Investigating the Domestic 

Travel Spending Trends 

during 2010-2019

Li-Chun Lin, Ph.D. 

Feliciano School of Business

Montclair State University, New Jersey 
Why Consumer Expenditure Survey? 

 CE data contains very valuable and detailed data related to the 

hospitality and tourism industry - travel expenditure, food and 

beverage, lodging, transportation, entertainment in Interview file 

and detailed food items and associated costs in Diary file.

 Most of hospitality and tourism researchers use the survey method to 

collect first-hand data which is only a snapshot for a short period of 

time and a limited scope. CE provides multiple years of data with 

participants representing the US population.

 CE is accessible online and free of charge 

 Well-organized annual workshop and symposium 

 Friendly and knowledgeable staffs
Purpose of Study and CE Data Used 

 The purpose of this study is to investigate the trends of domestic

travel spending during 2010-2019 by using the CE Interview survey 

datasets. Particularly, the study aims to profile the travel spending 

patterns between post-recession (2010) and prior to the pandemic 

(2019). 

 Year: 2010-2019

 Software: SPSS

 Survey: Interview

 File: FMLI and MEMI

 Variables: 

 Characteristics for reference people: Age, Gender, Race, Education, Total 

Family Income before Tax, Region, Family Size and Type

 Total Travel expenditures on food, alcoholic beverage, lodging, 

entertainment, and transportation
Creating Data Sets

 One year data set = sum of 4 quarterly data sets 

 For example: 2010 data set = fmli101x + fmli102 + fmli103 + fmli104

 Within each year data set, 6 total travel expenditure related 

variables were computed by combing the expenditures of last

quarter and this quarter.

 total trip expenditure = last quarter (TTOTALP) + this quarter (TTOTALC)

 Total Trip Expenditure = Total Trip Expenditures on Transportation + 

Total Trip Expenditures on Lodging + Total Trip Expenditures on Food

+ Total Trip Expenditures on Entertainment + Total Trip Expenditures 

on Alcoholic Beverage

Year 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Data 28,429 26,990 26,993 26,108 25,908 23,574 25,441 24,479 23,159 21,701
Preliminary Results for 2010-2019

Profiles of Reference People 

 Age: around 50 years old

 Gender: Slightly more female 

 Race: Caucasian (around 80%)

 Family type: married couple only + 

single (around 50%)

 Family size: 2.5

 Total income before tax: wide 

ranges

 Region: South + West (58.5% or 

more)

 Education: high school - college

Total Travel Expenditures 

 Total Trip Expenditures ($332-$517)

 Transportation ($149-$202)

 Lodging ($76-$153)

 Food ($69-$106)

 Entertainment ($32-$38)

 Alcoholic Beverage ($11-$18)

The travel expenditure patterns from 2010 

to 2019 were upward in all aspects, while 

the lodging expenditure had the highest 

percentage increase (101%)
2010 Profile of Reference Person

 Age: 49.7 (Range: 16-87)  Education:

 Gender: 53% Female 

 Race: 80.4% Caucasian

 Family Type: 

 Married Couple Only: 20.7%

 Single: 30.1%

 Family size: 2.5 (Range: 1-14)

 Total Income Before Tax: $63,234.7 

(Range: -$52,928 - $700,350)

 Region: 

 35% South

 23.1% West

0%5%

9%

26%

21%

9%

19%

8% 3%

Never attended

Nursery, kindergarten, and

elementary (grades 1-8)

9th-12th grade (No high

school diploma)

High school graduate

Some college, no degree

Associate's degree in

college

Bachelors degree

Masters, professional or

doctorate degree

Professional/doctorate

degree
Total Trip Expenditures in 2010-2019

336 344

373

354

378

417 417

449

498

517

0

100

200

300

400

500

600

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Mean

Year
Total Trip Expenditures on 

Transportation in 2010-2019

149 150

167

154 158

171 171 174

202 202

0

50

100

150

200

250

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Mean

Year
Total Trip Expenditures on Lodging in 

2010-2019

76 79

85 86

96

105 105

123

133

153

0

20

40

60

80

100

120

140

160

180

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Mean

Year
Total Trip Expenditures on Food in 2010-

2019

69 71

75

72

77

88 88

94

101

106

0

20

40

60

80

100

120

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Mean

Year
Total Trip Expenditures on 

Entertainment in 2010-2019

32

33 34

31

35

38 38

43

44

38

0

5

10

15

20

25

30

35

40

45

50

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Mean

Year
Total Trip Expenditures on Alcoholic 

Beverages in 2010-2019

11 11 11

11

13

15 15

16

18 18

0

2

4

6

8

10

12

14

16

18

20

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Mean

Year
The Overall Trend in 2010-2019

336 344

373

354

378

417 417

449

498

517

76 79 85 86 96 105 105

123 133

153

69 71 75 72 77 88 88 94 101 106

11 11 11 11 13 15 15 16 18 18 32 33 34 31 35 38 38 43 44 38

149 150

167 154 158 171 171 174

202 202

0

100

200

300

400

500

600

2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Total Trip Expenditures Lodging Food Alcoholic Beverages Entertainment Transportation
My Experience of Using CE Data

Like 

 Microdata available in different formats – SAS, SPSS, STATA, CVS

 Well-documented handbook, manual, getting started guide, dictionary, etc.

 The sorting function in the dictionary excel file

 Total travel expenditure variables computed 

 One-on-one support and consultation 

Dislike

 Very confused about which variable to use, e.g. total income before tax

 Some variables and their associated codes don’t match in data set/dictionary, 

e.g. OCCUPRE1, ORIGINR, etc.

 Could not find or don’t know how to find some variables, such as length of stay, 

destination, ethnic variables, etc.

 Variables changing over the years
Suggestions

 Make the “domestic vs international trip” variable available to the public to 

better evaluate the impact of travel expenditures on the domestic 

economy 

 Explore further the ethnic variable to truly reflect the diverse population in 

the U.S.

 Improve the accuracy of Dictionary for Interview and Diary Surveys (XLSX)

 Create Customized Chart / Table / Index for Travel and Tourism Sector

 Include Code Information within data set, for example SPSS “Label” and 

“Value” under Variable View tab
Special Thanks to 

Dr. Geoffrey Paulin
Any Questions or 

Comments?