A STUDY ON INCOME DISTRIBUTION AND SOCIO-ECONOMIC CON- DITIONS OF MGNREGA HOUSEHOLDS

The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) 2005 is one of the foremost social security programmes in India. It guarantees minimumwage, reduces poverty and checks large scale migration in rural India. It has reduced rural hunger. After implementation of MGNREGA, the PlanningCommission estimated that thepoverty amongScheduledCastes (SCs) in rural areas fell 22 percentage pointsfrom 53.5 per cent in 2004-05 to 31.5 per cent in 2011-12. For that reason, the study focuses on income distribution and the socio-economic conditions of MGNREGAworkers and their households in Dindigul district of Tamil Nadu state. The sample size of this research work is 345 MGNREGA Scheduled Castes (SCs) workers. The study found that there is a signi icant level of association existing between the annual income of MGNREGA workers/households and their socio-economic conditions, such as the participants’ gender, age, community and occupation, type of family, size of family, number of employees and migrant workers of the family in the study area. At the same time this study found that there is no signi icant level association existing between annual income and socio-economic conditions such as education, type of houses, and marital status. Hence, the MGNREGA is one of the major factors in determining the income level and also the socio-economic conditions of the of scheduled castes workers in the study area.

INTRODUCTION
The Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) is one of the foremost social security programmes in India. It guarantees minimum wage, reduction of poverty, and checks migration of population from rural areas to urban areas and reducing rural hunger. The National Rural Employment Guarantee Act (NREGA) was an Indian job guarantee scheme, enacted by the legislature of India on 25 th August, 2005 and it had come into force and implemented on 2 nd February, 2006 in the Anantapur district, Andhra Pradesh. The act was renamed as Mahatma Gandhi National Rural Employment Guarantee Act (MGNREGA) on 2 nd October 2009. It was implemented in all the states of India in three different phases. Phase-I was introduced in 200 of the most backward districts of the country out of the total districts of 615, and again with an additional to 130 districts in phase-II 2007 -2008. The Act was noti ied in the remaining 285 rural districts of India from April 1, 2008 in phase-III "Ministry Of Law And Justice Of India " (2005).
The Act guarantees to one who works minimum hundred days out of 365 days per year and he/she must give some requisition within ifteen days. An unemployment allowance should be provided to the inability workers, one who is not able to work for 15 days from the date, the Act provided some compensation Mukherjee (2016).
Initially, it ensured that the legal right to work for a hundred days for poor people, who was willing to work for a minimum wage rate, especially in rural areas, that would turn to reduce the low of rural to urban migration. Its addition to, other important objective of the Act is to strengthened the Panchayat Raj Institution (PRIs) The major dimensions of the impact of MGNREGA could be summarized by the following activities such as, increased employment opportunities, major participation by poor SC and ST population, economic empowerment of poor women, relief from rural village from moneylenders, disengagement from hazardous work, rural asset formation, improvement in rural environment and sanitation, creates SHG by MGNREGA, reducing the rural partiality, hunger, unemployment and migration.
The Act creates some awareness to the people about the Panchayat Raj Institution and government activities, increasing purchasing power and agricultural production, savings, increase in income, expenditure and strengthening the PRI.
The average days of work allocated to the ST job-card householders were less than for the SC communities, but the former group had less easy access to the registration of job cards and spent more time getting the jobs than other social groups. Only 36 per cent of the tribal respondents were aware of the provision for a minimum number of days of employment, a lower percentage than from the SC and general communities. Similarly, only 42 percent of tribal respondents were aware of the provision for a minimum wage rate in the scheme; this was a larger percentage than their SC counterparts but lagged far behind those from the OBC and general communities Mishra et al. (2010). In addition, an interesting and encouraging observation was the scheme to reduce the migration of people from rural to urban areas Devi et al. (2011). The Act has a positive contribution to the generation of employment, social protection for women and eradicating the poverty in rural areas Mary and M (2014).

STATEMENT OF THE PROBLEM
The MGNREGA is the main reason to economic changes in rural areas. The wage rates have increased in agriculture and allied activities in rural regions. It creates a shortage of labourers in agriculture and allied activities. There is no wage rate difference existing between the wages of MGNREGA and females' wage of agriculture at present. Hence women's participation is very high, especially SC women. The Act ensures a minimum wage to the workers. The minimum wage will not create high productivity and changes in rural areas. Many poverties alleviation programmes have not achieved the target because of, lack of management, expensive administration, corruption, political intervention and so on. The MGNREGA Act also has the same problems. The Act has not considered the classi ications of various factors such as economic, occupation, geographical location, socio-culture and rural divisions.
In this study area, researcher identi ied many problems while collecting data from the workers such as no work side facilities, wage determination problem, degradation of grazing land, create laziness among rural youths, low work productivity (may be "Not worked"), lack of work tools, lack of awareness and administration problems, political intervention, partiality, corruption, and the participants are the pregnant women, children and old aged person.

OBJECTIVE
The basic objective of the study is to analyze the income distribution and social economic conditions of MGNREGA Households in Dindigul district of Tamil Nadu.

SIGNIFICANCE OF THE STUDY
In India, Scheduled Castes (SCs) people are mainly depending upon the agriculture and agricultural related activities. There are no alternative employment opportunities available for most of the SCs population other than agriculture operations. The Planning Commission in the year 2004-05 had estimated that more than half the SCs (about 53.5 percent) in rural areas were living below the poverty line. After implementation of MGNREGA, the poverty among SCs in rural areas fell 22 percentage points-from 53.5 per cent in 2004-05 to 31.5 per cent in 2011-12 Jha (2014. In this situation the Act was introduced (Phase-I) in 200 most backward districts of the country for poor Below Poverty Line -(BPL) people. As a result, 62 per cent of the new employment by MGNREGA in Phase I and II are utilized by the SC and ST communities, since majority of them are very poor as high. Only six districts were covering in Phase I implementation in Tamil Nadu State such as the districts are Cuddalore, Dindigul, Nagapattinam, Sivagangai, Tiruvannamalai, Viluppuram. The Dindigul district was selected on the basis of most economic backward district index of Tamil Nadu.
The Act was implemented without any consideration of rural -regional differences. Therefore, the study was done purposefully and selected different rural regions, such as city surrounded rural regions, primitive rural region/hilly regions and backward rural regions.

LIMITATIONS OF THE STUDY
The study has covered micro region of Dindigul district only. The researcher interacted only with Scheduled Castes people, not with the people of other communities. Troubles also were faced in getting relevant data from the villages.

METHODS AND MATERIALS
The study has been carried out in the area of Dindigul district of Tamil Nadu state during the period of 2012-2016. The ield survey has been carried out from May 2014 to June 2015. Out of 14 blocks of Dindigul district, only three blocks were selected purposefully, such as city surrounded rural regions of Dindigul block, primitive rural region/hilly regions of Kodaikanal block and backward rural regions of Batlagundu block. The sample size of the study is 345. They were selected from MGNREGA workers of Scheduled castes communities through proportionate random sampling technique at 10 per cent level, which constituted 130 (37.70 per cent), 90 (26.10 per cent) and 125 (36.20 per cent) samples from Dindigul block, Kodaikanal block and Batlagundu block respectively. Three village Panchayats were selected from each block. The major bene iciaries were scheduled castes people in the nine village Panchayats.

ANALYSIS THE INCOME DISTRIBUTION AND SOCIO-ECONOMIC CONDITIONS (RESPONDENTS/HOUSEHOLDS)
The annual income of MGNREGA workers and their family represents with the variables of gender, age, education, marital status, community, occupation, types of houses, types of family, size of family, and the number of employees/income earners and migrant workers of the family. Karl Pearson Chi-square test was used in the income distribution analysis on socio-economic conditions. Pearson Chi-Square Test Chi-Square, symbolically written as x 2 (Pronounced as Ki-square), is a statistical measure used in the context of sampling analysis for comparing a variance to a theoretical variance Kothari (2004). As a non-parametric test, it "could be used to determine if categorical data show dependency or the two classi ications are independent. It could also be used to make comparisons between theoretical populations and actual data when categories are used". Neil and R (1978) X International Journal of Research -GRANTHAALAYAH O ij -Observed frequency of the cell in ith row and jth column. E ij -Expected frequency of the cell in ith row and jth column.
RT -The row total is row containing the cell. CT -The column total is column containing the cell. N -The total number of observations. The table value is calculated from V=(r-1) (c-1). Where, r is row and c are column.

