Forecasting under Uncertainty: How Network Composition Shapes Future-Oriented Cognition

DOI10.1177/00027162211061259
Published date01 September 2021
Date01 September 2021
ANNALS, AAPSS, 697, September 2021 99
DOI: 10.1177/00027162211061259
Forecasting
under
Uncertainty:
How Network
Composition
Shapes Future-
Oriented
Cognition
By
ILKA VARI-LAVOISIER
1061259ANN THE ANNALS OF THE AMERICAN ACADEMYFORECASTING UNDER UNCERTAINTY
research-article2021
Future migration is central to contemporary politics,
but we know little of how citizens and policy-makers
perceive and predict migratory trends. I analyze migra-
tion forecasting in a representative sample of the popu-
lation of France, using survey data and administrative
records to document differences in the accuracy of
forecasting among groups of individuals. The article
takes an interdisciplinary approach to future-oriented
thinking, conceiving it as a distributed cognitive pro-
cess, and showing that educational attainment and
migratory background shape one’s ability to predict
short-term trends. My analysis stresses the importance
of accounting for sociodemographic characteristics and
social networks in forecasting: I show that social diver-
sity can improve predictions and extend studies based
on the Delphi methodology by discussing the relevant
expertise to forecast in different realms.
Keywords: forecasting; prediction; cognition; interna-
tional migration; migratory trends; Delphi
methodology
In the geopolitics of mobility, 2020 has been
a turning point. Unprecedented travel
restrictions brought international migration
to historically low levels—and who knows
how and when mobility will resume. As in
many domains currently, uncertainty prevails.
However, migration politics inherently implies
a degree of anticipation for better or worse.
The threat that opening borders would lead to
the “invasion” of rich countries (Lessault and
Beauchemin 2009), or the statement that
migrants would contribute positively to their
countries of destination, imply assumptions
Ilka Vari-Lavoisier is a researcher on the PLAN project,
led by Virginie Guiraudon (CEE) at Sciences Po and in
collaboration with Jacqueline Broadhead (COMPAS) at
the University of Oxford. She is also a research affiliate
in the Department of Anthropology, an associate mem-
ber of the Department of Sociology, and teaches for the
Department for Continuing Education at the University
of Oxford.
Correspondence: ilka.vari-lavoisier@anthro.ox.ac.uk
100 THE ANNALS OF THE AMERICAN ACADEMY
about what would happen in the future. Anticipating the pattern of migratory
flows is key to “ensure effective management of asylum, migration and integra-
tion systems” (Nejad and Schurer 2018). But how do people form their predic-
tions about migration? Does the perception of the future of migration vary,
depending on individuals’ cognitive abilities, socioeconomic status, and social
networks; and which characteristics are associated with a better ability to fore-
cast?
The existing literature on forecasting has largely focused on highly educated
respondents, with an explicit interest in politics, as I discuss in the remainder
of this article. In the real world, citizens have heterogeneous levels of cognitive
skills, education, and political competence; but empirical research on predic-
tion making in the general population is lacking. Moreover, current studies
tend to focus on the psychological factors associated with prediction making,
overlooking the socioeconomic factors influencing one’s perception of the
future. This article shows that individual trajectories (in particular educational
attainment and migratory background) shape individuals’ ability to predict
short-term trends. Furthermore, prediction making has been mostly studied at
the individual level, concealing the influence of group-level characteristics on
future-oriented cognition. To the best of my knowledge, there is an absence of
empirical research conducted on the general population putting into perspec-
tive the influence of individual and collective resources when it comes to pre-
diction making. This article advances this line of research by showing that the
best forecasters have several traits: they score high on fluid intelligence and
cognitive flexibility, they tend to be highly educated, and they have more
diverse social networks. Discussing why people who interact with migrants
predict migratory trends accurately, this article adds to a growing literature that
stresses the cognitive benefits of social diversity (Baggio et al. 2019; Bai,
Ramos, and Fiske 2020).
To do so, this article draws on an empirical design mining the intersection
between the cognitive and the social sciences. More precisely, it combines sur-
vey data—collected from a representative sample of 1,405 French citizens in
July 2020—with administrative data accessed in November 2020. This empiri-
cal design sheds new light on the mainstream population’s and policy-makers’
perception of a burning social issue—the future of migration in the early 2020s.
By connecting several strands of literature, this piece further confirms the rel-
evance of combining disciplines to study sociopolitical cognition in a world on
the move.
NOTE: The PLAN project (Prediction-making at the Local level: Anticipating what’s Next) has
received funding from the IC Migrations (grant ANR-17-CONV-0001). It is led by Virginie
Guiraudon (Centre for European and Comparative studies, Sciences Po), in collaboration with
Jacqueline Broadhead (COMPAS, University of Oxford). The author thanks Jacqueline
Broadhead and Virginie Guiraudon for their supervision. Thanks are due to Sorana Toma and
all the participants of the 2020 Cognition & Migration conference for their constructive feed-
back. The author acknowledges Susan T. Fiske’s mentorship and key support to develop this
research.

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