1.
Socioeconomic trends in the host region
Trentino-Alto Adige/South Tyrol:
Public transport incentives
and green mobility
Matthias Cologna, PhD student at the Free University of Bolzano-Bozen
Spatial productivity for regional and local development - 19th meeting
14 December 2022 | Trento, Italy

2.
• Introduction
• Research Questions
• Literature Review and Contribution
• Data
• Empirical Strategy
• Results
• Conclusion and Policy Implications
• Q/A

3.
Introduction
Public transport incentives and green mobility Matthias Cologna 14th December 2022
• Transportation accounts
for >50% of South Tyrol’s
greenhouse gas
emissions
• Major role of individual
traffic
• More than 4,500,000
people visit South Tyrol
every year (ASTAT, 2021)
• Analysing a policy
implemented by the
Gröden Marketing
Tourism Association

4.
Research Questions
Public transport incentives and green mobility Matthias Cologna 14th December 2022
• How do interventions and incentives regarding public transport determine
choices?
• Was there an effect on the modal split by this policy in Val Gardena?
• How big is the magnitude of the intervention?

5.
Literature Review and Contribution
Public transport incentives and green mobility Matthias Cologna 14th December 2022
• Wayfarer Ticket (Lumsdon et alii, 2006): (a) parking problems, (b) enjoying a
stress-free day (‘day-out feeling’ connected with use of public transport in
tourism) and the presence of a good transport network and/or multi modal
options
• Attributes for attracting car users (Redman et alii, 2013): largely affective and
connected to individual perceptions, motivations and contexts. Promotions
and free tickets succeed in encouraging car users to try public transport
• Evidence that financial incentives work better than nudges, where framing is
used trying to convey positive messages e.g. about the role of emissions
(Gravner, 2021)

6.
Data
Public transport incentives and green mobility Matthias Cologna 14th December 2022
• Ticket validations, tourist stays and
traffic density for 22 months before
and 27 after intervention (January 2014)
• Matching 259 tariff zones
to 10 Tourism associations
• Matching traffic measurement stations to Tourism associations
• Calculation of an indicator representing the frequency of tourists using public
transport during their stay:
𝐼𝑛𝑑𝑖𝑐𝑎𝑡𝑜𝑟 𝑜𝑓 𝑠𝑢𝑠𝑡𝑎𝑖𝑛𝑎𝑏𝑙𝑒 𝑡𝑜𝑢𝑟𝑖𝑠𝑚 𝑚𝑜𝑏𝑖𝑙𝑖𝑡𝑦 =
𝑡𝑜𝑢𝑟𝑖𝑠𝑡 𝑣𝑎𝑙𝑖𝑑𝑎𝑡𝑖𝑜𝑛𝑠 𝑝𝑒𝑟 𝑚𝑜𝑛𝑡ℎ 𝑝𝑒𝑟 𝑇𝐵 𝑜𝑟 𝑇𝐴
𝑠𝑡𝑎𝑦𝑠 𝑝𝑒𝑟 𝑚𝑜𝑛𝑡ℎ 𝑝𝑒𝑟 𝑇𝐵 𝑜𝑟 𝑇𝐴

7.
Data
Public transport incentives and green mobility Matthias Cologna 14th December 2022

8.
Difference-in-difference model
Public transport incentives and green mobility Matthias Cologna 14th December 2022
• First difference: between the period before and after the intervention
• Second difference: between Gröden Marketing area and other areas which
do not receive the treatment
𝐼𝑛𝑑𝑖𝑐𝑎𝑡𝑜𝑟𝑖,𝑡 = 𝛽0 + 𝛽1 𝐺𝑟ö𝑑𝑒𝑛𝑀𝑖 + 𝛽2 𝐴𝑓𝑡𝑒𝑟𝑡 + 𝛽3 𝐺𝑟ö𝑑𝑒𝑛𝑀𝑖 ∗ 𝐴𝑓𝑡𝑒𝑟𝑡 + 𝛽4𝑋𝑖,𝑡
• i specifies the area,
• t specifies for time aggregated in month level,
• Indicator_(i,t) is the frequency of tourists using public transportation,
• GrödenM_i is a dummy equal to 1 in the case of Gröden Marketing
(Tourism Association) area,
• After_t is a dummy indicating the “after-intervention period”,
• X_(i,t) is a vector of other control variables.

9.
Results
Public transport incentives and green mobility Matthias Cologna 14th December 2022
• Treatment lead to about 7%
to 8% higher public
transport use
• Before intervention, Gröden
Marketing tourism
association had 10% higher
probability for tourists to
take public transport
• Effect of intrinsic
characteristics and the free-
ticket intervention led to a
higher usage of public
transport of 18%
All Data (All Travel Associations)
Gröden M. &
its Synthetic
OLS
Clustered
S.E.
Fixed
Effect
OLS
with Synthetic
Control
(1) (2) (3) (4)
Gröden Marketing (Gröden.M) 0.113*** 0.113*** - 0.663*** 0.101***
(0.017) (0.025) (0.105) (0.023)
After Treatment (After) 0.003 0.003 0.004 - 0.0002
(0.007) (0.007) (0.005) (0.015)
Groden.M x After 0.085*** 0.085*** 0.084*** 0.077***
(0.022) (0.005) (0.016) (0.020)
Traffic of Cars & Minivans
(logarithm)
0.047*** 0.047*** 0.069*** 0.071***
(0.003) (0.015) (0.009) (0.011)
Season (=1 for indicator > 70%
quantile)
0.103*** 0.103*** 0.099*** 0.149***
(0.007) (0.022) (0.006) (0.013)
Constant - 0.572*** - 0.572*** -0.851***
(0.039) (0.193) (0.150)
Observations 490 490 490 98
R2 0.55 0.55 0.889 0.792
Adjusted R2 0.546 0.546 0.886 0.781
Note: *p<0.1; **p<0.05; ***p<0.01

10.
Conclusion and Policy Implications
Public transport incentives and green mobility Matthias Cologna 14th December 2022
• Policy was effective: significant higher usage of public transport
• Evaluation of the magnitude of a (self-repaying) economic incentive
• Today 19 different guest cards -> vigorous political debate about new
"Südtirol Alto Adige Guest Pass“ in 2023

11.
Thank you for your attention!
Matthias Cologna | PhD student in Economics and Finance
mcologna@unibz.it