Air transport subsidies in regional development: A systematic review and meta-regression analysis

Hanjun (Louis) Wu, Massey University and Dr Yi-Hsin Lin, National Taichung University of Science and Technology, Taiwan

Background Information and Research PurposesBackground:

• Air transport is important to facilitate the economic growth (including tourism) in smaller regions.

• Air connectivity plays an important social role in providing access to essential services (e.g. healthcare).

• NZ Airports Association report (2017) called on the New Zealand government to allocate dedicated funding to isolated airports.

• The knowledge of subsidy’s impacts on regional development and wellbeing is still lacking.

Research purposes:

• Systematically review aviation subsidies relevant to regional development and wellbeing in previous studies

• Identify the benefits and impacts of aviation subsidies on regional air transport activity and wellbeing (economic, societal and

environmental)

• Synthesize results of aviation subsidies impact on regional wellbeing

Research method:

• Three database (Google Scholar, Web of Science, and Scopus ) + supplementary searching (Google.com)

• English literature only, 1974‒August 2019.

Overall, 110 publications were included, with 86 journal articles, 21 reports, and 3 book chapters.

Number of Publication of Regional Aviation Subsidies (1974‒August 2019)

1 1 1 1 12

1 1 1 1 12

1 12 2

5

1 1 1 1 1

7

17

1210

79

10

7

1

02468

1012141618

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

No.

of p

ublic

atio

ns

YearBefore 2010 After 2010

No. of publications 29 81

4826

2323

2221

1717

1615

1412

109

87

666

5555555

0 10 20 30 40 50 60

US

France

Italy

Germany

Portugal

Greece

Scotland

Belgium

Czech Republic

Slovakia

Austria

Netherlands

Romania

Countries Studied in Publications (publications >=5)

Trends Showing Aviation Subsidies Beneficiaries

1 11 11 111 1 11

2

1 1

22

4

1111

0

3

619

7419

7719

8019

8319

8619

8919

9219

9519

9820

0120

0420

07

No.

of p

ublic

atio

nsPanel A: 1974‒2009

1

43

45

1

4 4

11

7

14

97

4

87 7

12

3

1

3

1 1

0

3

6

9

12

15

2010201120122013201420152016201720182019

No.

of p

ublic

atio

ns

Panel B: 2010‒August 2019

Aviation supplier Airport Airline Local resident

No. of publications 1 32 92 12

Trends Showing Aviation Subsidies Types

1 1 1

3

1111 11

2

11 1 11

2

1 1

222

111111

0

3

6

1974

1977

1980

1983

1986

1989

1992

1995

1998

2001

2004

2007

No.

of p

ublic

atio

nsPanel A: 1974‒2009

2 2 2 21

24

21

3

14

98

5 57 7

13

2 21 1

32 2

12

12

1

0

3

6

9

12

15

2010201120122013201420152016201720182019

No.

of p

ublic

atio

ns

Panel B: 2010‒August 2019

Grants, equity and loansSubsidy schemes

pertaining to remote regions

Hidden subsidies No or reduced taxes

No. of publications 26 82 22 6

Trends Showing Aviation Subsidies Impacts

1 11

2

1 1 11 11

2

111

111

1 1

0

3

1974

1977

1980

1983

1986

1989

1992

1995

1998

2001

2004

2007

No.

of p

ublic

atio

nsPanel A: 1974‒2009

3

10

4

6

4

6

3 3

1

4 43

4 4

2 21 1

6

21

2 21

3

112

1 1 1

0

3

6

9

12

2010201120122013201420152016201720182019

No.

of p

ublic

atio

ns

Panel B: 2010‒August 2019

Air transport activities Economic wellbeing Societal wellbeing Environmental wellbeing

No. of publications 54 26 24 6

Findings of Descriptive Analysis

• Aviation subsidies research has attracted increasing attention since 2011

• Most attention given to the USA and EU countries, while countries from other continents have rarely

received attention

• Most studies were concerned with subsidies to airlines (routes), whereas less attention has been paid to

airports and local residents

• Subsidies schemes pertaining to remote regions had by far receiving the dominant attention, while

grants, equity and loans along with no or reduced tax have attached increasing attention since 2011

