Migration, labour demand, housing markets and the drought in regional Australia
- Executive summary
- Theoretical model of migration
- Background: Population dynamics in rural and regional Australia
- What is a drought?
- Selected data issues
- Labour market, housing market, migration and drought
- Descriptive analysis of relationships between recent drought and migration
- Multivariate analysis of out-migration, in-migration and net migration
- Drought and mobility in the RRFS
- Lists of tables and figures
- Appendix A: Gross migration flows across drought categories (total population)
- Appendix B: Gross migration flows across drought categories (all workers in the agricultural industry)
- Appendix C: Regression results
Theoretical model of migration
To understand the economic factors associated with migration, we follow the basic human capital model as developed in Sjaastad (1962), Harris and Todaro (1970) and elsewhere. According to this model, migration occurs when the anticipated future income stream available at a potential destination is greater than the future income stream at the person's current location plus the costs of migration. Individuals may therefore choose to move if they see another area as giving them a greater chance of obtaining employment or, if they are already employed, gaining a job with higher remuneration.
It is assumed, however, that the costs of migration are far from negligible. Hence, even if people do predict that there are areas where their income will be higher than it currently is, the increase in their predicted income from moving may not be enough to cover the costs of migration. These costs are perhaps best represented via a gravity model (developed originally in the 1940s, e.g., by Stewart, 1947). According to the modified gravity model in Greenwood (1997), the probability of moving between two areas is based in part on the size of the origin and destination populations, but inversely related to the distance between the two areas. The distance between the two areas is said to proxy the cost of migration, which could be either social or economic:
- Social (psychic) costs of migration: The main social cost of moving is related to the effect it has on a person's ability to maintain their existing social networks. The greater the distance between two areas, the more costly and time-consuming it is to make frequent return visits to maintain the social networks developed in the area. Distances from their source areas aside, individuals are able to build new social networks in their destination area. This is a possible reason why people move to areas with a high concentration of individuals with similar characteristics to themselves (based on ethnicity, country of birth, language, etc.) Other costs of migration are likely to vary throughout a person's life cycle. For example, those in mid- to late secondary school who move schools are likely to experience significant disruption to their studies (above and beyond the disruption to their peer social networks).
- Economic costs of migration: Moving to another area can also involve reasonably large economic costs. Firstly, there are the direct physical costs of moving oneself and one's family (e.g., transport, removalists, searching for accommodation). Secondly, especially in the short term, a family that moves may have to forego some of their income. That is, even though a person's income may increase in the long term, wages often decline in the short term because people lose firm specific human capital (Yankow, 2003). Furthermore, the opportunity costs in terms of spousal income may also be important; that is, for a married couple, moving to improve one spouse's income may come at the cost of their partner's income (Greenwood, 1997).
A further impediment to migration could be the uncertainty or risk involved with moving (Khwaja, 2002). If people already have a job lined up in another area, then they may be able to predict with reasonable accuracy the benefits of migration (at least in the short term). However, if people do not have a job in advance and are instead considering whether to move to improve their prospects of obtaining a job, then they may be less likely to feel that the uncertain future benefits are worth the risk (given the known economic and social costs).
To measure the association that area level variables have with migration decision, Biddle and Hunter (2006) assumed a two-step process. That is, individuals are assumed to first make the decision to move to a different SLA based on the characteristics of the source SLA or the SLA in which they lived in 2001. Once the decision to migrate has been made, the decision of where to move is assumed to be based on the characteristics of the potential destinations. Obviously this is a simplified assumption and, as pointed out by Greenwood (1997), individuals are likely to (a) make the decision to move based on the potential areas available to them; and (b) individuals are likely to make the decision about where to move based on where they are coming from.
Unlike Biddle and Hunter (2006), this report does not model the migration decision at the individual level because of a lack of access to the Census unit record data.1 Rather, we model the two migration decisions at an area level, using firstly the percentage of the population who moved out of an area between 2001 and 2006 (proxying for the decision to migrate), and secondly the percentage of the population who moved into an area between 2001 and 2006 (proxying for the choice of destination). We also separately model net migration or the difference between the rate of out-migration and in-migration in order to capture the effect of the two on population redistribution.
Notwithstanding the lack of suitable data to model the two-stage decision at an individual level, it is possible to use pairs of SLAs as the unit of analysis to model the joint effect of source and destination characteristics in influencing the two-stage migration decision. This is, however, left for future research.
1 There was an insufficient sample in the drought areas for the Census 1% sample to be of use for this analysis. The 5% sample for the 2006 Census has just been released, but the level of geographic detail provided is probably not adequate to analyse migration (ABS, 2009). For example, the lowest level of aggregation is statistical regions, and even then some of these regions have been aggregated in the released data.