CC BY
2DOI: 10.29141/2658-5081-2021-22-3-9 JEL classification: J21, J43, J60
Ivan A. Borisov Ural State University of Economics, Ekaterinburg, Russia
Agricultural personnel and rural labour: How is their reproduction related?
Abstract. Labour reproduction and improvement of its efficiency are the major determinants contributing to economic resilience of rural areas. The article aims to establish the relationship between the reproduction of agricultural personnel and rural labour force in Russia. Methodologically, the research relies on agricultural economics and theoretical propositions of labour reproduction. The author clarifies the concepts "agricultural personnel reproduction" and "rural labour reproduction", and reveals differences in parameters and mechanisms of these processes. The methods of comparative, correlation and multiple regression analysis help estimate the factors in the corresponding reproduction based on the data obtained from Unified Interdepartmental Statistical Information System (UISIS) of Russia. The research confirms the hypothesis on the interdependence between the reproduction of labour in rural areas and agricultural personnel. The analysis points to a significant correlation between migration inflow of rural population and characteristics of agricultural sector in an area, as well as to the dependence of the agricultural enterprises demand for labour on the characteristics of an area where potential employees live. The findings prove that the reproduction of rural labour force is an important condition for sustainable reproduction of agricultural personnel. The value of the research results lies in economic mathematical justification of the measures to increase the efficiency of reproduction processes. Further studies in this field can hold the analysis of agricultural personnel reproduction based on municipal statistics.
Keywords: spatial development; reproduction; labour; rural population outflow; agriculture; rural areas.
For citation: Borisov I. A. (2021). Agricultural personnel and rural labour: How is their reproduction related? Journal of New Economy, vol. 22, no. 3, pp. 161-183. DOI: 10.29141/2658-50812021-22-3-9 Received June 30, 2021.
Introduction
Sustainable reproduction of agriculture is an important factor in ensuring the food
security of the Russian Federation. Addressing this issue is becoming increasingly relevant due to the growing demand for food products reflected in a sharp rise in prices for basic food items.
The most important asset of agricultural production is the rural labour. Considerable attention is paid to the problems of its reproduction in the programme documents of the Russian Federation: the Strategy for Sustainable Development of Rural Areas for the Period until 20301, the State program "Integrated Development of Rural Areas for the Period until 2025"2 and the Strategy for the Development of the Agro-Industrial and Fisheries Complexes of the Russian Federation for the Period until 20303.
Concurrently, it has not yet been possible to overcome the tendency towards a decrease in the rural population in most regions of Russia and a sustained shortage of personnel in many rural areas.
The multifactorial nature and interdisciplinarity of the problem of labour reproduction also determines its theoretical significance. A considerable number of scientific works are devoted to this problem in relation to rural areas and agriculture. At the same time, there is a confusion between the concepts "reproduction of rural labour" and "reproduction of agricultural personnel", which leads to an incorrect focus of the proposed measures and mechanisms for influencing the factors of labour supply and demand, and, consequently, to ineffective spending of budget funds.
The scientific literature lacks studies that distinguish between these concepts. The purpose of the research is to ascertain the relationship between the reproduction of rural labour and agricultural personnel.
In accordance with the purpose, the following objectives were set:
• to clarify the concepts "reproduction of rural labour" and "reproduction of agricultural personnel", and identify the characteristics and conditions of the corresponding reproduction;
• to analyse the dynamics of key indicators of reproduction of labour and personnel, determine the factors affecting these indicators and assess their interregional differences;
• to perform an empirical assessment of the impact of the identified factors on reproduction rates by the method of multiple regression analysis using the Unified Interdepartmental Statistical Information System (UISIS) database for the constituent entities of the Russian Federation.
1 On the approval of the Strategy for sustainable development of rural areas for the period until 2030: Order of the Government of the Russian Federation February 2, 2015 no. 151-p. https://docs.cntd.ru/document/420251273. (in Russ.)
2 On the approval of the State program of the Russian Federation "Integrated development of rural areas" and on amendments to some acts of the Government of the Russian Federation: Resolution of the Government of the Russian Federation of May 31, 2019 no. 696. http://government.ru/docs/36905/. (in Russ.)
3 On the approval of the Strategy for the development of the agro-industrial and fishery complexes of the Russian Federation for the period until 2030: Order of the Government of the Russian Federation of April 12, 2020 no. 993-p. https://docs.cntd.ru/document/564654448. (in Russ.)
Theoretical approaches to the analysis of the reproduction of agricultural personnel
Research of the processes of labour reproduction within the framework of the agricultural economics is developing in three main directions [Sharapova, Borisov, Sharapova, 2019].
The first direction involves the analysis of various aspects of the formation of human capital in rural areas in accordance with the theory of human capital, formulated by Becker [1993].
The greatest contribution to the development of research methodology in this area was made by the works of Griliches [1964], Huffman [1977], Fan [1975], Wozniak [1984], Lin [1991], Orazem and Mattila [1991], Perloff [1991], Huffman and Mercier [1991], Foster and Rosenzweig [1996], Yang [1997].
