"... In PAGE 3: ... Although this paper focuses on the relationship between income prospects and migration decisions at the start of the life cycle, suitably modified versions of the model can potentially be applied to a range of issues, such as the migration effects of interstate differences in welfare benefits, the effects of joint career concerns on household migration decisions, and the effects on retirement migration of interstate differences in tax laws.4 2 Migration Dynamics The need for a dynamic analysis of migration is illustrated in Table1 , which summarizes interstate migration histories of young people in the NLSY. Two features of the data are noteworthy.... In PAGE 36: ... Table1 0: Estimates from Simulated Migration Histories NLSY 10 Reps 100 Reps 1000 Reps t Disutility of Moving ((0) 4.305 4.... ..."

"... In PAGE 35: ...Appendix B: Validation of ML Estimates The parameter estimates from Table 2 were used to generate replicas of each NLSY observation, starting from the actual value in the NLSY data, and allowing the model to choose the sequence of locations. Table10 gives results for 10, 100, and 1,000 replicas of each NLSY observation. The last column reports the t-value testing the difference between the 1,000 replica estimates and the individual DGP parameters; the last row reports likelihood ratio tests of the hypothesis that the data were generated by the process that did in fact generate them (assuming that the simulation program works) .... ..."

"... In PAGE 16: ... Model (B) adds measures for number of siblings, birth order, family income, religion, parental schooling, and AFQT (in the NLSY) to Model (A). Estimates using the NLSY are presented in Table3 , and those using the PSID are presented in Table 4. All standard errors are adjusted using the Huber-White method to account for the correlation between observations from the same family.... In PAGE 17: ...esults to be robust. In appendix tables B.1 and B.2 we use dummy variables for family structure instead of proportion living in a particular family structure. The estimates presented in Table3 fit the data better than those using family structure dummies but tell the same ... ..."

"... In PAGE 21: ... One can make a strong case that gender and race are exogenous, but sibship size (number of siblings), religion, and parental schooling can be considered endogenous to the family. Results for these models are presented in Table3 . Like previous research, our OLS and probit cross-section Models (A) and (B) show that years with a single parent or stepparent have negative and significant effects on schooling outcomes.... In PAGE 21: ... Years with a stepparent have negative and significant effects on college attendance and graduation.9 The fixed effects estimates in Table3 tell a different story. For all four schooling outcomes, the family structure variables are not statistically significant.... In PAGE 21: ... As reported in Tables 1 and 2, more of the variation in schooling outcomes occurs between than within households. 9 We have experimented with alternative specifications in Table3 and found our results to be robust. We used dummy variables for family structure instead of years living in a particular family structure.... In PAGE 21: ... We used dummy variables for family structure instead of years living in a particular family structure. The estimates presented in Table3 fit the data better than those using family structure dummies but tell the same story. In Model (B) we substituted dummy variables for number of siblings to account for nonlinearities in the effect of family size on outcomes.... ..."