Nigeria, a nation once flaunted as the “Giant of Africa”, is at present battling with a rising incidence of unemployment and poverty, with as much as 21.1% of the economically active people reported as unemployed in 2010 (NBS, [2011]) while 64.4% of the populace lived below the US$1.25 income poverty line in 2008 (UNDP, [2010]). The poor in Nigeria are reported to be predominantly rural dwellers and households that rely mainly on agricultural means of sustenance (World Bank, [2000]; FOS [1999]; NBS ([2012]); Babatunde, et al.[2008]). Moreover, socio-economic conditions in most rural communities in Nigeria are generally poorer that what obtains in the cities: hence rural–urban migration has been a strategy adopted by many in a bid to escape poverty (Okali et al., [2001]).
Evidence in literature suggest that rural urban migration in Nigeria is massive, with as much as about 38% of the economically active members of the rural farm families in Southwest Nigeria reported to have migrated to the urban centres (Shittu, [2011]). This massive rural out-migration has been a major cause of rapid urbanisation and congestion of Nigerian cities; leading to urban squalor and poverty, housing shortages, and pollution (DFID, [2004]), while many that could not find job sometimes resort to crime making most Nigerian cities very dangerous, especially at nights (USAID, [2002]). Moreover, rural out-migrants in Nigeria are predominantly the youths, male-folks and educated members of the rural farm households as well as artisans and other skilled workers in the rural sector (Okali et al., [2001]; DFID, [2004], Shittu, [2011]). Thus, rural–urban migration in Nigeria has meant that the rural areas are often left with a demographically unbalanced population of women, younger children, and older people (Okali et al., [2001]; DFID, [2004]). It also denies the rural sector the much-needed human capital, reduces availability of farm labour (Ogwumike and Aramolaran, [2000]), and thereby tends to weaken productivity and income levels in the sector. The fact that unemployment level in Nigeria is now much higher in the urban sector than what obtains in the rural areas is also worrisome.
Against the above background, there is a rising believe among policy analysts, academia and government functionaries that provision of urban-type employment opportunities in the rural areas may be a veritable means of addressing the multifaceted problem of poverty, urbanisation and unemployment in Nigeria. This view is supported by FAO ([1998]), Matshe and Young ([2004]), and many others that have observed that given the limitations imposed by the fixed stock of land and increasing urbanisation, provision of opportunity for involvement of members of rural farm households in rural non-farm activities might turn out to be a means of creating favourable conditions to reduce poverty in the rural areas. Goldsmith, et al. ([2004]) also observed that growth in the rural non-farm activities might also be used to stem rapid rural–urban migration and the attendant urban poverty in most developing countries.
This paper presents empirical evidences on the types of off-farm employment opportunities available to rural farm households in Southwest Nigeria, returns to household labour supply use within the rural farm and non-farm sectors, and implications of the labour use patterns on farm household production efficiency in the study area. The remaining part of the paper is organised thus: A brief review of literature is presented in Section 2, followed by the theoretical framework Section 3. The study methodology is presented in section 4 followed by the results and their discussions in section 5, while the final section summaries the main evidences and conclusions from the study.
Literature review
A wide range of empirical studies have examined issues relating to off-farm labour supply and the implications on household welfare. Lanjouw and Lanjouw ([2000]), in a review of some of these studies, observed that while the rural non-farm sector was traditionally viewed as a low-productivity sector producing low quality goods that are expected to wither away as a country develops, recent years have seen a shift away from this position towards recognition of the fact that the rural non-farm sector can, and often does, contribute to economic growth, rural employment, poverty reduction, and a more spatially balanced population distribution.
The most common evidence from most studies of off-farm work among farm households has been that income from off-farm work accounts for significant and increasing proportion of total income of farm households in the developing countries (Anderson and Leiserson, [1984]; Jacoby [1993]; Newman and Gertler, [1994]; Lanjouw, [2000]; Escobal, [2001]; Shittu, et al., [2006]; Haggblade, et al.[2010]; Shittu, [2011]; and many other). Recent estimates by Haggblade et al. ([2010]) put the non-farm share of the total income of rural households in the developing countries in the range of 35% and 50%, with the contributions among rural households in sub-Saharan Africa expected to rise significantly in the coming years given the increasing population growth and limited agricultural productivity growth in the region.
Evidences in literature suggest that a key motivation leading to off-farm labour supply among farm households in both the developed and the developing country has been the desire to have a diversified sources of income and manage risk (Chang and Mishra ([2008]). Hazell and Hojjati ([1995]) as well as Chavas, et al., ([2005]), among others, have also reported that given the very weak capital market in most developing countries, many farm households in the often resort to off-farm work to raise cash with a view to relaxing their cash flow and liquidity constraints. This view is supported by evidences in Stampini and Davis ([2009]) as well as Pfeiffer, et al. ([2009]) that reported that households engaged in off-farm activities were able to spend significantly more on seeds, services, hired labour, and livestock inputs, which confirms that off-farm income relaxes credit constraints in agriculture.
