0.020) (0.440)

Vehicles considered=Mini-Van 0.157 1.170 0.187 1.206

(0.800) (1.170)

Vehicles considered=Van -1.067 0.344 -0.820 0.440

(2.39)* (1.890)

Vehicles considered=Other 0.707 2.028 0.841 2.319

(1.750) (2.86)**

Early Adopter=2 (1 is first to adopt) 0.077 1.080 -0.274 0.760

(0.310) (1.310)

Early Adopter=3 (1 is first to adopt) 0.260 1.297 0.073 1.076

(1.080) (0.370)

Early Adopter=4 (1 is first to adopt) -0.062 0.940 0.120 1.127

(0.270) (0.610)

Early Adopter=5 (1 is first to adopt) -0.035 0.966 -0.012 0.988

(0.150) (0.060)

Early Adopter=6 (1 is first to adopt) 0.007 1.007 0.020 1.020

(0.030) (0.090)

Early Adopter=7 (1 is first to adopt) -0.585 0.557 -0.306 0.736

(1.820) (1.040)

Observa(ons 2358 2382

Absolute/value/of/z/sta(s(cs/in/parentheses

*/significant/at/5%;/**/significant/at/1%

+/significant/at/10%;/**/significant/at/5%;/*/significant/at/1%
EPA Fuel Economy Label Choice 

Models

Independent Variables

Constant

Label 1 Dummy Variable

Label 2 Dummy Variable

City Miles Share of Miles (e.g., 1-100)

Age 18-24

Age 25-34

Age 35-44

Age 45-54

Age 55-64

Less than High School

High School

Some College

College

Household Income Less Than $15k

Household Income $15-$25k

Household Income $25-$50k

Household Income $50-$75k

Household Income $75-$100k

Household Income $100-$125k

Household Income $125-$150k

Household Size=1

Household Size=2

Household Size=3

Household Size=4

Household Size=5

Household Size=6

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

-0.840 0.432 -1.132 0.322

(1.210) (1.620)

-0.326 0.722 -0.050 0.951

(3.21)** (0.500)

0.256 1.292 0.273 1.314

(2.42)* (2.53)*

0.001 1.001 -0.001 0.999

(0.350) (0.610)

0.032 1.033 0.421 1.523

(0.100) (1.340)

0.205 1.228 0.325 1.384

(1.000) (1.570)

0.004 1.004 0.114 1.121

(0.020) (0.550)

0.004 1.004 0.139 1.149

(0.020) (0.710)

0.077 1.080 0.369 1.446

(0.410) (1.950)

-0.110 0.896 -0.526 0.591

(0.140) (0.690)

-0.190 0.827 0.143 1.154

(1.050) (0.790)

-0.112 0.894 0.097 1.102

(0.920) (0.790)

-0.060 0.942 0.031 1.031

(0.550) (0.280)

0.191 1.210 -0.404 0.668

(0.450) (0.900)

-1.310 0.270 -0.088 0.916

(2.68)** (0.210)

-0.163 0.850 -0.023 0.977

(0.810) (0.110)

0.044 1.045 -0.021 0.979

(0.280) (0.130)

-0.074 0.929 0.032 1.033

(0.550) (0.230)

0.099 1.104 0.192 1.212

(0.720) (1.390)

0.164 1.178 0.042 1.043

(1.080) (0.270)

0.469 1.598 -0.421 0.656

(0.820) (0.730)

0.187 1.206 -0.057 0.945

(0.410) (0.130)

0.330 1.391 -0.045 0.956

(0.730) (0.100)

0.308 1.361 0.071 1.074

(0.680) (0.160)

0.354 1.425 0.142 1.153

(0.780) (0.320)

0.449 1.567 -0.107 0.899

(0.880) (0.210)

Correctly identified vehicle A, a Dual 

Fuel PHEV as the better vehicle for a 20-

mile round-trip compared to vehicle B, 

also a Dual Fuel PHEV.

Understanding Questions 3 & 4

Comparison of the Labels for two Dual Fuel Plug-in Hybrid Electric Vehicles

(Correct Answer=1, Incorrect Answer=0)

Correctly identified vehicle B, a Dual 

Fuel PHEV as the better vehicle for a 

120-mile round-trip compared to 

vehicle B, also a Dual Fuel PHEV.
EPA Fuel Economy Label Choice 

Models

Independent Variables

Household Vehicles=1

Household Vehicles=2

Household Vehicles=3

Household Vehicles=4

Licensed Drivers in Household=1

Licensed Drivers in Household=2

Licensed Drivers in Household=3

Licensed Drivers in Household=4

Male

Daily Miles Driven, Less than 20

Daily Miles Driven, 20-30

Daily Miles Driven, 31-40

Daily Miles Driven, 41-50

Daily Miles Driven, 51-60

Daily Miles Driven, 61-70

Daily Miles Driven, 71-80

Daily Miles Driven, 81-90

Daily Miles Driven, 91-100

Importance of Fuel Economy rated 2 

(7 =very important)

Importance of Fuel Economy rated 3

(7 =very important)

Importance of Fuel Economy rated 4

(7 =very important)

Importance of Fuel Economy rated 5

(7 =very important)

Importance of Fuel Economy rated 6

(7 =very important)

Importance of Fuel Economy rated 7

(7 =very important)

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Correctly identified vehicle A, a Dual 

Fuel PHEV as the better vehicle for a 20-

mile round-trip compared to vehicle B, 

also a Dual Fuel PHEV.

