|Rural Non-Farm Employment: A Survey(1)
March 24, 1995
Jean O. Lanjouw and Peter Lanjouw
Yale University and The World Bank
A. Why Are We Interested?
The rural non-farm sector is a poorly understood component of the rural economy and we
know relatively little about its role in the broader development process. This gap in our
knowledge is the product of the sector's great heterogeneity (see Box 1 for examples),
coupled with a dearth, until recently, of empirical or theoretical attention. As expressed
by Liedholm and Chuta (1990, pg 327) "...policy makers and planners charged with the
formulation of policies and programs to assist rural small-scale industry in the Third
World are often forced to make decisions that are 'unencumbered by evidence'." In
fact until recently, a commonly held view has been that rural off-farm employment is a low
productivity sector producing low quality goods. As such, it was expected to wither away
as a country developed and incomes rose, and its withering was seen as a positive rather
than a negative occurrence. A corollary of this view is that government need not worry
about the health of this sector in a pro-active sense, nor be concerned about negative
repercussions on the rural non-farm sector arising from government policies directed at
other objectives. More recently opinion has swung away from this view, and there are a
number of arguments which suggest that neglect of the sector would be mistaken. For
example, the sector's role in absorbing a growing labor force, in slowing rural-urban
migration, in contributing to national income growth, and in promoting a more equitable
distribution of that income, warrants further scrutiny.
Agriculture Cannot Employ a Growing Rural Labour Force.
In many developing countries a large proportion of the population lives in rural areas,
and this population continues to grow at a substantial rate. For example, in Bangladesh
the rural labour force is projected to grow at over 3 percent annually over the next
decades (Hossain, 1987). Given limits to arable land, such growth rates in the rural
labour force will not be productively absorbed in the agricultural sector. A cursory look
at the historical fall of the agricultural labour force in developed countries makes this
clear. For example, the percentage of the labor force employed in the agricultural sector
fell from 35 to 5 percent (1801 - 1951) in Great Britain; from 28 to 17 percent (1899 -
1947) in the Netherlands; from 68 to 12 percent (1840 - 1950) in the United States; and
from 85 to 33 percent (1872 - 1960) in Japan (Kuznets, 1966). This leaves migration to
urban areas or the development of non-farm employment in rural areas to take up the slack.
Not only does an increasing level of urbanization impose various social costs (see below),
but it has become amply evident that the large-scale urban industrialization strategies
pursued by many developing countries in previous decades have failed to absorb a growing
A Role to Minimize Migration
The simple observation that enterprises often tend to congregate in urbanized areas in
most countries, and to be large in scale, suggests that there are certain positive reasons
for this to happen. In the literature concerned with economic growth these reasons would
fall under the heading of the benefits of scale, scope or agglomeration. A large local
market, a locally available skilled workforce, a wider variety of production inputs,
technological spillovers and lower costs to the provision of infrastructure are a few
examples of the latter and they are real (social) benefits of concentration.
There are, however, private reasons for industry to thrive in urbanized environments
which do not reflect benefits to society. Some of these are created by governments. For
example, requiring firms to obtain licenses for production or foreign exchange makes it
advantageous for them to locate near government offices. The provision of high quality
physical and social infrastructure in urban areas to an extent not warranted on the basis
of lower costs is a phenomenon commonly observed in developing countries, and ascribed to
the presence of a political elite in cities. This lowers the relative costs of urban-based
production in a way which is socially costly. Perhaps most important, however, in causing
a divergence between private decisionmaking and social benefits is the fact that firms do
not incorporate most of the negative externalities, such as congestion, pollution and
higher land values, that they impose when they decide to locate in a city.
Rural-urban migration flows have been substantial and persistent. Over the period
1960-80, rural out-migration and urban in-migration have been estimated at 1 and 1.8
percent annually for the forty developing countries with available data (Williamson,
1988). For the same countries, projected figures to 2000 are approximately 1.5 and 2.5
percent, respectively. For some countries the rates are much higher. For example, during
the 1970's, Nigeria and Tanzania are estimated to have had 7.0 and 7.5 percent increases
in urban population annually with over 60 percent due to rural-urban migration (Todaro,
1994). Most governments have voiced concern about this relocation of people. In a U.N.
survey of developing country governments in 1978, only six of 116 respondents deemed the
country's spatial distribution of population 'acceptable'. Similar results were found in a
1983 survey (Williamson, 1988). As a result, many countries have expressed an interest in
developing economic activity in rural areas to encourage the population to stay in the
countryside. This concern is shared by donor agencies and particularly non-governmental
organizations (NGO's) who have become active in programs of credit, training and technical
assistance to both rural and urban small-scale enterprises (see, Meyer, 1992, and section
As a Contributor to Growth.
Parallel to the arguments made above about location decisions are arguments concerning
production technology choices. It is often pointed out that for a number of reasons, often
artifacts of government policies, relative factor costs diverge between rural and urban
areas. The factor costs facing rural-based enterprises are thought to more accurately
reflect the social opportunity costs of those factors and hence the labour intensive
technologies used in rural locations are more socially "appropriate". That is,
they are more productive when inputs are measured in terms of their real, social, costs.
Even if such activities do not generate very high labour income, in an environment with
seasonal unemployment, any utilization of labour can contribute to raising total income.
And there is always a time frame issue - withering need not be rapid. If total production
in the sector can be raised in a cost effective manner then for many years it can make an
important contribution to national income.
There are several distributional reasons to focus on this sector (given that
redistribution via taxes and transfers is politically and administratively costly in all
countries). Firstly, to the extent that rural industry produces lower quality goods which
are more heavily consumed by the poor, good health of this sector has indirect
distributional benefits via lowering prices to the poor. Second, the sector fulfills two
other functions - it is a residual source of employment to the poor who, because they are
small landholders or are landless, cannot find sustenance in agriculture. Through
diversification it also supplies a way of smoothing income over years and seasons to
people who have limited access to other risk coping mechanisms such as savings/credit or
The fairly scanty evidence concerning the productivity and distributional
characteristics of the sector will be examined in turn in sections II and III below.
Section IV considers the dynamic potential of the sector and, in conclusion, Section V
examines the role for policy. But first we look at some aggregate statistics which
demonstrate that, whatever withering may occur in the future, the rural non-farm sector is
currently large, and even growing, in most developing countries.
B. Overview of the Non-Farm Sector
The non-farm "sector" includes all economic activities except agriculture,
livestock, fishing and hunting. Since it is defined negatively, as non-agriculture, it is
not in any sense a homogeneous sector (see Box 1). For convenience, however, the term
sector will be retained. Judgements about the viability and importance of the rural
non-farm sector hinge crucially on what is meant by "rural". We will illustrate
in this paper, for example, non-farm activity undertaken by farm households as independent
producers in their homes, the subcontracting of work to farm families by urban-based
firms, non-farm activity in village and rural town enterprises, and commuting between
rural residences and urban non-farm jobs. For example, Basant (1994) finds, in a survey of
rural employment in the Indian state of Gujarat, that 25 percent of rural male
non-agricultural workers commuted to urban areas for work. See Box 2 for a somewhat
unusual example of this phenomenon.
Many different definitions of rural are used in the collection of census and survey
information making comparisons across countries difficult. Typically, the distinction
between rural and urban employment is based on the place of residence of workers, so those
who commute to a job in a nearby urban center are considered to be rural workers. Rural is
most often defined to include settlements of about 5,000 or fewer inhabitants. However,
the definitions of a rural locality, based on population size and/or functions and
characteristics of the settlement such as whether it has a school or hospital, do vary.
For example, in Table 1, which displays aggregate statistics for a number of countries
based on their own definitions of rural, the definitions range from Mali and Zimbabwe,
which limit rural to settlements with less than 3,000 and 2,500 inhabitants respectively,
to Mauritania, which includes settlements with under 10,000, to Taiwan, which excludes
only cities over 250,000 and two suburban counties surrounding Taipei (for further
definitions see Haggblade, et.al., 1989). Clearly, a more limited definition of
rural lowers the percentage of employment which is found outside of agriculture.
A number of features of the data suggest that the percentage of rural employment found
in the non-farm sector may be underestimated for all countries. The figures in Table 1
refer only to primary employment. As will be discussed below in section III, one of the
important roles of non-farm activities is to provide work in the slack periods of the
agricultural cycle. Thus, primary employment status will be an underestimate of the actual
percentage of labour hours which are devoted to non-farm activities. After surveying farm
management surveys and time allocation studies of African farm households, Haggblade, et.
al. (1989) conclude that 15-65 percent of farmers have secondary employment in the
non-farm sector and 15-40 percent of total family labour hours are devoted to
income-generating non-farm activities. Note that this is income-generating activities.
Much of non-farm activity in all developing countries, especially that of women, is
unremunerated work, such as clothing production, food processing and education for the
household, which is not included in employment figures. As countries develop, more of
these tasks are commercialized and more non-farm employment appears in the statistics
(although the problem never disappears - see Thomas, 1992). This is a second reason to
expect an underestimate of non-farm activity. Finally, since rural enterprises are
typically small and dispersed there is reason to think that they may simply be missed in
surveys. (Anderson and Leierson, 1980, note that in some African countries
under-remuneration has been as high as 40 percent.)
Bearing these considerations in mind, it is clear from Table 1 that the non-farm sector
is substantial in many countries - both in terms of income and employment - and has, in
the aggregate, been growing over time. For example, in China non-agricultural employment
grew from 11 percent of total rural employment in 1980 to 20 percent by 1986. Town and
village enterprises (private and communal ownership in localities with less than 30,000
inhabitants) increased real output and employment at annual rates of 23.4 and 12.7 percent
respectively over the period 1978-86, with employment in manufacturing increasing at 7.7
percent. In fact, TVE's have been veritable "engines of growth" for the Chinese
economy. As indicated in Table 1, the non-farm sector is composed of services, commerce
& transport, construction and mining, and manufacturing. There is some evidence to
suggest that there is a shift in composition towards services and away from manufacturing
in the smallest localities as development proceeds (see below).
We turn now to take a closer look at those characteristics of activity in this sector
which affect its contribution to social welfare, either through income growth or through
positive distributional features.
II. Characteristics of the Non-Farm Sector - Productivity
A. Measures of Productivity - Theory
An important question when considering the potential contribution of non-farm activity
to development is whether or not such activity is more or less efficient in converting
resources into output relative to its urban counterpart or agriculture. In studies of
productivity three measures are commonly used. The first two are partial measures: labour
productivity, which measures the value added by an activity (gross output deducting
intermediate inputs, but not deducting capital and labor costs) per unit of labour input,
and capital productivity, which measures the value added per unit of capital input. By
making comparisons based on one of these partial productivity measures, say labour
productivity, one is implicitly treating the other input, capital, as having a zero
opportunity cost. If both resources are scarce, then one must turn to an aggregate
productivity measure such the social benefit/cost ratio. This measure expresses value
added as a ratio of the weighted sum of labour and capital with weights based on their
social opportunity costs. Of course, if one activity has both higher labour productivity
and higher capital productivity then switching resources to it will increase the overall
output of the economy. Typically, however, higher labour productivity comes at the expense
of lower capital productivity as the amount of capital per worker is increased, and hence
an aggregate measure is necessary.
