Transcript ภาพนิ่ง 1

Index Insurance for Pro-poor
Biodiversity Conservation:
The Case of Hornbills
in Southern Thailand
Pin Chantarat, Chris Barrett. Tavan Janvilisri, Chularat
Niratisayakul, Sittichai Mudsri and Pilai Poonswad
Linking Biodiversity and Poverty Hotspots Seminar
Cornell University
February 24, 2011
Insurance, Conservation and Rural Poverty
 Environmental and economic costs of uninsured (weather and
natural disaster) risk, esp. w/ threshold-based irreversibilities
 Insurance  rural livelihood and poverty:
•
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Provide ex post safety net to prevent downward slide of vulnerable
populations
May encourage investment and asset accumulation by the poor
•
May induce financial deepening by crowding-in credit market
 Insurance  pre-finance rapid rehabilitation and recovery:
•
Ensure adequate, timely response that enhances resilience to
shocks so as to prevent species/system collapse
 When shocks are strongly linked to livelihood and ecosystem
dynamics, insurance for cash-for-conservation work can
•
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Provide safety net for both people and endangered species
Replace predatory behaviors with restorative behaviors as a way to
cope with shocks.
The Potential of Index Insurance
 Conventional insurance unlikely to work due to transaction costs
and incentive problems (moral hazard and adverse selection)
 Index insurance w/ indemnity payments based on “an index”
•
•
•
•
•
•
Objectively verifiable, available at low cost in real time
Not manipulable by either party to the contract
Strongly correlated with covariate risk being insured
No transactions costs of measuring individual losses
Preserves effort incentives (no moral hazard) as insured cannot
influence index
Available on near real-time basis: faster indemnity payment for
more effective recovery response
 Pre-requisite: strong correlation established from sufficiently highquality data of insurable risk (the index)
This paper
 Explores a novel application of index insurance for pro-poor
biodiversity conservation
 Illustrates using community-based hornbill conservation in Budo
Su-Ngai Padi National Park (BSNP), southern Thailand
•
Strong winds (e.g., tropical storms) are a key threat to both
endangered hornbill reproduction and to rural livelihoods
•
Human disturbance to hornbills also induced by adverse windrelated shocks, so need to break the vicious cycle
 Data:
•
Hornbill annual nest loss and reproduction data (1994-2009) from
Hornbill Research Foundation, Thailand
•
Per capita village consumption (6 villages, 1998-2006) from
Thailand National Statistical Office
•
Wind speed data (1980-2009) from Thai MET Department
Hornbills and Rural Livelihood in Budo Su-Ngai
Padi National Park (BSNP)
 Mountainous, tropical rainforest with >2,400 mm of annual rain
• Dry season (Feb-July) vs. rainy season (Aug-Jan) with >2400mm. annual
rainfall, sensitive to tropical storms
 Home to 6 endangered species of hornbills (density of 20.3/km2)
• Nesting season (Feb-Sept) each year
• Stable reproduction (population) relies on
(1) Availability of suitable nest trees
- Holding capacity for breeding pairs
- Storms as key cause of irreversible loss
(2) Breeding condition free of disturbance
- Key threat: extensive human disturbance
(poaching, forest clearance), some induced
by coping responses to adverse income
shocks as key threat to breeding success
Hornbills and Rural Livelihood in Budo Su-Ngai
Padi National Park (BSNP)
 Home to Muslim minorities (among Thailand’s poorest groups):
• Poverty rates ($1.25/day) ~ 43-89%
• Heavily forest-dependent livelihood,
vulnerable to weather shock
- 40-60% relying on rain-fed agri.
- Agri. lands predominated by rubber,
embedded within the BSNP
 Hornbill research foundation and
conservation project (since 1994):
• Collect annual data on nest
and reproduction variables
• Focus on nest modification and
replacement (e.g., artificial nests)
• Extensive community involvement
aiming to reduce human disruptions
Wind-based Index Insurance for Pro-poor Hornbill
Conservation: General Framework
Accumulation of nesting trees
Nesting tree loss





Tt 1  1  g  l (t ,  tl )  Tt

l t ,  tl  l t    tl


Tt I 1  1  g  l (t ,  tl )  Tt  Max l (t )  l * ,0  T
Effective nest recovery response
Hornbill population dynamics
Wind-based index
insurance for nesting tree
based on l t 
Strong winds
shock t 





