India contribution to the country’s GDP and

India is basically an agricultural economy, where more than 50% of the population is directly or indirectly depends upon agriculture. It is the biggest source of subsistence generation for the millions residing in the country. With 179.9 million hectares, India ranked second largest agricultural land in the world. The performance of the agricultural sector influences the growth of the Indian economy which is changing day by day with the change of its contribution to the country’s GDP and employment and capacity of absorbing labour force. The agriculture sector, at present, provides employment to 48.9% of the country’s workforce and the share of agriculture to India’s GDP is 17.0% in 2016-17(Economic Survey2016-17). The reduction in agriculture’s share to Gross Domestic Product from 30 per cent in 1990-91 to 17.0% in 2016-17 has not been accompanied by a matching decline in the share of agriculture in employment from 60% in 1990-91 to 48.9% in 2016-17, as the major part of the Indian population is dependent on agriculture directly or indirectly for livelihood. It clearly shows that this sector is not providing subsistence livelihood to a large chunk of the population which directly or indirectly depends upon agriculture.
In rural areas the agriculture sector engages 64% of the total workforce and contributes 39% to the total rural net domestic product. This shows over-dependence of the workforce in agriculture with significant underemployment. The estimated worker productivity in the agriculture sector was only Rs 62,235 as compared to worker productivity of Rs 1 17,587 in non-farm sectors during 2011-12. Thus non-farm sectors provide 2.76 times more productive employment than the agriculture sector in rural areas (NITI Policy Paper No.1 (2017), “Doubling Farmer’s income-Rationale, Strategy, Plan and Prospects”). According to NSSO, the workforce in the agricultural sector in rural areas has declined by about 34 million between 2004-05 and 2011-12 showing an annual decline at the rate of 2.04%. This decline in the workforce in agriculture is on the account of both the decline in the number of agricultural labour and the decline in the number of cultivators. The number of cultivators fell from 16.61 crore to 14.62 crore between 2004-05 and 2011-12, which makes an annual decline of 1.807 per cent. From last few years, the growth of the agricultural sector has deteriorated because it has a restricted perspective of productively absorbing the growing rural workforce which leads to the problems of poverty, unemployment and underemployment both in rural and urban areas. The severe problems of rural areas could not be resolved easily due to the acute structural problems associated with agricultural sector i.e., low productivity, unequal distribution of land, persistently high pressure of population on agriculture and increasing fragmentation of landholdings leading to decreasing availability of cultivated land area per household, failure to generate new productive employment opportunities to the growing labour force which in turns leads to the growing problem of disguised unemployment at a faster rate. Under this condition, diversification of the rural economy from agriculture to the non-agricultural sector can be seen as an important factor of the developing strategy. Non-farm activities have gained significant importance with the change of subsistence problems as well as viability issues; therefore people started moving from the farm sector to the non-farm sector. A shift in occupational pattern from the farm-sector to the non-farm sector is considered to be a natural process of economic development.
Farm sector consists of agriculture and allied activities and Non-farm sector includes manufacturing and services. Both farms as well as the non-farm sector are the two important components of the rural economy and we can say that the two pillars of the rural economy. The structure of the rural economy is paving a way for transformation through diversification of employment within these two sectors and the contribution of the rural non-farm sector to the rural income and employment is growing. Thus, diversification can be a better move to achieve a higher and much better state of living. Rural employment diversification is nothing but diversifying the source of employment to the non-farm sector which has been acquiring importance day by day in providing employment as well as more income opportunities to the increasing rural workforce since many years. Thus, the rural non-farm sector has acquired prominent place presently as a next best alternative for generating more employment, reducing the incidence of poverty, attaining a higher rate of growth along with the development of rural areas.