ASSOCIATION BETWEEN INCOME AND GENDER
Gender is an important factor in family and society. The Act is providing equal wages to their workers without any discrimination. Under the Act of wage payments, gender disparity is totally removed Veena (2015). The Table 1 revealed that, about 65.8 per cent of Males earnings were above Rs. 36000 than females' earnings of below Rs.36000 (about 54.9 per cent) annually from various works, not only the programme. Male were dominated in getting annual income than female, in spite of female are widely rolling in rural making of India such as backbone of agricultural activities, home making, construction and micro-small enterprises of rural. Wage discrimination is no more in MGNREGA. Female participants (about 68.7 percent) were higher than Male in the study area.

ASSOCIATION BETWEEN INCOME AND AGE
The age limit for the participants of MGNREGA workers is 18 years and above for female, and 21 years for Male. As a rule, age of below 21 years of respondents is not appearing. The youngest age group of respondents' is contributing to the risk bearing of MGNREGA works and they are called as skilled labourers. The Table 2 , revealed that the age group of 31-40 years was a majority in annual earnings (Rs. 36001-48000, 42.9 per cent) than other majority earner's age groups of below 31 (Rs. Below 24001, 40.0 per cent), 41-50 (Rs. 36001-48000, 33.8 per cent) and above 50 (Rs. 36001-48000, 32.9 per cent) respectively. They have earned income from MGNREGA and other employment sources. The majority of the participants were belonged the age group of 31-40 that is 28.4 per cent of the respondents.

ASSOCIATION BETWEEN INCOME AND EDUCATIONAL STATUS
In general, literate people have more information about the MGNREGA than illiterate people. This awareness includes the details on the basis of work status, working hours, inancial and physical status of the MGNREGA. The Table 3 revealed that, the literate (31.5 per cent) and illiterate (32.53per cent) peoples were leading annual income group of Rs. 36001-48000. The difference between literate and illiterate participants were existed only 3.2 per cent in MGN-REGA.

ASSOCIATION BETWEEN INCOME AND MARITAL STATUS
The study doesn't job cardholders based. It is Easy to determine that cardholders are married. Normally MGNREGA participants are not fully job card. The card may be wife or husband or father or mother. Cardholders are participants, but not necessary as participants are cardholders. The Table 4 revealed that, the married, others (widow or widower) and unmarried participants are getting high annual income of above Rs. 36000 (52.6 per cent, 50.0 per cent and 37.4 per cent) respectively. Married participants got more income than other two marital statuses of unmarried and others. Married participants were majority in MGNREGA (82.0 per cent).

ASSOCIATION BETWEEN INCOME AND COMMUNITY
The Scheduled Caste Arunthathiyar (SCA) means that the castes, like Arunthathiyar, Chakkiliyan, Madari, Madiga, Pagadai, Thoti  The Table 5 revealed that leading annual income groups were Rs. 36001-48000 (35.0 per cent) of SCG and Above Rs. 48000 (28.7 per cent) of SCA respectively. SCG has more income than SCA from local employment opportunities. SCG participants were higher than SCA in the study area (64.6 per cent).

ASSOCIATION BETWEEN INCOME AND OCCUPATIONS
Before two decades back most of the people were in agriculture sector and allied actives in rural India. Nowadays rural-urban connectivity, infrastructure facilities, technologies have improved the rural society with modern India. They are not depending on agriculture alone. In this situation the study analyses their income distribution from various occupations of the rural. The Table 6 revealed that agricultural labourers, non-agriculture laboures and Farmers were dominant in the income group of Rs. 36001-48000/-, 40.9 per cent, 40.7 per cent and 39.0 per cent respectively. While, Self-employers/Housewives were dominant income group of below Rs. 36001(80.9 per cent) than other occupational groups. Daily agricultural laborers (Agri-cooli) were the major participants in the study area (33.3 per cent).

ASSOCIATION BETWEEN ANNUAL INCOME AND TYPE OF HOUSE
Before introduction of the MGNREGA too many of Thatched and Tiled houses were in rural India than concrete houses. At present, more concrete houses are there than Thatched and tiled houses due to bank loan, Central and State governments housing schemes, NGO and Tamil Nadu Adi Dravidar Housing and Development Corporation (TAHDCO). Hence their housing types were classi ied with their household income. The Table 7 reveals that, annual earns were above Rs. 60000 from each type of housing of respondents' households, such as Thatched or Tiled (35.0 per cent), Concrete (35.4 per cent) and other (mixed) type house (44.2 per cent). Mixing or other type houses (44.2 per cent) of households were majority in above that income group than the Thatched or Tiled and Concrete households. Thatched/Tiled houses of the respondents were major participants in MGNREGA (49.5 per cent).

ASSOCIATION BETWEEN ANNUAL INCOME AND TYPES OF FAMILY
Family is an important social institution. Types of family are classi ied into two categories, nuclear family and joint family.
The Table 8 indicates that, joint families were leading in getting annual income than nuclear families. Both type of families was belonged the leading income group of above Rs.60000 (59.4 per cent) and below Rs. 48000 (40.9 per cent) respectively. Nuclear families (82.9 per cent) participation was higher than joint families (17.1) in the study area.

ASSOCIATION BETWEEN ANNUAL INCOME AND SIZE OF FAMILY
Annual household income and size of family described the statement of 'more members of the family as more income'. The Table 9 indicates that family size of 1-2, 3-4 and above 4 were belonged the maximum annual household income below Rs. 36001(42.2 per cent), above Rs.48000 (57.5 per cent) and above Rs. 48000 (84.1 per cent) respectively. Three to four members (have) families were major participants in the Act (55.9 per cent).

ASSOCIATION BETWEEN ANNUAL INCOME AND EMPLOYEES OF THEIR FAMILY
The government and private sector employees are mostly retiring between the ages from 58 to 65. Agricultural or allied laboures/farmers and illiterate peoples they have no retirement in their entire life of rural society. From the Table 10 , the number of employees of the respondent families was classi ied as 1-2 and above two, and they were belonged the maximum annual household income group of below Rs. 48001 (53.0 per cent) and above Rs.60000 (77.0 per cent) respectively. Above two employees have a family getting more income than other

ASSOCIATION BETWEEN ANNUAL INCOME AND MIGRANT WORKERS OF THEIR FAMILY
More income expectations, modern life, more expensive, low employment situation, poverty, unavailability of basic facilities and natural disorder are the main reasons for human migration. Meanwhile, the study deals only with migrant workers of respondent family (family members' migration for job purpose only). The Table 11 shows that, migrant and non-migrant workers of the respondents' families were belonged in the annual household income group of above Rs. 60000 (51.8 per cent and non 29.6 per cent). It is illustrated that migrant workers families were more annual household income than non-migrant workers families. Nonmigrant families were major participants in MGNREGA (67.5 per cent).

CHI-SQUARE TEST RESULTS FOR INDENTIFY THE ASSOCIATION BETWEEN
Hypothesis H 0 -There is no signi icant level of association between annual income of respondents and their socio-economic conditions H 1 -There is a signi icant level of association existing between annual income of respondents and their socio-economic conditions

ASSOCIATION BETWEEN INCOME AND GENDER
In the case of Table 12 , null hypothesis (H 0 ) is rejected and alternative hypothesis (H 1 ) is accepted because of x 2 (15.1303) greater than the table (7.815) value at 5 per cent level (p-.001709) of signi icance. As a result, there is some signi icant association between respondents' annual income and their gender. MGNREGA ensures equal wage to men and women, but agriculture and allied employments do not give equal wage to them. Gender wise income variation has been existed in the study area.

