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1.
Nature ; 617(7962): 676, 2023 05.
Artigo em Inglês | MEDLINE | ID: mdl-37221333
2.
PLoS One ; 15(3): e0229501, 2020.
Artigo em Inglês | MEDLINE | ID: mdl-32119692

RESUMO

Language is critical to coordination in groups. Though, how language affects coordination in groups is not well understood. We prime distributive and integrative language in a bargaining experiment to better understand the links between group outcomes and communication. We accomplish this by priming interests or positions language in randomized groups. We find that priming positions as opposed to interests language leads to agreements where controllers, subjects with unilateral authority over the group outcome, receive a larger share of the benefits but where the total benefits to the group are unaffected. In contrast to common justifications for the use of integrative language in bargaining, our experimental approach revealed no significant differences between priming interests and positions language in regards to increasing joint outcomes for the groups. Across treatments, we find subjects that use gain frames and make reference to visuals aids during bargaining experience larger gains for the group, while loss frames and pro-self language experience larger gains for the individual through side payments. This finding suggests a bargainer's dilemma: whether to employ language that claims a larger share of group's assets or employ language to increase joint gains.


Assuntos
Negociação Coletiva , Idioma , Adulto , Algoritmos , Comunicação , Feminino , Humanos , Masculino , Adulto Jovem
3.
Am J Agric Econ ; 100(1): 220-238, 2018 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-29332946

RESUMO

We introduce a model that incorporates two important elements to estimating welfare gains from groundwater management: stochasticity and a spatial stock externality. We estimate welfare gains resulting from optimal management under uncertainty as well as a gradual stock externality that produces the dynamics of a large aquifer being slowly exhausted. This groundwater model imposes an important aspect of a depletable natural resource without the extreme assumption of complete exhaustion that is necessary in a traditional single cell (bathtub) model of groundwater extraction. Using dynamic programming, we incorporate and compare stochasticity for both an independent and identically distributed as well as a Markov chain process for annual rainfall. We find that the spatial depletion of the aquifer is significant to welfare gains for a parameterization of a section of the Ogallala Aquifer in Kansas, ranging from 2.9% to 3.01%, which is larger than those found previously over the region. Surprisingly, the inclusion of stochasticity in rainfall increases welfare gains only slightly.

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