Rural Nonfarm Employment and Incomes in Chile
JULIO A. BERDEGUE
Â
Red Internacional de Metodolog
õa de Investigaci
o
n de Sistemas de Producci
o
n
(RIMISP), Santiago, Chile
EDUARDO RAMIÂREZ
Ministerio de Plani®caci
o
n y Cooperaci
o
n, Santiago, Chile
THOMAS REARDON
Michigan State University, East Lansing, USA
and
GERM
AN ESCOBAR
*Red Internacional de Metodolog
õa de Investigaci
o
n de Sistemas de Producci
o
n
(RIMISP), Santiago, Chile
Summary. ÐThis article analyzes the evolution of rural nonfarm employment (RNFE) and income in Chile during 1990±96. The data used come from the National Socioeconomic Survey (CASEN), and from a household survey undertaken by the authors in two municipalities in 1999. The latter contrasted two zones, very dierent in terms of economic dynamism and rural poverty. We show that during the period, RNFE and incomes increased 10% and 18%, respectively, in 1996, reaching 39% of rural employment and 41% of rural incomes. The rate of multiactivity (the share of households participating in more than one sector) was only 20%, lower than expected, indicating a tendency toward economic specialization in rural income strategies. The determinants of such employment are mainly household characteristics, in particular variables related to human capital, such as the age and gender of the household head, and the schooling of the household members, although also important are access to credit and physical capital. The level of nonfarm income of rural households is determined mainly by the economic context, in particular the economic level and dynamism of the overall zone and the quality of the roads. It is proposed that policies to develop RNFE should be geared to zone characteristics, and should in general favor investments in education, in roads, and in access to credit. Moreover, households headed by women should be the object of special attention. To promote such policies, it will be necessary to address important gaps and weaknesses in the public institutional structure. Ó 2001 Elsevier Science Ltd. All rights reserved.
Key words Ð Latin America, Chile, rural nonfarm employment, incomes, rural poverty, development
2001 Elsevier Science Ltd. All rights reserved Printed in Great Britain 0305-750X/01/$ - see front matter
PII: S0305-750X(00)00102-9
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*This research is based on generous grants from the Inter-American Development Bank (IADB) and the United Nations Food and Agriculture Organization (FAO). The authors thank Drs. Ruben EcheverrõÂa (IADB), Gustavo Gordillo De Anda, Kostas Stamou-lis, and Alexander Schejtman (FAO) for valuable support and comments, and three anonymous peer
reviewers for useful comments. The authors also acknowledge the support of the Planning and Cooper-ation Ministry of Chile (MIDEPLAN), that facilitated access to the CASEN survey data. The authors acknowledge the work of Ms. Ximena Milicevic in the organization and analysis of the municipal-level surveys.
1. INTRODUCTION
There is growing evidence that rural nonfarm employment (RNFE) is an important source of income for rural households in Latin American and the Caribbean (LAC), including for the landless and other poor rural groups (Berd-egue, Reardon, & Escobar, 2000; Reardon, Berdegue, & Escobar, 2001). Nevertheless, ru-ral development policies, in particular those aiming at rural poverty alleviation, generally concentrate on agricultural development. After many decades of rural development policies based on the agricultural sector, it is now clear that many rural zones and households are ®nding few opportunities in agriculture for sustainable increase in incomes, in sucient degree to substantially alleviate poverty (Berd-egue, 2000).
Although the principal instruments of agri-cultural development in Chile directed at small farmers have been successful in raising in-comes, the impact of these interventions has not been signi®cant in the poorest strata, and indeed there has been little impact on incomes of rural households not participating in own-farming (Comite Interministerial de Desarrollo Productivo, 1998). Thus, to reduce the poverty that aects a large share of rural households in Chile, the focus should be not only on small-scale agricultural production, but also on employment and incomes in the nonfarm sector.
RNFE can contribute to agricultural devel-opment by providing peasants with cash in-comes that can be invested in improvements in agricultural productivity. A substantial share of rural nonfarm activity is concentrated in the broad agrifood system (commerce in agricul-tural inputs and outputs, equipment service provision, and so on). By this means it can in-crease the pro®tability of agriculture via the better linking of agriculture to other sectors and markets. In turn, the development of ag-riculture stimulates growth in commerce, in-dustry, and other rural services. These farm± nonfarm links are crucial for rural regional development to be balanced, dynamic, and sustainable (Banco Interamericano de Desarr-ollo (BID), 1998).
2. APPROACH
The research is based on two sources of in-formation: (a) for the countrywide analysis, we
used data from the National Socioeconomic Survey (CASEN) of the Ministry of Planning and Cooperation (MIDEPLAN) for the years 1990 and 1996; (b) For the zone (``comuna'' or municipality) level analysis, RIMISP (Interna-tional Farming Systems Research Network in Santiago, Chile) undertook a survey in two
comunas in March 1999. The comunas were Portezuelo, to represent zones with extensive rural poverty and a dearth of agricultural modernization, and Molina, to represent situ-ations of little rural poverty and rapid eco-nomic growth and agricultural modernization, which in the case of Molina is in fresh fruit and, in particular, vineyards and wineries of high quality, oriented toward export markets.
