(ProQuest: ... denotes formulae omitted.)IntroductionIt is not only the size of labor force but also its composition, especially Female Labor Force Participation (FLFP), plays a central role in the economic development of a country. Although developing economies across the world have formulated policies, which have resulted in a significant increase in the proportion of women participation in economic activities (Jaumotte, 2003), FLFP rates have been declining in agriculture in most of the countries. It is pointed out that the problem of declining FLFP is serious in middle income agriculturebased economies (Tansel, 2002). According to the International Labour Organization (ILO) (2006), the gap in male-female participation rates for Botswana, Namibia, Lesotho and Swaziland in 1996 was 19%, 18%, 27% and 42%, respectively. It is worth noting that the gap in female and male labor force participation rates in Swaziland is wider in comparison to other developing countries indicated above. Furthermore, the ILO report mentioned that within the African region, the gap between male and female participation in the labor force is such that females are restricted to the agricultural sector only.In Swaziland, women constitute a majority (53%) of the population (CSO, 2007a and 2007b). However, participation of females in agriculture has declined from 38% in 1980 to 12% in 2005 (World Bank, 2005; and CSO, 2006) even though the economy of Swaziland is largely agriculture-based. Their participation is important given that the agricultural sector contributes 13% to the country's Gross Domestic Product (GDP) (Central Bank of Swaziland, CBS, 2007). According to the CBS (2007), females in Swaziland have limited access to non-agricultural wage paying jobs and are often employed in low paying jobs. This means that females have low income and this shows their poor status almost half of the households in Swaziland are female-headed, in the rural areas.While addressing the issue of FLFP in the Swazi agricultural sector, this paper analyzes the determinants of female participation in agriculture. This study differs from other studies because it concentrates on the socioeconomic and demographic factors as determinants of FLFP in agriculture rather than emphasizing on human capital factors and the role of wages. The understanding of the above will assist the policy makers in designing informed policies which are likely to improve the participation of females in agriculture.Against this background, the main objective of the study is to understand and analyze the determinants of FLFP in the Swaziland's agricultural sector. The objectives are: (a) To determine the relationship between age, marital status, level of education, female Headed households, household ownership, credit accessibility and female residence and FLFP in agriculture; and (b) To recommend how to enhance FLFP in the agricultural sector.This study hypothesizes a positive relationship between married women and participation in agriculture because the most empirical literature related to this study supports this relationship. A number of similar studies by Nnadi and Akwiwu (2005), Damisa et al. (2007) and Fabiyi et al. (2007) also have found a positive relationship. This study hypothesizes a negative relationship between increase in education and FLFP in agriculture. This is also due to the fact that empirical evidence showed a negative relationship. This includes studies done by Psacharopoulos and Tzannatos (1989) and Tansel (2002). It is hypothesized that land ownership is positively related to FLFP in agriculture. This is because empirical evidence from several studies done in developing countries shows a positive relationship. For instance, Benefo (2003) shows that land ownership by household may increase the probability of female participation in agriculture by removing restrictions in land utilization and management. Credit accessibility is hypothesized to be positively related to FLFP in agriculture because this study assumes credit accessibility gives women the incentive to participate in agriculture.Literature ReviewA number of studies have been done on FLFP. However, there are few which focused on female participation in agriculture (Bardhan, 1984; Psacharopoulos and Tzannatos, 1989; Kombe, 1999; Tansel, 2002; Atieno, 2006; Damisa et al., 2007; and Fayibi et al., 2007, etc.) They conducted studies on FLFP in agriculture for specified periods and examined the factors affecting it.In most countries, FLFP was studied to answer questions-what is the relationship between economic growth and FLFP, does the attainment of higher education lead to a decrease in female participation in agriculture, to what extent do the wages for women influence their participation in agriculture, does the participation of husbands in off-farm employment influence the decision of women to participate in agricultural activity, do household size and composition affect female participation in agricultural work and many others.Researchers used various approaches to find answers to these questions. For example, most studies have used Ordinary Least Square (OLS) method, Probit, Logit, and Tobit models to test for factors that determine FLFP in agriculture. A few studies have