The assessment of opportunity costs (either private or social - shadow - costs) is
important in comparing productivity across activities even when one is using partial
productivity measures. Inputs (and outputs) must be valued. While commonly an average
agricultural or urban wage is used to value labour and some common interest rate is chosen
to value capital, in fact opportunity costs, both private and social, will typically not
be reflected in these prices and are likely to vary across localities, households, gender,
etc., particularly when markets are very imperfect. For example, in a situation with
minimum wage legislation or wage rigidity leading to unemployment, it is often preferable
to assume that labour has a zero opportunity cost - despite positive market wages. More
generally, it may be quite difficult to know what wage or interest rate reflects the true
opportunity cost of labour or capital inputs in any given situation. It is not always
clear, for example, that capital has a high opportunity cost even when credit is very
expensive. Where there are large transactions costs in financial markets, the interest
rate for someone attempting to borrow may be vastly higher than the potential returns
available to the same individual if he has some small savings. If the financial markets
are so imperfect that it is not possible to invest savings except in one's own enterprise
then labour use and capital use are linked. The prevalence of self-employment using
exclusively own (or family) capital in rural non-farm activities, combined with very
rudimentary or non-existent savings institutions in many rural LDC contexts, suggests that
this may often be the case. Then the opportunity cost of the use of savings is zero and
labour productivity would be an appropriate measure of total productivity (see,
Social Versus Private Values
Private and social values do not necessarily coincide. A systematic divergence between
private and social values is used to argue in favor of government promotion of certain
sectors or technology choices, for example, in favor of policies to support small-scale
enterprises (SSE's). It is claimed that SSE's are more labour intensive and that the lower
labour and higher capital prices faced by small-scale firms correspond more closely to the
inputs' true relative scarcities (see section IV). For this reason, the relative factor
proportions in smaller enterprises are more 'appropriate' and they should be encouraged.
Since rural firms tend to be more concentrated in the smaller sized categories this
argument would apply to the rural/urban distinction as well. (Much of the information
available on productivity is with respect to the small-scale versus large-scale
distinction rather than rural/urban, and concerns manufacturing.) In the productivity data
which follow we shall see that there is a wide range of productivity levels across
activities in the rural non-farm sector. How these are evaluated depends on an assessment
of social opportunity costs.
B. Measures of Productivity - Empirical
Considering manufacturing, it is commonly found that small-scale enterprises generate
more employment per unit of capital than do large-scale enterprises (except for, perhaps,
the smallest units). However, they do not always succeed in producing higher output with
the greater inputs. In a survey of the literature on this issue, Uribe-Echevarria (1992)
notes that, contrary to popular belief, small-scale firms have often been found to be
inefficient users of capital. Little and others (1987) summarize the results of studies in
several countries (rural and urban). They conclude that in general there is not a linear
relationship between either capital per worker or capital productivity and firm size, when
size is measured by employment. It is medium-sized firms (employment over 50) which tend
to have the highest capital productivity (see, for example, Tables 2a and 2b, for Thailand
and India). They note, however, that in their own investigation of Indian data, when
enterprises are ordered by capital size, the expected relationships hold: the smallest
firms are more labour intensive, have lower labour productivity and higher capital
productivity (Table 2b). The choice of technology can be crucial to levels of labor and
capital productivity (see Box 3).
Using data from Sierra Leone, Honduras and Jamaica collected in the late 1970's,
Liedholm and Kilby (1989) address the question of the relative profitability of rural
small-scale firms vs their large-scale urban counterparts specifically. (Small scale is
less than fifty employees.) They calculate social benefit/cost measures for enterprises in
different industries including baking, wearing apparel, shoes, furniture and metal
products. The shadow price of capital was assumed to be 20 percent, unpaid family labour
was (conservatively) valued at the level of wages in the small-scale sector for skilled
workers, and labour in urban firms was valued at 80 percent of actual wages (with the
latter based on survey estimates of minimum wage distortions, see Haggblade, et. al.,
1986). In over two-thirds of the industries, the social benefit/cost ratios for the
small-scale firms were greater than one and higher than the ratios for the urban firms in
the same country and industry (see Table 3). The social benefit/cost ratios for the large
urban firms were often less than one - that is, their production actually decreased social
welfare. Similar results were obtained for industries where output could be valued at
world prices - which reflect shadow values (see Table 3, figures in parentheses). It was
also found that the productivity of rural enterprises was lower for those operating in
localities with populations less than 2,000 and for firms with one person. In fact, in
Honduras, output per hour in one-person firms was 53 percent below wages in small-scale
industry overall and 11 percent below the agricultural wage (Liedholm and Mead, 1987).
It is clear that the non-farm (or small scale) sector is very heterogeneous, comprised
of activities with a wide range of labour and capital productivities. One can think of two
rather different groups of occupations: low labour productivity activities serving as a
residual source of employment, and high labour productivity (and hence income) activities.
A study of Java notes the wide range of returns to labour in the non-agricultural sector :
"owners of brick and coconut plants cleared fives times as much as a successful
farmer, daily wages in some seasonal work would not purchase 100 grams of rice"
(Alexander, et. al., 1991). White (1991) investigating historical Indonesian data
from the early years of the century, notes that when agricultural wages for men were 15-30
guilder-cents per day and for women 10-20, wages in cottage industries were generally less
than 10 and as low as 2-3 cents per day. Based on a more recent 1981/82 survey of a
Javanese village, Ines Smith (1988) describes the role of anyaman, bamboo
weaving, as a source of income for 30 percent of households. She points clearly to its
residual employment character, both because earnings were very low - below casual
agricultural wages - and because of the attitude of villagers. They were always seeking
alternatives and when such were found, the bamboo weaving was dropped. On the other hand,
Du (1990) reports that the average annual per capita income in (rural) town and village
enterprises (TVE) in China was Y726 in 1985 versus Y351 in agriculture. Hossain (1987)
details daily wage rates and capital/labour ratios for 14 major cottage industries in
Bangladesh (see Table 4). Six of the fourteen activities yield daily wages which are lower
than the agricultural daily wage (12.24 Tk.) while the higher productivity activities,
such as carpentry and handloom weaving, generate daily wages over 50 percent above the
agricultural wage. The table also shows a positive relationship between capital per worker
and wages and the negative relationship between female workers and wage rates. Similarly a
study of two regions in Uttar Pradesh, India, in 1985 finds that value-added per worker
ranges from about 600 Rs/year in oil crushing to over 11,000 in cane crushing (Papola,
1987). The data on wages presented in Table 5 is drawn from a survey of cottage industries
in three provinces in Thailand in 1980/81. The returns to labour per hour indicated in the
table may be compared to a 20-30 Baht per day wage rate for farm labour. Clearly there is
wide variation by region and by type of cottage industry. The high productivity
activities, Thai noodle making and wood carving, are more capital intensive and more skill
intensive, respectively, and face healthy demands. Low productivity silk and cotton
weaving are activities dominated by women, generally under subcontract, with considerable
competition from factory made substitutes (especially for cotton) and a large pool of
III. Characteristics of Non-Farm Employment Sector - Inequality and Poverty
As discussed in the previous section, there are at least some activities in the
non-farm sector which give workers low returns even relative to casual agricultural wage
labour. This is particularly true for non-farm labour performed by women. This employment
may nevertheless be very important for the welfare of households for the following
A. The Distribution of Non-Farm Jobs
It is impossible to say whether the opportunity to engage in non-farm activities is
income inequality increasing or decreasing without information about what the situation
would have been in the absence of such occupations. Nevertheless, there is a strong
presumption that if the bulk of non-farm incomes goes to the richer segments of society
then it is inequality increasing and vice versa. Of course, even if non-farm jobs widen
the distribution of income, this does not mean that none of the poor will benefit.
The evidence here is very mixed. In some cases one sees the poorer/landless getting a
higher percentage of income from non-farm occupations suggesting an equalizing influence
and poverty alleviating role. This has been shown for Japan, Taiwan and South Korea.
(Table 6 provides details for Japan.) The table shows that the largest land-holding
households in Japan, which corresponds to the highest income households, receive the
smallest percentage of income from non-farm sources. An equalizing impact has also been
found in studies of Kenya, Botswana, Nigeria and the Gambia (Bagachwa and Stewart, 1992).
Other studies show that the relationship between non-farm income and total income or
assets is U-shaped. This fits into the residual employment/ productive sector dichotomy,
with better off households (either ex-ante or ex-post) involved in the latter. Hazell and
Haggblade (1990) present Indian data which shows that in the mid-1970's the wealthiest and
the poorest households (per capita) had the highest shares of income from non-farm
sources, business income in the case of the rich and wages for the poor. On the other
hand, White (1991) finds that in Java it has been the land-rich households which have
received the largest returns from non-farm enterprises (see Table 6). In Kutus Town,
Central Province, Kenya, a survey of 111 farm households found that the wealthier
benefited most from earning opportunities outside agriculture with the richest quartile
receiving 52 percent of income from non-farm sources compared to 13 percent for the lowest
quartile (Evans and Ngau, 1991). Reardon, et. al. (1992) found a similar result
for Burkina Faso, with total household income strongly positively correlated with the
share of income derived from non-farm sources. A recent study of of Vietnam found that the
lowest level of poverty in rural areas is among households whose income stems solely from
off-farm self employment (van de Walle, 1994). In the North Indian village of Palanpur,
the poor have not been direct beneficiaries from an expansion of employment opportunities
outside the village (although indirectly they may well have benefitted -- see Box 4).
Where individuals are involuntarily unemployed, i.e. looking for agricultural
employment at the prevailing wage rate but not finding it, then the agricultural wage is
not the opportunity cost of labour. There is evidence from India that agricultural wages
are rigid and that this situation persists even in the peak seasons. The following two
studies, cited in Dasgupta (1993) are indicative. Analyzing household survey data from
West Bengal, Bardhan (1984) estimated that unemployment among male casual workers was 8 to
14 percent in peak and 23 percent in slack seasons, and for female casual workers 20
percent in peak and 42 percent in slack seasons. Data from six villages in the semi-arid
regions of India (ICRISAT) in the mid-1970's yields average estimates of unemployment
(based on frustrated job search) for males of 12 and 39 percent in the peak and slack
periods, and 11 and 50 percent for females respectively (Ryan and Ghodake, 1984). There
are many theories as to why wages should be inflexible including various efficiency and
nutritional wage theories, imperfect information theories, and resistance on the part of
workers themselves (see Dasgupta, 1993, and Drčze and Mukerjee, 1989). With involuntary
unemployment of agricultural labourers, even low wage employment outside of agriculture
may be very crucial in raising the living standards of the poorest, particularly those who
do not have other resources, such as family, to fall back on. The fact that people take up
low productivity occupations suggests that they, at least, view them as worthwhile.
In many countries the ability of women to work outside the home is limited. Thus their
opportunity cost of time also bears little relation to the agricultural wage and, for the
poor, may be very low. Where data are available, Table 1 indicates that non-farm
employment is important to women in many countries (and as noted, the figures are likely
to be particularly downward biased for women).
Cottage industry, where work is performed in the home, is particularly useful from the
point of view of mixing with other occupations, such as preparing food and caring for
children. A study of eleven villages in Bangladesh in 1979/80 (Hossain, 1987) found that
employment in cottage industries was close to a full-time occupation for men in many
activities while it was most often a part-time occupation for women - despite the fact
that women rarely worked in agriculture (the main exception being pottery where women are
engaged full-time). This is clear from Table 7 which presents the distribution of working
hours for workers engaged in various cottage industries. Family responsibilities clearly
occupy a large part of women's time. The activities which have a majority of women workers
are those located inside the home - rice husking, mat making, coir products and net making
- where participation does not require breaking social customs. Studies also show African
women dominating activities which can be undertaken in the home. Examples are beer brewing
in Botswana, Burkina Faso, Malawi and Zambia; fish processing in Senegal and Ghana;
pottery in Malawi; rice husking in Tanzania and retailing and vending in general (Bagachwa
and Stewart, 1992). Boxes 5 and 6 provide examples of cottage industries, where women are
able to earn incomes from activities at home.
