Economic crises and statistics, from 1880 to 2010

Photo Alain Desrosières / Member of the Institut National de la Statistique et des Etudes Economiques (INSEE) / August 30th, 2010

Crises are times when statistics are used to portray the seriousness of the situation. They are also moments of heated debate where the state's role in regulating and steering the economy is questioned. Each major crisis is witness to the emergence of new ways of quantifying the social order, implying new models of action, variables, and systems of observation.

Economic history and policies from the 1880s to the present day offer at least three (if not four) examples of such configurations. The crisis of the 1880s led to the rise of large-scale labor and employment statistics. The crisis of 1929 gave rise to Keynesian macroeconomic and national accounting policies. The crisis of the 1970s, characterized by neoliberal microeconomic policies, brought about state reforms focusing in particular on performance indicators. Finally, the ecological and financial crisises of the early 21st century will perhaps be at the heart of radically new ways of conceptualizing and quantifying public action. An overview of how some relatively older crises were experienced and affected the use of public statistics could prove useful in understanding the potential consequences of the two recent crises.

1880-1930: labor statistics and analysis of economic cycles
In the 19th century, dominant liberal thought in industrialized nations called for minimal state intervention in market operations. An exception—but a huge one—was foreign trade. There were heated debates between those in favor of free trade and those in favor of protectionism. Besides old Regalian population statistics dating back to the 18th century, the only important statistics were those related to imports and exports.

The crisis of 1870-1880 changed everything. This crisis was analyzed with respect to its consequences on poverty and unemployment. Among all the markets that liberals considered capable of achieving spontaneous equilibrium, there was one that was very different from the rest: the labor market. In large, recently industrialized countries (countries of Great Britain, the U.S., Germany, France, Scandinavian countries), social reformers came up with legislation aimed at protecting workers. This period gave rise to labor law as well as nascent forms of the welfare state. In Germany, for instance, the “Bismarckian” system of social insurance was founded on contributions made by employers and employees. Public statistics underwent transformations in order to meet these new requirements. In France, a Labor Office was created in 1891, to which the General Statistics of France (Statistique générale de la France, SGF)—the predecessor of the French National Institute for Statistics and Economic Studies (Institut national de la statistique et des études économiques, INSEE)—was attached. This Office initiated massive surveys on employment and wages. The population census was completely transformed in 1896 by Lucien March in order to accommodate questions on professional activities and unemployment. Moreover, the concern for protecting workers’ wages against increases in the cost of consumer goods led to the creation of price indexes and the organization of the first-ever budget surveys of working-class families.

In connection to the emergence of these new policies was the evolution of statistical methodologies. Thus, the probabilistic survey method—conceived by Pierre-Simon Laplace in the 18th century but considered indadequate throughout the 19th century—made a comeback in the early 20th century. It was used in particular to conduct social surveys on income and poverty in support of social policies in Norway and then in Great Britain. Tools such as correlation and regression—conceptualized by Francis Galton and Karl Pearson around 1880-1890 to justify eugenist policies that have since been discredited—were used by economists such as Marcel Lenoir from 1913 onwards to develop models for cyclical crises.

The study of cycles and the concern for forecasting crises sparked a number of initiatives and tools in the 1920s. “Economic trend monitoring bureaus” were created in several countries. In the U.S., the “Harvard barometer” analyzed time lags between variations in certain macroeconomic indicators and tried to identify indicators (e.g., orders for packaging cartons) that could signal crisis situations. Unfortunately, this barometer failed to anticipate the October 1929 crash. This method gradually failed and gave way to business trend surveys (opinion polls) conducted with company heads. This is turn led to more sophisticated econometric models.

