Dynamics of Grain Yields in European Russia in the 19th — Early 20th Centuries: The Extent of Knowledge of the Issue

Abstract

This article deals with the problems of research in national science of the dynamics of grain yields in European Russia between the nineteenth and early twentieth centuries. For the purpose of the article, the author refers to crop statistics. Disputes about their reliability have been going on for about two hundred years, however, no irrefutable evidence of their unreliability has been presented. This is also true about the discussion of the early twenty-first century, where the source was criticised by B. N. Mironov and M. A. Davydov, and their opponents were S. A. Nefedov, A. V. Ostrovsky, and I. A. Kuznetsov. Interest in the dynamics of productivity emerged in the late nineteenth century. The focus of attention was the question of whether there was an increase in productivity in the period under review or not. At the turn of the twentieth century, A. F. Fortunatov and R. I. Preger maintained that productivity had increased, and I. Kh. Ozerov argued that it had not. In the 1920s, three views on the character of yield dynamics formed. V. G. Mikhailovsky and M. I. Semenov talked about a growth in yield combined with cyclical and random fluctuations. F. Cherevanin wrote that the yield in European Russia changed exclusively cyclically. V. M. Obukhov and A. L. Weinstein argued that grain yields grew, obscured by random fluctuations, in the absence of a cyclical component. It was the third point of view that prevailed with B. S. Yastremsky, A. S. Nifontov, A. V. Ostrovsky, V. G. Rastyannikov, and I. V. Deryugina following it. Only N. O. Voskresenskaya questioned the widespread increase in productivity. However, the previously used research methods (interval enlargement, correlation-regression analysis) are imperfect, and therefore the findings require rechecking using methods that are not in demand by national science for the analysis of crop statistics (hypothesis of the averages, Foster — Stewart method), which will help to better understand the nature grain yield dynamics in European Russia in the nineteenth and early twentieth centuries.

Keywords

• урожайность
• исторический источник
• тенденция
• цикличность
• случайная колеблемость
• укрупнение интервалов
• регрессионный анализ
• корреляционный анализ