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A Brief History of Indicators Part 1

Assessing Society: Historical Approaches and Recent Developments
Stephen Macekura

Last week Thriving Cities announced the release of the Indicator Explorer, an interactive online “data-discernment” tool to aid practitioners seeking to measure the health and well-being of their communities. I encouraged you to interact with this tool, but first to explore the history of indicators broadly.

We are awash in numbers. From big aggregate economic metrics such Gross Domestic Product (GDP), to more socially oriented indexes such as the Human Development Index (HDI), and all popular demographic statistics—life expectancy, to carbon footprints and “happiness” metrics—we measure almost all aspects of our lives. We even try to govern based on these numbers. Why and what metrics should we use? How are these numbers collected and calculated, and how do they shape the world? To begin answering these questions, a brief overview of indicators and the connections between statistics and governance is necessary.

An indicator is a measurable variable that provides specific information on the state or condition of something else. The modern origins of using indicators for national governance stretch back to seventeenth century England. A scientist named Sir William Petty set out to determine how much tax the Crown could levy to mobilize for the Second Anglo-Dutch War of the mid-1660s. The English government used his number to forecast future mobilization efforts, and, coupled with innovations of the previous century in double-entry accounting, began to make policy decisions with these nascent economic indicators. It was not until the late nineteenth century and early twentieth century that comprehensive, aggregate statistical depictions of an entire economy began to appear. Governments in the United States and Europe relied on statistics of productivity and investment to enact policies based on the effects that labor and consumption had on capital accumulation and market activity. Out of this data, U.S. and European economists and statisticians estimated the “national income” of their countries, depicting their economies as a system of goods and services flowing through their borders. This marked economists’ first description of “the national economy” as a cohesive entity that could be measured.

The biggest breakthrough in indicators came in the 1920s and 1930s as the field of economics became more quantitative. During the Great Depression, aggregate economic calculations became more important, as economists and statisticians in the United States, such as Simon Kuznets and Milton Gilbert, refined econometric experiments by estimating national income for the government. The first estimates for a new measure of national income—Gross National Product (GNP), the forerunner to GDP— appeared. Leading up to WWII, US and British war planners used GNP to determine how best to mobilize domestic resources and manage military procurement. After the war, GNP enabled Keynesian economists to make their targeted interventions and growth plans for balancing consumption, investment, and savings.

Soon, countries around the world started calculating their GNP number. New international institutions, chiefly the United Nations, grafted it onto colonies and “underdeveloped” countries, as well. The rising generation of nationalist postcolonial leaders helped make the 1940s and 1950s the highpoint of GNP, as they celebrated high GNP growth rates as a powerful symbol of modernity, and evidence for delivering on revolutionary promises.

It’s worth pausing to reflect on this revolution in statistics and policymaking. Most of these statistics were national, aggregate, and about productive capacity. They were meant to analyze national activity, particularly the capacity of a nation’s economy to produce. It’s important to note, also, that rising GNP per capita was originally meant to quantify progress toward some idealized state of industrial society where people worked little because of technological advancement, growth ensured old distributional conflicts wouldn’t reemerge, and rational experts carefully managed economic change. But, GNP growth often became a stand in for national vitality and well-being.

As GNP ascended, there also emerged a series of criticisms about the power of GNP and national economic indicators. Fundamentally, these debates were about what constituted the economy and what societies should value. Economists who visited the colonial (soon to be post-colonial) and developing world often pointed out that GNP and other national income metrics did not fit the subsistence (and often non-marketized) economies of much of the world. Kuznets and other economists harbored deep concerns about the reliance on GNP. “The welfare of a nation can scarcely be inferred from a measure of national income,” Kuznets warned in 1962, and he demanded that policymakers distinguish between “quantity” of GNP growth and the “quality” of economic change for the citizenry. Soon, reformers began to offer alternatives.

One particular group—international development experts—began focusing on inequality and wanted greater specificity than GNP allowed. Over the 1960s, even with high GNP growth rates across the third world, both poverty and unemployment remained equally high. In the late 1960s, the heterodox British economist Dudley Seers questioned GNP’s use in third world nations, claiming that a focus on GNP growth led national leaders to worship growth rates while failing to satisfy their populations’ basic needs. Seers and fellow economists such as Mahbub ul Haq and Amartya Sen undertook pioneering research into “social” indicators such as life expectancy and education levels and soon argued that these indicators should supplant GNP. Social indicator advocates in the 1960s gave rise to alternative aggregate metrics such as the Human Development Index (HDI)—an attempt to measure “social” and economic development.

A second group, environmentalists, assailed GNP for not including ecological damage. Ecological economics, beginning in earnest in the 1970s, aspired to rectify this problem. Inspired by GNP critics such as Kenneth Boulding and Herman Daly, ecological economists sought to incorporate environmental change into national statistical records, largely by putting a price on the economic value of the non-human world and including previous “externalities,” like pollution. Other reformers advocated for the use of new aggregate statistics that accounted for more holistic concepts such as “well-being.” The most notable criticism surrounding welfare and well-being became framed by notions of “happiness.” A famous offhand remark by the Kingdom of Bhutan’s leader in 1972 which suggested the country would strive to improve “gross national happiness” inspired a global effort to quantify national happiness levels through extensive surveying.

Although these measurement alternatives are still with us today, there are three trends and observations that stand out. For one, many of these stats seek to move beyond the state. The nation-state is no longer necessarily the object to be measured or developed. The Millennium Development Goals for instance, rely on individualistic or community levels, and only in this period have we seen a proliferation of city-specific indicators. Second, we should view frustrations over GNP and economic indicators, too, as a conflict over knowledge. On which type of knowledge and expertise should policymakers rely? How should non-quantifiable information factor into decision-making? GNP thrived, in part, because it reflected a schematic, reductive, positivistic thinking that cast itself as value-neutral and universal in mid-century economics and expert culture. Part of the challenge for indicator reformers today is how to leverage expertise without being paternalistic and closed off to many different viewpoints and values. Third, criticisms of GNP emerged because reformers believed the old goal of endless economic growth no longer seems so enticing. We now know that thinking of growth in terms of GNP does not, by itself, eliminate poverty, nor spread prosperity evenly.

Given this overview, what can we say about the role of such assessments in today’’s cities? What should those concerned with urban life— do with the mass proliferation of ways to measure the social world and our place in it? What are the potential benefits and downsides of these existing approaches? How do these measurements help us understand the dimensions of thriving? These are the question we’’ll take up in the next post.