1930-1975: Keynesian policies and national accounting
The crisis of 1929, which lasted until the end of the 1930s, was perceived in a different light than the previous crisis. This time, blame was attributed to the global disequilibrium between market supply and demand, notably by John Maynard Keynes (though he did not go as far as to recommend the central management of economies, as was then being experimented in the Soviet Union). Balance or imbalance was represented by the “Keynesian equation”:

Production + import = Consumption + investment + government expenditure + export

This manner of formulating the problem assigned a key role to government spending (that had been previously missing from economists’ analyses), owing to Keyne’s “multiplier effect.” Several policies were implemented and succeeded in boosting demand, including for example the large-scale public works initiated by Roosevelt in the U.S. and the manufacture of arms initiated by the Nazis in Germany. In addition, a macro-econometric model aimed at steering public action was developed in Norway by Ragnar Frisch and by Jan Tinbergen in the Netherlands. These policies and models gave rise to radically novel descriptions of capital flows. This paved the way for national accounting, based on the concepts of national income, gross domestic product (GDP), household consumption, gross fixed capital formation (investment), savings and financing requirements.

In the U.S., the crisis hit the farming and employment sectors the hardest, as illustrated by a slump in sales and unemployment. The New Deal brought federal policies for regulating agricultural markets and extending support to the unemployed, particularly through public employment schemes. Agricultural and employment statistics thus underwent a complete transformation with the application of the random survey method. The unemployed were even recruited to carry out these surveys throughout the country, a technique that was subsequently adopted in post-war Europe.

In this context of profound change in the public arena, statistical surveys changed in content and meaning over a period of time. Thus, earlier surveys on working-class employees’ budgets evolved into “household budget surveys” from the 1950s onwards. They began to target all sections of society and aimed in particular at quantifying the “consumption” variable of the Keynesian equation. They were also used to determine the weighted coefficient of consumer goods used in the calculation of price indexes—which started to include the expenditure of the entire population and not just that of workers alone.

Furthermore, the welfare state, conceived in the aftermath of the late 19th century crisis, started to expand and took on a new meaning in the Keynesian context. In fact, protection provided by unemployment insurance, family allowances, pension schemes and even health insurance contributed towards compensating for decreases in income and consumption that had been mechanically brought about by economic crises. Thus, the crises of 1975, 1993 and 2001 had far less-damaging effects than those of 1929 or 2008-2009.

The period from 1950 to 1980 saw the development of large-scale social and economic survey systems influenced in part by the requirements of national accounting, created in France by Claude Gruson (Fourquet 1980). Yet another major event that occurred during this period was the fight against social inequalities regarding consumption and access to schooling, health services, and culture. These inequalities were perceived from the viewpoint of “socio-economic categories,” a social grouping widely used at the time by public statistics, academic research, and business survey institutes. Insofar as methodologies were concerned, until the 1980s, macro-econometrics (introduced in France by Edmond Malinvaud) was used in more or less Keynesian models before the advent of the “rational expectations theory.” This theory discredited Keynesian policies for a short while with the idea that players, in anticipation of the impact of macroeconomic public policies, implicitly behave in a way that nullifies the expected outcome of those policies.

1975-2010: New Public Management, ecological crisis, financial crisis
The long period of crisis that began in 1975 with the sudden hike in gas prices led to a complete reappraisal of the explanation and action models of the previous crisis.: discrediting of Keynesian policies and macro-econometric models, criticism of the state’s role, deregulation, privileging of supposedly efficient and self-regulating market mechanisms, financialization of the economy, decision making over short-term horizons at the expense of long-term forecasting, and planning methods. In addition, this period witnessed the creation of the European Economic and Monetary Union and the euro, which conferred great importance to the Union’s institutions, and in particular to the European Central Bank (ECB).

These developments not only left their mark on the output of public statistical institutions but also, more generally speaking, influenced the use of quantitative indicators—that may or may not have originated from the above institutions. The New Public Management, prevalent in Great Britain during the 1980s and 1990s inspired the use of quantitative indicators (Hood and Peters 2004; Lascoumes and Le Galès 2005). France also followed suit in 2006 with the enforcement of the Organic Law on Finance Acts (Loi organique relative aux lois de finances, LOLF), based on a number of performance indicators for public administration. The widespread use of benchmarking techniques was characteristic of the neoliberal conception of the economy and the role of the state, as had already been forecast by Michel Foucault in his 1979 lectures at the Collège de France. A good example of this technique is the Open Method of Coordination (OMC) used by the European Union for orienting social policies. It is based on the record of achievements of different states in terms of various quantitative indicators.