Understanding Questions 3 & 4

Comparison of the Labels for two Dual Fuel Plug-in Hybrid Electric Vehicles

(Correct Answer=1, Incorrect Answer=0)

Correctly identified vehicle B, a Dual 

Fuel PHEV as the better vehicle for a 

120-mile round-trip compared to 

vehicle B, also a Dual Fuel PHEV.

-0.328 0.720 -0.082 0.921

(0.840) (0.210)

-0.213 0.808 -0.243 0.784

(0.970) (1.090)

-0.264 0.768 -0.237 0.789

(1.230) (1.090)

-0.351 0.704 -0.118 0.889

(1.500) (0.500)

0.131 1.140 0.535 1.707

(0.250) (1.010)

-0.203 0.816 0.279 1.322

(0.570) (0.770)

-0.360 0.698 0.216 1.241

(1.030) (0.610)

-0.269 0.764 -0.172 0.842

(0.750) (0.470)

0.281 1.324 0.513 1.670

(3.11)** (5.58)**

0.169 1.184 0.036 1.037

(0.570) (0.120)

0.221 1.247 -0.064 0.938

(0.740) (0.210)

0.150 1.162 -0.100 0.905

(0.500) (0.330)

0.073 1.076 -0.250 0.779

(0.230) (0.800)

0.188 1.207 -0.206 0.814

(0.600) (0.650)

0.295 1.343 -0.085 0.919

(0.840) (0.240)

0.046 1.047 -0.314 0.731

(0.120) (0.850)

0.202 1.224 0.248 1.281

(0.480) (0.570)

-0.030 0.970 -0.357 0.700

(0.080) (0.900)

0.453 1.573 0.668 1.950

(1.000) (1.460)

0.352 1.422 0.453 1.573

(0.820) (1.050)

0.383 1.467 0.495 1.640

(0.950) (1.220)

0.315 1.370 0.686 1.986

(0.780) (1.680)

0.481 1.618 0.582 1.790

(1.170) (1.400)

0.306 1.358 0.573 1.774

(0.720) (1.350)
EPA Fuel Economy Label Choice 

Models

Independent Variables

Importance of Fuel Economy Label=2

Importance of Fuel Economy Label=3

Importance of Fuel Economy Label=4

Importance of Fuel Economy Label=5

Importance of Fuel Economy Label=6

Importance of Fuel Economy Label=7

Vehicles considered=Sports Car

Vehicles considered=Subcompact Car

Vehicles considered=Compact Car

Vehicles considered=Midsized Car

Vehicles considered=Large Car

Vehicles considered=Station Wagon

Vehicles considered=SUV

Vehicles considered=Crossover

Vehicles considered=Pickup Truck

Vehicles considered=Mini-Van

Vehicles considered=Van

Vehicles considered=Other

Early Adopter=2 (1 is first to adopt)

Early Adopter=3 (1 is first to adopt)

Early Adopter=4 (1 is first to adopt)

Early Adopter=5 (1 is first to adopt)

Early Adopter=6 (1 is first to adopt)

Early Adopter=7 (1 is first to adopt)

Observa(ons

Absolute/value/of/z/sta(s(cs/in/parentheses

*/significant/at/5%;/**/significant/at/1%

+/significant/at/10%;/**/significant/at/5%;/*/significant/at/1%

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Correctly identified vehicle A, a Dual 

Fuel PHEV as the better vehicle for a 20-

mile round-trip compared to vehicle B, 

also a Dual Fuel PHEV.

Understanding Questions 3 & 4

Comparison of the Labels for two Dual Fuel Plug-in Hybrid Electric Vehicles

(Correct Answer=1, Incorrect Answer=0)

Correctly identified vehicle B, a Dual 

Fuel PHEV as the better vehicle for a 

120-mile round-trip compared to 

vehicle B, also a Dual Fuel PHEV.

0.311 1.365 -0.143 0.867

(1.090) (0.490)

-0.071 0.931 -0.163 0.850

(0.270) (0.600)

-0.149 0.862 -0.253 0.776

(0.590) (0.980)

-0.107 0.899 -0.266 0.766

(0.420) (1.030)

-0.046 0.955 -0.152 0.859

(0.170) (0.570)

0.013 1.013 -0.284 0.753

(0.050) (1.000)

-0.186 0.830 -0.153 0.858

(1.340) (1.110)

0.022 1.022 -0.067 0.935

(0.120) (0.360)

0.206 1.229 0.213 1.237

(1.720) (1.750)

0.048 1.049 -0.002 0.998

(0.520) (0.020)

0.133 1.142 0.115 1.122

(0.910) (0.770)

0.265 1.303 0.674 1.962

(1.290) (2.96)**

0.049 1.050 0.112 1.119

(0.520) (1.170)

0.043 1.044 0.031 1.031

(0.420) (0.300)

0.042 1.043 -0.035 0.966

(0.300) (0.240)

0.068 1.070 0.057 1.059

(0.440) (0.350)

-0.120 0.887 0.795 2.214

(0.290) (1.730)

-0.277 0.758 -0.136 0.873

(0.980) (0.490)

0.125 1.133 0.349 1.418

(0.610) (1.700)

0.302 1.353 0.638 1.893

(1.540) (3.22)**

0.124 1.132 0.424 1.528

(0.640) (2.19)*

0.178 1.195 0.462 1.587

(0.890) (2.32)*

0.054 1.055 0.376 1.456

(0.240) (1.680)

-0.181 0.834 0.002 1.002

(0.620) (0.010)

2389 2376
EPA Fuel Economy Label Choice 

Models

Independent Variables

Constant

Label 1 Dummy Variable

Label 2 Dummy Variable

City Miles Share of Miles (e.g., 1-100)

