The State of Food and Agriculture 1998

APPENDIX TABLE 1¹

RURAL NON-FARM INCOME: STUDIES REVIEWED

¹  Sources are cited in full in Appendix Table References, p.346.
Note: n.a. = not applicable.
² An expanded version of this table, elaborating on statistical data used in the chapter, is included in the diskette accompanying this publication (see the Excel file directory RNF-DATA).
 
 

APPENDIX TABLE 2¹

RURAL NON-FARM EMPLOYMENT: STUDIES REVIEWED

¹  An expanded version of this table, elaborating on statistical data used in the chapter, is included in the diskette accompanying this publication (see the Excel file directory RNF-DATA).
² Sources are cited in full in Appendix Table References, p. 346.
Note: n.a. = not applicable.
 
 
 
 

APPENDIX TABLE 3¹

RURAL NON-FARM HOUSEHOLD INCOME OVER INCOME OR LAND STRATA: STUDIES REVIEWED

¹  1 An expanded version of this table, elaborating on statistical data used in the chapter, is included in the diskette accompanying this publication (see the Excel file directory RNF-DATA).
² Sources are cited in full in Appendix Table References, p. 346.
Note: n.a. = not applicable.
 
 

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Notes

1 Throughout this chapter “farm activity” will be used synonymously with “agriculture” and “non-farm activity” synonymously with “non-agricultural activity”.

2 Farm households are defined as rural households that carry out some farming activities.

3 The distinction between “push” and “pull” factors is not always precise. Indeed, when considering the relative “merits” of the two sectors, “pull” and “push” factors are interchangeable. In some cases, however (e.g. the risk motive or credit/cash constraints), the distinction is clearer: the risk of farming and lack of insurance and credit markets may “push” farm households to devote some of their productive resources to RNF activities, which produce a more stable income even though the returns expected from the farm activity are higher on average (i.e. when averaged over several periods).

4 Agroclimatic zones are characterized by common rainfall patterns, soil characteristics, sunlight and temperature, and hence by a common potential for agriculture.

5 See note 2.

6 Data on non-farm income shares are based exclusively on survey case studies, while the data on non-farm employment shares are based on a combination of occupation censuses and survey data from Asia and Latin America.

7 A complete documentation of the statistical data used in the analysis can be found in spreadsheet format on the accompanying diskette, which also includes a set of international agricultural time series.  The Excel files containing these data are located in the directory RNF-DATA.

8 The coefficient of variation is a statistical indicator of the degree to which the various observations in a sample are dispersed around its mean. The smaller the coefficient of variation, the closer the observations on the whole are to the mean; the larger the coefficient of variation, the more they are dispersed around the mean value of the sample.

9 S. Haggblade, P. Hazell and J. Brown. 1989. Farm-non-farm linkages in rural sub-Saharan Africa. World Development, 17(8): 1173-1201.

10 Further reasons why it is difficult to make a comparison between the two sources are: i) the employment shares are derived from official aggregate statistics, while the income shares have been derived from selected case studies; ii) official employment statistics tend to include both rural towns and the countryside while the case study income information mainly refers to the countryside.

11 T. Reardon, A. Fall, V. Kelly, C. Delgado, P. Matlon, J. Hopkins and O. Badiane. 1994. Is income diversification agriculture-led in the West African semi-arid tropics? The nature, causes, effects, distribution and production linkages of off-farm activities. In A. Atsain, S. Wangwe and A.G. Drabek, eds. Economic policy experience in Africa: what have we learned?, p. 207-230. Nairobi, African Economic Research Consortium.

12 K. Otsuka. 1998. Rural industrialization in East Asia. In Y. Hayami and M. Aoki, eds. The institutional foundation of East Asian economic development. London, Macmillan.

13 Details on the methodology and findings can be found in A. Klein. 1992. El empleo rural no agricola en América Latina. Report No. 364. Santiago, PREALC.

14 Ibid.

15 D. Mead. 1994. The contribution of small enterprises to employment growth in southern and eastern Africa. World Development, 22(12): 1881-1894.

16 K. Otsuka, op. cit., note 12.

17 J.A. Schaffner. 1993. Rural labor legislation and permanent agricultural employment in northeastern Brazil. World Development, 21(5): 705-719.

