INTRODUCTION
There is a general agreement that poverty is widespread and prevalent
in developing countries. Many studies have also confirmed that the rate
of poverty in the rural areas is higher than in urban areas (De Janvry
and Sadoulet, 2001; Deininger and Olinto, 2001; Escobal, 2001). What is
still a subject of debate however is the best strategy for reducing rural
poverty (Lanjouw, 2001). Several poverty reduction strategies have been
suggested and used in different contexts. In Africa, the focus of poverty
reduction strategies has been on agricultural growth as the pathway out
of extreme poverty. However, unlike in many Asians and Latin American
countries, where agriculture-led growth played an important role in reducing
poverty and transforming the economies, the same has not yet occurred
in Africa. Most countries in Africa have not yet met the criteria for
a successful agricultural revolution and factor productivity lags far
behind the rest of the world. This has led to growing skepticism in the
international development discourse about the relevance of agriculture
to growth and poverty reduction in the region. At least, the Green Revolution,
that worked well elsewhere, was less successful for rural development
in Africa, which was partly due to differences in farming systems, climate
and infrastructure (Ellis, 2000).
The failure of many poverty reduction interventions has been because
they ignored the great diversity and heterogeneity in assets portfolios
across rural households and the range of activities in which they engage
to generate income (De Janvry and Sadoulet, 2001). But, now it has been
discovered that peasant households in developing countries typically earn
income from many different sources (Dercon and Krishnan, 1996; Block and
Webb, 2001). Literatures on income diversification across developing countries
have pointed to the increasing role of off-farm income in poverty reduction
(FAO, 1998; Matshe and Young, 2004) and with increasingly limited agricultural
resources; many have proposed a poverty reduction strategy, which would
focus on the role of the off-farm sector to eradicate poverty and ensure
equitable rural development.
The goal of any poverty reduction strategy is to increase income and
other welfare indicators. Any policy which aim is to increase income must
first understand the composition and determinants of rural income, so
that target interventions can be applied appropriately. This research
examines the income portfolios of farm households in rural Nigeria. It
specifically provides an in-depth understanding of the diverse activities
in which they engage to generate income, the income from each activity
and the factors that affect total income. The study examines whether the
poor differ from the rich households in their income generating activities
and which income activity is more important to the poor households. It
is envisage that the results of the study will contribute meaningfully
to the design of effective poverty reduction strategies that would benefit
the poor households.
MATERIALS AND METHODS
Data used in this research are from a comprehensive household income
and expenditure survey of farm households in Kwara State, North-Central
region of Nigeria. The data were collected between April and August 2006.
Kwara State was chosen as the survey area because of its considerable
socioeconomic heterogeneity and location; it is the gateway between the
northern and southern regions and it has a good mixture of the three major
ethnic groups in Nigeria. These factors tend to encourage the development
of off-farm activities in the area. Apart from this, Kwara State also
has a characteristic of high prevalence of poverty. The nationwide Living
Standard Measurement Survey (LSMS) conducted in 2004 shows that the state
is among the six poorest in Nigeria in terms of income poverty (National
Bureau of Statistics, 2006). Thus, the contrasting features of a thriving
off-farm sector bedevil with a high poverty rate makes the State an interesting
study area.
The total estimated population of the State is about 2.4 million people
out of which 70% can be classified as smallholder farmers. The State has
a total land area of about 32,500 km2, which is about 3.5%
of the total land area of the country, which is put at 923,768 km2
(KWSG, 2006). Approximately 25% of the land area of Kwara State
is use for farming. A humid tropical climate prevails over the state and
it has two distinct seasons; the wet and dry seasons. The farming system
is characterized by low quality but surplus land, low population density
and predominantly cereal-based cropping pattern. Farm enterprises are
generally small in size, so that-and in spite of own production-most households
are net buyers of food, at least seasonally (KWSG, 2006).
The sample consists of 220 farm households, which were chosen by a multi-stage
random sampling technique. Eight out of the 16 local government areas
(the lowest administrative unit in Nigeria) in the state were randomly
selected in the first stage. Then, five villages were randomly selected
from each of the 8 local government areas and finally, five to six households
were sampled in each of the 40 villages, using complete village household
lists provided by the local authorities. Apart from migrant farm workers,
who come from other states on a seasonal basis, all households living
in the villages can be classified as farm households, suggesting that
they cultivate at least a small piece of land. There are no landless rural
households in the study area. The survey questionnaire was designed to
gather information on household composition and other socioeconomic data,
including details on the participation of individual household members
in different income-generating activities. Broadly, I disaggregate activities
and income into seven categories: (i) crop income, (ii) livestock income,
(iii) agricultural wage income, representing earnings from supplying agricultural
wage labor to other farms, (iv) non-agricultural wage income, including
from both formal and informal employment, (v) self-employed income from
own businesses, (vi) remittance income received from relatives and friends
not presently living with the household and (vii) other income, mostly
comprising capital earnings and pensions.