Among the modern studies on this issue, the works of Zhang, Yu and Chen [2011], Palkina [2014], Gorbunova [2018], Medvedeva [2020], Ermolenko [2020], Golovina, Mikolaichik, Smirnova [2020], Voronin, Chupina, Voronina [2020] and others deserve to be mentioned.
Within the framework of the second research direction, migration processes in rural areas are analysed, primarily the processes of rural population outflow. Methodologically, this direction is based on the theories of labour migration, originating in the works of Ranis and Fei [1961], Todaro [1969], Stark and Bloom [1985], etc.
The most significant surveys are the works of Schuh [1962], Maddox [1960], Maldonado [1976], Taylor [1987], Stark and Taylor [1991], etc.
The investigation of the problem of the rural labour outflow was continued by Ser-gienko and Ivanova [2016], Kletskova [2018], Kalachikova and Budilov [2018], Imbert and Papp [2020], Yurkova, Glukhov, Kryuchkova [2020], etc.
The third research area involves the survey of the demand for labour in agriculture, including the issues of establishing the optimal system of remuneration. Its methodological foundations are the theory of contracts and effective wages, the works of Newbery and Stiglitz [1982], Bardhan [1983], Schaffner [1995], Newman and Jarvis [2000].
Relevant studies of wages in agricultural enterprises include the works of Dulzon [2018], Almeida and Bravo-Ureta [2019], Kuznetsova and Shelkovnikov [2019], Kiry-anova [2020], Starkova [2020], etc.
Analysis of publications on the reproduction of agricultural personnel shows that the concept under study is often confused with the concept of reproduction of rural labour due to the location of agricultural production mainly in rural areas.
Nevertheless, these concepts cannot be considered identical. As such, agricultural production can be concentrated around small urban settlements, since the principles of settlement are not directly dependent on industry specifics. The criteria for identifying the rural area are the density of the population and the proportion of the population living in cities. However, belonging to a rural settlement in itself does not imply
a relationship to agriculture: its inhabitants can be employed in forestry and mining, provide tourist services, etc. Moreover, when considering the mechanisms of reproduction of the labour in a territory, differences in the factors determining these mechanisms are found.
Let us proceed to the analysis of the relationship between the concepts "agricultural personnel" and "rural labour".
In the most general sense, personnel is understood as the main (standard) composition of employees of enterprises, institutions, organisations of a particular type of ac-tivity1. Agricultural personnel is a permanent composition of employees of enterprises who, due to the types of economic activities they carry out, are classified as agricultural producers. Of particular importance are qualified personnel, that is, employees whose job duties require primary, secondary or higher professional (special) education or other special training, and in some cases, practical experience in the relevant profession [An-tonova, 2012].
The generic concept in relation to personnel is the concept of labour, which is understood as a part of the working-age population with physical development and intellectual (mental) abilities necessary for labour activity2.
The nature of the transformation of labour into the personnel of enterprises is largely distinguished by the nature of the course of individual phases of the reproduction process. At the stage of this transformation, the qualitative characteristics of the human capital acquire special significance, depending on the specifics of production relations, the marketability of human capital is formed. In fact, only if the interests of the participants of the local labour market coincide, labour is transformed into agricultural personnel. These circumstances allow clarifying the term "reproduction" in relation to agricultural personnel.
Rural labour reproduction can be defined as a continuously repeating process of recreating these resources. Concurrently, their quality characteristics and the nature of their use do not matter.
The reproduction of agricultural personnel presupposes a continuously repeating process of recreating the human resources of agricultural enterprises based on the needs of agricultural producers in the qualifications of personnel. An essential feature of this reproduction is taking into account not only quantitative, but also qualitative, including changing, characteristics of workers.
In this regard, the concept of sustainable reproduction of agricultural personnel acquires special significance. If sustainable reproduction of rural labour force is understood as their recreation in constant or increasing quantities (i.e. in fact, we are talking about a typical definition of simple and extended reproduction), then sustainable reproduction of agricultural personnel means the recreation of the personnel of
1 Personnel. Great Soviet Encyclopedia. https//dic.academic.ru/dic.nsf/bse/92075/Personnel. (in Russ)
2 Labour. htpps://ru.wikipedia.org/wiki/TpygoBbie_pecypcbi. (in Russ.)
agricultural enterprises in amounts corresponding to quantitative the needs of agricultural producers and meeting or exceeding their quality needs. Thus, we can talk about an expanded reproduction of agricultural personnel even in the circumstances of a reduction in the number of personnel in agricultural enterprises, if such a reduction is in the interests of employers. The results of the comparison of the considered concepts are presented in Table 1.
Table 1. Comparison of the concepts "agricultural personnel reproduction"
and "rural labour reproduction"
Subject of comparison Reproduction
of rural labour of agricultural personnel
Defining characteristic Ability to work Employment in agriculture
Characteristics — Educational level, health status, general and special work experience, qualifications, individual characteristics, social status, etc.