ASSOCIATION BETWEEN INCOME AND AGE
As a result, from table-12, the calculated Chi-square (x 2 =22.439) value is greater than the table (16.919) value at 5 per cent level. The p-value is .007587. The result is signi icant at p< .05. Therefore, H 0 is rejected and the H 1 is accepted. Hence this study found that there is some signi icant association between respondents' annual income and their age groups. Age has been important to determine the respondent's annual income. Middle age group (31-40) participants' have higher income than others.

ASSOCIATION BETWEEN INCOME AND EDUCATIONAL STATUS
The calculated (Table-12) Chi-square (x 2 =2.389) value is less than the table (7.815) value at 5 per cent level. The p-value is .49569. The result is not signi icant at p< .05. Therefore, H 0 is accepted and H 1 is rejected. Hence this study found that there is no signi icant association between respondents' annual income and socio-economic factor of their education. Educational status does not in luence income earning in the study area. Educated and uneducated respondents were getting same wage.

ASSOCIATION BETWEEN INCOME AND MARITAL STATUS
12 revealed that the calculated Chi-square (x 2 =1.7902) value is less than the table (9.488) value at 5 per cent level. The p-value is .774281. The result is not signi icant at p< .05. Therefore, null hypothesis (H 0 ) is accepted and alternative hypothesis (H 1 ) is rejected. Hence this study found that there is no signi icant association between respondents' annual income and their marital status. Respondents' annual income does not depend upon their marital status of the study area.

ASSOCIATION BETWEEN INCOME AND COMMUNITY
In table-12, the calculated Chi-square (x 2 =10.0575) value is greater than the table (7.815) value at 5 per cent level. The p-value is .018084. The result is signi icant at p< .05. Therefore, null hypothesis (H 0 ) is rejected and the alternative hypothesis (H 1 ) is accepted. Hence this study inds that there is some signi icant association between respondents' Annual Income and their community. The interrelationship exists between annual income of respondents' and their community. SCG is economically wealthy society than SCA. SCA gets an annual income of above Rs. 48000, its only 29 percent compares to SCG. SCG has Rs. 36000-48000, but it's 35 per cent.

ASSOCIATION BETWEEN INCOME AND OCCUPATIONS
The

ASSOCIATION BETWEEN ANNUAL INCOME AND TYPE OF HOUSES
12 shows that, the calculated Chi-square (x 2 =8.2257) value is less than the table (12.592 value at 5 per cent level. The p-value is .22203. The result is not signi icant at p< .05. Therefore, null hypothesis is accepted and the alternative hypothesis is rejected. Hence this study found that there is no signi icant level of association between annual household income and type of house. Therefore, there is no relationship between them.

ASSOCIATION BETWEEN ANNUAL INCOME AND TYPES OF FAMILY
The is signi icant at p< .05. Therefore, null hypothesis is rejected and the alternative hypothesis is accepted. Hence this study found that there is a signi icant level of association existing between annual household income and their families. Joint family was getting higher annual income than nuclear family. Therefore, annual household income was depending upon type of family system.

ASSOCIATION BETWEEN ANNUAL INCOME AND SIZE OF FAMILY
In table-12, the calculated Chi-square (x 2 =46.9377) value is greater than the table (9.488) value at 5 per cent level. The p-value is < 0.00001. The result is signi icant at p< .05. Therefore, null hypothesis is rejected and the alternative hypothesis is accepted. Hence this study found that there is a signi icant level of association existing between annual households' income and their size of family. Therefore, annual household income was determined by the size of family.

ASSOCIATION BETWEEN ANNUAL INCOME AND EMPLOYEES OF THEIR FAMILY
The table-12 shows that the calculated Chi-square (x 2 =124.2202) value is greater than the table (5.991) value at 5 per cent level. The p-value is < 0.00001. The result is signi icant at p< .05. Therefore, null hypothesis is rejected and the alternative hypothesis is accepted. Hence this study found that there is a signi icant level of association existing between annual household income and number of employees in their families. Therefore, more incomes were from more employees of the family.

ASSOCIATION BETWEEN ANNUAL INCOME AND MIGRANT WORKERS OF THEIR FAMILY
In table-12, the calculated Chi-square (x 2 =16.6295) value is greater than the table (9.488) value at 5 per cent level. The p-value is .002281. The result is signi icant at p< .05. Therefore, null hypothesis is rejected and the alternative hypothesis is accepted. Hence this study found that there is any signi icant association between annual household income and their family member's migration. The past study Kareemulla et al. (2013) depicted that the income from migration also has decreased during MGNREGS period compared to the pre-MGNREGS period. Therefore, MGNREGA decreased the migration in rural India; while the present study illustrated those migrant workers, families were more annual household income than non-migrant workers families.

CONCLUSION
This study found that females, daily wage earners, married, youngest, illiterate, SCG category, thatched/tiled houses, nuclear families and non-migrant workers were the major participants in MGNREGA programe. Joint family was getting higher annual income than nuclear family. Size of family determines increase or decrease of the annual household income. As a result, more incomes were from more employees of the family. The study concluded that there is a signi icant level association existing between annual income of MGNREGA workers/households and their socio-economic conditions, such as the participants' gender, age, community and occupation, type of family, size of family, number of employees and migrant workers of the family in the study area. While, there is no signi icant level association existing between annual income and socio-economic conditions with respect to education, type of houses, and marital status. Hence, the MGNREGA is one of the major factors in determining the income level and also the socio-economic conditions of the of scheduled castes workers in the study area.

SUGGESTIONS
If one analyses the economic history of poverty reduction in India right from First Five Year Plan to end of the Twelfth Five Year Plan one could understand that the answer for this doubt seems to be in that direction only. The Director Sathyajith Ray one who took movie about poverty in India, was rewarded with best Directors Award, the Economist Amartiya Sen one who wrote intensively about poverty was rewarded with Nobel Prize, Muhammd Yunus one who introduced the concept of Micro-inance/Self Help Groups among poor Women in Bangladesh was rewarded with Nobel Prize, Mother Teresa one who dedicated her life for the poor was rewarded with Nobel Prize, the ilm "Salaam Bombay" rewarded with a lot of awards in India and abroad and the list continues till now. All those who wrote intensively about poverty in India, those who took movies about poverty in India, those who acted in movies as poor person, it seems that, became very rich in India and also in abroad. But the people who are living below the poverty line still living under poverty only. Only the de initions changed from the amount of calories needed in a day to wage per day, then it ended with multi-dimensional approach to poverty. The government or the government appointed committees like Y K Alagh Committee, Lakdawala Formula, Suresh Tendulkar Committee, C. Rangarajan Committee though varies from one another with respect to number of people who live below the poverty line in India, have one common point that is the per centage of poverty reduction is not as expected level, whatever may be their approaches in de ining poverty. The socio-economic Census 2011 has stated out of 1000 million people, who live in rural India, ifty per cent of them have less than ive cents of land. They are simply daily wage workers, agri cooli workers or casual labourers in farm sector. Unless these people get an opportunity, either directly or indirectly, of what is going on in the State Assemblies of different states and Parliament of India, no policies, programmes and schemes will help them to improve their standard of live. So governments both central and states should go for digitalisation of the rural areas immediately. Employment generation schemes, income generation schemes, poverty eradication programmes in rural areas should be very well connected and operated only through their bank accounts. Digitalisation is the only way to get rid of corruption at all levels. De initely the targeted group will get bene it out of digitalisation. (1). Huge investment on infrastructural facilities like Bullet train, eight-line highways, port development, more airports, constructing large dams etc.
(2). More liberalisation of FDI with respect to retail sector, export and import tariff etc. (3). More investment to boost the agricultural sector and rural infrastructural development. Starting food processing industries with air-conditioned warehousing facilities and air-conditioned containers facilities in village level at least block level in the beginning are welcome one. Repair and maintenance of existing ponds, lakes and canals for water harvesting and constructing more check dams to store the water should be considered at war footing. (4). More allotment to MSME under start-up programme, make in India programme and Mudra scheme. (5). Atleast consolidation of Fiscal de icit at current level is a well come effort. If the above items are considered seriously and incorporated in the budgets in the coming years, we hope that it will solve the basic and fundamental burning problems like unemployment, poverty, rural development and social inequality within ive years Arunachalam (2021).