Age 18-24

Age 25-34

Age 35-44

Age 45-54

Age 55-64

Less than High School

High School

Some College

College

Household Income Less Than $15k

Household Income $15-$25k

Household Income $25-$50k

Household Income $50-$75k

Household Income $75-$100k

Household Income $100-$125k

Household Income $125-$150k

Household Size=1

Household Size=2

Household Size=3

Household Size=4

Household Size=5

Household Size=6

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

0.087 1.091 -0.555 0.574

(0.120) (0.800)

-0.120 0.887 0.091 1.095

(1.180) (0.880)

0.282 1.326 0.471 1.602

(2.56)* (4.35)**

0.001 1.001 -0.003 0.997

(0.650) (1.320)

-0.289 0.749 -0.391 0.676

(0.900) (1.220)

-0.206 0.814 -0.377 0.686

(0.960) (1.810)

-0.171 0.843 -0.291 0.748

(0.800) (1.400)

-0.361 0.697 -0.130 0.878

(1.780) (0.660)

-0.152 0.859 -0.140 0.869

(0.770) (0.740)

-0.757 0.469 -0.746 0.474

(0.970) (0.970)

0.055 1.057 -0.593 0.553

(0.300) (3.19)**

-0.122 0.885 -0.231 0.794

(0.990) (1.890)

0.041 1.042 -0.022 0.978

(0.360) (0.200)

-1.050 0.350 -0.390 0.677

(2.40)* (0.880)

-0.863 0.422 -0.310 0.733

(2.12)* (0.740)

-0.186 0.830 -0.317 0.728

(0.910) (1.530)

0.093 1.097 -0.126 0.882

(0.570) (0.790)

-0.046 0.955 0.050 1.051

(0.330) (0.360)

-0.046 0.955 0.001 1.001

(0.330) 0.000

0.047 1.048 -0.020 0.980

(0.300) (0.130)

-0.159 0.853 -0.385 0.680

(0.270) (0.660)

-0.386 0.680 -0.540 0.583

(0.820) (1.190)

-0.294 0.745 -0.373 0.689

(0.630) (0.830)

-0.267 0.766 -0.303 0.739

(0.570) (0.680)

-0.474 0.623 -0.403 0.668

(1.010) (0.890)

0.119 1.126 -0.550 0.577

(0.220) (1.080)

Correctly identified vehicle B, an 

Electric Vehicle as better for 30-mile 

round-trip compared to vehicle A, a 

Dual Fuel Extended Range Electric 

Vehicle.

Dual Fuel PHEV Vehicle Label Compared With an Electric Vehicle Label

(Correct Answer=1, Incorrect Answer=0)

Understanding Questions 5 & 6

Correctly identified vehicle A, a Dual 

Fuel Extended Range Electric Vehicle 

as better for 120-mile round-trip 

compared to vehicle B, an Electric 

Vehicle.
EPA Fuel Economy Label Choice 

Models

Independent Variables

Household Vehicles=1

Household Vehicles=2

Household Vehicles=3

Household Vehicles=4

Licensed Drivers in Household=1

Licensed Drivers in Household=2

Licensed Drivers in Household=3

Licensed Drivers in Household=4

Male

Daily Miles Driven, Less than 20

Daily Miles Driven, 20-30

Daily Miles Driven, 31-40

Daily Miles Driven, 41-50

Daily Miles Driven, 51-60

Daily Miles Driven, 61-70

Daily Miles Driven, 71-80

Daily Miles Driven, 81-90

Daily Miles Driven, 91-100

Importance of Fuel Economy rated 2 

(7 =very important)

Importance of Fuel Economy rated 3

(7 =very important)

Importance of Fuel Economy rated 4

(7 =very important)

Importance of Fuel Economy rated 5

(7 =very important)

Importance of Fuel Economy rated 6

(7 =very important)

Importance of Fuel Economy rated 7

(7 =very important)

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Correctly identified vehicle B, an 

Electric Vehicle as better for 30-mile 

round-trip compared to vehicle A, a 

Dual Fuel Extended Range Electric 

Vehicle.

Dual Fuel PHEV Vehicle Label Compared With an Electric Vehicle Label

(Correct Answer=1, Incorrect Answer=0)

Understanding Questions 5 & 6

Correctly identified vehicle A, a Dual 

Fuel Extended Range Electric Vehicle 

as better for 120-mile round-trip 

compared to vehicle B, an Electric 

Vehicle.

-0.161 0.851 -0.386 0.680

(0.400) (0.980)

-0.438 0.645 -0.252 0.777

(1.890) (1.140)

-0.332 0.717 -0.273 0.761

(1.460) (1.250)

-0.136 0.873 -0.280 0.756

(0.550) (1.180)

-0.026 0.974 1.316 3.728

(0.050) (2.46)*

0.328 1.388 0.959 2.609

(0.880) (2.57)*

0.474 1.606 1.000 2.718

(1.290) (2.73)**

0.014 1.014 0.714 2.042

(0.040) (1.910)

0.484 1.623 0.415 1.514

(5.17)** (4.51)**

-0.134 0.875 -0.067 0.935

(0.440) (0.230)

-0.209 0.811 -0.170 0.844

(0.670) (0.570)

-0.177 0.838 -0.299 0.742

(0.570) (0.980)

-0.121 0.886 -0.219 0.803

(0.380) (0.700)

-0.179 0.836 -0.173 0.841

(0.540) (0.540)

-0.277 0.758 -0.341 0.711

(0.770) (0.960)

-0.224 0.799 0.032 1.033

(0.590) (0.080)

-0.290 0.748 -0.216 0.806

(0.670) (0.500)

