AGRICULTURAL ASSETS’ INFLUENCE ON BUILDING FARMERS’ RESILIENCE IN ROMANIA. FOOD SECURITY APPROACHES

An increasing number of scientific papers has been written on the topic of resilience. It explains the way individuals and regions face to shocks and stressors. It focuses on farmers’ resilience and food security. The main shocks related to food insecurity are weather variability, volatility, and agricultural assets. We assume that the level of assets plays a role in assessing the risk level of individuals’ exposure to shocks and stressors. The case of Romania is discussed, using statistical data concerning land, machineries and livestock, as main agricultural assets. The data have been analyzed using simple regression model. The results show medium influences of the agricultural assets on food supply. Significant influences have registered in macro region four: West and South-West, for land, machineries and swine. The results can be used in political frameworks and strategies and to widening the knowledge in the field of farmers’ resilience. © 2021. EA. All rights reserved


Introduction
Resilience is a modern concept which helps understanding the way individuals, households, and regions face to shocks and stressors, and an increasing number of academic papers and reports has been written on the topic. It is issued from system theory as "the ability of a system to bounce back or return to equilibrium following disturbance" (Holling, 1973). The concept then developed to a complex approach. As regards the food system resilience, it could be considered resilient in the situation in which it can maintain production of enough and nutritious food in the face of both chronic and acute social, economic and environmental perturbations.
The environment is continuously changing. Nowadays, the internal and external business environments are changing more rapidly than ever before (Stankevičiūtė, & Wereda, 2020). When speaking about dynamics and disturbance at the farm level, farmers have been always living and working in changeable environments, where socio-economic, ecological, and political risks are there. As other authors observed, (Berkes and Turner, 2006; Gunderson and Holling, 2002), major economic and social changes alter the farmer-environment relationship, and a new balance develops.
At the microeconomic level, the authors Milestad and Darnhofer (2003) developed a system of criteria for assessing farm resilience. It is based on farming systems literature, mentioned by Röling and Jiggins (1998), Pretty (1998Pretty ( ), (2002, and Ellis (2000). Agrofood systems have been analyzed from a variety of angles and with various purposes. One direction of research concerns the knowledge of farmers and their strategies to cope with and adapt to change (Scoones and Thompson, 1994;Sumberg and Okali, 1997;Ellis, 2000;Hoffmann et al., 2007;Burešova et al., 2020;Jokić, 2020). Milestad (et al. 2009) explored how farmers' experiments can contribute to developing socio-economic and ecological resilience on farms and in the regional food systems.
The resilience could be measures using different methods. One of them is the "Resilience Index Measurement and Analysis" (RIMA), developed by FAO (2016). It consists in assessing the following indicators comprised into four pillars: access to Basic Services, which shows the possibility of a household to meet their members' basic needs, as follows: sending children to school; accessing water supplies, electricity and sanitation facilities; assets, which allow households to produce and consume goods and services; social safety nets that assess the possibility of the household to have access to formal and informal assistance from public and private institutions, likewise from their relatives and friends; and adaptive capacity which consists in the possibility to adapt to new situations and develop new livelihood strategies. This paper aims to assess the influence of agricultural assets' on building farmers' resilience. Productive and non-productive assets are the key elements of a household, since they allow them to produce and consume goods. The indicators used are agricultural asset, land for cropping, livestock, house value etc.
The hypothesis tested in this piece of research argues that the level of assets plays a role in assessing the risk level of farm's exposure to shocks and stressors and cause the level of food supply of a household. This paper analysis the economic resilience in relation to food security. Following the introduction, the paper is divided into three main parts, followed by conclusions. Part 2 presents an overview of the regions of development in Romania. The data and methods of determining the resilience are presented in part 3. Part 4 presents the results of the regression models. Finally, part 5 draws the conclusions, and validates the hypotheses.