Availability and use indicators • Number • Employment level • Unemployment rate • Level of economic activity • Indicators of population movement • Number • Indicators of personnel movement • Remuneration of labour • Non-monetary remuneration • Labour productivity • Education
The conditions of restricted reproduction Reduction of the number of workers Lack of labour, decrease in the profitability of personnel, the growing discrepancy between the qualifications of workers and the needs of enterprises
Conditions for simple reproduction Regular headcount Change in headcount in accordance with the strategy of the enterprise, constant profitability of personnel, compliance of the qualifications of workers with the needs of enterprises
Conditions for expanded reproduction Headcount growth Change in headcount in accordance with the enterprise strategy, growth of personnel profitability, outstripping the growth of employee qualifications
The differences between the reproduction of rural labour and the reproduction of personnel in agriculture are manifested not only in the difference in the
characteristics of these processes. Deeper inconsistencies are observed at the level of the reproduction mechanism and lie in the difference between the key subjects of reproduction and the factors affecting it.
The key subject of the reproduction of rural labour is the household. Accordingly, decisions related to reproduction, such as the birth of children, investment in education and change of residence, are influenced primarily by the characteristics of the territory on which the quality of life depends. These characteristics include indicators of the social and educational infrastructure of the territory, as well as indicators of the labour market - levels of unemployment, wages, etc.
The reproduction of agricultural personnel presupposes the active participation of agricultural enterprises as employers: their decisions are influenced by indicators of productivity, production efficiency, equipment and its condition, and the financial situation of enterprises.
The multifactorial nature of reproduction processes implies the presence of a cross-effect of these features. Factors that shape the demand for labour of agricultural enterprises can affect the reproduction of the labour of the territory, but their effect will be indirect and is realised through the likelihood of successful employment in agriculture. The state of the labour of enterprises may depend on the factors of the territory, which indirectly determines the competitiveness of the employer.
Differences in the mechanisms of the influence of factors on different aspects of reproduction allow identifying the main problem areas of the personnel reproduction system and discerning vectors for increasing its efficiency.
So, if the hypothesis is confirmed that the performance indicators of agricultural enterprises significantly affect the indicators of reproduction of labour of the territory, it can be argued that an important problem of this reproduction is the demand for labour on the part of agricultural producers. In this case, agricultural enterprises can influence the territorial reproduction of personnel by changing the personnel policy. Refutation of this hypothesis will mean that the reproduction of labour in the territory is an exogenous factor for agricultural producers.
A similar assumption transpires with regard to the personnel of agricultural enterprises. If their reproduction is influenced by the characteristics of the territory, there is a dependence of agricultural enterprises on the reproduction of the labour in the territory and the need to develop the infrastructure of rural territories in the context of agricultural development. But if this assumption is not confirmed, we can talk about the autonomy of agricultural enterprises and their relative freedom in attracting labour force.
The hypotheses put forward formed the following work methodology:
1) select indicators of the system of rural labour reproduction, including both endogenous parameters and potentially influencing factors;
2) identify the parameters of the system of agricultural personnel reproduction and the factors of a sectoral nature that potentially affect it;
3) assess the regional differentiation of the indicators under consideration, which is a prerequisite for the suitability of indicators for assessing the impact;
4) make an econometric assessment of the influence of these factors both on the parameters of reproduction of labour of the territory, and on the parameters of reproduction of agricultural personnel by the method of multiple regression analysis;
5) give a meaningful interpretation of the results obtained, taking into account the hypotheses put forward;
6) discern the directions for the development of measures to improve the efficiency of the considered reproduction systems.
Indicators of agricultural personnel reproduction in the Russian Federation
When analysing the dynamics of indicators of reproduction of rural labour and agricultural personnel, it is advisable to consider first the endogenous indicators, and then the factors that potentially have a direct impact on them.
As an endogenous indicator of the reproduction of these resources, the indicator of the relative migration growth of the rural population was chosen (Table 2), since it is mostly of an economic nature, in contrast to the natural movement of the population, largely determined by non-economic reasons.
Table 2. Migration growth rate of the rural population in the Russian Federation in 2017-2019, %
Migration growth rate 2017 2018 2019
Within Russia, including: -0.26 -0.27 -0.17
intraregional migration -0.24 -0.27 -0.22
interregional migration -0.02 0.00 0.06
international migration, including: 0.13 0.08 0.19
with CIS countries 0.13 0.08 0.19
with other foreign countries 0.01 0.00 0.01
Total -0.13 -0.19 0.03
Source: own illustration based on Rosstat. (2021). The size and migration of the population of the Russian Federation. https://rosstat.gov.ru/compendium/document/13283.
The analysis of migration growth showed that for all rural areas, except for the territories of the Southern, Northwestern and Central Federal Districts, a stable outflow of the population is characteristic.