The CASEN surveys provided data on the socioeconomic conditions of the various so-cioeconomic groups in the country, problems in their living and economic situations, the degree and nature of their poverty, the distribution of incomes over households, and the geographic and socioeconomic strata coverage of social programs and their contributions to monetary and nonmonetary incomes of households (MI-DEPLAN, 1996). The sampling and survey unit is the residence, while the unit of analysis is the household, whether a single person or several, with or without family links among themselves, who live in the same residence and have a common food budget. Members of a household are only the permanent residents of the resi-dence, de®ned as not being absent more than two months of the year (MIDEPLAN, 1990). We used the CASEN surveys of 1990 and 1996. We did not use the 1987 CASEN because of various changes in methods and de®nitions between that survey and the later ones, which restricted comparison, nor did we use the 1998 survey because disaggregated data from that survey were not available at the time of the writing of this paper.
The 1990 sample comprised 25,793 house-holds, of which 18,549 urban and 7,244 rural. In 1996 the sample comprised 35,730 house-holds of which 25,640 urban and 10,090 rural. The sample in each case is nationally and re-gionally representative both for urban and ru-ral areas, and the sampling error is 5% with a con®dence interval of 95% (MIDEPLAN, 1990, 1996).
the 37,618 rural localities were aected by this change in the classi®cation system. The survey focuses on the location of the household to determine whether it is rural, and does not furnish data on the location of the households' economic activities or whether they migrate or commute to jobs in urban areas. The employ-ment data indicate sector but not location, and thus, RNFE refers to nonfarm jobs undertaken in either urban or rural areas by rural house-holds. Data limitations, therefore, restrict us from useful analyses of job location and thus, whether rural households commute or migrate to urban jobs, or nonfarm jobs in rural areas undertaken by urban households, or incomes of households which are today urban but were recently in rural areas. Moreover, the CASEN survey generates employment information for one month of the year, and thus, it is not pos-sible to know whether the employment pro®le changes over the year, which is of course im-portant to ascertaining accurately the degree of multiactivity of the household.
The study of RNFE in the comunas of Portezuelo and Molina is not meant to be representative in a statistical sense of the situ-ation in all Chile. Rather, these are case studies that are meant to be illustrative of dierent situations of rural poverty, economic dyna-mism, and agricultural modernization, in order to examine several themes and issues that can-not be studied using the national CASEN data. The determination of the sample size for Portezuelo was calculated using the two-step method of Stein, using the variance and mean of the incomes of rural households for the rainfed agriculture zone of Region VIII based on observations from a survey of 2,900 house-holds in Chile of which 188 househouse-holds in that zone. The sample size for our survey in Porte-zuelo was 200 households. For Molina, the size of the sample was limited for budgetary reasons to 75 households, and thus, the sampling error is higher for that comuna. In Portezuelo, the 200 households were distributed over 22 rural localities (e.g., villages, small rural towns), in proportion to the number of residences in the localities. In Molina, we selected at random 18 of the 47 rural localities, and the number of households per district was selected in propor-tion to the number of residences in the districts. In each district, households were chosen at random based on geographic sampling. It is important to note that the observations on in-comes and employment covered all households and their members over the whole year.
3. COUNTRY-LEVEL RESULTS
(a) Agricultural incomes
Table 1 shows that during 1990±96 the number of households whose principal income was from agriculture, hunting, and ®shing 1 did not change signi®cantly. Nevertheless, ur-ban households principally engaged in agri-culture increased 37%, while rural households thus, engaged fell 15%. 2 This change of resi-dence of households thus, engaged3 involved all occupational categories in agriculture: em-ployers/owners, wage-earners, and self-em-ployed farmers,4 althoughÐas expectedÐthe change was greatest among employers/owners. The upshot is that in 1996, 41% of households depending on agriculture had their residences in urban areas, a share much greater than the 31% reported in 1990. Our hypothesis is that, this change is due to improvements in rural roads.
Table 1 also shows that agricultural income stayed at about the same level over 1990±96, but that this is a result of a reduction in ag-ricultural income among rural households and an increase among urban households. This occurred because of the change of residence discussed above, but also, more fundamen-tally, because the households that shifted to the towns and cities were households with greater incomes, in all occupational catego-ries. The average monthly income of house-holds whose principal income comes from agriculture did not vary signi®cantly over 1990±96. This average, however, masks a sharp drop in the monthly income of those who maintained their rural residence (in par-ticular owners and employers with rural resi-dence, whose incomes fell nearly 7% per year over the period), and an increase in the av-erage monthly incomes of those who migrated to urban centers, especially in the category of small producers (the incomes of whom in-creased at nearly 9.5% per year) (MIDE-PLAN, 1998).
(b) Rural employment and incomes
During 1990±96, RNF income in Chile grew due to an increase in the number of rural in-habitants working in manufactures and servic-es, as well as to an increase in the average monthly income of those employed in those sectors. The number of rural households with members whose principal income comes from RNFE increased 10% over 1990±96, coming to account for nearly 40% of rural households in 1996 (see Table 2). Moreover, the average monthly income generated by RNFE increased 7% during the same period. These two trends combined to produce an increase of 18% in RNF income during that period (MIDEPLAN, 1999a).
These trends oset the decline in agricultural employment and incomes of rural households during the period, implying an increase in the weight of RNFE and RNF incomes in the total income of rural households, with the result that in 1996 nonfarm sources constituted 41% of incomes and 39% of the employment of rural households, ®gures that are in the range of those estimated by Reardon et al. (1998) and Berdegue et al. (2000) as averages for Latin America.
