Behavioral Insights for Agri-Environmental Program and Policy Design: A Literature ReviewLeah H. Palm-Forster, University of Delaware

Coauthors:Nicholas Janusch, California Energy CommissionKent D. Messer, University of DelawarePaul J. Ferraro, Johns Hopkins University

USDA, Washington D.C. April 25, 2018

• Applying behavioral insights and experimental designs to improve programs related to agriculture and the environment.

• Funding from USDA ERS and NIFA support à researchers work closely with USDA partners – ERS, NRCS, FSA

• More information: www.centerbear.org

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Conference on Behavioral & Experimental Agri-environmental Research: Methodological Advancements and Applications to Policy

Conference discussion emphasized ways to increase the rigor of experimental economics research in this area:

1. Careful design à treatments, randomization, identification strategy, power analyses; peer-reviewed designs

2. Register hypotheses à Caution with ex-post multiple comparisons, causal vs. predictive questions

3“We need to slow down in order to go fast.” -someone smart

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Behavioral insights can inform policy

• Nudges have the potential to alter decisions in predictable and cost-effective ways

• Successful examples in health, education, finance, poverty alleviation and charitable giving.

… and energy and water conservation too.

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How can behavioral insights inform the design of agri-environmental programs?

Environmental benefits

Cost-effective incentives and

technical assistance

Management changes

The objective of agri-environmental programs

© USDA ERS [source link]

Why are agri-environmental programs challenging to design and implement?

• We rely on voluntary programs

• Heterogeneity à Not all fields and farmers are alike

• Information asymmetries

• Disproportionality of pollution à targeting is difficult

• Additionality à would benefits exist without the program?

• Transaction costs of participation can limit enrollment

• Farmers’ rely on different information sources

• Land tenure dynamics

Why are agri-environmental programs challenging to design and implement?

• We rely on voluntary programs• Heterogeneity à Not all fields and farmers are alike

• Information asymmetries

• Disproportionality of pollution à effective targeting is limited.

• Additionality à would benefits exist without the program?

• Transaction costs of participation can limit enrollment

• Farmers’ rely on different information sources

• Land tenure dynamics

In this paper we:

1. Review the experimental literature of behavioral insights within the agri-environmental domain

2. Categorize the behavioral insights that could be relevant for policy design and implementation

3. Present effect sizes for behavioral treatments relevant for agri-environmental policy.

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How can behavioral insights inform the design of agri-environmental programs?

In this paper we:

1. Review the experimental literature of behavioral insights within the agri-environmental domain

2. Categorize the behavioral insights that could be relevant for policy design and implementation

3. Present effect sizes for behavioral treatments relevant for agri-environmental policy.

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How can behavioral insights inform the design of agri-environmental programs?

Wait a minute… If we already have all of these insights,

don’t we know what will work?

We use the MINDSPACE framework developed byDolan et al. (2012)

Cue Behavior

Messenger We are heavily influenced by who communicates information to us

Incentives Characteristics and delivery of incentives affects their impact

Norms We are strongly influenced by what others do

Defaults We “go with the flow” of pre-set options

Salience Our attention is drawn to what is novel and seems relevant to us

Priming Our acts are influenced by subconscious cues

Affect Our emotional associations can powerfully shape our actions

Commitment We seek to be consistent with our public promises

Ego We act in ways that make us feel better about ourselves 11

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Ag-E MINDSPACE: inclusion criteria

To be included, the study must:

1. test the effect of one or more behavioral nudge

2. be motivated by an agri-environmental challenge or program.

3. have economic content or consequences.

4. employ an experimental design in which the measured behavioral outcomes are revealed behaviors (rather than stated preferences) with salient costs and benefits.

… & be published (?)

To be included, the study must:1. test the effect of one or more behavioral nudge2. be motivated by an agri-environmental challenge or

program.3. have economic content or consequences.4. employ an experimental design in which the measured

behavioral outcomes are revealed behaviors (rather than stated preferences) with salient costs and benefits.

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Ag-E MINDSPACE: inclusion criteria

Producer behavior Consumer behavior

Land/habitat preservation

Working lands management

To be included, the study must:1. test the effect of one or more behavioral nudge2. be motivated by an agri-environmental challenge or

program.3. have economic content or consequences.4. employ an experimental design in which the measured

behavioral outcomes are revealed behaviors (rather than stated preferences) with salient costs and benefits.

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Ag-E MINDSPACE: inclusion criteria

Producer behavior Consumer behavior

Land/habitat preservation

Working lands management

Ag-E MINDSPACE Taxonomy of Experiments Adapted from Harrison and List (2004), Messer (2014), and Higgins et al. (2017)

Experiment Type Description

Laboratory experiment Student participants, abstract framing, and imposed sets of rules.

Artefactual field experiment

Same as a laboratory experiment but with a subject pool from the target population.

Framed field experiment

Subject pool from the target population; field context is incorporated in the experiment

Enlisted field experiment

Same as a framed experiment except that the environment is one in which the participants would naturally undertake the tasks being observed.