It is noteworthy that the migration growth is not interconnected with the share of the rural population in the region, i.e. the migration outflow is formed not by the predominance of the rural population, but by other factors. It should be noted that about 90 % of the migration turnover is internal migration. Since the main receiving territories for foreign migrants, as well as donor territories, are large cities, in the analysis of the reproduction of agricultural personnel, international migration can be ignored, since its influence is local in nature. Internal migration flows are divided between intraregional and interregional approximately in half, depending on the specifics of a particular territory.
Exogenous indicators that have a potential impact on the attractiveness of rural areas are presented in Table 3.
Table 3. Indicators determining factors of labour reproduction, 2017-2019
Indicator 2017 2018 2019
Crime rate, units 1, 402.19 1, 355.89 n.a.*
Housing affordability level, % n.a. n.a. 48.70
Share of the housing stock provided with all types of services and utilities in the total housing stock in the constituent entity of the Russian Federation, value per year, % 32.60 34.20 36.30
Ratio between the share of the housing stock of rural settlements provided with all types of services and utilities and the share of the corresponding housing stock of cities and urban-type settlements, % 41.21 43.24 45.32
Share of the population provided with drinking water that meets safety requirements in the total population, % 91.46 91.35 n.a.
Life expectancy of villagers at birth, years 71.38 71.67 72.21
Unemployment rate (according to the methodology of the International Labour Organisation), % 5.20 4.80 4.60
Cash income (average per capita), rubles 31,897 33,266 35,338
Average monthly nominal gross wages of employees for a full range of organisations 39,167 43,724 47,867
Note: n.a. means not available.
Source: own illustration based on UISIS. State statistics. Official statistical indicators. https://fedstat.ru.
The first group of indicators of the attractiveness of the territory is the indicators of social well-being, characterising the levels of crime and socially dangerous diseases (including the incidence of drug addiction and alcoholism).
Analysis of the dynamics of the crime rate indicates its decline. The most unfavorable in relation to illegal acts are the eastern territories of the Russian Federation, and the lowest values of this indicator are registered in the North Caucasian Federal District. As
revealed by the regression analysis, the crime rate does not correlate with the share of the rural population, which indicates that there are no significant differences in this area between cities and rural areas.
Data on the incidence of drug addiction is available for 2016 and demonstrate multidirectional dynamics. A notable increase in drug abuse is observed in the Far Eastern Federal District, which is also the leader in morbidity. The growth of the concerned indicator in the Southern Federal District is explained by the inclusion in its composition of the territories of the Crimean Federal District, which were characterized by an increased incidence. In other districts, the situation is more positive and tends to improve. The incidence of drug addiction is negatively correlated with the share of the rural population (correlation coefficient - 36.9 %).
Information on the incidence of alcoholism is also available for 2016 and shows a pattern similar to the incidence of drug addiction both in dynamics and in comparison by districts. The corresponding indicator also negatively correlates with the share of the rural population, but the level of its correlation is significantly lower - only 22.9 %.
In general, the results of the analysis allow us to conclude that rural areas are distinguished by greater social well-being than cities.
The next group of indicators - the provision of the population with housing and communal benefits - includes the affordability of housing; the share of the housing stock of rural settlements provided with all types of services and utilities; the ratio between the share of the housing stock of rural settlements provided with all types of services and utilities and the share of the corresponding housing stock of cities and urban-type settlements; share of dilapidated and disrepair housing stock; the ratio between the share of dilapidated and disrepair housing in urban and rural settlements, the provision of the population with drinking water.
The indicator of housing affordability is new in domestic statistics, and data on it has existed only since 2019.The leaders in terms of housing provision are the Yamalo-Nenets and Khanty-Mansiysk Autonomous Districts, where about 80 % of residents can buy housing, outsiders are the Republics of Crimea and Tyva, where less than 30 % of residents have such an opportunity. This indicator does not correlate with the share of the rural population, which indicates that there are no differences in housing affordability between the urban and rural population.
According to the data in Table 3, the level of the housing stock is steadily increasing in all rural settlements. The highest growth rates are observed in the Volga and Ural federal districts, however, in general, this level in villages is much lower than in cities. The best value in terms of the ratio is presented by the Southern Federal District, but it is also achieved due to the lower level of equipping with services and utilities of cities and even regarding this circumstance it is only 60 %. The worst indicators are noted in the Siberian and Far Eastern Districts, where the level of equipping with services and utilities is the lowest in both absolute and relative terms.
Data on the share of dilapidated and disrepair housing is limited to 2015 and indicates a tendency for its reduction in all districts, except for the Far East, which, moreover, ranks second in terms of disrepair housing rate. Analysis of the ratio of the share of dilapidated and disrepair housing stock in urban and rural settlements shows that this share in rural areas is 1.5-3.0 times higher, with the exception of the Southern Federal District, where, on the contrary, it is lower by a third.
The share of the population provided with drinking water is 90 % almost everywhere and continues to grow. A decrease is observed only in the North Caucasian and Southern Federal Districts. This indicator is not interrelated with the share of the rural population, which indicates the equal availability of drinking water for urban residents and villagers.
