The Impact of Information Provision on Agglomeration Bonus Performance: An Experimental Study on Local Networks

Date: 2013-08
By: Banerjee, Simanti
de, Vries Frans
Hanley, Nicholas
van, Soest Daan
URL: http://d.repec.org/n?u=RePEc:stl:stledp:2013-09&r=net
 
The Agglomeration Bonus (AB) is a mechanism to induce adjacent landowners to spatially coordinate their land use for the delivery of ecosystem services from farmland. This paper uses laboratory experiments to explore the performance of the AB in achieving the socially optimal land management configuration in a local network environment where the information available to subjects varies. The AB poses a coordination problem between two Nash equilibria: a Pareto dominant and a risk dominant equilibrium. The experiments indicate that if subjects are informed about both their direct and indirect neighbors’ actions, they are more likely to coordinate on the Pareto dominant equilibrium relative to the case where subjects have information about their direct neighbors’ action only. However, the extra information can only delay – and not prevent – the transition to the socially inferior risk dominant Nash equilibrium. In the long run, the AB mechanism may only be partially effective in enhancing delivery of ecosystem services on farming landscapes featuring local networks.
Keywords: Agglomeration bonus, agri-environment schemes, biodiversity conservation, ecosystem services, information spillovers, Payments for Ecosystem Services, spatial coordination
廣告

有關用實驗進行 policy evaluations

Roth 的 papers

  • Roth, Alvin E. 2002. “The Economist as Engineer: Game Theory, Experimentation, and Computation
    as Tools for Design Economics.” Econometrica 70 (4): 1341–78.
  • Roth, Alvin E. 2007. “Repugnance as a Constraint on Markets.” Journal of Economic Perspectives
    21 (3): 37–58.
  • Roth, Alvin E. 2008. “What Have We Learned from Market Design?” Economic Journal 118 (527):
    285–310.

Organ Allocation Policy and the Decision to Donate

Kessler, Judd B., and Alvin E. Roth. 2012. “Organ Allocation Policy and the Decision to Donate." American Economic Review, 102(5): 2018–47. DOI:10.1257/aer.102.5.2018; Download Data Set

==noted by yinung==

哇! 器管捐贈也可以進行 lab 行為實驗來評估等候名單優先序之政策。

又見 Alvin Roth 的新作。不過除了實驗之外, 此文還建立了一個 simple model 理論模型來討論, 難怪可以上 AER…

器管捐贈註冊 (registry) 可以視為公共財 (因為 no medically eligible candidate can be excluded under present US law), …In other words, registering to be an organ donor resembles a public good ex ante that is a private good ex post. … the allocation rules allow for nondonors to be excluded (or to have a smaller probability of receiving an organ), effectively turning the registry into a club good…

分配法則將 public good 轉為 club good, 故可提高捐贈之意願…

==Abstract==

Organ donations from deceased donors provide the majority of transplanted organs in the United States, and one deceased donor can save numerous lives by providing multiple organs. Nevertheless, most Americans are not registered organ donors despite the relative ease of becoming one. We study in the laboratory an experimental game modeled on the decision to register as an organ donor and investigate how changes in the management of organ waiting lists might impact donations. We find that an organ allocation policy giving priority on waiting lists to those who previously registered as donors has a significant positive impact on registration. (JEL C91, D64, I11)

Mechanism Experiments and Policy Evaluations

Ludwig, Jens, Jeffrey R. Kling, and Sendhil Mullainathan. 2011. “Mechanism Experiments and Policy Evaluations." Journal of Economic Perspectives, 25(3): 17–38.
DOI:10.1257/jep.25.3.17

Abstract Randomized controlled trials are increasingly used to evaluate policies. How can we make these experiments as useful as possible for policy purposes? We argue greater use should be made of experiments that identify the behavioral mechanisms that are central to clearly specified policy questions, what we call “mechanism experiments." These types of experiments can be of great policy value even if the intervention that is tested (or its setting) does not correspond exactly to any realistic policy option.

