Academic journal article Review of European Studies

Economic Analysis of the Impact of Changing Production Conditions on Wheat Productivity Level

Academic journal article Review of European Studies

Economic Analysis of the Impact of Changing Production Conditions on Wheat Productivity Level

Article excerpt

1. Introduction

The mass production of wheat in Kazakhstan, when it was still part of the USSR, began in 1954 along with the launching of a plowing campaign of virgin and fallow lands. Within six years of the campaign (1954-1960), 25.5 million hectares of harvested area, or 61% of all plowed virgin and fallow lands across the former USSR was brought into operation (Lioubimtseva & Henebry, 2012).

The historical maximum of total wheat yields was observed in 1956 at 19.2 million tons. By 1999 the wheat area declined by more than half to almost 9 million ha. Besides other factors related to the state of the economy and agriculture, the sharp decline was caused by weather conditions (Tarrant, 1984) and use of specific wheat production technologies (Longmire & Moldashev, 1999). However, beginning in 2000, the wheat areas began to steadily increase and reached 13.1 million ha in 2012. Thus, the goal of the paper is to examine the impact of changing production conditions (specifically weather conditions and production practices) on wheat productivity level.

Similar studies and calculation methods of the impact of production conditions on wheat productivity level were carried out in the following works (Nagy & Sanders, 1990; Morgounov et al., 2005). Different studies have assessed impacts of climate change on wheat productivity. Knight et al. (1978) analyzed the potential for wheat production in various regions of Alaska on the basis of air temperature. Ashfaq et al. (2011) studied that the climate change is the major determinant of wheat productivity at each stage of wheat growth. The majority of the existing methods are dedicated to labour productivity calculation as such and to its dynamics. At present the following researchers are studying the impact of production practices on labour productivity in Kazakhstan and throughout the Central Asian states (Shegebaev, 1997; Baydildina et al., 2000; Meng, 2000; Morgounov et al., 2007). Peer-reviewed journals have a small number of publications that touch upon the research question one way or the other; it is necessary to point out first of all the following works (Griffith et al., 1995; De Beurs & Henebry, 2004).

2. Method

2.1 The Problem Features

To carry out our research on the measurement of the impact of production factors, including wheat growth technologies, the agricultural enterprise "Rodina" LLP was selected as the most appropriate site since it has a relatively more reliable and fuller database. The significant feature of the research problem is also its main difficulty. This is virtual impossibility of performing an experiment, whose primary aim is to compare and assess the efficiency of different agricultural technologies, under current socio-economic conditions. Furthermore, it is difficult to find enterprises with comparable conditions, that is, an enterprise where, for example, only an intensive technology is used or simplified, or a resource-saving technology is used. Therefore, the only possible way to solve this problem is to conduct a comparative analysis within the frames of an individual enterprise, with reference to retrospective historical data covering a considerable period of time, including the 1960s-70s (the time when conservation tillage technology was used), the 1980s (intensive technology), the 1990s-the beginning of the 2000s (simplified technology), and the early 2000s and up to the present (resource-saving technology). The crucial factors which affect wheat productivity level are considered to be weather hydrothermal production conditions. The calculation of the change in wheat productivity level given the use of a new technology is based on an econometric model.

2.2 Evaluation and Concretization of Factors to Be Involved in the Model

The selection of weather conditions periods to be involved in the model: Five precipitation periods were used for comparison in this model: Octobe-April; May-July; October-July; May-August; October-August. …

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