Measure formulas between countries and over time

The FickleFormulas project has examined macroeconomic indicators. But the political economy drivers underlying them are not easy to pin down. They play out in national statistical offices, government ministries, and sprawling international organizations. They have roots in academic debates that stretch back more than a century. They are fought out between unions and employers, between savers and depositors, across gender divides, or simply between national capitals. We have therefore had to be attentive to the long arches of intellectual history as much as to mundane office politics in statistical offices.

A plethora of approaches and methods

A research object that has so many different facets has called for a broad range of lenses to bring it into focus. Above all, we are pragmatic: the questions we ask determine our methodologies. With so many white spots on our intellectual map, the FickleFormulas projects feature a plethora of approaches and methods.

Chronicle the evolution of formulas

Many of our subprojects have tried to explain why we measure our economies the way we do. Our dependent variable have been the choices for or against particular formulas to measure a concept. Our first step has been to chronicle the evolution of formulas over time and to discover key junctures – moments when officials adjusted these formulas or rejected forceful reform initiatives.

The places we study

When and where we study these formulas varies. The first subproject has compared the indicator politics over the past decades in a handful of West-European and North American countries, where global indicator debates in the post-War period surfaced first. A systematic comparison has helped to reveal which factors have been most important in pushing countries towards one or the other formula.

Beyond the North Atlantic, data becomes scarcer

Venture beyond the North Atlantic, and data becomes much scarcer. Needing to dig deeper, other subprojects have focused on South Africa, China, and Brazil to understand what journey indicators have taken in these countries. 

National politics are not enough

National dynamics are key to indicator politics, but so is what happens in organizations that go beyond the nation state – the OECD, the IMF, the World, and of course the EU. These organizations do not just coordinate international harmonization efforts but work hard to convert other countries to international statistical conventions and to make them legible. And in the case of the EU a single, supranational entity – Eurostat – enmeshes formerly standalone national agencies in a dense European web of official statistics.

Focus on key players

FickleFormulas has studied indicators that stand at the heart of macroeconomic statistics: those measuring growth, inflation, public debt and unemployment. But not all of them deserve equal attention in each project. Subproject 2 has focused on EU initiatives that have been most important for employment and public debt statistics. The World Bank and UN have been the anchor for subproject 3 as they have been pushing for harmonized statistics, especially GDP calculation. Also in these choices, our subprojects have taken a pragmatic approach.

Where did we get our data?

We have been able to find a lot of data online: official reports, minutes of working group meetings, consecutive editions of statistics manuals. Depending on the case at hand, we have also been able to draw on existing scholarship that sheds light on selected episodes in indicator politics. Every now and then, battles over for example unemployment statistics even end up in the news, allowing us to reconstruct part of the story from there.

Talking to the people who devise the formulas

Interviews have remained our most important qualitative data source: talking to the people who actually devise the indicator formulas we have studied. It is only when we triangulated their historical knowledge and insight with the other data we had that we were able to reconstruct the political history of macroeconomic indicators and trace the processes through which they had evolved.

Going quantitative

Once we had distilled the core insights from our subprojects, we subjected them to quantitative tests. Beyond the publications that that has yielded, we have also created a new data base for international trade (lead-compiled by Lukas Linsi) that uses mirror statistics and thereby can help scholars to understand potential problems in their statistical inference better.