The next criterion for the attractiveness of a territory is life expectancy at birth. The corresponding data shows significant territorial differences. The maximum values are observed in the North Caucasian, Southern and Central Federal Districts; in general, life expectancy is increasing in all territories.
The final group of indicators is formed by indicators of the state of the labour market in the territory: the unemployment rate (according to the methodology of the International Labour Organisation), the average per capita monetary income of the population and the average monthly nominal wage per employee for the full range of organisations.
The dynamics of unemployment shows a decrease in all territories, especially in the Ural and Far Eastern Districts. The unemployment rate is positively associated with the share of the rural population (correlation coefficient - 56 %), i.e. in rural areas it is higher than in cities.
Cash incomes tend to decline in real terms and negatively correlate with the share of the rural population (the correlation coefficient is - 47 %), which indicates a lower level of these incomes in rural areas.
The average monthly gross wages, on the contrary, are growing in real terms and also negatively correlate with the share of the rural population (the correlation coefficient is -49.5 %) due to lower wages in rural areas.
The results of the analysis indicate that rural areas are much less attractive for living than urban areas, which leads to an increase in migration flows from rural areas.
Let us turn to the analysis of the reproduction of agricultural personnel.
The indicators characterizing the demand for labour of agricultural enterprises will act as dependent variables of reproduction: the need for workers to fill vacant jobs (section A of the OKVED1); the share of the number of resigned workers in the average number of employees; the share of the number of resigned workers due to the staff reductions in the average number of employees; the share of the number of resigned employees by agreement of the parties in the average number of employees; the share of the number of hired workers in the average number of employees; the number of employees trained, educated, of the total number of employees (section A of OKVED).
1 All-Russian Classification of Economic Activities
Data of demand for personnel is available for the period of 2018 and 2020. As an example, the structure of demand for 2018 will be considered (Table 4).
Table 4. The demand for workers in agriculture, forestry, hunting, fishing and fish farming, 2018
Personnel category Availability of demand
persons %
Executives 1,160.89 3.80
Specialists of the highest qualification level 3,374.01 11.05
Specialists of the average qualification level 1,314.11 4.30
Employees involved in the preparation and execution of documentation, accounting and maintenance 362 1.19
Workers in the service sector and trade, protection of citizens and property 1,261.68 4.13
Skilled workers in agriculture, forestry, fish farming and fisheries 6,432.03 21.06
Skilled workers in industry, construction, transport and related workers 3,978.92 13.03
Plant and machine operators, assemblers and drivers 6,696.64 21.93
Unskilled workers 5,956.2 19.51
Total specialists 30,536.49 100.00
Source: own illustration based on UISIS. State statistics. Official statistical indicators. https://fedstat.ru.
In the structure of demand for personnel in this area, the demand for skilled workers prevails. Even taking into account the specifics of the all-Russian classifier of types of occupation, the corresponding need is 34.09 against 17.25 % on average in the economy. The total need for workers in agriculture is 79.66 against 53.30 % on average in the economy. Concomitantly, the demand for specialists and managers is almost 2.5 times less - 20.34 against 46.70 % on average in the economy. Thus, the demand for skilled labour in agriculture is lower than the average for the economy, which is an important factor in educational migration from rural areas.
The indicators of the relocation of personnel are presented in Table 5.
The data on the turnover of staff on admission shows higher values for agriculture in comparison with other industries - the excess increased and amounted to 1 % in 2019.
The value of the turnover rate for staff resignation remains at a significantly higher level than the average for the economy - 3.2 % higher, according to data for 2019. All together, the dynamics of this value is unstable, accompanied by an increase in 2018. Layoffs due to staff reductions are encountered in agriculture much less frequently than on average in the economy, and along with other indicators of resignations, they demonstrate an unstable dynamics. At the same time, in general, this basis for dismissals is rather uncharacteristic for the Russian labour market and is only 0.95 % for
Table 5. Personnel turnover of agricultural enterprises (without auxiliary activities, provision of services) in 2017-2019, %
Indicator 2017 2018 2019
Share of the number of hired workers in the average number of employees 7.5 7.6 7.9
Share of the number of resigned workers in the average number of employees, of which: due to the reduction in the number of employees, of which: by agreement of the parties 11.7 0.04 0.44 12.4 0.10 0.54 11.7 n.a. n.a.
Source: own illustration based on UISIS. State statistics. Official statistical indicators. https://fedstat.ru.
agriculture and 2.33 % for the economy. In percentage terms, the share of parties who quit by agreement is also low, but lower than the average for the economy - 4.9 versus 7.7 %.
Wages were considered as an endogenous factor in the reproduction of agricultural personnel (Table 6).
Table 6. Average monthly nominal gross wages of agricultural employees, 2017-2019
Factor 2017 2018 2019
Wages of agricultural employees, rubles 23,301.0 25,480.96 28,370.54
Wages of agricultural employees, % of the average wages in the economy 59.49 58.28 59.27
Source: own illustration based on UISIS. State statistics. Official statistical indicators. https://fedstat.ru.
