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Article

A Difficult Pattern to Change in Romania, the Perspective of Socio-Economic Development

by
Tiberiu Iancu
1,
Ionuț Laurențiu Petre
2,
Valentina Constanta Tudor
3,*,
Marius Mihai Micu
3,
Ana Ursu
4,
Florina-Ruxandra Teodorescu
3 and
Eduard Alexandru Dumitru
4,*
1
Faculty of Management and Rural Tourism, Banat’s University of Agricultural Sciences and Veterinary Medicine “King Michael I of Romania” Timisoara, Calea Aradului, No. 119, 300645 Timisoara, Romania
2
Department of Agrifood and Environmental Economics, The Bucharest University of Economic Studies, 010374 Bucharest, Romania
3
Faculty of Management and Rural Development, University of Agronomic Sciences and Veterinary Medicine, 010961 Bucharest, Romania
4
The Agricultural Economics Office, Research Institute for Agriculture Economy and Rural Development, 010961 Bucharest, Romania
*
Authors to whom correspondence should be addressed.
Sustainability 2022, 14(4), 2350; https://doi.org/10.3390/su14042350
Submission received: 25 January 2022 / Revised: 14 February 2022 / Accepted: 15 February 2022 / Published: 18 February 2022
(This article belongs to the Collection Sustainable Economic Development: Challenges, Policies, and Reforms)
Browse Figures
Versions Notes

Abstract

:
The rural area is a basic component from a socio-economic point of view, being closely linked to the activities that take place in these areas. Normally, Romanian rural localities should show significant differences from one development region to another, being influenced by a number of factors (geographical positioning, the influence of agriculture in the economy, etc.). In this sense, data were collected from the town halls of the localities from Calarasi and Timis counties. The analyzed data were processed by the linear regression method, and the estimation of the evolution of the population was determined using the Vensim simulation program. The paper identifies a pattern in rural localities in Romania that hinders their development, reflected by various socio-economic indicators available in the analyzed localities. The main factor that can change this pattern in rural localities is the influence of local and national decision-makers, who can encourage investment in these areas either through the development of local and national infrastructure or through fiscal measures that encourage the development of quality non-agricultural activities that can generate financial resources and jobs at the local level. Moreover, it is not only the low number of non-agricultural activities that is causing the poor development of rural areas, but rather the low number of economic operators in general and the quality of these types of activities, which in most cases do not have the capacity to create new jobs.

1. Introduction

The concept of “rural” includes several dimensions that refer on the one hand to the predominant activity in rural areas—agriculture—and life in rural areas, including people engaged in agriculture or other related activities [1,2,3,4].
According to Bold and Buciuman (2003), “rural” can be defined as the totality of activities that take place in a space other than an urban one, with a relatively small number of inhabitants, who have multiple relationships with each other and where agriculture and forestry have an important role [5,6].
According to some authors who have researched this complex concept, over time the idea has emerged that “rural space” includes everything that is not urban. Among the multiple definitions assigned to the term of rural space, the most representative are [7,8,9]:
  • The rural area can be characterized by a relatively small number of inhabitants, with a small number of buildings, and where there are mainly natural landscapes, where nature blends perfectly with the activities that man undertakes. In the rural space, the activities mainly carried out by its inhabitants are agriculture, animal husbandry, forestry, or beekeeping.
  • The rural area can also be characterized as having a multitude of non-urban areas, which include fields and people carrying out activities associated with field work;
  • The rural area is the ideal environment in which agricultural activity can be developed and where, compared to urban areas, the concentration of people is low.
Taking into account the “artisanal” dimension of the rural space, we can say that the rural is not only related to agriculture, but also includes all the activities carried out by folk craftsmen or activities with a tourist profile. Whether it is wood carving, weaving, or making traditional sandals called opinci, all these activities are specific to the rural area and define the identity of the Romanian people [10,11,12,13].
Various authors consider that the modern rural area is the result of a complex process of continuity and discontinuity, where the new life models replace the traditional ones and the modernization of the villages and rural communities implies its transformation as a whole [14].
The term “rural area” is also widely used in politics and economics, but there is no accepted unitary definition. However, it can be stated that a more accurate definition of rural space consists of a “diverse and complicated economic structure that includes villages, small towns, forests, commercial activities that may include tourism, small companies, craft workshops, small and medium industry, landscapes, and cultural traditions. This indicates the high degree of complexity that such an area has [15].
In recent times, rural regions from Romania and beyond have seen significant population declines [16,17], with people often choosing to migrate to urban centers or other countries. The factors behind this phenomenon are particularly complex and interrelated [18,19]. Most research indicates that the two main aspects that lead to the successful development of a locality are its geographical location and local and regional resources [20,21,22,23]. Being located close to urban centers generates multiple advantages for neighboring localities, as they can find jobs in urban centers [24,25]. Mountain areas, with their impressive landscape potential, can also develop other related activities and tourism, but this cannot be achieved without a developed road infrastructure (Figure 1) [26,27].
With the depopulation of rural areas, not only is cultural heritage lost [28,29], but food security is also under threat, especially as most food resources are obtained in rural areas [30,31,32]. Even the United Nations proposed that food security should be addressed at international, national, and local levels (Figure 1) [33].
Various authors have stated that the main activity in rural areas is agriculture, whether developed farms or household activities that provide a daily livelihood for the population. With the widening gap in living standards between urban and rural areas, more and more people, especially young people, have chosen to migrate, leaving the ageing population behind [34,35]. This has led to a fall in the birth rate and an increase in the death rate. The low rate of EU funding attracted by local authorities is reflected in the poor infrastructure in a significant proportion of rural localities, which can also be attributed to low interest and lack of funds to finance investments [36,37,38].
The aging population can no longer carry out the usual activities of growing crops or raising livestock, and households are unkempt [39]. The legal heirs of these properties have also left their native places, and selling the farms is not an option as there is no market demand, thus increasing the degradation of these farms [40].
A locality with a high number of inhabitants also has a high number of economic agents to satisfy local needs, but this is also influenced by the standard of living, which in rural areas is much lower than in urban areas [41,42].
With an aging population and an acute shortage of jobs, a high number of people on social assistance is generated, who have no other source of income to ensure their daily living [25,26,43].
The study compares two development regions with different approaches as follows: The West region is located in Western Romania, on the border with Hungary and Serbia, with easier access to Western European countries, encouraging trade. Romania’s poorly developed road infrastructure also makes it difficult for other regions to access Europe, so this region has a significant advantage. The West region has a diversified economy, where agriculture is not a major driver of the economy. On the other hand, the South-Muntenia region is based on agricultural activities, being located in the Baragan Plain, where the fertile soils allow the cultivation of a variety of plant species over a large area. The relatively close location to the Black Sea allows the marketing of cereals and oil plants in the Black Sea basin.
The aim of the study is to demonstrate that, no matter how different the development regions in Romania may be in terms of geographical positioning, and focusing on localities in counties with a high value of agricultural production, the socio-economic development prospects are relatively similar and bleak. The paper also identifies a pattern in some rural localities that stands in the way of their development.

2. Theoretical Background

The rural area is characterized by diversity, including both physical and morphological aspects, biodiversity, and landscapes, but also social aspects, such as land use, traditions, and customs, while maintaining the priority of the development of these areas.
Looking at it from a different perspective, the rural area is considered an area of “disadvantages” characterized by low-income households, people with a poor level of education, and lack of basic infrastructure (water, gas, and sewerage). A harsh but real prospect is often the level of extreme poverty, which is usually passed down from one generation to the next [44].
There are three types of disadvantaged regions: mountainous areas, other disadvantaged rural areas (low-productivity land, low-income enterprises, low agricultural incomes, low density, sustained population exodus), and areas with specific disadvantages (unfavorable natural conditions) [45].
According to Steiner, the main disadvantages of rural areas include low density, special social and economic structures, dependence on agriculture, low incomes, and difficult accessibility [46].

The Evolution of Rural Development in Romania

Until 1990, the emphasis of the communist regime was on the development of industry, which contributed to the development of cities, to the detriment of rural areas. Due to this aspect, there is still a significant gap between the two areas. In addition, during that period, a large part of the population in rural areas worked partly from their residences, until the emergence of the collectivization process, profoundly transforming the Romanian village, especially by dispossessing them of owned agricultural land [47].
After this period, the rural environment entered a new stage, with the return of the population to the rural area, where the process of restitution of agricultural land occupied by the communist regime was quite difficult and impartial, with small and very small areas being returned to the population and agricultural practiced being one of subsistence. The restitution of these lands led to the emergence of small and medium-sized farms, but with low productivity due to the lack of machinery and equipment needed to work the land. This led to the practice of subsistence farming, based on the production of primary agricultural products in small quantities [47].
A negative characteristic of the Romanian rural area is the demographic decline, caused by the decrease in the rural population, determined by the aging population, but also due to the migration of the population to the areas with better-paid jobs. Small businesses, especially those that create jobs, cannot grow due to lack of funding (co-financing), but also due to poor infrastructure. There has been a change in rural areas in recent years, especially in terms of demographic change, core occupations, and moral value [47].
According to data published in 2019, only 11.3% of the rural population had access to sewerage services, and only 40% of households have constant access to drinking water. It should be mentioned that a part of the rural population of Romania has the possibility to connect to these sewerage services, but the costs related to construction and connectivity are much too high for them [47].
The road infrastructure has significant deficiencies, with only 15% of the road network in rural areas being modernized, with the rest as dirt or cobbled roads (in 2019). Gas supply is also low, due to high connection costs but also poor infrastructure, including in areas with a high population concentration [47].
Due to the poor condition of primary and secondary schools, in recent years their number has been reduced by a third, which has contributed to an overcrowding of functional schools, but also an increase in schooling costs of students in the environment, Determined by their transport to nearby functional educational units [47].
Rural space, at the European level, is precious natural space as a result of a long history, and whose survival and revitalization is a constant concern for modern society [48,49,50].
At the European level, the member states of the European Union use their own definition of the term “rural area.” In France, the rural area is the territory where agricultural production is predominant and the landscape elements are found in their natural state [51,52]. On the other hand, the Belgians chose to define rural space as a set of natural landscapes and cultivated areas. The Germans consider that the rural area represents all the areas that are positioned outside the areas that have a large number of inhabitants [53,54,55]. In the United States of America, two terms are widely used to differentiate between rural and urban: “rural farm” (rural agricultural) and “rural non-farm” (rural non-agricultural), and this can be explained by the existence of two rural areas, some mainly agricultural and others where non-agricultural activities predominate in rural areas [56].
In Russia, rural areas are considered to be ones where the main functions are agriculture, forestry, fishing, and industrial activities of primary processing of these branches [56,57,58].
In other countries (UK, USA, Brazil), the definition is given according to the main occupation of the majority of the active population.
The most important regulation on sustainable development was given by Agenda 21, adopted at the United Nations Conference on Environment and Development in Rio de Janeiro in 1992, attended by 178 countries and 120 leaders. The defined principles provided for measures to prepare people and authorities to produce and live differently than how they had before. Agenda 21 is the most important moment for the concept of sustainable development [33].
In its report entitled “Our Common Journey: A Transition towards Sustainability,” the Academy of Sciences of the United States of America tried to establish an order in terms of the definitions given so far of the concept of sustainable development. The authors of the US report believe that it is important to differentiate between the priorities to be supported by specific measures and the priorities to be developed. The scientists who contributed to this report found three important categories involved in sustainable rural development: nature, life support systems, and the human community. The first studies on sustainable development addressed, first of all, the economic aspects of the job-generating sectors. Subsequently, consumption and human health were taken into account. The authors of the American report believe that the approach to the concept of sustainable development has focused on the progress of society and the values and security of the welfare of countries, areas, and authorities at the national and local levels [58].
Sustainable development and rural areas are topics that have been analyzed and researched by scientists from countries such as Germany, Austria, and Poland. The need to preserve and develop the village has recently been studied due to the fact that people have become increasingly concerned with having a better, healthier life and the preservation of natural landscapes.
Moser et al. (2018) studied the extent to which the lives of people living in rural areas of Germany can be improved. In the paper entitled “Improving the quality of life through rural development programs in Germany (2007–2013). Evidence of the assessment,” the researchers from Germany analyzed the extent to which the rural development programs implemented in the 16 German Länder have fulfilled their purpose, that of enabling the sustainable development of the rural environment and improving the quality of life of the villagers. The results of the study showed that the improvement of the quality of life through the implemented development programs was achieved only in certain regions [59].
The LEADER axis, which is found in many rural development programs in the member states of the European Union, has been studied in terms of the effect felt by member states such as France, Germany, and Italy. In the paper entitled “LEADER as a European policy for rural development in a multilevel governance framework: a comparison of implementation in France, Germany and Italy,” Pollermann et al. (2020) analyzed the way in which the implementation of the LEADER axis in three different countries brought substantial changes to the rural area. The paper analyzed the similarities and differences between the three countries in terms of implementation mechanisms of the LEADER axis. The study was based on the analysis of documents and a series of interviews with stakeholders, and the institutional differences in the implementation of LEADER at the local level were analyzed in order to identify the best strategy for the development of the LEADER axis in the future [60].