(c) Evolution of rural nonfarm incomes by subsector and occupation category
In 1996, commerce was the main subsector of the RNF economy, constituting 24% of RNF
Table 2. Nonfarm employment and income
Rural households Households Household average monthly income Ch$a
1990 1996 1996/
1990
1990 1996 1996/ 1990 Number
Percent-age
Number Percent-age
Main employ-ment farm
387,037 78 331,000 74 0.86 186,466 158,438 0.85
Main employ-ment nonfarm
161,072 32 177,332 39 1.10 192,719 205,891 1.07
Total 496,616 100 449,075 100 0.91 208,247 198,084 0.9578
aChilean Pesos of March 1999
106. US$1 483.3 Chilean Pesos of March 1999. Table 1. Farm employment and income
Households employed in agriculture
Households Total monthly income Ch$a
1990 1996 1996/1990 1990 1996 1996/1990
Rural
Self-employed 131,110 113,569 0.87 24,128 19,735 0.82 Wage workers 259,399 222,512 0.86 28,440 24,556 0.86 Owners and employers 17,194 11,454 0.66 19,601 8,153 0.42
Total 387,037 331,000 0.85 72,169 52,444 0.73
Urban
Self-employed 31,451 46,201 1.47 6,845 15,806 2.31 Wage workers 132,527 178,623 1.35 18,600 30,689 1.65 Owners and employers 8,519 12,099 1.42 13,771 13,108 0.95
Total 169,974 233,194 1.37 39,216 59,602 1.52
Total national
Self-employed 162,561 159,770 0.98 30,973 35,541 1.14 Wage workers 391,926 401,135 1.02 47,040 52,245 1.17 Owners and employers 25,713 23,553 0.92 33,372 21,261 0.64
Total 557,011 564,194 1.02 111,385 112,046 1.01
a
incomes. Manufactures represented 17% of RNF incomes, although this was below its contribution to RNF incomes of 23% in 1990. By contrast, construction increased substan-tially its share of RNF incomes from 8% in 1990 to 12% in 1996.
Table 3 shows that during 1990±96, there was an increase in the number of households in all the occupational categories of RNFE, with the exception of the self-employed. Nevertheless, the latter, along with domestic service workers, experienced a substantial increase in their av-erage monthly incomes, as did the other occu-pational categories with the exception of owners and employers, who suered monthly income declines (MIDEPLAN, 1999b).
(d) Multiactivity of rural households
Based on how many rural households had members working in the various categories of farm and nonfarm employment, we calculated that in 1996: (i) 5% of the households had members working in dierent categories of principal employment within agriculture, hunting and ®shing (for example, households with one self-employed agriculturalist and one farm wage-laborer); (ii) 9% of the households had members working in dierent categories of principal employment within the nonfarm sec-tor; (iii) 6% of households with one or more members working in the farm sector and one or more working in the nonfarm sector. Thus, overall, 20% of the households can be consid-ered to be ``multiactive'' in 1996 by the above de®nitions. The rate in 1990 was 17%.
This suggests that, with respect to the prin-cipal occupation of members of rural Chilean
households, there is relative specialization. In-comes from secondary occupations of house-hold members contributed at most 2% of overall household incomes in 1996, which is not sucient to aect our main conclusions re-garding multiactivity.
This ®nding diers from those in other countries of Latin America. The dierences are probably due to the fact that Chilean rural households are relatively small (4.2 members on average) and to the fact that rural Chile had nearly full employment during 1990±96 which in principle would facilitate year-long work in the sector and activity to which a given worker is best suited.
4.COMUNA(MUNICIPAL) LEVEL RESULTS
The patterns discussed above at the aggre-gate level can now be explored in more detail using the municipal level surveys in Molina (illustrative of zones with a dynamic agriculture and relatively low levels of poverty) and Port-ezuelo (illustrative of zones with traditional agriculture and relatively high levels of rural poverty).
Thecomunaof Molina is in the province of Curico, and is part of the irrigated valley of Region VII ``del Maule.'' Sixty-eight percent of the population is rural according to the Demographic Census of 1992 (INE, 1992). The city of Molina (17,301 inhabitants) is on the main highway of Chile, and is near a rela-tively large city (Curico). In the comuna of Molina, there are four other urban centers. According to the Agricultural Census of 1997,
Table 3. Evolution of nonfarm employment and income, by employment category
Nonfarm employment
Nonfarm self-employed 48,301 7,690 7 44,168 9,058 10.2 Nonfarm wage worker 104,778 17,341 17 121,240 20,948 23.5 Nonfarm owner or
em-ployer
3,149 5,122 5 4,901 4,511 5.1
Armed forces and police 1,050 228 0 2,137 398 0.4 Domestic services 13,490 647 1 21,766 1,597 1.8
Nonfarm unclassi®ed 67 14 0 ± ± ±
Rural nonfarm total 161,072 31,042 30 177,332 36,511 41.0
aChilean Pesos of March 1999
in the cropping patterns in Molina, substantial shares of cropland are under wine grapes (18.1%), fruit trees (18.9%) and vegetables (6.5%). Farmland is extremely concentrated: of the 868 farms in Molina, 20% of them ®gure among the smallest and occupy 0.1% of farm-land, while the 5% largest farms occupy 88% of the farmland; the Gini coecient for land-holdings in Molina is 0.76. This is more con-centrated than the average for Region VII. This concentration is the result of a process of transfer of land distributed by the Agrarian Reform to producer associations and com-mercial producers. According to our data, 8% of rural households in Molina are extremely poor, 15% are poor, 77% are not poor, a situ-ation which places this comuna at a socioeco-nomic development level above the national rural average, even though the rate of extreme poverty is actually the same as the national rural average.
