Hum Ecol (2010) 38:675–690 Variables Agricultural production Size of per laborer cultivated land (mu) Total number of types of agricultural production involved Yield of rice (kg) per mu of land Yield of corn (kg) per mu of land Use of agricultural technologies Expense of farming chemicals per mu of land (RMB) Total number of traditional agricultural technologies used Total number of modern agricultural technologies used Household income, expenditure, and assets Per capita annual cash income (RMB) Per capita annual cash living expenditure (RMB) Household consumer asset index Resource use and management Proportion of firewood and crop residues in total fuels Total number of types of forest products used Total number of resource improvement activities taken Sociodemographic characteristics Years of residence Total number of household members Number of household laborers Average age of household laborers Average educational level of household laborers Table 4 Discriminant analysis of differences among labor-migrant, local off-farm work, and farming households, given as F values of variables Model 1 Model 2 Model 3 Model 4 Model 5 Final model 10.78*** 0.47 1.63 0.12 13.94*** 0.50 1.41 0.05 4.34* 0.58 0.01 10.77*** 0.76 1.91 0.07 3.24* 0.59 0.12 3.77* 0.64 6.94** 9.84*** 0.82 2.20(*) 0.07 3.09* 0.52 0.07 3.97* 0.64 5.42** 0.57 0.26 0.44 3.76* 0.85 1.42 0.01 4.48* 0.35 0.28 1.90 0.26 3.05* 2.42(*) 0.26 0.08 3.36* 0.25 28.28*** 6.30** 3.52* 685 5.61** 2.38(*) 5.29** 2.84* 3.87* 3.11* 3.27* 38.70*** 6.91** 3.95* ***sig. at the .001 level; **sig. at the .01 level; *sig. at the .05 level; (*) marginally sig. at the .1 level addition, farming households tended to have older and less educated laborers than the other two groups, which had almost the same aggregate results in this regard. The final model included six livelihood variables and four household socio-demographic characteristics. Per capita annual cash income and the yield of rice per mu of land showed significant effects again in the analysis. As compared with the final reduced model for the multivariate comparison of labor-migrant and non-labor-migrant house- holds, two more livelihood variables (size of per laborer cultivated land and expense of farming chemicals per mu of land) became significant in this model. Discussion This study empirically assesses the conceptual framework incorporating household livelihoods as a key mediating factor between rural migration and the rural environment. Results showed that with the exception of use of agricul- tural technologies, at least one variable measuring each livelihood construct in the conceptual model was statisti- cally significant (albeit marginally significant in some cases) in differentiating rural labor-migrant households and non-labor-migrant households. In the discriminant analysis of differences among labor-migrant, local off- farm work, and farming households, all livelihood con- structs had at least one measure with significant effect. These findings confirm the research hypothesis that labor- migrant and non-labor-migrant household are significantly different with respect to livelihood activities. Results also show that rural non-labor-migrant house- holds are more heterogeneous than the literature often suggests. The comparison of labor-migrant, local off-farm work, and farming households found more significant differences among household groups than the comparison between labor-migrant and non-labor-migrant households in both the bivariate and the multivariate analyses. In sum, the analysis showed that livelihood differences between labor-migrant and non-labor-migrant households were largely due to the differences between labor-migrant and farming households, while labor-migrant households shared many similar livelihood characteristics with local off-farm work households. The livelihood differences between rural labor-migrant and non-labor-migrant households have important implica-