Hum Ecol (2010) 38:675–690 the analysis, blocks of variables were added to build multiple models to examine interactions among variables measuring different livelihood constructs, and to assess the extent to which different sets of livelihood variables distinguish household groups. A final reduced model was estimated by systematically removing non-significant var- iables from the full model until all the variables remaining in the model had significant effects. The results of discriminant analysis of differences between labor-migrant and non-labor-migrant households in livelihood activities are presented in Table 3.6 The first model included only the four agricultural production variables. The size of per laborer cultivated land and the yield of rice per mu of land had statistically significant effects in differentiating the two household groups (though only marginally significant for rice production). On average, households with labor migrants cultivated less farmland on a per laborer basis and had lower rice production for each mu of farmland than those without migrant members. In Model 2, variables measuring agri- cultural technology use were introduced into the discrim- inant analysis. The size of per laborer cultivated land remained statistically significant in distinguishing between household groups, but the yield of rice per mu of land was no longer significant. None of the three technological use indicators had significant effects in the model. Model 3 added the three income and consumption variables. The size of per laborer cultivated land remained a powerful differentiator between labor-migrant and non- labor-migrant households. The yield of rice per mu of land became marginally significant again in the analysis. Variables measuring the use of technologies were still not statistically significant. Of the three newly introduced income and consumption indicators, only per capita annual cash income had a significant effect. Controlling for the effects of other variables in the model, labor-migrant households had higher levels of rural cash income than non-labor-migrant households on a per capita basis. The measures of natural resource use and management were introduced in Model 4, which included all the thirteen livelihood variables. None of the newly added indicators showed significant effects in the model. However, the three key differentiators in Model 3 (size of per laborer cultivated land, yield of rice per mu of land, and per capita annual cash income) retained their statistical significance. The full model (Model 5) added household socio- demographic characteristics to the discriminant analysis. All the five variables except household size showed 6 Because of the exploratory nature of this study, the analysis set a .10 significance threshold instead of the more conventional .05 signifi- cance level. 683 significant differences between the two household groups. Labor-migrant households lived longer in the village and had more laborers than non-labor-migrant households. Their active labor members also tended to be younger and more educated. With the inclusion of socio-demographic characteristics, the size of per laborer cultivated land and the yield of rice per mu of land were no longer statistically significant in distinguishing labor-migrant households from non-labor-migrant households. Per capita annual cash income remained statistically significant, but with weaker effect than in the previous models. Two other livelihood variables, the household consumer asset index and the proportion of firewood and crop residues in total fuels, became significant in the full model. Non-labor-migrant households on average owned fewer consumer assets and depended more on natural resources for fuel. Finally, a reduced model was obtained by systematically eliminating non-significant variables from Model 5. The final model for multivariate comparison of labor-migrant and non-labor-migrant households included the yield of rice per mu of land, per capita annual cash income, consumer asset index, proportion of firewood and crop residues in total fuels, and four household socio-demographic charac- teristics (length of residence, number of laborers, mean age of laborers, and mean educational level of laborers). Although the size of per laborer cultivated land attained statistical significance in the first four models, it was not significant in the full and the reduced models. This change suggests that the difference between labor-migrant and non- labor-migrant households in per laborer cultivated farmland is explained away by their differences with respect to socio- demographic variables. Multivariate Discriminant Analysis for Labor-Migrant, Local Off-Farm Work, and Farming Households In order to enhance our understanding of the impacts of rural migration on household livelihoods, block discrimi- nant models were also used to analyze differences among the three more narrowly-defined subgroups in the survey sample: labor-migrant households, local off-farm work households, and farming households (Table 4). When the model contained only the four agricultural production variables (Model 1), the size of per laborer cultivated land was statistically significant. Farming households in general cultivated more land than the other two groups on a per laborer basis. On average, each laborer of a local off-farm work household farmed approximately the same amount of land as that of a labor-migrant household. The other three variables were not significant. Model 2 added the agricultural technology use measures to the multivariate analysis. The significance of the size of per laborer cultivated land remained unaffected. Expense of