The comuna of Portezuelo is located in the province of Nuble, in Region VIII ``del BõÂo~ BõÂo,'' in the agro-ecological zone known as the ``Interior Rainfed Zone,'' the agricultural po-tential of which is very inferior to that of the irrigated Central Valley where Molina is lo-cated. Seventy-®ve percent of the population is rural, and there is only one urban center, that of the town of Portezuelo (1,464 inhabitants). The closest city is Chillan, distant 35 km. Of cultivated land, 30.6% is under rainfed vine-yards of traditional varieties that have lost much of their markets due to an increase in vineyards to the north; only 0.5% of the farm-land is under vegetables and 1.3% is under fruit trees. The Gini coecient of landholding is 0.61. According to our surveys, 38% of the rural households in Portezuelo are extremely poor, 31% are poor, and only 31% are not poor, which places thecomunawell below the national rural average.
At ®rst glance, the dierence between Molina and Portezuelo in terms of population and proximity to urban centers, can be considered an essential dierence for our purposes. Nev-ertheless, Table 4 shows that the dierences between them are not so important that they negate the fact that half of the RNF jobs of rural households take place in rural areas, and the other half in urban centers. In addition, households in Molina and in Portezuelo are relatively homogeneous in terms of family size and gender, age, and schooling characteristics. Almost all the rural households in Portezuelo have access to land, with an average of 6.0 ha/
household, of rainfed cropland, much of it hillside. Less than half of the households in Molina have access to land, with an average of 2.0 ha, though with irrigation and under in-tensive cropping.
The landed households of Molina are mainly engaged in production of vegetables and ¯ow-ers, while those in Portezuelo concentrate on rainfed vineyards and staples (mainly wheat). Note that the great majority of landed rural households in Molina do not grow wine grapes of high quality, nor do they grow fruit, which, while being principal crops of thecomuna, have high entry barriers for small farmers.
There are also signi®cant dierences between Molina and Portezuelo in terms of physical capital of the households. The households of Molina tend to have more buildings, but there are no satistically signi®cant dierences between them and those of Portezuelo in terms of agri-cultural machinery and equipment. This is pos-sible because half of the households in Molina are landless, and by extension would not have farm machinery. Moreover, relatively more households in Portezuelo have their own home, which surely re¯ects the fact that many families are recent immigrants to Molina, as was the case in many other comunas enjoying the Chilean fruit production boom (Rivera & Cruz, 1984).
Finally, Molina residents have access to better roads than those of Portezuelo, and in the latter there is absolutely no paved road in all its breadth and width.
(a) The income composition of rural households in Molina y Potezuelo
Table 5 shows that the landed households of rural Molina have higher incomes than the Molina landless, and both higher than the households of Portezuelo. The landless of rural Molina rely the most on nonfarm incomes, followed by the households of Portezuelo, and least reliant on nonfarm incomes are the landed households of Molina. Thus, the degree of re-liance on nonfarm incomes, measured by the Table 4. Location of nonfarm activities of rural
house-holds
Activity takes place in
Percentage of rural households
Molina Portezuelo
Urban locality 50 47 Rural locality 50 53
share of nonfarm income in overall household income, is determined broadly by access to land and local labor market opportunities.
Within Portezuelo, the degree of reliance of households on nonfarm incomes is conditioned by access to nonearned income (with ``earning'' de®ned as receiving income from work of the household members in the period of observa-tion, the year); an example of nonearned in-come is a transfer from the government. As a share of earned income only, nonfarm income constitutes 41%, while it is only 26% of overall income (earned plus nonearned), that is, a 15% spread. Contrast this with the case of the landed households of Molina, where there is only a 4% spread, and only a 9% spread for the landless of Molina. Hence in the richer Molina, earned income is a higher share of total income than in the poorer Portezuelo.
The better paid nonfarm jobs are concen-trated in the more dynamic zones and under-taken by the richer households, in particular the landed. This supports what Reardon, Cruz, and Berdegue (1998) call the ``meso paradox'' of RNFE: the least dynamic zones have the greatest need for and rely more on RNFE, but have fewer opportunities to generate such in-comes. The data also support their ``micro paradox'' whereby the poorest rural house-holds, in a given zone, are most need of RNFE
opportunities but have less capacity to have access to them. These results are important for rural development policies and combating poverty: it is not clear that RNFE is a strong lever for development in poor zones and households. Policies promoting RNFE will confront the same sorts of challenges among poor zones and households that confront agri-cultural development policies.
The main reason for this is that in the dy-namic zones such as Molina there are greater employment opportunities than in the poorer zones such as Portezuelo. Note that the mem-bers of the average sample household in Molina work 367 days/year while in Portezuelo the ®gure is only 157. Yet it is important to note the contribution of RNF incomes to family incomes in Portezuelo: without nonfarm in-comes, the average rural household income would be below the ocial poverty line and just 18% above the extreme poverty line. Among the landless of Molina, without nonfarm in-comes their average household income would be slightly below the ocial poverty line.
In sum, RNF employment and incomes are indispensable to reduce poverty levels, espe-cially in the case of the poorer zones and households and the landless, but the greatest potential as a development instrument is in the richer zones and households.
Table 5. Income composition of rural households in Molina and Portezuelo
Income Molina landed households Molina landless Portezuelo Ch$a % Of
earned % Of
total
Ch$a % Of earned
% Of total
Ch$a % Of earned
% Of total
Farm, self-employed
1,860,709 55 49 70,450 5 4 275,875 36 24
Farm, wage worker
591,900 18 16 780,395 51 40 175,043 23 15
Farm, total 2,452,609 73 65 850,945 56 44 450,918 59 39 Nonfarm,
self employed
507,760 15 13 208,521 14 11 139,213 18 12
Nonfarm, wage worker
396,600 12 10 467,513 31 24 168,367 23 14
Nonfarm, total
904,360 27 23 676,034 44 35 307,580 41 26
Total earned 3,356,969 100 88 1,526,969 100 78 758,498 100 65
Total non-earned
462,285 12 425,066 22 414,061 35
Total household
3,819,254 100 1,952,035 100 1,172,559 100
aChilean Pesos of March 1999
(b) Multiactivity in the rural households of Molina and Portezuelo
As an indicator of the level of multiactivity of households we calculated the percentage of households whose members had two or more distinct jobs that together generated at least 80% of their earned income. A household is ``specialized in employment'' if 80% or more of its earned income comes from a single type of employment.