Overview of the development regions of Romania
Resilience explains how individuals and/or regions face to shocks and stressors. This paper investigates the regional resilience, thus an overview of the development regions in Romania is presented.
Regional policy is one of the key issue of the European Union. It is addressed to all the EU regions, both rural and urban, and it aims to boost economic growth and employment, in order to finally improve the quality of life through strategic financial investments (European Commission, 2020). Regional development focuses on creating and diversifying the economic activities, by stimulating investments meant to reduce the socio-economic differences between various regions (Apostolache, 2014).
A region is defined in EU's documents as "the next level after the state" or "a territory that forms a net unit from geographical point of view. It also means a similar assembly of territories having continuity, and population sharing certain common elements and willing to keep and develop their specificity for stimulating the cultural, social and economic progress" (European Commission).
From statistical point of view and data collection reasons, at the EU level there were created territorial units called NUTS (Nomenclature of Territorial Units for Statistics). They are organized on six territorial levels that depend on the number of inhabitants and the level of development. The European Union regional development policy envisages NUTS II level. At this level, the average size of the regions is 2.5 million people, and 13.000 sq. km (Apostolache, 2014).
According to Law no.315 (2004) on regional development, in Romania there are set up eight development regions, comprised into four main macro regions. The macro region one comprises North-West and Center Regions. The macro region two comprises the North East and South East Regions. The macro region three comprises South-Muntenia and Bucharest-Ilfov Regions. The macro region four comprises the South-West Oltenia and West Regions. They belong to NUTS II level and they are subject of the regional development policy, which is considered a key factor that facilitates the absorption of EU funds, through Rural Development National Program (Istudor, 2006).
The regions vary in size, assets and development. Considering the GDP as the main indicator showing the development of a region, in Table 1 and Figure 1  A general increasing trend of the values of GDP can be observed in Figure 1, for all regions, over the period under analysis. The GDP grew up to 60-70% in 2018 as compared to 2012, depending on the region. The highest growth registered in the region North West, considered to be the most dynamic region in Romania.

Materials and methods
It is assumed that the regions with high levels of GDP are able to ensure food security for its inhabitants. In this paper, the relationships between assets, particularly agricultural assets, and food security are analyzed.
The influence of agricultural assets on farmers' resilience can be explained by the relationship between the endogen variable, food security, and the exogenous variable, resilience capacity, with its shocks and stressors. Within this paper, the exogenous variable is agricultural assets, as pillar of resilience, and the endogen variable is food security, considered as an effect or outcome of individual's well-being.
The indicators suitable to agricultural assets are land for cropping, technical endowments and livestock. They are presented in Figure 2. The indicator suitable to food security is food supply rendered in daily calories consumed per person. It is presented in Figure 3. This was used in FAO report of 2014 (RM-TWG), and other scientific paper: Bullock (et al. 2017) reported that food quantity, expressed as the amount of production or food calories, is the most common metric of food security and thus resilience.

Results
For assessing the influence of agricultural assets on farmers' resilience, the relationship between food security, as dependent variable, and resilience capacity are analyzed.
The indicators are introduced into SPSS and analyzed using simple regression model, using 28 observations. The results of the model of regression are presented in Table 2, showing the influence of the agricultural assets, land, machinery, cattle and swine, on food supply. Agriculture, Year 68, No. 1, 2021, (pp. 101-111), Belgrade The agricultural assets have moderate influence on food supply, because the values of the coefficients of correlation are around 0.5. The land registered the highest influence of agricultural assets on food supply, since the value of the coefficient of correlation is 0.616, compared to machinery (0.588), cattle (0.504) and swine (0.412). The results of the regression model are retrieved with a standard error bellow 0.001 and a probability of 95%.

Economics of
The analysis goes deep into the macro regions of Romania, assuming that the influence of agricultural assets varies from one region to another, due to their differences in those regarding economic activity, agricultural land, technical endowment, livestock, people income and, generally, people wellbeing. As mentioned before, there are four macro regions in Romania: macro region 1, including North-West and Center, macro region 2, including North-East, South-East, macro region 3, including South-Muntenia, Bucharest-Ilfov, and macro region 4, including South-West Oltenia and West. The influence of the agricultural assets on food supply is presented in Table 3.
It can be noticed that significant results are registered for macro region 4, West and South-West Oltenia, where land use and machinery influence food supply, since the values of the coefficients of correlation between variables are above 0.5. They show a medium correlation between variables. The relations are negative, as the values of the coefficients of the regression function show. The results are retrieved with standard errors bellow 0.005, and a probability of 95%. In all the other regions, the results of the regression model are significant only for livestock, namely for cattle. In macro region 1, the cattle influence the food supply with a moderate intensity of 64%. The food supply modifies by 0.803 kcal as a result one-unit change in the number of cattle. In macro region 2, the cattle influence the food supply with a low intensity of 18%. The food supply modifies by 0.425 kcal as a result one-unit change in the number of cattle. In macro region 3, the cattle influence the food supply with a moderate intensity of 48%. The food supply modifies by 0.698 kcal as a result one-unit change in the number of cattle.
For land and machinery, although they are significant agricultural assets in farms activities, the results are not statistically significant. This could be considered a limit of the research, needing a detailed analysis, using different econometric methods and models.

Conclusions
The results of the research validate the hypothesis, assumed at the beginning of the article, that the level of assets plays a role in assessing the risk level of farmer's exposure to shocks and stressors and causes the level of individuals' and farmers' food supply. The results of the regression models show medium influences of the agricultural assets on food supply and regional disparities concerning the relationships of the agricultural assets on farmers' resilience. Thus, significant influences have registered in macro region 4, West and South-West, for land, machineries and swine. Less significant influences have registered in all the other macro regions, where only cattle influence, with a lower intensity, the food supply.