The peaks and troughs in labour demand from agriculture mean that many people in rural
areas are seasonally unemployed. In 1983, a labour force survey in Thailand estimated that
20 percent of the workforce was underemployed due to seasonal variations (Romijn, 1987).
As a result, for both men and women much non-farm employment is secondary, versus primary,
(regular versus semi-regular) performed in the off-season. Again, in the slack season
there may not be any agricultural employment so even a low productivity occupation can be
useful to raise and smooth income over the year. On the other hand, it is important to
realize that the types of employment which are available on a seasonal basis are limited.
Capital (both human and physical) intensive activities are not likely to be undertaken
seasonally because it leaves capital underutilized during the agricultural peak season.
This in turn means that labour productivity will rarely be very high.
Box 7 details four cottage industries in Thailand where employment is primarily under
subcontracting arrangements. Most of these activities are secondary and provide additional
household income during the slack seasons. As a result of such non-agricultural
employment, the variation in household labour utilization over the year is considerably
smoothed. The wages paid are very low (see Box 7) but they are preferred to the
alternative of being unemployed. Interviewers were told that, despite the low pay, people
would work more if it were available (Mead, 1982). Other data from Thailand (discussed in
Romijn, 1987) indicates that 90 percent of wicker workers, 74 percent of wood carvers and
78 percent of handloom weavers are also involved in farming.
In addition to smoothing the flow of income received by agricultural households over
the cropping cycle, non-farm income may stabilize income by spreading risk through
diversification. A smoother flow of income directly increases welfare at a constant level
of income (making the standard assumption that utility functions are concave in
consumption). It is common to see households deriving income from multiple sources. In
China, for instance, most TVE workers retain rights to agricultural land and many work
part-time in farming (Du, 1990). Both seasonal smoothing and risk diversification can be
very important in environments where agricultural output varies greatly over the year and
across years and where mechanisms for smoothing income, such as credit and transfers, are
costly or absent. The fact that villagers are concerned about risk is indicated in a study
by Morduch (1993) of ten Indian villages in the semi-arid tropics (ICRISAT) over the
period 1976-84. He found that households which were estimated to be more constrained in
their ability to obtain consumption credit when faced by a bad harvest were more likely to
minimize the possibility of a bad harvest in the first place. They scattered their plots
more widely and chose a more diversified cropping pattern.
The opportunity to earn non-farming income can lead to higher average agricultural
incomes in two ways. First, if there are several production technologies or crops, with
higher average productivity being associated with greater variability in output, then
having an alternative source of income which does not fall with a bad agricultural outcome
makes farmers more willing to choose the high risk/high return options. (A similar
rationale is posited to explain why larger, wealthier farmers are often observed to be the
first to adopt new agricultural technologies.) Furthermore, in the absence of low cost
credit, additional income from outside farming facilitates the purchase of costly inputs
when they are required to take advantage of high return options. Using data on smallholder
agriculture in Kenya, Collier and Lall (1986) found that crop output was significantly
related to non-crop income and liquid assets after controlling for production inputs. This
suggests that wealthier and more diversified farmers were making higher productivity
cropping choices. It was found, moreover, that non-farm income not only contributed
directly to household resources available for input purchases but was also important for
obtaining credit. In another study of Kenya, the town of Kutus, Evans and Ngau (1991)
found that farm revenue is positively associated with the proportion of land devoted to
coffee (versus maize) controlling for input costs, and that the proportion of land given
to coffee is positively associated with non-farm revenue. It is informative that even the
wealthiest farm families still diversify risk by continuing to grow maize.
Of course, to the extent that the non-farm sector depends on demand derived from local
agricultural incomes, it will covary and will only effectively smooth idiosyncratic risk.
For example, the North Arcot district of Tamil Nadu suffered a severe drought in 1982/83
with a fall in over 50 percent from normal rice yields. Non-farm business income also
plummeted as a result. For nonagricultural households in the surveyed villages, average
non-farm business earnings were 493 (1973/74 rupees) in 1973/74, fell to 19 rupees in
1982/83 and rebounded to 1,094 by the following year (Hazell, P. et. al., 1991a).
Clearly in this case non-farm income was very sensitive to levels of agricultural income.
On the other hand, Reardon, et.al. (1992) report that for three regions in
Burkina Faso, the ratio of the coefficient of variation of total income to the coefficient
of variation of cropping income was 0.61, 0.76 and 0.69, indicating that total income was
considerably more stable than cropping income alone. In most situations, non-agricultural
income will probably be a stabilizing force.
IV. Dynamic Potential
A. Intersectoral Linkages - Theory
In the 1960's, Hymer and Resnick (1969) formulated a model to explain the purported
decline of rural non-farm activities under colonialism. They envisaged an initially
self-sufficient economy producing both agricultural goods and other goods and services,
labelled Z-goods, for local consumption. With the advent of colonial links there would
arrive, on the one hand, new opportunities for exporting cash crops and natural resources
and, on the other, cheap and higher quality manufactured goods available from the outside
world. Both the competition from imports and the drawing off of labour into the growing
cash crop sector would stifle rural non-farm activity. Ranis and Stewart (1993) have
recently extended this model by positing a two part Z-goods sector, with part of the
sector engaged in producing traditional goods and services in households and villages (the
low productivity activities seen above) and the other composed of more modern activities
which are more often located in towns. Once the heterogeneity of the rural non-farm sector
is recognized one can more easily accept that some parts of the sector are dynamic. Ranis
and Stewart contrast the Philippines and Taiwan, and conclude that while the Philippines
experience with colonialism corresponded to the Hymer-Resnick model, Taiwan came through
its colonial period with much of its rural non-farm sector intact (see below). Boomgaard
(1991) documents the disastrous impact of colonial rule on the Javanese textile industry.
There, while the import of colonial goods had a detrimental impact some parts of the
non-farm sector, the sector was simultaneously growing in importance as a source of
residual employment as land became more scarce in the face of population growth.
In the mid-1970's, John Mellor stated an influential and contrary position regarding
the role of rural non-farm activity in a set of proposals for India (see also Mellor and
Lele, 1972, and Johnston and Kilby, 1975, for early contributions). As result of emerging
green revolution technologies he saw a virtuous cycle emerging whereby increases in
agricultural productivity and thus the incomes of farmers would be magnified by multiple
linkages with the rural non-farm sector. These were production linkages, both backward,
via the demand of agriculturalists for inputs such as plows, engines and tools, and
forward, via the need to process many agricultural goods, e.g. spinning, milling, canning.
Consumption linkages were also thought to be important. As agricultural income rose, it
would feed primarily into an increased demand for goods and services produced in nearby
villages and towns. Furthermore there were potential linkages through the supply of labour
and capital. With increased productivity in agriculture either labour is released or wages
go up. And the new agricultural surplus would be a source of investment funds for the
To complete the cycle, growth in the non-farm sector was expected to stimulate still
further growth in agricultural productivity via lower input costs (backward linkages),
profits invested back into agriculture, and technological change. Thus growth in the two
sectors would be mutually reinforcing with employment and incomes increasing in a
In both of these stories, a lack of demand for rurally produced goods is viewed as the
crucial issue. In the first view, demand stagnates as rising incomes are spent on cheaper
manufactured imports. In the second, geographic isolation and the tastes of the rural
population combine to make demand for locally produced goods increase with income. The
following section surveys empirical work which attempts to determine whether there is, in
fact, a positive feedback effect of agricultural growth on the rural non-farm sector and,
if so, how important the various linkages are. In addition to informing the theoretical
debate outlined above, this line of inquiry has been supported by an interest in
calculating cost/benefit analyses of agricultural investments which capture the full set
of regional impacts. It should be noted that, in terms of policy, a finding that
agricultural growth spurs the rural non-farm sector does not, by itself, mean that
agriculture should be targetted, nor does an absence of linkages mean that it should not
B. Intersectoral Linkages - Empirical.
The empirical investigations come in two types. The first is econometric estimates of
the relationship between growth in agricultural income and growth in employment or income
in the rural non-farm sector. These use cross-section or pooled data and so suffer from
the fact that both sets of growth rates may differ across regions for many reasons,
introducing noise which may swamp any relationship which exists. Furthermore, as
emphasized above in section II, there are high and low wage occupations in the non-farm
sector. As agricultural productivity grows, one would expect the residual employed in the
non-farm sector to be drawn into agriculture, lowering employment in the non-farm sector
but raising wages there. On the other hand, if the linkages are operating, higher demand
for non-farm products and investment in the non-farm sector would lead to higher wages and
might draw labour out of agriculture and increase employment in that sector. It is
impossible to predict a priori whether non-farm employment should grow or shrink with
agricultural productivity although in either case wages should rise. In addition, as
emphasized by Ranis, et.al. (1990), the direction of causation is not clear. They
cite evidence from the Philippines that suggests that the presence of modern (although not
traditional) non-farm enterprises has a positive influence on agricultural productivity.
Vaidyanathan (1983) estimated a regression of the importance of non-agricultural
employment in total employment on farming income, its distribution, the importance of cash
crops and the unemployment rate, using several state-level data sets for India. In all
cases he found a strongly significant, positive relationship between unemployment and the
importance of non-farm employment. This means that where agriculture was unable to provide
widespread employment, the non-farm sector played an important role in picking up part of
the slack. The incidence of non-farm employment was also found to be positively associated
with both higher farm incomes and a more equal distribution, pointing to consumption
linkages. Average daily wage rates in non-agriculture are found to be highest in states
with high agricultural daily wages, as expected, a relationship which is confirmed in more
disaggregated district level studies (Hazell and Haggblade, 1990). Overall, wage rates in
the rural non-farm sector were found to be higher than the agricultural wage so the low
productivity residual activities do not dominate the sector - although one might expect
such occupations to be under-enumerated due to their seasonal and self-employed character.
Hazell and Haggblade (1990) perform a similar analysis using state and district level
Indian data in which they also look at the relationship between (total) agricultural
income and rural non-farm income. They interact agricultural income with factors thought
to influence the magnitude of the multiplier: infrastructure, rural population density,
per capita income in agriculture and irrigation. The estimations were done for rural
areas, rural towns (urban < 100,000), and the combined area. They calculate that on
average a 100 rupee increase in agricultural income is associated with a 64 rupee increase
in rural non-farm income, with 25 rupees in rural areas and 39 in rural towns. All of the
interaction terms, except irrigation, increase the multiplier as expected. As a result the
multiplier is estimated to range from .93 in high productivity, more urbanized, states
(Punjab and Haryana) to .46 in low productivity states (Madhya Pradesh and Bihar).
Estimating the same regression with rural non-farm employment rather than income as the
dependent variable they found that an increase in (total) agricultural income by 100,000
rupees is associated with 3.7 more non-farm jobs, 2.1 in rural areas and 1.6 in rural
towns. In another study in India, the North Arcot district in Tamil Nadu, a 1 percent
increase in agricultural output was associated with a 0.9 percent growth in non-farm
employment (IFPRI, 1985).
Ranis, et. al. (1990) report on several micro studies from the Philippines.
For example, an Upper Pampanga River project which roughly doubled net farm income was
associated with a 7 percent per year increase in non-farm employment, 1975-79. Most of the
non-farm activities in the area were consumption based (93 percent), although employment
related to production linkages grew more strongly over the period. Between 1960 and 1975
there were high rates of growth in small rural establishments in areas with rapid
Social Accounting Matrices
The second type of investigation uses social accounting matrices (SAMs) to calculate
growth multipliers from certain structural relationships among agents in the economy. SAMs
trace the circular flow of income and expenditure, on the one hand, and goods and
services, on the other, among households, firms, the government and the rest of the world.