-0.570 0.566 -0.809 0.445

(1.420) (1.99)*

0.611 1.842 -0.180 0.835

(1.350) (0.400)

0.066 1.068 -0.364 0.695

(0.160) (0.860)

0.189 1.208 -0.278 0.757

(0.480) (0.710)

0.329 1.390 -0.036 0.965

(0.830) (0.090)

0.561 1.752 -0.156 0.856

(1.380) (0.390)

0.375 1.455 -0.205 0.815

(0.900) (0.500)
EPA Fuel Economy Label Choice 

Models

Independent Variables

Importance of Fuel Economy Label=2

Importance of Fuel Economy Label=3

Importance of Fuel Economy Label=4

Importance of Fuel Economy Label=5

Importance of Fuel Economy Label=6

Importance of Fuel Economy Label=7

Vehicles considered=Sports Car

Vehicles considered=Subcompact Car

Vehicles considered=Compact Car

Vehicles considered=Midsized Car

Vehicles considered=Large Car

Vehicles considered=Station Wagon

Vehicles considered=SUV

Vehicles considered=Crossover

Vehicles considered=Pickup Truck

Vehicles considered=Mini-Van

Vehicles considered=Van

Vehicles considered=Other

Early Adopter=2 (1 is first to adopt)

Early Adopter=3 (1 is first to adopt)

Early Adopter=4 (1 is first to adopt)

Early Adopter=5 (1 is first to adopt)

Early Adopter=6 (1 is first to adopt)

Early Adopter=7 (1 is first to adopt)

Observa(ons

Absolute/value/of/z/sta(s(cs/in/parentheses

*/significant/at/5%;/**/significant/at/1%

+/significant/at/10%;/**/significant/at/5%;/*/significant/at/1%

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Correctly identified vehicle B, an 

Electric Vehicle as better for 30-mile 

round-trip compared to vehicle A, a 

Dual Fuel Extended Range Electric 

Vehicle.

Dual Fuel PHEV Vehicle Label Compared With an Electric Vehicle Label

(Correct Answer=1, Incorrect Answer=0)

Understanding Questions 5 & 6

Correctly identified vehicle A, a Dual 

Fuel Extended Range Electric Vehicle 

as better for 120-mile round-trip 

compared to vehicle B, an Electric 

Vehicle.

0.215 1.240 0.036 1.037

(0.750) (0.130)

0.453 1.573 0.114 1.121

(1.690) (0.430)

0.360 1.433 0.076 1.079

(1.420) (0.300)

0.262 1.300 -0.139 0.870

(1.030) (0.540)

0.188 1.207 -0.156 0.856

(0.710) (0.590)

0.371 1.449 -0.229 0.795

(1.320) (0.810)

-0.020 0.980 -0.101 0.904

(0.140) (0.730)

0.045 1.046 0.390 1.477

(0.230) (2.08)*

0.248 1.281 0.308 1.361

(1.99)* (2.51)*

0.164 1.178 0.256 1.292

(1.740) (2.74)**

-0.207 0.813 -0.023 0.977

(1.400) (0.160)

0.368 1.445 0.060 1.062

(1.660) (0.280)

0.027 1.027 0.176 1.192

(0.280) (1.830)

0.027 1.027 0.385 1.470

(0.260) (3.70)**

0.275 1.317 0.159 1.172

(1.860) (1.110)

0.038 1.039 0.381 1.464

(0.240) (2.36)*

-0.013 0.987 -1.060 0.346

(0.030) (2.32)*

0.548 1.730 0.230 1.259

(1.830) (0.820)

0.060 1.062 0.461 1.586

(0.280) (2.19)*

0.081 1.084 0.569 1.766

(0.400) (2.82)**

0.073 1.076 0.529 1.697

(0.370) (2.67)**

0.024 1.024 0.514 1.672

(0.120) (2.52)*

-0.102 0.903 0.390 1.477

(0.450) (1.700)

-0.107 0.899 0.331 1.392

(0.370) (1.130)

2398 2378
EPA Fuel Economy Label Choice 

Models

Independent Variables

Constant

Label 1 Dummy Variable

Label 2 Dummy Variable

City Miles Share of Miles (e.g., 1-100)

Age 18-24

Age 25-34

Age 35-44

Age 45-54

Age 55-64

Less than High School

High School

Some College

College

Household Income Less Than $15k

Household Income $15-$25k

Household Income $25-$50k

Household Income $50-$75k

Household Income $75-$100k

Household Income $100-$125k

Household Income $125-$150k

Household Size=1

Household Size=2

Household Size=3

Household Size=4

Household Size=5

Household Size=6

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

0.192 1.212 1.106 3.022

(0.260) (1.540)

0.470 1.600 0.003 1.003

(4.12)** (0.030)

-0.120 0.887 0.362 1.436

(1.060) (3.17)**

-0.007 0.993 -0.004 0.996

(3.01)** (1.660)

-0.488 0.614 -0.590 0.554

(1.450) (1.740)

-0.515 0.598 -0.947 0.388

(2.27)* (4.36)**

-0.213 0.808 -0.547 0.579

(0.930) (2.58)*

0.020 1.020 -0.506 0.603

(0.090) (2.52)*

0.014 1.014 -0.511 0.600

(0.070) (2.65)**

0.120 1.127 0.838 2.312

(0.140) (1.080)

-0.077 0.926 0.022 1.022

(0.390) (0.110)

-0.103 0.902 0.092 1.096

(0.770) (0.700)

-0.122 0.885 0.056 1.058

(1.020) (0.470)

0.340 1.405 -0.174 0.840

(0.680) (0.370)

-0.007 0.993 -0.144 0.866

(0.020) (0.320)