The territorial differentiation of wages in agriculture during the entire concerned period was about 15 %. Its average growth was 149.49 % with the highest one in the Far Eastern Federal District has, and the lowest in the Urals. As the analysed data shows, the value of the indicator is significantly lower than the average for the economy, in almost all territories. It amounts to only 58.28 %, which indicates the low competitiveness of jobs in this area. The worst ratio is observed in the Ural Federal District, the best - in the South and North Caucasian Federal Districts. Simultaneously, a positive trend in the growth of relative wages in agriculture can be noted in all territories, except for the Northwestern Federal District, where this trend turned out to be unstable.
Exogenous factors in the reproduction of agricultural personnel were agricultural products at actual prices; the profitability of these products; share of profitable organisations; the amount of state support within the framework of programs and measures for the development of agriculture; number of tractors per 1,000 hectares of arable land; equipment (tractors) renewal factor; energy capacity per 100 hectares of sown area (Table 7).
Table 7. Indicators determining exogenous factors of agricultural personnel reproduction in the Russian Federation, 2017-2019
Factor 2017 2018 2019
Agricultural production in actual prices (value of the indicator for the year, agricultural organisations (all agricultural enterprises)), billion rubles 2,818.5 3,022.2 3,348.4
Profitability (unprofitability) of goods, products, services sold, % 13.2 14.9 14.1
Share of profitable organisations, % 82.0 80.51 80.38
Amounts of state support within the framework of programs and measures for the development of agriculture, % of the value of manufactured products 6.12 5.64 n.a.
Power capacity, hp per 100 hectares of sown area 198 200 199
Number of tractors per 1,000 hectares of arable land, units 3.1 3.0 2.9
Equipment renewal factor, total amount of tractors (excluding tractors on which earthmoving, reclamation and other machines are mounted), units 3.6 3.4 3.4
Source: own illustration based on UISIS. State statistics. Official statistical indicators. https://fedstat.ru.
Data presented in Table 7 designates a rise in agricultural production. The only exception is the Southern Federal District. The highest growth rates were recorded in the Central and North Caucasian Federal Districts. The profitability of these products is significantly higher than the average for the economy, especially in crop production. The overall increase in the profitability of production has been noted since 2018, which indicates an upturn in the financial capabilities of agricultural enterprises. The share of profitable organisations is higher than the average for the economy. The volume of government support is considerable and comparable in size to the profitability of agricultural products (free access to the indicator has been suspended since 2019). The dynamics of the relative size of state support is multidirectional and depends on the territory: the smallest amounts of support are typical for the Southern Federal District, the largest for the Far East.
The provision of sown areas with energy capacities demonstrates stability. There are significant territorial dynamics. In the Northwestern Federal District, which is the leader in this indicator, its largest reduction is observed. In general, the volumes of energy capacities tend to values of about 200-220 liters per 100 hectares, which may state the convergence of agricultural production technologies.
The data on the provision of agriculture with tractors indicates its decline throughout the entire period under consideration. The most favorable situation has developed in the Northwestern Federal District, where the level of equipment provision is 1.5
times higher than the average Russian indicators, the most unfavorable is in the Siberian and Far Eastern Districts. Concurrently, the equipment renewal rate is at a consistently low level.
According to the results of the analysis, enterprises in the agricultural sector have sufficient financial capabilities to ensure a competitive level of wages, but at the same time they are crucially dependent on state support funds.
Regression analysis of the factors behind the reproduction of rural labour and agricultural personnel
In order to test the hypothesis about the ratio of the reproduction of rural labour and agricultural personnel, a regression analysis of the influence of the considered factors on the parameters of the reproduction system was carried out. As a sample of the analysis, statistics were used in the context of the constituent entities of the Federation according to the UISIS data for 2018, since in this year the information on the largest number of indicators is available in the public domain. The total sample size was 84 surveys. The hypothesis was tested by multiple least squares regression analysis.
The results of assessing the factors of the relative migration inflow of the rural population are presented in Table 8.
Table 8. Results of the regression evaluation of the factors behind the relative migration inflow of the rural population
Final sample size 79
Determination coefficient 0.461695
Adjusted coefficient of determination 0.424825
F-statistics 12.52219
Prob. (F-statistics) 0.000000
Variable Coefficient Standard error t- statistic Prob.
C -0.231481 0.043247 -5.352561 0.0000
Crime rate, units 1.19E-05 3.48E-06 3.427241 0.0010
Ratio of the share of dilapidated and disrepair housing in urban and rural settlements, 2015, % -0.001672 0.000607 -2.756007 0.0074
Life expectancy of villagers at birth, years 0.002868 0.000543 5.278731 0.0000
Average monthly nominal gross wages of people employed in agriculture, rubles 4.77E-07 1.34E-07 3.566318 0.0006
Power capacity, hp per 100 hectares of sown area -7.08E-06 2.62E-06 -2.704039 0.0085
According to the Table 8, the model has a fairly high explanatory power for spatial data. In general, the hypothesis about the dependence of the reproduction of rural labour on the state of agriculture is confirmed. Thus, migration gain is positively related to the level of wages in agriculture - correspondingly, it can be used by agricultural enterprises as a tool for managing reproduction. There is also a negative relationship with the power supply in agriculture, which is presumably explained by the substitution of labour for capital in agricultural production.