These multipliers can easily be decomposed into portions attributable to the various
linkages. One can address in a detailed manner the question of how income distribution
effects the magnitude of local linkages. The main drawback of SAM multipliers is the
detailed data required for their calculation. SAMs require a (marginal) input/output
table; an account of who receives income, both factor incomes and net transfers; and
information on the marginal expenditure patterns of all agents. When supplies are not
infinitely elastic, then price effects of demand changes must be incorporated. Data this
rich is not available. Information gives way to assumptions and SAM multipliers are left
with something of a blackbox quality. They should be treated with the appropriate
skepticism (see Harriss, 1987, for a critique).
Bell, et.al. (1982) present a study of the World Bank's irrigation project in
Muda, Malaysia, for the period 1969-74. They found that every dollar of extra value added
in agriculture generated an additional 83 cents of value added through linkages. Of this
83 cents, 33 cents could be attributed to production linkages. The study assumes that
supplies of non-agricultural output are perfectly elastic and therefore prices remain
fixed in the face of demand shifts. Agricultural output is assumed to be inelastic in
supply. Further, 'local' refers to any good sold in the region and therefore includes
non-local goods retailed locally. Both of these features tend to bias the multiplier
upwards, so it should be seen as an upper bound.
Using a SAM constructed for the North Arcot district, Hazell and others (1991b)
calculate, using 1982/83 data, that .87 Rs additional value added would be stimulated by a
1.00 Rs. increase in agricultural value added. This result is also under the assumption of
inelastic supplies of agricultural products so the additional value added is in the
non-farm sector - and is similar to the result in Bell et al (1982). Assuming
elastic supplies of agricultural products, the multiplier is an additional 1.18 Rs. of
(agricultural plus non-agricultural) income. Unfortunately, as in the Bell, et.al.
(1982) study, there is no distinction between locally produced and locally retailed
products so it is impossible to say how much of growth in non-farm value-added is commerce
as opposed to manufacturing.
Haggblade, et.al. (1989) compare marginal consumption expenditures for rural
households in Nigeria, Sierra Leone, Malaysia and India (see Table 8). Marginal
consumption of locally produced non-foods is much larger in the Asian studies (about 35
percent versus 15 percent), although marginal expenditure on local products including food
is about 80 percent in all countries. They note that African expenditure on non-food goods
is likely to be biased down more than in Asia because of the higher proportion of
nontraded goods and services. Using a very simple, three parameter SAM model, and
'representative' African data on consumption parameters from Sierra Leone and Nigeria, and
production parameters from surveys in many countries, they calculate agricultural growth
multipliers on the order of 1.5. This means that a $1 increase in value added in
agriculture generates an additional 50 cents of rural income.
Lewis and Thorbecke (1992) present a considerably more detailed SAM analysis for the
village of Kutus (population about 5,000) in Central Province, Kenya, and its surrounding
region (total population, 46,000). They disaggregate production activities into: several
types of agriculture, farm-based non-farm activities (such as basket-weaving, carpentry,
tailoring), rural non-farm (coffee processing), town and other. Non-marketed production is
included. Households are classified according to location in a similar fashion with small
and large land owning farmers, rural non-farm households, and low and high education town
households. Many town households are involved in agriculture, and conversely, farm
households on average obtain barely half of their income from farming with 19 percent of
income coming from town businesses operated by farm families.
The SAM is estimated using marginal expenditure patterns and assuming either infinite
supply elasticities (fixed-price multipliers) or infinite supplies of non-agricultural
commodities and inelastic supplies of agricultural commodities (mixed multipliers) with
excess demands met from imports from outside of the region. Under either assumption,
additional expenditure by large farm and high education town households generates the
lowest impact in terms of regional income growth. Additional production in agriculture
provides the strongest income multiplier effects even for town households, with, for
example, a 1 KSh increase in coffee outputgenerating 1.12 to 1.42 Ksh in regional
value-added (see Table 9, columns 1 and 2). (In value-added terms these multipliers are
even larger and are close to the 1.5 found by Hazell, et.al., 1992.) Farm-based
non-farm activities have stronger linkages than town-based manufacturing. High education
town households benefit most from production increases in all sectors of the economy. In
terms of hired labour employment, the service sector, followed by farm-based non-farm and
manufacturing production, has the strongest employment generating impact (Table 9, columns
3 and 4).
Other evidence is available concerning specific structural relationships which
influence inter-sectoral linkages.
Hazell and Roell (1983) study the Muda project in Malaysia in 1972/73 as well as the
Gusau agricultural development project in northern Nigeria in 1976/77. In this study it is
also assumed that output supplies of non-agricultural products are elastic so there are no
price effects. The share of locally produced items in marginal non-food spending for the
top income decile in Muda was 61% while it was 55% for the poorest. In Gusau increasing
income resulted in a broadly unchanged share of locally produced items in marginal
non-food spending. In Muda, redistributing $1.00 income from the 9th decile to the second
decile was calculated to reduce demand for locally produced nonfoods by about 20 cents,
while in Gusau, aggregate regional demand for nonfoods would not change significantly. The
authors ascribe this difference to the relative isolation of the Gusau villages - pointing
to the important influence of infrastructure on linkages (see below). In both regions it
is the largest farms by size-holding which have the most desirable expenditure patterns
from the point of view of stimulating the local non-agricultural economy.
A comparison of the industrial and agricultural growth in 16 regions of Colombia
1960-75 showed that the larger the share of modern medium/small farming, vs. traditional
or modern extensive farming, the stronger the linkage between agricultural income growth
and industrial production.
Governments often play a large role in transferring agricultural surpluses to the
non-farm sector via trade policies, the underpricing of output by marketing boards, and
government spending patterns. The same is seen at private level. Harriss and Harriss
(1984) report for the town of Arni, Tamil Nadu, south India, that over a period stretching
from 1983 back more than 40 years, about 15 to 40 percent of the starting capital of
non-farm enterprises derived from agriculture (mainly profits plus occasional land sales).
Haggblade, et. al. (1989) estimate that in Kenya and Sierra Leone agricultural
income is the source of between 15 and 40 percent of nonfarm investment funds. However,
they note that the opposite has also been observed in many countries, with non-farm
earnings allowing investments in agriculture (see discussion above under diversification).
C. Dynamic Aspects of Linkages
If we assume that the consumption behaviour of higher income or more urban households
reflects the direction in which expenditure patterns will move as development proceeds
then one can look at cross-sectional data to predict dynamic changes in linkages. In the
Muda study (Hazell and Roell, 1983) about 28 percent of marginal spending by the top 4
deciles was on imported nonfoods while the bottom four deciles averaged 19 percent. In the
Philippines, the elasticity of expenditure on local products (food and non-food) was found
to fall rapidly with income, from .94 for households depending on rainfed upland farming
with an average household income of 3,405 pesos to .435 for nonagricultural households
with an average income of 17,930 pesos (Ranis, et. al., 1990). Note that since
the elasticities are all positive, the demand for local products does increase in absolute
amounts as incomes rise. Hossain (1987) in a study of villages in Bangladesh found that
the demand for imported industrial goods rose at the expense of local manufactures as
incomes increased. Harriss (1987b) reports that in the rural town of Arni, south India,
the relative importance of goods produced in metropolitan factories or wholesaled via big
cities increased from an already high 57 percent of local commodity flows in 1973 to 75
percent by 1983. In the latter year, new urban products had appeared in the markets such
as soft drinks, cosmetics and consumer plastics (Harriss and Harriss, 1984).
There is likely, too, to be a change in the nature of local linkages as development
proceeds. For example, using town-size as a proxy, Hazell and Haggblade (1990) report that
services and cottage industry dominate non-farm activities in rural areas of India with
growth coming in commerce and services as one moves to rural towns, accompanied by a shift
from cottage to factory manufacturing as town size increases. They also note that,
considering only rural areas, the same change occurs as one moves from low to high
productivity states. This transition in types of activities with urbanization was also
found in a detailed study of employment in the city of Bouake, Cote d'Ivoire (population
110,000 in 1970) and surrounding region. Traditional activities diminished rapidly in
importance close to the city. For example, basket making, weaving and pottery comprised
6.2 percent of total employment at a distance of 25+ km from the city but only 1.9 percent
within 10 km. Similarly, the percentage of rural employment provided by manufacturing fell
in Pakistan from 12 percent in 1968/9 to 9.4 percent in 1982/3 and in Colombia from 18
percent in 1970 to 10.1 percent in 1978 (Uribe-Echevarria, 1991). On the other hand, there
are examples of the survival and even growth of traditional handcraft sectors when an
export market is successfully developed (see section V, below, and Box 8).
Vogel (1994) presents a cross-country comparison of SAM production multipliers to
consider dynamic changes as development occurs and incomes rise. The 27 countries included
are grouped as low, middle and high income developing, NICs, and low and high income
developed. Because of the need for consistency across countries and data deficits the SAMs
are highly aggregated and reliant on strong assumptions. Just as an example, six of the
countries did not have any rural household income or expenditure information so the
missing data were simply estimated from figures for other countries. Furthermore,
non-agriculture is not decomposed into rural and urban so one cannot trace the linkages
between agriculture and rurally produced goods and services. Nevertheless, a few points
are interesting. First, at very low levels of development the strongest linkage is through
consumption. The backward production linkages via agricultural inputs become stronger with
development as agriculture becomes more capital intensive. Finally, the forward linkages,
via agricultural processing, are never very strong and decline as processing becomes less
important in the overall economy. The important point is that all of the multipliers
presented here are estimated using data on a country's current state. When using them to
predict the results of more than marginal changes, it must be realized that the
multipliers themselves may change in the process.
Implications of Infrastructure - Competition vs. a Larger Market
In his view of the operation of local linkages, Mellor treated the local area as
isolated, that is, closed to outside demands and supplies. The characterization of rural
areas as isolated is possibly accurate for some goods which are costly to transport, such
as furniture, and for services. However, markets are often integrated regionally and
nationally. Rural firms, for example, typically do not depend only on local inputs. A
shortage of imported production inputs is often cited in surveys of rural firms as an
important constraint on growth. Harriss (1987b) finds that markets may be widely
integrated even with regard to agro-processing, the forward production linkage. For North
Arcot's major agro-industry, leather, she reports that less than 5 percent of hides
originated in the region with the rest coming from urban slaughterhouses in south India or
imported from the north. In the rural town of Arni, over half of the grain supplying
agro-industry and 90 percent of non-grain inputs (particularly silk and cotton) was from
outside the district (with 20 percent of grain inputs from outside the state). She
concludes that with transport available and for goods with a high ratio of value-added to
weight, the location of industry depends not on local demands or input supplies but on
relative labour costs.
Many studies indicate that at least some part of rural expenditure goes to goods
imported from outside the region. For example, a sample survey of Kutus Town, Kenya, found
that, on average, 59 percent of total spending by farm families accrued to Kutus Town and
the surrounding region. However, this spending was almost exclusively for food, services
and purchases of goods produced elsewhere. The remaining 41 percent of spending leaked out
of the region, mainly to Nairobi and the rest of the world (Evans, 1992). Addressing the
question of why agricultural investments in the Muda region of Malaysia have not
stimulated much local industry, Hart (1989) notes the facilitating role of infrastructure
in both changing demands and allowing cheap non-local supplies. She finds in a 1988
village survey that products from Thailand were readily available in local markets
arriving via the North-South Highway. Rural electrification had also generated large
demands for several non-local products, with 70 percent of households owning a television
and 30 percent a refrigerator.