As per the literature majority of the workforce in developing countries is involved in different types of non-farm activities rather than engaging in farming which is their main activity. The rural non-farm sector includes activities like handicrafts, mining and quarrying, household and non-household manufacturing, trading or agro-processing, the setting up of small enterprises, repairs, and construction, trade, transport and communication, community and personal services in rural areas. It refers to those activities which are used to be done by rural households anywhere irrespective of its location. RNFS (Rural Non-Farm Sector) can broadly be classified into three categories based on their types of employment they are regular employment (salaried), casual employment (daily wage) and self-employment or own enterprise activities. Among these regular non-farm employment is highly preferable, as it is associated not only with high income but also with high entry constraints like assets holdings higher, education, etc. On the other side Self-employment in the non-farm sector can be residual, last resort option as well as high return activity depending upon the invested capital. Lastly, Causal non-farm employment may be both physically demanding and hazardous and low return activities due to the fact that the returns may be marginally higher than agricultural wage labour productivity Lanjouw and Sharif (2004); Kijima and Lanjouw,(2005). Based on literature studied it has been concluded that non-farm income activities have the capability to reduce increasing rural unemployment, providing more income opportunities for young people, women and other vulnerable groups. This indirectly helps in increasing growth in rural areas by increasing the income of the rural people as non-farm wage is found higher than the agricultural wage. It also gives security and reduces risk and unpredictable associated with agricultural income and reduces the pressure of labour on land. As per the literature, it can be said that non-farm sector employment can help the Indian economy to come out of the trap of a vicious circle of poverty. This sector also provides supplementary employment to small and marginal farm households during the slack season and thus helps in smoothing the income flow throughout the year. The role played by the non-farm sector can also be seen “under the conditions of increasing rural unemployment due to frequent land fragmentation, mechanization of farm-land and population pressure” where it not only accelerates the growth in employment opportunities but also leads to the augmentation of the primary sector in terms of income growth and development.
The growth of non-farm employment depends on various types of factors which are widely discussed in the literature. The various developmental factors like the modernization of agriculture and its commercialization, increased demand for non-farm goods and services, growing literacy, urbanization, have tried to pull the labour force with more skills to move away from the agricultural sector to more remunerative non-agricultural activities. Meanwhile, distress factors like poverty; unemployment, underemployment and natural disasters like drought, crop failure as well as floods have tried to push the rural workforce away from the one sector to many another more remunerative one. As per the literature socio-economic factors like age, gender, household size, farm size, annual household income, educational status of households, economic status of the household are the main factors that leading the workforce to diversify from the farm sector to the non-farm sector.
As per Census 2011, In Jammu and Kashmir the total population is 1.25 crores, out of which 72.62% of population lives in urban areas and 27.3% lives in rural areas. The number of total workers in J&K state is 4,322,713 out of which 1,793,021 are farm workers and 2,529,702 are non-farm workers. In J&K state, a majority of the population derives their livelihood from agriculture. The average size of land holding is very small which continues to act as a constraint for development. People in the state also depend directly or indirectly on this very sector. But the agriculture sector in Jammu and Kashmir does not fulfill even the subsistence need for the survival of a majority of rural households. The state is facing the problem of unemployment, since long. Therefore, expansion of the non-farm sector is very essential to provide them with supplementary gainful employment. The need for diversification arises from the fact that there is greater risk in depending exclusively on agriculture for livelihood. Employment diversification towards non-farm sector is necessary not only to reduce the risk from agriculture sector but also to provide sustainable livelihood options to rural households. Thus, it becomes very important to study the employment diversification towards the non-farm sector particularly in rural areas of the state.
Statement of the problem
The present study “Rural Employment Diversification towards non-farm sector: A case study of Jammu district of Jammu and Kashmir State” will be conducted in Jammu district. Total population of Jammu district is 15.29 lakhs, out of which rural population is 7.65 lakhs and urban population is 7.64 lakhs. The male and female population in rural area is 4.02 lakhs and 3.63 lakhs and in urban area 4.12 and 3.52 lakhs, respectively. The number of total workers in Jammu district is 508622 comprising of 236708 rural workers and 271914 urban workers (2011 census). In J&K state around 70% of the population resides in the rural areas and is directly or indirectly dependent upon the agricultural sector for their livelihood and employment opportunities. The contribution of Agriculture sector towards Gross State Domestic Product (GSDP) has remained constant which marks the beginning of declining trend of the sector. Also the agriculture sector does not provide a sufficient means of survival to a majority of rural households. With the demographic pressure on land and limited opportunity of expanding cultivated area, the role of non-farm sector is becoming important. Keeping this in mind the present study will focus on investigating the Rural Employment diversification towards non-farm sector; to enhance livelihood opportunities of rural households in Jammu district of J&K. Employment Diversification towards non-farm sector plays an important role in upliftment of rural poor. Various studies conducted which are related to the topic either directly or indirectly revealed that diversification has a positive impact on improving the socio-economic conditions of the rural poor. In this context, the present study will be conducted to find out whether it is so happening in Jammu district of J&K or not. Now the question arises is as how to improve the socio-economic condition of rural poor in Jammu district of J&K through employment diversification towards non-farm sector.
