RDP 2016-06: Jobs or Hours? Cyclical Labour Market Adjustment in Australia 3. Why Has More Adjustment Occurred through Average Hours Worked?

The estimated date of the break in the late 1990s provides clues as to the source of this change in the nature of labour market adjustment. This date broadly coincides with a decline in the volatility of GDP growth in Australia. Also, this followed a period of substantial labour market reforms in the 1980s and 1990s. However, because these changes overlapped, it is difficult to disentangle their separate effects (see Section 3.3). The following sections discuss these influences in more detail.

3.1 Explanation 1: Downturns in the 2000s were Less Severe

A plausible explanation for the higher share of average hours adjustment since the late 1990s is that the economic downturns in the 2000s were relatively short and shallow compared with the recessions in the 1980s and 1990s (Figure 4).[6] Firms are likely to prefer to adjust to weaker demand, at least in the first instance, by reducing employees’ hours rather than employee numbers because of the costs and other difficulties associated with firing employees and future rehiring. Had the downturns in the 2000s been more severe, firms may have needed to shed more labour eventually. This is consistent with analysis from the Organisation for Economic Co-operation and Development (OECD) (2010) – based on 68 recessions in 18 countries – which concluded that adjustments to average hours tend to make the largest contribution to the decline in labour input at the early stages of a downturn. As the downturn progresses, employers increasingly resort to reducing the number of employees. In each of the downturns shown in Figure 2, the cyclical decline in average hours worked accounted for around half of the adjustment during the first year of the downturn. But for the deeper recessions of the 1980s and 1990s, employment became the dominant source of adjustment as weak demand conditions persisted.[7]

Figure 4: Real GDP Growth
Year-ended
Figure 4: Real GDP Growth

Note: Downturns in total hours worked are shaded

Source: ABS

The lower severity of downturns in Australia in the 2000s may help explain why it was the only country shown in Figure 3 to experience a large increase in the contribution of average hours worked to the change in total hours. The volatility of Australian output – measured by the standard deviation of year-ended growth in real GDP – more than halved between the periods 1978–98 and 1999–2016. In contrast, the volatility of output in the other countries was broadly unchanged, because these countries experienced much deeper downturns in the 2000s.

One qualification to this argument is that economic theory suggests that the decision about whether to adjust via employment or hours is influenced by both current and expected demand conditions. Thus, if firms expect a substantial downturn in demand, they may be more likely to shed labour pre-emptively rather than adjust working hours of their staff. While the 2008–09 downturn in Australia turned out to be less severe than those in the 1980s and 1990s, at the time there were widespread expectations that demand conditions would deteriorate to a similar extent to those earlier recessions (e.g. RBA 2009). Notwithstanding these expectations, there are a number of possible reasons why firms did not engage in more adjustment through redundancies in this episode:

  • While future demand was expected to be very weak, current demand conditions at the time were not especially weak.
  • The labour market was very tight in the lead-up to the 2008–09 downturn, with the unemployment rate falling to around 4 per cent and a historically high proportion of firms reporting that it was difficult to find suitable labour (Figure 5; Plumb, Baker and Spence (2010)). Given this, when growth in demand slowed, firms may have been reluctant to part with their staff to avoid the costly process of rehiring once demand recovered.
  • There was heightened uncertainty surrounding economic conditions during the 2008–09 downturn compared with previous downturns (Figure 5; Moore (2016)). In these circumstances, theory suggests that firms will be less inclined to make investment decisions that are difficult or costly to reverse, including either hiring or firing workers.
  • Workers were very pessimistic about their future employment prospects during the 2008–09 downturn, with self-reported perceptions about future unemployment prospects rising to unprecedented levels (Figure 5). Therefore, employees may have been more reluctant to leave their jobs amid concerns about being able to find new ones, and more willing than usual to negotiate over working hours and other conditions in return for job security.

While these factors should, in theory, be related to average hours worked, the volatile and noisy nature of measures of average hours makes it difficult to find empirical evidence of such relationships. We were not able to find evidence of a relationship between average hours and the above factors in a regression model.