18 See R. Adams. 1996. Remittances, income distribution and rural asset accumulation. Research Report No. 17. Washington, DC, IFPRI.

19 X. Milicevic and J. Berdegue. 1998. Non-farm employment linked directly and indirectly to the agro-industrial boom: the horticultural belt of central Chile. Paper presented at the III Simposio Latinoamericano de Investigación y Extensión en Sistemas Agropecuarios, 19-21 August 1998, Lima, RIMISP.

20 E. Francis and J. Hoddinott. 1993. Migration and differentiation in western Kenya: a tale of two sub-locations. Journal of Development Studies, 30(1): 115-145.

21 L. Daniels. 1995. Entry, exit and growth among small-scale enterprises in Zimbabwe. Michigan State University, East Lansing,  USA. (Ph.D. Dissertation)

22 This comparison could be made in the case of household studies reported from Botswana, Ethiopia, Kenya, Malawi, Rwanda, the Sudan and Zimbabwe.

23 C. Liedholm and D. Mead. 1987. Small-scale industries in developing countries: empirical evidence and policy implications. Report No. 9. Department of Agricultural Economics. Michigan State University, East Lansing, USA; and D. Mead. 1994. The contribution of small enterprises to employment growth in southern and eastern Africa. World Development, 22(12): 1881-1984.

24 The latter argument dates back to the British economist David Ricardo whose model reflected circumstances in nineteenth-century United Kingdom but is still widely applicable in developing country agriculture today. In Ricardo’s model, rising food costs (driven by rising farm production costs from diminishing returns to labour, i.e. declining factor productivity) drive up the subsistence wage, hence the market wage, which drives down profits and investment and growth in the non-farm economy. By contrast, “cheap food” was an important factor – and agricultural success a preliminary condition – in the East Asian rural industrialization from the 1950s (A. Saith. 1986. Contrasting experiences in rural industrialization: are the East Asian successes transferable? In R. Islam, ed. Rural industrialization and employment in Asia. New Delhi, ILO). The converse also holds – high food costs have been a drag on African industrialization, whether rural or urban (M. Lipton and M. Lipton. 1993. Creating rural livelihoods: some lessons for South Africa from experience elsewhere. World Development, 21(9): 1515-1548).

25 R. Ahmed and M. Hossain. 1990. Developmental impact of rural infrastructure in Bangladesh. Research Report No. 83. Washington, DC, IFPRI.

26 H. Oshima. 1986. Levels and trends of farm families’ non-agricultural incomes at different stages of monsoon development. In Y.B. Choe and F.C. Lo, eds. Rural industrialization and non-farm activities of Asian farmers. Seoul, Korea Rural Economics Institute.

27 Y.B. Choe. 1986. M-cycle hypothesis, non-farm activities and rural industrialization in the Asian monsoon economy. In Choe and Lo, op. cit., note 26.

28 See M.U. Ahmed and N. Rustagi. 1987. Marketing and price incentives in African and Asian countries: a comparison. In E. Elz, ed. Agricultural marketing strategy and pricing policy. Washington, DC, World Bank.

29 Reardon et al., op. cit., note 11.

30 Saith, op. cit., note 24.

31 J. Dione, J.-C. Le Vallée, J. Staatz, J. Tefft, M. Yade, A. Chohin and B. Kante. 1997. Lessons from the impact of the devaluation of the CFA franc on agri-food subsectors in West Africa. Policy Brief. Department of Agricultural Economics, Michigan State University, East Lansing, USA.

32 P. Collier and D. Lal. 1984.  Why poor people get rich: Kenya 1960-79. World Development, 12(10): 1007-1018.

33 R. H. J. Adams. 1994. Non-farm income and inequality in rural Pakistan: a decomposition analysis. Journal of Development Studies, 31(1): 110-133.

34 J.E. Taylor and A. Yunez-Naude. 1998. Selectivity and the returns to schooling in a diversified rural economy. University of California at Davis, Davis, USA. (mimeo)

35 P. Lanjouw and N. Stern. 1993. Markets, opportunities and changes in inequality in Palanpur, 1957-1984. In A. Braverman, K. Hoff and J. Stiglitz, eds. The economics of rural organization: theory, practice and policy. New York, Oxford University Press.

