Rete Montagna Interna,onal Congress Eurac Conven,on Center -‐ Bolzano/Bozen -‐ IT November, 6th -‐ 8th 2014
The economic value of environmental resources in the Alps: is it important? MARA THIENE Dep. LEAF, University of Padua
The economic value of environmental resources in the Alps: is it important? THE ALPS IN MOVEMENT – PEOPLE, NATURE AND IDEAS NOVEMBER 6-‐8 2014 -‐ BOLZANO
Mara Thiene Dep. LEAF, University of Padua
Introduction The Alps tradiNonally generate a wide range of ecosystem goods and services to the populaNon and tourists: landscape beauty, outdoor recreaNon, cultural values, air quality, etc.
Non-‐market valuaNon methods (Travel Cost, Choice Experiment) are used to esNmate the economic value of such services: 1. determinants of recreaNon demand (preference heterogeneity); 2. the probability of selecNng an alternaNve (within a set of Alpine recreaNon sites); 3. marginal WTPs (welfare measures) due to the implementaNon of environmental policies.
Why are such methodologies useful?
They allow to provide informaNon to policy makers who are in charge to manage the land and the environment.
The eﬀects of Alpine park management policies on outdoor recreaNon are increasingly coming under public scruNny.
Alpine park agencies face controversial decisions: Ø preserve land and ecosystems Ø provide services to visitors. It increasingly diﬃcult to fund the services to facilitate the broad variety of outdoor recreaNon acNviNes (decreasing funds).
This is further exacerbated by the increasing expectaNons for high-‐ quality experiences by recreaNonists .
The literature Thiene M., Boeri M., Chorus C. (2012) Random Regret MinimizaNon: ExploraNon of a new choice model for environmental and resource economics, Environmental and Resource Economics, 51(3), 413-‐429 Scarpa R., Thiene M., Train K., (2008), UNlity in WTP space: a tool to address confounding random scale eﬀects in desNnaNon choice to the Alps, American Journal of Agricultural Economics, 90(4), pp.994-‐1010.
Olchewsky et al., (2012) Avalanche protecNon by forests — A choice experiment in the Swiss Alps, Forest Policy & Economics 15 108–113. Gaho P., Vidale E., Secco L., Pehenella D. (2014) Exploring the willingness to pay for forest ecosystem services by residents of the Veneto Region, Bio-‐based and Applied Economics 3(1): 21-‐43.
Aims of the presentation Can modeling techniques be of help to implemenNng environmental policies in the Alps?
Between methodology & outcomes.
Topics: 1. MulN-‐sites perspecNve: the Veneto mountains 1.1 Preference heterogeneity & constraints 1.2 Choices of site desNnaNons and subsNtuNon paherns 2. Single-‐site perspecNve: Natural Park of the Regole D’Ampezzo 2.1 WTP esNmates for park ahributes and services 2.2 UNlity MaximizaNon or Regret MinimizaNon? 2.3 Structural Choice Models (SCM): individuals vs couples.
The Models The Random UNlity Model (RUM): U in = Vin + in = βxin
MulNnomial Logit Model
+ ε in
exp(λβ xin ) Prin = ∑ exp(λβ x jn ) j∈J
Latent Class Model
exp( β c xi ) Prn c (i ) = ∑ exp( β c x j ) j∈J
β attribute WTPx = − β cos t
n=individual i = alternaNve ε = error term x= ahribute λ= scale parameter
The Mountains of the Veneto Region: Site CharacterisNcs
The Mountains of the Veneto Region Most research in recreaNon demand focuses on modeling behavioral heterogeneity. Two conjectures are invesNgated : 1. how onen one person recreates and where, are inﬂuenced by kids, ﬁtness, BMI, skill, health, smoking and drinking, age, gender, and educaNon; 2. these are life constraints, not preferences.
Examples: a) injured athletes know too well the diﬀerence between what they want to do and what they can do b) being overweight, one can only play tennis with diﬃculty: he/she might have same preferences than a thin person, but have a diﬀerent weight constraint! c) avoiding extended ﬁshing trip because of paren1ng obliga1ons does not indicate less preference for ﬁshing than a single friend.
Two objecNves: a) How to idenNfy behavioral heterogeneity?
b) How to parsimoniously model their inﬂuence? We look to life-‐constraint heterogeneity to help explain and model behavior heterogeneity.