Figure 5: Determinants of Average Hours Worked
Standard deviations from average
Figure 5: Determinants of Average Hours Worked

Notes: Downturns in total hours worked are shaded
(a) ‘All industries’ is the share of firms indicating that the availability of suitable labour is a constraint on output; ‘Manufacturers’ is the net balance of firms finding it harder to get labour than three months ago
(b) Net balance of consumers expecting unemployment to be higher in the coming 12 months

Sources: ACCI-Westpac; Moore (2016); NAB; Westpac and Melbourne Institute

3.2 Explanation 2: Labour Market Reforms and Rising Hiring Costs

Another possible explanation for the larger contribution of average hours to labour market adjustment since the late 1990s is that the reforms to industrial relations arrangements in the late 1980s and early 1990s made it easier for firms to bargain directly with their employees over matters like wages and working hours. This may have provided firms with more scope to reduce working hours in an effort to lower labour costs while retaining employees. As noted by Borland (2011), the 2000s were the first time in which these reforms were ‘tested’ by an economic downturn.

In practice, measuring flexibility of the labour market and how it has changed over time is not straightforward. The cyclical adjustment in average hours was larger in the 2000s, which provides tentative evidence that the labour market reforms played a role; the peak-to-trough decline in average hours was 2¼ per cent in both downturns, compared with 1¾ per cent in the early 1980s and early 1990s recessions (Figure 2). However, these differences are fairly modest.

The cost of terminating employment and the cost of screening and training new employees can also affect the nature of labour market adjustment. If firing or hiring costs are high, firms may be more inclined to respond to weaker demand conditions by decreasing the hours worked by existing staff. The average employment termination payment in Australia was nearly $14,000 in 2012/13, or 25 per cent of an average annual salary.[8] Broader measures, such as the OECD's employment protection legislation (EPL) indices, suggest that firing costs in Australia are lower than in most European countries, although higher than in the United States where employment protection is relatively limited.[9] However, these indicators showed little change between the mid 1980s and late 2000s for Australia, so it is unlikely that changes in firing costs have been a significant driver of changes in the nature of labour market adjustment.

In terms of hiring costs, the cost of screening and training labour is likely to have risen over time, given the increase in the number of jobs requiring specialist skills and training (Faccini and Hackworth 2010). Hiring costs are particularly high during periods of labour market tightness, since firms face higher search costs to fill vacant jobs. This might suggest that higher hiring costs can explain part of the increase in the contribution of average hours adjustment over time. However, it cannot explain why average hours adjustments have become more important in Australia but not in other advanced economies, since these countries are also likely to have seen an increase in the cost of screening and training labour.

3.3 Empirical Evidence

The analysis in the previous sections suggests that the less severe nature of downturns in the 2000s, labour market reforms and increases in hiring costs may all help to explain the increased role of changes in average hours in Australian labour market adjustment since the 1990s. However, it is difficult to distinguish between these explanations using statistical techniques given the available data, as all imply that changes in average hours worked have been more sensitive to changes in the business cycle (relative to employment) since the late 1990s. Specifically:

  • If average hours adjust more during the initial stages of a downturn and only up to a point, then econometric models would tend to find that average hours worked are relatively more responsive to changes in GDP during less severe downturns (and relatively less responsive during severe downturns, in which more adjustment occurs through employment). Since the downturns in Australia were less severe after the late 1990s, this suggests that the relative sensitivity of average hours worked to a given change in GDP should have risen in recent decades.
  • Labour market reforms and rising hiring costs suggest that the sensitivity of average hours to a given change in GDP should have increased (or that the sensitivity of employment has decreased, or both). Given that many important labour market reforms had been completed by the late 1990s, the relative sensitivity of average hours worked should have increased after the late 1990s.

