Agriculture is important to the development of any nation, Ghana being no exception (Department for Environment, 2015; Food and Agriculture Organization (FAO), 2006). The international development community has recognized that agriculture is an engine of growth and poverty reduction in countries where it is the main occupation of the poor (The World Bank, 2008). Furthermore, young people are very important resource required for every nation’s development especially for sustainability in agricultural production (Ahaibwe  et  al.,  2013).  However, with low participation of youth in agricultural production, the future of the agricultural industry is questionable. Agricultural sector in many developing countries is underperforming. This is because youth, who represent a crucial resource in agriculture and the rural economy through their roles as farmers, labourers and entrepreneurs, almost everywhere, has developed a sort of perception to agriculture (White, 2012; Leavy and Hossain, 2014). There is recognition that for Africa to achieve food security, special attention must  be  given to the youth because the youths are regarded as critical agricultural players (Brooks et al., 2013).

The agricultural sector is believed by many analysts that it is naturally endowed with multiple potentials to engross unemployed and excess or idle labour which consists of youths especially, graduates, from other sectors of the economy (Akpan, 2010). In a developing country like Ghana, the Ministry of Food and Agriculture (MOFA) in order to encourage youth participation in the agricultural sector (MoFA, 2014)has establish a program, Youth in Agriculture Programme (YIAP) to change the negative perception the youth have on participation in agriculture, that is, farmers are uneducated, unskilled, physical labourers with extremely low economic return. The introduction of the program is necessary and vital to facilitate food and nutrition security for the future and also highlights the essential benefits attached to agriculture (MoFA, 2014). In Ghana, youths are distancing themselves away from agriculture in the face of government making efforts to attract them into the sector, creating employment while producing food for ever growing populations (Naamwintome and Bagson, 2013).

The researchers try to justify why increase participation of the youth in agriculture activity in Ghana is an important tool for economic growth by the following facts. The Ghanaian economy is broadly categorised into three sectors, namely, Agriculture (including Forestry and Fishing), Industry and Service. Agriculture’s contribution to total employment is estimated to be 40.6%, with the Service and Industry sectors accounting for 45.2 and 14.1%, respectively as at the year 2017 (The World Factbook, 2017). This means, agriculture has lost its position as the largest employer, after dropping second to the Service’s Sector. From Figures 1 and 2, the reduction in the agriculture employment rate also affects its contribution to Ghana gross domestic product (GDP). Agriculture contribution to GDP is estimated as 18.30% with the service and industrial sectors recording for 24.50 and 57.2%, respectively in the year 2017 (The World Factbook, 2017). This simply reconfirms that agriculture production and its contribution to GDP will boost should the employment rate of agriculture increase (Speth et al., 2015). Therefore, in order to halt the reduction in the agriculture employment rate, increase investment in agriculture by encouraging these young ones to participate in agriculture activities is needed. Furthermore, the current level of youth unemployment in Ghana is alarming. Youth unemployment incurred huge costs to the economy, society and their families (Maguire et al., 2013; ILO, 2013; Ajaegbu, 2012). Ghana’s real GDP growth reached about 15.2% when the country began its commercial oil production in 2011 (Baah-Boateng, 2013; Ackah-Baidoo, 2016). In spite of this strong growth performance, employment generation remains a challenge (Peprah et al., 2015).

 

 

 

However, while previous studies focus on the youth as a whole especially youths in the rural areas, their perception on farming and determinant of their involvement in agriculture activity, no known study to the best of the authors’ knowledge  investigated  determinant of youth in the tertiary institution decision and the intensity of participation in agriculture activities which this study does. This study objectives are therefore in twofold; first to examine the determinants of tertiary institution youth participation in agriculture activities and second to determine the intensity of tertiary institution youth participation in agriculture activities. Findings of this study will lead to better understanding of major reasons why youths are discarding or not putting in much effort in agriculture activities.

