Evaluating youth-centred agricultural extension programs for enhancing agripreneurship and rural employment

Introduction

"Agriculture is what you do when you have failed at everything else" this sentiment, voiced by a 22-year-old university graduate in Antsirabe, captures the attitude that youth extension programs must overcome before they can succeed [1] . Across Madagascar, rural young people are caught between shrinking farm sizes and an urban job market that cannot absorb them. The country's agricultural labor force is aging rapidly: average farmer age rose from 38 to 47 years between 2005 and 2020, and fewer than 12% of farmers under 30 report being satisfied with farming as a profession [2] . The paradox is that agriculture offers genuine economic opportunity. Madagascar's rice, vanilla, clove, and horticulture sectors are growing, and value chains from farm to export contain numerous points where entrepreneurial young people could create viable businesses [3] . But conventional extension programs were not designed for this population. They assume farmers are already committed to agriculture and need technical advice. Young people need something different they need to be convinced that agriculture can be a career, equipped with business skills alongside technical knowledge, and connected to markets and mentors who can help them navigate the startup phase [4] . Youth-centred extension is an emerging approach that redesigns advisory services around the aspirations and constraints of young people. Rather than treating youth as future farmers waiting for land, it treats them as potential entrepreneurs who can create agricultural businesses with or without large landholdings [5] . Evidence for this approach is growing in East and West Africa but remains thin for island nations like Madagascar, where agro-ecological conditions, market structures, and cultural attitudes toward youth employment differ considerably from mainland contexts [6] . This research evaluated a nine-month youth-centred extension program in central Madagascar, measuring its effects on agribusiness knowledge, entrepreneurial selfefficacy, farm income, employment outcomes, and market participation among rural youth.

Conceptual Model

The program design drew on an input-pathway-outcome model linking three types of extension inputs (technical skills, business literacy, mentorship) to three intermediate outcomes (knowledge gain, self-efficacy, social capital) and three final outcomes (agribusiness establishment, income generation, rural employment) [7] . The model posits that technical skills alone are insufficient youth also need entrepreneurial confidence and professional networks to translate knowledge into functioning businesses. Five moderating variables (age, education, land access, market proximity, and gender) were hypothesized to influence the strength of input-to-outcome pathways. This framework specifically avoids treating youth as a homogeneous group, recognizing that a 19-year-old with primary education faces different barriers than a 32-year-old with vocational training [8] .

Research area description

The research was conducted in four districts of the Vakinankaratra and Amoron'i Mania regions of central Madagascar: Antsirabe II, Ambatolampy, Ambositra, and Fandriana. The area sits on the central highlands plateau at 1,200-1,700 meters elevation, receiving 1,300-1,600 mm of annual rainfall concentrated between November and March. Agriculture centers on irrigated rice in valley bottoms and rainfed crops (maize, cassava, beans, potatoes) on hillsides [9] . Youth unemployment in these districts ranges from 38% to 52%, with most unemployed youth holding at least primary education. Road infrastructure connects all four district capitals to Antsirabe city, the regional commercial hub, within 2-4 hours by public transport.

Material and Methods

Material

The research enrolled 364 rural youth aged 18-35 from 28 fokontany (villages) across the four districts. Eligibility required residence in the research area, interest in agricultural entrepreneurship, and availability for the ninemonth program. A structured questionnaire with 56 items measured agribusiness knowledge (25-item test, 0-100), entrepreneurial self-efficacy (12-item scale adapted from Chen et al. [10] , Cronbach's α = 0.87), farm income (monthly records in Ariary), employment status (categorical: unemployed, casual labor, agricultural self-employed, nonagricultural), and market participation (frequency and volume of sales). Baseline data were collected in January 2023; endline in September 2023. Secondary data came from district offices and the Institut National de la Statistique for 2020-2023.

Methods

A single-group pre-test/post-test design was used. The extension program ran from January to September 2023 in three integrated modules: technical skills training (biweekly sessions on crop production, value addition, and post-harvest handling), business and financial literacy (monthly workshops on business planning, record-keeping, pricing, and access to microfinance), and mentorship networking (quarterly events connecting participants with established agripreneurs and market actors). Each participant received an average of 42 contact hours across the three modules. The model explained 47.6% of variance (adjusted R² = 0.476, F = 24.1, p<0.001). Participation intensity was the strongest predictor (beta = 0.37) youth who attended more sessions achieved better outcomes. Education and age also contributed positively. Gender was not a significant predictor, suggesting the program was equally effective for male and female participants. www.extensionjournal.com