Review of literature
Araujo (2004) conducted a study to assess the impact of non-agricultural rural employment on poverty and to explored in which environmental policy interventions in education and roads can be more effective in reducing poverty through non agriculture rural employment. He found that manufacturing-employment is more poverty reducing than services in semi-urban municipalities. He suggested that poverty is higher in municipalities with higher income inequality and with lower government expenditure and these two effects are stronger in semi-urban than in rural municipalities. He also observed that interventions in education and roads are poverty reducing through manufacturing employment in semi-urban municipalities and through services employment in all municipalities.
Schwarze and Zeller (2005) described the income activities of rural households and examined the determinants of non-farm diversification at the Lore Lindu National Park in Indonesia. He has used Tobit model in his study. He found that agricultural activities are the most important source of income for rural households, contributing 68% to total household income while the remaining 32% is originating from non-agricultural activities. He also found that the poverty index and the access to formal financial market both have a positive impact on the share of non-agricultural income.
Zhu et al. (2005) observed the role of non-farm income in reducing rural poverty and inequality in China. He found that without non-farm employment, rural poverty would be much higher and deeper and that income inequality would be higher as well. He concluded that participation in non-farm activities provides rural households with an additional source of income, improving their living standards and narrowing income gaps as well.
Kijima and Lanjouw (2005) analyzed National Sample Survey data for 1978-88, 1993-94 and 1991-00 to explore the relationship between rural diversification and poverty. He suggested that there has been no acceleration in the rate of poverty decline or in the rate of diversification out of agriculture. He concluded that poverty reduction is more clearly associated with changes in agricultural wages and agricultural wage-labour employment levels, than with expansion of non-farm employment opportunities.
Bhaumil (2007) examined the patterns and determinants of employment and income diversification amongst the rural household in West Bengal. He observed that the majority of the households were multi active, as they participated in both farm and non-farm sector. The non-farm sector generated more employment per household than the farm sector both in the advanced and backward regions. He found that the landless and sub-marginal farmers received the bulk of their employment and income from wage labour in agriculture, non-farm wage labour and self-employment in the non-farm sector. He observed a no. of factors such as age, education, caste, land-man ratio, a percentage of non-farm assets, total no. of workers, the distance between the residence of the household and nearby urban centre that encourage rural households to adopt more diversified employment/earning structures.
Sujithkumar (2007) analyzed livelihood diversification among rural households in Vellore district of Tamil Nadu by using Inverse Simpson Diversity Index. He observed that rural households are no longer generating income from agricultural sources alone and there is a significant difference among different income groups and different landholding groups with respect to livelihood diversity. He found that the better-off households showed greater ability to diversify in more favourable labour markets than the poor households because of lack of assets of the poor and their exclusion from the more highly remunerative labour markets due to skill-related and educational constraints. He concluded that landless households diversified less than the landed households but diversify do not increase with an increase in the landholding status.
Kumar (2009) attempted to measure the trends and patterns of the employment diversification within the agriculture especially in eastern India and assessed the employment potential of different sub-sectors of agriculture, which can provide succour to the rising problem of unemployment. The employment growth trends witnessed in the agriculture sector have not been able to inspire confidence. By using a Multinomial Logit model several socio-economic factors were examined that have a significant effect on rural employment in non-farm and horticultural activities.
Dixit (2009) analyzed the growth and employment in the primary and other sectors in Gujarat. He found that the growth in the state is driven by the secondary sector. Between 1960-61 and 2005-06, the growth in the primary sector was only about 4 times, as compared to 17 times in the secondary and 15 times in the tertiary sector. He also observed a little change in state at the employment level. The survey data concluded that the high-income households diversify due to non-farm assets and higher education and poor household diversify due to inadequate means of agricultural production.
Fabusoro et al. (2010) conducted a study to examine the forms and determinants of livelihood diversification among rural farm families in Ogun state, Nigeria. The study revealed the importance of diversification as it accounted for 69.1% of household income. Education, Household size and income were significant predictors of diversification. The non-farm activities identified in the study have the potential for enhancing the capability of individuals and households to construct positive livelihoods. The successes of these activities depend largely or partly on the success achieved in agriculture which is a significant determinant of diversification.
