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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  


2014


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  

ε

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

Marginal WTP  

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?    

Constraint heterogeneity  

Preference 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

57%

lfClass 1

21%

lfClass 2

15%

lfClass 3

8%

lfClass 4

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    

A:ribute descrip1on    

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)    

Trail signs    

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)    

Via Ferrata    

Iron cable  along  the  whole  path     Iron  cable  along  the  whole  path  plus  arNficial  holds  (baseline:  iron  cable  part  of  the  path)    

Shelters (n)    

Decrease of  3  alpine  shelters     Increase  of  3  alpine  shelters      (baseline:  20)    

CongesNon (n)    

Number of  people  met  along  the  trails  (20-­‐50)     Number  of  people  met  along  the  trails  (more  than  50)      (baseline:  less  than  20)    

InformaNon  

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    

Cost  

Entrance fee  (2,  5,  7,  10  €)    


Example of  choice  task  in  CE   Which  of  the   following  alterna1ve   would  you  choose?  

Alterna1ve   A  

Alterna1ve   B  

5 in  addiNon  

5 in  addiNon  

Trails (km)  

350 (baseline)  

300 (1/7  less)  

Trail signs  

verNcal +  horiz.  200m  

verNcal only  

Excursions (hours)  

6

1

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  

leaflet

brochure

Entrance fee  (€)  

5

2

                                     

Choice

 

 

 

ThemaNc iNneraries  (n.)  

Vie-­‐ferrate  

InformaNon

Sequence of  12  choice-­‐tasks  

Neither  


-1,00

-3,00 TRL_SIGNS2

TRL_SIGNS1

NET_TRAILS2

NET_TRAILS1

IT_THEMES2

Serial ANA

Choice Task ANA

1,00

Estimated Marginal WTP

INFO2

INFO1

3,00

CROWD2

5,00

CROWD1

7,00

SHELTERS2

SHELTERS1

FERR_SAFE2

FERR_SAFE1

NEW_CLIMBS2

NEW_CLIMBS1

MNGD_TRAILS2

MNGD_TRAILS1

-5,00 IT_THEMES1

Willingness to Pay Estimates for Park Management Attribute Level Ignored ANA

-7,00

(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   €)  

Choice

RRM   Alterna1ve   B  choice   Change  in  

Neither Total    

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%  

Average Ahribute    

28%

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!    


2014

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