3. Methodology

The focus of the study on the two development regions of Romania was based on the share of the rural population in the total population, and the extremes were selected. Thus, in the South-Muntenia region, in 2019, the share of the rural population in the total population was 60.3%, whereas the West region had the lowest rural population, with only 39.3% (except for the Bucharest-Ilfov region, whose socio-economic situation is extremely favorable in the context of its location in the immediate vicinity of the Romanian capital) (Figure 2).
Based on the situation described above, the counties with the highest share of agricultural production value in the region were selected, namely, Timis (West region) and Calarasi (South-Muntenia region), reflecting the influence of agriculture in local socio-economic development (Figure 2).
Hypotheses 1 (H1).
The high mortality rate due to the high number of elderly people contributes to the decline of the rural population.
Hypotheses 2 (H2).
The number of households in rural areas tends to decrease as a result of the decrease in the number of inhabitants.
Hypotheses 3 (H3).
The number of economic agents, which reflects the economic situation of the localities, influences the number of inhabitants.
Hypotheses 4 (H4).
Population influences the number of people on social assistance. The number of people on social assistance is influenced by the number of inhabitants.
In order to carry out this section, all the localities from the rural area (communes) existing in the two counties of Calarasi and Timis were identified. According to law 544/12.10.2001 regarding the free access to information of public interest, a request was sent by e-mail to all these local authorities in order to obtain information about them, classified in demographic/social, economic, and infrastructure indicators for the period 2015–2020 as follows [61]:
  • Number of inhabitants;
  • Number of households;
  • Number of newborns;
  • Number of deaths;
  • Number of persons receiving social assistance;
  • Number of economic agents, including those with an agricultural profile;
  • Number of tourist units (including agrotourism units).
Given the fact that the request to the local authorities was official and binding for them, the number of requests received was quite low (Table 1).
It should be mentioned that the centralization of the information was carried out 45 days after the last e-mail sent in order to provide the maximum term, provided by law, to respond to the request.
Because the large volume of data transmitted by the authorities does not make it possible to present them in this article, it was decided to present and analyze the following localities that responded to the request (Table 2):
  • Criterion 1—the locality with the highest number of inhabitants in 2020;
  • Criterion 2—the locality with the lowest number of inhabitants in 2020;
  • Criterion 3—the locality with the largest number of economic agents in 2020;
  • Criterion 4—the locality with the lowest number of economic agents in 2020.
The rural localities, which will be analyzed from a socio-economic point of view and were determined according to the criteria mentioned above, were Dragalina, Nicolae Balcescu, Soldanu, and Sarulesti for Calarași County. Regarding Timis County, the localities that were selected were Sanmihaiu, Valcani, Peciu Nou, and Fardea (Figure 3).
The socio-economic analysis of the localities also took into account aspects related to geographical location and local resources (Table 3).
The data centralized as a result of the responses received from local authorities were processed using the statistical program SPSS version 27, thus determining the average and annual rate, and linear regression was performed. In addition, the establishment of links between variables and the simulation of the population evolution was carried out using the Ven-sim PLE program, based on the following relationship (Figure 4):

4. Results and Discussion

4.1. Results of Socio-Economic Analysis of Rural Localities Determined in Calarasi County

4.1.1. Case Study 1. Dragalina Locality

Analyzing the data provided by local authorities in Dragalina, Calarasi county, the population decreased slightly in the period of 2015–2020, with 2.71% fewer inhabitants in 2020 compared to the number recorded in 2015. Despite the decrease in the population number, the number of households in the commune registered an evolution of 4.66%, and the annual growth rate was at a low level, at only 0.9% (Table 3).
The birth rate in Dragalina commune remained low compared to the mortality rate, where on average around 77 people lost their lives annually. The persons receiving social assistance in Dragalina commune decreased, registering a decrease of 47.37% registered in 2020 compared to the number of persons benefiting from such support in 2015. The annual average of the persons receiving social aid was 172 people, with a negative annual rate of 12% (Table 4).
In Dragalina commune, the number of medical units was constant, at four (Table 4).
An important indicator regarding the rural development of Dragalina commune in Calarasi county is represented by the number of economic agents registered in the local community. From 2015 to 2020, the number of economic agents increased by 98.1%, registering an annual rate of 14.7%. In 2020, there were 420 economic agents registered at the commune level, of which 197 were economic agents with an agricultural profile, representing 46.9% of the total economic agents. This distribution of economic agents present in Dragalina commune indicates that the economic activities were diverse and almost half of the economic agents carried out agricultural activities (Table 5).
In the period 2018–2020, the water supply for the population of Dragalina improved. Thus, in 2020 the water network covered 61.8 km out of a need of 80 km, with the existing network covering 77.3% of the need (Table 5).
On the other hand, in terms of the sewerage network, it remained at the same level throughout the analyzed period, covering 12% of the 80 km needed to fully cover the needs of the local community (Table 5).
We can say that of all the independent variables, the number of deaths had the highest impact on the dependent variable, with a beta value of 0.333, so the population was influenced by the number of deaths. However, we noted that the other variables, which showed negative values of the beta coefficient, showed us that when the population decreased, the number of households and economic agents increased (Table 6).
In addition, the beta coefficient (−0.575) regarding the independent variable “no. households” had a high impact on the dependent variable, so we can say that the population was influenced by the number of households. In this case study, it can be explained by the fact that the households owned by the elderly were divided by their children, who built their houses (households) near the parental home, being the place where they laid the foundations of a family (Table 6).
If the data, based on which the values were entered into the Vensim simulation program, remain constant, we can say that within 10 years the population of Dragalina will register a significant decrease, reaching a number of approximately 7800 inhabitants (Figure 5).

4.1.2. Case Study 2. Nicolae Balcescu Locality

Analyzing the data provided by the local authorities from Nicolae Balcescu commune, from Calarasi county, the population registered a slight decrease in the period 2015–2020, with 3.80% fewer inhabitants in 2020 compared to the number in 2015. Despite the decrease in the population, the number of households in the commune registered a slight evolution of 3.29%, and the annual growth rate was at a low level, at only 0.6% (Table 7).
The birth rate in Nicolae Balcescu commune remained low compared to the mortality rate, where on average, annually, around 32 people lost their lives. On average, 18 children were born annually in Nicolae Balcescu commune. The number of people benefiting from social assistance in Nicolae Balcescu commune decreased, registering a decrease of 73.17% in 2020 compared to the number of persons benefiting from such support in 2015. Annually, the average of persons benefiting from social assistance was 24 people, with a negative annual rate of 23.1%. The number of people receiving social assistance represented a percentage of 0.7% from the total number of inhabitants (Table 7).
In Nicolae Balcescu commune, the number of medical units was constant, with only 1 such medical unit found (Table 7).
An important indicator regarding the commune of Nicolae Balcescu, in Calarasi county, is represented by the number of economic agents registered at the commune level. From 2015 to 2020, the number of economic agents increased by 58.8%, registering an annual rate of 9.7%. In 2020, the commune registered 27 economic agents, out of which 14 economic agents had an agricultural profile, representing 51.85% of the total economic agents. This distribution of the economic agents present in the commune indicates that the economic activities carried out by the inhabitants were mainly agricultural (Table 8).
Comparing the number of inhabitants to the number of economic agents registered in Nicolae Balcescu commune, it was found that there was one economic agent per 58.1 inhabitants, a fairly high proportion, which reflects the need to promote the development of local businesses and the evolution of the number of economic agents to cover the necessary job needs (Table 8).
Taking into account the criterion for which this locality was chosen, a mathematical model was created using linear regression to observe the relationship between the factors that can influence, in this case, the population. To determine the mathematical model, independent variables were selected, which were closely related to the independent variable, according to the table below (Table 9).
In order to establish the intensity of the connection between the variables, the coefficient R2 was determined, in this case with a value of 0.999, which indicates that the dependent variable (population) was explained in a proportion of 99.9% by the independent variables (no. households, number of persons receiving social assistance, and number of economic agents) (Table 9).
We can say that, of all the independent variables, the number of people receiving social assistance had the highest impact on the dependent variable, with a beta value of 0.770, so the population was influenced by the number of people receiving social assistance. We noted that, although the number of inhabitants tended to decrease, the same was true for people receiving social assistance, being directly proportional, which can be explained by the fact that in an aging population, usually the people benefitting from this help are elderly or have health problems (Table 9).
In addition, the beta coefficient (−0.148) regarding the independent variable “no. of households” had a high impact on the dependent variable, so we can say that the population was influenced by the number of households, being inversely proportional. In this case study, we can explain that once the population tended to decrease, the number of households increased. Basically, the households of the elderly who died were inherited by their children, who chose not to sell them (for reasons of attachment) or had no one to sell them, but the newly founded families chose to build new households (Table 9).
If the data on the basis of which the values were introduced in the Vensim simulation program remain constant, we can say that within 10 years the population of Nicolae Balescu will register a significant decrease, reaching approximately 1400 inhabitants (Figure 6).

