Some Geographic Dimensions of Being Work-Rich and Work-Poor: Changes Between 1986 and 1996

SOME GEOGRAPHIC DIMENSIONS OF BEING WORK-RICH AND WORK-POOR: CHANGES BETWEEN 1986 AND 1996[1]

Paul Callister

Sociology and Social Policy Department

VictoriaUniversity of Wellington

Consider for a moment a neighbourhood in which most working-age women are not in paid jobs. This may conjure up a picture of tidy homes, children at play and gossip. Now think of a neighbourhood in which most men are jobless. The picture is more sinister. Areas of male idleness are considered, and often are, places of deterioration, disorder and danger. Non-working women are mothers; non-working men, a blight. (The Economist, 28 September, 1996:27)

INTRODUCTION

A geographic dimension is increasingly considered to be of importance in research on the distribution of paid work, income, wealth, and well-being within industrialised societies (e.g. Crampton et al. 1997, Cutler and Glaeser 1995, Gregory and Hunter 1995, Morrison 1993a). Such research recognises that in areas where a high proportion of people, and particularly working-age men, are not in paid work this may impact negatively on a range of economic, social and health indicators for the residents in these communities. For example, having high unemployment in a community can be associated with lower levels of provision and quality of services such as shops, transport, health facilities, schooling, and housing. Van Kempen (1997) even suggests that in" poverty pockets" the quality of welfare delivery could be lower than in other areas. There may also be "neighbourhood" effects in terms of negative role models and social norms (e.g. Case and Katz 1991).[2] Conversely, research also suggests that communities which are cohesive through a high rate of participation in community-based activities are also those which are economically prosperous (Putnam 1993).[3]

People with certain similar characteristics tend to cluster together in particular geographic areas. Various reasons have been proposed as to why this might occur. These include the provision of low-cost public housing bringing together low-income people; inner-city crime forcing middle-class residents out to the suburbs; or only high-income people being able to afford the prime geographic sites (e.g. Coleman 1997, Mills and Lubuele 1997). Research in the United States shows that clustering by some characteristics, such as religion or ethnicity, can result in a relatively wide mix of employment and income-earning ability in a community (Wilson 1987). However, the same research suggests that in black, inner-city ghettos the well educated have tended to move out in recent years.[4] With educational attainment increasingly representing a key factor in determining labour market outcomes for individuals, clustering by educational attainment is far more likely to lead to a homogeneous community in terms of employment patterns and income. Again in the United States, Hermstein and Murray (1996:xxi-xxii) argue that those with good jobs, education and incomes ".. .gravitate to one another, increasingly enabled by their affluence and by technology to work together and live in one another's company - and in isolation from everybody else". Similarly, the Brookings Institution (1997) describes how "gated" residential communities with private security guards, private gardeners, and other private facilities are becoming more common in the United States for those in the upper-income brackets. Linking this to changes in employment, Reich (1993) describes how highly educated people with "symbolic-analytical" type jobs are increasingly well placed in both local and international labour markets. Reich also discusses the manner in which this group "share" their income:

In allocating personal income, the symbolic analyst has shown no lack of willingness to engage in collective investment. But increasingly, the public goods that result are shared only with other symbolic analysts. Symbolic analysts take on the responsibilities of citizenship, but the communities they create are composed only of citizens with incomes close to their own. In this way, symbolic analysts are quietly seceding from the large and diverse publics of America into homogeneous enclaves, within which their earnings need not be redistributed to people less fortunate than themselves. (p.268)

Reich goes on to suggest that as the highly educated, high-income groups seek tax cuts they effectively"... withdraw their dollars from the support of public spaces shared by all and dedicate the savings to private spaces they share with other symbolic analysts." There I is also a range of other policy implications that arise as a result of similar people grouping together. For example, there is a concern in both New Zealand and overseas about the quality of schooling in areas where low-income people are concentrated.

This paper explores some geographic dimensions of two factors that strongly influence the distribution of paid work, income, wealth, and ultimately, well-being. These are participation in paid work and, linked to this, educational attainment. In particular, the paper examines whether, in parallel to the growth of work-rich and work-poor individuals and families (Callister 1998), some geographic areas are also becoming work poor or work rich. Finally, in order to assess the possible relationship of paid work to a wider concept of well-being, a New Zealand index of deprivation is compared with the geographically based employment data.

