Labrousse is a prominent figure of the French ‘Ecoles des Annales’. He is particularly recognized for his works about the long run movement in agricultural prices. His Esquisse du mouvement des prix et des revenus en France au XVIIIe siècle (1933) argues for the existence of an exceptional increase in grain prices during 18th century in France but also more largely at the international level (the rise starting circa 1734 in France until 1817). The influence of the Physiocratic thought can be detected in his book La crise de l'économie française à la fin de l'Ancien Régime et au début de la Révolution (1944), in which Labrousse argues for the existence of an abnormal “inter-cycle” for the years 1778-91. Interestingly, Labrousse develops an economic explanation for the French Revolution based on grain prices.
Because as a historian he shifts the attention towards quantitative approach to the French Ancien Régime, because of his strong concern for the construction of data to obtain long run series, and last because his quantitative approach is rooted in a theoretical framework, Labrousse might be considered as a forerunner of cliometrics. The purpose of the paper is to assess to which extent such a claim is well founded.
First, we present the figure of Labrousse and his methodology regarding data (his construction of long run series) and regarding statistics (use of mobile averages) together with investigations regarding the long run movement in agricultural prices. Second, by using contemporary data analysis, we propose to test different hypotheses raised by our reading of Labrousse (1933, 1944). Last, we reassess the arguments put forward by Labrousse by using the empirical methods that were used at his time. Instead of his mobile averages, we reconsider Labrousse’s own data set with the linear or polynomial regression to extract the long-term tendency. And instead of a descriptive analysis of the deviation from the trend, we use the ‘periodogram’ method (the forerunner of spectral analysis) to study the cyclical component. By using statistical methods that could have been at his disposal, we show that Labrousse would have come closer to our contemporary results.