Academic journal article The Economic and Labour Relations Review : ELRR

Location and Unemployment

Academic journal article The Economic and Labour Relations Review : ELRR

Location and Unemployment

Article excerpt

1. Introduction

Access to the social and economic benefits of employment varies widely across the regions of Australia. This reflects both the inability of people with poor labour market prospects to afford to live close to available jobs, and the direct impact of local labour market conditions. In this paper we seek to shed light on the latter mechanism, using administrative data on receipt of income support. What impact do local labour market conditions have on the likelihood of exit from (or receipt of) unemployment benefit payments?

In Australia, it is well recognised that unemployed (or nonemployed) people tend to be concentrated in particular regions, and there is some evidence that this association has increased over time in Australia (Gregory and Hunter 1995). However, it is equally well recognised that it is difficult to separate out the effects of local labour markets from the characteristics of people that tend to live in different regions (McDonald, 1995).

The high unemployment rates that are observed in the outer suburbs of the major cities may be due to regional characteristics that make it difficult to find work, such as poor public transport and an inadequate supply of child-care. Additionally, the concentration of disadvantaged people in these regions may lead to further social problems, which further disadvantages those living there. Both of these impacts we describe as locational impacts. (In this study we focus on labour market conditions as our key locational indicator--other social factors are only considered to the extent to which they are associated with labour market conditions).

However, it is also possible that the high unemployment regions in the outer suburbs of the major cities may have high unemployment rates because these are the only areas in which individuals that are disadvantaged in the labour market (such as the long-term unemployed and long-term low wage workers) can afford to live. That is, the outcomes are a reflection of the individual characteristics of the people that can afford to live there.

The policy implications of these two sets of explanations are quite different. For some targeting purposes, it may not matter whether it is locational impacts or individual characteristics that lead to an association between high unemployment regions and low exit rates from benefit. For example, if we are trying to identify which people are most likely to have a long spell of income support receipt.

However, for many policy purposes the direct impact of location is important. For example, in Australia, unemployment payment recipients are penalised if they move to an area of higher unemployment, because it is assumed that this will reduce their employment prospects. This 'Move to an Area of Lower Employment Prospects' (MALEP) exclusion rule means that people who move to an area of higher unemployment may be excluded from benefit receipt for a period of 26 weeks. (1) Such a policy may be defensible if location does indeed matter for employment prospects. However, if people with low levels of labour market skills will remain unemployed wherever they live, then such a policy has little merit.

Indeed, if location has a direct impact on individual labour market outcomes, this has implications for both labour market and housing policies. Whether or not this arises from direct labour market effects or broader neighbourhood effects, it suggests a greater need for regionally-specific labour market policies and for housing policies that encourage unemployed people to move to better labour markets. The latter might include policies to increase the supply of affordable housing in strong labour markets, or policies to increase rental assistance to people in higher housing cost regions. (2)

In this paper we estimate the impact of local labour market conditions on unemployment related income support receipt using data from the Australian Department of Family and Community Services (FaCS) Longitudinal Data Set 1 per cent sample (LDS). …

Search by... Author
Show... All Results Primary Sources Peer-reviewed

Oops!

An unknown error has occurred. Please click the button below to reload the page. If the problem persists, please try again in a little while.