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See also Journal of Economic Perspectives Vol. 25, Issue 3 — Summer 2011

(2) Why Economists Should Conduct Field Experiments and 14 Tips for Pulling One Off
John A. List
In this introduction to the symposium, I first offer an overview of the spectrum of experimental methods in economics, from laboratory experiments to the field experiments that are the subject of this symposium. I then offer some thoughts about the potential gains from doing economic research using field experiments and my own mental checklist of 14 steps to improve the chances of carrying out an economics field experiment successfully.
Full-Text Access | Supplementary Materials
(4) The Role of Theory in Field Experiments
David Card, Stefano DellaVigna and Ulrike Malmendier
We classify all published field experiments in five top economics journals from 1975 to 2010 according to how closely the experimental design and analysis are linked to economic theory. We find that the vast majority of field experiments (68 percent) are Descriptive studies that lack any explicit model; 18 percent are Single Model studies that test a single model-based hypothesis; 6 percent are Competing Models studies that test competing model-based hypotheses; and 8 percent are Parameter Estimation studies that estimate structural parameters in a completely specified model. We also classify laboratory experiments published in these journals over the same period and find that economic theory has played a more central role in the laboratory than in the field. Finally, we discuss in detail three sets of field experiments—on gift exchange, on charitable giving, and on negative income tax—that illustrate both the benefits and the potential costs of a tighter link between experimental design and theoretical underpinnings.
Full-Text Access | Supplementary Materials
(5) Field Experiments with Firms
Oriana Bandiera, Iwan Barankay and Imran Rasul
We discuss how the use of field experiments sheds light on long-standing research questions relating to firm behavior. We present insights from two classes of experiments—within and across firms—and draw common lessons from both sets. Field experiments within firms generally aim to shed light on the nature of agency problems. Along these lines, we discuss how field experiments have provided new insights on shirking behavior and the provision of monetary and nonmonetary incentives. Field experiments across firms generally aim to uncover firms’ binding constraints by exogenously varying the availability of key inputs such as labor, physical capital, and managerial capital. We conclude by discussing some of the practical issues researchers face when designing experiments and by highlighting areas for further research.
Full-Text Access | Supplementary Materials

IREE:2010 Special issue: Experimental Economics in the Classroom

International Review of Economics Education

(IREE), Volume 9, Issue 2, 2010

Editorial
Mike Watts and Ross Guest

Discovering Economics in the Classroom with Experimental Economics and the Scottish Enlightenment
Taylor Jaworski, Vernon Smith and Bart Wilson

Teaching Opportunity Cost in an Emissions Permit Experiment
Charles Holt, Erica Myers, Markus Wrake, Dallas Burtraw and Svante Mandell

Do Classroom Experiments Affect the Number of Economics Enrollments and Majors?
Tisha Emerson and Beck Taylor

Experiential Learning with Experiments
Henrik Egbert and Vanessa Mertins

Patents and R&D: a Classroom Experiment
Amy Diduch

To Work or Not to Work … That is the Question: Labour Market Decisions in the Classroom
Arlene Garces-Ozanne and Phyll Esplin

Using Economic Classroom Experiments
Todd R. Kaplan and Dieter Balkenborg

Mechanism Experiments and Policy Evaluations

 

Date: 2011-05
By: Jens Ludwig
Jeffrey R. Kling
Sendhil Mullainathan
URL: http://d.repec.org/n?u=RePEc:nbr:nberwo:17062&r=net
Randomized controlled trials are increasingly used to evaluate policies. How can we make these experiments as useful as possible for policy purposes? We argue greater use should be made of experiments that identify behavioral mechanisms that are central to clearly specified policy questions, what we call “mechanism experiments.” These types of experiments can be of great policy value even if the intervention that is tested (or its setting) does not correspond exactly to any realistic policy option.
JEL: C93