Administrative field experiment

Same as enlisted experiment but systematically tests new ways of operating an ongoing program. Participants likely unaware of research participation.

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• Allows for comparison of treatment effects across outcomes using normalized units

• Researchers can estimate the direction and magnitude of the expected treatment effect

• Can be used to conduct power analyses

• Note: Many studies do not present the necessary information –we need to do a better job presenting the relevant data 16

Standardized effect sizes

Estimated treatment effect

standard deviation of the outcome variable for the control group

Ag-E MINDSPACE applying the framework by Dolan et al. (2012)

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• People respond to the messenger who delivers information or an intervention

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Messenger

Messages and messengers are critical

• Media campaigns v. one-on-one interactions• Building credibility• ‘Localizing’ knowledge• Convincing people that their actions matter• Construction and interpretation of

knowledge among groups.• Different ‘agri-cultures’ among farmers

Many lessons from case studies, few from

controlled experiments

• Butler et al. (2017) and Griesinger et al. (2017) used lab experiments to test how polluting behavior was affected by feedback from mascots (community and unfamiliar) and peers.

• Relating this to agri-environmental decision-making� Peers� Community leaders� Input suppliers� University Extension� Program managers

• Communicating about controversial issues.

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Messenger

• Characteristics of incentives and their delivery affect behavior.

• Dolan et al.’s (2012) insights about incentives: (1) reference points matter(2) losses loom larger than gains (loss aversion)(3) small probabilities are over weighted(4) money is allocated mentally to discrete accounts(5) choices consistently reflect living for today at the expense of tomorrow (present bias).

• Mechanism design has been widely studied, but few studies investigate the effects of incentive attributes.

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Incentives

Program application: What is the optimal timing of payments for conservation actions?

• Duquette et al. (2012) used an administrative field experiment to investigate farmers’ discount rates for conservation payments� $400 now or more later --> find average discount rate of 34%� Timing of payments may increase participation; decrease costs

• Clot and Stanton (2014) found that present-biased individuals were more likely to participate in a tree planting program in Uganda.

• Costa Rica’s (oversubscribed) reforestation program – large up-front payment and smaller future payments.

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• We often try to conform to the expectations of others

• Banerjee et al. (2014) found that information on neighbors’ behaviors improved the environmental efficiency of a land conservation program.

• Wallander et al. (2017) could not detect any difference in sign-up rates between farmers who received a simple reminder about the enrollment period and farmers who received the reminder and social comparisons.

• Key questions:� How are norms communicated? � Norms can be group specific – which norms matter?

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Norms

• People stick with the default (status quo) option instead of exerting effort to actively make another choice.

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Defaults

• Each $1 increase in the default bid, increased residents’ cost-share bids by 19 cents, on average (Li, Fooks, and Messer, 2017).

• Bids were 10 percentage points higher if (~$1,400) if they started with a 100% starting bid (Ferraro and Messer, unpublished)

• Our attention is drawn to what is novel and seems relevant to us

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Salience

• Examples:

� Impact of different CRP reminder letters (Wallander et al. 2017).

� Salient information can have adverse effects – e.g., rent-seeking from information disclosure in reverse auctions (Cason et al. 2003; Banerjee et al. 2015).

• Our acts are often influenced by sub-conscious cues

• Behavior can be altered by exposure to words, sights, and sounds.

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Priming

• Priming w/ reminders� CRP sign up reminder letter

(Wallander et al. 2017)

� Reminder postcards before and after delivery of county committee elections ballots (Higgins et al. 2017)

• Our emotional associations can powerfully shape our actions

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Affect

Option A ($100 wine)

Option B (4 bottles of $25 wine)

• Certain words, images, and events can change the way people view and value various options.

• Examples: � Framed experiment using the

threat of imminent destruction (Messer & Borchers 2015)

� Framing of instructions when presenting downstream water pollution game (Czap et al. 2013)

• We seek to be consistent with our public promises � Change behaviors and self-identity� Evoke willingness to conform� Cognitive elaboration à engagement generates

positive attitude toward the behavior

• Can be used as a nudge to ask producers and consumers to make voluntary conservation commitments.

• Lokhorst et al. (2009) found that Dutch farmers that made a public commitment regarding conservation, stated a greater desire to engage in unsubsidized conservation. 27

Commitment

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• We act in ways that make us feel better about ourselves

• Image motivation: Both consumers and agricultural producers may be motivated by a desire to be seen as protecting the environment

• Example:� Smiley and frowney faces in downstream water pollution game (Czap et al., 2013)� People could send a costly signal to upstream producers

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Ego (& Identity)

• We act in ways that make us feel better about ourselves

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Ego (& Identity)

© Cape Gazette, Deny Howeth

Awarding environmental stewardship

Ag-E MINDSPACE Evidence of Agri-Environmental Behavioral Insights

(this table is a work in progress)

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MINDSPACE ProducersLand Preservation Working Lands