Average Estimated Responses, by Life-Constraint Class Average estimated responses
3,50 3,00 2,50 2,00
1,50 1,00 0,50 0,00
(Morey Thiene, 2012)
Percentage of trips to each site, by esNmated Class Pre-‐Alps (total) Dolomites (total) PreAlps Feltrine Piccole Alpago Asiago Grappa Baldo Dolomites Antelao Pelmo CorNna Duranno Sorapis Agner Tamer Marmarole Lavaredo Civeha MarNno Marmolada
lfClass1 55.7 44.3
lfClass2 55.6 44.4
lfClass3 68.9 31.1
lfClass4 65.9 34.1
8.4 18.9 4.3 9.1 6.1 8.9
7.7 16.8 6.1 9.1 7.0 8.9
7.4 23.4 3.7 14.3 9.3 10.9
7.2 17.1 3.7 13.4 9.1 15.4
2.2 2.4 3.2 0.8 1.5 1.6 2.9 2.4 6.6 8.8 8.4 3.6
2.1 3.9 2.9 0.5 1.4 1.1 2.1 1.9 7.8 9.0 8.0 3.7
1.6 1.7 2.2 0.4 0.8 1.4 1.8 1.7 5.2 5.5 6.5 2.4
2.8 2.7 2.4 0.4 0.9 1.0 2.4 1.5 6.7 5.1 5.7 2.5
(Morey Thiene, 2012)
Site substitution patterns Two Policy simulaNons: comparing scenarios changes
(Thiene Scarpa, 2008)
The Natural Park of the Regole D’Ampezzo
Ahributes and Levels Variable
ThemaNc iNneraries (n)
Building of 5 and 7 addiNonal themaNc iNneraries, focusing on ﬂora, fauna and historical aspec (baseline 2)
Network of trails (km)
Decrease the network of trails and hiking paths to 300 km Increase the network of trails and hiking paths to 400 km (baseline 350 km)
VerNcal signs at juncNons plus painted signs every 200 mt along the path
VerNcal signs at juncNons plus painted signs every 50 mt along the path (baseline verNcal sign) Managed trails excursions New challenge iNneraries of 3 and 6 hours (baseline 1 hour) (hours) Climbing routes (n)
New 40 and 60 climbing iNneraries along cliﬀs and crags (baseline 20 climbs)
Iron cable along the whole path Iron cable along the whole path plus arNﬁcial holds (baseline: iron cable part of the path)
Decrease of 3 alpine shelters Increase of 3 alpine shelters (baseline: 20)
Number of people met along the trails (20-‐50) Number of people met along the trails (more than 50) (baseline: less than 20)
Brochure providing a lihle more than basic informaNon of the area (baseline: leaﬂet) Book containing an extended descripNon of the ﬂorisNc, historic aspects and the wildlife
Entrance fee (2, 5, 7, 10 €)
Example of choice task in CE Which of the following alterna1ve would you choose?
5 in addiNon
5 in addiNon
300 (1/7 less)
verNcal + horiz. 200m
Climbing routes (n.)
40 in addiNon
20 in addiNon
Complete iron cable
Complete iron cable + arNf. holds
Alpine huts (n.)
23 (3 in addiNon)
17 (3 in addiNon)
CongesNon (n. of people)
between 20 e 50
more than 50
Entrance fee (€)
ThemaNc iNneraries (n.)
Sequence of 12 choice-‐tasks
Choice Task ANA
Estimated Marginal WTP
Willingness to Pay Estimates for Park Management Attribute Level Ignored ANA
(Scarpa, Thiene, Hensher, 2010)
Minimizing Random Regret RUM: strong econometric foundaNons & conceptual elegance. Nevertheless, RUM partly lacks of behavioral realism.
Random Regret MinimizaNon paradigm (Chorus, 2010): i. people aim to minimize future regret when choosing, rather than aiming to maximize future uNlity. ii. regret is what one experiences when a non-‐chosen alternaNve performs beher than a chosen one.
Why should RRM be relevant in environmental economics? i. RRM adds on understanding visitors decision making process: rather than focusing exclusively on the maximizaNon of uNlity, it minimizes anNcipated regret, which is crucial informaNon to implemenNng environmental policies.
POLICY SCENARIO: Predicted change in choice probabiliNes due to an increase of entrance fee by 15 % Which of the RUM Alterna1ve following alterna1ve A Total would you choose? Change in choice
ThemaNc iNneraries (n.) Trails (km)
AlternaNve aﬀected Trail signs (Average eﬀect) Excursions (hours) Climbing routes (n.) Other AlternaNve Vie-‐ferrate (Average ﬀect) Alpine huts (en.) CongesNon (n. of people) Status Quo InformaNon (Average e(ﬀect) Entrance fee €)
RRM Alterna1ve B choice Change in
5 in addiNon 5 probability in addiNon probability change change 350 (baseline) 300 (1/7 less) verNcal + horiz. 200m verNcal only -‐3.10% -‐100.00% -‐2.06% -‐100.00% 6 1 40 in addiNon 20 in addiNon Complete iron cable Complete iron cable + arNf. holds 1.52% 48.81% 0.98% 47.53% 23 (3 in addiNon) 17 (3 in addiNon) between 20 e 50 more than 50 leaﬂet brochure 1.58% 51.19% 1.08% 52.47% 5 2
(Thiene, Boeri, Chorus, 2012, ERE)
Structural Choice Models Outdoor acNviNes are onen performed by visitors jointly as a couple. Members of a couple may display diﬀerent preferences, but outdoor experiences are usually the outcome of joint decisions. SCM is a new approach designed to: 1. incorporate latent variables and structural equaNons (SEM) into choice processes; 2. specify simultaneous equaNons and correlaNons; simultaneously modeling more than one DCEs.
Three idenNcal DCEs conducted separately: 1) DCE1 women; 2) DCE2 men; 3) DCE3 couples. QuesNons: 1. Is preference heterogeneity due to some latent factor? 2. Do individual preferences of men and women inﬂuence their joint deliberaNons (Inﬂuence Model)?
Who wears the trousers?
Which ahributes in joint decision are most inﬂuenced by each gender? A9ributes
Par11on of the Joint Variance Inﬂuence of Inﬂuence of Women Men
ThemaNc INneraries Network of Trails VerNcal Signs Challenge excursions Climbs Via Ferrata Alpine Shelter CongesNon InformaNon
40% 1% 42% 52% 23% 0% 26% 55% 15%
60% 99% 58% 48% 77% 100% 74% 45% 85%
72% (Thiene, Rungie, Scarpa, 2014)
Conclusions Dedicated surveys and analysis among visitors are crucial: • they allow the invesNgaNon of aytudes and variaNon in taste of visitors towards a selecNon of environmental services already in place or that could be provided; •
in the light of a gradual decrease of public funds, alpine parks might be forced to introduce an entrance fee;
Joint decisions: one member of the couple cannot be taken as representaNve of the couple;
if the goal of policy makers is to really tailor acNons on both members of the couple (see via ferrata), then they may take into account to propose alternaNve & speciﬁc acNviNes to women only.
Thanks for the ahenNon!