Migration, Commuting, or a Second Home? Insights from an Experiment Among Academics

Abstract

In the last decades, more complex types of residential mobility, such as second homes, arose while one-way relocations declined. Existing studies that address migration and commuting as being substitutes often face problems of endogeneity or lack of data regarding decision-making on different types of residential mobility. In contrast, we investigate decision-making on migration, commuting, and establishing a second home by using a factorial survey experiment, which allows for the accounting of both endogeneity bias through randomisation and complexity in decision-making through treatment variation. Hypothetical job offers were presented to a sample of academic staff of a Swiss university (ETH Zurich) in order to examine the intended types of residential mobility and their drivers. Referring to the concept of loss aversion, the utility of a second home can exceed the joint utilities of migration and commuting particularly when the total loss of the current residence bears intolerable costs caused by location-specific capital, and daily commuting bears prohibitive costs caused by a lengthy distance. Analyses show that the migration intention is mainly caused by low migration and high transition costs and the commuting intention is mainly caused by low transition costs and high migration costs. Establishing a second home is indeed more intended with simultaneously higher migration and transition costs. In sum, a second home may be understood as a substitute for one-way relocations and daily commuting, yet primarily under conditions of extremely high or irreversible migration costs and unsustainable transition costs.

Keywords: Academics; Commuting; Experiment; Factorial survey; Migration; Second home.

Fig. 1

Vignette example

Fig. 2

Distributions of willingness to compete for the job and of the mobility intentions

Fig. 3

Second home intention across the difference between migration vs. commuting intention (fitted values)

Fig. 4

Heckman-corrected regression models on mobility intentions

Fig. 5

Interaction of property ownership and distance on mobility intentions (predicted values)

Fig. 6

Interaction of suitable housing and distance on mobility intentions (predicted values)

Fig. 7

Interaction of job of spouse and distance on mobility intentions (predicted values)

Fig. 8

Interaction of job chances of spouse and distance on mobility intentions (predicted values)