Page 361 - Invited Paper Session (IPS) - Volume 1

IPS169 Markku L.

The multiple faces of trust in statistics and
composite indicators: A case for healthy mistrust
Markku Lehtonen
Universitat Pompeu Fabra, Barcelona; Ecole des Hautes Etudes en Sciences Sociales, Paris;
University of Sussex, Brighton, UK

Abstract
Declining public trust in official statistics and institutions responsible for
statistics and indicator production is frequently highlighted as a key obstacle
to reasoned debate on policy options and governance choices. The potentially
harmful impacts of Big Data and an alleged “post-truth” era have further
accentuated such concerns. To remain trusted and credible, statistical
institutions must safeguard their authority as sources of independent and
scientifically sound indicators, while at the same time being prepared to
innovate and explore new methodological options. However, this paper
argues that, in addition to this trust-building work, indicator designers need
to embrace mistrust and distrust as essential for the generation of relevant
and influential composite indicators. While important, regaining trust should
not be seen as the overarching objective let alone a ‘silver bullet’. This paper
seeks to unpack the notion of trust and makes the case for mistrust and
distrust as potential resources rather than mere threats to the credibility and
authority of official statistics. For further empirical work, it proposes a
conceptual framework consisting of three dimensions of trust and a distinction
between mistrust and distrust, and illustrates the framework by concrete
examples from indicator work. The conclusions suggest ways for statistical
institutions to exploit the potential virtues of mistrust and adjusting their
strategies to maintain trust via a more nuanced understanding of the multiple
dimensions of trust, mistrust and distrust.

Keywords
Indicators; trust; mistrust; distrust; statistical offices; post-truth

1. Introduction
The alleged decline of trust in statistics and in statistical authorities has in
recent years generated increasing concern, often framed as part of broader
debates over the dangers of Big Data and post-truth politics. In one of the
most prominent among such accounts, Davies (2018) argues that “the basic
honesty of mainstream politicians, journalists and senior officials is no longer
taken for granted”, and pinpoints statistics as a key target of attack by the
“populist right”: “…with statisticians and economists chief among the various
“experts” that were ostensibly rejected by voters in 2016. Not only are statistics
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