# Internet Survey Results on the Effects of Fuel Econ omy Labels on Understanding and Selection

Prepared by

PRR Inc.

November 2010

## 1



# Internet Survey Results on the Effects of Fuel Econ omy Labels on Understanding and Selection

**Summary** This report presents the results of a survey conduc ted on three fuel economy label designs proposed by the U.S. Environmental Protection Agency and the Na tional Highway Traffic Safety Administration. 1 

## Each respondent saw only one label design and was a sked 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 de signs with respect to understandability are small.

The “selection” questions asked respondents to ide ntify which vehicle s/he preferred to buy, if vehic les were identical except for the information on the la bels. 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. an d the EPA, with input from NHTSA (National Highway Traffic Safety Administration) and OMB (Off ice of Management and Budget). 2 

## The survey questions were pretested in seven cognitive intervi ews.
A total of six different versions of the survey wer e used. These six versions differed only in regard to:

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

• The order in which the labels were presented in th e 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 (Au tobytel, 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 Ve hicle Fuel Economy Labe; Proposed Rule,” Federal Register 75(184) (September 23, 2010): 58078-58202. 2 

## Drafts of the survey were reviewed by Dr. Clay Voor hees of Michigan State University and Dr. Randall P ozdena of ECONorthwest, former vice president of the Federal Reserve Bank of San Francisco.

## 2

• the e-Rewards TM panel 3 

## 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 merge d 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 s urvey 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 carefu lly 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 fr om the e-Rewards panel, but it includes some responden ts 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 statistical ly significant differences, except that age for those who viewed the Label 3 design was slightly older th an those who viewed the other two label designs. Resp ondents 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 differ ent label designs. For both these kinds of questions, respondents were shown labels of the sam e 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 di stance. The “selection” questions asked which vehi cle the respondent would prefer to buy if all vehicle c haracteristics other than those on the label were t he same. This memo provides the results of these ques tions.

3 

## The e-Rewards panel (part of ResearchNow TM http://www.researchnow.com/ ) is among the most highly rated of such online survey panels, and has a global automot ive panel of over 1.5 million panelists. Respondent s are paid a small fee ($1.25) for completing surveys. A number of government projects have used e-Rewards panelist s, including but not limited to surveys conducted for the United States Department of Homeland Security a nd the United States Department of Defense. 4 

## The responses include 191 people who self-identifi ed as intending to buy a new vehicle, rather than h aving bought a new vehicle. These people came from the A utobytel database, as there were no “intenders” in the eRewards panel. Because intenders were found to be demographically different from buyers (e.g., more m ale, older, less wealthy), the intenders were excluded f rom the analyses presented here. Including intende rs might affect the results, without sufficient numbers of t hem to identify what effects are associated with in tenders vs. buyers, or to separate the demographic effects from differences in preference between intenders and bu yers. 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 Autoby tel panel cannot be distinguished from the e-Reward s panelists. They are likely to be a small enough nu mber that they will not significantly affect the re sults.

## 3

The labels presented in the survey are based on hyp othetical vehicles and are not intended to reflect the performance of any specific vehicles. The results of these surveys are not intended to be representat ive of any larger group of new vehicle buyers and refle ct 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, Understandin g Questions (UQ) 1-6). In each pair, respondents were asked to identify which vehicle was better to use for trips of specified distances. “Better” wa s chosen as the comparison word, rather than “more fu el-efficient” or “less costly,” to allow respondent s to decide on their own what information on the labe l they would use. Answers may therefore reflect individuals’ idiosyncratic attitudes and assumption s; 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, diff erences in responses across label designs are expec ted 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 emi ssions, and vehicle range and will identify this a s 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 propo rtion of “correct” answers from question to questio n, as either the driving distance or the vehicle techn ologies changed. Limited understanding of advanced technology vehicles may contribute to incorrect res ponses to these questions. The differences in “correct” answers across label designs in response to any individual question are much smaller than th e differences from question to question.

Pair #1 Key Metrics:

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

• Vehicle B: Electric, range 100 miles, 98 mpge, $61 6 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 effici ency and lower operating costs of the electric vehi cle.
In this comparison, regardless of label design, res pondents gave a high proportion of “correct ” answe rs. Average “correct” response was 77.5%, with the prop ortion 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 t he electric vehicle is less than the trip distance.

In this comparison, all three labels produced a lar ge proportion of “incorrect ” answers compared to t he answers for the 30-mile range. Average “correct” r esponse 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 usi ng electricity, and the EREV is more fuel-efficient an d less costly to operate in that range.

In this comparison, all three labels produced a lar ge 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 aver age of fuel costs for the two modes that would be used over the distance. The PHEV’s gasoline mode i s sufficiently more efficient than that for the ERE V to outweigh the higher efficiency of the EREV for the mode using electricity.

In this comparison, all three labels produced a maj ority 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 mi les? * 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, $50 8 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 eff iciency and lower operating cost for the electric vehicle.

In this comparison, all three labels produced a sol id majority of “correct ” answers. Average “correc t” response is 61%, with the proportion of “correct” r esponses 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 lengt h.

In this comparison, all three labels produced a lar ge proportion of “incorrect ” answers. Average “correct” response is 49%, with the proportion of “ correct” responses across label designs varying fro m 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 b etter for a round-trip of 30 miles?

