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Rural Nonfarm Employment: A Survey


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This paper-- a product of the Office of the Vice President, Development Economics-- was prepared as a background paper for World Development Report 1995 on labor. Copies of this paper are available free from the World Bank, 1818 H Street NW, Washington, DC 20433. Please contact Jim Shafer, room N5-061, extension 85581 (76 pages). May 1995. The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the names of the authors and should be used and cited accordingly. The findings, interpretations, and conclusions are the authors' own and should not be attributed to the World Bank, its Executive Board of Directors, or any of its member countries
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Rural Nonfarm Employment Although governments
# ~~~~~some
countries are
implementing projects to
A Survey support small-scale and rural
more commonly
jean 0. Lan ouw the rural nonfarm sector
Peter Lanjouw operates in a policy
environment that is biased
against it. This survey
highlights the positive roles
that the rural nonfarm sector
can play in promoting growth
and welfare by slowing rural-
urban migration, using more
appropriate technologies,
paper for World Development Report 1995 providing
alternative employment for
those left out of agriculture,
and improving household
The apparent
neglect of this sector does no.
seem warranted on the basis
of available information.
Office of the Vice President
Development Economics
May 1995
Summary findings
So little is known about the rural nonfarm sector that potential in agriculture, the nonfarm rural sector can
those making policy to assist rural small-scale enterprises lower unemployment and slow rural-urban migration. I
have done so largely "unencumbered by evidence." The is particularly useful in employing women and providing
Lanjouw survey of nonfarm data and policy experience off-season incomes. The technologies used in small-scale
attempts to correct this. rural manufacturing may be more appropriate and thus
Until recently, the commonly held view was that rural generate greater income from available productive
nonfarm employment was relatively nonproductive, inputs.
producing goods and services of low quality. The rural What role could government play in promoring the
off-farm sector was expected to wither away with nonfarm sector? The emphasis of government policy has
development and rising incomes, and this was viewed as been on large-scale urban industry as the main engine oV
a positive, rather than a negative, event. A corollary of growth. More recently, there has been a move toward a
this view was that the government need not actively more "broad-based growth" approach, with greater
worry about the sector -or be concerned about how emphasis on the development of agriculture and the r ural
policies elsewhere might harm it. economy. Increasingly countries have targeted project
More recently, opinion has swung the other way, and assistance schemes, for example to provide training,
it is increasingly argued that neglect of the sector would infrastructure, and technology to support small-scale and
be mistaken. The survey highlights the positive roles that rural enterprises. Nonetheless, in most countries it
the rural nonfarm sector can play in promoting both remains true that projects to support the nonfarm rural
growth and welfare. In the widespread situation of a sector are undertaken in a policy environment whicli is
rural workforce growing faster than the employment biased against this sector.
This paper-a product of the Office of the Vice President, Development Economics-was prepared as a background paper
for World Development Report 1995 on labor. Copies of this paper are available free from the World Bank, 181 8 H Street
NW, Washington, DC 20433. Please contact Jim Shafer, room NS-061, extension 85581 (76 pages). May 1995.
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about
development issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. 'The
papers carry the names of the authors and should be used and cited accordingly. The findings, interpretations, and conclusions are the
authors' oun and should not he attributed to the World Bank, its Executive Board of Directors, or any of its member countries.
Produced by thc Policy Research Dissemination Center
Rural Nonfarm Employment
A Survey
Jean 0. Lanjouw
Peter Lanjouw
Background paper for World Development Report 1995
Rural Non-Farm Employment: A Survey'
Jean 0. Lanjouw and Peter Lanjouw
Yale University and The World Bank
I. Introduction
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 I 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
. Prepared as a. background paper for the 1995 World Development Report, directed by Mike Walton.
are grateful
for comments from Gus Ranis and Dominique van de Walle.
example, the sector's role in absorbing
a growing labor force, in slowing rural-urban migration, in
to national
growth, and in promoting
a more equitable
of that income,
warrants further scrutiny.
Agriculture Cannot Employ a Growing Rural Labour Force.
In many developing
a large proportion
of the population
lives in rural areas, and this
to grow at a substantial
rate. For example,
in Bangladesh
the rural labour force is
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
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
pursued by many developing countries in previous decades have failed to
absorb a growing labour force.
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 work-force, 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 I 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
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
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 4).
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
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
of labour can contribute to raising total income. And there is always a time frame issue -
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.
Income Distribution
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 insurance.
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,, 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 I refer only to primary
employment. As will be discussed below in section 111, 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 employmient 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.
Opportunity costs
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, Vijverberg, 1988).
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
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
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"
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
potential workers.
m. Characteristics of Non-Farmn Employment Sector - Inequality and Poverty Alleviation.
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 reasons:
A. The Distribution of Non-Farm Jobs
It is impossible to say whether the opportunity to engage in non-farm activities is income
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
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
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).