4.1.3. Case Study 3. Soldanu Locality

In Soldanu commune, no births were registered in the period analyzed. Regarding the number of deceased persons, a downward trend was registered in 2020 compared to 2015, with a decrease of 28.81%. On average, in the analyzed period, 43 people died every year (Table 10).
The persons receiving social assistance in Soldanu commune increased in the analyzed period, with an evolution of 20.53% registered in 2020 compared to the number of persons benefiting from such support in 2015. The annual average of persons who benefitted from social assistance was 220 people, with a positive annual rate of 3.8%. The number of people receiving social assistance represented a percentage of 6.89% of the total number of inhabitants (Table 10).
In Soldanu commune, the number of medical units was constant, with only one such medical unit found at the commune level. Relating the population to the number of medical units in the commune, it can be seen that the only existing medical unit served almost 3320 people (Table 10).
An important indicator regarding the Soldan commune, in Calarasi county, is represented by the number of economic agents that carried out their activity in the commune. From 2015 to 2020, the number of economic agents registered an upward trend. In 2020, the commune registered 135 economic agents, of which only six economic agents had an agricultural profile, representing 4.44% of the total economic agents. This distribution of the economic agents present in Soldanu commune indicates that there was a diversification of economic activities, and the share of agricultural activities was insignificant. In the commune, no tourist unit was registered (Table 11).
Comparing the number of inhabitants to the number of economic agents registered in Soldanu commune, it was found that there was one economic agent per 24.59 inhabitants—a good proportion, given that we are talking about a commune located in the southern part of Romania, where the diversification of agricultural activities is significant (Table 11).
In order to establish the intensity of the connection between the variables, the coefficient R2 was determined—in this case, with value of 0.929, which indicates that the dependent variable (no. of economic agents) was explained in proportion of 92.9% by the variables independent (population, no. of households and no. of persons receiving social assistance) (Table 12).
We can say that of all the independent variables, the number of households had the highest impact on the dependent variable, with a beta value of 1654, so the number of economic agents was influenced by the number of households. It is noted that, while the number of households increases, the same happened with the number of economic agents, with the variables being directly proportional. We noted that although the number of deaths was high, the population seemed to remain constant, which can explained by the fact that the town managed to attract people from other towns who wanted to start economic activities due to the location of the commune, being located halfway between Bucharest and Oltenita (near the Danube River) (Table 12).
In addition, the beta coefficient (−0.464) regarding the independent variable ”no. of people receiving social assistance” had a high impact on the dependent variable, so we can say that the number of economic agents was influenced by the number of people receiving social assistance, being inversely proportional. By increasing the number of economic agents, jobs are created, to which the persons belonging to this category can be introduced (Table 12).
If the data on the basis of which the values were introduced in the Vensim simulation program remain constant, we can say that within 10 years the population of Soldanu will register a significant decrease, reaching approximately 2900 inhabitants (Figure 7).

4.1.4. Case Study 4. Sarulesti Locality

The number of inhabitants in Sarulesti commune, in Calarasi county, registered a slight decrease of 0.28% in 2020 compared to 2015. The average population in the five years was 3214 inhabitants. In addition, against the background of the slight decrease in the number of inhabitants, the number of households in the commune registered an evolution of 9.30%, and the annual growth rate was positive, at 1.8%. Relating the number of inhabitants to the number of households in the commune, it was found that 2.85 people lived in a household (Table 13).
In Sarulesti commune, in the five years analyzed, the birth rate registered a significant decrease. In 2020 28.57% fewer children were born than in 2015. Regarding the number of deceased persons, a downward trend was registered in 2020 compared to 2015, with a decrease of 2.94%. On average, 35 people died per year during the analyzed period. Analyzing comparatively the number of newborns with the number of people who lost their lives in 2020, it was found that the number of deceased persons was six times higher than that of newborns (Table 13). The persons receiving social assistance in Sarulesti commune decreased in the analyzed period, registering in 2020 a decrease of 21.45% compared to the number of persons benefiting from such support in 2015. The annual average of persons benefitting from social assistance was 148 people, with a negative annual rate of 4.7%. The number of people receiving social assistance represented a percentage of 4.65% of the total number of inhabitants (Table 13). In Sarulesti commune the number of medical units was constant, with two such medical units at the commune level. Relating the population to the number of medical units in the commune, it can be seen that one medical unit served almost 1610 people (Table 13).
The number of economic agents operating in the commune of Sarulesti is an important indicator. From 2015 to 2020, the number of economic agents registered an upward trend. In 2020, the commune registered 27 economic agents, out of which only seven economic agents had an agricultural profile, representing 25.92% of the total economic agents. This distribution of the economic agents present in Sarulesti commune indicates that there was a diversification of economic activities, and the share of agricultural activities was not significant. In 2020, there were four tourist units in the commune. The existence of these tourist units can be attributed to the fact that fishing activities take place in this commune (Table 14).
Relating the number of inhabitants to the number of economic agents registered in Sarulesti commune, it was found that there was one economic agent per 119.29 inhabitants (Table 14).
In order to establish the intensity of the connection between the variables, the coefficient R2 was determined—in this case, with value of 0.985, which indicates that the dependent variable (no. economic agents) was explained in a proportion of 98.5% by independent variables (no. of households, no. of persons receiving social assistance, and number of tourist units) (Table 15).
We can say that of all the independent variables, the number of tourist units had the highest impact on the dependent variable, with a beta value of 0.820, so the number of economic agents was influenced by the number of tourist units. It was noted that the two variables were directly proportional, so when the number of economic agents increased, there was an increase in tourist units. The fact that the Sarulesti locality benefits from favorable conditions for the establishment of these types of economic activities is also reflected by the total number of economic agents at the locality level (Table 15).
In addition, the beta coefficient (−0.143) regarding the independent variable “no. people receiving social assistance” had a high impact on the dependent variable, so we can say that the number of economic agents was influenced by the number of people receiving social assistance, being inversely proportional. By increasing the number of economic agents, jobs are created to which the persons belonging to this category can be introduced (Table 15).
If the data based on which the values were entered in the Vensim simulation program remain constant, we can say that within 10 years the population of Sarulesti will register a significant decrease, reaching approximately 2900 inhabitants (Figure 8).

4.2. Results of Socio-Economic Analysis of Rural Localities Determined in Timis County

4.2.1. Case Study 5. Sanmihaiu Roman Locality

The number of inhabitants in Sanmihaiu Roman commune in Timis county registered a slight increase of 9.43% in 2020 compared to 2015. The average population over the five years was 8671 inhabitants. The number of households in the commune also registered a significant evolution in 2020 compared to the number registered in 2015, at 70.42%, and the annual growth rate was positive, at 11.3%. Relating the number of inhabitants to the number of households in the commune, it was found that 2.19 people lived in a household (Table 16).
In Sanmihaiu Roman commune in the five years analyzed, the birth rate registered a significant evolution. In 2020 12.63% more children were born than in 2015. Regarding the number of deceased persons, an ascending trend was registered in 2020 compared to 2015, at an evolution of 8.16%. On average, 46 people per year died during the analyzed period. Analyzing the number of newborns compared to the number of people who lost their lives in 2020, it was found that the number of newborns was two times higher than the number of people who lost their lives (Table 16).
The persons receiving social assistance in Sanmihaiu Roman commune decreased in the analyzed period, with a 28% decrease registered in 2020 compared to the number of persons benefiting from such support in 2015. Annual average of persons benefit from social assistance is 25 people, with a negative annual rate of 6.4%. The number of people receiving social assistance represents a percentage of 0.20% of the total number of inhabitants (Table 16).
In Sanmihaiu Roman commune, the number of medical units was constant, with four in the commune. Relating the population to the number of medical units in the commune, it can be seen that one medical unit served almost 2247 people (Table 16).
The number of economic agents operating in Sanmihaiu Roman commune is an important indicator. From 2015 to 2020, the number of economic agents registered an upward trend. In 2020, the commune registered 552 economic agents, out of which only 10 economic agents had an agricultural profile, representing 1.81% of the total economic agents. This distribution of the economic agents present in Sanmihaiu Roman commune indicates that there was a diversification of economic activities, and the share of agricultural activities was insignificant. In 2020 there was only one tourist unit in the commune (Table 17).
Comparing the number of inhabitants to the number of economic agents registered in Sanmihaiu Roman commune, it was found that there was one economic agent per 16.28 inhabitants (Table 17).
In order to establish the intensity of the link between the variables, the coefficient R2 was determined—in this case, with value of 0.908, which indicates that the dependent variable (population) was explained in a proportion of 90.8% by the independent variables (no. of households, number of persons receiving social assistance, and number of economic agents) (Table 18).
We can say that of all the independent variables, the number of households had the highest impact on the dependent variable, with a beta value of 543, so the population was influenced by the number of households. It was noted that the two variables were directly proportional, so as the population grew there was an increase in households (Table 18).
In addition, the beta coefficient (−0.523) regarding the independent variable “no. people receiving social assistance” had a high impact on the dependent variable, so we can say that the population was influenced by the number of people receiving social assistance, being inversely proportional (Table 18).
If the data based on which the values were introduced in the Vensim simulation program remain constant, we can say that within 10 years the population of Sanmihaiu Roman will register a significant increase, reaching approximately 9250 inhabitants (Figure 9).

4.2.2. Case Study 6. Valcani Locality

The number of inhabitants in Valcani commune from Timis county registered a slight decrease of 0.94% in 2020 compared to 2015. The average population in the five-year period was 1379 inhabitants. Regarding the number of households in the commune, it remained constant in the analyzed period (2015–2020), with 534 households. Relating the number of inhabitants to the number of households in the commune, it was found that there were 2.56 people per household (Table 19).
In Valcani commune, in the five-year analyzed period the birth rate registered an evolution. In 2020 18.18% more children were born than in 2015. Regarding the number of deceased persons, a downward trend was registered in 2020 compared to 2015, with a decrease of 16.67%. On average, 14 people died per year during the analyzed period. Analyzing the number of newborns compared to the number of people who lost their lives in 2020, it was found that the number of newborns was exceeded by the number of people who lost their lives (Table 19).
In the commune of Valcani in Timis county, in the analyzed period there was only one person with social assistance in 2015; after this year there was no other beneficiary of social benefits (Table 19).
In Valcani commune, the number of medical units was constant, with only one such medical unit. Relating the population to the number of medical units in the commune, it can be seen that one medical unit served 1372 people (Table 19).
The number of economic agents operating in Valcani commune is an important indicator. From 2015 to 2020, the number of economic agents registered a slight evolution. In 2020, the commune registered 10 economic agents, half of whom were represented by economic agents that had an agricultural profile, indicating a significant share of agricultural activities carried out in the analyzed area (Table 20).
Comparing the number of inhabitants to the number of economic agents registered in Valcani commune, it is found that there was one economic agent per 137.2 inhabitants, which indicates an insufficient development of economic activities at the commune level and a possible lack of jobs (Table 20).
In order to establish the intensity of the link between the variables, the coefficient R2 was determined—in this case, with a value of 0.462, which indicates that the dependent variable (population) was explained in a proportion of 46.2% by the independent variables (number of deaths and the number of economic agents) (Table 21).
We can say that of all the independent variables, the number of deaths had the highest impact on the dependent variable, with a beta value of 0.677, so the population was influenced by the number of deaths. It was noted that the two variables were directly proportional (Table 21).
If the data on the basis of which the values were introduced in the Vensim simulation program remain constant, we can say that within 10 years the population of Valcani will decrease, reaching approximately 1350 inhabitants (Figure 10).