Theoretical framework of the study

Youth involvement in agriculture cannot explain without elaborating on migration studies. Many researchers have included migration as part and parcel of development studies for decades. The migration pull and push model had been employed to explain various issues relating to youth involvement in farming by few researchers like Noorani (2015) and Akpan et al. (2015). Some of the factors ‘pulling’ young people away from agriculture and more specifically farming, may include increased educational opportunities and higher paying jobs in the cities as well as sound economic environment. The push factors on the other hand also include: lack of access or restricted access to land, inadequate social amenities, poor transportation network and lack of opportunity for personal development. This research study examines the determinant of youth decision to engage and participate in farming and therefore employed the push and pull factor model as a guide to understand this study. There are numerous theories of migration but this study considered the dual labour market theory based on the objective of the study.

The dual labour market theory developed by Michael Piore in 1979, links migration to structural changes in the economy but explains migration dynamics with the demand side (Massey, 1999). This theory posits a bifurcated occupational structure and a dual pattern of economic organization in advanced economies. Two types of organization in the economy is expatiated by duality, namely capital-intensive where both skilled and unskilled labour are utilized, and labour intensive where unskilled labor prevails. The theory argues that migration is driven by conditions of labour demand rather than supply. This implies that the atmosphere of the economy creating a demand for both skilled and unskilled in the urban areas as compared to the rural areas causes migration.  Therefore, as immigration becomes desirable and necessary to fill the jobs, policy choices in the form of active recruitment efforts follow the needs of the market. This theory places much emphasis on the pull factors of migration. Many youths are leaving the rural areas, that is, neglecting farming to the urban area based on economic, social and personal factors (Lee, 1966; Massey, 1999; Kurekova, 2011). Hence, this study rest on the fact that, youth migration (from the rural  area/farming)  is  a function  of several  factors  such  as  pull  factors,  push factors and economic factors as well.

 

 

Data source and sampling procedure

The targeted population for this research was the youth in Ghana. The study was narrowed to the students at the tertiary institution. A pre-test structured questionnaire was prepared for collecting data from the respondents at the university level. Based on the experiences of  pre-testing  of  the  interview  questionnaire,  it  was modified and amended. The questionnaires were then finalized for the collection of data. Data on respondents’ decision and the intensity of participation in agriculture activities were collected through interview schedule. Information was obtained on tertiary institution youth socio-economic characteristics, agriculture participants farm enterprise characteristics such as reason for farming, type of farming these participants have engaged themselves and their annual income earnings. Also their participation constraints information was solicited. Data was edited and coded to ensure accuracy, validity, uniformity, consistency and completeness. A double-huddle model as previously used by Simtowe and Zeller (2007), Akpan et al. (2013), and Kuwornu et al. (2017)was employed to determine factors which influence the youth decision and the intensity of participation in agriculture activities. Data collected was analysed using descriptive and inferential statistical tools.

The multi-stage sampling technique was employed in selecting respondents for the study and again, ensure each respondent had equal chance of being selected in the sample (Stafford et al., 2006; Ascione et al., 2016). The first stage involved purposive sampling, where three universities were selected namely, University of Cape Coast (UCC), Kwame Nkrumah University of Science and Technology (KNUST) and University of Ghana (UG). These universities were purposively selected because they among the few universities in Ghana which offer agriculture as a course, that is, there exist college of agriculture in these school. The second stage employed the simple random sampling to select three halls each within these universities and in each hall. In the third and final stage, 50 students per hall were randomly selected making a total of 450 students. Among these 50 students selected includes both agriculture and non-agriculture students. A total of 135 students decided to engage and participate in farming and 315 decided not to engage and participate in farming.

Data was edited and coded to ensure accuracy, validity, uniformity, consistency and completeness. A double-huddle model as previously used by Simtowe and Zeller (2007), Akpan et al. (2013), and Kuwornu et al. (2017)was employed to determine factors which influence the youth decision and the intensity of participation in agriculture activities.

