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This article uses a quantitative activity choice approach, based on identification of activity variables and application of latent class cluster analysis, to identify five major rural livelihood strategies pursued by households (n= 576) in Bolivia, Nepal, and Mozambique. Income sources and welfare outcomes are compared across strategies and household differences in asset holdings are analyzed using multinomial logit regression. Findings reveal that income diversification is the norm, that a higher degree of specialization does not characterize more remunerative livelihood strategies, that nonfarm income significantly contributes to higher income earnings, that environmental reliance does not vary across strategies, and that small‐scale farmers are the largest and poorest livelihood group. Some livelihood strategies are superior to all other strategies in terms of income earned; access to more remunerative livelihood strategies is determined by land ownership, education, and ethnic affiliation. Finally, the article also highlights that additional work is required to determine the most suitable methods for livelihood strategy identification.

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Forests contribute to livelihoods of rural people throughout the tropics. This paper adds to the emerging body of quantitative knowledge on absolute and relative economic importance, through both cash and subsistence income, of moist forests to households. Qualitative contextual information was collected in six villages in lowland Bolivia, followed by a structured survey of randomly selected households (n = 118) that included four quarterly income surveys. We employed a novel data collection approach that allows detailed estimation of total household accounts, including sources of forest income. We estimated the average forest income share of total annual household income (forest dependency) at 20%, ranging from 18 to 24%. Adding environmental income increased the average to 26%, being fairly constant across income quartiles at 24-28%. Absolute levels of forest income increased with total household income, while forest dependency was the highest in the best-off income quartile-the primary harvesters of forest products are better-off households. The pattern of high forest dependency among better-off households has also been reported from other countries, indicating that this pattern may be more common than advocated by conventional wisdom. Using ordinary least squares (OLS) regressions, we found significant determinants of absolute forest income to be household size, sex of household head and area of cultivated land; the significant determinants for forest dependency were level of education, whether household head was born in village and whether household was food self-sufficient. Better-off households were able to realise cash income from forests, while poorer households-in particular if headed by women-were more reliant on subsistence forest income. We argue that the differential patterns of forest income across income quartiles should be considered in future development interventions and that findings indicate a potential for forests to contribute to moving households out of poverty.Readers should send their comments on this paper to BhaskarNath@aol.com within 3 months of publication of this issue.