4.2.3. Case Study 7. Peciu Nou Locality

Peciu Nou commune in Timis county is composed of Dinias, Peciu Nou (residence), and Sanmartinu Sarbesc villages. Regarding the population, in this commune the trend increased slightly, registering 5.34% more inhabitants in 2020 than in 2015. The annual average population in the analyzed period was 5567 inhabitants, and the growth rate was positive one, at 1% (Table 22).
From 2018 until 2020, the number of households in the commune of Peciu Nou registered a positive evolution, with an increase of 9.02% in the number of households in 2020 compared to the value registered in 2015. The average number of households in the period analyzed was 2107, and the annual rhythm was positive, at 1.7% (Table 22).
Regarding birth and mortality, the number of newborns in the commune fluctuated, registering a maximum in 2016, when 58 children were born, whereas the minimum registered was in 2019, when 28 children were born. In 2020, the number of newborns was 21.62% higher than the number registered in 2015, and the average number of newborns in the analyzed period was 43 children per year. Regarding the mortality indicator, the number of people who died in 2020 was 2.13% lower than the number of deaths recorded in 2015. The number of people who died in 2020 slightly exceeded the number of newborns (Table 22).
In Peciu Nou commune in 2020 a total of 11 people benefited from social aid, 15.38% less than the beneficiaries of social aid in 2015. Comparing the number of inhabitants to the number of social aid beneficiaries, it was noted that those who received social benefits represented 0.19% of the commune’s population (Table 22).
In 2020, in the commune of Peciu Nou there were four medical units, and each unit served, on average, 1425 people (Table 22).
The number of economic agents from Peciu Nou commune registered an ascending trend in the analyzed period. Thus, if in 2015 there were 485 economic agents, in 2020 that number increased by 8.2%. The annual growth rate of the number of economic agents was positive, at 1.6%. Of the 525 economic agents existing in 2020, 45 of them had an agricultural profile, representing 8.5% of the total economic agents. This report indicates that there was a diversification of the economic agents’ activity, and agriculture was little represented at the level of existing economic agents in Peciu Nou commune (Table 23).
In order to establish the intensity of the link between the variables, the coefficient R2 was determined—in this case, with a value of 0.878, which indicates that the dependent variable (number of economic agents) was explained in a proportion of 87.8% by the independent variables (population, no. of households, and no. of economic agents with agricultural profile) (Table 24).
We can say that, of all the independent variables, the population had the highest impact on the dependent variable, with a beta value of 0.828, so the number of economic agents was influenced by the population. It was noted that the two variables were directly proportional, so when the number of economic agents increased, there was an increase in the population (Table 24).
If the data based on which the values were introduced in the Vensim simulation program remain constant, we can say that within 10 years the population of Peciu Nou will decrease, reaching approximately 5535 inhabitants (Figure 11).

4.2.4. Case Study 8. Fardea Locality

Fardea commune in Timis county is composed of the villages of Dragșinesti, Fardea (residence), Gladna Montana, Gladna Romana, Hauzesti, Matnicu Mic, and Zolt. Regarding the population, in this commune the trend decreased slightly, registering 5.89% fewer inhabitants in 2020 than in 2015. The annual average population in the analyzed period was 1699 inhabitants and the annual rhythm was negative, at 1.2% (Table 25).
From 2018 until 2020, the number of households in Fardea commune registered a positive evolution, with an increase of 1.66% in the number of households in 2020 compared to the value registered in 2015. The average number of households in the analyzed period was 548, and the rate was positive, at 0.3% (Table 25).
Regarding the birth and mortality rates, the number of newborns in the commune registered a significant decrease in 2020 compared to 2015, with 41.67% fewer newborns in 2020 compared to 2015. The average number of newborns in the analyzed period was 10. Regarding the mortality indicator, the number of people who died in 2020 was 19.05% higher than the number of deaths recorded in 2015. The number of deaths in 2020 was 3.5 times higher than the number of newborns. In Fardea commune in 2020, no one benefited from social assistance, whereas in 2019 two people received social assistance. In 2020, in the commune of Fardea there was only one medical unit, which served a total of 1647 inhabitants (Table 25).
Analyzing the data provided by local authorities, in 2020 there was no economic operator registered in the commune. During the analyzed period, it was noticed that in 2018 there were eight economic agents, of which two had an agricultural profile, and there were also three tourist units. Since in 2020 there was no registered economic agent, we can assume that those with an agricultural profile, as well as the tourist units, ceased their activities (Table 26).
To establish the intensity of the link between the variables, the coefficient R2 was determined—in this case, with a value of 0.990, which indicates that the dependent variable (population) was explained in a proportion of 99.0% by the independent variables (no. households and no. newborns) (Table 27).
If the data on the basis of which the values were entered in the Vensim simulation program remain constant, we can say that within 10 years the population of Fardea will decrease, reaching approximately 1600 inhabitants (Figure 12).

5. Discussion

The aging population influences the high level of mortality in the localities analyzed, and there is a link between these two variables [62,63,64]. This highlights the high number of elderly inhabitants, more so as the number of deaths exceeds the birth rate, which is highlighted by the population trend over the next 10 years, which shows negative values. This hypothesis is therefore verified and proves true [65,66].
Drawing a parallel between the demographic situation of rural areas in Romania and other countries, Kasimis [67] presented in his paper that “demographic aging has been a major problem in rural areas of some Member States, especially in Spain, Greece, Portugal and France, where the rural population is made up of a higher proportion of people over the age of 65.” The study revealed a situation like the one facing our country, namely, that in the same countries mentioned above, there is a relatively low percentage of children compared to retirees, a low proportion of young adults compared to retirees, and a high overall dependency ratio (total population/ages 15–64).
At the EU level, about 17% of the rural population is already over the retirement age, and in countries such as Spain, France, Greece, and Portugal in particular, this share stands at 18–22%, which was also the case at the beginning of Romania’s accession [68].
Romania can be compared in many respects (similar agricultural area, similar past, Eastern Europe) with Poland. Analyzing the literature, we observed similarities in this phenomenon in the rural environment. Studies have shown that rural areas with a higher standard of living are often located along the most important transport routes. Additionally, the areas near big cities attract bigger investments. At the same time, the results of the study showed that in Poland, like in Romania, the standard of living in rural areas is very diverse, depending on the spatial distribution, industrialization, and urbanization. Rural areas with economic and often social underdevelopment, with low development dynamics, appear in peripheral locations compared to the main urban network [69].
In all eight localities analyzed, the number of new births per population was extremely low [70]. This is due to the aging population and the low number of young people in these localities. The “lifestyle” factor, which is predominantly found in urban areas, was also evident in these rural areas, where young people are looking for ways to secure a better standard of living and are leaving their native villages [71].
An interesting aspect is the evolution of the number of households, which generally tended to increase [72]. Households of deceased people are usually taken over by legal heirs, who often choose not to return to their places of origin. Even if they would like to sell the household, due to the lack of demand for these households, they remain in a state of severe decay [73,74].
However, young people who still live in these rural areas prefer to build a new houses rather than live in the old ones. Thus, the number of such households tended to increase because old households remained and new ones appeared (if young people chose to stay in the villages) [75,76,77]. Clearly, there was an association between population and number of households, so H2 does hold.
The larger the population in the localities, the more the number of economic agents tended to increase to meet market needs [78]. However, this was also influenced to a large extent by the standard of living, which in rural areas is much lower than in urban areas [79,80].
As a rule, the economic activities existing at the local level do not create enough jobs, because to a large extent, these activities are service providers, mostly represented by bars, entertainment halls, shops, and betting shops, which are managed and run by a small staff [81]. In addition, large or very large agricultural activities are equipped with high-performance machinery and equipment, which do not require many staff, given that the cultivation of cereal and oilseed crops predominates in these two regions. In recent years, large companies (supermarkets and building materials) have entered the local market and tend to take over the normal economic activities of residents [82].
Insufficient funds at the disposal of local authorities, due to low contributions to the local budget both in terms of the reduced number of economic agents and the number of existing employees, are blocking local infrastructure development processes. Although European funds can be accessed, the lack of co-financing prevents them from being accessed [83,84]. Without adequate infrastructure, young people cannot be retained or attracted to rural areas. The exception is areas close to urban centers (peri-urban areas) where significant development is taking place [85,86].
All the localities analyzed have a minimal, partially developed local infrastructure, which limits the access of potential investors who can generate funds for the local budget and create new jobs [87].
The aging population and the lack of jobs are also reflected in the high number of people receiving social aid in relation to the population, but this aspect is characteristic of the analyzed localities in Calarasi county. In this case H4 is partially true, since in the case of the localities in Timis the links between the two variables were not strongly influenced.

6. Conclusions, Implications, and Limitations

The topic of this research has been and remains highly up to date, being debated by researchers around the world and drawing on both old and new policies applied at the European level. Its implications, so important from a social and economic point of view, continue to be relevant.
In some rural areas of some EU countries, socio-economic discrepancies may arise due to various factors, but in Romania these discrepancies are only found between rural areas close to cities and rural areas. At the regional level, whether the region is analyzed as a region with predominantly agricultural economic activities (South-Muntenia region, Calarasi county) or with diversified activities (West region, Timis county), the rural area presents mostly the same characteristics.
The connections between internal and external factors that can contribute to the development of localities are extremely diverse. According to the localities analyzed, their geographical location limits their development in the sense that the distance to the nearest town is relatively far. The local resources available at local or regional level are mainly based on agricultural land.
The local economy has a direct influence on the population and local authorities. With a poorly developed economy, people tend to migrate to urban centers, depopulating rural areas, and local authorities lack funds to revitalize local infrastructure. Competition from large firms entering local markets also puts local activities at risk. In this way, instead of financial resources staying and circulating within the region, creating added value, they leave the locality or region [88,89,90].
It was found that the jobs are insufficient due to the fact that the local infrastructure is poorly developed and unable to attract external investors, but also due to the lack of entrepreneurship of the residents. At the same time, the generation of new jobs can contribute to the local economy and create conditions for retaining and attracting people to rural areas [90,91].
Taking into account all the elements analyzed, it can be concluded that the main factor that can change this pattern of rural localities is the local authorities and the government, which can encourage investment in these areas, either through the development of local and national infrastructure or through fiscal measures that encourage the development of quality non-agricultural activities that can generate financial resources and jobs at the local level.
However, the low number of non-agricultural activities is not the only factor causing the poor development of rural areas, nor is it the most important. Rather, it is the low number of economic agents in general and the quality of the types of activities undertaken, which cannot generate jobs. Economically viable family farms can contribute to the development of rural areas by functioning as an ecosystem.
In conclusion, rural areas have an interdependent relationship with both internal and external factors, where one variable is influenced by another, thus building a pattern that is difficult to break through to develop these rural areas.