Empirical method

The study employed the independent double-hurdle model (DHM) originally formulated by Cragg (1971), with the assumption that youth decision and intensity of participation in agriculture activity are two distinct or independent decisions. In addition, different sets of variables are believed to influence the decisions of a youth decision to participate in agriculture and extent or effort put in the participation. The model is equivalent to a combination of a probit or logit and truncated regression model (Worku and Mekonnen, 2012). This work employed logit instead of probit since both econometric regression models are almost the same. A different latent variable is used to model each decision process, with a logit model to determine decision of engagement level one and a Tobit model to determine the intensity of participation (Blundell and Meghir, 1987). The first hurdle, a binary Logit model was used to identify significant factors that influence youth decision to engage in agriculture. This method was chosen because it is a standard method of analysis when the outcome variable is dichotomous (Hosmer et al., 2013), measured as having a value of 1 or 0, where 1 implies decision to something and 0 implies otherwise. Implicitly, the specified model is shown in Equations 1 and 2. The Logit model which captures youth decision to engage in farming is shown in Equations 4 and 5.

Tertiary youths are partitioned into two categories, participants in agriculture (> 0) and non-participants (= 0). Where  is the intensity of participation  (amount of  capitals invested in the agriculture activities carried out by participant). Let  represent the category to which the youth belongs, since the participant and non-participant partitions give an ordered response. Let the ordered response  be such that:

where is a latent discrete accessibility choice variable that denotes binary censoring, which is the utility the youth gets from participating in the agriculture. is a vector of explanatory variables hypothesized to influence farming choice,is a vector of parameters and  is the standard error term.

                                                                                       

Finding the determinants of the intensity of participation was achieved by estimating the equation of the second hurdle. The second hurdle involves an outcome equation, which employs a truncated regression (tobit) model to determine factors affecting the actual amount of capital used for agriculture by a youth who decided to participate in farming. This stage uses observations only from respondents who reported positive or greater than zero amount of capital. The truncated model is expressed as shown in Equation 6.

 is the   observed size of money (capital) by the sampled respondent. For a youth who does not engage in farming,  cannot be measured and was set to be equal to zero (0). This indicates that the observed amount of capital is zero either when there is censoring at zero ≤ 0 or if there is faulty reporting, or due to some random circumstance. The empirical model used to estimate the truncated regression model of the intensity of participation among the youths’ is as follows: 

where the dependent variable,= intensity of participation (Amount of capital invested in agriculture activity by a youth measured in Ghana Cedis (GH¢)) and = farming participation (1, if participated; 0, otherwise)  represent parameters of the model to be estimated and  represents the stochastic error term.

 

Descriptive statistics of socio-economic characteristics of respondents

The descriptive statistics of respondents is shown in Table 1.  The result revealed  an  average  age  of  about  26±5.86  years  for  youth  in  the  study  area.  This is because the targeted populations were students in the university. The result also showed that, about 65, 39, 40, 39 and 48% of the respondents had access to credit, perceived that farm inputs (fertilizer, seed, etc.) price were high, parents engage in farming as their occupation, had basic farming knowledge and perceived that, one can generate high income in farming, respectively. An average amount of GH¢1246.67±708.88 was revealed to be the amount of capital spent on the farm by the respondents. This is an indication that tertiary institution youth intensity of participation in agriculture activities are not  encouraging.  Also,  about  65%  of  the  respondents were male youth. The result also showed that 25% of youth interviewed were married. Only 38% of the respondents sampled had accessed to land for farming.

 

 

Participants farm enterprise characteristics descriptive statistics

From the study, it was revealed that out of the 135 participants, 58 (43%) of the respondents were non agriculture students and the remaining 77 (57%) respondents were agriculture students. These participants were asked the following questions: the reason why they choose farming, the kind of farming activities they involved themselves in and their average income per year.

Table 2 shows the reason why these 135 respondents decided and participate in farming. From the table, farming being an income generating job records the highest, that is, 127 (94.1%) respondents see farming as a source of income, farming serving as self-employment is the next reason, that is, 61 (45.2%) respondents consider farming as a substitute for being jobless. Access to land and parental influence is also identified as the reasons why these respondents chose farming. About 29 (21.5%) of the respondents had access to land through inheritance, lease and rent whiles 19 (14.1%) participate in farming because their parents are farmers  and  due  to that, influenced their young ones.

