This appendix contains eight sections. Section 1 gives technical details of how we calculate standard errors in the CPS data. Section 2 discusses changes in the ACS procedures before 2005. Section 3 examines demographic and economic patterns in migration over the past two decades, in more detail than in the main paper. Section 4 examines the cross-sectional variance of location-occupation interactions in earnings when we define locations by MSAs instead of states. Section 5 describes alternative methods to estimate the variance of location-occupation interactions in income. Section 6 measures the segregation of industries across states and of occupations and industries across MSAs. Section 7 gives technical details on the use of SIPP and census data to calculate repeat and return migration rates. Section 8 discusses transition dynamics in the model.

We analyze the secular decline in interstate migration in the United States between 1991 and 2011. Gross flows of people across states are about 10 times larger than net flows, yet have declined by around 50 percent over the past 20 years. We argue that the fall in migration is due to a decline in the geographic specificity of returns to occupations, together with an increase in workers’ ability to learn about other locations before moving there, through information technology and inexpensive travel. These explanations find support in micro data on the distribution of earnings and occupations across space and on rates of repeat migration. Other explanations, including compositional changes, regional changes, and the rise in real incomes, do not fit the data. We develop a model to formalize the geographic-specificity and information mechanisms and show that a calibrated version is consistent with cross-sectional and time-series patterns of migration, occupations, and incomes. Our mechanisms can explain at least one-third and possibly all of the decline in gross migration since 1991.

We estimate the factors determining specialization of crop choice at the level of individual fields, distinguishing between the role of natural advantage (soil characteristics) and economies of density (scale economies achieved when farmers plant neighboring fields with the same crop). Using rich geographic data from North Dakota, including new data on crop choice collected by satellite, we estimate the analog of a social interactions econometric model for the planting decisions on neighboring fields. We find that planting decisions on a field are heavily dependent on the soil characteristics of the neighboring fields. Through this relationship, we back out the structural parameters of economies of density. Setting an Ellison-Glaeser dartboard level of specialization as a benchmark, we find that of the actual level of specialization achieved beyond this benchmark, approximately two-thirds can be attributed to natural advantage and one-third to density economies.

In the last century, the evolution of female labor force participation has been S-shaped: It rose slowly at first, then quickly, and has leveled off recently. Central to this dramatic rise has been entry of women with young children. We argue that this S-shaped dynamic came from generations of women learning about the relative importance of nature (endowed ability) and nurture (time spent child-rearing) for children’s outcomes. Each generation updates their parents’ beliefs by observing the children of employed women. When few women participate in the labor force, most observations are uninformative and participation rises slowly. As information accumulates and the effects of labor force participation become less uncertain, more women participate, learning accelerates and labor force participation rises faster. As beliefs converge to the truth, participation flattens out. Survey data, wage data and participation data support our mechanism and distinguish it from alternative explanations.