0.286 1.331 -0.263 0.769

(1.300) (1.170)

0.238 1.269 -0.167 0.846

(1.390) (0.970)

0.080 1.083 0.029 1.029

(0.550) (0.200)

0.252 1.287 0.059 1.061

(1.670) (0.400)

0.043 1.044 0.019 1.019

(0.260) (0.110)

0.053 1.054 0.387 1.473

(0.090) (0.630)

-0.012 0.988 0.134 1.143

(0.030) (0.280)

0.025 1.025 0.392 1.480

(0.050) (0.810)

-0.073 0.930 0.073 1.076

(0.160) (0.150)

0.356 1.428 0.229 1.257

(0.750) (0.470)

-0.185 0.831 -0.344 0.709

(0.350) (0.600)

Selection Questions 1 & 2

Selected Gasoline Vehicle over Electric 

Vehicle

Advanced Technology Vehicle Choice Models 

(Vehicle A Selected=1, Vehicle B Selected=0)

Selected Gasoline Vehicle over Dual 

Fuel Extended Range Electric Vehicle
EPA Fuel Economy Label Choice 

Models

Independent Variables

Household Vehicles=1

Household Vehicles=2

Household Vehicles=3

Household Vehicles=4

Licensed Drivers in Household=1

Licensed Drivers in Household=2

Licensed Drivers in Household=3

Licensed Drivers in Household=4

Male

Daily Miles Driven, Less than 20

Daily Miles Driven, 20-30

Daily Miles Driven, 31-40

Daily Miles Driven, 41-50

Daily Miles Driven, 51-60

Daily Miles Driven, 61-70

Daily Miles Driven, 71-80

Daily Miles Driven, 81-90

Daily Miles Driven, 91-100

Importance of Fuel Economy rated 2 

(7 =very important)

Importance of Fuel Economy rated 3

(7 =very important)

Importance of Fuel Economy rated 4

(7 =very important)

Importance of Fuel Economy rated 5

(7 =very important)

Importance of Fuel Economy rated 6

(7 =very important)

Importance of Fuel Economy rated 7

(7 =very important)

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Selection Questions 1 & 2

Selected Gasoline Vehicle over Electric 

Vehicle

Advanced Technology Vehicle Choice Models 

(Vehicle A Selected=1, Vehicle B Selected=0)

Selected Gasoline Vehicle over Dual 

Fuel Extended Range Electric Vehicle

0.648 1.912 0.536 1.709

(1.510) (1.350)

0.356 1.428 -0.266 0.766

(1.490) (1.170)

0.127 1.135 -0.347 0.707

(0.550) (1.550)

0.203 1.225 -0.363 0.696

(0.800) (1.480)

0.504 1.655 -0.256 0.774

(0.910) (0.460)

0.609 1.839 0.057 1.059

(1.620) (0.150)

0.799 2.223 0.051 1.052

(2.16)* (0.130)

0.686 1.986 0.302 1.353

(1.820) (0.780)

0.135 1.145 0.190 1.209

(1.350) (1.940)

-0.470 0.625 -1.099 0.333

(1.350) (3.69)**

-0.228 0.796 -0.812 0.444

(0.650) (2.70)**

-0.286 0.751 -1.034 0.356

(0.800) (3.38)**

-0.169 0.845 -1.050 0.350

(0.460) (3.31)**

-0.154 0.857 -0.977 0.376

(0.410) (3.03)**

0.150 1.162 -1.317 0.268

(0.360) (3.55)**

-0.219 0.803 -0.686 0.504

(0.510) (1.840)

0.303 1.354 -0.311 0.733

(0.580) (0.740)

0.568 1.765 -0.373 0.689

(1.110) (0.950)

-0.411 0.663 -0.460 0.631

(0.870) (1.010)

0.253 1.288 -0.155 0.856

(0.560) (0.360)

0.487 1.627 -0.343 0.710

(1.150) (0.860)

0.358 1.430 -0.490 0.613

(0.840) (1.220)

0.711 2.036 -0.611 0.543

(1.630) (1.490)

0.443 1.557 -0.562 0.570

(0.990) (1.330)
EPA Fuel Economy Label Choice 

Models

Independent Variables

Importance of Fuel Economy Label=2

Importance of Fuel Economy Label=3

Importance of Fuel Economy Label=4

Importance of Fuel Economy Label=5

Importance of Fuel Economy Label=6

Importance of Fuel Economy Label=7

Vehicles considered=Sports Car

Vehicles considered=Subcompact Car

Vehicles considered=Compact Car

Vehicles considered=Midsized Car

Vehicles considered=Large Car

Vehicles considered=Station Wagon

Vehicles considered=SUV

Vehicles considered=Crossover

Vehicles considered=Pickup Truck

Vehicles considered=Mini-Van

Vehicles considered=Van

Vehicles considered=Other

Early Adopter=2 (1 is first to adopt)

Early Adopter=3 (1 is first to adopt)

Early Adopter=4 (1 is first to adopt)

Early Adopter=5 (1 is first to adopt)

Early Adopter=6 (1 is first to adopt)

Early Adopter=7 (1 is first to adopt)

Observa(ons

Absolute/value/of/z/sta(s(cs/in/parentheses

*/significant/at/5%;/**/significant/at/1%

+/significant/at/10%;/**/significant/at/5%;/*/significant/at/1%

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Selection Questions 1 & 2

Selected Gasoline Vehicle over Electric 

Vehicle

Advanced Technology Vehicle Choice Models 

(Vehicle A Selected=1, Vehicle B Selected=0)

Selected Gasoline Vehicle over Dual 

Fuel Extended Range Electric Vehicle

-0.046 0.955 -0.432 0.649

(0.150) (1.460)