Author Contributions

The authors worked together for this research, but, per the structure, conceptualization T.I., V.C.T. and M.M.M.; methodology, software validation, and resources, I.L.P., A.U. and F.-R.T.; formal analysis, E.A.D. and I.L.P.; writing—original draft preparation and writing—review and editing, E.A.D. and I.L.P. All authors have read and agreed to the published version of the manuscript.

Funding

The publication of this paper was made possible by the funds of Banat University of Agricultural Sciences and Veterinary Medicine “King Michael I of Romania” in Timisoara and the Research Institute for Biosecurity and Bioengineering in Timisoara.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding author. The data are not publicly available due to privacy.

Acknowledgments

This article is the result of the ADER 23.1.1 project “Fundamentarea tehnico-economică a costurilor de producţie şi estimări privind preţurile de valorificare ale principalelor produse vegetale și animale, obținute în sistem conventional și în agricultura ecologică” (Techno-economic substantiation of production costs and estimates of the value-added prices of the main crop and livestock products obtained in conventional and organic farming) and the project “Proiect de formare continuă în domeniul cercetării științifice pentru cercetătorii ASE” (Project for continuous training in the field of scientific research for the Bucharest University of Economic Studies researchers), conducted at the Bucharest University of Economic Studies.

Conflicts of Interest

The authors declare no conflict of interest.

Limitations

We can consider the fact that the eight localities may not be statistically representative to extrapolate the situation at the national level for all localities, but we cannot notice the pattern that was found in seven of these localities, at a rate of 87.5%.

