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Trust in Official Statistics. an Econometric Search for Determinants

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Trust in Official Statistics. an Econometric Search for Determinants Trust in official statistics. An econometric search for determinants. The case of Luxembourg Dr Serge Allegrezza. Director General. Institute of Statistics and Economic Studies (STATEC) Paper prepared for the 16th Conference of IAOS OECD Headquarters, Paris, France, 19-21 September 2018 Session 2.C., Day 1, 19/09, 14:30: Communication & statistical literacy, strategic issues Dr Serge Allegrezza [email protected] STATEC Trust in official statistics. An econometric search for determinants. The case of Luxembourg Prepared for the 16th Conference of the International Association of Official Statistics (IAOS) OECD Headquarters, Paris, France, 19-21 September 2018 2 ABSTRACT In a complex society, flooded with a deluge of data from the Internet, trust in official statistics and in the national institutes of statistics play a key role in preserving public numbers as a reference and benchmark. This paper takes the view of the demand-side of statistics, investigating the perception of the trustworthiness of public numbers and the functioning of the national institutes of statistics. Trust is a matter of perception and opinion, which is as important as the supply-side view, i.e. compliance with peer reviewed processes and quality standards. The difficulty to assert statistical facts as reality, in particular in a context of “post-truth” social media and populist discourse, has increased. Representative surveys on the trust of statistics are quite rare and available data is not systematically analysed. Comparative cross country studies at macro and micro level are missing. This study uses two surveys dating back to 2015 and 2017, carried out by an independent pollster (TNS-ILRES) which interviewed over 2500 residents in each wave in Luxembourg. The questionnaire contains a bunch of questions on trust in institutions (parliament, government, central bank, NSI etc.) and on different types of media channels. The questionnaire asks interviewees about perceived political independence of the NSI, the use of official data in business, research and public debate and, finally, participation in official surveys. There are some questions on political preferences and confidence in fellow citizens. Furthermore, the questionnaire collects data on education, income, gender, professional activity and age. Ideally, the econometric analysis (logit regressions) should confirm the independence, neutrality, non-discrimination and high trust of official statistics and the NSI. All the coefficients of variables linked to political independence or political preferences, gender, age and class (education and income) revealing some discrimination in the perception of official statistics, should not be significant. There should be, ideally, a positive effect of confidence resulting from the protection of personal data, the participation in official (compulsory) time consuming surveys and from the utilization of statistics. The analysis of data related to 2015 and 2017 strongly confirms the political independence of statistics and of the NSI (STATEC), the importance of data protection, the use of statistics and the importance of confidence in media as main distribution channel. The conclusion advocates systematic and in-depth analysis of micro data on various dimensions of trust in statistics and their determinants, over time and across countries. The success of “fact checking” activities, training and tailor made communications (narratives for precise targets) might also be assessed by systematic and representative surveys on trust and numeracy. To gain more insights and share recommendations, I advocate that those surveys should be based on a common questionnaire (in the framework of the OECD) and exploited according to an agreed methodology. Keywords: Trust in official statistics, cognitive science, econometrics 3 Introduction “Damned lies and statistics”. Funny jokes about statistics are popular and stories about the way unabashed politicians or ruthless advertisers misuse statistics are quite familiar. In this paper, we will examine trust in official statistics and its determinants. Trust in official statistics, both in the official numbers and in the organizations producing the numbers, depends on trustworthiness, the standards by which the production process works and the availability of data to the public. Trust in statistics is defined and measured by the guidelines set up by the OECD. An early version of the paper1 was presented at the Marrakech ISI conference in July 2017 analysing the data from the 2015 trust survey. This paper has been extended to incorporate the most recent survey on trust in statistics of 2017 in the case of Luxembourg and deepens former research on this topic (Allegrezza, 2014). In the first part, the paper is arguing why statisticians should focus on perception, underscoring the subjective view of “official numbers” and of the functioning of NSIs. Perception, with all its cognitive flaws and biases, as described in the emerging cognitive science literature, is an essential element to assess the trustworthiness of official statistics, both numbers and organizations producing the latter. The second part of the paper describes the data at hand and the relevant variables used in a bunch of logit regressions. The results of the analysis of the two data sets are compared. All in all, the findings confirm that, all else equal, personal data protection and political independence have a positive and significant impact on the probability of trust in official statistics and the NSI. Unfortunately, there is knowledge segregation: more educated people have more trust in numbers than the less educated. Trust and cognitive barriers to official statistics Trust is a complex phenomenon and the communication between official statistical institution and the public is not as straightforward as the basic “sender-receiver” scheme might suggest. There are few empirical studies available on trust in statistics and their determinants. The receivers of statistical information are very heterogeneous, endowed with different knowledge competencies in statistics and social sciences, have different expectations or wishes and are limited by time and money constraints. We propose to dig deeper in the relationship between the perception of trustworthiness, and the actual use of statistics by focusing on the subjective evaluation of the trustworthiness of official statistics produced by the national statistics institute in Luxembourg (STATEC). The communication of data and information has changed dramatically since the Internet and the social media are regarded as the main channels to access information. There seems to be some anxiety about a growing defiance of science and expertise in general, despite a growing level of education in our countries. It is difficult to assess quantitatively to what extent the limitations in literacy, numeracy and the resistance towards science are increasing2. In a 1 “Statistics in a post-truth society. Determinants of confidence, independence and usage of official statistics” 2 Eurobarometer survey (2010) suggests that reluctance towards science is significant (in 2010, 38% think we depend too much on science and not enough on faith) but this proportion is decreasing. 4 more general context, trust vis à vis public institutions (government, parliament, bureaucracy) and trust in other fellow citizens might be linked to trust in official statistics, interesting enough to be explored empirically. The suspicion of statistics has multiple reasons The first reason is certainly rooted in the awkward representation of society as a whole, structured around Quetelet’s “average man” wiping out uniqueness of individual characters, peculiar situations, contexts and biographies inherent to a single person. Olivier Rey, a French philosopher and mathematician, who has studied the emergence of numbers as convenient way of depicting the world, puts forcefully forward the denial of the singularity and distinctiveness of an individual by official numbers. He claims that this is a major cause explaining frustration with statistics. William Davies on the same lines argues that “both statisticians and politicians have fallen into the trap of talking like a state, giving the impression of having lost touch with single citizens3. The second reason of suspicion: statistics is a branch of mathematics. Probability for example entails a way of thinking which is distinct from everyday thinking. Our brains are wired in such a way that we need a conscious effort to dismiss the default mode of reasoning: using Bayes theorem does not come to our mind spontaneously and many solutions are counter intuitive. Thinking statistically is hard, as Nobel Prize winner Daniel Kahneman has demonstrated by manifold experiments in his famous book “Thinking, Fast and Slow”. It has been forgotten that trust in statistics is the result of a long and painful history. Theodor Porter (1996) in his book “Trust in numbers” makes it clear that official statistics can’t be understood properly unless examined through the lense of science history. The authority of official statistics is linked to the progressive emergence of quantification, the standardization of measurements and the process of validation of social numbers. Objectivity, taken as a synonym of realism, has been cultivated by promoting rules of fairness, impartiality, impersonality. Since a genuine, ontological “absolute objectivity” is not possible, scientists must cultivate proxies like “disciplinary objectivity”,
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