Legal Aspects Of Cooperation Of The Republic Of Uzbekistan Within The Islamic Development Bank

This article describes the role of the Islamic Development Bank in today’s international community and the basic aims of this organization. The article also discusses the problems of cooperation between Uzbekistan and the IDB, and also proposes legal solutions for a wider use of the investment opportunities of this financial institution. This is evidenced by a number of laws adopted in Kazakhstan on Islamic finance among the CIS countries. The article examines the research of theorists and practitioners on the benefits of using IDB financial resources. The practical results of the initiatives of the President of Uzbekistan Sh. Mirziyoyev in the framework of cooperation between Uzbekistan and the IDB are presented. In the conclusion part of the article, the author offers proposals for cooperation in the field of science and technology in the framework of IDB programs.

INTRODUCTION
The Islamic Development Bank (hereinafter referred to as IDB) is one of the largest intergovernmental organizations, the significance of which is growing currently. The IDB has 57 member states and the organization supports the development of these member countries. According to the IDB Charter, any member of the Organization of Islamic The American Journal of Political Science Law and Criminology (ISSN -2693-0803) Published: February 28, 2021 | Pages: 131-138 Doi: https://doi.org/10.37547/tajpslc/Volume03Issue02-19 - IMPACT FACTOR 2021: 5. 952 Cooperation can become an Islamic Development Bank member after paying the minimum membership fee.
The basic directions of the Islamic Development Bank's activities are strengthening cooperation between Islamic countries, fighting poverty, raising the level of education, supporting science and technology, as well as investing in the infrastructure of the banking and financial sector.
Russian scholar E.Sh. Sultanov describes the Islamic Development Bank in his research, noting that its member states are the largest development banks in the developing world [1]. In fact, the Islamic Development Bank, according to E.Sh. Sultanov, is the largest development bank, which is one of the basic reasons why we consider the largest donor countries in the Persian Gulf with enormous financial strength.
According to another study by R. Beckin, the Russian state is interested in the inflow of investments from the Muslim world, especially from the Persian Gulf countries, and in this regard should be a member of the OIC within the Islamic Development Bank for closer economic integration with the Muslim world. said that there will be opportunities for soft loans for the implementation of urgent projects [2].
We also agree with R. Beckin on the significance of integrating the Gulf countries into the IDB to increase investment flows to the Gulf countries.
The ideas put forward by R. Beckin are confirmed by the example of Kazakhstan. Currently, Kazakhstan is making important progress in cooperation with the countries of Central Asia within the IDB.

MAIN PART
The Republic of Uzbekistan cooperates as a full member of the IDB. As for the cooperation of Uzbekistan with the IDB, Uzbekistan joined the international organization in 2003. Since joining the IDB, Uzbekistan has been actively cooperating with the IDB and within it. Currently, the number of shares of the IDB of the Republic of Uzbekistan is 1344 (0.03%) formed.
The basic areas of activity of the IDB in Uzbekistan are financing of socially significant projects in the main infrastructural and strategic sectors of the economy. It should be noted that the legal framework of international relations with the IDB is developing bilaterally. There is no shortage of more efficient use of the financial resources of this organization.
According to the chairman of the IDB office in Uzbekistan Kh. Khasanov, if laws on Islamic finance are adopted in Uzbekistan, 10 billion soums will be allocated annually. It was confirmed that there is an opportunity to attract investments up to 1 billion US dollars and that there are companies willing to invest in the banking sector and the private sector [5].
In accordance with these words, Kh. Khasanov met with the scholars of the Baltic Law University O.A. Serov, Sh.A. Niyatbekov's opinion can also be noted. According to him, Islam noted the implementation of the main principles of banking in Russian legislation, thereby attracting financial resources of the Arab countries.
Also, according to the economic research of Yu.D Magomedova, "the goal of the Islamic economic model is to find an alternative approach to solving the issues of the financial sector in modern conditions" [7].
We also agree with the above points, and believe that the Islamic financial principles of the IDB should be applied and strengthened as an alternative solution to many modern economic problems in the context of Uzbekistan. At the same time, we note that the principles of Islamic banking can be reflected in the legislation, and thus the integration into the Roman-German legal system will not affect the secular views of the people, and only strengthen cooperation within the organization and develop investment flows. Confirming the point of view expressed by R. Beckin, we believe that the strengthening of legislation with the aim of wider application of Islamic financial principles is a legal mechanism for increasing investment flows from the Persian Gulf countries.
We currently propose active application of Islamic financial principles such as Murobakha and Ijar in Uzbekistan. We believe that there are a number of opportunities and benefits to applying these principles.
According to Beckin, "One of the fundamental differences between Murabakha and traditional interest-bearing loans is that an Islamic bank does not lend money to a client in the same way as a traditional bank, but buys a specific product for him. In other words, the Murabakha mechanism is not a loan, but a specific product or service however, the bank bears a greater risk in financing the purchase of a product or service " [9].

RESULTS AND DISCUSSIONS
In Uzbekistan alone, projects worth $ 96 million have been funded over the past three years under the Islamic financial principle of Murobakh. Banks such as Turonbank, Uzpromstroybank and Kapitalbank participated in it as partners.
According to H. Khasanov, in Uzbekistan "more than 10 banks have been provided with financing lines on the basis of rent, lease" [10].
Currently, the fact that traditional banks are opening branches of the IDB also indicates the potential of this banking system. Islamic financial centers have been established in the United Kingdom, Luxembourg, France, Germany, Belgium, the United States, and other countries [11]. Many international companies tailor their private financial resources to their needs by attracting investors from the Gulf countries. As developed countries use the above experience as an investment interest, we propose to open IDB branches in traditional banks in Uzbekistan and make greater use of the opportunities of Islamic financial principles. At the same time, it offers alternative services to meet the financial needs of individuals and legal entities, attracts free funds to participate in the country's economy increases the production and export potential of the private sector in the country through the introduction of Islamic financial services. We understand that fighting poverty will create a range of opportunities, including contributing to the implementation of the government program.
According to H. Khasanov, chairman of the IDB office in Uzbekistan, "An Islamic window is often created in countries where there is no Islamic financial system or legislation on Islamic finance [12]. This is because the Islamic window offers a limited number of services and products as a product of a traditional bank, based on the existing laws and legal framework of a particular country. So, acknowledging the views of H. Khasanov, an expert in this field, we believe that in the absence of legislation on Islamic finance in Based on the results of the above research, we believe that today it is beneficial to implement with the IDB not only cooperation within the organization, but also on the basis of bilateral cooperation, enshrined in law the basic principles of the bank. In this regard, the chairman of the IDB office in Uzbekistan H. Khasanov noted that the legally coordinated use of Islamic banking in Uzbekistan will ensure the attraction of free resources by the population, which will lead to the development of entrepreneurship and create new jobs.
Taking into account the current economic situation in Uzbekistan, we note the need for the formation and continuous improvement of the relevant regulatory framework for the development of investment cooperation with the IDB. Currently, despite the ongoing business activity in Uzbekistan and the need of the population of Uzbekistan for financial resources of Islamic banking, there is no development of the legal framework for Islamic finance.
At the same time, a number of measures are being taken to reduce poverty in Uzbekistan. One of the basic activities of the IDB is to strengthen cooperation between Islamic countries and fight poverty. At the same time, we consider it expedient to establish active cooperation between the IDB and the Ministry of Economic Development and Poverty Reduction of the Republic of Uzbekistan and strengthen it on an appropriate contractual basis.
As noted above, the contractual legal framework of Uzbekistan with the IDB has intensified since 2016. It should be noted that in 2018, Uzbekistan signed the first agreement on Islamic trade financing.
Speaking about the integration of countries into international organizations today, it should be noted that Uzbekistan's membership in the World Trade Organization (WTO) is also important. The IDB conducts seminars and consultations on WTO agreements, as well as trade policy courses for government officials of IDB member states. According to research conducted by the Russian scientist R. Beckin, the ITB assisted in resolving the technical issues of Kazakhstan's accession to the WTO [13]. Therefore, we believe that, its economic and investment cooperation with the IDB will play an important role in Uzbekistan's future membership in the WTO.
During the meeting of the President of Uzbekistan Sh. Mirziyoyev with the President of the IDB B. Hajar during his visit to Saudi Arabia, it was noted that the relations between Uzbekistan and the IDB are developing steadily, the parties cooperate in developing and implementing socio-economic projects. Islamic Development Bank allocates more than $ 1.4 billion for 21 projects for development of healthcare, education, irrigation and land reclamation, energy, road infrastructure and utilities.
In this regard, the IDB, in cooperation with the Government of Azerbaijan, has developed a special program for Central Asian countries. The IDB Group presented a regional program to support cooperation between Central Asian countries, promote trade, increase competitiveness and stimulate economic growth in line with the UN Sustainable Development Goals (SDGs). The goal of the program is not only to strengthen regional cooperation in the field of energy and transport corridors, trade, agricultural financing, but also to expand regional cooperation in reducing trade, transport and investment costs. The total cost of the program is 6 billion soums. In US dollars, it includes projects planned to be completed in 2016-2020.
It should be noted that in the period from 2009 to 2016, specific targeted work was carried out on the construction of housing, social and communal facilities in rural areas, about 70 thousand comfortable houses were built in 1,300 residential areas. The living conditions of more than 83.5 thousand rural families have improved. While the legal basis for the implementation of such projects has been formed, from 2016 to the present, the implementation of these projects has increased 2-3 times clear strategic road maps have been formed.
During the visit of the IDB President's Advisor for Science, Technology and Innovation Professor Hayat Suleiman Sindi to the Ministry of Innovation of Uzbekistan, negotiations were held on using the potential of the IDB in developing a concept of joint actions of the participating countries on agriculture. Also, the issue of establishing cooperation with the IDB in the framework of the project to place one of the six high-capacity computer centers in Uzbekistan and the creation of an International Islamic Center of Young Scientists on the basis of this center was raised. It was also noted that in order to glorify and popularize the rich heritage of Al-Khwarizmi, the organization of the International Olympiad of Young Mathematicians needs financial, technical and advisory support. The need to implement experimental-innovative, research projects in the field of alternative energy sources was also noted. It should be noted that the initiative of these projects was put forward by President Sh. Mirziyoyev at the 1st Summit on "Science and Technology" in 2017 in Kazakhstan [14].