 

 

Participants’ reasons for farming

Type of farming system engaged in by participants

The kind of farming activities carried on by these participants is also shown in Table 3. Majority of the respondents, 126 (93.3%) are into crop farming such as maize, cassavas, beans, yams and plantains. The reason why most of these students chose crop farming is because, accessing a market for these crop products was relatively easy (Table 4). Again, these crops are traditional staple products that one is more than likely to be exposed in Ghana. Livestock farming took the second position. A total number of 11 (8.1%) respondents raise animals such as cows, goats, pigs and sheep. They also decided to raise these animals because one can easily access market for these products. Respondents engaged in mixed farming, that is, raising animal and growing crops at the same time are 10 (7.4%). Despite of the divided attention and resources over several activities associated with mixed farming, thus leading to reduced economies of scale, these farmers chose to practice it because of the possibility of reducing risk and re-utilizing resources. Fish farming and poultry recorded 5 (3.7%) and  3  (2.2%)    respondents,    respectively.    The   less participation of these kinds of farming can be attributed to the following: first, a lot of money is needed to sustain the birds and fishes. Second, most people do not know the technicalities in raising these kinds of animals; therefore, in order not to risk their resources, they prefer other options to these ones.

 

 

 

Annual income earnings from farming

Monthly income earnings from farming are shown in Table 5. Out of the 135 participants, only 57 (42.2%) reported their monthly income. From the table, 24 (42.1%) participants earn 100 to 1000 GHC per month. Again, 15 (26.3%) and 11 (19.3%) participants reported monthly income earnings of GH¢1100-2000 and GH¢2100-3000 per month, respectively. Only a few of the participants, 7 (12.3%), concluded that they earn above GH¢3000 per month. All those who earn above GH¢3000 in additional to 10 participants revealed that, they have market to sell their goods.

 

 

Differences between means of the independent variables for participants and nonparticipant in farming

From the Table 2, perceived price of farm inputs, access to credit, basic farming knowledge, access to land, and perception on income were all significant at 1%. Education was also significant at 5%. This implies that there are significant differences between the means for participants  and  nonparticipants  in  terms  of  perceived price of farm inputs, access to credit, basic farming knowledge, access to land, education and perception on income. There are, however, no significant differences between means for participants and non-participants for the rest of the variables (Table 6).

 

 

Determinant of youth decision and intensity of participation in agriculture activities

Results of the determinants youth decision and intensity to engage in agriculture activity are shown in Table 7. The first hurdle  reveals  that  the  Log  Likelihood  and  chi square value are -196.43532 and 101.82, respectively,  while  the  Log  Likelihood for  the  second  hurdle  was  -1277.1122. The entire models were significant at 1% levels of probability. The results showed that the coefficients of perceived price of farm input, access to credit, access to land, education, youth courses of study, gender of the youth and youth perception on income were found to be significant at the various levels of significance (p < 0.05, p < 0.01). The results in the table further revealed that while perceived price of farm input reduces participation and intensity of farming, access to credit, access to land, youth courses of study increased participation and intensity of farming. The more youth perceive farm input prices to be high by Gh¢1 would reduce the odd of increase in participation by 0.46 times and intensity by 93.20 cedis. This is as a result that, most of these youths are not working and do not have enough money to purchase high or expensive inputs. This result is in consistent  with  the  findings  of Goldsmith et al.  (2010)who indicated that,  high  price  of  products  leads to low patronage holding all other things constant. An increase in access to credit by Gh¢1 and land by 1acre would increase participation by 5.48 and 3.29 times, respectively and intensity by 210.299 and 202.72 cedis, respectively too. This result confirms Yuan and Gao (2012) and Chandio et al. (2017) that access to credit relaxes the financial constraint and this helps farmers to diversify their portfolio. Again, it supports Cotula et al. (2004)who explains that access to land brings hope to the youth because securing a land will have implications for the distribution of wealth, rates of economic growth and the incidence of poverty if used properly.