The ECB started calling for monthly and quarterly economic indicators (production, prices, employment, foreign trade) for increasingly short time periods. The objective was to orient an interest rate policy driven by an overriding fear of inflation. The publication of these indicators became a media event, leading to debate on policy efficiency and the potential manipulation of figures and their interpretations, especially regarding unemployment. This polarization on the topic of economic indicators took a sudden turn in the fall of 2008 when crisis hit—a crisis that was no more anticipated than that of 1929 and was even more surprising and upsetting.

A better explanation (upon hindsight) of the failure to anticipate the recent crisis lies in the complete lack of consideration of the transformations of financial instruments (e.g., derivative products, securitization). Previous analyses focused in fact on economic variables. On the topic of quantitative indicators, one of the consequences of financialization—which is hardly discussed but has serious implications—is the modification of European accounting standards. These aim more at valuing balance sheet assets at their “market value” (i.e., their possible resale value), or fair value, rather than their original cost. This manner of reporting appeals to investors, shareholders, and speculators but tends to make company balance sheets volatile and thus increases variations in financial statistics—which only worsens the crisis.

Stock market prices display instantaneous herd-like behavior. At least on a short-term basis, they are relatively disconnected from real economic trends. They fascinate financial investors but are not used in purely economic models. What is even more worthy of mention is the “interbank offered rate” (Libor), an indicator that is most apt for reflecting and even foreseeing the seriousness of financial crises (and which reached great heights at the end of 2007). Relatively unknown, it is seldom commented on by the media—contrary to the CAC 40 or the Dow Jones indexes, which are continuously displayed by TV news channels. The Libor increases when banks no longer trust each another and therefore refuse to lend money to one another. The sudden onslaught of financial phenomena is undoubtedly one of the most salient features of the current economic crisis—though far from the only one. Its occurrence is, in addition to an older and increasingly worrisome crisis, the ecological crisis and the distress caused by global warming. This threat has revived criticism of economic indicators originating from outdated national accounting.

Economic models and, more generally speaking, the evaluation of the standard of living and national growth make wide use of the central aggregate represented by GDP. Initially conceived to implement Keynesian policies, today it is seen, rightly or wrongly, as a monetary indicator of well-being, if not happiness. This has attracted major criticism as it reflects neither social inequalities nor does it express non-monetary activities (e.g., women’s work, voluntary work), or even degradation of nature caused by human activity, represented today by carbon dioxide (CO2) emissions. This kind of criticism, which dates back to the famous 1971 “Club de Rome Report,” is at the source of several suggestions for “new indicators of wealth.” One of the most well-known of which is the human development index (HDI), popularized by the Indian economist Amartya Sen. His formula, which is very rudimentary in nature, is an average of longevity, educational level, and standard of life. This indicator has met with great success despite its unsophisticated nature. In 2008, the French government entrusted a Commission on the Measurement of Economic Performance and Social Progress, co-chaired by Joseph Stiglitz and Sen, with the responsibility of coming up with proposals for assessing national performance in light of social and ecological factors, now considered crucial aspects. The Commission’s report, submitted in September 2009, suggests calculating a certain number of new indicators of well-being. In addition, researchers and activists who met in France for the “Forum for other indicators of wealth” (FAIR) are trying to initiate a major discussion on this issue in society at large. However, it is still rather difficult to clearly predict the effects of the financial crisis that erupted in 2008 insofar as statistical indicators are concerned. We can assume for instance that the carbon market as well as the effects of a potential carbon tax could account for indicators integrating the dimensions of both crises.

Thus, the concurrence of these two crises—the ecological crisis and the financial crisis—could be the source of an entirely new generation and use of statistical indicators. The importance of Intergovernmental Panel on Climate Change (IPCC) reports as well as indicators of CO2 emissions, changes in average global temperature, rising sea levels, and ecological footprint are but a few examples. As demonstrated by the events of 1880, 1930, 1970, and 2000, crises are represented by statistical indicators. But at the same time, they are also the source of major changes in the these indicators. It is difficult to tell how they will evolve in coming years, but the outcome will certainly depend on what global citizens and governments decide to privilege as a last resort.


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