The flip side of this is that rural infrastructure is also crucial to the growth of the
rural non-farm sector. Although improved infrastructure may have a detrimental impact on
rural non-farm enterprise due to competition from outside products and shifts in tastes,
poor infrastructure also imposes serious costs on rural firms. For example, due to
electricity shortages in Wuxi Provence of China, almost every TVE had installed diesel
generators to meet its own needs - at a cost several times that of power transmitted
through the electricity network (Wang, 1990). This is a widely observed problem for all
firms (rural and urban) in developing countries. Two recent surveys of large- and
small-scale manufacturers in Nigeria and Indonesia found that 92 and 59 percent,
respectively, had their own electricity generators - operating at less than 50 percent
capacity (World Bank, 1994). It is a problem which is particularly acute in rural areas
and for smaller firms, raising costs and leaving them less able to compete with foreign or
In addition to lowering costs, good infrastructure in the form of transport links are
essential if non-farm enterprises are to breakaway from dependence on local market demands
and sell to the outside world (see Mead 1984). An evaluation by USAID of six new rural
roads in the Philippines found that the fall in the costs of transportation and broadening
of the market led to a substantial increase in both agricultural and non-farm incomes
between 1975 and 1978 when the roads were built. Further, there was an average net
increase in the number of non-farm establishments in the region of the roads of 113
percent (Ranis, et.al., 1990). In a survey of rural firms in four counties of
China, Byrd and Zhui (1990) note that a large majority of the firms sold more than sixty
percent of output outside their home province. Such sales include sales of final goods
domestically or exports abroad. They may also include subcontracting relationships with
urban (or foreign) firms, an indirect way to tap into a wider market.
Tapping Larger markets - Subcontracting (Putting Out).
Subcontracting is a system whereby a buyer agrees to purchase semi-finished or final
goods from another firm (or household) which it then sells to consumers or to another
producer. A common system in developing countries is for a local "agent" to
contract with households to produce goods which he then sells to an urban firm which then
packages the goods and distributes them domestically or for export. There are many
different arrangements concerning which parties bear the costs (and risks) involved in the
financing of costs during production, ensuring quality, and marketing. The urban-based or
multinational firm has an advantage over households in terms of marketing, both from the
point of view of knowing what larger markets will purchase and because they may have their
own distribution network. It may have less costly access to technical information which
can be passed on to suppliers. By buying in bulk or producing semi-finished goods
themselves, such firms may obtain inputs at lower cost which can be dispersed to household
workers. (See, for example, the case of yarn being advanced or sold to cottage knitters or
unfinished dresses being distributed to cottage embroiderers in Box 7.) Local agents have
an advantage over non-local firms in their ability to chose the best workers and to
supervise work in progress. As a result, the local agent is often expected to ensure
quality. Local agents working as independent subcontractors may also bear the financial
burden of purchasing finished goods from the households and finding buyers. Subcontractors
can supply inputs - knowledge of the wider market and technology, and finance - which are
costly for rural households to obtain. Thus, particularly when expanding sales beyond the
immediate vicinity, rural households may benefit from working under subcontract instead of
trying to produce and sell final products independently. Of course, larger rural
enterprises may be able to take on these roles themselves. For example, Yang (1994), in a
study of a factory producing health-care products in the village of Shenquan, China,
describes how it, in effect, set up an independent retailing arms to purchase the
factory's output and market it in urban centers.
The main advantage to firms gained from choosing a geographically dispersed mode of
production via subcontracting is lower labour costs (other potential advantages of
subcontracting include the ability to pass on fluctuations in output demand and cheaper
inputs due to greater specialization and economies of scale on the part of suppliers -
Mead, 1984). By subcontracting, a firm can utilize labour hours where the opportunity cost
of labour is close to zero - either by subcontracting in regions with unemployment or by
supplying work which can be done by women at home or in the agricultural slack seasons
(see above). At the same time, the firm can capture some of the benefits of an urban
location. This strategy will only be cost effective in certain sectors, for instance where
the (unskilled or traditionally skilled) labour component is high, where the capital
requirements are minimal, and where transport costs are relatively low.
Getting a handle on how important subcontracting is as an employment contract is
difficult because such work is often supplementary (and hence does not appear in labour
force surveys of primary employment) and because outworkers are often not registered and
do not appear in enterprise surveys. However, sectoral studies indicate that
subcontracting is quite prevalent in certain industries such as clothing manufacture. Box
7 details the operation of some cottage subcontracting arrangements in Thailand. In all
cases local agents (who may themselves be operating on a subcontract basis) act as
intermediaries in subcontracting out work to village households. In the case of bamboo
weaving we see local we see local subcontractors taking on a financing and marketing role
as the wealthier village producers of bamboo goods purchase from their neighbors and sell
the goods on to urban buyers.
Subcontracting systems are not just limited to cottage workers in backwards regions of
poor countries. They can continue to be important as a country develops. Japan, for
instance, stands out among developed countries in its continued heavy reliance on
subcontracting relationships between small and large-scale firms (representing perhaps a
third of all employment). Paine (1971) suggests that this pattern is the result of the
need to introduce flexibility into the otherwise very rigid lifetime employment system
introduced in Japan after World War I. Taiwan is often discussed among developing
countries as an example of the successful development of a geographically dispersed
industrial structure, and subcontracting has been a notable feature of this development.
The initial impetus in the development of rural industry in Taiwan came from agriculture
and was stimulated by a fairly equitable distribution of rural income and investments in
higher value crops. However, the newer rural industries operate on a subcontracting basis
with export oriented urban firms, often using imported inputs, and are no longer dependent
on the local market for growth. Many aspects of Taiwanese policy may have contributed to
these developments. For example, a land reform policy was effectively implemented and
farmers' organizations developed, with government support, which helped farmers to pool
their savings, improve irrigation and obtain new technologies. Unlike most countries,
Taiwan avoided the problem of urban bias in its provision of infrastructure with rural
areas well connected to both electricity and transport networks. Rural industrial estates
and export processing zones were also established at an early stage. All of these factors
are likely to have contributed to an annual 11.5 percent growth in rural nonagricultural
income over the period 1962-80 (Ranis and Stewart, 1993).
Subcontracting among small producers in rural areas is also prominent in certain
industries and regions in other countries. Small producers cluster, often around a town or
small city, and form dense networks with strong divisions of labour. They obtain
agglomeration benefits from proximity to each other while avoiding the large urban areas.
Examples are: Emilia Romangna, Italy; Silicon Valley, California; Baden Wurtemberg,
Germany; Cambridge, UK (Uribe-Echevarria, 1991).
V. Policy Implications: Lessons and Experience
By means of conclusion, this section considers what, if any, role there might be for
government intervention in the non-farm sector. Governmental efforts to support the
development of small-scale enterprises and specifically rural enterprises have
traditionally taken the form of project assistance which is directed at targeted groups.
These efforts have a fairly long history. Financial support programs were launched in
Mexico, Venezuela and Argentina in the 1950's, and in Brazil, Chile and Colombia in the
1960's. These were intended to transform cottage enterprises into modern small-scale
firms. In Africa programmes to support small-scale firms via the creation of industrial
estates and training were initiated soon after independence. The focus of these programs
was often on assisting in the transfer of business from foreign owners to nationals
(Uribe-Echevarria, 1992). Following independence, India followed a strategy of import
substitution, investing heavily in large-scale heavy industry. At the same time,
traditional small-scale industries were protected by reserving certain goods for
production in small scale firms and limiting the capacity of larger firms (see below). In
all cases, however, it was the large-scale urban industrial sector which was expected to
be the real engine of growth. In light of experience, there has been a move away from this
view and new emphasis on more 'balanced' growth, with the development of agriculture and
the rural economy gaining importance. Interest in the non-farm sector is a part of this
focus on rural development.
Nevertheless, in most countries projects to support small-scale and rural enterprise
continue to be undertaken in a general policy environment which is biased against them.
Before turning to targeted projects, we consider the differential impact across firms of
some common policies.
A. Policy Impacts
Input Price Distortions
As noted in section II, there are a number of policies commonly followed in developing
countries which alter the relative labour/capital rental rates such that large (urban)
firms face a higher ratio than small (rural) firms. Some distort the relative costs of
capital, such as subsidized credit and interest rate ceilings, and others distort the
costs of labour, such as minimum wage legislation. Note, however, that the observation
that wages are higher in larger firms and capital costs lower does not by itself imply the
presence of distortions since there may be economic reasons for such differences. For
example, urban labour may be paid more to ensure reliability over the year or it may be
more skilled. Capital costs may be lower because the level of risk is lower, and so on.
That said, some policies are clearly distortionary.
Interest rate ceilings on specified types of loans are imposed in order to give an
incentive to investment. However, interest rate ceilings also make it unprofitable to lend
to borrowers who impose high transactions costs, e.g. those who can provide little
information on credit worthiness and desire small-sized loans, and have little collateral
(and thus represent greater risks). This lowers the potential funds available to small and
start-up enterprises, forcing them to rely more heavily on the informal market at markedly
higher interest rates. While in principle investment credit subsidies would encourage
greater capital intensity of production overall, in practice not all credit is subsidized
and similar biases result. Subsidies are mainly captured by larger firms (especially
urban) and both subsidies and interest rate ceilings lower the cost of capital to large
urban relative to small rural producers. Another indirect impact of government policies
which lower interest rates has been emphasized by Adams (1988). Low lending rates make it
unattractive for financial institutions to develop mechanisms to mobilize small-scale
rural savings (again because of transactions costs) which would then be available for
lending to entrepreneurs. Rural people do save - most start-up capital is from family
resources - and the lack of low cost savings institutions makes the pooling of local
resources more costly.
The common policy of maintaining an overvalued exchange rate with low or zero import
duties on imported capital equipment often has a similar detrimental impact on the cost of
equipment to small-scale producers because their production equipment may not be
recognized as such in the tariff codes. For example, in Sierra Leone, sewing machines, a
crucial piece of equipment for small tailoring firms, were classified as a luxury consumer
good and taxed as such (Leidholm and Chuta, 1990). As a result of such policies, it was
estimated in 1974 that the effective rate of protection, i.e. taking into account tariffs
on both outputs and inputs, for large-scale clothing manufacturers was 430 percent, while
for their small-scale counterparts the effective rate of protection was only 29 percent
(Haggblade, et. al., 1986). Similar biases have been noted in the treatment of
imported raw materials and intermediate inputs. In general, the need for import licenses
hurts both smaller firms and rurally located firms.
Distortionary policies in the labour market include minimum wage legislation, mandated
benefits and labour legislation. These policies are particularly prevalent in Latin
American countries and less so in Asia and Africa. If minimum wages and benefits are
binding (which they are not always) then they serve to raise the cost of labour to
affected firms. Because enforcement is weak, even in countries with labour legislation the
labour market distortion it typically small, except, perhaps, for firms which are very
large and visible and therefore forced to comply. In general, the labor market distortion
is thought to be less than the capital market distortion. Considering both distortions
together, estimates of the percentage difference in the labour/capital rental rates
between small and large firms as a result of government policies range from 43 percent
higher in large firms (South Korea, 1973) to 243 percent higher (Sierra Leone, 1976)
(Haggblade, et.al., 1986).