0.013 1.013 -0.348 0.706

(0.040) (1.280)

-0.481 0.618 -0.355 0.701

(1.690) (1.370)

-0.485 0.616 -0.307 0.736

(1.690) (1.180)

-0.453 0.636 -0.394 0.674

(1.510) (1.450)

-0.589 0.555 -0.660 0.517

(1.880) (2.25)*

-0.014 0.986 0.051 1.052

(0.090) (0.340)

0.145 1.156 0.152 1.164

(0.710) (0.770)

-0.024 0.976 0.032 1.033

(0.180) (0.240)

-0.107 0.899 0.098 1.103

(1.070) (0.990)

0.052 1.053 0.055 1.057

(0.320) (0.350)

0.330 1.391 -0.019 0.981

(1.380) (0.080)

-0.110 0.896 0.085 1.089

(1.060) (0.830)

0.081 1.084 0.206 1.229

(0.720) (1.870)

0.129 1.138 0.160 1.174

(0.820) (1.060)

-0.189 0.828 0.199 1.220

(1.110) (1.180)

-0.219 0.803 -0.358 0.699

(0.510) (0.760)

-0.193 0.824 -0.246 0.782

(0.660) (0.770)

0.280 1.323 0.373 1.452

(1.300) (1.630)

0.068 1.070 0.137 1.147

(0.330) (0.620)

0.597 1.817 0.389 1.476

(2.92)** (1.790)

0.360 1.433 0.209 1.232

(1.720) (0.940)

0.710 2.034 0.233 1.262

(2.90)** (0.930)

0.034 1.035 0.642 1.900

(0.110) (2.09)*

2404 2404
EPA Fuel Economy Label Choice 

Models

Independent Variables

Constant

Label 1 Dummy Variable

Label 2 Dummy Variable

City Miles Share of Miles (e.g., 1-100)

Age 18-24

Age 25-34

Age 35-44

Age 45-54

Age 55-64

Less than High School

High School

Some College

College

Household Income Less Than $15k

Household Income $15-$25k

Household Income $25-$50k

Household Income $50-$75k

Household Income $75-$100k

Household Income $100-$125k

Household Income $125-$150k

Household Size=1

Household Size=2

Household Size=3

Household Size=4

Household Size=5

Household Size=6

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

0.839 2.314 -1.669 0.188

(1.220) (2.21)*

0.088 1.092 -0.056 0.946

(0.870) (0.530)

0.377 1.458 -0.055 0.946

(3.52)** (0.490)

-0.001 0.999 0.007 1.007

(0.310) (3.27)**

-0.145 0.865 0.224 1.251

(0.460) (0.700)

-0.350 0.705 0.098 1.103

(1.700) (0.460)

-0.396 0.673 0.113 1.120

(1.930) (0.530)

-0.094 0.910 0.036 1.037

(0.490) (0.180)

-0.198 0.820 -0.317 0.728

(1.060) (1.590)

-0.231 0.794 -0.142 0.868

(0.320) (0.170)

-0.055 0.946 0.253 1.288

(0.300) (1.340)

-0.077 0.926 0.092 1.096

(0.630) (0.710)

0.111 1.117 0.249 1.283

(1.010) (2.14)*

-0.605 0.546 0.177 1.194

(1.360) (0.400)

-0.002 0.998 -0.210 0.811

0.000 (0.510)

-0.186 0.830 -0.097 0.908

(0.910) (0.460)

-0.124 0.883 -0.123 0.884

(0.790) (0.750)

-0.058 0.944 -0.176 0.839

(0.430) (1.220)

0.001 1.001 -0.095 0.909

0.000 (0.660)

-0.043 0.958 0.081 1.084

(0.280) (0.510)

0.190 1.209 0.866 2.377

(0.340) (1.440)

0.128 1.137 0.506 1.659

(0.290) (1.040)

0.274 1.315 0.415 1.514

(0.630) (0.860)

0.132 1.141 0.238 1.269

(0.300) (0.490)

0.225 1.252 0.173 1.189

(0.510) (0.350)

0.110 1.116 0.481 1.618

(0.220) (0.890)

Advanced Technology Vehicle Choice Models 

(Vehicle A Selected=1, Vehicle B Selected=0)

Selected Dual Fuel Extended Range 

Electric Vehicle over Electric Vehicle

Selected Dual Fuel Extended Range 

Electric Vehicle over Electric Vehicle

Selection Questions 3 & 4
EPA Fuel Economy Label Choice 

Models

Independent Variables

Household Vehicles=1

Household Vehicles=2

Household Vehicles=3

Household Vehicles=4

Licensed Drivers in Household=1

Licensed Drivers in Household=2

Licensed Drivers in Household=3

Licensed Drivers in Household=4

Male

Daily Miles Driven, Less than 20

Daily Miles Driven, 20-30

Daily Miles Driven, 31-40

Daily Miles Driven, 41-50

Daily Miles Driven, 51-60

Daily Miles Driven, 61-70

Daily Miles Driven, 71-80

Daily Miles Driven, 81-90

Daily Miles Driven, 91-100

Importance of Fuel Economy rated 2 

(7 =very important)

Importance of Fuel Economy rated 3

(7 =very important)

Importance of Fuel Economy rated 4

(7 =very important)

Importance of Fuel Economy rated 5

(7 =very important)

Importance of Fuel Economy rated 6

(7 =very important)

Importance of Fuel Economy rated 7

(7 =very important)

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Advanced Technology Vehicle Choice Models 

(Vehicle A Selected=1, Vehicle B Selected=0)