Nevertheless, it is useful to test whether at least one of these explanations contributed to the changes in labour market adjustment in Australia in recent decades. One way of exploring whether labour market variables have become more or less sensitive to the cycle is to estimate a vector autoregression (VAR) model, which captures the dynamic relationships between GDP, average hours worked and employment.[10] The response of labour market variables to a negative 1 per cent ‘shock’ to GDP is shown in Figure 6. The left- and right-hand panels show the impulse response functions (IRFs) estimated over the 1978–98 and 1998–2016 sub-samples, respectively, along with the +/− 2 standard error bands. Comparing the left- and right-hand panels reveals whether the relationship between GDP and each variable changed over time.

Figure 6: Response of Labour Input to a GDP Shock
By sub-period, response to a negative 1 per cent shock to GDP
Figure 6: Response of Labour Input to a GDP Shock

Note: Grey lines show +/− 2 standard error bands

Sources: ABS; Authors' calculations

In general, the volatile and noisy nature of measures of average hours worked makes it difficult to find empirical evidence of relationships between average hours worked and the other variables that should, in theory, be related to it. That said, the VAR model provides some tentative evidence that average hours became more sensitive to the cycle after 1998, although the difference between the IRFs in the two sub-periods is not statistically significant. The model also suggests that the responsiveness of employment declined after 1998, although again the difference between the sub-periods is not statistically significant. Thus, while it is difficult to draw any firm conclusions from this model, it seems likely that either the reduction in the severity of downturns or labour market reforms (or both) explains at least part of the greater contribution of average hours worked to labour market adjustment in recent decades.

One distinction is that the ‘severity of downturns’ explanation (at least as defined above) only relates to downturns, while the ‘labour market reforms’ explanation is relevant for both downturns and non-downturn periods. So, if the contribution of average hours adjustment has increased since the late 1990s even if we focus only on non-downturn periods, then one interpretation is that this supports the ‘labour market reforms’ explanation.

To examine this, we re-estimate the contributions of average hours and employment to the variation in total hours worked after excluding the downturn periods, and find that the results are almost identical to those shown in Table 1. While at first glance this suggests that labour market reforms have been an important factor, this type of analysis does not adequately control for the moderation in the economic cycle since the late 1990s. Figures 4 and A1 show that the economic cycle was more pronounced in the earlier sub-sample, even if we focus only on non-downturn periods. In particular, economic downturns were often preceded by a large cyclical upswing in the labour market. If firms respond to booms in a similar way to downturns – by adjusting hours in the initial stages, and then adjusting employment as the boom/recession persists – then simply excluding the downturn periods does not help us to isolate the separate contribution of ‘labour market reforms’. In other words, the ‘severity of downturns’ explanation could be framed more broadly in terms of the ‘severity of the economic cycle’ – both booms and busts.

3.4 Changes in the Composition of Employment

Average hours worked are affected not just by changes in the hours of workers in given jobs, but also by changes in the composition of employment between jobs involving long hours of work and jobs involving fewer hours. Falls in average hours worked could reflect changes in the industry composition of the economy during a recession. For example, if industries with longer working hours incur relatively more job losses during an economic downturn, this will contribute to a decline in overall average hours worked. Thus, another possible explanation for larger adjustments in average hours worked since the late 1990s is that compositional effects changed over time.

To estimate whether compositional changes have played a role, deviations in average hours worked can be decomposed into two effects (Figure 7; see Appendix B for details):

  • A ‘composition effect’, which is the change in average hours worked owing to shifts between different categories of employment, while holding hours unchanged within each category. Within-category hours are kept at their August 2008 levels, and the categories include age group, gender, industry and occupation of employment, marital status and part-time and full-time employment status.
  • A ‘within effect’, which captures changes in average hours worked within each category of employment; for example, a fall in average hours worked by employees within the manufacturing sector or a fall in average hours worked within part-time employment.
Figure 7: Composition and Average Hours Worked
Deviation in average monthly hours relative to August 2008
Figure 7: Composition and Average Hours Worked

Notes: Downturns in total hours worked are shaded

Source: ABS; Authors' calculations

The decline in average hours worked since the late 1970s is entirely due to longer-run changes in the composition of employment. In particular, part-time employment has grown rapidly relative to full-time employment. However, during downturns, the primary driver of shifts in average hours is changes in average hours worked within categories, rather than changes in the composition of employment.[11] The ‘within effect’ contributed more than two-thirds of the peak-to-trough decline in average hours worked in the 1980s and 1990s recessions and more than half in the 2000s downturns.

