Nonfarm entrepreneurship, crop output, and household welfare in Tanzania: An exploration of transmission channels

Barasa, Laura; Kinuthia, Bethuel Kinyanjui; Araar, Abdelkrim; Maende, Stephene; Mariera, Faith

doi:10.1002/agr.21788

Cited by 2 publications

(6 citation statements)

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“…This paper uses a modified income-leisure framework to analyze how a standard rural household maximizes its utility over income and leisure, subject to time constraint (Barasa et al ., 2022; Benjamin, 1992; Chang et al ., 2012). Let T be the farm household's total time endowment in a given time period such that the household allocates T between farm work (Lf), non-farm work (Lnf), unpaid domestic work (Ld) and leisure time (Le).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…For farm work, we assume that household and hired labors are heterogeneous. They are imperfect substitutes because of differences in skills, experience and motivation as well as the limited labor market opportunity in rural areas (Barasa et al ., 2022). Therefore, there would be two competitive markets such that the wage rate of household labor (WH) differs from the wage rate of hired labor (Wh) (Mishra and Sandretto, 2002).…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…Taking and solving the first-order conditions (FOC) show that farm household's preferences are optimal when the marginal substitution of leisure by income equals the non-farm labor wage which represents the competitive price of leisure: ∂U(.)∂HIWH=∂U(.)∂LeWLnf (Barasa et al ., 2022). Similarly, the FOC provide the following insights.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…Third, the farm household hires labor up to the point that the value of the marginal product of hired labor equals the hiring wage pQ=whH. In summary, the farm household's decision is made in two steps (Barasa et al ., 2022; Chang et al ., 2012; Tesfaye and Nayak, 2022). Household first spends its labor force on farm work and domestic activities to the point where the marginal products are each equal to the competitive wage of nonfarm labor.…”

Section: Theoretical Frameworkmentioning

confidence: 99%

“…During the last two decades, a large body of literature has investigated the importance and features of rural non-farm sector (Davis et al ., 2010; Winters et al ., 2009, 2010; Haggblade et al ., 2007; Barrett et al ., 2001; Lanjouw and Lanjouw, 2001 Barasa et al ., 2022; Basu and Kashyap, 1992; Christiaensen and Maertens, 2022; Gaddis et al ., 2023; Tesfaye and Nayak, 2022). A major conclusion from these studies is that non-farm activities in rural areas are the norm rather than the exception (Davis et al ., 2016).…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Policy interventions and productive employment in rural sub-Saharan Africa: a gender-differentiated meta-analysis

Singbo

Lokossou

2023

JADEE

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PurposeThe farm sector is crucial for rural poverty alleviation, alongside the non-farm sector, which contributes to mitigating risks associated with crop failures. This paper investigates the effects of public policies on productive employment within both the farm and non-farm sectors in sub-Saharan Africa.Design/methodology/approachA meta-analysis is conducted exclusively on the results of the Partnership for Economic Policy (PEP)-funded studies under the Policy Analysis on Growth and Employment (PAGE II) initiative. Selected studies focused on the impact of public policies on productive employment in rural farm and non-farm sectors, encompassing a total of nine sub-Saharan Africa countries in: Benin, Burkina Faso, Cote d'Ivoire, Democratic Republic of Congo, Ghana, Lesotho, Nigeria, Senegal and South Africa.FindingsThe results indicate that public investments in rural areas and public policies that facilitate access to productive resources are likely to enhance productive employment. The overall effect size is positive and significant, ranging from 2% to 10% increases in productive employment. Sources of variation include the sector of activity and the policy instrument. In addition, the policy effects are gender-sensitive and seem more consistent in the non-farm sector.Research limitations/implicationsAlthough the selected working papers addressed several aspects of productive employment, other aspects warrant further investigation. Policies involving restrictions or regulations have received little attention in the impact analysis. Researches to fill this gap would be important. Another suggestion for further research is the analysis of the relative importance of non-farm employment in rural areas in developing countries. It is always assumed that rural households depend heavily on agriculture for their subsistence.Originality/valueThe contribution of the paper lies in the comparative analysis of numerous public policies implemented in nine distinct countries. By consolidating data from fourteen 14 different experiences into a single study, the paper offers valuable insights on factors that determine policy effectiveness and contribute to understanding what worked for whom and why.

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Section: Theoretical Frameworkmentioning

confidence: 99%

Section: Theoretical Frameworkmentioning

confidence: 99%

Section: Theoretical Frameworkmentioning

confidence: 99%

Section: Theoretical Frameworkmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Policy interventions and productive employment in rural sub-Saharan Africa: a gender-differentiated meta-analysis

Singbo

Lokossou

2023

JADEE

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Socioeconomic Characteristics on Livelihood Outcomes of Conservation Agriculture Farmers in Makueni and Machakos Counties

Justin¹,

Maurice²,

David³

2023

IJARBSS

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It is estimated that a majority of the population in Sub-Saharan Africa (SSA) reside in rural areas where agriculture is the main source of livelihood. There is therefore the need to promote agricultural development to improve livelihoods and reduce poverty levels. The current study sought to assess conservation agriculture practices and their impact on livelihood outcomes focusing on Makueni and Machakos Counties. Specifically, the study investigated the effect of socioeconomic characteristics on livelihood outcomes of conservation agriculture farmers in Makueni and Machakos Counties. The study adopted sustainable livelihoods approach. The study employed cross-sectional survey as a research design. The sampling frame provided by the organization involved in the project indicates that there are 5091 Conservation Agriculture farmers. The Cochran formula was used with a 5% level of significance to obtain sample size of 384 respondents. The study relied on stratified random sampling to achieve a high degree of representation from groups with the desired characteristics. Sample size for each stratum was determined proportionately and individual elements selected through systematic sampling whereby the nth item was obtained by dividing the population in each stratum by the sample size. Qualitative data was be subjected to content analysis while quantitative data was analyzed using both descriptive and inferential statistics. Findings show that skills on CA and access to income positively influences CA farmers livelihood outcomes. On the other hand, non-farm activities have a negative effect on livelihood outcomes of smallholder farmers in Makueni and Machakos counties. The study recommends that the government at national and county levels should take responsibly in creating awareness on CA practices across the country and provide any necessary support for the farmers to embrace this noble practice.

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Nonfarm entrepreneurship, crop output, and household welfare in Tanzania: An exploration of transmission channels

Cited by 2 publications

References 51 publications

Policy interventions and productive employment in rural sub-Saharan Africa: a gender-differentiated meta-analysis

Policy interventions and productive employment in rural sub-Saharan Africa: a gender-differentiated meta-analysis

Socioeconomic Characteristics on Livelihood Outcomes of Conservation Agriculture Farmers in Makueni and Machakos Counties

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