The Netherlands

Basic Sample Description

The sample constructed for the Netherlands includes 2213 men, each with between 4 and 8 observations, with the average being 6.6.18 _{Of these 2213 men, 1638 (74.0%) are first observed} in the private sector and remain in the sample for an average of 6.6 years. A further 519 individuals (23.5%) are initially observed in the public sector and are retained in the sample for 6.7 years on average. The remaining 56 men (2.5%) are first encountered in unemployment and remain in the sample for an average of 5.6 years.

With regard to education, the Netherlands sample breaks down overall as 24.8% “high”, 55.1% “medium” and 20.0%“low”. There are however, considerable differences between the sectors in terms of education composition: the private sector breaking down as 20.9% high, 57.2% medium and 21.9% low, whereas the corresponding public sector figures are respectively 41.5%, 45.2% and 13.3%. The public sector thus attracts substantially more better educated workers and fewer medium and low educated workers than the private sector. In terms of age and labour market experience, the public sector employees are on average more than three-and- a-half years older (43.4 years old versus 39.7) and have more (potential) experience (23.6 years compared to 20.7 years).

Figure 4.2 illustrates the evolution of the Netherlands labour market over time, the top panel plotting the male unemployment rate for the years 1990-2001 (thus encapsulating our sample time frame plus the preceding 4 years), while the lower panel shows the public sector share of total employment in our sample. The unemployment rate is steady at around 5-6% prior to the start of the sample period in 1994, but then falls gradually over the following years to be around

18

There is some sample attrition, 16.0% after 4 years and 53.3% at 8 years, which we assume exogenous. Some of the attrition is a result of our sample selection rules that censor individuals from the first gap in their response history (this affects 7.2% of the individuals in our sample.)

0 1 2 3 4 5 6 7 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 year

Netherlands: unemployment rate (LFS)

17.5 20 22.5 25 27.5 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 year

Netherlands: public share of total employment (sample)

Figure 4.2: Netherlands: Unemployment rate, males, 1991-2001, and Sample public sector share

3% in 2001. The public sector share of total employment remains largely stable in the sample, though falling steadily from 25% in 1994 to just under 22% in 2001.

Differences in Earnings

Earnings levels. Table 4.3 describes public-private differences in earnings levels through a num- ber of simple regressions, where again the dependent variable is the log of current gross monthly earnings. The hours distributions for full-time workers are similar for each sector, though median weekly hours is slightly less in the public sector (38 versus 40); therefore by looking at monthly earnings we will slightly under-estimate any positive public premium in hourly wages. As we might expect, the distribution of hours in the public sector is less spread than in the private sector, the standard deviation of weekly hours is smaller by approximately one hour and a half. The first column of Table 4.3 shows that the raw public pay gap in the Netherlands sample is 9.4 log points (9.8%) in favour of the public sector. However, selection effects are clearly im- portant as when we control for a quadratic in potential labour market experience and education band (column 2) the public pay premium is estimated to be −3.3 log points (−3.2%) and sig- nificant. Moreover, when we allow the effects of education and experience to differ between the

sectors (column 3) the public premium is estimated to be−9.7 log points (−9.3%) and remains significant. This is the public premium for “high” education workers, and the premium for “low” education workers is not significantly different, however, for “medium” band educated men the premium is estimated to be almost exactly zero. The public premium does not however vary with experience. Estimating the model including individual-level fixed effects19 and controls for a quadratic in potential labour market experience (column 4), the public premium is estimated to be−0.2 log points and is not statistically significant. Introducing interactions between the public sector dummy and education and the quadratic in experience results in a positive esti- mate of the public premium of 4.5 logs points (4.6%) though the estimate is imprecise (t=1.46) According to this latter (column 5) fixed effects specification, returns to experience are higher in the private sector for all levels of experience, and as such the small positive public premium is eroded with experience, the premium tracing a U-shape in experience with an estimated min- imum at 36 years. The public premium is negative for all levels of experience greater than 12 years.

Earnings dispersion. The standard deviation of log earnings in the public sector (0.298) is smaller than in the private sector (0.322) and the slightly greater compression of pay in the public sector is also reflected in the 90:10 percentile ratios of raw earnings which are 2.098 and 2.317 respectively. The corresponding ratios conditional on age and education are 1.800 (public) and 1.962 (private), further illustrating the greater degree of pay compression in the public sector.

Earnings mobility. The sections above illustrate that the public and private sectors differ in terms of the cross-sectional distribution of earnings. In addition, there are differences in terms of earnings mobility, as illustrated in the upper panel of Table 4.4 which shows the transition matrices between quintiles of the unconditional log earnings distribution from one year to the next for the public and private sectors respectively.20 These matrices show that there is greater persistence in earnings rank amongst those individuals continuously employed in the public sector than amongst those continuously employed in the private sector. Moreover, the lower panel of the Table, which shows the transitions for log earnings residual rank after conditioning

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The reported fixed effects results are estimated using the within estimator. First differenced estimates are similar for the Netherlands.

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on education and a quadratic in (potential) labour market experience, illustrate the same pattern of greater earnings persistence in the public sector.

Since the earnings distribution is slightly more compressed in the public sector than in the private sector, transitions between earnings quintiles in the private sector represent larger changes in earnings than similar transitions in the public sector, further underscoring the greater mobility of earnings in the private sector. In addition, we computed the 1-lag auto-covariance of normalised log earnings for each individual, having conditioned on education and a quadratic in (potential) labour market experience. For individuals employed in the private sector in consecutive periods the mean auto-covariance is 0.874 whereas for the public sector this figure is higher at 0.884, again illustrating the greater persistence in earnings in the public sector.

Differences in Job Mobility

The following transition matrix shows the changes in employment sector between one wave and the next, with rows referring to sector in year t-1, columns to sector in year t:

Private Public Unemp. Private 96.5 1.9 1.4 Public 7.8 90.8 1.3 Unemp. 40.3 6.8 52.7

Few individuals (1.9%) initially employed in the private sector move directly to employment in the public sector from one year to the next, and though movements in the opposite direction are more common, still only 7.8% of individuals employed in the public sector in year t-1 move into the private sector in yeart. The average annual transition rate into unemployment is slightly greater in the private sector, 1.4%, compared with 1.3% in the public sector. This similarity in unemployment risk is also reflected in the different probabilities of ever being observed in unemployment depending on the sector in which the individual is first observed. For men initially observed in the private sector, the probability of ever experiencing unemployment in the sample is 7.4%, which is only slightly above the corresponding probability for those first observed in the public sector, 6.6%. Just over half (52.7%) of the unemployed remain so in the following period, with 40.3% exiting to private sector employment, the other 6.8% gaining employment in the public sector. Of the 212 individuals (9.6% of the sample) who ever experience unemployment

during the sample, 20.8% report being unemployed for 3 or more consecutive periods during the time-span of the sample. These “long-term” unemployed have only an 8.5% probability of finding a job in the next period, whereas for the “short-term” unemployed the probability is 84.5%. Thus though aggregate unemployment persistence is not that high, with just under half of the unemployed in any year finding employment by the next interview, the persistence appears to be highly concentrated on the “long-term” unemployed.

There is evidence of attachment to the public sector in the different rates of entry to public sector employment from unemployment, depending on whether the unemployed individual’s last employment was in the public sector. Of the unemployed whose most recent employment was in the public sector, 19.5% re-entered public sector employment by the time of the next interview. For those unemployed whose most recent employment was in the private sector, the public sector entry probability is just 4.2%.21