[ABE-L] Lembrete: COLMEA - 22/07/2021 - hoje

[Maria Eulalia Vares]

Prezados colegas,



Devido à pandemia, estamos realizando de forma virtual as atividades do
COLMEA, colóquio interinstitucional que congrega vários grupos do Rio de
Janeiro.

Nosso próximo encontro será no dia 22 de julho (quinta-feira) com início às
14 horas, utilizando o software Google Meet.  Na ocasião teremos as
palestras de José Heleno Faro (Insper) e Marcelo Cunha Medeiros (PUC-Rio)
abordando temas de amplo interesse na nossa comunidade.

Todos são muito bem-vindos. O acesso ao encontro se dará através do link
abaixo: https:// meet.google.com/hjr-wkvz-tyi

Para participar por telefone, disque +1 316-778-8055 e digite este PIN: 534
154 505#. Pode-se também acessar utilizando o código QR que consta no
cartaz.

Títulos e resumos no final da mensagem. Mais informações sobre o nosso
colóquio COLMEA, inclusive sobre todos os encontros anteriores podem ser
encontradas através da homepage http://www.im.ufrj.br/~coloquiomea/

Agradecemos a divulgação.

Atenciosamente,

O comitê organizador:

Americo Cunha (UERJ)

Augusto Q. Teixeira (IMPA)

Evaldo M. F. Curado (CBPF)

Leandro P. R. Pimentel (UFRJ)

Maria Eulalia Vares (UFRJ)

Nuno Crokidakis (UFF)

Simon Griffiths (PUC-Rio)



===============



Resumos:



*Dynamically consistent objective and subjective rationality*
José Heleno Faro (Insper)

A group of experts, for instance climate scientists, is to choose among two
policies f and g. Consider the following decision rule. If all experts
agree that the expected utility of f is higher than the expected utility of
g, the unanimity rule applies, and f is chosen. Otherwise, the
precautionary principle is implemented and the policy yielding the highest
minimal expected utility is chosen. This decision rule may lead to time
inconsistencies when an intermediate period of partial resolution of
uncertainty is added. We show how to coherently reassess the initial set of
experts' beliefs so that choices become dynamically consistent: new beliefs
should be added until one obtains the smallest ``rectangular set'' that
contains the original one. Our analysis offers a novel behavioral
characterization of rectangularity and a prescriptive way to aggregate
opinions in order to avoid sure regret.





*Counterfactual analysis with artificial controls: inference, high
dimensions and nonstationarity *
Marcelo Cunha Medeiros (PUC-Rio)

Recently, there has been growing interest in developing statistical tools
to conduct counterfactual analysis with aggregate data when a single
``treated'' unit suffers an intervention, such as a policy change, and
there is no obvious control group. Usually, the proposed methods are based
on the construction of an artificial counterfactual from a pool of
``untreated'' peers, organized in a panel data structure. In this paper, we
consider a general framework for counterfactual analysis for
high-dimensional, nonstationary data with either deterministic and/or
stochastic trends, which nests well-established methods, such as the
synthetic control. We propose a resampling procedure to test intervention
effects that does not rely on postintervention asymptotics and that can be
used even if there is only a single observation after the intervention. A
simulation study is provided as well as an empirical application.
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