B. Unemployment
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
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
(Ryan and Ghodake, 1984). There are many theories as to why wages should
be inflexible
various efficiency
and nutritional wage theories,
imperfect information
theories, and resistance
on the part of workers themselves (see Dasgupta, 1993, and Dreze and Mukerjee, 1989). With
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.
C. Women
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 I indicates that non-farm employment
is important to women
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
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.
D. Seasonality
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.
E. Diversiflcation
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 (lCRISAT) 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, (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
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
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 (&ee 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 non-farm sector.
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 dispersed pattern.
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
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 be targetted.
B. Intersectoral Linkages - Empirical.
Econometric Studies
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
exists. Furthermore,
as emphasized above in section B, 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, (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
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
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
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 agricultural
Social Accounting Matrices
The second type of investigation uses social accounting matrices (SAMs) to calculate growth
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
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) inputloutput 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
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, (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
83 cents of value added through linkages. Of this 83 cents, 33 cents could be attributed to
linkages. The study assumes that supplies of non-agricultural
output are perfectly elastic and
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
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 (199 lb) 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
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
plus non-agricultural)
income. Unfortunately, as in the Bell, (1982) study, there is
no distinction
between locally
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, (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
Irepresentative' 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
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 I KSh increase in coffee output generating 1.12 to 1.42 Ksh in regional value-added
Table 9, columns I and 2). (In value-added terms these multipliers are even larger and are close to the
1.5 found by Hazell,, 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
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
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-
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
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
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)
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
from low to high productivity states. This transition in types of activities with urbanization
also found in a detailed study of employment in the city of Bouake, Cote d'lvoire (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
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
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.
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
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 domestic imports.
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
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,, 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.
Larger markets - Subcontracting
(Putting Out).
is a system whereby
a buyer
agrees to purchase
or final goods from
another firm (or household)
it then sells to consumers or to another producer. A common
in developing
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
which parties bear the costs (and risks) involved in
the financing of costs during production, ensuring quality, and marketing. The urban-based or
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
It may have less costly access
to technical
which can be passed on to suppliers. By buying
in bulk
or producing semi-finished
goods themselves,
such firns 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
in progress. As a result, the local agent is often expected to ensure quality. Local agents working as
may also bear the financial burden of purchasing finished goods from the
and finding
buyers. Subcontractors
can supply inputs
- knowledge
of the wider market and
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
instead of trying to produce and sell final products independently. Of course, larger rural
may be able to take on these roles themselves. For example, Yang (1994), in a study of a
factory producing
products in the village of Shenquan,
China, describes how it, in effect,
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
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 modem 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
presence of distortions since there may be economic reasons for such differences. For example, urban
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
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,, 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 remain unaffected.
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 beneficiaries.
"..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.
Financial Projects
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 I 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
Industrial Estates
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
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
production. The intention was to support the handloom producers,
but since powerlooms
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
versus mill production by Little, (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, khapdsari, 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
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
Scheme, with an average
of half a million (1975-89),
the Bangladesh
Food for Work Programme, which
was of comparable
size in 1990. First, by drawing
from other activities,
in other sectors
increased. Simulations
that this indirect
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
than similar
such a program. Finally, women
were able to benefit
and had participation
rates as high as men's. Particular
features of the employment
to this result, for
short travel distances
and the provision
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Industrialization,' Oxford Economic
Papers. Vol. 46. pp. 136-156.
Wang, X. (1990) "Capital Formation and Utilization," Chapter 10 in Byrd, W. and Lin, Q. (eds.)
China's Rural Ilndustry: Structure,
Development, and Reform. New York: Oxford University
Press for
the World Bank.
Weijland, H. (1989) "Rural Cottage Industry in Transition: The Roof Tile Industry in Kabupaten
Boyolali, Central
Java," Bulletin of Indonesian
Economic Studies. Vol. 25, no. 2, pp. 79-98.
White, B. (1991) 'Economic Diversification and Agrarian Change in Rural Java, 1900-1990," in
Alexander, P. et. at. (eds.) In the Shadow
of Agriculture: Non-Farm
Activities in the Javanese
Past and Present. Amsterdam:
Royal Tropical Institute.
Williamson, J. (1988) "Migration
and Urbanization,"
Chapter 11 in Chenery, H. and T.N. Srinivasan
(eds.) The Handbook
of Development Economics. Vol. 1. New York: North-Holland.
World Bank
(1994) World Development
Report 1994: Infrastructurefor
New York: Oxford
Press for the World Bank.
Yang, M. (1994) 'Reshaping Peasant Culture and Community: Rural Industrialization
in a Chinese
Village', Modern China, 20(2), April.
Box 1
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
boiled eggs. They receive a net profit per week per person of 42.45 K.
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 limes (March 1983);
Milimo and Fisseha (1986).
Box 2
Mexico: Industrial Estate or Rural Town?
Ciudad Industrial, Mexico, is an interesting
hybrid of a small rural city and an industrial
in the middle
of the semi-arid
valley, a region of marginal agricultural
little industrial development,
this 'city' was planned to bring new economic opportunity
to local people.