CONCLUSION
According to the research, Uzbekistan was not one of the first Central Asian countries to join the IDB, but today it has established active cooperation. We can note that the legal framework of partnership has developed rapidly, especially since 2016. The development of Kazakhstan's cooperation with the IDB Bank can serve as an example among Central Asian countries. In today's era of globalization, as well as in the development of the digital economy, we believe that it is necessary to strengthen the legal framework and implement a number of technical cooperation with the IDB and the Gulf Arab states, ie its main donor countries. projects. In this regard, the IDB has a Technical Cooperation Program [15]. The program is based on an IDB grant for the transfer and exchange of skills, knowledge and know-how between member countries. Based on a tripartite system, this program includes three partners in each event; those. technically reasonable as the beneficiary and intermediary of the IDB. In our opinion, Uzbekistan is also interested in using this program.
It should be noted that cooperation on grant projects announced by the IDB in the field of education is not very developed. For more than 30 years, the Bank has been conducting research in various fields to finance the formation of more than 9,000 young people as professionals who serve the development of their countries. We believe that taking


Is It Possible to Tackle Youth Needs with Agricultural and Rural Development Policies?

: Rural youth are inﬂuenced by a wide range of uncertainties regarding their personal and professional development. Rural youth and in particular rural NEETs (Not in Employment, Education or Training) are especially vulnerable and face higher risks of labour market, social and economic exclusion. This paper aims to analyse the determinants of the dynamics of rural NEETs in three post-transitional countries (Bosnia and Herzegovina, North Macedonia and Serbia) compared to the EU-28 average and to Ireland as an example of an established EU member state with over 50% of its population living in rural areas that can act as a benchmark for effective policy implementation to address challenges of marginalized youth, during the 2009–2019 period. The dynamics of rural NEET status and the efﬁciency/adaptability of regional development policies are revealed through analysis of macro and socioeconomic factors as well as speciﬁc employment-related indicators disaggregated by gender and degree of urbanisation. The comparative analysis indicates deﬁciencies in regional development policies among post-transitional countries and the potential to adapt modern European practices and policies for improving the rural NEETs’ position.

Introduction
Youth citizenship is continually faced with various uncertainties regarding their general and professional development and career/job opportunities [1]. In many countries across Europe, young people (aged 15-24 as defined by International Labour Organization) suffer significant disadvantages compared to their peers, by being detached from both the labour market and the education and training systems [2]. Central to this is the cohort of young people characterised as 'Not in Employment, Education and Training' (NEET youths) [3]. Although especially vulnerable, this societal faction contains unexploited potential in terms of their capacity to engage in the labour force and contribute to local economies. The NEET concept encapsulates a heterogeneous group [4,5], represented by (i) long-term and short-term unemployed NEETs, (ii) unavailable NEETs due to family duties, (iii) unoccupied NEETs, i.e., those not actively seeking a job, but also not restricted due to other obligations, (iv) NEETs seeking opportunities, including youth actively trying to find a job or education and training but who are still waiting for offers that match their competencies and status, and (v) voluntary NEETs, i.e., those who choose to be in such a situation [6].
The importance of this concept has been recognised by policy makers and researchers in many countries, as isolated attention is focused on the NEET indicator as a supplement for youth unemployment rates [7]. This focus has drawn uniform attention across and beyond Europe, evidenced with the reduction of NEETs population being highlighted in the Sustainable Development Goals 2030 (specifically goal 8.6), and thus adopted by all United Nations Members in 2015 [8]. Consequently, the rate of NEETs (aged [15][16][17][18][19][20][21][22][23][24], has significantly decreased for most European countries, reaching its lowest level in 2019. The average NEET rate for the EU-28 countries in this year was 10.10%, the highest rate evidenced by Italy at 18.10% and the lowest by the Netherlands at 4.30% [9]. However, this is still an emerging public policy issue for the post-transitional economies where relatively higher rates of NEETs were evidenced in North Macedonia (18.10%), Bosnia and Herzegovina (21.28%), and Serbia (15.30%) in 2019 [9,10].
The situation is particularly concerning in terms of the increased distribution of NEETs in rural areas, where the likelihood of falling into a NEET category is more prominent in most European countries, including those aspiring to become EU members. In 2019 the EU-28 countries demonstrated a higher NEET rate in rural regions (10.60%) compared to their urban counterparts (10.10%). These numbers were higher still in the rural NEET population of the post-transitional countries of North Macedonia (R:17.60%, U:18.10%), Serbia (R:18.70%, U:15.30%) and Bosnia and Herzegovina (R:24.12%, U:21.28%) [9]. The rationale for this numerical NEET surge is due to lower socioeconomic status, poor educational achievements [11] and limited opportunities for professional development of the rural population [6,12]. Furthermore, NEETs in rural areas experience higher risk regarding their economic and career advancement, are more often exposed to unemployment and poverty [13] and also develop longer dependence on parental support [14]. The level of economic development and the rural-urban population distribution are closely related, but post-transition countries are challenged with more acute demographic changes and internal and external migration. These trends therefore limit the capacity of rural NEETs to avail of positive mobility opportunities for education, employment and training.
In the context of post-transitional economies, numerous factors discourage and demotivate rural youth to secure an enhanced future in rural areas or indeed to mobilise and return (e.g., lack of access to services and technology and the remoteness-geography of the locality, social setting, role of family, friends and social networks, etc. [15,16]). Their primary challenge is seen in the restricted access to education and information, which is largely limiting their personal development, expertise and innovative thinking [17]. Limited access to financial resources, underdeveloped infrastructure and communication systems are some of the other factors which contribute to the exclusion of rural youth in the labour market [17]. Moreover, agriculture as the main source of income in rural areas, remains to be an unattractive profession for young people. This is mostly due to the low average wages in the sector, the lack of large capital investments to support modern technology advancement in the area emanating from a risk of uncertain markets and low prices of agricultural products, intensive physical work and many other unfavourable aspects [18,19].
The dyadic impact of migrated youths not seeing value in a return to agriculture in rural locations, coupled with unsupported youths in situ raises a particular concern for youth NEETs left behind and the agricultural industry in these areas. These factors are constantly contributing to labour force shortages in agriculture. This is not only directly damaging agricultural production but also influencing rural and regional development and the agricultural labour markets. It has been acknowledged that long-term or permanent migration can be reduced if the infrastructure, technology and information channels in rural areas are initiated or improved [17,20] or through the initiation of new business in rural areas with better paid positions for their employees [21] With an ageing population and a lack of investment in the education, training and labour opportunities that support a financially receptive workforce in rural areas, and the potential negative impact on agriculture within and beyond rural communities, it is imperative that policy makers pause for thought and reassess current responses to Sustainability 2021, 13, 8410 3 of 15 challenges faced in rural areas. This paper aims to provide support in this regard by addressing the following research questions: RQ1: What are the determinants of rural NEETs in three post-transitional countries, Bosnia and Herzegovina, North Macedonia and Serbia, in comparison to those of select European countries?
RQ2: What deficiencies are evident in the regional development policies among posttransitional countries, and in contrast, what successful practices and policies have been evidenced in EU-28 countries, with specific attention to Ireland, in an effort to identify barriers and solutions towards enhanced rural NEET positive mobility?