By these criteria, 37% of the rural households in Portezuelo and 30% in Molina are multiac-tive. These percentages are greater than the 17% calculated using the 1996 CASEN data at the countrywide level. We do not know if the dierence is due to their having been an in-crease in multiactivity during 1996±99 (as there had been during 1990±96), and/or whether these comunas have greater levels of multiac-tivity than others in the country, or whether the dierence is simply due to methodological dif-ferences between the two surveys.
Given the comuna, multiactivity increases with household income. In Molina there is no extremely poor household that is multiactive, while 18% of poor households and 33% of nonpoor households are multiactive. In Porte-zuelo, 32% of the extremely poor households, 52% of the poor households, and 56% of the nonpoor households are multiactive. Hence as in Nicaragua (see Corral & Readon, 2001), multiactivity is a ``superior good.''
Table 6 shows that poverty conditions access to nonfarm jobs, with nonfarm incomes rising with household income. The main policy im-plication is that, as nonfarm income is as un-equally distributed as farm income, one cannot be an alternative to the other for the poor. In other words, the poor who lack farm incomes cannot easily compensate for that lack with nonfarm income. Our hypothesis is that mul-tiactivity at the household level requires previ-ous access to physical, human, ®nancial, social, or natural capital. The lower the endowment of
these capital assets, the fewer options are available to households to undertake nonfarm employment.
(c) Types of RNFE in Molina and Portezuelo
Linkages between farm and rural nonfarm activities are greater in the poorer zone, Port-ezuelo. In Molina, only 22.1% of RNF income is linked directly (in production linkages) to agriculture, such as agro-processing,5 versus
56.5% in Portezuelo. It appears that the econ-omy of the richer comuna oers greater opportunity for wage employment and self-employment in nonfarm activities not directly linked to agriculture; of course, such nonfarm activities might be indirectly linked via con-sumption linkages, hence, spurred by eective demand from incomes arising in the commer-cial farm sector. In the poorer zone, the weight of agriculture is much greater and there are few activities that can develop independent of it.
Moreover, neither in Molina nor in Porte-zuelo do more than half of rural households undertake their nonfarm activity in the rural area per se (and in the rural area, mostly in their own residences). The other half are un-dertaken in urban areas by the rural residents, as shown in Table 4. This is an important ®nding, as it contradicts the conventional wis-dom that having a job in urban areas requires that a rural resident leave the countryside and move to the town or city. This point can be added to the other complication discussed above, that there are also many urban house-holds who work in agriculture in rural areas. These two complications blur the boundary between urban and rural and leads to the con-cept of the emergence of ``rur-urban space.''
In both comunas, returns to labor increase the further is the nonfarm activity from being production-linked with agriculture: nonfarm jobs production-linked with agriculture such as agro-processing pay only 33±43% of the returns to nonfarm activities not thus linked.
More-Table 6. Rural poverty and multiactivity (% of households in each poverty class)
Household condition according to per capita income of its members
Molina (dynamic municipality) Portezuelo (poor municipality)
Specialized households Multiactive households
Specialized households Multiactive households Farm Nonfarm Farm Nonfarm
Extremely poor 67 33 0 62 6 32
Poor 82 0 18 38 10 52
over, the rural nonfarm activities undertake in rural areas pay only 64±70% of the returns to employment of rural household members in nonfarm activities in urban centers; the latter jobs provide substantial income ¯ows to rural households.
There are no big dierences between the
comunas in rankings of nonfarm wage-em-ployment activities in terms of structure of employment. Most of the rural individuals who have nonfarm wage employment work in the private services sector outside of construction. Construction is the second source of nonfarm wage income. Between these two is concen-trated 63±70% of persons undertaking nonfarm wage employment. In third place, but well be-low the others, is employment in the public sector.
As for nonfarm self-employment, this time there are large dierences between thecomunas. In Molina, commerce in farm outputs and in-puts is by far the most important enterprise activity. In second place is machinery repair. In Portezuelo, 70% of nonfarm self-employment income is concentrated in small-scale manu-factures using agricultural raw material, in particular agro-processing (winemaking).
(d) The relation between household and individual characteristics and RNF employment
and incomes
We examined participation in RNFE as a function of gender, education, and total income position relative to the poverty line. Women's participation in the farm and nonfarm wage-labor markets is roughly in the same propor-tions. The type of RNFE undertaken by men diers from that undertaken by women. Women dominate commerce and other servic-es, while men dominate manufactures. The gender dierence with respect to nonfarm em-ployment production-linked to the farm sector and/or taking place in the rural area depends on local labor market conditions and prevailing agricultural systems. Returns to labor are also in¯uenced by the worker's gender: women earn more than men in nonfarm wage employment (in Molina, $11.3/day versus $10.3/day; in Portezuelo, $11.0/day versus $8.9/day), but women earn less than men in farm wage em-ployment (in Molina, $7.3/dayversus$8.8/day; in Portezuelo, $5.7/dayversus$6.4/day) and in nonfarm self-employment (in Molina, $5.6/day
versus$10.6/day; in Portezuelo, $9.0/dayversus
$21.1/day).