References

  1. Bold, I.; Drăghici, M. Two Centuries of Rural and Agrarian Economy. Portraits and Meanings; Mirton: Timisoara, Romania, 2004; p. 51. [Google Scholar]
  2. Bologa, G. Sustainable Rural Development in Romania. Productivity Advances in Agriculture; Pro Universitaria: Bucharest, Romania, 2013; p. 143. [Google Scholar]
  3. Istudor, N. Romania’s Rural and Regional Development in the Perspective of Integration into the European Union; ASE Publishing House: Bucharest, Romania, 2006; pp. 72–73. Available online: https://www.editura.ase.ro/Dezvoltarea-rurala-si-regionala-a-Romaniei-in-perspectiva-integrarii-in-Uniunea-Europeana/ (accessed on 5 January 2022).
  4. Geamasu, T.; Alecu, I. Conceptual approaches of the rural space. In Agrarian Economy and Rural Development-Realities and Perspectives for Romania; The Research Institute for Agriculture Economy and Rural Development: Bucharest, Romanian, 2014; pp. 8–12. [Google Scholar]
  5. Bold, E.; Buciuman, N.; Drăghici, M. Rural Space—Definition, Organization, Development; Mirton: Timisoara, Romania, 2003; p. 149. [Google Scholar]
  6. Radulescu, C.V. Regional and Rural Development; ASE Publishing House: Bucharest, Romania, 2007; pp. 17–20. Available online: https://www.targulcartii.ro/carmen-valentina-radulescu/dezvoltare-regionala-si-rurala-ase-2007-728506 (accessed on 5 January 2022).
  7. Dumitru, E.A.; Micu, A.R.; Alecu, I.; Tudor, V.; Micu, M.M. Analisys of the situation of Romanian village—Case study Grindu Commune, Ialomita County. In Proceedings of the 29th International-Business-Information-Management-Association Conference, Vienna, Austria, 3–4 May 2017; pp. 740–747. [Google Scholar]
  8. Dumitru, E.A.; Micu, M.M.; Tudor, V. Conceptual approches regarding the Romanian rural area. Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2019, 19, 121–127. [Google Scholar]
  9. Dinu, M.; Patarlageanu, S.R.; Chiripuci, B.; Constantin, M. Accessing European funds for agriculture and rural development in Romania for the 2014–2020 period. In Proceedings of the 14th International Conference on Business Excellence (ICBE)—Business Revolution in the Digital Era, Bucharest, Romania, 27 June 2020; pp. 717–727. [Google Scholar] [CrossRef]
  10. Giosan, N. Romanian Agriculture; Agro—Silvica: Bucharest, Romania, 1965; p. 195. [Google Scholar]
  11. Glogoveţan, O.E. The Evolution of Agricultural Holdings in Romania—A Fundamental Element of the Rural Economy. Ph.D. Thesis, Babeș-Bolyai University, Cluj Napoca, Romania, 2014. [Google Scholar]
  12. Ivanovic, O.D.M.; Golušin, M.T.; Dodić, S.N.; Dodić, J.M. Perspectives of sustainable development in countries of Southeastern Europe. Renew. Sustain. Energy Rev. 2009, 13, 2079–2087. [Google Scholar] [CrossRef]
  13. Kerekes, K.P.B.; Szocs, E.; Veres, E.; Vincze, M. Rural Development. Employment in Rural Areas; Accent: Cluj-Napoca, Romania, 2010; pp. 33–38. [Google Scholar]
  14. Popescu, M.; Popescu, C.; Per, E. Rural Area and Rural Development. Agric. Manag. 2018, 20, 88–93. [Google Scholar]
  15. Baum, S.; Weingarten, P. TypIsierung Landlicher Raume in Mittel-und Osteuropa; Europa Regional: Leibnitz, Austria, 2004; pp. 149–150. [Google Scholar]
  16. Mitrică, B.; Şerban, P.; Mocanu, I. Social Development and Regional Disparities in the Rural Areas of Romania: Focus on the Social Disadvantaged Areas. Soc. Indic Res. 2020, 152, 67–89. [Google Scholar] [CrossRef]
  17. Comanescu, I.S.; Foris, D.; Floris, T. Dimensions of the Funding Programmes for Sustainable Rural Development in Romania. Econ. Sci. Rural Dev. 2019, 50, 44–51. [Google Scholar] [CrossRef]
  18. Raicov, M.; Banes, A.; Brad, I.; Feher, A. Absorption of Rural Development Funds. A Lesson Learned? Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2021, 21, 505–512. [Google Scholar]
  19. Paul, L. Rural Development in Romania—A Few Considerations. Stud. Bus. Econ. 2020, 15, 165–175. [Google Scholar] [CrossRef]
  20. Mack, G.; Fintineru, G.; Kohler, A. Do Rural Development Measures Improve Vitality of Rural Areas in Romania? AgroLife Sci. J. 2018, 7, 82–98. [Google Scholar]
  21. Pavel, A.; Moldovan, B.; Neamtu, B.; Hintea, C. Are Investments in Basic Infrastructure the Magic Wand to Boost the Local Economy of Rural Communities from Romania? Sustainability 2018, 10, 3384. [Google Scholar] [CrossRef] [Green Version]
  22. Frone, D.F.; Frone, S. Regionalization Increasing Access to Water Supply and Sanitation in Rural Romania. Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2019, 19, 135–143. [Google Scholar]
  23. Popovici, E.A.; Mitrica, B.; Mocanu, I. Land concentration and land grabbing: Implications for the socio-economic development of rural communities in south-eastern Romania. Outlook Agric. 2018, 47, 204–213. [Google Scholar] [CrossRef]
  24. Bran, F.; Ciobanu, G.; Popescu, M.L.; Vasilache, P.C. Sustainable Local Development in Romania in the Opportunity of Creating Jobs. Eur. J. Sustain. Dev. 2020, 9, 287. [Google Scholar] [CrossRef]
  25. Simescu, L.; Rahoveanu, M.M.T.; Risnoveanu, L. Diversification and consolidation of the system training in agriculture in Romania. Educ. Excell. Innov. Manag. Vis. 2020, 11, 1306–1309. [Google Scholar]
  26. Ibănescu, B.-C.; Stoleriu, O.M.; Munteanu, A.; Iațu, C. The Impact of Tourism on Sustainable Development of Rural Areas: Evidence from Romania. Sustainability 2018, 10, 3529. [Google Scholar] [CrossRef] [Green Version]
  27. Uliu, D.V.; Vladu, M. Researches Regarding the Increase and Modernization of the Meat Processing Capacities by Using the Funds Offered through the National Rural Development Program in the North West Development Region. Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2020, 20, 593–598. [Google Scholar]
  28. Ulman, S.R.; Isan, V.; Mihai, C.; Ifrim, M. The Responsiveness of the Rural Area to the Related-Decreasing Poverty Measures of the Sustainable Development Policy: The Case of North-East Region of Romania. Transform. Bus. Econ. 2018, 17, 780–805. [Google Scholar]
  29. Pavel, A.; Moldovan, B.A.; Kourtit, K.; Nijkamp, P. Urban or Rural: Does It Make A Difference for Economic Resilience? A Modelling Study on Economic and Cultural Geography in Romania. Sustainability 2020, 12, 3776. [Google Scholar] [CrossRef]
  30. Mihai, F.-C.; Minea, I. Sustainable Alternative Routes versus Linear Economy and Resources Degradation in Eastern Romania. Sustainability 2021, 13, 10574. [Google Scholar] [CrossRef]
  31. Lile, R.; Boghicevici, C.; Stoian, C.D. Role of social professions in the process of sustainable development of rural area. Study case. Jurid. Trib. Trib. Jurid. 2018, 8, 415–424. [Google Scholar]
  32. Pop, C.; Georgescu, M.A. Romanian Rural World Heritage Sites and Tourism Development. Entrep. Bus. Econ. Rev. 2019, 7, 135–158. [Google Scholar] [CrossRef]
  33. United Nations Division for Sustainable Development. United Nations Conference on Environment & Development, Agenda 21, Rio de Janerio, Brazil, 3–14 June 1992. Available online: https://sustainabledevelopment.un.org/content/documents/Agenda21.pdf (accessed on 5 January 2022).
  34. Nagiu, A.; Vázquez, J.L.; Georgiev, I. Rural Development Strategies through Rural Tourism Activities in Romania: Chance for an Internal Demand. Int. Rev. Public Nonprofit Mark. 2009, 2, 85–95. [Google Scholar] [CrossRef]
  35. Cebotari, S.; Cristea, M.; Moldovan, C.; Zubascu, F. Renewable energy’s impact on rural development in northwestern Romania. Energy Sustain. Dev. 2017, 37, 110–123. [Google Scholar] [CrossRef]
  36. Dachin, A. Rural development—A basic condition for narrowing regional disparities in Romania. Rom. J. Reg. Sci. 2008, 2, 106–117. [Google Scholar]
  37. Mihăilescu, V. Peasant Strategies and Rural Development in Romania; Coping with Local Diversity in Development Policy; Social Cost of Economic Transformation in Central Europe: Bucharest, Romania, 2000; pp. 4–6. [Google Scholar]
  38. Alboiu, C.; Kuliesis, G.; Salengaite, D. The impact of rural development program on agriculture and business/rural development in lIthuania and Romania: A mirror situation. Agric. Econ. Rural Dev. 2011, 8, 654–665. [Google Scholar]
  39. Ciutacu, C.; Chivua, L.; Jean, V.A. Similarities and dissimilarities between the EU agricultural and rural development model and Romanian agriculture. Challenges and perspectives. Elsevier Land Use Policy 2015, 44, 169–176. [Google Scholar] [CrossRef] [Green Version]
  40. Munteani, A. Aspects of implementation of information technology in rural development in Romania. Anim. Husb. Ser. 2009, 53, 88–93. [Google Scholar]
  41. Ciani, A.; Gambardella, A.; Pociovălișteanu, D.M. Circular economy and sustainable rural development. Theory and best practice: A challenge for Romania. Ann.-Econ. Ser. 2016, 1, 52–56. [Google Scholar]
  42. Micu, M.M. Research on accessing european funds for young farmers in Romania under the two national rural development programs. Econ. Soc. Dev. 2018, 184–190. Available online: https://am.e-nformation.ro/conference-papers-proceedings/research-on-accessing-european-funds-young/docview/2131162967/se-2?accountid=136549 (accessed on 5 January 2022).
  43. Albu, R.G.; Chiţu, I.B. Local action groups (lags)—An important instrument in ensuring the sustainable development of rural areas in Romania. Bull. Transilv. Univ. Braşov Ser. V Econ. Sci. 2014, 7, 97. [Google Scholar]
  44. Gallardo-Cobos, R. Rural Development in the European Union: The concept and the policy. Agron. Colomb. 2010, 28, 475–481. [Google Scholar]
  45. Thomas Dax, I.M.; Machold, M. Forderung der landwirtschaftlich benachteiligten Gebiete in denneuen Mitgliedstaaten der EU. In Ländlicher Raum-Online Fachzeitschrift des Bundesministerium für Land-und Forstwirtschaft, Umwelt und Wassemirtschaft; Bundesministerium für Landwirtschaft, Regionen und Tourismus (Federal Ministry for Agriculture, Regions and Tourism): Vienna, Austria, 2007; pp. 1–14, (In Germany). Available online: https://info.bmlrt.gv.at/dam/jcr:6e1b2d4b-d6c6-46ed-87c6-b270ad0e5e71/Dax_Machold_pdf_END.pdf (accessed on 5 January 2022).
  46. Steiner, M. Ländliche Regionen—Gib’s die? Einige Anm. Strateg. 2003, 1, 17–31. [Google Scholar]
  47. Henry, D.C. Reviving Romania’s rural economy. RFE/RL Research Rep. 1994, 3, 18. Available online: https://am.e-nformation.ro/trade-journals/reviving-romanias-rural-economy/docview/233236058/se-2?accountid=136549 (accessed on 5 January 2022).
  48. Micu, A.R.; Dumitru, E.A.; Tudor, V.; Alecu, I.N.; Micu, M.M. The factors that influence the development of rural villages: Case study Semlac Commune, Arad County. In Proceedings of the 29th International-Business-Information-Management-Association Conference, Vienna, Austria, 3–4 May 2017; pp. 748–756. [Google Scholar]
  49. Mihăilescu, I. General Sociology; Polirom: București, Romania, 2003; p. 77. [Google Scholar]
  50. Pilar García-Guadilla, M.; Blauert, J. Environmental Social Movements in Latin America and Europe: Challenging Development and Democracy. Int. J. Sociol. Soc. Policy 1992, 12, 1–274. [Google Scholar] [CrossRef]
  51. Moser, A.; Peter, H.; Fengler, B.; Strohm-Lompcke, R. Improving the quality of life with rural developement programms in Germany (2007–2013). Eur. Countrys. 2018, 11, 321–339. [Google Scholar] [CrossRef]
  52. Oprea, R. Sustainable Development and Environmental Protection; Universitatea Dunărea de Jos: Galati, Galati, 2008; pp. 145–168. [Google Scholar]
  53. Oprean, C.; Vanu, M.A.; Bucur, A. Sustainable Development Modeling. Manag. Sustain. Dev. 2018, 1, 10–18. [Google Scholar]
  54. Pascaru, M. Sociology of Communities; Argonaut: Cluj-Napoca, Romania, 2003; p. 134. [Google Scholar]
  55. Dinga, E. Economic Sustainability through Adjustment Policies in the Context of Globalization; Academia Romaine: Bucharest, Romania, 2001; p. 24. [Google Scholar]
  56. Dona, I. Rural Economy; Economică: Bucharest, Romania, 2015; p. 104. [Google Scholar]
  57. Dumitru, E.A.; Badan, D.; Petre, I.L.; Bratulescu, A.M. Analysis of agricultural holdings in Romania in terms of size. Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2020, 20, 193–198. [Google Scholar]
  58. Wagner, K. Going beyond the Rural Development Programme: A master plan for Austria’s rural areas in the framework of the CAP. In The Common Agricultural Policy of the European Union—The Present and the future EU Member States Point of View, Proceedings of the International Scientific Conference The Common Agricultural Policy of the European Union-the Present and the Future Multi-annual Programme 2015–2019 The Polish and the EU Agricultures 2020+. Challenges, Chances, Threats, Proposals, Stare Jablonki, Poland, 5–7 December 2017; Institute of Agricultural and Food Economics-National Research Institute(IAFE-NRI): Warsaw, Poland, 2018; pp. 62–68. [Google Scholar] [CrossRef]
  59. European Court of Auditors. Special Report: Programming for Rural Development: There Is a Need to Reduce Complexity and Put More Emphasis on Results; Publications Office of the European Union: Luxembourg, 2017; ISBN 978-92-872-8249-1. [Google Scholar]
  60. Podreka, J.; Rodela, R. Local action groups and environmental protection: Overview of the projects which contribute to the second axis of the Rural Development Programme. Geogr. Vestn. 2013, 85, 47–56. Available online: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84889052989&partnerID=40&md5=a89a92c1e1cf604d4b70bc606f17906c (accessed on 5 January 2022).
  61. Pollermann, K.; Aubert, F. LEADER as european policy for rural development in a multi level governance framework: A comparison of implementation in France, Germany and Italy. Eur. Ctry. 2020, 12, 156–178. [Google Scholar]