Focusing on impacts of off-farm work, available evidence suggests that increased participation in off-farm work among members of farm households is associated with higher incomes as well as improved food consumption, nutrition and food security (Chang and Mishra, [2008]; Babatunde and Qaim, [2010]; Owusu et al., [2011]). It was also reported as linked to significant reduction in variance of total income (Schultz, [1990]) as well as reduction in intensity of agricultural production (Phimister and Roberts, [2006]; Huang et al., [2009]; Shi et al., [2011]; Owusu et al., [2011]) with positive environmental impacts due to reduction in the use of certain agrochemicals that impact negatively on the environment (Phimister and Roberts, [2006]).
Despite the common evidences that income from non-farm sources helps in relaxing financial constraints on farm households and enhancing farm investment, evidences on the impacts on domestic food supply, production efficiency and household welfare, in general, remain quite conflicting. For example, while Lien et al., ([2010]) reported that off-farm income had a positive effect on farm output but no systematic effect on farm technical efficiency, Pfeiffer, et al. ([2009]) reported that off-farm income has negative effect on agricultural output and the use of family labour on the farm, but positive impact on use of purchased inputs and confer a slight efficiency gain on farm households participating in off-farm activities. Shi et al. ([2011]), however, found that the negative lost-labour effect is much stronger than the (small) positive income effect while Holden et al. ([2004]) reported that access to non-farm income in less favoured Ethiopian highlands reduces farm households’ incentives to invest in conservation and this leads to more overall soil erosion and more rapid land degradation even though intensity of production is reduced.
While Chang and Wen ([2011]) reported that off-farm work is not necessarily associated with lower (or higher) technical efficiency, they noted that farmers with off-farm work face higher production risk. They reported, however, that for farmers in the lower percentiles of the efficiency distribution, those with off-farm work are more efficient than their counterparts without off-farm work. Similarly, Chavas, et al. ([2005]), in a study of farm households in Gambia found that a significant part of a substantial allocative inefficiency that exists in the production systems of the farm households comes from inefficiency in labour allocation between farm and non-farm activities. They noted however, that in the presence of weak capital market in Gambia, off-farm activities acts to relax cash flow and liquidity constraints.
Wandschneider ([2003]) in a review of several studies of non-farm employment in developing countries of Africa and South Asia as well as the Transition Economies observed that a significant proportion of rural households and entrepreneurs in the studied regions do not only lack many of the required assets to successfully engage in non-farm employment, but also operate in a relatively adverse environment, characterised by limited opportunities both within and outside the farm economy. Consequently, he concluded that diversification into non- farm economic activities in all studied regions were largely out of necessity (distress-push) rather than as a response to remunerative wage employment and high return business opportunities (demand-pull). Similarly, Lanjouw ([2001]) in a study in rural El Salvador found that the poor were mainly engaged in "last resort" non-farm activities.
In summary, evidences in existing body of literature seem to suggest that while off-farm income accounts for significant and increasing share of total income of rural farm households in the developing countries, the implications on efficiency of household resource allocation, food supply and overall household welfare remain uncertain, and vary widely by locality and socio-economic environments. While for some, off-farm labour supply might be a response to remunerative wage employment and high return business opportunities, for many, working off-farm may be borne out of necessity to seek ways and means to relax credit constraints, raise supplementary income to complement what obtains from the farm most especially during lean seasons, or otherwise. Therefore, bearing in mind the likely presence of rigidity in rural off-farm labour market and/or reliance on joint technology for farm and off-farm activities among the rural-folks, more empirical evidences are required to assess the implications of off-farm labour supply on efficiency of resource allocation and household welfare. This study is an effort along this direction, with focus on resource poor farm households in rural Southwest Nigeria.
Conceptual framework
The conceptual framework for this study is based on a variant of agricultural household models developed in Chavas, et al. ([2005]). Reliance on agricultural household modelling framework is in recognition of the fact that the semi-commercial nature of smallholder agriculture in the developing countries makes it imperative that the production, consumption and labour allocation decisions of the farm households are interdependent. The framework is further justified given the well-documented evidences of labour market imperfection in the developing countries and/or the fact that farm households may rely on joint technology for their farm and off-farm activities. The framework, as developed by Chavas, et al. ([2005]), may be summarised as follows:
Consider a farm household with m family members making production, consumption, and labour allocation decisions during a specific time period. Let F = (F
1
, … F
m
) and L = (L
1
, …, L
m
) be the amount of labour supplied by the m family members in pursuit of the household farm and off-farm activities respectively; and H, the amount hired labour hired and used in conjunction with the non-labour inputs x (including land) and F to produce the vector of farm output, y in addition to the off-farm income, N earned from L. The technology facing the household is represented by the feasible set X, where (x, F, H, L; y, N) ∈ X means that inputs (x, F, H, L) can feasibly produce outputs (y, N), and farm and off-farm labour productivity is allowed to vary across family members.