36 J.P. Estudillo and K. Otsuka. 1998. Green revolution, human capital and off-farm employment: changing sources of income among farm households in central Luzon, 1966-94. Economic Development and Cultural Change (forthcoming).

37  For the purpose of this chapter, agro-industrial activities are defined as the collective set of production linkage activities, i.e. farm input provision and agroprocessing and distribution.

38 J. von Braun and R. Pandya-Lorch. 1991. Income sources of malnourished people in rural areas: microlevel information and policy implications. Working Paper No. 5. Washington, DC, IFPRI.

39 A. de Janvry, G. Gordillo de Anda and E. Sadoulet. 1997. Mexico’s second agrarian reform: household and community responses, 1990-1994. La Jolla, Center for US-Mexican Studies, University of California, San Diego, USA.

40 M.U. Ahmed. 1995/96. Development of rural non-farm activities: a dynamic approach to poverty alleviation in rural Asia. Regional Development Studies, 2(winter): 1-22.

41 T. Reardon. 1997. Using evidence of household income diversification to inform study of the rural nonfarm labor market in Africa. World Development, 25(5): 735-748.

42 The Gini coefficient is a statistical indicator that measures the extent to which the actual income distribution diverges from a hypothetical perfectly equal distribution. The larger the Gini coefficient is, the more unequal income distribution is.

43 In this case, in a comparison of Gini coefficients, the coefficient for total income is higher when non-farm income is included than when it is not or, if using the Gini decomposition approach, marginal changes in non-farm income – when all other factors are constant – increase the Gini coefficient.

44 T. Reardon and J.E. Taylor. 1996. Agroclimatic shock, income inequality and poverty: evidence from Burkina Faso. World Development, 24(4): 901-914.

45 Op. cit., note 35.

46 Op. cit., note 44.

47 G.K. Chadha.  1986. Off-farm economic structure of agriculturally growing regions: a study of Indian Punjab. In R.T. Shand, ed. Off-farm employment in the development of rural Asia. Canberra, National Centre for Development Studies, Australian National University.

48 A. Narongchai. 1981. Rural off-farm employment in Thailand. Bangkok, Industrial Management Company, Ltd.

49 For a report on Mexico, see J.E. Taylor. 1992. Remittances and inequality reconsidered: direct, indirect and intertemporal effects. Journal of Policy Modeling, 14(2): 187-208; for a report on Africa, see T. Reardon, E. Crawford and V. Kelly. 1994b. Links between nonfarm income and farm investments in African households: adding the capital market perspective. American Journal of Agricultural Economics, 76(5): 1172-1176.

50 Francis and Hoddinott, op. cit., note 20.

51 C. André and J.-P. Platteau. 1998. Land tenure under unbearable stress: Rwanda caught in the Malthusian trap. Journal of Economic Behavior and Organization, 34(1).

52 Estudillo and Otsuka, op. cit., note 36.

53 In some countries, an infrastructural instrument that has been used, with mixed results, to effect RNF company starts and the relocation of businesses to rural areas is the establishment of industrial parks or districts (such as in South Africa and the Republic of Korea and in some developed countries, such as Italy).

54 For a further discussion, see V. Kelly, J. Hopkins, T. Reardon and E. Crawford. 1995. Improving the measurement and analysis of African agricultural productivity: promoting complementarities between micro and macro data. MSU International Development Paper No. 16. East Lansing, USA, Michigan State University.

55 The assessment of such effects for different agro-industries and products is the subject of a current FAO project on farm/non-farm linkages.

56 A. Schejtman. 1996. Agroindustria: alcances conceptuales para una política de estimulo a su articulación. LC/R Report No. 1660. Santiago de Chile, CEPAL.

57 Ibid.

58 For the case of West Africa, see N.N. Dembele and K. Savadogo. 1996. The need to link soil fertility management to input/output market development in West Africa: key issues. Paper presented at the International Fertilizer Development Center Seminar, 19-22 November, Lomé, Togo.

59 FAO. 1996. Ciudades intermedias y desarrollo rural: el caso de Zamora, Michoacán (Mexico). By F. Rello. Santiago de Chile, FAO Regional Office for Latin America and the Caribbean.

60 Op. cit., note 24