RESULTS AND DISCUSSION
The result of Table 1 show that, the average income
of rural households and the sources from which the income is derived.
The Table 1 also shows how different income sources contribute
to total household income in the sample. In order to better reflect household`s
living standards, the analyses build on per adult equivalent income instead
of total income. The results indicate that all households derive income
from farming, which, however, only accounts for half of total income on
average. The other half is derived from different off-farm sources. Crop
farming, which is mainly subsistence in nature, is by far the most important
single source of income for the rural households, providing about 45%
of total income. This finding is consistent with those of other studies
from similar settings (Dercon and Krishnan, 1996; Van den Berg and Kumbi,
2001; Karugia et al., 2006; Abdulai and Delgado, 1999). Despite
the growing scepticism on the role of agriculture for reducing poverty
among rural household, this result shows that, it remains the major source
of rural income.
More than half of the sample households derive income from livestock
enterprises, but income from this source is only 5% of total income. This
suggests that the type of livestock activities is small-scale, mostly
extensive free range backyard type. Eighty-eight percent of the sample
households in rural Nigeria receive income from off-farm sources and self-employed
income is the most important, accounting for 24% of total income and 48.5%
of off-farm income. Self-employed income is mainly derived from handicrafts,
food processing, shop-keeping and other local services, as well as trade
in agricultural and non-agricultural goods. Forty percent of the households
participate in non-agricultural wage activities, but this source only
contributes 6% to total income. The non-agricultural wage employment includes
formal and informal jobs in construction, manufacturing, education, health,
commerce, administration and other services. The smaller contribution
of non-agricultural wage income to total income could be because of the
little educational and professional qualification of the rural farmers,
which reduce their earning from available non-agricultural activities.
Even though all the sample households have land, about 44% receive income
from supplying agricultural wage labour, which accounts for about 13%
of total income. The phenomenon by which landed farmers, as oppose to
landless farmers, participate in supplying wage labour is common in the
study area. The reasons for this include the need to earn cash income
to meet urgent financial need, reduce income risks and finance farm expansion
(Reardon, 1997; Lanjouw and Lanjouw, 2001). Nearly two-thirds of the households
receive remittances from local and international sources, but it contributes
only 5% to total income. Given that a larger proportion of the households
receive remittance income, which contribute a smaller share of total income,
it would be risky for poor households to rely on this income source. Moreover,
it depends more on the economic situation of the givers. The least important
income source is other income, comprising capital earnings and pensions,
contributing only 1% to total income.
| Table 1: |
Average composition of household incomes (N = 220) |
 |
|
Official exchange rate in 2006: 1 US
dollar = 120 naira. Income estimates are based on annual per capita
incomes expressed in terms of adult equivalents
|
Considering the total income of households participating in the various
income activities, the results show that households participating in self-employed
activities receive the largest annual income per adult equivalent of about
41,247 naira or US $ 344. This indicates that self-employed activity is
the most remunerative and the productivity of family labour is highest
in self-employed activities in the area. However, because establishing
self-employed business require initial investment, households that are
disadvantage in terms of financial capital, will be constraint from reaping
the potential benefit of self-employed activities. Table
2 shows the contribution of household members to total off-farm income
among the sample households. While the household head accounts for the
largest share on average, it becomes evident that there are also significant
contributions by other household members, including the spouse, older
children and other relatives. The contribution of spouses is more through
remittances, while other members contribute more through non-agricultural
wage employment. Both men and women are engaged in all activity categories,
indicating that there are no strict cultural restrictions, although certain
gender patterns emerge when further disaggregating by sectors.
Income Portfolio According to Household Types
Here, income portfolios in a more disaggregated way is described.
Households classification is first by farm size and then by income quartiles.
Table 3 shows percentage income composition by farm size
quartiles. It is worth noting, however, that farm size was not adjusted
for quality. Notably, share of off-farm income increase with increase
in farm size. This shows that farm and off-farm activities are complementary
rather than substitutes. In the study area, land in general is not a major
constraint for increasing agricultural production because permission to
use land is usually granted by the village head and farmers may cultivate
as much land as their capacity permits. Rather, financial capital for
buying farm inputs, machinery, or to pay for hired labor seems to be the
scarcest factor. Given this condition coupled with the failure of rural
credit markets, cash income from off-farm sources can help to pay for
agricultural inputs and expand the farm size accordingly. This is why
households with larger share of off-farm income also cultivate larger
farm size. This result dispute the concern that working off-farm can reduce
agricultural production as a result of competition for family labour between
farm and off-farm works.