Discussion

The doubling of agribusiness knowledge scores reflects the low starting point conventional extension had not reached most of these youth, so even a nine-month program could fill enormous knowledge gaps. More encouraging is the self-efficacy shift (31.7 to 67.3), because self-efficacy predicts sustained entrepreneurial behavior beyond the program period [10,11] . Youth who believe they can succeed as agripreneurs are more likely to persist through the inevitable early failures of business startup. The employment transition from 22.6% to 54.1% agricultural self-employment deserves careful interpretation. Some of this shift may reflect seasonal patterns rather than www.extensionjournal.com permanent career changes the endline coincided with the post-harvest marketing season when agricultural selfemployment naturally peaks [12] . However, the magnitude of the change and the accompanying income gains suggest real behavioral shifts beyond seasonality. The participation intensity finding (beta = 0.37) reinforces a lesson from adult extension research: contact hours matter. But the relationship may be partly endogenous more motivated youth attended more sessions and may have achieved better outcomes regardless of the program [13] . The non-significance of gender (beta = -0.08, p = 0.184) is a positive finding, suggesting that when programs are designed to be inclusive, young women can benefit equally. This contrasts with evidence from conventional extension where women consistently show lower adoption rates [14] .

Limitations

The single-group design without a control group prevents causal attribution improvements could partly reflect external factors such as favorable market conditions or seasonal employment patterns during the research period. The ninemonth timeframe captures short-term outcomes but cannot establish whether agripreneurial behaviors persist long-term. Self-reported income data carry recall bias, particularly for youth engaged in multiple informal income streams. The sample was drawn from four highland districts and may not represent coastal, humid, or arid zones of Madagascar where agricultural opportunities and youth demographics differ.

Conclusion

This research provides evidence that youth-centred agricultural extension can produce substantial improvements in agripreneurial knowledge, self-efficacy, income, and employment outcomes among rural youth in Madagascar. Agribusiness knowledge more than doubled, entrepreneurial self-efficacy increased by 112%, farm income doubled, and agricultural self-employment rose from 22.6% to 54.1% over nine months. The core lesson for extension policy is that young people respond when agriculture is presented as entrepreneurship rather than subsistence. Programs that combine technical skills with business literacy and mentorship networks address the full range of barriers that prevent youth from viewing agriculture as a career. Scaling this approach requires rethinking extension curricula, training agents in entrepreneurship facilitation, and building institutional partnerships between agricultural advisory services and youth employment agencies.

References

1. Leavy J, Hossain N. Who Wants to Farm? Youth Aspirations, Opportunities and Rising Food Prices. IDS Working Paper. 2014;439:1-44.
2. Madagascar Ministry of Agriculture. National agricultural census 2020: summary report. Antananarivo: MinAgri; 2021.
3. World Bank. Madagascar agricultural value chain analysis. Washington DC: World Bank Group; 2019.
4. Sumberg J, Anyidoho NA, Leavy J, et al. Introduction: the young people and agriculture problem in Africa. IDS Bulletin. 2012;43(6):1-8.
5. FAO, CTA, IFAD. Youth and agriculture: key challenges and concrete solutions. Rome: FAO; 2014.
6. Filmer D, Fox L. Youth Employment in Sub-Saharan Africa. Washington DC: World Bank; 2014.
7. Ajzen I. The theory of planned behavior. Organizational Behavior and Human Decision Processes. 1991;50(2):179-211.
8. Bandura A. Self-efficacy: toward a unifying theory of behavioral change. Psychological Review. 1977;84(2):191-215.
9. Minten B, Barrett CB. Agricultural technology, productivity, and poverty in Madagascar. World Development. 2008;36(5):797-822.
10. Chen CC, Greene PG, Crick A. Does entrepreneurial self-efficacy distinguish entrepreneurs from managers? Journal of Business Venturing. 1998;13(4):295-316.
11. McGee JE, Peterson M, Mueller SL, et al. Entrepreneurial self-efficacy: refining the measure. Entrepreneurship Theory and Practice. 2009;33(4):965988.
12. Barrett CB, Reardon T, Webb P. Nonfarm income diversification and household livelihood strategies in rural Africa. Food Policy. 2001;26(4):315-331.
13. Heckman JJ, Ichimura H, Todd PE. Matching as an econometric evaluation estimator. Review of Economic Studies. 1998;65(2):261-294.
14. Ragasa C. Improving gender responsiveness of agricultural extension. IFPRI Discussion Paper. 2014;1382:1-40.