Economic statistics as political artefacts

Abstract

Macroeconomic statistics simultaneously shape and try to capture the political economy we study. Their biases mold social and political dynamics; they also infect academic and policy analysis. Political economy can both benefit from and advance an understanding of economic statistics as political artefacts. To help unlock that potential, this article builds on scholarship dispersed across disciplines and highlights three points. First, a binary debate that either acclaims or vilifies economic data is misdirected. Indispensable for public policy, quantification is neither good nor bad per se; the question is what its specific ramifications are. Second, macroeconomic statistics have been built around an ideal of white male factory work for wages. The further economic activity is removed from that image, the more statistics misrepresent or ignore it, with systematic biases as a result. Third, the real-world impact of statistics always depends on how they are understood, used, and subverted. It hinges on statistical practices, not just on abstract measurement approaches. As political economists we are political agents when we define, and reproduce, our object of study. We face both an analytical and a normative imperative to work with and towards statistics that do justice to the world and the people in it.

The delusive economy: how information and affect colour perceptions of national economic performance

“…We thus do not assume that official figures about unemployment or inflation are objectively correct. Indicators’ underlying definitions are ambiguous enough to justify doubts about their concept validity (Aragão and Linsi 2022 ; Linsi and Mügge 2019 ; Mügge and Linsi 2021 ; Mügge 2022 ). At the same time, the survey questions explicitly ask for people’s familiarity with official numbers as reported in the media, such that they become our yardstick for accuracy.…”

What does gross national happiness really measure? An immersive observation in Lamshey, Bhutan

“…For the authors, the issues at stake remain, first of all, to study the effects produced (and potentially new) by quantification, to compare quantification exercises in similar fields, or to propose a case study on a quantification system and the decisions affected. In this extension, studies have questioned the use and political recovery of data (Demortain, 2019;Mügge, 2020) and the methods of calculation of certain specific domains such as the labor market (Dufour, 2021), the digital market (Chun & Sauder, 2021) or the music industry (Baym et al, 2021), and education (Hillebrandt & Huber, 2020). Moreover, none seems to have looked at measuring the population's happiness.…”

Illicit financial flows and country-by-country reporting in extractive industries

“…The growing realization of their importance has meant that improving data is now a priority in development initiatives (Gates Foundation 2016). But economic data, much like economic models, also work to construct rather than merely reflect the economy (Callon 2020;MacKenzie 2008;Mügge 2020). Economic data are made up from standards and definitions which we have predefined on the basis of what we perceive to be important and meaningful in the economy (Perry and Nölke 2006).…”

“…Missing data or imprecise measurements in economic data are common, particularly in the developing world, and undermine the value of statistics. Potentially even more troublesome are the figures which are used widely and viewed as reliable, but suffer from problems in their conceptual underpinnings (Linsi and Mügge 2019;Mügge 2020). How we should address these weaknesses in current data systems and measurement remains an open question.…”

“…Tax collection has historically motivated the invention of economic measurements (Graeber 2011;Mügge 2020). In modern times, tax collection is still motivating the invention of new data standards.…”