Sharma (2010) attempted to understand broadly the dynamics of rural livelihood diversification in the state of Jammu and Kashmir by using secondary sources of information. He found that agriculture remained as a dominant livelihood strategy among workers in the state despite the shift to manufacturing and tertiary activities over the period, that is, 1983 to 2004-05. This may partly be attributed to high percentages of rural illiterate workers among those engaged in the cultivation and partly to fewer opportunities in other sectors due to the insurgency in the state. He also observed that those households which have low monthly per capita expenditure have diversified their sources of income to multiple avenues than one source of income.
Asmah (2011) found that level of welfare is higher for those farm households who work in the non-farm sector than the farm sector. The non-farm diversification activities and household welfare are mostly driven by household assets and compositions including household age structure, education level and gender. Livelihood diversification is an important mean of enhancing the welfare and deserves attention.
Kumar et al. (2011) conducted a study of rural employment diversification in India and across major states using NSSO data at household level for the period 1983 and 2009-10. A no. of factors have been observed affecting rural employment significantly in both non-farm and horticultural sectors. He observed that the non-farm sector has consistently grown over time and employed nearly one-third of the rural workforce in 2009-10, as compared to one-fifth in 1983and all-India level. The similar trend is seen across major states as well, though the pace and pattern varied widely. The study has also revealed that the growing rural non-farm employment has a positive and a very significant effect on reducing rural poverty at the national level. A positive link between income and employment has also been observed in diversifying towards horticultural activities.
Panda (2012) analyzed the nature, extent and determinants of RNFE in North-East in general and Assam and Meghalaya in particular. He found that 66% of sample households were engaged in RNFE as their principal household occupation and the rest 34% on farm occupation. Within the non-farm sector, about 42% of households are engaged in service sector closely followed by 39 % in trade and commerce sub-sector and less than 1 percent of the household is engaged in manufacturing. He also observed that participation of the households in non-farm activity is significantly influenced by both pull and push factors. The field data analyzed that household income from agriculture, access to credit, household poverty and distance from the nearest urban centre are the important variables that determine the participation of households in RNFE.
Khatun and Roy (2012) conducted a study in West Bengal to identify the determinants and constraints of livelihood diversification among different livelihood groups. He found that household-heads experience (age), education level, asset position, dependency ratio, social status, training, access to credit, irrigation, network, agro-climatic condition and the overall level of economic development of a region are the main driving force towards livelihood diversification in the study area. He observed that several constraints act as obstacles to livelihood diversification but the nature of these constraints differ across regions and livelihood groups. The main constraints faced by the households in the more diversified area are: poor asset base, lack of credit facilities, lack of awareness and training facilities, fear of taking risk, lack of rural infrastructure and lack of opportunities in non-farm sector, while the main constraint in less diversified area are: poor transport facilities, poor asset base, unfavourable agro-climate, lack of awareness and training, and lack of basic infrastructure.
Darry and Kuunike (2012) identified the types and determinants of the probability of participation in non-farm employment areas in the Upper West Region of Ghana. He observed five groups of NFEAs such as extractive, manufacturing/processing, constructive, commercial and direct services. He found that commercial services dominate the non-farm economic activities followed by constructive industry; manufacturing, extractive industry and personal services. The predominant non-farm economic activities found include trading charcoal and fuelwood production, casual employment in building and construction pito (local beer) brewing, stone mining, food vending and retail shop operation. The factors such as sex, age, marital status, education, vocational training, belongingness to a group and location also found to be significantly associated with the probability of participation in NFEAs.
Vatta et al. (2013) examined the role of the non-farm sector in sustaining rural livelihood in Punjab especially of the landless and marginal farm households who are often poor and derive a sizeable proportion of their income from non-farm activities. He found that the households with productive assets diversified into more productive non-farm activities while landless, marginal and small households could have access to only relatively less-remunerative sources of non-farm income. The non-farm income sources have been found to contribute towards the reduction in income inequality. He also found that larger family size, higher dependency ratio, small landholding and social backwardness are the important determinants that motivate farm households to participate more in the non-farm sector.