• 49% of publications regarding aviation subsidies’ impact on societal wellbeing, followed by economic

wellbeing (24%), and societal wellbeing (22%), and environmental wellbeing were considerably less

studied

Co-occurrence of Keyword Lists

RemarksColour of bubbles Average year of publication

Size of bubbles Importance (based on frequency)

Link between bubbles

Relationship between keywords

Co-occurrence of Common Words in Title and Abstract

RemarksColour of bubbles Average year of publication

Size of bubbles Importance (based on frequency)

Link between bubbles

Relationship between keywords

Word Cloud Showing Top 100 Frequently Used Words

Impact categories Indicators % of publications with indicators Number of publicationsAir transport activities 49.09% 54

Air accessibility 40.91% 45Flight frequency 10.00% 11Flight movements or traffic 4.55% 5Seat capacity 4.55% 5Number of passengers 10.91% 12

Economic wellbeing 23.64% 26Employment growth 7.27% 8GDP/GRP 2.73% 3Gross Value Added (GVA) 0.91% 1Local business 5.45% 6Per capita income 0.91% 1Population 2.73% 3Real aggregate taxable income 1.82% 2Tourism 10.00% 11Cargo 3.64% 4

Societal wellbeing 21.82% 24Airfare 16.36% 18Education 5.45% 6Medical treatment 6.36% 7Social cohesion 3.64% 4Work-related mobility 0.91% 1

Environmental wellbeing 5.45% 6Carbon emission 5.45% 6

Aviation Subsidies Impact Categories & Indicators

Findings of Content Analysis

Co-occurrence of Keyword List and Common Words in Abstract and Title

• The most frequently used keywords appear to be subsidies, subsidy programs, and air service providers

• Increasing attention to look at the aspects of regions and remote regions

• A distinct lack of knowledge regarding aviation subsidies’ impacts

Word Cloud

• Results are similar to co-occurrence maps

• Few keywords show the effect of aviation subsidies on regional air transport activity, economic and societal

wellbeing (e.g. connects, economics, fare, pricing, and airline seats)

Impact Categories and Indicators

• 20 indicators of aviation subsidies’ impacts on regional development were identified.

• The most important indicator is air accessibility, followed by airfare, number of passengers, tourism, and flight

frequency

Meta-regression Estimation (Probit)

Air transport activity

Economic wellbeing Societal wellbeing

Environmental wellbeing

Subsidy typesGrants, equity and

loans1.142 (0.698) 1.305 (0.854) N/A -0.734 (0.925)

Subsidy schemes pertaining to remote

regions

1.043 (0.722) 1.701* (0.992) -1.086 (0.969) -2.094** (0.835)

Hidden subsidies 1.223 (0.835) 2.745** (1.149) N/A -1.341 (1.022)

Subsidy beneficiariesAirport 6.341*** (0.521) -0.982 (0.798) 2.543*** (1.084) N/AAirline 6.459*** (0.481) -1.892** (0.782) 3.203** (1.024) -0.817 (0.915)

Resident 5.894*** (0.656) N/A 4.242*** (1.126) N/A

Findings of Meta-regression Analysis

• Subsidy schemes and hidden subsidies are more likely to contribute to regional economic

wellbeing

• Studies focusing on subsidy schemes pertaining to remote regions tend to less address

environmental wellbeing

• Subsidies to airport, airline, and resident are more likely to find aviation subsidies impact on

regional air transport activity and societal wellbeing

• Economic wellbeing is less addressed when study looking at subsidies to airline

Possible future research directions

1. Extend identified indicators and develop more of air transport, economy, social wellbeing, and environmental wellbeing to

measure aviation subsidies’ impact

• Extend knowledge of indicators such as regional tourism (e.g. New Zealand and Taiwan)

• Develop more indicators such as unemployment rate, trade, etc.

2. More research studying aviation subsidies impact on economic, societal and environmental wellbeing is needed

• More empirical research studying airport and airline subsidies’ impact on regional economic and societal wellbeing

is needed

• More research studying subsidies to resident and reduced tax is needed

• Environmental wellbeing should be received more attention from academia and professional practitioner

• Employ surveys or interviews (e.g. stakeholders like tourism and airport authorities, airlines; government, regional

councils; general public) to collect data for analysis (e.g. aviation subsidy data does not always available)

3. Explore the impact of regional aviation subsidies in countries outside the EU and US (e.g. China)

Thanks for your attention!