MessengerGriesinger et al. 2017Lab

Butler et al. 2017Lab

Incentives

Duquette et al. 2012Admin

Li et al. 2014 Lab

NormsWallander et al. 2017Adm

Banerjee et al. 2014 Lab

Griesinger et al. 2017 Lab

DefaultsMesser et al. 2015Framed

Salience

Wallander et al. 2017Adm

Banerjee et al. 2014 Lab

Banerjee et al. 2015 Lab

Cason et al. 2003 Lab

Li et al. 2014 Lab

Higgins et al. 2017Adm

Cason et al. 2003 Lab

PrimingWallander et al. 2017Adm Czap et al. 2013 Lab

Higgins et al. 2017Adm

AffectMesser & Borchers 2015 Framed Czap et al. 2013 Lab

Commitment

EgoGriesinger et al. 2017 Lab

Czap et al. 2013 Lab

Take aways

• Challenge: Despite promising behavioral insights in other contexts, we need more (& robust!) evidence to know how behavioral interventions affect agri-environmental decision-making

• Opportunity: There may be some low-hanging research fruit à study behavioral interventions that have been shown to be powerful drivers of environmental behaviors and test them in an agri-environmental context. � Careful experimental design is critical.� Build partnerships with program administrators

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Thank you! Questions?Email: leahhp@udel.edu Join us in

three weeks!

ReferencesBanerjee, S., A.M. Kwasnica, and J.S. Shortle. 2015. “Information and Auction Performance: A Laboratory Study of Conservation Auctions for Spatially Contiguous Land

Management.” Environmental and Resource Economics 61(3):409–431.

Butler, J., J. Fooks, K.D. Messer, and L.H. Palm-Forster. 2017. “How Public Information, Mascots, and Data Graphics Can Help the Environment: An Experimental Study Related to Nonpoint Source Pollution” Working Paper, Department of Applied Economics & Statistics, University of Delaware, Newark, DE.

Cason, T.N., L. Gangadharan, and C. Duke. 2003. “A Laboratory Study of Auctions for Reducing Non-Point Source Pollution.” Journal of Environmental Economics and Management46(3):446–471.

Clot, S., and C.Y. Stanton. 2014. “Present bias predicts participation in payments for environmental services: Evidence from a behavioral experiment in Uganda.” Ecological Economics 108:162–170.

Czap, N.V., H.J. Czap, M. Khachaturyan, M.E. Burbach, and G.D. Lynne. 2013. “Smiley or Frowney: The Effect of Emotions and Empathy Framing in a Downstream Water Pollution Game.” International Journal of Economics and Finance 5(3):9.

Dolan, P., M. Hallsworth, D. Halpern, D. King, R. Metcalfe, and I. Vlaev. 2012. “Influencing behaviour: The mindspace way.” Journal of Economic Psychology 33(1):264–277.

Duflo, E., M. Kremer, and J. Robinson. 2011. “Nudging Farmers to Use Fertilizer: Theory and Experimental Evidence from Kenya.” American Economic Review 101(6):2350–2390.

Duquette, E., N. Higgins, and J. Horowitz. 2012. “Farmer Discount Rates: Experimental Evidence.” American Journal of Agricultural Economics, 94(2), 451–456.

Griesinger, M., L.H. Palm-Forster, J. Butler, K. Messer, and J. Fooks. 2017. "Stewardship Signaling and the Power of Using Social Pressures to Reduce Nonpoint Source Pollution." Paper presented at the Agricultural & Applied Economics Association (AAEA) Annual Meeting, Chicago, IL, 30 July – 1 August.

Harrison, G.W., J.A. List, and C. Towe. 2007. “Naturally Occurring Preferences and Exogenous Laboratory Experiments: A Case Study of Risk Aversion.” Econometrica 75(2):433–458.

Higgins, N., D. Hellerstein, S. Wallander, and L. Lynch. 2017. “Economic Experiments for Policy Analysis and Program Design: A Guide for Agricultural Decisionmakers.” Washington, DC: U.S. Department of Agriculture, Economic Research Service Economic Research Report Number 236, August.

Li T., J. Fooks, K. Messer. 2017. “Residents’ Preferences in Adopting Water Runoff Management Practices: Examining the Effect of Behavioral Nudges in A Field Experiment” Paper presented at the Agricultural & Applied Economics Association (AAEA) Annual Meeting, Chicago, IL, 31 July – 1 August.

Messer, K.D., and A.M. Borchers. 2015. “Choice for Goods Under Threat of Destruction.” Economics Letters 135:137–140.

Messer, K.D., and J.J. Murphy. 2010. “Special Issue on Experimental Methods in Environmental, Natural Resource, and Agricultural Economics.” Agricultural and Resource Economics Review 39(2):3–6.

Wallander, S., P. Ferraro, and N. Higgins. 2017. “Addressing Participant Inattention in Federal Programs: A Field Experiment with The Conservation Reserve Program.” American Journal of Agricultural Economics 99(4):914–931.

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