Total Label 1 Label 2 Label 3 Label Type Total

Q: Which v ehicle 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 u sed 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) provid e 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 in consistent 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 ap pear 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 variabl es may be serving as proxies for some personal characteristics not picked up in the other demograp hic variables. Q: What label information did you use in deciding w hich vehicle you would purchase in the previous que stions? (Multiple responses allowed; Percents add up to mor e 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 pe ople’s selections of vehicle purchases, respondents saw pairs of labels for hypothetical vehicles (see Appendix 1, Selection Questions (SQ) 1-4). They we re asked:
Assuming the same make and model of vehicle for bot h labels above and assuming that both vehicles met all your other requirements (including size, reliability, comfort, performance, appearance, and safety) and are identical in purcha se price, which vehicle would you purchase when you consider your typical travel pattern?
Because driving patterns of respondents were distr ibuted randomly across the label designs, differences in responses across label designs are e xpected to be due to the label designs. In these questions there is no correct answer. Respondents identify their preferred vehicles based on their ow n decision factors.
In all four comparisons, the majority of respondent s selected the vehicle with projected higher fuel c ost savings or lower fuel costs. Those who saw either Label 1 or (in 2 of the 4 regressions) Label 3 chos e 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 m et all your other requirements (including size, reliability, co mfort, performance, appearance, and safety) and are identical in purchase price, which vehicle would you purchase when you co nsider your typical travel pattern? * Label Type Cr osstabulation

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, mos t respondents chose the conventional gasoline engin e 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 Appendi x 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 co st

• Vehicle B: Electric, range 85 miles, 123 mpge, $49 0 annual fuel cost
Selection Q. 2:



## In this comparison, regardless of label design, mos t respondents chose the electric vehicle. Average proportion choosing the electric vehicle is 65%, wi th the proportion choosing the electric vehicle acr oss label designs varying from 60% to 68%. 12



## Regression results for this comparison (see Appendi x 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, $50 1 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 b oth labels above and assuming that both ve hicles met all your other requirements (including size, reliability, co mfort, performance, appearance, and safety) and are identical in purchase price, which vehicle would you purchase when you co nsider your typical travel pattern? * Label Type Cr osstabu lation

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 choosin g 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 Appendi x 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 m et all your other requirements (including size, reliability, co mfort, performance, appearance, and safety) and are identical in purchase price, which vehicle would you purchase when you consider your t ypical 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 m et 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 co nsider your typical travel pattern? * Label Type Cr osstabulation

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, mos t respondents chose the Plug-in Hybrid Electric Vehicle (PHEV). Average proportion choosing the PH EV is 59%, with the proportion choosing the PHEV across label designs varying from 58% to 61%. 14



## Regression results for this comparison (see Appendi x 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 metric s 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 la bel 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 decidi ng which vehicle you would purchase in the previous questions?

(Multiple responses allowed; Percents add up to mor e 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 fro m Logistic Regressions This technical memorandum presents the preliminary resul ts 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 choic e modeling of the following: 1. Respondent label understanding responses (Understanding Que stions 1-6) 2. Respondent vehicle preference/likely to purchase (Selec tion 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 ques tions) on the left-hand side of the model. The label design indicator variables and a se ries 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 variab le 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 t he outcome are key concepts for correctly interpreting the results from these mode ls. For the label understanding choice models:

 Probability is defined as the probability that the resp ondent selects the correct answer. E.g., p is the probability that the respondent ans wers correctly, or p(correct=1)

 The ‘odds’ of a correct answer is the ratio of the prob ability 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 Qu estions 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 resp ondent selects the first vehicle (i.e., Vehicle A). To interpret the results fro m 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” respo nses were randomly assigned to Vehicle A or Vehicle B, using a uniform distributio n. Simple Numerical Example of an Odds Ratio Prior to Understanding Questions 1 and 2 in the survey, r espondents 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 f or 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 Tabulat ion for Understanding Question 1 Understanding Question 1 Frequency

Correct 2,097 Incorrect 608 Total 2,705 From this frequency tabulation of the answers to Underst anding 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 c oefficient on the constant term in a model without any other predictor variables: Table 2 Logistic Regression Results for Understandi ng Question 1, Constant Term Only Logistic regression Num ber 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 onl y 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 coeffi cients and odds ratio does not change in any fundamental way.

1 

### This exposition is based on the explanation provid ed at: UCLA, Academic Technology Services, Statisti cal Consulting Group. FAQ: How do I interpret odds ratios in logistic reg ression? http://www.ats.ucla.edu/stat/mult_pkg/faq/general/o dds_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) var iable.

 These changes are interpreted relative to the default case for dichotomous RHS variables; and are interpreted for a one-unit change in t he 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 int erpret 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 abo ut the coefficients and odds ratios:

 An odds ratio of 1.5 is interpreted as the predictor v ariable being associated with the odds of a correct answer being 1 and 1/2 tim es more likely than the odds of the incorrect answer.

 Negative coefficients from the model produce odds rat ios of less than one, so a change in the right-hand side variable makes the outc ome less likely to
occur. Again, the coefficients from the logistic regression fo r dichotomous right-hand side variables are always interpreted relative to the de fault 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 t hat 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 coefficie nt 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 i n 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 conceptuall y 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 (conti nuous) for a unit increase in the corresponding RHS variable holding other variables a t constant value(s). The following pages present the model estimation results for the choice models. The results contain both the estimated coefficient and the o dds ratio. The z-statistic is displayed in parentheses underneath the estimated coeffici ent. The z-statistic indicates whether the estimated coefficient is statistically diff erent 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 2376EPA 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 2378EPA 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 VehicleEPA 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 2404EPA 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 & 4EPA 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 2404EPA 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 QuestionsEPA 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