Materials and Methods
To ascertain the determinants of rural NEETs in the identified countries (post-transitional countries: Bosnia and Herzegovina, North Macedonia and Serbia; and EU-28 countries, Ireland given specific attention), EU-28 countries were chosen as a benchmark comparison as the literature evidences their particular success in terms of declining numbers of rural youth NEETs. Ireland was chosen in particular, as an example of an established EU member state with over 50% of its population living in rural areas. Ireland scores above the EU-28 average across a number of factors that influence the prevalence of rural NEETs. Between 2009 and 2019 Ireland has introduced a number of macro to micro level actions that have had a positive impact on unemployment figures with the target group and that establish this country as a benchmark standard for tackling challenges associated with rural disadvantage, in particular, challenges associated with being a rural NEET.
Secondary data was collected through different official data sources (Eurostat, ILOstat, State Statistical Office of each country, as well as national programmes and reports). The dynamics were observed within a time range of a 10-year period (2010-2019), as it is considered a recovery decade from the 2008 economic crisis (the Western Balkan region and transitional economies in general were directly hit mostly in 2009 and 2010). The analysis began with descriptive statistics in order to understand the macroeconomic context for being NEET in the observed countries [2]. Thus, the following indicators were included: youth population (aged 15-24) as a share of the total population, labour productivity (based on the Gross Value Added (GVA)), as a volume measure of the output, and the number of employed people, as a measure of the input use [22]. The influence of the general economic development on youth unemployment and NEETs was also assessed through the countries' level of Gross Domestic Product (GDP) and, where available, through the risk of poverty rate. Additionally, an overview of the agricultural and rural development policy measures which directly or indirectly shape the rural environment and possibilities for young people was also included.
In addition to the international literature in which NEETs and rural youth issues are addressed [23], this issue has not attracted the attention of researchers or policy makers in the Western Balkan post-transitional countries. Therefore, a lack of youth policies is evident. As a consequence, there have been very few attempts (other than ad-hoc actions) to craft policies or programs to assist rural youth (including the more general NEET population) in capacity building to support and enable their transition to the labour market, thus improving their quality of life. Therefore, agriculture and rural development policies are seen as a major policy support to the rural areas of post-transitional countries. The analysis of the agricultural and rural development budget transfers focus on direct support measures [24], which is not an efficient way of dealing with youth or rural-urban migration challenges [21]. However, in situations where NEET-targeted policies do not exist, the set of existing agriculture and rural development policies will be presented and compared across the countries during the period from 2010-2019 (APM database for BA, MK and RS and the DAFM database for Ireland/EU-28). Furthermore, it is important to point out successfully applied public policies which contribute to the decrease of NEET share in total population, such as policies in Ireland, which has similar political, economic and social problems. Such analysis, together with a socioeconomic analysis, highlights the need to apply modern policies or those modelled on EU best practice. Specifically, analysis focused on the determinants of employment-related indicators (employment rate, unemployment rate and NEET rate) at the national level, and specifically for rural areas, to help identify priorities in the policy decision-making process. A linear regression model is used to determine whether the rural NEET indicator depends on other factors (rural unemployment, rural employment, gross domestic product and the youth population aged 15 to 24). However, because this model does not provide information on how strongly the variables are related, the Pearson correlation coefficient, calculated for each country, is employed for analysis of the relationship among the employment-related and the macroeconomic indicators [3].