In bothcomunas, women work fewer days (in both sectors) per year than men (107 days/year for women in Molina,versus245 days/year for men. In Portezuelo, the ®gures are 44 days/year for women and 82 for men). Note that in both
comunasalmost half of adult women are not in the labor market. Nevertheless, Molina women work 143% more days per year than do those of Portezuelo, while Molina men work 200% more days per year than do their peers in Portezuelo. Nonfarm jobs production-linked with the farm sector are dominated (63%) by women in Molina but by men (65%) in Portezuelo. In Molina, nonfarm employment taking place in urban centers is dominated by men (64%), but in Portezuelo, women dominate these jobs (65%) while men stay at home and work on the farm and in small-scale manufactures enter-prises using farm products as inputs (71% of those jobs are undertaken by men). In both
comunas, manufacture sector jobs are domi-nated by men (76% in Molina and 79% in Portezuelo), while women dominate services (60% in Molina and 59% in Portezuelo).
The upshot of these ®ndings for policies to improve women's access to nonfarm jobs is two-fold: (i) measures that eliminate barriers to participation of women to labor markets in general will also be useful in improving wom-en's access to RNFE; (ii) that many programs striving to increase nonfarm self-employment of rural women (such as in small-scale manu-factures enterprises) might be driving women to enter precisely the types of nonfarm jobs that have lower pay relative to men; by contrast, women appear to have advantages when they undertake wage employment in commerce or other services or manufactures.
Education has a clear impact on access to nonfarm jobs, but one should note that the impact is greater in the richercomuna(Molina) than in the poorer one (Portezuelo). Between nonfarm self-employment and wage employ-ment, the persons in the latter have higher ed-ucation. Farm wage employment is the domain of the least educated, wherein half to two-thirds of the workers do not even have a primary school education.
5. DETERMINANTS OF RNF INCOMES
Table 7 shows the results of Probit and or-dinary least squares (OLS) regressions, linked using the two-stage Heckman procedure to control for selectivity bias. The regressions es-timate the determinants of the probability of access to and the level of nonfarm income. The types of nonfarm income are treated: the total nonfarm income of the household, nonfarm self-employment income, and nonfarm wage-employment income. As noted above, the re-sults are speci®c to the case study areas, but illustrative.
The underlying conceptual model is that the above dependent variables are functions of the incentives oered by the economic context (proxied in our regressions by variables indi-cating the comuna itself as well as the road network); and the capacity of households to respond to those incentives, which in turn depends on the households assets, including human capital (age, gender, and education), physical capital (farmland, access to irrigation, vehicles, and equipment), social capital (par-ticipation in rural economic organizations), and access to external ®nancial capital (access to credits and government transfers). House-holds living in a more favorable economic context and with more assets will have greater access to nonfarm jobs and will earn more in them than households in the opposite situa-tion.
(a) Determinants of participation
The results concerning the probability of participation in some sort of nonfarm income generation, abstracting from the levels of non-farm income earned, are shown in Table 7. Human capital (gender of the household head, average age of the married couple, and average education of the household members older than 15) are statistically signi®cant determinants for all three dependent variable categories (total nonfarm, nonfarm wage-income, and nonfarm self-employment income).
The negative sign of the coecient on the gender of household head variable indicates that households headed by women have a greater probability of earning nonfarm in-comes. Households of older couples and those households with more education also have a greater probability of earning nonfarm incomes of both types.
Holdings of vehicles, equipment and ma-chines have a positive eect on the probability of earning nonfarm income in general, and from self-employment in particular. The coef-®cient is, however, negative for nonfarm wage employment.
Access to farm credit has a positive eect on the household's undertaking nonfarm self-em-ployment. Farm households that have access to more funds use them (or other funds freed by having the farm credit) at least partly to di-versify their incomes.
After controlling forcomuna, neither roads, economic organization participation, nor landholdings, irrigation, or government trans-fers, drive households' participation in nonfarm income generation.
Whether the household is located in the richer comunadoes not signi®cantly aect the probability of earning nonfarm income in general. But, as expected from the descriptions of patterns above, the eect of Portezuelo on earning nonfarm self-employment income was signi®cant. Recall that many Portezuelo households are winemakers.
(b) Determinants of levels
In contrast with the results concerning the determinants of participation where the zone and location variables did not have much ef-fect, here, in the determinants of nonfarm in-come levels, those variables are important. The most important variable determining total nonfarm earnings is the location of the household. Households in Molina earn more nonfarm income than those in the poorer Portezuelo.
The regressions show that households near very poor roads earn more nonfarm income from self-employment. This ®nding is driven by the fact that many households in Portezuelo live near poor roads and produce cheap wine. The very inferiority of their roads ``protects'' (in a trade sense) the traditional agro-industry activities of these hinterland households, as well as increases transaction costs to house-holds to participate in better-paying work fur-ther a®eld or to invest in higher quality wine the pro®table production and sale of which requires easier contact with the market.
