One of the problems with empirical studies of migration (as with a lot of empirical research) is that we don't observe the counterfactual. In the data, we see people migrating, and where they migrate to, but we don't see what they don't do. For migrants, we don't see where they would otherwise have migrated to, or if they wouldn't have migrated at all. For non-migrants, we don't see where they would have migrated to. What would be ideal would be to see potential migrants making lots of migration decisions, or ranking the available options. Lab experiments may help here, since we can ask research participants about a lot of hypothetical choices, where the parameters of the choices are controlled by the researcher. Because the choices are hypothetical, they may not line up with what potential migrants would actually do, but that illustrates the trade-off we face in this sort of research.
This recent working paper by Catia Batista (Universidade Nova de Lisboa) and David McKenzie (World Bank) provides some lab experiment evidence on migration decision-making, and uses the data to test some classic migration theories (the Roy model, that was critiqued by Michael Clemens, as I noted in yesterday's post, and the Sjaastad model, which I briefly discussed in that post as well). Batista and McKenzie collected data from university students in their final year of study - 154 students in Lisbon, and 265 students in Nairobi. Since university graduates are among the population groups most likely to migrate, these are appropriate research participants for asking hypothetical migration questions.
The experimental study asked research participants to choose between two (or sometimes three, or five) destinations, where the destinations had differences in wages, cost of relocating, the risk of unemployment, and the availability (and generosity) of social insurance in case of unemployment. Some scenarios also had incomplete information, and the research participants could buy information before making their decision. Research participants also had randomly allocated observed and unobserved skill levels (which determined the wages) and wealth endowments (which determined whether they could afford the costs of moving, and pay for information). In all, each research participant made 24 choices under different conditions.
There is far too much detail across the individual games (or groups of games) for me to summarise them all here (for that, I recommend reading the working paper). However, the paper did have some important takeaways. First:
Our results show that adding real-world features which take account of liquidity constraints, risk and uncertainty, and incomplete information to the classical Sjaastad/Borjas migration model makes a huge difference in terms of predicting the rate of migration and the selection pattern. The largest impact comes from adding risk (of unemployment) to the migration outcome.
The relative impact of the different features added to the migration decision-making process was based on a regression model that included the various characteristics of the game as explanatory variables for the decision to migrate (rather than not migrate). This is interesting, but I wonder about the external validity of the results beyond the particular values of the features used in the experimental choices. While the values that Batista and McKenzie use are plausible and based on real-world equivalents, I think we need more studies of this type with a wider range of values (and across more contexts) before we can derive some strong conclusions about which real-world features of the migration decision have the largest effect.
One of the most interesting parts of the paper, was where Batista and McKenzie test the independence of irrelevant alternatives assumption that is inherent in many migration models. That assumption essentially says that the relative probability of choosing to migration to a destination x1 rather than x2 doesn't depend on whether the potential migrant could have chosen x3 or not. Batista and McKenzie look at this by comparing the relative choices when there are two options, three options, or five options available (and where some of the options are clearly inferior to the original two options). They find that:
...the independence of irrelevant alternatives (IIA) assumption, which underlies many models of multi-destination migration choices, holds well for simple migration decisions that just involve comparisons of costs and wages in a developed country setting, but even in these simple cases, violations occur for 14-21 percent of our sample in Nairobi. Moreover, when the risk of unemployment and incomplete information are added, IIA no longer holds for 20 percent of the people in our game in Lisbon. Since most real-world migration decisions involve considerable risk and incomplete information, real-world violations of IIA are likely to be non-trivial.
Whether you interpret those results as being favourable for the IIA assumption or not is pretty subjective (and probably depends on some motivated reasoning depending on what migration model you want to use!). It is interesting to me that in the simplest decisions, there was a non-trivial level of violations of the IIA assumption in the Nairobi sample. Violations of IIA were not systematically different based on any of the characteristics of the research participants, including their migration preferences, level of risk aversion, or ambiguity aversion. Again, this would be worth following up further in other contexts.
Finally, and probably the most important (and a useful caution) for those who prefer the Sjaastad model of migration (like Michael Clemens and myself), income maximisation was not universal, as:
...even in the simplest settings, people do not always make the destination choice which maximizes net income. Instead, cost minimization seems to be a key decision factor in the migration decision – particularly for individuals in the Nairobi sample.
It would have been nice to see another regression model demonstrating the factors that were associated with making cost minimising, rather and income maximising, choices. I wonder about the extent to which risk aversion was playing a role here (the Nairobi sample appeared to be more risk averse across two of the three measures than the Lisbon sample), especially as Batista and McKenzie note that:
Seventy-five percent in Lisbon and 84 percent in Nairobi of those who do not migrate in Game 6, even though they have positive expected returns from doing so, are risk averse according to the Dohmen et al. (2011) measure.
A risk averse potential migrant might be more inclined to cost-minimise, rather than income-maximise, especially as in Game 6 that Batista and McKenzie refer to, the chance of unemployment was endogenous, and depended on the number of other research participants in the same session who chose to migrate to that destination. If you are worried about unemployment, and risk averse, then you are more likely not to migrate. Again, something to explore more, and in additional contexts.
Overall, I think there is a lot more that can be done to explore migration experimentally. This paper provides a useful starting point for what will, hopefully, build into an interesting contribution to our understanding of migration decision-making.
[HT: David McKenzie on the Development Impact blog]
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