Selected Dual Fuel Extended Range 

Electric Vehicle over Electric Vehicle

Selected Dual Fuel Extended Range 

Electric Vehicle over Electric Vehicle

Selection Questions 3 & 4

-0.845 0.430 -0.032 0.969

(2.09)* (0.080)

-0.391 0.676 0.241 1.273

(1.780) (1.010)

-0.358 0.699 0.355 1.426

(1.660) (1.520)

-0.399 0.671 -0.103 0.902

(1.700) (0.400)

0.826 2.284 -0.622 0.537

(1.580) (1.150)

0.072 1.075 -0.607 0.545

(0.200) (1.620)

0.156 1.169 -0.455 0.634

(0.440) (1.240)

-0.028 0.972 -0.367 0.693

(0.080) (0.970)

0.164 1.178 -0.089 0.915

(1.800) (0.930)

-1.025 0.359 0.296 1.344

(3.35)** (0.860)

-0.761 0.467 0.360 1.433

(2.46)* (1.040)

-1.023 0.360 0.242 1.274

(3.27)** (0.690)

-1.298 0.273 0.523 1.687

(4.02)** (1.460)

-0.865 0.421 0.430 1.537

(2.64)** (1.180)

-1.106 0.331 0.199 1.220

(3.05)** (0.490)

-0.573 0.564 0.223 1.250

(1.520) (0.530)

-0.795 0.452 0.342 1.408

(1.850) (0.710)

-0.275 0.760 0.096 1.101

(0.680) (0.210)

-0.428 0.652 0.723 2.061

(0.960) (1.540)

0.014 1.014 0.077 1.080

(0.030) (0.170)

-0.204 0.815 0.303 1.354

(0.520) (0.720)

-0.321 0.725 0.254 1.289

(0.810) (0.600)

-0.161 0.851 0.030 1.030

(0.400) (0.070)

-0.442 0.643 0.233 1.262

(1.070) (0.520)
EPA Fuel Economy Label Choice 

Models

Independent Variables

Importance of Fuel Economy Label=2

Importance of Fuel Economy Label=3

Importance of Fuel Economy Label=4

Importance of Fuel Economy Label=5

Importance of Fuel Economy Label=6

Importance of Fuel Economy Label=7

Vehicles considered=Sports Car

Vehicles considered=Subcompact Car

Vehicles considered=Compact Car

Vehicles considered=Midsized Car

Vehicles considered=Large Car

Vehicles considered=Station Wagon

Vehicles considered=SUV

Vehicles considered=Crossover

Vehicles considered=Pickup Truck

Vehicles considered=Mini-Van

Vehicles considered=Van

Vehicles considered=Other

Early Adopter=2 (1 is first to adopt)

Early Adopter=3 (1 is first to adopt)

Early Adopter=4 (1 is first to adopt)

Early Adopter=5 (1 is first to adopt)

Early Adopter=6 (1 is first to adopt)

Early Adopter=7 (1 is first to adopt)

Observa(ons

Absolute/value/of/z/sta(s(cs/in/parentheses

*/significant/at/5%;/**/significant/at/1%

+/significant/at/10%;/**/significant/at/5%;/*/significant/at/1%

Coefficient

(z-statistic) Odds Ratio Coefficient(z-statistic) Odds Ratio

Advanced Technology Vehicle Choice Models 

(Vehicle A Selected=1, Vehicle B Selected=0)

Selected Dual Fuel Extended Range 

Electric Vehicle over Electric Vehicle

Selected Dual Fuel Extended Range 

Electric Vehicle over Electric Vehicle

Selection Questions 3 & 4

-0.132 0.876 -0.052 0.949

(0.460) (0.180)

-0.273 0.761 -0.139 0.870

(1.030) (0.500)

-0.022 0.978 -0.118 0.889

(0.090) (0.440)

-0.135 0.874 -0.039 0.962

(0.530) (0.150)

-0.276 0.759 -0.043 0.958

(1.040) (0.160)

-0.270 0.763 -0.062 0.940

(0.960) (0.210)

-0.118 0.889 0.072 1.075

(0.850) (0.510)

0.155 1.168 -0.131 0.877

(0.850) (0.680)

0.138 1.148 0.099 1.104

(1.150) (0.790)

0.041 1.042 0.169 1.184

(0.450) (1.760)

-0.039 0.962 -0.220 0.803

(0.270) (1.380)

-0.029 0.971 -0.242 0.785

(0.140) (1.050)

0.003 1.003 -0.040 0.961

(0.030) (0.400)

0.411 1.508 -0.221 0.802

(4.02)** (2.00)*

0.068 1.070 -0.087 0.917

(0.480) (0.580)

0.093 1.097 -0.111 0.895

(0.590) (0.650)

-0.116 0.890 0.350 1.419

(0.280) (0.850)

0.208 1.231 0.284 1.328

(0.760) (1.010)

0.375 1.455 0.200 1.221

(1.780) (0.920)

0.323 1.381 0.125 1.133

(1.610) (0.600)

0.517 1.677 -0.048 0.953

(2.61)** (0.230)

0.242 1.274 0.068 1.070

(1.180) (0.320)

0.327 1.387 0.100 1.105

(1.430) (0.420)

0.451 1.570 0.194 1.214

(1.560) (0.650)

2400 2404
EPA Fuel Economy Label Choice 

Models

Independent Variables

Constant

Label 1 Dummy Variable

Label 2 Dummy Variable

City Miles Share of Miles (e.g., 1-100)