Independent variables
Probit models: dependent variableaccess to RNF income (No RNF income0; Yes RNF income1)
OLS models: dependent variablelognof RNF income
Total RNF income Self-employment RNF income
Salaried RNF income
Total RNF income Self-employment RNF income
Salaried RNF income
McFadden's
R2 0.10
McFadden's
R2 0.10
McFadden's
R2 0.13
R2 0.39 R2 0.37 R2 0.42
Est.b t Est.b t Est.b t b t b t b t
1. Lambda )2.40 )0.94 )0.54 )0.16 0.84 0.25
2. Sex )0.68 )2.72 )0.54 )2.14 )0.58 )2.13 0.54 0.49 )0.62 )0.49 )0.61 )0.45 3. Age 0.02 2.91 0.01 2.07
)0.02 2.08 )0.02 )0.57 )0.00 )0.22 0.04 1.13
4. Number 0.01 0.23 )0.08 )1.23 )0.10 1.56 0.12 1.03 )0.01 )0.44 0.35 1.38 5. Schooling 0.11 2.91 0.06 1.85 0.15 4.02 0.06 0.38 0.12 0.83 0.23 0.65
6. Irrigation )0.38 )1.01 0.21 0.55 )0.82 )1.88 0.12 0.14 0.55 0.78 )0.06 )0.03 7. Land )0.01 )0.43 0.00 0.05 0.00 0.17 )0.00 )0.09 0.00 0.21 )0.03 )1.85 8. Equipment 0.00 1.96 0.00 2.44
)0.00 )0.68 0.00 0.36 0.00 0.56 0.00 1.09
9. Distance 0.10 1.38 0.07 1.20 )0.01 )0.24 )0.13 )1.10 )0.06 )0.43 )0.04 )0.39 10. Credit 0.28 1.57 0.43 2.41
)0.08 )0.45 )0.46 )0.87 )0.23 )0.23 )0.06 )0.20
11. Organization )0.30 )1.35 )0.01 )0.45 )0.15 )0.68 0.03 0.05 )0.41 )0.97 )0.07 )0.18 12. Municipality )0.20 )0.74 )0.43 )1.81 0.35 1.45 1.09 2.13 0.88 0.84 0.59 0.72 13. Paved road 0.92 1.70 0.40 0.79 0.38 0.79
)0.38 )0.28 1.21 1.01 )0.11 )0.11
14. Gravel road )0.12 )0.41 )0.25 )0.81 )0.36 )1.16 0.18 0.31 1.19 1.44 )0.64 )0.66 15. Good dirt road 0.22 0.81 0.16 0.59 0.07 0.24 0.17 0.29 1.00 1.65
)0.26 )0.65 16. Bad dirt road )0.14 )0.51 )0.22 )0.77 )0.16 )0.53 0.84 1.42 1.66 2.19 )0.48 )0.77 17. Subsidies )0.00 )0.86 )0.00 )0.57 0.00 0.99 0.00 0.58 )0.00 )0.85 0.00 0.04 18. Constant )0.90 )1.97 )0.86 )1.87 )1.91 )3.79 13.58 3.97 11.78 2.63 8.16 1.13 aIndependent variables: 1
Lambda, 2Sex of head of household (Female0, Male1), 3Age of heads of household, 4Number of economically active members of household, 5Average schooling of members of household 15 years of age or older, 6Percentage of total farm land with irrigation, 7Total farm area (hectares), 8Total value of vehicles, tools, and machinery, 9Distance to nearest town (km), 10Access to credit (0no, 1yes), 11Membership in farmers' economic organization (0no, 1yes), 12Municipality (0Portezuelo, 1Molina), 13Paved road (1yes, 0other), 14Gravel road (1yes, 0other), 15Dirt road, can be used throughout the year (1yes, 0other), 16Dirt road in bad condition (1yes, 0other), 17Income from public subsidies, 18Constant. *
Statistically signi®cant at 10% level. **Statistically signi®cant at 5% level.
***Statistically signi®cant at 10% level.
CHILE
6. CONCLUSIONS AND RECOMMENDATIONS
It was once held that rural±urban migrants are among the poorest, and that by their migration they, thus, abandon farm wage la-bor; but our nationwide results ¯y in the face of these theories. In today's Chile, at least in the intermediate cities and small towns and in zones with good roads, many small farmers, farmworkers and commercial farm owners/ managers have migrated to urban centers, but they are neither the poorest nor have they abandoned the farm sector. The urbanization of the residence of persons who remain em-ployed in agriculture has transferred to rural areas a phenomenon noted for some time in the great cities: the spatial segregation of rich and poor. Nevertheless, seeking to reverse the urbanization of agriculturalists' residence would be counterproductive as it implies the improvement of living conditions for thou-sands of farm wage-workers and small farm-ers.
Moreover, we have shown that many rural households are working outside the farm sec-tor, in nonfarm wage and self-employment. In fact, these nonfarm sources contribute 41% of the total income of rural households in Chile. It is critical to design and reinforce policies that facilitate that development of these kinds of employment. In particular, investments in rural education and policies that ease households' access to credit and equipment/machinery would improve rural households capacity to under nonfarm activities.
An important implication of our ®ndings is that RNF employment promotion should be designed with special consideration for female-headed households, as they tend to depend more on such employment. Such programs should be primarily geared to preparing women for wage employment in the services or manu-factures subsectors, with only secondary at-tention to what has been the traditional focus of nonfarm development programs, self-em-ployment in microenterprises. This is because our results have shown that women have access to and earn more than men in wage employ-ment as compared to farm labor or in self-employment.
Policies and programs promoting nonfarm employment should dier by zone and socio-economic group, because the motives and sit-uations of households in undertaking such employment vary greatly. On the one hand,
the nonfarm income share in total income might be high because nonfarm earnings are relatively high. An example such as is Molina, an agricultural boom area, where there is dy-namic growth in the nonfarm economy. On the other hand, the share might be high not because the nonfarm economy is particularly successful but merely because farm incomes are weak and stagnant, such as in Portezuelo, our case study in a hinterland zone with poor traditional agriculture and weak infrastruc-ture. Clearly, dierent policies are required to promote equitable growth in the nonfarm sector in rural Molina versus in rural Porte-zuelo.
