Hum Ecol (2010) 38:675–690 erosion; (4) mending terrace ridges to prevent soil erosion; (5) maintaining and improving irrigation of farmland; (6) converting sloping farmland into terraces; (7) increasing the use of organic farm fertilizer; (8) reducing the use of artificial fertilizer and other chemicals; (9) planting legumes and other kinds of green manure crops; (10) practicing fallowing; (11) manually weeding household farmland and/or forested land; and (12) acquiring information on natural resources and the environment from sources such as television, newspapers, and magazines. Responses (0 = no, 1 = yes) were summed up to create another composite variable of total number of resource improvement activities taken in the past year. Furthermore, five socio-demographic variables were included in the analysis to account for the effects of basic household characteristics on livelihood activities. The use of these control variables allows for a more accurate evaluation of the differences between labor- migrant households and non-labor-migrant households in rural livelihoods. The variables were: years of residence, household size, number of laborers in a household (including labor migrant members), mean age of laborers, and mean educational level of laborers. Educational attainment was measured by eight different levels in the survey: (1) little or no formal education; (2) less than an elementary school degree; (3) elementary school degree; (4) junior high school degree; (5) senior high school degree; (6) middle level professional, technical or vocational school degree; (7) two year associate degree; (8) four year college degree or above. Analytic Methods The statistical analysis of the rural household survey data included three phases. First, descriptive analyses of the data were used to describe survey sample characteristics and aggregate patterns of household livelihoods in the study area (results not included here). Next, variations between different household groups regarding livelihood variables and socio-demographic characteristics were explored with simple bivariate comparison statistics (independent t-test and one-way ANOVA). Finally, multivariate discriminant analysis was used to compare the differences between household groups in livelihood activities while controlling for the effects of household socio-demographic character- istics. This technique was particularly suitable here because it allowed for the comparison of two or more groups on multiple variables simultaneously. Discriminant analysis is usually used to classify known and unknown cases into categories. Here it is used to examine the multivariate differences between household groups, instead of maximiz- ing the odds of correctly predicting the class of a particular case. The bivariate and multivariate analyses included both 681 the comparison of labor-migrant and non-labor-migrant households and the comparison of labor-migrant, local off- farm work, and farming households. Results Bivariate Comparisons As a preliminary step for the multivariate data analysis, bivariate statistical tests were conducted to identify socio-demographic and livelihood differences between household groups. Results of bivariate comparisons of labor-migrant and non-labor-migrant households are shown in Table 2, with significant variables highlighted. In sum, labor-migrant households differed significantly from non-labor-migrant households in all the five house- hold socio-demographic characteristics. On average, labor- migrant households lived longer in the village, and had more members and labor force than non-labor-migrant households. In general, laborers of labor-migrant house- holds tended to be younger and more educated than those of non-labor-migrant households. In addition, these two groups differed significantly in some of the livelihood variables. Notably, non-labor- migrant households cultivated more land than labor- migrant households on a per laborer basis. As expected, labor-migrant households on average enjoyed higher per capita cash income and more consumer assets than non- labor-migrant households. Households with labor migrants also depended less on firewood and crop residues for fuel. Table 2 also summarizes results of bivariate comparisons of labor-migrant, local off-farm work, and farming house- holds. All the household socio-demographic variables again indicated significant differences among different household groups. Labor-migrant households and farming households in general lived longer in the village than local off-farm work households. On average, labor-migrant households were the largest in terms of household size and labor pool, followed by local off-farm work households, with farming households being the smallest. Active labor members of farming households also tended to be older and less educated than those of the other two groups. Compared to the two-group comparisons, per capita annual cash consumption expenses differed significantly among household groups in the three-group comparisons. As shown in Table 2, farming households differed significantly regarding five livelihood indicators from the other two household groups. They cultivated more farmland on a per laborer basis, had lower per capita cash income and living expenditures and fewer consumer assets, and relied more on forests and crop residues for