The result further shows that share of farm income decreases with farm
size. Among the off-farm income sources, the smallest farms derive higher
share from agricultural wage labor, remittances and other income. This
suggests that these income sources are more important to the small farmers
than larger farmers, for whom non-agricultural wage and self-employment
are more important.
| Table 2: |
Percentage contributions of household members to annual off-farm
income |
 |
| Table 3: |
Percentage composition of annual per capita income by farm
size |
 |
| Table 4: |
Percentage composition of annual per capita income by income
quartiles |
 |
| Table 5: |
Descriptive statistics (N = 220) |
 |
| Official exchange rate in 2006: 1 US
dollar = 120 naira; SD is standard deviation. AE is adult equivalent |
Table 4 shows that for the poorest households, farming
(crop and livestock) is the most important income source, accounting for
over two-thirds of total income. The share of off-farm income increases
with total income, indicating that the richest households derive the largest
income share from off-farm activities. Self-employed activities are exceptionally
important for the richest households. This is not surprising, because
establishing an own business often requires seed capital. The result is
also in line with the earlier one that identifies self-employed activities
as the most lucrative for investing family labor. Remittance and other
income are more important for the poorest households. This suggests that,
targeting the poor with transfer income, could offer some pathway out
of poverty. However, this must be done with caution because of the concerns
that have been raised about the effectiveness of such income targeting
in developing countries.
Determinants of Total Income
Here, the study analyze the determinants of total income at the household level.
This is useful in particular, to understand the factors which affect total income
and why the income of some households is large and others are small. I estimate
a regression model of total income against a set of explanatory variables, using
the Ordinary Least Square (OLS) techniques. The sample statistics of the dependent
and explanatory variables included in the model are shown in Table
5.
Of the eleven variables included in the regression model, six were found
to have significant impact in determining household total income (Table
6). Household size has a positive impact on total income. This is
not surprising, as income is not expressed in per capita term. Every additional
adult equivalent added to the household increases total income by approximately
10,000 naira on average. Farm size positively influences total income
and increasing the land size by one hectare would increase income by about
34,500 naira. The results also indicate that increasing household assets
by 1000 naira would increase total income by 300 naira on average. This
result is quite consistent with those of other similar studies (Karugia
et al., 2006; De Janvry and Sadoulet, 2001).
| Table 6: |
Determinants of total household income (OLS, estimates) |
 |
| *, **, ***Coefficients
are significant at the 10, 5 and 1% level, respectively; The dependent
variable is the total annual household income expressed in naira.
N = 220 |
Expectedly, access to electricity and pipe-borne water influence total
income in a positive and significant way. These social capital are particularly
important because they facilitate the starting-up of an own business and
contribute to higher average incomes from those businesses. Moreover,
the presence of these social capital in the villages could increase economic
opportunities and improve the income earn from both farm and off-farm
activities. Inability to access the market reduces household income. Households
that are located one kilometer farther away from urban market center would
have their income reduced by about 1800 naira. Overall, the results suggest
that household assets and social capital are the significant factors that
affect total income. Education and gender have no influence on total income
in the study area. Provision of social infrastructure as well as empowering
the rural households to enhance their assets position is likely to raise
income and reduce poverty in the area.
CONCLUSION
This study examined income portfolios and determinants of total
income among rural farm households in Kwara State, Nigeria. The results
show that households earn income from many different sources and that
50% of total income is from farming while the other 50% is from different
off-farm sources. While crop farming is the dominant source of farm income,
accounting for about 45% of total household`s income, self-employed activities
are the dominant sources of off-farm income, accounting for nearly one-quarter
of total income. The share of off-farm income increases with increase
in farm size, indicating that there are important complementarities between
farm and off-farm activities in the area. With regard to the question
raised in the introduction, of whether the poor differ from the rich households
in their income activities and which income source is more important to
different type of households, the result clearly show that for the poor
households, farming is the main income source. On the other hand, for
the relatively rich households, off-farm employment and especially self-employed
activities are the main income sources. Econometric analysis shows that
household assets, size, farm size, social infrastructure and market access
are the significant factors that determine total income.
The first policy implication of the results is that agricultural activities
should be promoted, because it remains the major income source of the
rural poor. Despite the growing concern, the findings of this paper demonstrate
that there is scope for poverty reduction through agricultural growth.
Efforts such as distribution of improved seed varieties and better extension
services delivery can help to boost agricultural production. The second
implication is that direct targeting of the poor households for income
transfer should also be considered in designing poverty reduction strategies.
The result shows that apart from farming, the poor households also rely
more on remittance income and targeting them could offer some pathway
out of poverty. Finally, the results of this study indicate that farm
and off-farm activities are complementary rather than substitute and this
dispute the skepticism that working off-farm can reduce agricultural production
due to competition for family labor between farm and off-farm work. Therefore,
there is need for policy instruments that would ensure the simultaneous
development of both sectors. For instance, accessible credit schemes and
provision of physical infrastructure like electricity, pipe-borne water
and market, would increase overall employment opportunities and development
in the two sectors.