used Heckman model. Several studies have found that various demographic, economic and social factors have an effect on FLFP in agriculture. They provide empirical evidence that FLFP in agriculture is influenced by age, marital status, education level, household income, land ownership, access to credit, access to fertilizer, household size, etc. They argued that these factors have contributed to the increasing or declining rate of FLFP in agriculture.Using the OLS method, Erdogan et al. (2006) determined the driving factors of woman participation in forestry in Turkey. Age and marital status were found to be important variables in explaining female participation in forestry. Specifically, the study found a positive relationship between married, older women and their participation in forestry. This was associated with the limited education opportunities available to older women and high monthly income of husbands. These findings are similar to those provided by Damisa et al. (2007) and Fabiyi et al. (2007).Damisa et al. (2007) used probit model to determine women participation in agriculture in Nigeria. He found that the majority of the women who participated in agriculture were in the upper middle age group and married. He also found that higher education increases the likelihood of women moving away from the agricultural sector to better-paid jobs. Furthermore, this study found an inverse relationship between the level of income of a woman farmer and her participation in agriculture. According to Damisa et al. (2007), this is attributed to the uncertainties associated with agricultural production. Women with higher disposable income prefer to diversify their resource base to less risky investments. The probit model results also showed a positive and significant relationship between female participation in agriculture and extension services. Based on these, the study recommends that there should be an improvement in extension services, accessibility of inputs and farming technology so as to enhance FLFP in agriculture.Fabiyi et al. (2007) investigated the role of women in agriculture and the constraints for their participation in the Gombe State in Nigeria. Using descriptive statistics, Fabiyi et al. (2007) found that the majority of women engaged in agriculture were middle aged, married and acquired land for farming mainly through their husbands. Another finding was that the majority of women mainly accessed income for farming from cooperatives or from previous season's output. Only 13% had access to bank loans. This study recommends the review of the land tenure system and increased access to credit.Weijland et al. (1988) conducted a study on FLFP in agriculture in the Dominican Republic. He analyzed female participation in agriculture based on the household labor supply model. The findings of the study reveal that the final decision on FLFP is taken at the household level, where the supply of female labor is largely determined by codes of conduct derived from community norms and values. The results obtained in this study showed a positive relationship between FLFP in agriculture and age, innate capabilities, training in agriculture, access to credit and health. The results also showed a negative relationship between FLFP in agriculture and increase in education, rise in nonagriculture income and household size. The study concludes that female participation in agriculture is determined by the farm size, access to non-agricultural wage and access to own land. In an attempt to induce female participation in agriculture, this study suggested that there should be improvements in women access to credit information and agricultural training.Bardhan (1984) discussed FLFP in agriculture for West Bengal. The conclusions drawn from this study are that the withdrawal of females from the agricultural labor force is linked to changes in seasons, uncertainty associated with weather conditions, number of children born to a woman, level of skill and age. The study argues that there is a positive relationship between participation of women in agriculture and lower level of education and skills, low caste households, female-headed households and middle-aged females. Bardhan (1984) concluded that the withdrawal of females from the labor force is not entirely voluntary but in most cases due to discouragement effects of the local labor market conditions such as lower wages and uncertain rainfall. Bardhan (1984) pointed out that improvements in female access to land and income earned in agriculture can encourage the participation of women.The studies carried out in different countries show that FLFP in agriculture is crucial for development. According...
Determinants of Female Labor Force Participation in the Agricultural Sector of Swaziland
This study investigates the determinants of Female Labor Force Participation (FLFP) in the Swaziland agricultural sector. This study uses data from the Swaziland Integrated Labor Force Survey 2007/08 collected by the Central Statistics Office, Swaziland. The methodology used to analyze the data included the use of the probit and multinomial logit models. The findings of the study indicate that... (see full summary)
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