Policy Stance with Respect to Agriculture
In light of the studies discussed in earlier sections describing first, how off-farm
activities typically form only subset of a household's portfolio of activities (which
usually will also include agriculture), and second, how there exist numerous linkages
between the non-farm sector and agriculture, it is apparent that agricultural policies can
have a pronounced impact on rural non-farm activity. Although the strength of the linkages
between the two sectors varies across regions and countries, virtualy all of the studies
confirm the presence of some relationship. Moreover, while cross-sectional studies suggest
that some of the linkages may diminish over time, they may be critical in the initial
development of the sector. Taiwan and China provide the classic examples. An important
lesson is that while policies aimed at the rural non-farm sector should not be made
without consideration of their impact on agriculture, nor should agricultural policies be
made in isolation. In developing countries, where the policy stance is often implicitly or
explicitly biased against agriculture, it is unlikely that the rural non-farm sector will
B. Project Impacts
Projects rather than policies have been the primary method of encouraging the
development of rural enterprise. The primary difficulty of project assistance, however, is
that small and geographically dispersed enterprises are exceedingly difficult to reach,
particularly in a cost effective manner. And the number of small enterprises is vast -
even the largest projects, such as the Grameen bank in Bangladesh, with more than 630,000
borrowers in 1989 (Hulme, 1990), is thought to reach only a small fraction of potential
"..virtually all small enterprise surveys reveal that only a tiny fraction of the
entrepreneurs have heard of the programs intended for them and even fewer have been aided
by them " (Liedholm and Mead, 1987, page 101).
Project assistance to small-scale and/or rurally located enterprises takes several
forms in terms of targets and type of assistance. Some projects are designed to aid
potential entrepreneurs in starting new enterprises while others assist operating firms to
develop. The former often offer a range of services, both financial and non-financial,
from equipment loans and education in business skills, such as accounting, to advice on
technologies and marketing. Other projects provide one or two components which are seen as
particular constraints to the development of the sector.
By far the most common form of project assistance is targetted credit programs. These
may be operated through government-owned commercial or development banks, private
commercial banks, or NGOs. The record with such projects is very mixed. Loans from
government institutions or mandated lending by private banks tends to end up in the hands
in the wealthiest segment of the targetted group for the reasons cited above under credit
subsidies (e.g. transactions costs). Some projects are quite successful in keeping costs
under control while others are plagued by both high transactions costs and high rates of
default (see table 10). The Grameen Bank, an oft cited project funded by the International
Fund for Agricultural Development (IFAD) which lends to poor women in Bangladesh for both
agricultural, especially livestock, and non-agricultural projects, has a default rate of
less than 1 percent (Hulme, 1990). (However, even at a sixteen percent rate of interest it
does not cover the administrative costs of its small-scale and dispersed lending program.)
The projects which are most successful are locally based, lend to groups, disperse small
initial loans with addition lending conditional on repayment and charge something
approaching realistic interest rates.
Combined Financial and Non-Financial Projects
Experience with projects which attempt to launch new enterprises, offering a range of
services as opposed to simply credit, have been very expensive to implement and very
limited in reach. In a mid-1980's assessment of its microenterprise projects, USAID found
that the average costs per dollar lent in enterprise formation projects was $3.20 compared
to $0.43 - $0.51 in projects to foster existing businesses with more limited non-financial
components. Even the latter, which charged real interest rates over 15 percent, did not
cover operating costs. It was also found that the projects aided only several hundred
clients per year, with the exception of purely financial credit projects which reached
several thousand. Of course, the fact that a project is not financially self-sustainable
does not mean that it is not worthwhile so it is not clear what one should conclude from
this type of information aside from the fact that external (to the project) funding will
continue to be necessary. There is remarkably little systematic analysis of social costs
and benefits given their importance to project design. Leidholm and Mead (1987) discuss
the results of two cost/benefit analyses of projects offering non-financial assistance. In
most cases, the costs were found to exceed the benefits. The successful projects were
those which did not attempt to start from scratch and offer a whole package of services
but rather those which focused on loosening a single constraint, such as providing a new
market or introducing an improved technology. Projects aiding existing rather than
potential entrepreneurs were also found to generate more net benefits.
Apart from credit, particularly for working capital, marketing problems are one of the
most often cited constraints on rural enterprise development. Careful consideration of the
market potential of non-farm activities is very important in project design. Box 8
provides examples of both success and failure in this dimension. As we have seen in the
cases of Taiwan and China, non-traditional rural enterprises can successfully break away
from reliance on a local market by exporting. This can also be true for traditional
handicrafts. In Ghana, for example, handicrafts has recently been a rapidly growing export
sector, growing by 75 percent between 1993 and 1992. This sector has been promoted by
aggressive product and market development by the government (Levy, 1994. See also Box 8).
C. Other Government Programmes Targetted at the Non-Farm Sector
With few exceptions it has been found that industrial estates targeted at the
development of small-scale and rural enterprises have not reached that group, often
because the sites and services provided are too expensive. Uribe-Echevarria (1991) notes
that between 1970 and 1980 rural industrial estates in India grew by 63 percent while
those located in urban and periurban areas grew by more than 200 percent. A rationale
often provided for establishing industrial estates in rural areas in the first place is
that these will act as "growth poles" and stimulate local economic activity.
However, Harriss (1987b) investigates the industrial estates in North Arcot district,
India, and finds first that they are situated not in backward areas but in the more
developed areas of the district and second that they have few local linkages. There are
few agro-industries and their inputs are not local. Little of the production on the
estates is for local consumption. For example, in the case of one estate only 7.5 percent
of output remains in the district and, of that, 75 percent goes to urban areas. Of the
leather industry, 89 percent is exported. Of course, where such firms are intensive in
their employment of local labour, they will still have an impact on the local economy.
India has frequently used the tool of reserving production of specified goods to
small-scale or traditional enterprises as a method of preserving certain sectors in the
face of competition from modern factories. For example, in the 1950's India banned textile
mills from expanding capacity, except for export, and later reserved synthetic cloth
production for small-scale powerloom (less than six looms) and handloom production. The
intention was to support the handloom producers, but since powerlooms were much more
profitable, powerloom production grew four times as quickly from 1956-81. Asking whether
this unintended result of the reservation policy was beneficial, a rough social cost
benefit analysis of powerloom versus mill production by Little, et.al. (1987)
suggest that it was not. Mill production was much more socially profitable than powerloom
production at any plausible shadow wage rate. They note also that while the reservation
policy certainly increased employment in the textile industry directly, it is likely to
have lowered it in the end by destroying the industries export potential. Similar
developments occurred in the sugar industry, where restrictions on mill production have
encouraged an intermediate product, khandsari, rather than the traditional gur industry.
The traditional industry was probably hurt by the policy and cost/benefit analyses suggest
that production khandsari was less beneficial than mill production.
Public Works Schemes
Many of the benefits of non-farm employment discussed in section III have been found
for employment generated by government-run public works schemes. These projects build
infrastructure, primarily in rural areas, and are operated either on a continual basis to
give employment to the poor, or in response to natural calamities such as harvest
failures, to compensate for temporary income falls. The importance of infrastructure for
the development of the private non-farm sector has been noted in section IV. Ravallion
(1991) reviews cost/benefit analyses of two large public works schemes: the Maharashtra
Employment Guarantee Scheme, with an average monthly participation of half a million
(1975-89), and the Bangladesh Food for Work Programme, which was of comparable size in
1990. First, by drawing labour away from other activities, wages in other sectors
increased. Simulations suggest that this indirect benefit of higher wages received by
those not employed by the programs could be as high as the direct benefit to participants.
The opportunity to engage in this non-farm activity stabilized incomes substantially.
Income was found to be fifty percent less variable in villages with a public works program
than similar villages without such a program. Finally, women were able to benefit and had
participation rates as high as men's. Particular features of the employment schemes were
conducive to this result, for example, short travel distances and the provision of child
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From Petty Vendors to ....
From Vendors in Zambia
The charcoal vendor:
She purchases three large bags of charcoal per week and divides them into twenty small
tins each. Net revenue is 12.00 K per week.
The chikanda cake vendor:
She buys chikanda root from another vendor and prepares chikanda "meal" cake
which looks like uncooked sausages. She sells four cakes a week which take one and a half
days to prepare and sell. Net revenue is 22.8 K per week.
The boiled egg vendors:
A partnership of three people. Two of them travel by train to a city 1,000 km away
every two weeks to by fresh eggs. They purchase 75 crates of 30 eggs on each trip and sell
them in the market as boiled eggs. They receive a net profit per week per person of 42.45
To Cigarette Manufacturer in Indonesia
Surya Wonowidjojo began manufacturing hand-rolled kretek cigarettes, a mixture of
tobacco and cloves, as a cottage industry in 1958 in the Javanese village of Kediri,
employing fewer than 50 people. By 1982 the company, Gudang Garan, produced approximately
2 billion cigarettes with a turnover of US $700m and employed 35,000 members of the 90,000
inhabitants of the rapidly growing Kediri. Mr. Surya is a multi-millionaire, and one of
Indonesia's richest businessmen, owner of 5 personal homes and two helicopters.
Sources: Financial Times (March 1983); Milimo and Fisseha (1986).
Mexico: Industrial Estate or Rural Town?
Ciudad Industrial, Mexico, is an interesting hybrid of a small rural city and an
industrial estate. Situated in the middle of the semi-arid Llanos valley, a region of
marginal agricultural productivity and little industrial development, this 'city' was
planned to bring new economic opportunity to local people. In 1952 an automobile
manufacturing plant began producing Fiat automobiles and Dina (Diesel Nacional) buses and
trucks. A government agency was formed to plan and contruct the new city and by 1958 there
were three factories and about three thousand workers producing railroad cars, automobiles
and trucks, and textile machinery (the latter factory was later converted to tractor
production). By 1966, the 'city' had grown to 14,000 inhabitants.
The way in which Ciuadad Industrial was allowed to develop by the planners has given
rise to a somewhat unusual situation. The city has some the typical features of an urban
area - a post office, schools, small shops, a church. However, commercial permits have
been issued sparingly so the business district is quite limited. In addition, cantinas
and other drinking establishments are forbidden so there is a dearth of night life.
Finally, only those with jobs in the factories, administration or the few commercial
operators are allowed to be resident in the city. As a result, the city is something like
an industrial estate with workers in residence. Another result has been that a large
proportion of those employed in Ciudad Industrial choose to remain living in the
surrounding rural villages, of which there are about thirty within a half hour radius, and
commute daily to the city to work. Life is freer in the villages and many workers have
small plots of land that they can continue, in this way, to cultivate. This residence
pattern is facilitated by an extraordinarily dense transport network. For example, the
next largest city, with about 8,000 residents, was connected to Cuidad Industrial by
approximately 150 scheduled buses per day, and even to smaller towns buses number over
fifty per day. In addition, there are large numbers of private automobiles in the region
purchased by workers on concessionary terms from the car factory.
One can think of the total region as a single geographically spread metropolitan area.
Rather than losing workers to outmigration, the rural areas have retained them as
residents. As a result, the relatively high incomes earned from employment in Cuidad
Industrial find their way back to the villages in the form of new housing and demand for
other village produced goods and services. The urban workers have been active in community
affairs, contributing their skills to town water projects, electical systems, etc. In the
late 1960's a group of anthropologists did a study of the 'modernity' of attitudes of
those who commuted to work in the factories and those who remained in the villages in
order to discover if, as has been suggested, work in industry promoted a more modern view
of the world than that of traditional villagers. They found that attitudes did not differ
substantially. It appears that not only did the urban workers bring material wealth back
to the rural areas in which they were resident, but they brought modern ways of thought as
Source: Poggie, Jr. (1987)
Dhenki Huskers Versus the Commercial Mill
Paddy husking is a leading rural industry in Bangladesh and until the 1960's, almost
all husking was done using the traditional dhenki technique. The dhenki
is a heavy wooden bar with a pestle at one end. The bar is used as a foot operated lever
to lift and drop the pestle into a mortar set below on the ground. Two or three people are
required to operate the dhenki. While many households husk their own paddy, it is
an occupation which provides an important source of income to poor families, and
especially women (see Box Table 3.1). The most prevalent alternative to the dhenki
technique is small rural mills using a steel huller driven by a diesel or electric motor.