 

 

However, while  an  increase in  education  by  a year reduces the odd of increase in participation by 0.82 times, the intensity of participation fall by 124.96 cedis among male youth farmers. The result suggests that, as youth acquired more years of formal education, there is an increase tendency of agricultural diversification. The result suggested that most youth perceived agricultural production is not profitable enough or yield  fast income as compared to non-agro based businesses. Therefore, seek for greener pastures (white collar job) in the urban area, neglecting farming. This result is also in agreement with the research findings of Akpan et al. (2013)who reported that educated people give less priority to farming because they have higher chance  to find less tedious job in  the  cities  that  can  earn  them  huge  sum  of income.

Similarly, a number increase in agriculture students increases participation by 5.98 times and intensity by 317.47 cedis. Meanwhile, a 227.55 cedis increment in the intensity occurs as youths perceive Gh¢1 increase in income, thus, perceives a higher income. This result explains that, if agriculture becomes more remunerative and rewarding in terms of incomes and profitability, it will attract the youths to participate in it, therefore, increasing the amount of capital spent so as to increase production and income. These findings agree with the research study of Chikezie et al. (2012) andAhaibwe et al. (2013). They reported that high income from agriculture activities encourages individuals to participate in agriculture activities.

Constraints to youth involvement in farming

The results on the constraints to participation in agriculture activities in Ghana are shown in Table 8. Qualitative tools such as percentages and ranking were employed  to identify the most important constraints. Results revealed that, insufficient capital (72.40%) is the most important constraint faced by tertiary institution youth in Ghana. High cost of farm input (62.70%) and poor storage facilities (61.80%) also serves as hindrances to youth involvement in agriculture in the country. Farmers are not respected (61.40), inadequate land availability for farming (57.70%) and poor income generating (55.30%) as well inadequate credit facility (44.70%) are other significant deterrent to tertiary institution youth involvement in farming. In addition, the study identified farming as energy demanding (43.20%) and no agriculture insurance (40.60%) as mild constraints to youth involvement in farming. However, the study asserted that, the opinion those youths having no farming experience (35.80) is not upheld by majority of tertiary institution youth in the country.

 

 

 

 

 

 

 

 

 

In conclusion, youth participation is a key way to alleviate unemployment, food insecurity, immoral social behaviour like crimes and drug abuse and extreme poverty in developing countries of which Ghana is not excluded. Though farming comes with a lot of benefits to a nation but the result of this study reveals that majority of the tertiary institution youths, 315 (70%) compared to their counterparts 135 (30%), decided not to engage in farming. The findings of this research has also discovered that, youth perception of farm input price, youth level of education, access to credit, access land and youth course of study at the tertiary institutions, gender composition of the youth, and youth perception of farm income significantly affect decision and the intensity to engage in farming. Furthermore, insufficient capital, high cost of farm input, poor storage facility, farmers are not respected, poor income generating and inadequate credit facility are some of the constraints of tertiary institution youth participation in farming.

Based on the findings of this study, it is recommended that in order to push the youth into farming, communities and the government have a role to play. The following factors should be addressed and dealt with. They include:

(1) Motivating successful youth farmer through merit awards during every farmer’s day celebration.

(2) Provision of subsidies on major farm inputs prices such as fertilizers, seeds and other farming equipment.

(3) Putting on measures to curtail credit and land constraints so that, sufficient capital and access to land could be acquired by the youths to participate in farming.

(4) Provision of small farm in all primary and junior high schools in addition to the agriculture subjects studied in schools for practical purposes. This will give the students basic farming experience and increase their love for agriculture.

 

We gratefully acknowledge financial support from the Soft Science Program of Sci-Technolgy, department of Sichuan Province, China (18RKX0773). The authors also extend great gratitude to the anonymous reviewers and editors for their helpful review and critical comments.

 

The authors have not declared any conflict of interests.