Among the characteristics of the territory, the ratio of the share of dilapidated and disrepair housing in urban and rural settlements has a significant negative impact on reproduction, which indicates the need to improve the condition of the housing stock in rural areas. There is also a positive impact on life expectancy, which reflects the desire of the population to choose places of residence with the best natural, climatic, ecological and other favorable conditions.
The evaluation of the dependence of the reproduction of agricultural personnel on the reproduction of the labour of the territory was carried out for all dependent variables. The results of this evaluation are presented in Table 9.
Table 9. Results of the regression evaluation of the factors behind the demand for workers for filling vacancies (overall total)
Final sample size 80
Determination coefficient 0.760728
Adjusted coefficient of determination 0.733768
F-statistics 28.21667
Prob. (F-statistics) 0.000000
Variable Coefficient Standard error t-statistic Prob.
C 0.038920 0.003664 10.62303 0.0000
Crime rate, units -1.65E-06 3.84E-07 -4.300112 0.0001
Housing affordability level, % -4.46E-05 8.18E-06 -5.457995 0.0000
Share of the population provided with drinking water that meets safety requirements in the total population, % -2.96E-05 1.13E-05 -2.617051 0.0108
Life expectancy of villagers at birth, years -0.000454 4.39E-05 -10.34146 0.0000
Cash income (average per capita), rubles 7.49E-08 2.66E-08 2.816284 0.0063
Average monthly nominal gross wages of employees for a full range of organisations, rubles -8.76E-08 2.24E-08 -3.902859 0.0002
Table 9 (concluded)
Variable Coefficient Standard error t-statistic Prob.
Average monthly nominal gross wages in agriculture, rubles 6.52E-08 2.18E08 2.987873 0.0039
Equipment renewal factor, total tractors (excluding tractors on which earthmoving, reclamation and other machines are mounted), units 0.000133 5.26E-05 2.535869 0.0134
The corresponding model has a very high explanatory power.
The hypothesis about the dependence of the reproduction of agricultural personnel on the characteristics of the territory was also confirmed. The demand of enterprises for personnel is higher for territories that are worse provided with housing, drinking water, and with a lower life expectancy. In addition, this need increases with less competitiveness of enterprises, which leads to its direct dependence on the size of average per capita income. Concomitantly, the demand for personnel forces enterprises to increase the level of wages. In fact, a negative dependence on the general level of wages and a positive dependence on wages in agriculture can be interpreted as a positive dependence on the ratio of these wages, which reflects the presence of price competition for labour (the regression with the ratio variable was tested, but showed a lower explanatory power at preservation of the same set of variables; therefore, it is omitted). The negative dependence on the crime rate is somewhat unexpected. The reason for this may be the existence of endogeneity and the delayed effect of agricultural development on the state of society in the territory.
Among the exogenous factors of agricultural reproduction, we note the positive influence of the rate of renewal of equipment, which is explained by an increase in the need for personnel when new equipment is introduced into production, including due to the emergence of a need for new competencies of workers.
The results of the regression evaluation for the share of the number of hired workers in the average number of employees are presented in Table 10.
The explanatory power of this model is rather low. Concomitantly, it can be seen that the dynamics of the actual admission of personnel depends, in fact, on intra-industry factors. Thus, the share of profitable organisations has a negative impact on recruitment, which can be explained by the greater stability of their staff. In addition, recruitment of personnel is positively associated with the competitiveness of wages in the territory, which also confirms the presence of price competition. The model tested the effect of the growth rates of agricultural production, but this variable turned out to be insignificant, therefore, the increase in production is not always accompanied by an increase in the number of employees. Comparison of the model
Table 10. Results of the regression evaluation of the factors behind the share of the number of hired workers in the average number of agricultural employees
Final sample size 85
Determination coefficient 0.168301
Adjusted coefficient of determination 0.148016
F-statistics 8.296707
Prob. (F-statistics) 0.000523
Variable Coefficient Standard error t-statistic Prob.
C 10.39313 1.927871 5.390985 0.0000
Ratio of the average monthly wages in agriculture to the average monthly nominal gross wages of employees across the full range of organisations, % 4.867419 2.100500 2.317267 0.0230
Share of profitable organisations, % -0.078715 0.020834 -3.778160 0.0003
results in relation to the need and the actual recruitment of personnel reveals that with a low attractiveness of the territory, there may be a problem of understaffing in agricultural enterprises, which is expressed in the lag in recruitment of personnel from the need.
The lack of dependence of the recruitment of personnel on the characteristics of the territory may indirectly indicate the orientation of agriculture to filling vacancies at the expense of the internal resources of the territory.
The results of the regression evaluation of the share of the number of resigned workers in the average number of employees are presented in Table 11.