DEFINITIONS

Geographic Areas

In New Zealand, there has recently been some interest in building stronger communities. This includes the concept of delivering more services and developing employment initiatives at a community level. Unfortunately, the concept of a community is often unclear. In a recent "thinkpiece" the Department of Internal Affairs (1997) acknowledges that the term "community" has a variety of meanings, with only one of them being the place in which people live. For this research, it would be useful if there were geographic areas that were not only places to live and interact socially, but were also geographically defined labour markets. In Wellington, Morrison (1995) found that a significant proportion of people worked locally. However, he also found that people in areas that were "job-poor", in general, had to travel the greatest distances when in paid work. In some other communities, such as rural areas, people often live where they work such as on a family farm. However, even in traditional farming areas many people now commute to off-farm jobs. In addition, improved communications and globalisation of work mean that a workplace could also be a home, but with the employer on the other side of the world rather than across town. While these complexities are important in understanding the changing dynamics of communities, in this research I focus on the areas in which people live.

The smallest geographic area used by Statistics New Zealand is the meshblock. There are three disadvantages associated with using meshblocks. Firstly, the small number of people in each meshblock can present confidentiality problems, thereby limiting the analysis. Secondly, as meshblocks often represent only a couple of streets they may be too small to, create "neighbourhood effects". However, most importantly, meshblocks have coded names which are not generally recognisable. Having recognisable names assists policy makers and the general public locate and consider the characteristics of an area.

The first aggregation of meshblocks is an area unit. Area units are easily identified as each area unit must be a single geographic entity with a unique name referring to a geographical feature. For this research, work patterns within 1,636 area units were analysed (see appendix for a more detailed discussion of issues involved in selecting the areas to be analysed).

Work Rich and Work Poor Area Units

In a previous paper, the concept of work-rich and work-poor prime-age individuals and families was explored (Callister 1998). Prime-aged people were defined as being in the 25-59 age group. There are, however, various possible measures for determining the work status of a geographic area (see appendix for a brief discussion). In this study a new approach was taken. First, the hours of paid work were added together for every prime-age person in each area unit. This measure of total hours of paid work in each unit was then divided by the total population, whether in paid work or not, in the target age group in each area. This gave an average of hours of involvement in paid work per person per week across the total prime-age population.[5] This calculation was carried out using data from the 1986, 1991 and 1996 censuses to provide a time series. This type of measure controls for differences in population in each area unit, although there are still some problems with a potentially changing age distribution within the prime-age group within each area.

SOME GEOGRAPHIC CHANGES IN HOURS OF PAID WORK

As discussed in Callister (1998), there were major changes in the population, participation in paid work, and hours worked for prime-aged women and men between 1986 and 1991, and again between 1991 and 1996. Overall, the changes at a national level meant that in 1986 there were 32.7 hours worked per week for each prime-age person, in 1991 this had declined to 29.3 hours, and then in 1996 increased back to 32 hours only slightly under the 1986 figure.

Table 1 shows the proportion of communities that might be considered work rich or work poor using five cut-off points. It firstly shows that, like poverty lines, there can be great sensitivity around the choice of cut-off point for work-poor area units. However, the table does show a rise in the proportion of areas that were work-poor, in each of the chosen measures, between 1986 and 1996. In contrast, there was little or no rise in the proportion of areas that were work rich. It also shows that the loss of paid work between 1986 and 1991 had an impact on a significant number of areas within New Zealand.

Table 1 Percentage of Area Units by Average Hours of Paid Work: Prime-Age People

Average hours per person / 1986 / 1991 / 1996
Under 20 hours (work poor 1) / 0.4 / 4.1 / 1.4
Under 25 hours (work poor 2) / 1.7 / 15.2 / 7.4
Under 30 hours (work poor 3) / 15.3 / 52.0 / 27.4
35 or more hours (work rich 1) / 24.6 / 11.9 / 25.4
40 or more hours (work rich 2) / 6.2 / 2.8 / 6.2

Source: Census of Population and Dwellings, Statistics New Zealand.

However, Table 1 provides no idea of whether it was the same areas that were work-rich or work-poor in each census period.

Figure 1 shows the distribution of area units by average hours for prime-age people in 1986 as well as the average hours for the same areas ten years later. The data for each area unit are presented in ascending order of 1986 average number of hours of paid work (the white line), and the 1996 data for each area unit are plotted in black.

Figure 1 Average Hours of Paid Work for Prime-Age People in Area Units in 1986 and Average Hours in These Same Areas in 1996

Source: Census of Population and Dwellings, Statistics New Zealand.