Closer examination of the decomposition in Figure 7 reveals that the estimated ‘composition effect’ during the 2008–09 downturn is driven almost entirely by the increase in the part-time share of employment, from 28.3 per cent in August 2008 to 30.1 per cent in August 2009. Less than 0.1 hours of the 3.3 hours decline in average monthly hours worked between 2008 and 2009 can be accounted for by other compositional changes. The other compositional forces were small and offsetting; shifts in the industrial and occupational structures, and the rise in the female share, all exerted downward pressure on overall average hours worked. These effects were partly offset by a sharp decline in the employment share of 15–19 year olds, who tend to work shorter hours than other age groups.[12]

The problem with attributing changes in the part-time share of employment during 2008–09 to the ‘composition effect’ is that it could also reflect a within-job shift to shorter hours, rather than more part-time jobs being created. That is, during a downturn, firms can temporarily downgrade full-time workers to part-time hours (i.e. labour hoarding). Indeed, during the 2008–09 downturn there was an increase in the share of part-time employees who reported that they ‘usually’ work full time, but were working part-time hours because they were ‘stood down’, placed on ‘short time’, or because of ‘insufficient work’. Such workers accounted for 10 per cent of the overall rise in the part-time share during the downturn. The next section addresses this concern, by analysing changes at the job level rather than at the category level.

With this in mind, although compositional effects were relatively more important in the 2000s – and therefore may account for some of the increased contribution of average hours adjustments – they do not appear to have been the main driver.

Footnotes

The downturn periods shaded in Figures 4–5, 7–9 and D1 are dated based on the peak-to-trough decline in (detrended) total hours worked. [6]

It is also possible that the downturns in the 2000s were less severe because more adjustment occurred through average hours. However, examining this hypothesis is beyond the scope of this paper. [7]

These calculations are based on the total value of employment termination payments (ETP) and income from salary or wages from the Australian Taxation Office (ATO 2015). The value of ETP measures the taxable component of payments related to resignation, dismissal, redundancy, retirement or death. [8]

The EPL index is available from the mid 1980s and covers a range of termination cost indicators, including dismissal costs, procedural inconveniences (i.e. ‘red tape’), notification requirements and the potential compensation if a dismissal is found to be unfair. [9]

The results in Figure 6 are from a VAR(3) model with three variables, ordered as follows: real GDP, average hours worked and employment. Following RBA (2014), this ordering assumes that GDP is the most exogenous variable in the system, with the ordering of the other variables reflecting the relative speed at which they are assumed to respond to a shock to GDP. In turn, GDP is assumed not to respond contemporaneously to any of the labour market variables, but may respond with a lag. All variables in the VAR are in logs and detrended with an HP filter (λ = 1,600). The results from VAR models can be sensitive to the variables included and the structure of the VAR, so the results shown here should be considered as illustrative only. [10]

The ‘within effect’ is not the same as the ‘cyclical’ average hours worked series derived earlier using the HP filter. The ‘within effect’ captures all changes in average hours that are not explained by compositional changes in employment. In contrast, the ‘cyclical’ change in average hours captures all deviations of average hours from trend, due to both cyclical ‘within effects’ and cyclical ‘composition effects’. Nonetheless, the two series are highly correlated, reflecting the limited contribution of compositional effects to cyclical movements in average hours. [11]

These estimates are based on an Oaxaca-Blinder decomposition of the change in average hours worked between August 2008 and August 2009 (using the individual LFS cross-sections at both points in time). Including the parttime dummy attenuates the effects of industry, occupation, gender and age composition, which suggests that the effect of these factors largely operates through their effect on the part-time share of employment. [12]