This model is characterized by sufficient explanatory power for spatial data.
Basically, the dynamics of staff dismissal is shaped by intra-industry parameters. Thus, the level of resignations is lower for enterprises with a higher profitability of production and a higher level of state support. This pattern suggests that the initiators of the release, most likely, are employers. None of the factors of labour supply had a significant impact on the level of resignations. The positive relationship between the incidence of drug addiction and staff dismissal is probably explained by the problem of endogeneity and the presence of a delayed effect of the state of the industry on the social well-being of the territory.
Regression evaluation of the share of people dismissed due to staff reductions did not reveal a single significant factor, which is presumably connected with the relative specificity of this reason for dismissal.
Table 11. Results of the regression evaluation of the factors behind the share of the number of resigned workers in the average number of agricultural employees
Final sample size 85
Determination coefficient 0.327654
Adjusted coefficient of determination 0.302752
F-statistics 13.15787
Prob. (F-statistics) 0.000000
Variable Coefficient Standard error t-statistic Prob.
C 16.69041 2.224669 7.502425 0.0000
Incidence of drug addiction diagnosed for the first time in life per 100 thousand population, in 2016, people 0.290017 0.070322 4.124162 0.0001
Profitability (loss ratio) of goods, products, works, services sold, % -0.208856 0.064174 -3.254520 0.0017
Amounts of state support within the framework of programs and measures for the development of agriculture, % of the value of manufactured products per employee -0.017778 0.005523 -3.218722 0.0019
The results of the regression evaluation of factors affecting the share of parties dismissed by agreement are presented in Table 12.
The corresponding model demonstrates a low explanatory power. All together, it should be noted that the share of people dismissed on this basis depends significantly on the characteristics of the territory. Such layoffs are less common in regions with a larger share of the rural population, with high per capita incomes and lower average wages (for example, in regions with a low birth rate). Of the intra-industry parameters, only the profitability of products has a significant negative impact, since it reduces the likelihood of dismissal. The results obtained indicate that dismissal by agreement of the parties actually occurs under pressure from the employer and is common in regions with more difficult employment conditions in the industry in case of a job loss.
Analysis of the factors of reproduction of personnel in agricultural enterprises allows us to assert that the parameters of the actual movement of personnel are primarily dependent on the internal characteristics of the industry and have little to do with the parameters of the territory, with the exception of price competition. Simultaneously, the need for personnel is ascribed to the characteristics of the territory. In cases
Table 12. Results of the regression evaluation of the factors behind the proportion of agricultural personnel dismissed by agreement of the parties
Final sample size 84
Determination coefficient 0.142906
Adjusted coefficient of determination 0.099509
F-statistics 3.292988
Prob. (F-statistics) 0.015035
Variable Coefficient Standard error t-statistic Prob.
C 0.033688 0.010255 3.284943 0.0015
Share of rural population, % -0.031441 0.015636 -2.010884 0.0477
Cash income (average per capita), rubles 7.39E-07 3.63E-07 2.035302 0.0452
Average monthly nominal gross wages of employees for a full range of organisations, rubles -1.03E-06 3.31E-07 -3.125612 0.0025
Profitability (loss ratio) of goods, products, works, services sold, % -0.000346 0.000155 -2.224811 0.0289
where the territory of residence is notable for its low attractiveness, this dependence can serve as an indirect confirmation of the emergence of a shortage of personnel.
Conclusion
As we have seen, the study confirmed the hypothesis of the interdependence between the reproduction of rural labour and agricultural personnel. We can conclude that sustainable reproduction of rural labour is an important condition for the sustainability of reproduction of agricultural personnel.
The presence of the mutual influence of the scrutinised parameters allows establishing the directions for the development of measures to increase the efficiency of reproduction processes.
Thus, it is possible to recommend the implementation of programs that contribute to the development of the housing infrastructure of rural areas, including the provision of housing for specialists involved in agricultural enterprises. In addition, since wages are a crucial factor in the migration attractiveness of a territory (preventing population outflow), agricultural producers should change their attitude towards personnel and raise wages to a competitive level. The experience of advanced agricultural enterprises shows the potential effectiveness of the implementation of these recommendations.
In addition, the findings point to the need to take measures on increasing the life expectancy of the rural population. It is also noteworthy that government support measures for agricultural producers have a positive impact on staff retention.
In further research, we expect to use the data from municipalities to analyse the reproduction of agricultural personnel. The presented approach is limited by the fact that the official open access statistics are significantly poorer than the statistics for the regions. Furthermore, the detailing of the data will help to determine additional factors of the reproduction system due to a clearer identification of the territory of residence.
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Information about the author
Ivan A. Borisov, Sr. Lecturer of Economic Theory and Corporate Governance Dept., Ural State University of Economics, 62/45 8 Marta/ Narodnoy Voli St., Ekaterinburg, 620144, Russia Phone: +7 (343) 283-10-52, e-mail: borisia@usue.ru
© Borisov I. A., 2021