Akaahol (2014) examined the determinants of diversification using Logit model and also the impact of diversification on household welfare by using OLS regression model in Benue state. He found that probability of diversification increases with male-headed household, education, credit and market and decreases with farming experience. He also found that diversification, age, education and credit have a positive effect on household welfare while household size has a negative effect.
Katega and Lifuliro (2014) investigated the extent to which rural non-farm activities contribute to alleviating poverty in participating households. He also examined the factors affecting the performance of rural non-farm activities and the mechanisms through which rural non-farm and farm activities are interlinked. He found a number of factors affected the performance of non- farm activities, including inadequate capital, lack of business education, poor business premises, inefficient transport to and from markets, and women’s gender roles. He observed that rural farm and non-farm activities are interlinked because in most households farm activities provided the capital for starting and running non-farm activities and non-farm activities provided the income to purchase farm inputs. He also found that rural non-farm activities contributed a significant share of total income in participating households and enabled these households to purchase food and consumer goods, pay for medicine and health care, pay for the education of children, as well as invest in farm inputs to enhance the productivity of agricultural activities such as crop farming and livestock keeping. He concluded that rural non-farm activities play an important role in alleviating both income and non-income poverty.
Venkatesh et al. (2014) analyzed the performance of Indian agriculture in terms of growth, employment and output using secondary data in the last two decades (1990-2010) at the national level and also with the special focus on the major states. It was found that the share of agriculture in the national employment came down from 64% to 57% only during the last two decades, whereas its share in GDP halved from about 25 to 12.5%. It was also analyzed that the growth process of the economy brought significant changes in RNFE and five states have share of more than 40% in 2009-2010. The study also examined that the infrastructure development, agricultural growth and farm-size are the key factors which positively influence the RNFE.
Misra (2014) attempted to understand the trends and patterns of growth of employment in RNFS in Maharashtra and also analyzed the determinants of diversification in post-liberalization period based on 66th round NSS data on employment and unemployment. He found that rural employment in Maharashtra in the non-farm sector has not shown any significant increase in post-liberalization period. He observed that the probability of male employment in non-farm activities is more as compared to female. He also observed that age and education have a positive impact on employment in RNFS while household size has a negative impact.
Bantilan et al. (2014) attempted to assess the changing structure of the rural production and employment in the last two decades and its implication on the rural labour market. He found that RNFE is emerging as one of the key drivers of rural development and transformation, contributing 65% to the rural Net Domestic Product in 2009-10 as compared to 36% in 1980-81. He also found that the share of rural non-farm employment is growing (19% in 1980-81 to 31% in 2009-10) still; agriculture is the major employees of the rural workforce (68% in 2009-10). He observed a significant structural transformation within the rural labour market with labour moving from agricultural towards non-agricultural activities. This significant movement has led to the tightening of the labour market.
Lama (2014) attempted to understand the nature of diversification of economic activities in two backward districts of West Bengal and also examined the factors that force such diversification at household level by Binary logit model. He found two ways through which the diversifications of economic activities take place. An individual may diversify his work by shifting away from the agricultural sector towards non-agricultural sector or he may diversify by undertaking more than one activity at a period of time. He observed that education played a very vital role in getting access to non-farm employment, even a small attainment of education could help the individual to get a job in RNFS. The individuals from socially disadvantaged groups such as ST/SC or backward caste and female candidates were, however less likely to work in RNFS. He also observed that village characteristics like population density, a distance of the village from the nearest town and availability of basic infrastructural facilities also played important role in the diversification of economic activities in the study area.
Zeray et al. (2015) investigated the push and pull factors that influence the participation decision of rural households in non-farm activities by using Multinomial Logistic Regression and the income obtained from this sector by using Tobit model. He observed that only 21% of the total household income was derived from different non-farm activities with a participation rate of 46%. He found that the factors like better education, land holding, access to irrigation and number of adult members have a positive influence on the likelihood of involvement in non-farm activities and also access to credit, better land size, livestock and number of adults in the household appreciably and positively influence the share of income from RNFE. He concluded that the household with a better economic condition is pulled to the non-farm sector by the better return from the non-agricultural sector.
Sultana et al. (2015) conducted a study to present an empirical evidence of the state of income diversification and its impact on household’s well-being in the rural areas of Rajshahi district of Bangladesh. A multistage random sampling technique is used for collecting the data. To measure the level of income diversification Simpson Index of Diversity is calculated and to measure the level of well-being, household consumption expenditure is used. He observed that the extent of income diversification is comparatively low in the study area and it has a positive and significant effect on the household’s well-being.