The graph shows that there were considerable changes in the average hours per person in many individual area units. However, the extremely large shifts tended to be in very small area units.[6] Overall, in this period of initial major job loss followed by strong employment growth the average hours worked per person per week declined in 57% of area units.

There are many dimensions to these changes, including some differences between urban and rural areas. To illustrate this, Figure 2 restricts the analysis to changes within the Auckland urban area between 1986 and 1996. When compared with Figure 1 the graph shows that there were far fewer areas which had very high average hours of paid work in 1986. In addition, there was a decline through to 1996 in average hours per person of those ten areas with the highest hours in 1986. In some of these areas, this simply reflects a process of urbanisation in which farmland, where people tend to work long hours, was subdivided. However, of more interest to policy makers was the decline in average hours of paid work between 1986 and 1996 in many of those areas which were already work poor in 1986. These areas include communities well known to researchers and social service agencies including Otara East, Otara West and Glen Innes East.[7] The one community within those ten with the lowest average hours ofpaid work in 1986 that did show a marked increase in average hours was Point Chevalier South. This primarily reflects "gentrification" which, in turn, was linked to changes in government housing policy. Former state houses, which were in a prime location close to the harbour and city centre, were sold to higher-income people. This gentrification process can be seen in the proportion of the prime-age population in this area who had a degree or higher qualification. In 1986, 5% of the prime-age population in Point Chevalier South had a degree or higher, which was below the national average. However, by 1996, in this area unit the proportion of the prime-age population with a degree or higher had risen to over 16%, over the national average. This example, and the rural subdivision example, illustrate some ways in which the work status of a community can change over time.

Figure 2 Average Hours of Paid Work forPrime-Age People in Area Units in the

Auckland Urban Area in 1986 and 1996

Source: Census of Population and Dwellings, Statistics New Zealand.

In order to provide a further New Zealand-wide analysis, area units were grouped into deciles by their average hours of paid work per person in each census. Given the concern about the lack of paid work in many area units, there is a particular focus on the status and characteristics of a group of area units that might be considered to be work poor. These are the area units in the bottom decile.[8] In contrast, work-rich area units are seen as those in the top decile of hours of paid work.

Of those area units that were in the bottom decile of hours in 1986, 60% were still in the bottom decile in 1991. The movement out of the bottom decile was not as strong in the next five years, despite this being a period of significant overall employment growth. Of those area units that were in the bottom decile of hours in 1991, 78% were again in the bottom decile in 1996.

Overall, 52% of those area units in the bottom decile in 1986 were still in the bottom decile in both 1991 and 1996. In addition, of those in the bottom decile in 1986, 82% were in the bottom two deciles in 1996, a further 7% in the third to bottom decile, and 4% had moved into the forth to bottom decile. Only two very small rural areas rose from the bottom decile in 1986 to reach the third to top decile by 1996. Also noteworthy is the fact that the average hours of paid work per person increased between 1986 and 1996 in only 32% of the area units in the bottom decile in 1986.[9]

These data lend some support to the Australian work of Gregory and Hunter (1995), whichfound that in particular areas labour market disadvantage continues over a long period. But the data also suggest that there is some, albeit limited, mobility of area units in terms of average hours of paid work undertaken.

Of critical importance, however, is whether large groups of people remain for long periods in work-poor areas. Some US research suggests that there is considerable movement in and out of poor urban areas, even amongst those people who are persistently poor (Gramlich et al. 1992)[10] Gregory and Hunter gave no indication as to whether the same people were in the disadvantaged communities in each time period. In New Zealand, it may be that a high proportion of people spend a short time in work-poor area units and ) move out when their employment prospects, education or income improve. Or, it may be that many people are mobile but simply move from one work-poor area to another work-poor area. Such mobility may be due to insecure housing arrangements rather than for more positive reasons. These New Zealand data do not directly shed light on these issues. However, in some area units, such as Otara East, North and South, which were work-poor in each census, there was a high concentration of people from PacificIsland ethnic groups in each time period. If there had been a considerable level of mobility this concentration might be expected to reduce (although this might be masked by inward migration), and that there would be far more Pacific Island people living in work-rich areas. In addition, in a study of the long term unemployed, Parker (1997) notes that around 40% of the respondents stated that they could not move to areas with more jobs. These data would suggest that there may only be limited mobility for at least some groups of people.