Inferring Age and Spatial Patterns

Andrei Rogers (), James Raymer () and Jani Little ()
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Andrei Rogers: University of Colorado, Boulder Inst. Behavioral Science Population Program
James Raymer: University of Southampton, School of Social Sciences
Jani Little: University of Colorado Institute of Behavioral Science

Chapter Chapter 6 in The Indirect Estimation of Migration, 2010, pp 121-153 from Springer

Abstract: Abstract In this chapter, we focus on methods for estimating migration flows in the absence of migration data. To obtain the patterns of interest, we use auxiliary information. Our examples illustrate both current and historical applications of indirect estimation. In Section 6.2, a model for estimating the age composition of out-migration in the United States from aggregate totals of out-migration and population age compositions is presented. This work draws from a recent paper by Little and Rogers (2007). The possibility of using 0–4 year old birthplace-specific population stocks to estimate interregional migration flows is demonstrated in Section 6.3, following work set out in Rogers and Jordan (2004) and Raymer and Rogers (2007). We then apply the methodology to estimate the historical (and completely missing) migration flows for the 1905–1910 and 1915–1920 periods. Finally, in Section 6.4, we focus on the potential for merging migration data obtained from multiple sources. Here, the aim is to follow Frans Willekens’s recommendation that “in order to compile coherent and internally consistent information on migration, data from several sources ought to be combined” (Willekens, 1994, p. 31). Smith, Raymer, and Giulietti (2010), for example, follow this advice by combining census, registration, and survey migration data in England and Wales.

Keywords: Model Schedule; American Community Survey; Migration Data; Discriminant Function Analysis; Logistic Regression Method (search for similar items in EconPapers)
Date: 2010
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-90-481-8915-1_6

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DOI: 10.1007/978-90-481-8915-1_6

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