Results
In most European countries, urban areas dominate, encompassing around 75% of the territory. In contrast, the portion of rural areas in the observed post-transitional countries dominate. The rural areas in North Macedonia cover around 88.70% of the territory and 47.50% of the total population. In Bosnia and Herzegovina it is even higher, with 91.94% of the territory being rural areas and 67.05% of the total population living there, while the rural population living in the rural areas of Serbia comprise 39% of the total population [25]. Heightened societal challenges in these rural regions include poverty or social exclusion (23.90% in rural areas versus 21% in urban areas), and in terms of academic prowess, levels of tertiary educational attainment are reduced (most of the rural regions in the EU present levels of tertiary educational attainment below 40%, while in the most urbanised regions, it is 60-80%), with lower levels of digital skills among the rural population (49% of the population have relatively basic skills compared to 63% for those living in the urban parts) [7,26]. In recent years, the rural areas in post-transitional countries have faced notable challenges relating to negative mobility, such as immigration, and have a small number of inhabitants. Furthermore, considering the age structure of people living in these areas, there is a high risk of regional depopulation through abandonment in the relatively near future. This trend is also evident in European countries, thus becoming a major concern for agricultural and rural development and sustainability [27,28].
The macroeconomic context of the observed countries reveals a modest but positive trend in all countries ( Table 1). The GDP per capita in 2019 varies from EUR 5.1 thousand in Bosnia and Herzegovina, to EUR 6.5 thousand in Serbia. Similar positive trends are observed in European countries where the GDP per capita is significantly higher, that is, the EU-28 average reveals an increase of about 22% between 2010 and 2019, resulting in a GDP per capita of around EUR 32 thousand in 2019, and even higher in Ireland with around EUR 60.2 thousand per capita.
In contrast, all countries show a negative mobility depopulation trend when it comes to youth aged between 15 and 24. The lowest share of this category of youth is evidenced in Serbia (10.50% of the total population in 2019), while in Bosnia and Herzegovina, this youth category captures a relatively higher share of 11.20% of the total population. The share of this youth category is almost the same in North Macedonia and Ireland with 12.40% and 12.60% of the total population, respectively. The declining trend compared to 2010 is more prominent for Western Balkan countries, ranging from 14.63% in Serbia to 20% in North Macedonia. The youth population aged between 15 and 24 is also declining in Ireland, but at a relatively lower rate compared to the post-transitional countries. The correlation between general economic development and unemployment revealed some interesting findings across countries. Total employment from EU-28 countries from 2010 to 2019 exposed a relatively small drop, whereas in the other observed countries, a significant growth in employment was recorded, except in Bosnia and Herzegovina where the total employment remained relatively stable during the analysed period. Consequently, the unemployment rate dropped markedly in all countries. The lowest unemployment rate is evidenced in Ireland (5%), while the unemployment is very similar within the Western Balkan countries, among which the lowest rate is determined for Serbia (14.60%) and the highest for North Macedonia (17.30%) in 2019. Considering the dynamic economic development, labour productivity is one of the key economic indicators offering a dynamic analysis of the economic growth, competitiveness and the living standards within an economy, as it depends on both labour availability and quality [24]. Calculated as the total Gross Value Added per employed person, the labour productivity levels have risen in all observed countries.
Consequently, these results are reflected in the youth unemployment in all countries. Considering youth aged 15-24, the highest drop is noted for Ireland (approx. 59%), and the lowest for the EU-28 countries (approx. 32%). Regarding the post-transitional economies, a significant decrease of about 43% is marked for Bosnia and Herzegovina and Serbia, while for North Macedonia was around 38% in 2019 compared to 2010. Such dynamics are also in line with the literature, whereby there is a strong positive correlation between the positive economic development trends and the general unemployment rate, including the youth unemployment and consequently the share of NEETs in one country [29,30].
Regarding the determinants of youth unemployment in the analysed countries, the results show quite different levels. The evidence presented on Figure 1 confirms the disparities among all observed countries on a national level and, in particular, for localised rural areas. Focusing on youth aged 15-24, all post-transitional countries reveal an unemployment rate of approximately 30%, with highest value marked for North Macedonia (35.60%) and the lowest rate determined for Serbia (27.50%). The youth unemployment in the post-transitional countries is almost comparable to the European countries; the youth unemployment rate of Ireland was 12.50% in 2019, while at the level of the EU-28 it amounts 14.40%. Very high youth unemployment rates and the relative disadvantage of young people compared to adults was also noted for the Mediterranean countries, which has arisen mostly due to the inflexible and sequential educational system enforced in those countries [2]. The situation deteriorates for those in rural settings. The combination of unsuccessful academic advancements and a limited labour market results in a pressure to accept less qualified jobs [6], the limited labour market in particular yielding significantly higher unemployment in rural regions in comparison to the national average. In this respect, the results for 2019 reveal the highest unemployment rates of rural youth (aged [15][16][17][18][19][20][21][22][23][24] in Bosnia and Herzegovina (34.10%), followed by the unemployed rural youth population in North Macedonia (32.94%). The unemployment of the rural youth in the observed European countries is significantly lower, i.e., for the EU-28 it is 13% and for Ireland in particular, 12.10%. Nevertheless, the economic growth evidenced for all analysed countries positively correlates with the employment possibilities for the rural population, leading to a significant drop of the unemployment rates when compared to 2010. 40%. Very high youth unemployment rates and the relative disadvantage of young people compared to adults was also noted for the Mediterranean countries, which has arisen mostly due to the inflexible and sequential educational system enforced in those countries [2].  The situation deteriorates for those in rural settings. The combination of unsuccessful academic advancements and a limited labour market results in a pressure to accept less qualified jobs [6], the limited labour market in particular yielding significantly higher unemployment in rural regions in comparison to the national average. In this respect, the results for 2019 reveal the highest unemployment rates of rural youth (aged [15][16][17][18][19][20][21][22][23][24] in Bosnia and Herzegovina (34.10%), followed by the unemployed rural youth population in North Macedonia (32.94%). The unemployment of the rural youth in the observed European countries is significantly lower, i.e., for the EU-28 it is 13% and for Ireland in particular, 12.10%. Nevertheless, the economic growth evidenced for all analysed countries positively correlates with the employment possibilities for the rural population, leading to a significant drop of the unemployment rates when compared to 2010. Subsequently, employment has increased during the analysed period for all countries. With regard to the post-transitional Western Balkan countries, the highest employment rates are suggested for Serbia (41.10%), followed by Bosnia and Herzegovina (23.10%) and North Macedonia (20.70%). Nevertheless, the employment in these countries is still lagging behind the EU countries, where the employment rate is much higher. These trends are also reflected for the rural population in all countries. Compared to 2010, the highest increase is found for Bosnia and Herzegovina (+38%), followed by Serbia (+33%) and North Macedonia (+31%). In the context of the observed EU countries, a steady growth of the employment in the rural regions is evident.
The unemployment rate is often correlated with the share of youth in the NEET category. In most of the European countries, a relatively high share of NEETs are registered, mostly due to the fact that this group of young people are in a detrimental position in the labour market compared to their peers [2]. In this context, the most adequate indicator of this detrimental position derives from the comparison between the youth unemployment rate and the corresponding rate for the rest of the population. In this Sustainability 2021, 13, 8410 8 of 15 respect, Figure 2 reveals the determined NEET rates for the observed post-transitional countries in comparison with the EU-28 average and Ireland. As we can see, the share of NEET has significantly decreased in all countries during the 2010-2019 period. The reduction of the NEET rate primarily relates to the proactive inclusion of young people in the job market and/or investment in youth education and training, thus determining their position in the labour market and improving their participation in positive mobility actions. The highest share of the NEET population is registered in Bosnia and Herzegovina (21.28%) and the lowest is in Serbia (15.30%). However, this is considerably higher than the share of the NEET population in the EU countries, with 10.1% for both the EU-28 and Ireland in particular. Considering that the highest NEET rates are not necessarily associated with the highest unemployment rates (for instance, the highest NEET rate is registered for Bosnia and Herzegovina, while the highest youth unemployment rate is evidenced for North Macedonia) leads our research to reveal that the NEET status should not be directly explained in reference to youth unemployment rates. This is not only a case within the observed countries, a similar situation is also evident for other European countries [2].
trends are also reflected for the rural population in all countries. Compared to 2010, the highest increase is found for Bosnia and Herzegovina (+38%), followed by Serbia (+33%) and North Macedonia (+31%). In the context of the observed EU countries, a steady growth of the employment in the rural regions is evident.
The unemployment rate is often correlated with the share of youth in the NEET category. In most of the European countries, a relatively high share of NEETs are registered, mostly due to the fact that this group of young people are in a detrimental position in the labour market compared to their peers [2]. In this context, the most adequate indicator of this detrimental position derives from the comparison between the youth unemployment rate and the corresponding rate for the rest of the population. In this respect, Figure 2 reveals the determined NEET rates for the observed post-transitional countries in comparison with the EU-28 average and Ireland. As we can see, the share of NEET has significantly decreased in all countries during the 2010-2019 period. The reduction of the NEET rate primarily relates to the proactive inclusion of young people in the job market and/or investment in youth education and training, thus determining their position in the labour market and improving their participation in positive mobility actions. The highest share of the NEET population is registered in Bosnia and Herzegovina (21.28%) and the lowest is in Serbia (15.30%). However, this is considerably higher than the share of the NEET population in the EU countries, with 10.1% for both the EU-28 and Ireland in particular. Considering that the highest NEET rates are not necessarily associated with the highest unemployment rates (for instance, the highest NEET rate is registered for Bosnia and Herzegovina, while the highest youth unemployment rate is evidenced for North Macedonia) leads our research to reveal that the NEET status should not be directly explained in reference to youth unemployment rates. This is not only a case within the observed countries, a similar situation is also evident for other European countries [2].  Moreover, the population living in the countryside face different, although related, barriers with respect to labour opportunities or education and training attainment, often forcing them to abandon rural communities in search of academic and professional opportunities in urban areas [31]. This induced migration contributes to degradation of rural Moreover, the population living in the countryside face different, although related, barriers with respect to labour opportunities or education and training attainment, often forcing them to abandon rural communities in search of academic and professional opportunities in urban areas [31]. This induced migration contributes to degradation of rural communities, leading to limited job and education opportunities for rural youth. Consequently, the share of rural NEETs is higher compared to the share of this category of youth for the total country. In the context of the analysed post-transitional economies, it is even worse. It is more prominent for Bosnia and Herzegovina, with a share of 24.12% of the total rural population aged 15-24, followed by Serbia with 18.70%. Although the share of the NEET population in North Macedonia was higher at the national level, when examined for rural areas, the results show a decreasing trend, thus leading to lowest rate in 2019 of 17.60%. However, the lower rates for North Macedonia might arise from the fact that there is a significant migration from the rural regions on one side but also a notable decrease in the population aged 15-24 in the country. The share of rural NEETs at the European level is significantly lower in comparison to the Western Balkan countries.
In particular, the rural NEET indicator in all four countries is strongly influenced by the studied independent variables, such as employment and unemployment rates on one hand, and the gross domestic product and the share of youth aged 15-24 on the other, with an R 2 of 0.781 in Bosnia and Herzegovina to R 2 of 0.994 in Ireland (Table 2). Furthermore, the Pearson Correlation Coefficient confirms the strong positive relationship between the rural NEET indicator and each country's unemployment rate on one side, as well as the negative correlation between the rural NEETs and the general macroeconomic conditions in terms of GDP and rural employment in the observed countries on the other. All this highlights the low efficiency and efficacy of the applied public development policies, particularly in rural areas, i.e., most of the observed indicators clearly indicate that the rural areas are at high risk of being depopulated in the relatively near future, and therefore, prompt action should be focused there. This is partly a result of the negative image that rural regions have, but also due to ongoing processes of globalisation such as growing services and industry sectors that attract a more low-skilled, more youthful population. Bearing this in mind, tailor-made instruments and mechanisms should be developed and applied through national and European funds [28].
As evidenced in the available literature, in the post-transitional countries, public policies targeting young or NEET populations in rural areas are very rare and, in some instances, non-existent. Thus, agricultural and rural development policies are the only permanent source of support to the rural communities including youth. Those policies promote very traditional approaches to development in rural areas, focusing on the primary sector and mostly providing direct support to farmers. Only a small share of total budgetary support to agriculture is dedicated to structural and rural development measures (in BA 6.66%, MK 26.38%, in 2019), except in Serbia, where 62.24% of the budget is dedicated to the structural and rural development support in 2019. In addition, the subsidies from agriculture, are not policies that enable connections between markets, information and social networks and therefore do not contribute efficiently to rural development [21]. Despite limited success stories, there are few alignments between policy implementation and addressing the needs of the rural population (including youth, NEETs and producers) and where the discretion to make decisions is in the hands of those who are most connected to the context of influence [32]. Table 3 sums up different measures implemented under the rural development programmes within the observed countries, for the 2010-2019 period. Within the agricultural and rural development measures, there are a limited number of measures that support the youth population in BA, MK and RS. In the case of BA, measures targeting youth are still not attractive to government representatives and policymakers. Typically, such measures include building housing units for young married couples and single parents in rural areas, support for young agronomists who graduate from the Faculties of Agriculture and return to the countryside, and measures that support cofinancing up to 35% of mechanisation purchase. Lack of consistency within these measures remains a concern. For example, it can be the case that when funds from specific measures are allocated under the budget, individual farmers who are eligible for the support do not have necessary skills to apply for specific funds either through low awareness or low education. One of the factors associated with this challenge is that specific measures that deal with information exchange and knowledge transfer do not exist to support such individuals in rural settings. Indeed, modern, non-traditional measures have not adapted to the knowledge level and capabilities of agricultural producers and/or youth populationthe election is the other way around. Consequently, most of the "modern", sophisticated public policy measures, focused on social capital development, remain unused resulting in such measures being identified as ineffective.
It is clear that change is necessary in order to support the EU youth citizenship. They play a crucial role in societal development, and they are drivers of modern rural development in era of rapid digitalisation caused by the on-going COVID-19 pandemic. In particular, young farmers tend to be more productive [33] as a result of their openness to new ideas and are more open to informed risk taking [34]. It is vital that this demographic is supported as youth farmers play an important role in meeting the challenges of food security and global warming [35]. In the case of the observed post-transitional countries, the role of rural youth is crucial considering the ageing profile of the rural population, the inheritance of the agricultural production and also the effects of the agricultural and rural development policies in strengthening the agricultural sector and the rural areas. In addition, such change must come with a recognition that challenges being faced by rural youth are also related to underdeveloped infrastructure, high land prices, difficulty in accessing credit and policy support as well as problems with farm succession [36]. The issues of farm succession are of particular importance in the case of older farmers who do not have formal retirement plans or are concerned about the future, as they are usually not willing to transfer their farms or they want to maintain social currency, lifestyle, identity and status [37,38]. If older farmers do not pass farms to the younger generation, as part of a structured process of transition, there is a risk that rural youth may become disillusioned, further compounding the issue [39,40].
In contrast, and with these issues that face young people in rural areas, Ireland has taken a position to proactively support youth NEETs, which may be considered by other European partners. A Progress Report [41] reveals several measures targeting youth in the Ireland Rural Development Policy and programs of works are broken down on a region by region basis. In addition, government initiatives include a targeted youth scheme that supports young people impacted by a range of factors including rural isolation. In addition, ongoing measures or programmes include: the engage youth in new activities in local communities (Pillar 4 Fostering Culture and Creativity in Rural Communities); support for local community groups, including low income workers and youth NEETs and support for lifelong and community education opportunities for disadvantaged communities and individuals (completed activity 2017-2019); the participation of young people in rural Ireland in Science, Technology, Engineering and Maths through the SFI Smart Futures Programme; public engagement activities through the support of regional science festivals in rural Ireland; and supporting the inclusion of the voices of children and young people in the development of tourism and recreation opportunities through the Children and Young People's Participation Hub. Such a comprehensive approach to the NEET, rural youth population and its challenges underpins the success that Irelands is experiencing in decreasing the NEET population and increasing the quality of life in rural areas.