Age 18-24

Age 25-34

Age 35-44

Age 45-54

Age 55-64

Less than High School

High School

Some College

College

Household Income Less Than $15k

Household Income $15-$25k

Household Income $25-$50k

Household Income $50-$75k

Household Income $75-$100k

Household Income $100-$125k

Household Income $125-$150k

Household Size=1

Household Size=2

Household Size=3

Household Size=4

Household Size=5

Household Size=6

Coefficient

(z-statistic) Odds Ratio

-0.324 0.723

(1.160)

-0.119 0.888

(2.89)**

0.232 1.261

(5.30)**

-0.001 0.999

(1.330)

-0.161 0.851

(1.270)

-0.069 0.933

(0.820)

-0.099 0.906

(1.180)

-0.065 0.937

(0.820)

0.038 1.039

(0.490)

-0.621 0.537

(2.04)*

-0.252 0.777

(3.46)**

-0.136 0.873

(2.74)**

-0.025 0.975

(0.550)

-0.294 0.745

(1.680)

-0.573 0.564

(3.43)**

-0.109 0.897

(1.330)

0.057 1.059

(0.890)

0.053 1.054

(0.960)

0.091 1.095

(1.620)

0.115 1.122

(1.830)

-0.073 0.930

(0.320)

-0.183 0.833

(1.020)

-0.038 0.963

(0.210)

-0.046 0.955

(0.260)

-0.062 0.940

(0.340)

0.020 1.020

(0.100)

Understanding Questions (1-6)

Pooled Understanding Questions
EPA Fuel Economy Label Choice 

Models

Independent Variables

Household Vehicles=1

Household Vehicles=2

Household Vehicles=3

Household Vehicles=4

Licensed Drivers in Household=1

Licensed Drivers in Household=2

Licensed Drivers in Household=3

Licensed Drivers in Household=4

Male

Daily Miles Driven, Less than 20

Daily Miles Driven, 20-30

Daily Miles Driven, 31-40

Daily Miles Driven, 41-50

Daily Miles Driven, 51-60

Daily Miles Driven, 61-70

Daily Miles Driven, 71-80

Daily Miles Driven, 81-90

Daily Miles Driven, 91-100

Importance of Fuel Economy rated 2 

(7 =very important)

Importance of Fuel Economy rated 3

(7 =very important)

Importance of Fuel Economy rated 4

(7 =very important)

Importance of Fuel Economy rated 5

(7 =very important)

Importance of Fuel Economy rated 6

(7 =very important)

Importance of Fuel Economy rated 7

(7 =very important)

Coefficient

(z-statistic) Odds Ratio

Understanding Questions (1-6)

Pooled Understanding Questions

-0.269 0.764

(1.680)

-0.286 0.751

(3.16)**

-0.270 0.763

(3.04)**

-0.240 0.787

(2.49)*

0.708 2.030

(3.33)**

0.531 1.701

(3.64)**

0.526 1.692

(3.68)**

0.343 1.409

(2.35)*

0.390 1.477

(10.46)**

-0.025 0.975

(0.210)

-0.072 0.931

(0.590)

-0.146 0.864

(1.180)

-0.079 0.924

(0.620)

-0.069 0.933

(0.530)

-0.210 0.811

(1.460)

-0.152 0.859

(1.000)

-0.221 0.802

(1.280)

-0.286 0.751

(1.780)

0.254 1.289

(1.400)

-0.036 0.965

(0.210)

0.083 1.087

(0.520)

0.192 1.212

(1.190)

0.189 1.208

(1.150)

0.059 1.061

(0.350)
EPA Fuel Economy Label Choice 

Models

Independent Variables

Importance of Fuel Economy Label=2

Importance of Fuel Economy Label=3

Importance of Fuel Economy Label=4

Importance of Fuel Economy Label=5

Importance of Fuel Economy Label=6

Importance of Fuel Economy Label=7

Vehicles considered=Sports Car

Vehicles considered=Subcompact Car

Vehicles considered=Compact Car

Vehicles considered=Midsized Car

Vehicles considered=Large Car

Vehicles considered=Station Wagon

Vehicles considered=SUV

Vehicles considered=Crossover

Vehicles considered=Pickup Truck

Vehicles considered=Mini-Van

Vehicles considered=Van

Vehicles considered=Other

Early Adopter=2 (1 is first to adopt)

Early Adopter=3 (1 is first to adopt)

Early Adopter=4 (1 is first to adopt)

Early Adopter=5 (1 is first to adopt)

Early Adopter=6 (1 is first to adopt)

Early Adopter=7 (1 is first to adopt)

Observa(ons

Absolute/value/of/z/sta(s(cs/in/parentheses

*/significant/at/5%;/**/significant/at/1%

+/significant/at/10%;/**/significant/at/5%;/*/significant/at/1%

Coefficient

(z-statistic) Odds Ratio

Understanding Questions (1-6)

Pooled Understanding Questions

0.123 1.131

(1.050)

0.067 1.069

(0.620)

-0.028 0.972

(0.270)

-0.035 0.966

(0.340)

0.018 1.018

(0.160)

0.003 1.003

(0.030)

-0.133 0.875

(2.39)*

0.121 1.129

(1.590)

0.240 1.271

(4.85)**

0.109 1.115

(2.91)**

0.032 1.033

(0.540)

0.118 1.125

(1.370)

0.059 1.061

(1.530)

0.154 1.166

(3.65)**

0.059 1.061

(1.020)

0.136 1.146

(2.11)*

-0.342 0.710

(2.05)*

0.254 1.289

(2.23)*

0.122 1.130

(1.460)

0.297 1.346

(3.72)**

0.196 1.217

(2.50)*

0.183 1.201

(2.27)*

0.121 1.129

(1.330)

-0.116 0.890

(1.000)

14,281