These mills also employ two to three people. Large mills have four or five steel hullers
driven by steam engines (powered by husks) or diesel or electric motors. These mills also
have attached to them non-mechanized soaking, parboiling, drying, pre-cleaning and
winnowing operations, and they buy, husk and sell rice as well as simply husking it for a
fee. The large mills employ about twenty people. Finally, there are automatic integrated
mills using rubber roll huskers and mechanized processes for the related operations. These
mills often include wholesale operations or work on contract for the government. They
employ about thirty workers per mill.
The first rows of Table 3.1 show the increase in the number of mechanized mills and the
concommitant fall in dhenki operations over the past three decades. A large
factor behind this spread has been the expansion of electricity into rural areas at low
prices. Other factors include accelerated depreciation and tax holidays making capital
investments more attractive. It is clear that the shift from dhenki husking to
mechanized methods lowers total employment: a dhenki can husk 1.43 maunds of rice
per day compared to 124 for a large husker. A small huller replaces 91 dhenki
operators and a large mill replaces 226 dhenki operators. Further, there is an
additional loss to women since the move away from the traditional technique means a move
away from female employment.
The second section of the table gives some relevant operating and productivity figures
for dhenki, small huller and large huller husking techniques. Not surprisingly,
the capital/labour ratio for the dhenki technique is much lower than for the
mechanized methods. The relationship is not monotonic as the larger mills, while using
more capital than small mills, provide even more employment and so have a lower
capital/labour ratio. Capital productivity, VA/FC, is highest for dhenkis,
reflects these factor intensities. However, because of the abysmal labour productivity in dhenki
operation, large mills provide the highest profit rate on capital and have the lowest per
maund cost of processing. Note that this is subtracting the cost of labour at some
positive value, probably the agricultural wage, and gives a negative profit rate for dhenki
operations. If the shadow value of labour is about zero in this context, then the VA/FC
ratio is a more appropriate indicator of social productivity and the dhenki
Fully automated mills can process over 1,000 maunds of rice per day, replacing about
1,000 dhenkioperators with about thirty employees. At the low levels of capacity
utilization attained by these mills, their capital productivity is only 0.15, compared to
0.94 in the large huller mills and 2.27 with the dhenki. They are also costly in
foreign exchange and appear to be clearly less appropriate than the other techniques
Ranis, et. al., provide information on rice husking in the Phillipines which
indicates that the relative productivities of various technology choices depends on
capacity utilization. They find that at current rates of utilization, village rubber
role/steel huller mills (capital cost $7,633) have the lowest cost per unit processed
closely followed by the largest scale cono mills (capital cost $42,700). At 50
pecent capacity utilization, however, the small-scale steel huller mills (capital cost
4,734) dominate as long as their somewhat lower quality is acceptable followed by the
rubber role/steel huller combination. Labour productivity does not differ much across mill
types. The Philipine government has actively encouraged the move to large mechanized
process of threshing, drying, and milling with credit subsidies, licensing policy, and
government run milling complexes.
Sources: Ahmad, Q. K. (1990); Ranis, et.al. (1990)
Outside Employment and the Economy of a North Indian Village
Palanpur is a village located in the west of the populous Indian state of Uttar
Pradesh. Since 1957 the village has been the subject of close study, with surveys of the
village occurring on five occasions up to 1993. During the years 1957/58, 1962/63,
1974/75, and 1983/84 detailed information covering a very wide range of topics was
collected, including village population, its structure and composition, incomes and
occupations, land usage and cultivation practices. Most recently in 1993, a survey was
conducted in which further occupational and demographic material was collected. For this
last year however, not enough information to permit the calculation of incomes was
Palanpur is not a large village. In 1957/58 its population numbered 528, growing to 585
in 1962/63, 757 in 1974/75, 960 in 1983/84 and 1133 in 1993 (a growth rate per annum of
2.1% over the entire period -- not far from the Indian average). Although the population
of Palanpur has been growing, land available to villagers has not increased. This region
in which Palanpur is located is quite densely populated, even in rural areas, leaving
little scope for augmenting cultivable land. Growing population has translated into
increased pressure on those land resources which are available.
Agriculture lies at the heart of the village economy. Wheat is the main crop grown
during the winter season and rice is grown during the summer months. Sugarcane is the main
annual crop grown. Technological changes in agriculture, commonly grouped together under
the heading of the "Green Revolution" (comprising mechanized irrigation, new
high-yield variety seeds, and improved fertilizers) have exerted a profound influence on
cultivation practices and first introduced in Palanpur between the 1962/63 and 1974/75
surveys. Wheat yields have increased by a factor of two or three, and rice yields have
risen even more sharply. Moreover, prior to these advances, villagers had been able to
only one harvest per year. Double-cropping is now commonplace. Intensification of
agriculture has continued beyond 1974/75, with further expansion of irrigation devices and
other productive assets. This has allowed agricultural production to rise alongside
An Expanding Non-Farm Sector.
Alongside agricultural intensification and population growth, a further major
development has impacted on the economy of Palanpur over the course of the 36 years
covered by the study. Prior to 1974/75 very few of the villagers were employed outside of
agriculture - usually in traditional caste-based occupations barbering or carpentry, or
desperate last-resort non-farm activities within the village for those unable to
participate in agriculture. The railway line which runs just adjacent to the village did
offer some limited non-farm employment but aside from this virtually no villagers were
employed outside of Palanpur. Outside income represented at best 10 percent of village
income. By 1974/75 several sources of non-farm employment outside the village had become
available. For example, eleven villagers had found employment in a cloth mill or spinning
factory in the nearby towns of Chandausi and Moradabad, and were commuting on a daily
basis to these towns (usually by rail, but also by bicycle, ox-cart, and foot). In total
in that year some 44 villagers were either regularly or semi-regularly employed in such
outside activities. By 1983/84, the range and extent of village employment in outside
activities had expanded further. As many as 71 village households had at least one member
employed in the railways, in textiles, a bread factory, metalworks, in clerical work, as
teachers, or as an electrician. In this year, regular outside job income represented 34
percent of village income. The number of households with outside jobs had declined
somewhat by 1993, to 59, although the range of activities had expanded further. The big
change between 1983 and 1993 was a sharp decline in regular outside employment while
semi-regular employment actually continued to expand.
The outside jobs in which Palanpur villagers are engaged cover a broad range of
activities, and can vary markedly in terms of stability and remuneration. In general the
highest incomes accrue to activities which may suffer from other, less attractive,
features. For example, the steel polish workshops in which 8 villagers were employed in
1983/84 operated on a piece-rate basis, offering an opportunity for sizeable incomes but
little job security. They were also said to provide an unpleasant and hazardous work
environment which only young men would be able to cope with. In Palanpur, employment in
the non-farm sector is exclusively male. (Women are rarely involved in agriculture, and
then usually only on family-owned land).
Access to, and incomes from, outside jobs
The growth of outside jobs represents an expansion of opportunities which has been
embraced by many in Palanpur, both better off and worse off. The distribution of outside
employment opportunities has shown clear patterns, perhaps the most being that they tend
to cluster around well-defined locations and socio-economic groups. Certainly, in 1974/75
and 1983/84 a relatively small number of employers accounted for the bulk of outside jobs.
These included a spinning factory in Moradabad, a bakery in Chandausi, and the railways.
Similarly the composition of the group of employees shows identifiable sub-groups, often
Table 1 presents results from three probit models exploring the determinants of outside
job employment. For 1974/75 we examine the relationship between certain household
characteristics and the probability of having at least one member employed in a regular
outside job. For 1983/84 and 1993 we are able to examine employment data at the level of
the individual to investigate the determinants of outside employment.
For all three years, holding other variables constant, a larger household size
increases the probability of regular outside employment. Education, proxied either with a
household level indicator, or with years of schooling for individuals, also increased the
probability of employment. In 1974/75 and 1993 the more land cultivated the less likely a
household would have a family member employed outside the village. In 1983/84, the
significant land variable was land owned, once again suggesting that the influence of land
(either owned or operated) was more through its providing an alternative productive
activity than representing a role of wealth acting to facilitate the acquisition of
outside employment. (Note that due to widespread sharecropping in Palanpur, land owned and
land operated need not be perfectly correlated). The probit specifications included a
series of caste dummies but were generally not significant and are not reported here.
Table 2 examines the determinants of outside job incomes in Palanpur in 1974/75 and
1983/84, on the basis of a Tobit model. In 1974/75 an additional bigha cultivated reduced
outside job incomes by Rs 76 (in nominal terms). An additional household member increase
average outside job income by Rs 488, while a household with at least one literate member,
other things being equal, earned Rs 2748 more from outside employment. In 1983/84 an
additional bigha of land (approximately one sixth of an acre) cultivated reduced the
average amount earned from outside employment by nearly Rs.100 (Rs 72 in 1974/75 rupees).
An additional household member increased earnings from outside employment by Rs 898.
Whereas in 1974/75 literate households had tended to earn more from outside employment, by
1983/84 the relationship had switched in sign and such households averaged Rs 3130 less
from outside employment. This is surprising given the finding that higher levels of
schooling strongly increased the likelihood of regular outside employment. One possible
explanation is that income levels might only one feature of outside employment which is
attractive, and that higher incomes are more usually associated with relatively less
stable and more dangerous jobs. In this case, the more educated might prefer relatively
lower paid, but stable and more comfortable, jobs.
Impact on Income Distribution
A study of the impact of outside income on total income inequality in Palanpur
described first how over time such income became increasingly important in the village
economy over the survey years up to 1983/84. In 1957/58 outside job income made up about 8
percent of total income and this had risen to 34 percent by 1983/84 (recall that there are
no income figures available for 1993). Regular outside income had a differing impact on
the distribution of total income in the different years. In 1974/75 income from regular
outside jobs was very equally distributed when villagers were ranked in terms of total per
capita incomes. In 1983/84, outside job incomes accrued disproportionately to households
which were richer in terms of total per capita income. In that year those who held well
paying outside jobs were also those who were well-off in total income terms. A difficulty
in interpreting the contribution of certain income sources to total income inequality
arises from the fact that as a particular income source becomes increasingly important, it
has a larger role to play in determining total income inequality. As a result, it becomes
increasingly difficult to establish the counterfactual of what the distribution of total
income would have been in the absence of that specific income source. Nonetheless, it
seems clear that by 1983/84 (a year during which the agricultural harvest was also
particularly poor) outside job income contributed markedly to increased income inequality.
On the basis of an inequality decomposition exercise, the contribution of outside job
income to total income inequality in 1983/84 amounted to 49 percent, while in the previous
three survey years the contribution had not exceeded 13 percent.
Impact on the Poor: Direct and Indirect
Examination of the impact of outside job income on income inequality suggests that poor
households in Palanpur derived relatively little direct benefit from employment
opportunities outside the village (which is not to say that they did not engage in various
non-farm activities within the village). A study of the chronically poor in
Palanpur lends independent support to this contention. This study demonstrates that while
a fair amount of income mobility does take place among village households, there exists in
Palanpur a subgroup of households which are relatively less likely to participate in this
income mobility and who figure highly among the poor in any one year. This group of
households has in common that at least some members in any one year are employed as casual
agricultural laborers. Agricultural labor is widely perceived in the village as a
"last-resort" employment option, offering low incomes and working conditions
which are often considered as demeaning. Households which were involved in agricultural
labor in the earlier survey years, were considerably more likely to still be involved in
this occupation in the later years, and to still be counted among the poor in those later
years. Very few households engaged in agricultural labor have ever been able to move out
of poverty by means of access to outside employment. This suggests that some form of
rationing is taking place in terms of access to outside employment, and the long-term poor
are most likely to feel the effect of this rationing.