In 1952 an automobile
plant began
Fiat automobiles
and Dina
(Diesel Nacional)
buses and trucks. A government
was formed
to plan and contruct the new city and by 1958 there
were three factories and about three thousand workers
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
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,
permits have
been issued
sparingly so the business
district is quite limited. In addition,
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
operators are allowed to be resident in the city. As a result, the city is something like an
estate with workers in residence. Another
result has been that a large proportion of those
in Ciudad Industrial
to remain
living in the surrounding
rural villages,
of which
are about thirty within a half hour radius, and commute
daily to the city to work. Life is freer in the
and many
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
buses per day, and even to smaller
towns buses
number over fifty per day. In addition,
are large numbers
of private automobiles
in the region purchased
by workers on concessionary
from the car factory.
One can think
of the total
region as a single geographically
spread metropolitan
area. Rather
to outmigration,
the rural areas
have retained
them as residents. As a result, the relatively
high incomes
from employment
in Cuidad
find their way back to the villages
in the form
of new housing
and demand
for other village
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
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
ways of thought as well.
Source: Poggie, Jr. (1987)
Box 3
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 dhenJa. 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 dhenhi 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
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 dhenh 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
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 dhenAis, 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 appears superior.
Fully automated mills can process over 1,000 maunds of rice per day, replacing about 1,000
dhenki operators 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 examined.
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
Box Table 3.1
Characteristics and Productivity of Huskinf Technologies
Small Huller Large Huller
Dhenki Mill Mill
Percent of Crop
Husked by:
1967 83% 17%
1977 65-75 2-25 5-10%
1981 60-65 25-30 10
Employment, L (no.) 2.6 2.5 20.5
Percent family 62% 19% 18%
Percent female 100 9 4
Fixed Capital, FC (Tk) 3,285 85,832 453,667
Working Capital (Tk) 816 2,456 108,479
Value added, VA (Tk) 7,445 37,964 426,347
Net Yearly Profit,
NP (k) negative 22,066 281,412
FC/L (Tk) 1,263 34,333 22,130
VA/L (Tk) 2,863 15,186 20,797
VA/FC 2.27 0.44 0.94
NP/FC - 0.26 0.62
Paddy husked per
8 hour day 1.43 50.72 124.12
Per Maund cost of
Husking (Tk) 27.40 4.04 3.50
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, (1990)
Box 4
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
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 collected.
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 village population.
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
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
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,
can vary markedly in terms of stability and remuneration. In general the highest incomes accrue to
which may suffer from other, less attractive,
features. For example, the steel polish
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, outsidejobs
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
and socio-economic
groups. Certainly, in 1974/75 and 1983/84 a relatively small number of employers
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
often caste-based.
Table I 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
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
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
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 1974175 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
were also those who were well-off in total income
terms. A difficulty in interpreting the contribution
certain income sources to total income inequality arises from the fact that as a particular income source
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
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
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 demand.
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
and strengthening the credit market,
it seems likely that it has exercised
some influence in this
Dreze et al (1992), Dreze et al (forthcoming),
Lanjouw and Stern (1993).
Box Table 1
Probit Results for the Probability of Holding a Reeular Outside Job
Estimated Coefficients with probability values in parentheses:
1974/75 1983/84 1993
Total Observations 112 953 1123
Observations at 0: 75 890 1087
Observations > 0: 37 63 37
Constant -0.62 -1.87 -2.298
(0.073) (0.000) (0.000)
Land Owned -0.01 -0.02 -0.003
(0.409) (0.022) (0.734)
Land Cultivated -0.03 -0.01 -0.028
(0.013) (0.158) (0.015)
Household Size 0.17 0.06 0.087
(0.002) (0.005) (0-009)
Literate Household Member 1.14
Education of Individual 0.14 0.094
(0.000) (0.000)
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.
Table 2
Tobit Results for Household Earnings from Outside EmDlovment
1974/75 and 1983/84
Estimated Coeflficients with probability values in parentheses:
1974/75 1983/84
Total Observations 112 143
Observations at 0: 75 48
Observations > 0: 37 95
Constant -1586 -4349
(0.073) (0.004)
Land Owned -39 -76
(0.200) (0.200)
Land Cultivated -76 -99
(0.013) (0.038)
Household Size 488 898
(0.000) (0.000)
Literate Household Member 2748 -3130
(0.003) (0.037)
Log Likelihood with All Coefficients
(Except Constant) zero (0) -412.9 -458.6
Log Likelihood for Model(M) -396.7 -440.0
Likelihood Ratio Test Model 32.4 37.2
Degrees of Freedom 8 8
Critical X2 15.5 15.5
Box 5
The Papad Ladies
Shri Makila Gricha Udyog Li.jat 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 Lijat
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 account.
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 Cornmission).
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)
Box 6
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 mnachine,
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 scarce.
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.
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.
Box 7
Subcontractinm 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 househol