Cash incentives and cooperative behavior: Payments for...

BackgroundTheoretical framework

Empirical strategyConclusions

Cash incentives and cooperative behavior:Payments for Ecosystems Services and

common property management in Mexico

Patricia Yanez-Pagans

University of Wisconsin-Madison

Summer School in Development Economics, June 21, 2012

Patricia Yanez-Pagans Cash incentives and cooperation



MotivationMain idea of studyResearch questionsPSAH program

Motivation

Traditional economic theory predicts positiverelationship between economic incentives and effort.

Human behavior can be driven by multiple motivations(intrinsic or extrinsic) that interact with incentives inunexpected ways.

Potential problems with activities that have beentraditionally unpaid (charity, donations, prosocialactivities).





Main idea of this study

Test the impact of cash incentives on participation incommunity work in a context driven by social norms.

Exploit a unique situation in Mexico, currentlyimplementing one of the largest Payments for EcosystemServices (PES) programs in the world.

More than 70% of forest land in Mexico is owned bycommon property communities, where unpaidcommunity work has a long history.

PES incentives are increasingly given for communityactivities that were previously uncompensated. Framing ofincentive varies across communities.





Research questions

Do monetary incentives for forest conservation changecooperative behavior within common propertycommunities?

How does the framing of the incentive affects households’participation in community work?





Related literature and potential contributions

Behavioral economics literature: Incentives mightweaken or strengthen social norms (Benabou and Tirole,2006; Gneezy and Rustichini, 2000; Fehr and Falk, 2002;Carpenter and Myers, 2010) - Mostly experimentalevidence.

PES literature: Depending on local institutions, incentivesincrease or decrease collective action (Vatn 2010;Sommerville et al. 2010; Kerr at al. 2011) - Few robustempirical evidence.





Mexico’s Payments for Hydrological Services Program

2003-present. National level.

Goal: improve hydrological services bypreventing deforestation.

5 year contracts. Yearly paymentscontingent on maintaining forest cover andperforming forest management activities(aprox. USD 480 per household).

Voluntary. Private and common propertieschoose parcels to enroll.

Random monitoring by satellite and fieldvisits.




Basic intuitionCommunity leaders’ problemHouseholds’ problem

Theoretical model: Basic intuition

Two actors whose decisions are interrelated(Principal-agent framework).

Leaders choose the optimal distributional rule anticipatinghouseholds’ behavior. Households choose theirparticipation after observing the rule.

Distributional rule might change the enforcement of socialnorms making free-riding more or less acceptable.





Community leaders’ problem

maxγ

{pf F + g(N∑

i=1

lpi (γ,Vi ,X ) +N∑

i=1

lui (γ,Vi ,X ))− c(γ,F ,Z )}

s.t . 0 ≤ γ ≤ 1Where:

γ = Proportion of PSAH income distributed as lump-sum transferspf = Payment per hectare of forest enrolled in programF = Hectares of forest enrolled in programg(.) = Benefit function from aggregate community worklp and lu = Labor supplied in paid and unpaid community workN = Total population in the communityX = Vector of community characteristics that affect labor decisionsc(.) = Cost function of program implementationZ = Vector of community characteristics that affect costsVi = Vector of household i characteristics





Community leaders’ problem

Given the FOC, the optimal distributional rule is:

γ∗ = γ(Z ,F ,X ,N∑

i=1

Vi)

Where:

Z = Vector of community characteristics that affect program costs.

F = Amount of forest enrolled in program.

X = Vector of community characteristics that affect households’ labor decisions.

Vi = Vector of household characteristics that affect labor decisions.

Fundamental question: What is in Z?





Households’ problem

maxloi ,l

pi ,l

ui

{pq(loi )− c(loi ) + w(γ)lpi − c(lpi )− c(lui ) + B(γ)

+aig(N∑

i=1

lpi +N∑

i=1

lui )− θiR(

∑Ni=1 luiN

− lui ,N,B(γ))}

s.t . T = loi + lpi + luiWhere:

p = Price for own production; q(lo) = Own production activities function

w = Payments for community work; B = Lump-sum transfers;

lp,ui = Labor supplied in paid and unpaid community work

c(lp,ui ) = Costs of participating in paid and unpaid community work

g(.) Benefit function from aggregate community work; ai = Marginal benefit

R(.) = Punishment function; θi = Degree of exposure to punishment





The punishment function

θiR(

∑Ni=1 luiN

− lui ,N,B(γ))

Households exposed to punishment differently: 0 ≤ θi ≤ 1

More punishment when you deviate below averagebehavior: ∂R

∂(l̄u−lui )> 0

Less punishment when actions less visible: ∂R∂N < 0

Leaders can punish more when they provide cashincentives without conditions: ∂R

∂B > 0; ∂R∂γ > 0





Predictions from households’ problem

With simple functional forms it can be shown that:

Lump-sum transfers increase the time allocated tounpaid community work: ∂lu∗i

∂γ > 0

To the extent that households are subject to punishment,the effect of lump-sum transfers on cooperation will bepositive: ∂2lu∗i

∂γ∂θi> 0

To the extent that households’ actions are visible, theeffect of lump-sum transfers on cooperative behavior willbe positive: ∂2lu∗i

∂γ∂N < 0




DataIdentification strategySuggestive evidence

Data

Community and household surveysof 2008 PSAH applicants.