  62. LAW No. 544 of October 12, 2001 on Free Access to Information of Public Interest, Romania. Available online: https://legislatie.just.ro/Public/DetaliiDocument/31413 (accessed on 5 January 2022).
  63. Fanea-Ivanovici, M. Culture as a Prerequisite for Sustainable Development. An Investigation into the Process of Cultural Content Digitisation in Romania. Sustainability 2018, 10, 1859. [Google Scholar] [CrossRef] [Green Version]
  64. Iorga, A.M.; Stoicea, P.; Dobre, C. Statistics of the Rural Population from the Regional Perspective. Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2020, 20, 287–294. [Google Scholar]
  65. Vladu, M.; Panzaru, R.L.; Savescu, P.; Matei, G. Studies on the Situation of Investments Made with Public Funds under 123 Measure “Increasing the Added Value of Agricultural and Forestry Products” of the National Rural Development Program, in the South-West Oltenia Development Region in Romania. Rom. Agric. Res. 2018, 35, 275–281. [Google Scholar]
  66. Stanciu, M. Economic and Social Policies to Combat Poverty in Romania in the Last Century. In The Romanian Economy, A Century of Transformation (1918–2018): Proceedings of Espera; Peter Lang GmbH: Berlin, Germany, 2019; pp. 233–244. [Google Scholar]
  67. Kasimis, C. Demographic trends in rural Europe and international migration to rural areas. Agriregionieuropa 2010, 21, 1–6. [Google Scholar]
  68. European Commission. Agriculture in the European Union—Statistical and Economic Information. 2007. Available online: https://ec.europa.eu/info/food-farming-fisheries/key-policies/common-agricultural-policy/cmef#indicator (accessed on 5 January 2022).
  69. Brambert, P.; Kinjorsja, I. Changes in the Standard of Living in Rural Population of Poland in the Period of the EU Membership. Eur. Countruside 2018, 10, 263–279. [Google Scholar] [CrossRef] [Green Version]
  70. Popescu, A.; Dinu, T.A.; Stoian, E. Demographic and Economic Changes Characterizing the Rural Population in Romania. Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2018, 18, 333–346. [Google Scholar]
  71. Pavel, A.; Moldovan, O. Determining Local Economic Development in the Rural Areas of Romania. Exploring the Role of Exogenous Factors. Sustainability 2019, 11, 282. [Google Scholar] [CrossRef] [Green Version]
  72. Mihai, C.; Ulman, S.R.; David, M. New Assessment of Development Status among the People Living in Rural Areas: An Alternative Approach for Rural Vitality. Sci. Ann. Econ. Bus. 2019, 66, 167–192. [Google Scholar] [CrossRef]
  73. Tecau, A.S.; Dimitriu, C.; Marinescu, N.; Tescasiu, B.; Epuran, G.A. Qualitative Research on the Food Security of School Children in the Rural Area. Sustainability 2020, 12, 9024. [Google Scholar] [CrossRef]
  74. Pargaru, I.; Stancioiu, F.; Ladaru, R.G.; Teodor, C. Sustainable Development in Agriculture at the Level of Romania and the European Union. Qual. Access Success 2019, 20, 446–450. [Google Scholar]
  75. Olar, A.; Jitea, M.I. Enabling Factors for Better Multiplier Effects of the LEADER Programme: Lessons from Romania. Sustainability 2021, 13, 5184. [Google Scholar] [CrossRef]
  76. Vijulie, I.; Lequeux-Dincă, A.-I.; Preda, M.; Mareci, A.; Matei, E.; Cuculici, R.; Taloș, A.-M. Certeze Village: The Dilemma of Traditional vs. Post-Modern Architecture in Țara Oașului, Romania. Sustainability 2021, 13, 11180. [Google Scholar] [CrossRef]
  77. Florea, A.-M.; Capatina, A.; Radu, R.I.; Serban, C.; Boboc, M.G.; Stoica, C.; Munteanu, M.; Ion, I.M.; Stanciu, S. Limiting Factors that Influence the Formation of Producer Groups in the South-East Region of Romania: A Fuzzy Set Qualitative Comparative Analysis (fsQCA). Sustainability 2019, 11, 1614. [Google Scholar] [CrossRef] [Green Version]
  78. Maican, S.Ș.; Muntean, A.C.; Paștiu, C.A.; Stępień, S.; Polcyn, J.; Dobra, I.B.; Dârja, M.; Moisă, C.O. Motivational Factors, Job Satisfaction, and Economic Performance in Romanian Small Farms. Sustainability 2021, 13, 5832. [Google Scholar] [CrossRef]
  79. Chiripuci, B.-C.; Constantin, M.; Popescu, M.-F.; Scrieciu, A. The Socio-Economic Impact of Migration on the Labor Market in the Romanian Danube Region. Sustainability 2020, 12, 8654. [Google Scholar] [CrossRef]
  80. Popescu, A. Considerations on the rural population as a resource of labor force in Romania. Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2013, 13, 146–156. [Google Scholar]
  81. Badiu, A. European funds for agriculture and rural development—Help or burden for Romania? Europolity 2013, 7, 73–86. [Google Scholar]
  82. Beciu, S.; Lădaru, R.G. Trends and actual issues concerning sustainable regional development in Romania, study case: The north east region of development. Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2013, 13, 27–30. [Google Scholar]
  83. Sandu, D. Social Disparities in the Regional Development and Policies of Romania. Int. Rev. Soc. Res. 2011, 1, 1–30. [Google Scholar] [CrossRef] [Green Version]
  84. Nițescu, A. Aspects of rural development in Romania. Annals of the University of Petroşani. Economics 2014, 14, 251–258. [Google Scholar]
  85. Sima, E. Sustainable rural development through tourism activities in Romania. Agric. Econ. Rural Dev. New Ser. 2018, 15, 219–224. [Google Scholar]
  86. Ignat, R.; Stoian, M.; Rosca, V. Socio-economic aspects of rural Romania. Emerg. Mark. Queries Financ. Bus. 2015, 15, 1331–1338. [Google Scholar] [CrossRef] [Green Version]
  87. Rusu, A.; Crunteanu, M.E. Leader—The social development of the rural area in Romania. Sci. Pap. Ser. Manag. Econ. Eng. Agric. Rural Dev. 2021, 21, 389–694. [Google Scholar]
  88. Panagoret, I.; Panagoret, D. Influence factors on agrifood and rural development policies in Romania. 2nd central & eastern european lumen international conference—Multidimensional education & professional development. Ethical Values 2017, 27, 529–536. [Google Scholar]
  89. Razvanta, F. The role of European funds in developing and sustaining rural entrepreneurship in Romania. In Proceedings of the International Conference on Business Excellence, Bucharest, Romania, 11–12 June 2020; Volume 14, pp. 134–148. [Google Scholar]
  90. Popescu, D.L. Rural Population in Romania. Development and Tendencies (2000–2010). In Proceedings of the International Economic Conference of Sibiu 2013 Post Crisis Economy: Challenges and Opportunities, IECS, Sibiu, Romania, 17–18 May 2013; Volume 4, pp. 120–127. [Google Scholar]
  91. Tache, I. Industrialization versus Rural Traditionalism in Inter-War Romania: A Reappraisal from the Globalization Perspective. Ind. Revolut. Glob. Post-Glob. Perspect. 2009, I, 338–344. [Google Scholar]
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Figure 1. Interdependence of internal and external factors on localities. Source: Canva processing.
Figure 1. Interdependence of internal and external factors on localities. Source: Canva processing.
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Figure 2. Relevant aspects concerning the focus of the study on these regions. Source: data processing INS through the Canva program.
Figure 2. Relevant aspects concerning the focus of the study on these regions. Source: data processing INS through the Canva program.
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Figure 3. Territorial distribution of the analyzed localities. Source: geographical distribution using the MapChart application.
Figure 3. Territorial distribution of the analyzed localities. Source: geographical distribution using the MapChart application.
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Figure 4. The relationship established between the variables through the Vensim simulation program. Source: data processing from the local authorities.
Figure 4. The relationship established between the variables through the Vensim simulation program. Source: data processing from the local authorities.
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Figure 5. The result of the simulation regarding the evolution of the population in Dragalina over a period of 10 years. Source: data processing from the local authorities.
Figure 5. The result of the simulation regarding the evolution of the population in Dragalina over a period of 10 years. Source: data processing from the local authorities.
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Figure 6. The result of the simulation regarding the evolution of the population in Nicolae Balcescu for a period of 10 years. Source: data processing from the local authorities.
Figure 6. The result of the simulation regarding the evolution of the population in Nicolae Balcescu for a period of 10 years. Source: data processing from the local authorities.
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Figure 7. The result of the simulation regarding the evolution of the population in Soldanu for a period of 10 years. Source: data processing from the local authorities.
Figure 7. The result of the simulation regarding the evolution of the population in Soldanu for a period of 10 years. Source: data processing from the local authorities.
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Figure 8. The result of the simulation regarding the evolution of the population in Sarulesti for a period of 10 years. Source: data processing from the local authorities.
Figure 8. The result of the simulation regarding the evolution of the population in Sarulesti for a period of 10 years. Source: data processing from the local authorities.
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Figure 9. The result of the simulation regarding the evolution of the population in Sanmihaiu for a period of 10 years. Source: data processing from the local authorities.
Figure 9. The result of the simulation regarding the evolution of the population in Sanmihaiu for a period of 10 years. Source: data processing from the local authorities.
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Figure 10. The result of the simulation regarding the evolution of the population in Valcani for a period of 10 years. Source: data processing from the local authorities.
Figure 10. The result of the simulation regarding the evolution of the population in Valcani for a period of 10 years. Source: data processing from the local authorities.
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Figure 11. The result of the simulation regarding the evolution of the population in Peciu Nou for a period of 10 years. Source: data processing from the local authorities.
Figure 11. The result of the simulation regarding the evolution of the population in Peciu Nou for a period of 10 years. Source: data processing from the local authorities.
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Figure 12. The result of the simulation regarding the evolution of the population in Fardea for a period of 10 years. Source: data processing from the local authorities.
Figure 12. The result of the simulation regarding the evolution of the population in Fardea for a period of 10 years. Source: data processing from the local authorities.
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Table
Table 1. The centralizing situation of the answers received from the local authorities.
Table 1. The centralizing situation of the answers received from the local authorities.
CountyNo. Localities to Which Requests Were SentNo. Localities That Responded to the RequestNo. Localities That Did Not RespondShare of Localities That Responded of the Total (%)
Calarasi50193138.0
Timis88355339.8
Total138548439.1
Source: centralized data.
Table
Table 2. Communes that were selected according to the criteria needed to determine mathematical models.
Table 2. Communes that were selected according to the criteria needed to determine mathematical models.
No. Crt.Locality from Calarasi CountyLocality from Timis County
1DragalinaSanmihaiu
2Nicolae BalcescuValcani
3SoldanuPeciu Nou
4SarulestiFardea
Source: centralized data.
Table
Table 3. Classification of the analyzed localities.
Table 3. Classification of the analyzed localities.
No. Crt.LocalitiesDistance to Nearest Urban Center (km)Local Resources
1Dragalina22 (Slobozia)Close to the A2 highway; agricultural land
2Nicolae Balcescu12,4 (Lehliu-Gara); 70 (Bucharest)Close to A2 highway; agricultural land; railway access
3Soldanu20 km (Oltenita); 47 (Bucharest)Near National Road 4 (access with Bulgaria); agricultural land; railway access; lake (recreation)
4Sarulesti21 (Fundulea); 26 (Lehliu-Gara)Near the A2 highway; agricultural land; lake (recreation)
5Sanmihaiu12 (Timisoara)Bega river, agricultural land
6Valcani20 (Sannicolau Mare)Agricultural land, close to the border with Hungary and Serbia
7Peciu Nou21 (Timisoara)Agricultural land, lake (recreation)
8Fardea90 (Deva); 88 (Timisoara)Agricultural land, hills, natural lake, cultural buildings
Source: data centered using Google Earth.
Table
Table 4. Analysis of the evolution of the main demographic indicators in Dragalina commune (CL) in the period 2015–2020.
Table 4. Analysis of the evolution of the main demographic indicators in Dragalina commune (CL) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Population (no inhabitants)877586298537856084278537−2.718578−0.5
Households (no.)3303335834653444351934574.6634240.9
Birth rate (no. of newborns)210010-1-
Mortality (no. deaths)847976756878−7.1477−1.5
No. persons receiving social assistance209208207172128110−47.37172−12.0
No. dispensaries/medical units4444440.0040.0
Source: data processing obtained from local authorities.