Although the poor in Palanpur cannot be said to have benefitted much in a direct way
from the expansion of off-farm employment opportunities outside the village, there are two
routes through which the growth of outside jobs may have contributed to improved living
standards of even the poor. First, between 1957/58 and 1983/84, despite a growing
population, real wages received by agricultural laborers increased from the equivalent of
2.5 kilograms of wheat per day to 5. We have already seen that agricultural
intensification has been made possible by improved agricultural technologies. These have
also raised the labor intensity of cultivation. However, it is hard to imagine that
returns to labor would have risen by this magnitude, against a backdrop of a growing labor
force, if the non-farm sector had not acted as an important additional source of labor
Second, there is some evidence suggesting that over time per capita incomes in Palanpur
have come to move less in concert around their long-term paths. In the earlier survey
years, income shocks tended to affect all households in the same direction. Covariate
incomes are widely recognized to act as critical impediments to well functioning village
insurance and credit markets. Increased access to outside incomes has reduced the
vulnerability of households to covariate income shocks and has resulted in greater
divergence across households of their yearly income "draws". As income shocks
become more idiosyncratic across households, there is increased scope for within-village
transfers of incomes. A study of the Palanpur credit market in 1983/84, revealed that
indeed an informal market was in operation and that while far from perfect, the poor were
not entirely rationed out of this market nor facing impossibly high interest rates. While
it is difficult to demonstrate that the off-farm sector played a decisive role in
promoting and strengthening the credit market, it seems likely that it has exercised some
influence in this respect.
Drčze et al (1992), Drčze et al (forthcoming), Lanjouw and Stern (1993).
Box Table 1
Probit Results for the Probability of Holding a Regular Outside Job
Estimated Coefficients with probability values in parentheses:
Observations at 0:
Observations > 0:
Literate Household Member
Education of Individual
1. For 1983/84 and 1993, the unit of observation is the individual, whereas for 1974/75
it is the household.
2. 7 Individuals from the population of 960 in 1983/84 were discarded due to lack of
information on educational status. 10 individuals from the population of 1133 in 1993 were
discarded for the same reason.
3. Caste dummies were included in the above specifications but were not significant and
are not reported here.
Tobit Results for Household Earnings from Outside Employment
1974/75 and 1983/84
Estimated Coefficients with probability values in parentheses:
Observations at 0:
Observations > 0:
Literate Household Member
Log Likelihood with All Coefficients
(Except Constant) zero (0)
Log Likelihood for Model(M)
Likelihood Ratio Test Model
Degrees of Freedom
The Papad Ladies
Shri Makila Gricha Udyog Lijjat Pappad is a women's food processing cooperative in
India. It was founded by seven poor women in 1959 and originally financed by an 80 rupee
loan. In 1978/79 the organization sold 300,000 rupees of pappads and had over 6,000 active
earning members spread throughout seven states. Lijjat is a commercial enterprise run on
cooperative lines on a putting out, or subcontracting, basis. Any woman over the age of
fifteen may join as a member/co-owner by agreeing to certain principles: for example,
religious devotion to work, cooperation for the benefit of all members, rolling pappads
for Lijjat only and rolling a minimum of three kilograms of dough per day.
Each day at four in the morning, the women in charge of preparing pappad dough arrive
at the Lijjat centres. Most centres have their own minibuses to collect workers. By six
the dough is ready for distribution. Members come to collect dough and bring with them the
pappads that they rolled in their homes, or a Lijjat owned shed, the previous day. The
pappads are weighed and compared to the amount of dough distributed. Quality checks are
very thorough with any pappads which are not clean, white and completely dry rejected.
Then the pappads are packed in polyethylene bags and labelled. Members are paid in
accordance with the quantity and quality of their pappads and given more dough. This is
rolled in the afternoon when the sun is very hot and they dry quickly. A woman may earn
between 4 and 40 rupees per day and 1.2 rupees are deposited into a compulsory savings
Sales are through agents who are paid on a commission basis. The organization does not
depend, as do many cooperatives, on sales through official marketing outlets (e.g., the
Khadi Village Industry Commission). Unlike most putting out arrangements, here all of the
intermediaries are women in the same organization. As a result, the workers receive a
larger part of the proceeds.
Source: Carr (1984)
Pelileo - Jeans Tailoring in the Ecuadorean Sierra
The rural town of Pelileo is located some 200 kms south of Quito in the Sierran
province of Tungurahua. The town has a population of 26,000 and is connected by paved road
to the city of Ambato, about 20 kms away.
In Pelileo there are around 400 enterprises engaged in the tailoring of jeans. This
activity started in the early 1970s when an entrepreneur started sub-contracting out to
households. Rapid expansion of tailoring activities took place during the 1980s. While
Pelileo has specialized in jeans tailoring, other communities in Tungurahua have focussed
on shoe-making, knit-wear and shirt-making. In total some 3,000 people are employed in one
capacity or other by the jeans economy. A few firms are large (about 15 out of the 400 in
Pelileo, employing around 70 people each), but most are household based, with an average
of no more than 5 members. Most of the household based enterprises operate in a
subcontracting relationship with the larger firms.
Many of the smaller firms are located in the environs around Pelileo, where households
combine their tailoring activities with agriculture. Agriculture in this part of
Tungurahua province has stagnated in recent years, and tailoring represents an important,
albeit modest, supplement to household income.
In the household based enterprises, one person, using a simple sewing machine, tailors
a pair of modest-quality jeans in about 45 minutes. The cost of inputs in producing such
jeans is about US $5.00, and profit received per pair of jeans is approximately $0.60. For
a five-member firm, with each member tailoring perhaps 9 hours per day, six days a week,
total weekly profits amount to less than $220. In many of the household firms, women and
children make up the workforce. For these individuals alternative income sources are often
Larger firms produce jeans of better quality in approximately 27 minutes (compared with
23 minutes per pair in the US). A pair of such jeans fetches a price of around $14 in
Quito. Unlike the lower quality products produced by household firms, and usually marketed
locally with crudely imitated designer-labels, these jeans are sold under their own labels
and are exported to Colombia, Peru and even as far as Canada.
Government provided credit to small enterprises, through the Banco Nacional de Fomento
(BNF), can be obtained in loans ranging from $1,500-5,000. This credit is available at
relatively attractive interest rates (about 36% per annum in nominal terms), but
additional transactions costs through corruption, delays and complications significantly
raise the total cost of credit from BNF. A private financial institution known as INSOTEC
provides loans of similar size at a rate of about 6% per month. All in all, credit is
available but expensive. Few of the Pelileo entrepreneurs turn to such sources of finance,
preferring to draw on savings and sources of informal credit.
Personal interview with the head of the Pelileo Chamber of Commerce in Pelileo,
Ecuador, May 1994.
Subcontracting in Thailand
Subcontracting to individuals working in their homes in rural locations is a common
practice in several industries in Thailand:
Clothing: Parent firms cut cloth and make dresses and blouses in their factories. They
distribute the clothing to rural households to be embroidered on a piecework basis. The
firms then inspect, package and market the finished goods. The relationship with
households is intermediated by local agents who are hired, again on a piecework basis, to
transport the garments, to choose households on the basis of their local information, and
to collect and return the finished items. Because of the seasonal demand for workers in
agriculture, piece rate wages increase during the peak season.
Knitting: In this case the capital requirements are more substantial, in the form of a
knitting machine, and this cost is borne by the households (facilitated by a large supply
of second hand machines). Again agents distribute yarn from the parent firm to the
households and collect the finished goods. In the case of one firm interviewed, the yarn
was sold, rather than advanced, to its agents, transferring the financing cost from the
firm to the agents. The seasonal shortage of workers is especially acute in this industry
because the peak demand for sweaters corresponds to the peak agricultural demand for
labour. Under this pressure, piece rate wages vary by about 20% over the agricultural
cycle. In the off season there is considerable underutilization of the capital equipment
with workers expressing the wish to obtain more orders despite low pay.
Fish Nets: Fish nets are made either by tying string or by cutting, joining and
finishing pieces of factory made netting. With both methods labour is subcontracted. A
villager or a town merchant may supply string or netting to another villager to tie or
finish. Again, town merchants operate through local agents. Unlike the previous cases
however, here households sometimes buy inputs themselves, produce nets, and sell them
locally. As with sweaters, peak demand for nets corresponds to peak demand for labour from
agriculture and again piece rates increase about 20% at that time. The netting factories
also subcontract (via agents) households to inspect and repair netting.
Bamboo Weaving (anyaman): households make products to order, with orders
received through either village or outside intermediaries. Sometimes less skilled, or
particularly difficult, parts of the work are subcontracted further. Capital equipment is
minimal and owned by the households and they purchase the raw materials (bamboo and
varnish). Occasionally the intermediaries supply credit on orders.
Sources: Mead, (1982); Smyth (1988).
In Search of Markets
One of the important lessons of past attempts to increase non-farm employment in rural
areas is that careful consideration of potential markets is crucial. This is particularly
true in the case of programs to support women's employment as often the expansion of
traditional craft-based activities with limit potential is encouraged, with limited
success. Tototo Home Industries is an NGO operating out of Mombasa, Kenya. In addition to
a training and credit program targetting women's groups, it runs a training course and
workshop for sewing, tailoring and tie-dye and markets handicrafts through a retail shop
in Mombasa, and wholesaled to other retail outlets in Kenya. Of the 42 women's groups
participating in the program, at least 12 have marketed goods through the Mombasa retail
outlet, retaining most of the profit. However, demand is not bouyant. The Bogoa Women's
Group sold goods woven from palm leaves from 1980-85, then in 1986 their last order was
returned by Tototo, having failed to sell at shows in Nairobi and Mombasa. They have no
other market so production stopped. A similar problem was faced by a women's group in
Mapimo. For a short period of time the group made a substantial profit making traditional
jewelry from copper wire, brass and colored beads. However, after two years, they were
producing far more than could be sold and the project collapsed. This problem was also
experienced by the Women in Development Project in Swaziland. The local market was quickly
saturated by production of crochet work, patchwork and other handicrafts. Other marketing
problems have occured when goods are not suited to consumers demands. For example, a
project in Honduras to process mangoes into mango puree faltered because the package size
was far to large and because puree was not a traditional food. In response to these
problems, smaller packaging was designed and new products developed such as jams, candy,
and a mango filled biscuit.
If market potential is considered in advance, projects can be designed which take
advantage of both local and export opportunities. The women's momvement in Guyana
responded to a government ban on imports of cakes, biscuts and sweets by successfully
initiating domestic rural production of coconut sweets. A ready-to-eat infant food mixed
based on local foodstuffs was created and patented by a home science college in Madras,
India. Produced by villagers, the product was marketed as an indigenous substitute for
more expensive imported baby foods. It was exhibited at trade fairs, the World Vegetarian
Congress and sold to schools and orphanages.
The rural weaving industry in Guatemaula was targetted by a local NGO, Fundap, in 1986,
supported by USAID, Appropriate Technologies International and the government. At that
time, handicraft production was a source of income for about 18 percent of the labour
force. In the project area, the municipality of Momostenango in Westerm Guatemaula, the
figure was 27 percent in 1976. The NGO researched the domestic and international market
for artisanal products, and finding the products from this region competitive in quality
and price, decided to invest in the development of both the wool and weaving industries.
The project included credit, training in new techniques, the introduction higher quality
sheep and improved product marketing. Of particular importance was the establishment of a
weaver organization which jointly ran a exhibition and sales room.
Sources: Carr, M. (1984); Gutierrez, R. (1990); McCormack, et.al. (1986)
1. 0. Prepared as a background paper for the 1995 World Development
Report, directed by Mike Walton. We are grateful for comments from Gus Ranis and Dominique
van de Walle. All remaining errors are ours.