Accepted and rejected properties.

1086 households distributed in 111communities and 4 regions.

Recall questions from 2007.

Data about participation decisionsand intensity.

Data is part of a larger project toevaluate the environmental andsocioeconomic impacts of PSAH.





Measuring the impact of payments on cooperation

Difference-in-Difference estimation:

Yijt = β0 + β1Tt + β2Pjt + β3(Tt ∗ Pjt) + αVi + δXj + εijt

Where:

Yijt = Cooperation outcome of interest for individual i in community j and time tI Decision to participate in paid or unpaid community workI Number of days per year worked in paid or unpaid community work

Tt = 1 if 2011 and 0 if 2007

Pij = 1 if community participates in PSAH program

Vi = Household characteristics

Xj = Community characteristics

Combine matching with DID estimation.





Measuring the impact of different incentive schemes

Using only the sample of beneficiaries:

Yijt = β0 + β1Tt + β2Djt + β3(Tt ∗ Djt) + αVi + δXj + ηuj + εijt

Where: Djt Proportion of PSAH distributed as lump-sum transfers in period t

uj are PSAH per capita payments received by community j .

Simultaneity Problem. Need IV that predicts distributional rulebut that does not affect cooperation.

Remember that: γ∗ = γ(Z ,F ,X ,∑N

i=1 Vi)

Forest size? A variable in vector Z? For now, averagedistributional rule of (not so close) neighbors





Participation in forest management activities (FMA)





Table: Participation in forest management activities

(1) (2) (3) (4) (5)OLS OLS IV OLS IV

Beneficiary * Year 0.106**(0.052)

Prop. dist. * Year 0.045 -0.014 -0.020 -0.100(0.084) (0.135) (0.105) (0.155)

Prop.dist*Year*Rights 0.091 0.107(0.129) (0.194)

N 1470 700 700 700 700Controls Yes Yes Yes Yes Yes* p<0.1 ** p<0.05 *** p <0.01 Robust standard errors clustered at the community level.

Cash incentives increase baseline participation by 23%, but nosignificant differential effects by distributional rule.





Changes in number of days worked in FMA





Table: Number of days in forest management activities

(1) (2) (3) (4) (5)OLS OLS IV OLS IV

Beneficiary*Year 6.379*(3.281)

Prop. dist.*Year 4.919 10.456 -7.811 -15.779(5.830) (8.556) (5.992) (10.404)

Prop.dist.*Year*Rights 18.917** 36.278***(9.185) (13.965)


Cash incentives almost double the number of days worked inFMA. With full redistribution this result triples for those withland-use rights.





Participation in other unpaid community work





Table: Participation in other unpaid community work

(1) (2) (3) (4) (5)OLS OLS IV OLS IV

Beneficiary 0.077*(0.043)

Prop. distributed 0.141** 0.246** 0.042 0.064(0.061) (0.112) (0.094) (0.161)

Prop. distributed*Rights 0.148 0.230*(0.093) (0.131)


Cash incentives increase participation in unpaid communitywork by 18%. This increase is higher with full distribution andfor those with land-use rights.





Days worked in other unpaid community work





Table: Number of days in other unpaid community work

(1) (2) (3) (4) (5)OLS OLS IV OLS IV

Beneficiary 3.109*(1.788)

Prop. distributed 2.537 -1.221 -0.703 -4.497(3.679) (6.872) (4.276) (7.207)

Prop. distributed*Rights 4.788 4.081(6.714) (9.843)


Cash incentives increase the number of days in other unpaidcommunity work by 50%, but no significant differences bydistributional rule.




Conclusions

Preliminary evidence suggests:

PES incentives promote more cooperation in forestmanagement activities.

Framing of the PES incentive can have positive spillovereffects on unpaid community work not necessarily relatedto forest.

Results important not only for efficiency and sustainability ofPES programs. Most important, for the sustainability ofcommunities.




Next steps...

Is this the right IV? More information about thedecision-making process will come from case studies.

Need to explore more heterogeneity and deviantbehavior.

Use the IV to construct alternative control groups usingnon-beneficiaries data.

Refine the theoretical framework to introduce maybeuncertainty, other functional forms?




Special thanks to...

Project Co-PIs:

Jennifer Alix-Garcia, University of Wisconsin-Madison

Volker Radeloff, University of Wisconsin-Madison

Elizabeth Shapiro, University of Duke

Katharine Sims, Amherst College

Also:

Mexican National Forestry Commission (CONAFOR).

Rodolfo Rubio, encuestadores, and research assistants.

3ie and NSF grants.

Graduate school at UW-Madison for financial assistance.




Thank you!


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