Conclusions
Several research findings indicate the importance of new programmes that focus on youth as drivers of inclusive rural transformation. As stated above, this vulnerable group of people is affected by many factors, and one of the indicators that captures the vulnerability of youth are NEET (Not in Education, Employment or Training) statistics. While it is true that that the NEET demographic is decreasing worldwide, it is still a significant challenge for developing countries, especially in rural areas. This is also reflected in high unemployment rates within youth populations and a low level of employment in observed countries.
Applied public policies in BA, MK and RS were focused on the first pillar measures based mainly on direct support to agricultural producers to generate additional income and to make their workplace more attractive so as to sustain production and, in addition, develop their business. However, it is evident that this approach decreases farmers' autonomy on what and how to produce because the policies are oriented towards the generation of additional income and not towards the efficiency and efficacy of the use of available resources. The results are an ageing demographic of producers who are not oriented towards the market demands, nor to the optimisation of business processes, nor to the sustainable use of resources. Indeed, efforts to innovate are often frustrated by a dearth of educational programmes for older farmers or rural youth who are open to lifelong learning opportunities once there is a sustainable pathways for succession in place.
This issue has been addressed, in part, by Ireland and the EU-28. In these instances, specific production areas are not targeted; rather, there is a focus on general weaknesses within the sector. Policy users, in this sense, agricultural producers and indeed all other stakeholders e.g., tourism workers, hiking, etc., are considered in order to shape and implement interventions/projects to overcome specific problem or problems within the sector. Such approaches are more holistic in nature and require multi-stakeholder buy-in for successful implementation. In such contexts, rural youth play a critical role in this process.
In recent years, the launch of non-agricultural activities on the family farm has become topical (investment in tourism in rural areas, direct sale of own products, investment in crafts and trades related to agriculture, forestry, tradition, souvenirs, processing of domestic products). For example, the organising of various cultural programs, art colonies, art exhibitions, production and tasting of cakes, cheeses and wines (gastro program), an exhibition of old folk costumes, sightseeing of ethno-museums with old tools and old furniture. All this promotes the holistic involvement of rural communities as well as attracting visitors. The goal of such initiatives is to keep and revive the tradition of old knowledge and crafts. Providing the opportunities to youth to express themselves in a way that would lead to the improvement of engagement with the agricultural sector, as young farmers tend to be more productive than older generations when provided with opportunities to do so. Young farmers are more open to new ideas and are eager to take a greater risk that consequently leads to higher innovation capacities within the rural regions, resulting not only in agricultural development but also in the development of complementary businesses. Is it possible to tackle youth needs with agricultural and rural development policies? The authors believe that it is. However a more concerted approach is required along with a clear and unambiguous recognition of the relationship between lifelong learning specific to rural settings, the availability of targeted policies and the energy of young rural citizens that is required to perpetuate rural dwelling. Therefore, future research activities should be focused on education and lifelong learning system impact on rural NEET. In addition, future research should emphasize the "greying of Europe" (and observed countries). It is important to outline the main limitations of this study such as the use of secondary data and the weakness of statistical systems in transitional countries (BA, MK, RS).