Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/206552 
Authors: 
Year of Publication: 
2018
Series/Report no.: 
Studies on the Agricultural and Food Sector in Transition Economies No. 91
Publisher: 
Leibniz Institute of Agricultural Development in Transition Economies (IAMO), Halle (Saale)
Abstract: 
The aim of this study is to conduct a comprehensive analysis of Russian grain production, to determine country's production potential and its possibility to remain one of the major grain producers on the world market. On the one hand we estimate the technical efficiency during the period of transition to the market economy. By applying a novel approach to the estimation of production efficiency on a regional level, we assess the grain production potential and determine factors that influence productivity beyond the control of the farmers. On the other hand we conduct a detailed analysis of the climate change impact on grain production. We base our study on panel fixed-effect regressions of grain yields on a set of crop specific weather indicators. Furthermore, we use climate change projections for the medium and long terms to estimate the effect of global warming on grain productivity in different regions of the country. Empirical results of the production efficiency model are based on a balanced panel of Russian regions which were involved in grain production during the period 1995-2011. We rely on a production function that accounts for the effect of labour, land, capital, and variable inputs. In addition, we construct specific variables to control for factors that remain outside of the farmers' control, i.e. the level of human and infrastructure development and climate and soil conditions. In the climate change model we use yields of three the most popular grain types - winter wheat, spring wheat, and spring barley - on a regional level to determine their relation to indicators that account for climate conditions during the vegetation period, specific for each grain type. Specifically, we approximate the distribution of daily temperatures using a trigonometric sine curve to construct measures of growing and heat degree days. The data covers the period from 1955 to 2012. In order to estimate the effect of future climate change we rely on the latest available projections, provided by the Intergovernmental Panel on Climate Change (IPCC 2014) for the medium and long terms. [...]
Persistent Identifier of the first edition: 
ISBN: 
978-3-95992-058-2
Document Type: 
Research Report

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