In zones such as Molina, the growth of RNFE derives from the dynamic growth of the overall zone economy. Public sector ac-tions can and should accompany, regulate, and facilitate this development, but the funda-mental dynamic arises from the market itself. We found that in these situations, much RNFE is not closely tied (``production-linked'') to agriculture, such as cinemas and restaurants, home construction, clothing stores, banks, pharmacies, public oces, etc. Of course, the original impetus for this growth in Molina was dynamic commercial agriculture and agro-industry, but in other zones with dynamic economies one can ®nd other original motors of growth such as tourism, mining, proximity to a large city, etc. The origin of the dynamism of RNFE is frequently outside the countryside itself, although it is incontrovert-ible that a modern, competitive, and dynamic agriculture requires and foments links between itself and services and manufactures, and generates incomes that are spent in those subsectors of the nonfarm economy. Thus, farm and nonfarm development are not ex-clusive alternatives, but rather can be mutually reinforcing.
nonfarm self-employment in small enterprises needs then to be basedÐat least in an initial phase in which capital is accumulated by households that in turn diversify their incomes outside of the farm sectorÐon the development of small- and medium-scale farming. This re-quires government action, in particular, mea-sures to develop the land market to help the poor to obtain land through purchase or rental, and to intensify production and increase pro-ductivity through irrigation, technical assis-tance, and credit.
Our results also contradicted the conven-tional wisdom that the poor and the landless earn the lion's share of nonfarm incomes. It is true that they tend to rely more on RNF in-comes because of lack of farm inin-comes as in Portezuelo in general, but they do not neces-sarily earn higher nonfarm incomes than richer and landed households. In fact, the latter earn more nonfarm incomes, either because they can capitalize their enterprises with farm pro®ts, or because they earn service sector income by renting out or using as physical capital their tractors and trucks, or because farm incomes fed their family education in-vestments that allowed their sons and daugh-ters to obtain salaried employment in a local business or to start their own businesses. In zones such as Portezuelo, households with more land earn more nonfarm income partly because the latter is often linked to processing farm products or selling farmers services and other inputs.
For similar reasons, multiactivity (where a household earns substantial income from more than one source) is more prevalent in nonpoor households. With more assets (physical, ®nan-cial, and human capital), a household has more and better job opportunities in the nonfarm sector. In either type of zone, however, multi-activity is less common than one would think: Chilean rural households have a tendency to specialize in one type of employment (own-farming, farm wage labor, nonfarm wage-em-ployment, nonfarm self-employment), possibly because this ®ts best with the household's en-dowment of assets. This eases the design of policies dierentiated by target group and ac-tivity, because it is thus, probable rural house-holds will self-select into programs according to their specialization.
Unfortunately, RNFE and incomes are as inequitably distributed as farm incomes. The best opportunities tend to be concentrated in richer and dynamic zones such as Molina. This
is particularly serious from the zone perspective because the promotion of nonfarm employ-ment has emerged in the rural developemploy-ment policy debate in Chile as a way of ®nding an alternative to agriculture in poor zones. But unless a zone poor in agriculture is fortunate enough to have some other growth motor such as mining or tourism, this hope is in vain. In poor zones, nonfarm development is as limited as farm sector development. Moreover, the nonfarm jobs found in these zones are of low productivity and are poorly paid. Yet without even those nonfarm jobs, the poverty rates in poor zones would be much higher. RNFE is thus, not a panacea for poor zones and does not permit an escape from the need to design policies that help the out-migration under fa-vorable conditions of a portion of the youths of these zones.
Finally, we have shown that rural nonfarm self-employment takes place mainly in small family ®rms. Most of these ®rms, in both study zones, are in the informal sector (lack ocial tax status, access to credit and technical assis-tance, and so on).
more funds into training and infrastructure that bene®t RNF activity. The State Bank can increase access to credit to start or capitalize rural enterprises undertaking nonfarm activi-ties. The National Tourism Service (SERNA-TUR) can redouble its support of rural tourism, agro-tourism, and ecotourism. The Social Investment and Solidarity Fund
(FO-SIS) should pay more attention to investments and services that facilitate links between rural small enterprises in poor zones and dynamic markets for nonfarm goods and services. We conclude by underscoring the importance of education and roads for the development of nonfarm activities by rural Chilean house-holds.
NOTES
1. Of the total number of households, according to the CASEN survey, there were only 12,930 households with income from ®shing in 1990 and 14,186 in 1996.
2. This explanation is consistent with the rapid urbanization in Chile. But, strictu sensu we cannot discard other explanations that would lead to the same ®nal net result, such as, for example, that a share of the poorest rural households have completely abandoned agriculture, or that a considerable number of urban households that in the past had no link to the farm sector now are earning a share of their incomes from that sector.
3. We can be fairly sure that this is a change of residence and not just an eect of changes in the
de®nition of ``rural,'' because during 1990±96 only 85 of the 37,618 rural localities were rede®ned as urban due to changes in the ocial de®nitions or because of popula-tion growth in those localities.
4. The category of self-employed farmers can be lumped into that of small farmers and peasants.
5. A nonfarm activity is considered to be (production)-linked to the farm sector when its main inputs or the demand for its output come exclusively or mainly from the farm sector (e.g., the case of farm machinery services, winemaking, commerce of agro-chemicals). There are some nonfarm activities that can be said to be linked to the farm sector as well as other sectors of the economy (e.g., the case of transport and construction).
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