The paper develops a tractable econometric model of optimal migration, focusing on expected income as the main economic influence on migration. The model improves on previous work in two respects: it covers optimal sequences of location decisions (rather than a single once-for-all choice), and it allows for many alternative location choices. The model is estimated using panel data from the NLSY on white males with a high school education. Our main conclusion is that interstate migration decisions are influenced to a substantial extent by income prospects. The results suggest that the link between income and migration decisions is driven both by geographic differences in mean wages and by a tendency to move in search of a better locational match when the income realization in the current location is unfavorable.2 See Greenwood [1997] and Lucas [1997] for surveys.3 Holt (1996) estimated a dynamic discrete choice model of migration, but his framework modeled the move/stay decision and not the location-specific flows. Similarly, Tunali (2000) gives a detailed econometric analysis of the move/stay decision using microdata for Turkey, but his model does not distinguish between alternative destinations. Dahl (2002) allows for many alternative destinations (the set of States in the U.S.), but he considers only a single lifetime migration decision. Gallin (2004) models net migration in a given location as a response to expected future wages in that location, but he does not model the individual decision problem. Gemici (2007) extends our framework and considers family migration decisions, but defines locations as census regions.

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Attrition, screening, and signalling models of strategic bargaining are characterized in terms of their predictions about the incidence, mean duration, and settlement rates of strikes and the terms of wage settlements. These predictions are compared with the general features observed in empirical studies of strikes in Canada and the United States. Conclusions are drawn about the types of models capable of generating these features, and about the conformity of the models to the evidence. Methods are described for computing the numerical examples used to illustrate the models.

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