Abdulsalam et al. (2015) examined the factors that determine non-farm occupations among rural farming households and to what livelihood strategies have improved the well-being of their households. He observed that the factors that influence the decision of participating in non-farm activities by the rural farming household slightly vary from those factors influencing the level of decisions taken for the engagement in non-farm activities and where it does, not by the same extent and way. Distance travelled and adjusted household size was found to significantly influence the farmer’s decision and education, poverty status and per-capita income did influence the level of participation significantly.
Guatam and Anderson (2016) assessed the role of livelihood diversification in household well-being in Humla, a remote mountain district in West Nepal. He found a uniform pattern of diversification in terms of the no. of activities undertaken for livelihood but a highly varying degree of resultant well-being across households. He analyzed that well-being was associated with household’s involvement in high return sectors which is dependent on the antecedent level of resources and assets. The resource-rich households diversify into high return sectors and substantially improve their well-being while the resource-poor households, on the other hand, are forced to continue their low return diversification. He concluded that livelihood diversification has a highly skewed effect leading to inequality of income and well-being.
Kessle et al. (2017) investigated the determinants of diversification using a Logit model. He found that the institutional factors such as secured land, right perception and cooperative membership have the positive effect on farm household’s decision to participate in the non-agricultural activity while age, education and distance to the proximate market have a negative effect.
Ogunsipe et al. (2017) analyzed the contributions of non-farm activities in addressing rural unemployment and determined factors influencing smallholder farmer’s participation in non-farm activities in Ondo-East local Govt. areas of Ondo State, Nigeria by using Tobit model. He found that age, education, wage earned access to credit and distance were the significant variables influencing participation in non-farm activities. He concluded that non-farm activities help to reduce unemployment supplement farm income, provide a safety net and alleviate poverty among households.
Odoh et al. (2017) determined the effects of socio-economic characteristics of rural households on non-farm income diversification and analyzed the factors that influence the farm household’s participation in different non-farm activities. He observed that socio-economic characteristics of the farm households have a significant effect on their non-farm income. He found that 82.5% of the farm households diversified their income, 17.5% solely dependent on income from farming activities. He factors that influenced rural farm household’s participation in different non-farm activities were found to be poor returns to agricultural activities, small farm size, risk and uncertainties in agriculture, membership of a social organization, poor household earnings from farming, limited access to credit facilities and a profit motive.
Mech et al. (2017) conducted a study to examine the rural employment situation and also attempted to identify the determinants which influence the rural workforce to participate in non-farm employment as principal occupation by using a Binary Logistic Regression model. He found that the engagement of rural workforce in non-farm activities is more in comparison to farm activities. He also found five factors namely land size, educational level, household size, age and ratio of non-farm to farm income have turned out to be a significant determinants of rural non-farm employment where land size and age have a significant negative impact on non-farm employment while education level, household size and ratio of non-farm to farm income have appositive impact.
Sharma et al. (2017) studied the composition and contribution of non-farm activities in rural household’s livelihood also studied the factors causing participation in non-farm activities. He found that out of 300 rural households, 298 households were engaged in a variety of non-farm activities. He observed that casual non-farm employment occupies the most common livelihood source, followed by regular non-farm employment and self-employment. Factors causing non-farm work participation were found to be an average education of the households, credits and finance, household asset position, family size and operational holdings.
Research Gap
A number of studies have been conducted earlier related to rural non-farm activities, growth of rural non-farm employment, pattern, and determinants of employment diversification, role and significance of rural non-farm employment at state level, national level as well as international level. There is dearth of studies having focused on employment diversification in J&K. Such type of study has not been conducted in J&K till now specifically related to rural employment diversification towards non-farm sector. Rural non-farm sector is considered to be an important source of employment besides other farm activities to the rural households, therefore an attempt has been made in the study to examine whether people diversify towards non-farm sector. It will also cover the aspects like what is the trend of growth and composition of non-farm sector, what is the impact of socio-economic determinants of employment diversification towards non-farm sector and what is the impact of employment diversification on improving the standard of living of rural people in Jammu district.


I'm Owen!

Would you like to get a custom essay? How about receiving a customized one?

Check it out