BtI2  1  m   Bt 1  RtI1
Rural village consumption




RtI1  st 1 YvI,t , t ,  ts1  Min bBt 1 , Tt I 1
Community-based
nest recovery program


Bt 2  1  m   Bt 1  Rt 1
  Max l (t )  l * ,0  c  T
Yv,t t ,  vy,t  Y t    vy,t

Rt 1  st 1 Yv,t , t ,  ts1  MinbBt 1 , Tt 1 

y
y
*


Yvinsured

,


Y




Max
l
(

)

l
,0  ci
,t
t
v,t
t
v,t
t
Reduce human disturbance
induced by adverse
consumption shock

Wind-based Index Insurance for Pro-poor Hornbill
Conservation: Results of Predictive Relationships
(1) Total
nest tree loss wind
(% total
available):

Two constructed
variables:
• wt annual
maximum
wind speed
1
l1
wt  



if
l
w
,
cw


l
t
t
t
l t•,  t cw
t  cumulative
monthly
maximum wind speeds that exceed the
2
l2
w
if


l
w
,
cw


t 
t
t
t
 month-specific
long-term average


• Endogenous regime switching with κ = 25 knots
wthe
wt well
Maxin
,
cwt   Maxwm  wm ,0
• Model predicts nest loss
regime
m  bad
mt
mt
• Predicted nest loss captures history well
Annual nest tree loss 𝑙𝑡
(% of nest trees)
Explanatory Variables
𝑤𝑡 ≥ 25
Village expenditures
per capita 𝑌𝜈,𝑡
𝑤𝑡 < 25
Coef.
SE
Coef.
SE
Max windspeed, 𝑤𝑡 (knots)
-0.0052***
(0.0013)
0.0003
(0.0032)
Max windspeed squared, 𝑤𝑡2
0.0002***
(0.0000)
0.0000
(0.0002)
Cum.abv.avg.max windspeed, 𝑐𝑤𝑡
0.0017*
(0.0009)
-0.0012
(0.0028)
(monthly $)
Coef.
SE
Observations
Adjusted R2
(% of nest trees)
Coef.
SE
-0.1250
(0.1637)
-0.0034
(0.4000)
-0.6697***
(0.1442)
-0.0100***
(0.0026)
-0.2495***
(0.0423)
0.4465***
(0.0763)
Official forest clearance (=1 if yes)
50.5676***
Constant
Following year’s chick
production rate 𝑠𝑡+1
(4.6678)
16
30
16
0.896
0.601
0.728
Wind-based Index Insurance for Pro-poor Hornbill
Conservation: Results of Predictive Relationships
(2) Village per capita consumption