Table
Table 5. Analysis of the evolution of the main economic indicators in Dragalina commune (CL) in the period 2015–2020.
Table 5. Analysis of the evolution of the main economic indicators in Dragalina commune (CL) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Number of economic agents (companies, SRL, PFA, II, etc.), of which:21226431636840042098.1330.014.7
Agricultural profile17017318118519119715.9182.83.0
Tourist units (including agrotourism units)000000-0.0-
Source: data processing obtained from local authorities.
Table
Table 6. The main indicators, using linear regression, Dragalina commune.
Table 6. The main indicators, using linear regression, Dragalina commune.
Model 1RR-SquareStd. Error of the EstimateF-Change
0.986 0.97131.11722.707
Independent variableBStd. ErrorBetat
No. deaths7.3406.5740.3331.117
Households (no.)−0.8490.653−0.575−1.299
Number of economic agents−0.1640.400−0.114−0.410
Source: data processing from the mayor’s office through the SPSS statistical program.
Table
Table 7. Analysis of the evolution of the main demographic indicators in Nicolae Balcescu commune (CL) in the period 2015–2020.
Table 7. Analysis of the evolution of the main demographic indicators in Nicolae Balcescu commune (CL) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Population (no inhabitants)163116201598158415721569−3.801596−0.8
Households (no.)7607607717717817853.297710.6
Birth rate (no. of newborns)181520192212−33.3318−7.8
Mortality (no. deaths)29373431253520.69323.8
No. persons receiving social assistance413626161211−73.1724−23.1
No. dispensaries/medical units1111110.0010.0
Source: data processing obtained from local authorities.
Table
Table 8. Analysis of the evolution of the main economic indicators in Nicolae Balcescu commune (CL) in the period 2015–2020.
Table 8. Analysis of the evolution of the main economic indicators in Nicolae Balcescu commune (CL) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Number of economic agents (companies, SRL, PFA, II, etc.), of which:17212223272758.822.89.7
Agricultural profile9131414141455.613.09.2
Tourist units (including agritourism)000000---
Source: data processing obtained from local authorities.
Table
Table 9. The main indicators, using linear regression, Nicolae Balcescu commune.
Table 9. The main indicators, using linear regression, Nicolae Balcescu commune.
Model 2RR-SquareStd. Error of the EstimateF-Change
0.999 0.9991.541456.226
Independent variableBStd. ErrorBetat
Households (no.)−0.3640.213−0.148−1.709
Number of socially assisted persons1.5400.1810.7708.487
Number of economic agents−0.6250.578−0.094−1.082
Source: data processing from the local authorities through the SPSS statistical program.
Table
Table 10. Analysis of the evolution of the main demographic indicators in Soldanu commune (CL) in the period 2015–2020.
Table 10. Analysis of the evolution of the main demographic indicators in Soldanu commune (CL) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Population (no inhabitants)3280329033003300331033201.2233000.2
Households (no.)1432147014911520153115447.8214981.5
Birth rate (no. of newborns)000000---
Mortality (no. deaths)593847462842−28.8143−6.6
No. persons receiving social assistance19020322024024022920.532203.8
No. dispensaries/medical units1111110.0010.0
Source: data processing obtained from local authorities.
Table
Table 11. Analysis of the evolution of the main economic indicators in Soldanu commune (CL) in the period 2015–2020.
Table 11. Analysis of the evolution of the main economic indicators in Soldanu commune (CL) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Number of economic agents (companies, SRL, PFA, II, etc.), of which:80879311712013568.8105.311.0
Agricultural profile44446650.04.78.4
Tourist units (including agritourism)--- --- ---
Source: data processing obtained from local authorities.
Table
Table 12. The main indicators, using linear regression, Soldanu commune.
Table 12. The main indicators, using linear regression, Soldanu commune.
Model 3RR-SquareStd. Error of the EstimateF-Change
0.964 0.9299.1828.670
Independent variableBStd. ErrorBetat
Population (no.)−0.4321.612−0.281−0.268
Households (no.)0.8530.8621.6540.989
Number of socially assisted persons−0.4950.867−0.464−0.571
Source: data processing from the local authorities through the SPSS statistical program.
Table
Table 13. Analysis of the evolution of the main demographic indicators in Sarulesti commune (CL) in the period 2015–2020.
Table 13. Analysis of the evolution of the main demographic indicators in Sarulesti commune (CL) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Population (no inhabitants)323032053201321532103221−0.283214−0.1
Households (no.)1032102511401137113311289.3010991.8
Birth rate (no. of newborns)763245−28.575−6.5
Mortality (no. deaths)343530413733−2.9435−0.6
No. persons receiving social assistance191163149126108150−21.47148−4.7
No. dispensaries/medical units2222220.0020.0
Source: data processing obtained from local authorities.
Table
Table 14. Analysis of the evolution of the main economic indicators in Sarulesti commune (CL) in the period 2015–2020.
Table 14. Analysis of the evolution of the main economic indicators in Sarulesti commune (CL) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Number of economic agents (companies, SRL, PFA, II, etc.), of which:22232527272722.75.24.2
Agricultural profile777777-7.00.0
Tourist units (including agritourism)223444---
Source: data processing obtained from local authorities.
Table
Table 15. The main indicators, using linear regression, Sarulesti commune.
Table 15. The main indicators, using linear regression, Sarulesti commune.
Model 4RR-SquareStd. Error of the EstimateF-Change
0.993 0.9850.43044.205
Independent variableBStd. ErrorBetat
Households (no.)0.0020.0080.0550.283
No. persons receiving social assistance−0.0110.012−0.143−0.922
Tourist units (including agritourism)1.8600.5070.8203.665
Source: data processing from the local authorities through the SPSS statistical program.
Table
Table 16. Analysis of the evolution of the main demographic indicators in Sanmihaiu Roman (TM) commune in the period 2015–2020.
Table 16. Analysis of the evolution of the main demographic indicators in Sanmihaiu Roman (TM) commune in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Population (no inhabitants)8215845284529006891289909.4386711.8
Households (no.)24043450363236323944409770.42352711.3
Birth rate (no. of newborns)959211410511610712.63105-
Mortality (no. deaths)4937434154538.16461.6
No. persons receiving social assistance253531201918−28.0025−6.4
No. dispensaries/medical units4444440.0040.0
Source: data processing obtained from local authorities.
Table
Table 17. Analysis of the evolution of the main economic indicators in Sanmihaiu (TM) commune in the period 2015–2020.
Table 17. Analysis of the evolution of the main economic indicators in Sanmihaiu (TM) commune in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Number of economic agents (companies, SRL, PFA, II, etc.), of which:32343644547452755270.9486.811.3
Agricultural profile891010101025.09.54.6
Tourist units (including agritourism)111111---
Source: data processing obtained from local authorities.
Table
Table 18. The main indicators, using linear regression, Sanmihaiu Roman commune.
Table 18. The main indicators, using linear regression, Sanmihaiu Roman commune.
Model 5RR-SquareStd. Error of the EstimateF-Change
0.9530.908163.1246.548
Independent variableBStd. ErrorBetat
Households (no.)0.3080.3280.5430.941
No. persons receiving social assistance−25.35611.238−0.523−2.256
Economic agents with agricultural profile39.181237.3830.0970.165
Source: data processing from the local authorities through the SPSS statistical program.
Table
Table 19. Analysis of the evolution of the main demographic indicators in Valcani commune (TM) in the period 2015–2020.
Table 19. Analysis of the evolution of the main demographic indicators in Valcani commune (TM) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Population (no inhabitants)138513901380137413701372−0.941379−0.2
Households (no.)5345345345345345340.005340.0
Birth rate (no. of newborns)111496131318.18113.4
Mortality (no. deaths)18151612915−16.6714−3.6
No. persons receiving social assistance100000---
No. dispensaries/medical units111111---
Source: data processing obtained from local authorities.
Table
Table 20. Analysis of the evolution of the main economic indicators in Valcani commune (TM) in the period 2015–2020.
Table 20. Analysis of the evolution of the main economic indicators in Valcani commune (TM) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Number of economic agents (companies, SRL, PFA, II, etc.) of which:9101010101011.19.82.1
Agricultural profile45555525.04.84.6
Tourist units (including agritourism)000000---
Source: data processing obtained from local authorities.
Table
Table 21. The main indicators, using linear regression, Valcani commune.
Table 21. The main indicators, using linear regression, Valcani commune.
Model 6RR-SquareStd. Error of the EstimateF-Change
0.679 0.4627.4761.286
Independent variableBStd. ErrorBetat
Mortality (no. deaths)1.6751.2980.6771.291
Number of economic agents−0.09610.134−0.005−0.010
Source: data processing from the local authorities through the SPSS statistical program.
Table
Table 22. Analysis of the evolution of the main demographic indicators at the level of Peciu Nou (TM) commune in the period 2015–2020.
Table 22. Analysis of the evolution of the main demographic indicators at the level of Peciu Nou (TM) commune in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Population (no inhabitants)5412549055915591561557015.3455671.0
Households (no.)2040204020402147214922249.0221071.7
Birth rate (no. of newborns)37584942284521.62434.0
Mortality (no. deaths)4746454250482.13460.4
No. persons receiving social assistance131615131311−15.3814−3.3
No. dispensaries/medical units4444440.0040.0
Source: data processing obtained from local authorities.
Table
Table 23. Analysis of the evolution of the main economic indicators at the level of Peciu Nou (TM) commune in the period 2015–2020.
Table 23. Analysis of the evolution of the main economic indicators at the level of Peciu Nou (TM) commune in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Number of economic agents (companies, SRL, PFA, II, etc.) of which:4854904944975015258.2498.71.6
Agricultural profile182530344045150.032.020.1
Tourist units (including agritourism)111110−100.00.8-
Source: data processing obtained from local authorities.
Table
Table 24. The main indicators, using linear regression, Peciu Nou commune.
Table 24. The main indicators, using linear regression, Peciu Nou commune.
Model 7RR-SquareStd. Error of the EstimateF-Change
0.937 0.8787.7644.782
Independent variableBStd. ErrorBetat
Population (no inhabitants)0.1150.1540.8280.745
Households (no.)0.1280.1170.7141.095
Economic agents with agricultural profile (no.)−0.7852.092−0.551−0.375
Source: data processing from the local authorities through the SPSS statistical program.
Table
Table 25. Analysis of the evolution of the main demographic indicators in Fardea commune (TM) in the period 2015–2020.
Table 25. Analysis of the evolution of the main demographic indicators in Fardea commune (TM) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Population (no inhabitants)175017421712168016621647−5.891699−1.2
Households (no.)5435445465505515521.665480.3
Birth rate (no. of newborns)1210111097−41.6710−10.2
Mortality (no. deaths)21232334182519.05243.5
No. persons receiving social assistance212120−100.001-
No. dispensaries/medical units1111110.0010.0
Source: data processing obtained from local authorities.
Table
Table 26. Analysis of the evolution of the main economic indicators in Fardea commune (TM) in the period 2015–2020.
Table 26. Analysis of the evolution of the main economic indicators in Fardea commune (TM) in the period 2015–2020.
Specification201520162017201820192020%Avr.Annual Rhythm
Number of economic agents (companies, SRL, PFA, II, etc.), of which:551820−100.03.5-
Agricultural profile051210-1.5-
Tourist units (including agritourism)000300---
Source: data processing obtained from local authorities.
Table
Table 27. The main indicators, using linear regression, Fardea commune.
Table 27. The main indicators, using linear regression, Fardea commune.
Model 8RR-SquareStd. Error of the EstimateF-Change
0.995 0.9905.520147.056
Independent variableBStd. ErrorBetat
Households (no.)−10.5851.152−0.953−9.189
No. of newborns1.2492.5610.0510.488
Source: data processing from the local authorities through the SPSS statistical program.
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Iancu, T.; Petre, I.L.; Tudor, V.C.; Micu, M.M.; Ursu, A.; Teodorescu, F.-R.; Dumitru, E.A. A Difficult Pattern to Change in Romania, the Perspective of Socio-Economic Development. Sustainability 2022, 14, 2350. https://doi.org/10.3390/su14042350

AMA Style

Iancu T, Petre IL, Tudor VC, Micu MM, Ursu A, Teodorescu F-R, Dumitru EA. A Difficult Pattern to Change in Romania, the Perspective of Socio-Economic Development. Sustainability. 2022; 14(4):2350. https://doi.org/10.3390/su14042350

Chicago/Turabian Style

Iancu, Tiberiu, Ionuț Laurențiu Petre, Valentina Constanta Tudor, Marius Mihai Micu, Ana Ursu, Florina-Ruxandra Teodorescu, and Eduard Alexandru Dumitru. 2022. "A Difficult Pattern to Change in Romania, the Perspective of Socio-Economic Development" Sustainability 14, no. 4: 2350. https://doi.org/10.3390/su14042350

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