If the total amount of time available to any family member over a time period is T; and the m family members can allocate their time between leisure activities I = (l
1
,…, 1
m
), on-farm labour F = (F
1
, …, F
m
), and off-farm employment L = (L
1
,…, L
m
), the time constraint facing each family member can be written as:
If the farm-household consumes goods z, purchased at market prices q, and faces competitive markets for its products and inputs with p as the price vector for farm outputs y, r the price vector for non-labour inputs x, and w the wage rate for hired labour H, the household consumption decisions would be made subject to the budget constraint, which requires that consumer expenditure (q′z) cannot exceed the net farm income (p ′ y - r′x – wH) plus the non-farm income (N). That is:
(2)
Therefore, if it is assumed that household members make production, consumption, and labour allocation decisions under cooperative bargaining, and that members’ preferences can be aggregated into a non-satiated and quasi-concave "social utility function" function U ( z, l ) defined over (z, l) ≥ 0, reflecting their relative bargaining power; then, the household decisions may be analysed based on the following optimisation problem:
(3)
Chavas, et al. ([2005]) asserted that under non-satiation of the utility function U( z, l ), the budget constraint (2) is necessarily binding, and the optimisation problem (3) can be decomposed into two stages: first, choose (x, F, H, L; y, N); and second, choose (z, l).
The first stage optimisation with respect to (x, F, H, L; y, N) can be written as:
(4)
(5)
where (T - l) ≡ (T – l
1
, …, T - 1
m
) are the amounts of time the m family members spend working either on or off the farm. Equation (4) establishes profit maximization with respect to the household choice of (x, F, H, L, y, N), with π( p, r, w, T - l) being the indirect profit function conditional on (T - l).
Chavas, et al. ([2005]) drew attention to the fact that for a given amount of time allocated to work by household members (T - l), a failure to maximize profit would reduce household income, which would restrict consumer expenditure (from equation (2)), and which under non-satiation, would make the household worse-off. Thus, a failure to maximize profit would be inconsistent with household utility maximization.
Furthermore, considering that solution to (4) would yield the profit maximizing input and labour decisions, x*(p, r, w, T - l), F*(p, r, w, T - l), H*(p, r, w, T - l), and L*(p, r, w, T - l) as well as the profit maximizing outputs decisions, y*(p, r, w, T - l) and N*(p, r, w, T - l) that together with the profit function π( p, r, w, T - l) do not depend on consumption levels z, we find that production decisions are "separable" from consumption decisions. Hence, analysis of the production and consumption decisions of farm households can be undertaken separately as a two stage problem, starting with the profit maximisation problem (4) as a first stage optimisation.
The profit function π( p, r, w, T - l) and production decisions, y*(p, r, w, T - l) and N*(p, r, w, T - l) are, however, jointly dependent on the amount of time available for work, (T - 1). Note also that equation (4) includes farm and non-farm activities, both in terms of labour allocation (F and L) and income (p'y and N) at the household level. It involves the general technology X, allowing for joint household decisions between farm and non-farm activities. Hence, decisions on labour allocation between farm and off-farm activities are dependent, and have to be jointly resolved within the profit maximisation problem (4). Chavas, et al. ([2005]) pointed out that examples of jointness in farm and off-farm activities include skills acquired in non-farm employment that improve farm management, and non-farm income that reduces the adverse effects of credit market imperfection on farm decisions.
Now, given that utility maximization (3) implies profit maximization (4) as a first stage optimisation, the second stage decisions with respect to (z, l) becomes:
(6)
Equation (5) is a standard utility maximization problem subject to the household budget constraint. Combining the two stages (4) and (5) is fully consistent with utility maximization (3). Chavas, et al. ([2005]) noted that the profit maximization (4) is the relevant framework to analyse production efficiency at the household level. They observed that in the presence of market imperfections and/or poor managerial skills, it is possible that households may not behave in a way consistent with (4) because they do not or cannot respond to economic incentives. They concluded thus, that economic analysis based on (4) could yield useful insights into the nature and causes of economic inefficiency. They stressed further, that the profit maximization problem (4) implies the following revenue maximization:
(7)
where R(p, x, F, H, L, X) is the revenue function, conditional on inputs (x, F, H, L). This suggests that analysis of production efficiency of farm households that exhibits significant off-farm labour market participation can be undertaken by focusing on output decisions, conditional on available inputs (x, F, H, L). Chavas, et al. ([2005]) pointed out that equation (6) assumes only well-functioning output markets. And, that this is important in the sense that analysis of farm household production efficiency, such as would be undertaken in this study, remains valid in the presence of factor market imperfections.
Given a representation of the production possibility frontier of a household involved in both farm and off-farm activities that is characterized by the use of inputs (x, F, H, L) in producing outputs (y, N). Chavas, et al. ([2005]) observe that the output based technical efficiency index, TE, is defined as:
(8)
Where 0 ≤ TE ≤ 1, and TE = 1 when the household is producing on the production frontier and is said to be technically efficient, while TE < 1 shows the farm is not technically efficient.
Similarly, the allocative efficiency index, AE, with respect to farm outputs may be defined as:
(9)
where (y/TE, N/TE) is a technically efficient output vector. In general, 0 ≤ AE ≤ 1, where AE = 1 represents a revenue maximizing firm that is allocatively efficient with respect to outputs, and AE < 1 shows that the farm is not allocatively efficient.