Yv,t t ,  vy,t  Y wt , cwt    vy,t
• Weighted least square of 6 villages in biennial
survey period (1998-2006)
• Elasticity of village consumption wrt.
cumulative intensity of severe wind = -0.35
Annual nest tree loss 𝑙𝑡
(% of nest trees)
Explanatory Variables
𝑤𝑡 ≥ 25
Village expenditures
per capita 𝑌𝜈,𝑡
𝑤𝑡 < 25
Coef.
SE
Coef.
SE
Max windspeed, 𝑤𝑡 (knots)
-0.0052***
(0.0013)
0.0003
(0.0032)
Max windspeed squared, 𝑤𝑡2
0.0002***
(0.0000)
0.0000
(0.0002)
Cum.abv.avg.max windspeed, 𝑐𝑤𝑡
0.0017*
(0.0009)
-0.0012
(0.0028)
(monthly $)
Coef.
SE
Observations
Adjusted R2
(% of nest trees)
Coef.
SE
-0.1250
(0.1637)
-0.0034
(0.4000)
-0.6697***
(0.1442)
-0.0100***
(0.0026)
-0.2495***
(0.0423)
0.4465***
(0.0763)
Official forest clearance (=1 if yes)
50.5676***
Constant
Following year’s chick
production rate 𝑠𝑡+1
(4.6678)
16
30
16
0.896
0.601
0.728
Wind-based Index Insurance for Pro-poor Hornbill
Conservation: Results of Predictive Relationships
Evidence that villagers cope with wind storm shocks by disturbance to hornbills
(3) Breeding success (% of total fledged chicks from total nest trees available )
st  swt 1 , cwt 1    ts
• High correlations between breeding success and lagged consumption = 0.77
• Cannot directly estimate this due to limited village consumption data availability
• Strong effects of lagged cumulative wind speeds on subsequent chick production,
which includes the effects of storm-induced anthropogenic pressure
Annual nest tree loss 𝑙𝑡
(% of nest trees)
Explanatory Variables
𝑤𝑡 ≥ 25
Village expenditures
per capita 𝑌𝜈,𝑡
𝑤𝑡 < 25
Coef.
SE
Coef.
SE
Max windspeed, 𝑤𝑡 (knots)
-0.0052***
(0.0013)
0.0003
(0.0032)
Max windspeed squared, 𝑤𝑡2
0.0002***
(0.0000)
0.0000
(0.0002)
Cum.abv.avg.max windspeed, 𝑐𝑤𝑡
0.0017*
(0.0009)
-0.0012
(0.0028)
(monthly $)
Coef.
SE
Observations
Adjusted R2
(% of nest trees)
Coef.
SE
-0.1250
(0.1637)
-0.0034
(0.4000)
-0.6697***
(0.1442)
-0.0100***
(0.0026)
-0.2495***
(0.0423)
0.4465***
(0.0763)
Official forest clearance (=1 if yes)
50.5676***
Constant
Following year’s chick
production rate 𝑠𝑡+1
(4.6678)
16
30
16
0.896
0.601
0.728
Wind-based Index Insurance for Pro-poor Hornbill
Conservation: Contract Specifications
How would this insurance work?
• Conservation project can insures any T nest trees
• If wind-based nest loss index exceeds strike l*,
insurance payout can finance rapid communitybased nest replacement (e.g., artificial nests)




 l (t ),l * , T  Max l (t )  l * ,0  c  T
• c: total replacement cost per tree nest (artificial
nest =$400, installation and annual monitoring by
local villager = $600, which goes directly to villager)
Strike 𝑙 ∗
Frequency of
indemnity
payment:
𝑃𝑟 𝑙 𝜔𝑡 > 𝑙 ∗
Frequency of
correct indemnity
trigger decision
Fair annual
premium rate (%
replacement cost
insured nest tree)
Annual premium ($)
per insured nest
tree
(at c = $1000 per
tree)
3%
46.7%
87.5%
2.9%
$29.0
7%
20.0%
93.8%
1.5%
$15.0
11%
13.3%
100.0%
0.9%
$9.0
Wind-based Index Insurance for Pro-poor Hornbill
Conservation: Simulated Evaluation
 Assume that project insures all nest trees at the beginning of any year t,
and that each villager receives $600/12 = $50 for full installation and
monitoring of an artificial nest
 3% strike contract would reduce prob. of flock collapse below initial size
(1096) by from 80% to 60% and eliminate prob. of falling <75% current.
 It would reduce poverty headcount ($1.25/day) by 20%
Discussion
 Index insurance shows promise as a mean to manage weather
and natural disaster risk (which commonly affects conservation
outcomes and rural livelihoods that depend on natural resources)
 In the case of hornbill conservation, wind-based index insurance:
•
Can enable project to finance community-based nest recovery
program for rapid restore of necessary nesting capacity
•
Provide disaster support to storm-affected rural villager s
•
Potentially reduce human disruption to hornbill breeding success
 Opportunities provided by index insurance could widely apply:
•
When both people and biodiversity are threatened by a common,
measurable shock
•
Where there exists high-quality longitudinal data on an insurable
interest (nest trees) and a reliable weather or covariate risk index
(cost effective, objectively verifiable in near real time)
Thank you
for your attention
Back Up
Summary of Nesting Cycle and Density in BSNP
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60
60
50
50
Monthly Max
40
Wind speed (knots) 40
30
30
Monthly Mean
20
Rainfall (cms)
20
10
10
0
0
Mar Apr
Apr May
May Jun
Jun
FebFebMar
Temporal structure
of the wind-based
hornbill index insurance
Jul
Jul
Aug
Sep
Sep
Oct
Oct Nov
Nov Dec
Dec JanJan
Artificial nest installation and Use by hornbills
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