Ž The hypothesis is that being a UB-receiver and belonging to the 1991 post rule
. change sample adds negatively to the exit hazard.
As an indicator of labour demand, we use the monthly local unemployment rate. Where the 4-week periods that the durations are split into do not fall within a
single month, we use a weighted mean of two succeeding months. Although the national unemployment rate showed an increasing trend in the observation period,
there is considerable variation in this variable.
4. Results and discussion
We estimated the model separately for each sample, allowing the baseline hazard to vary between UB receivers and non-receivers. Both specifications, Eqs.
Ž .
Ž .
20
2.2 and 2.6 , were estimated. For the specification without gamma hetero-
geneity, we also estimated the model on the pooled sample to test if g s g
t,1990 t,1991
for UB receivers and non-receivers, respectively.
21
Ž .
Before turning to the results from estimating Eq. 2.6 , a look at some
nonparametric estimates also is instructive. Figs. 1–3 plot Kaplan–Meier hazard rates for the same three spell definitions as in Table 1. In the first sample, there is
Ž .
a marked jump upwards in the hazard out of the unemployment register Fig. 1 at about 20 four-week periods, when benefits cease — suggesting that for some
‘‘survivors’’, benefit entitlement may be an important motivation for reporting.
22
Ž .
For the hazards into the employment register Fig. 2 , no such effect is detectable from the nonparametric estimates alone. Fig. 3 suggests an increasing hazard after
72 weeks for the 1990 sample. The right-hand side panel of Fig. 1 shows that also in the 1991 sample, there is an increase in the hazard around 80 weeks, even if it
is not as marked as in the 1990 group. One possible explanation is that lack of information about the change in benefit rules kept some unemployed individuals
from reporting after having finished the 80 weeks. Finally, it is important to note that the hazard out of the unemployment register is about four times the hazard
into recorded employment, suggesting that the unemployment register alone is a poor indicator of unemployment duration.
The estimation results favour the gamma heterogeneity specification, neverthe- less we report results from both specifications.
23
To improve readability, the
20
Ž .
The program for estimating the model with gamma heterogeneity is written by Jenkins 1997 .
21
The specification with heterogeneity did not converge, probably due to the number of parameters necessary to estimate the unrestricted model — four baselines and a full set of sample interaction
dummies on the covariates.
22
Stratification by the UB receiverrnon-receiver dichotomy — not shown here — affirms that the jump in the hazard is caused by UB receivers.
23
Likelihood ratio tests of H : s
2
s 0 yield x
2
test statistics of 21.92 and 15.38, respectively Ž
. critical values10.83 at the 0.1 level .
Fig. 1.
Out of
unemployment register.
Fig. 2.
Into employment
register.
Fig. 3.
Into employment
— combined
registers.
Ž .
estimates of g are reported separately in Table 3a estimated by sample and 3b
t
Ž .
pooled estimation . The estimates of b can be found in Table 4. We can use Table 3a and 3b to evaluate two hypotheses. First, comparing receivers and
non-receivers of UB, we predict higher hazard rates for the latter group. Second, if a fixed benefits period increases the hazard to employment, we predict higher
Ž hazard rates for the UB receivers in the 1990 sample when there was a fixed
. period than in the 1991 sample. For the non-receivers there should be no such
decrease. This is our natural experiment. Ž
Inspection of the g -estimates without heterogeneity for the 1990 sample in
t
. Table 3a suggests a tendency towards negative duration dependence for both UB
Ž receivers and non-receivers. As one would expect, in the first three periods i.e.,
. three months the latter group’s risk of leaving unemployment is higher than for
those receiving UB, but from then on there are basically no differences in the estimated baselines. As for the effect from receiving benefits around the time of
Ž .
exhaustion period 20 , there are, surprisingly, no signs of increase in exit rates. There is, however, a slight increase in the periods after period 20. The estimates
with heterogeneity show flatter rates, consistent with the general result that unobserved heterogeneity implies downward biased duration dependence. Here,
Ž .
too, the rate does not increase in period 20 in fact, it decreases , but it then increases slightly in the next 4 periods.
24
Turning to the 1991 sample, there seem to be only small changes in the risk of leaving unemployment for the group of non-receivers. For UB-receivers, on the
other hand, there is a distinct decrease in exit rates. Again, the differences between the two groups appear to be significant in the early periods. When approaching
benefit exhaustion, the differences by and large become insignificant. This goes for both specifications. Note, however, that this time the lack of significance is not
counter-intuitive. With the new rules there is no reason to expect any peak in the baseline hazard for benefit receivers.
25
Table 3b shows estimates of the baseline parameters obtained from pooled Ž
. estimation
without heterogeneity of the samples, making statistical tests of
sample differences possible. It confirms the impressions from the findings reported in Table 3a. First, it indicates no statistically significant change in the behaviour of
unemployed without benefit entitlement. For those who were affected by the 1992 reform, namely the benefit receivers, the improved insurance for long term
24
We do not present formal tests of whether the increases after period 20 are statistically significant, but inspection of confidence intervals indicate that they are not. In the specification without heterogene-
w x
ity, the 95 confidence interval for g is y5.885, y4.877 for UB receivers, in the heterogeneity
20
w x
specification it is y5.674, y4.479 . The g ’s for the following periods fall within these intervals.
t 25
On the other hand, it is hard to find an intuitive reason that a difference which is there in the early periods should disappear in the later. The reason may be purely statistical and due to increased noise
because of the inherent decrease in the number of individuals at risk in the later periods.
unemployment appears to have lowered the probability of exiting the unemploy- ment state.
26
It is surprising, however, that the decrease is statistically significant only at the early stages of the unemployment spell. When it comes to the time
when benefits expire, the conclusion from this part of the analysis is that it cannot be verified that the behaviour has changed because of the 1992 policy change.
27
For visualisation, we refer the reader to the figures below. For the specification with gamma heterogeneity, Fig. 4 and 4b plot the estimated baseline hazards for
UB receivers and non-receivers for the 1990 and 1991 sample, respectively. Fig. 5 compares UB receivers in 1990 and 1991, while Fig. 5b does the same for
non-receivers.
Turning to the rest of the covariates, the effects are very much as one would expect. Previous income, which can be interpreted as an indicator of the opportu-
nity cost of rejecting a job offer, has a significant and positive effect on the
28
Ž .
hazard. Having had a job the previous year Experience2 increases the hazard,
Ž .
as does the number of years with income above a minimum level Experience1 . Education has a positive and significant effect, almost identical in both samples.
Ž .
Those younger than the reference age group 36–45 years have a larger probabil- ity of getting a job, whereas the hazard is lower for people belonging to the older
age groups. Having a non-Scandinavian citizenship also decreases the hazard. The local unemployment rate is a rough indicator of local labour demand, and should
have a negative effect, which it has. Relatively to the base category, eastern Norway including Oslo, residing in other regions has a positive and significant
effect in the 1991 sample that cannot be found in the other group.
26
Ž The expected duration of the mean individual calculated as the integrated survivor function in the
. specification with heterogeneity with UB increased from 605 to 776 days. For non-receivers, it
decreased from 512 to 306 days. Because of censoring, these estimates by far exceed the observed Ž
. mean durations. This, however, also seems to be the case in similar work, cf. e.g., Carling et al. 1996
Ž .
and Hernæs and Strøm 1996 .
27
We have also estimated UB receivers and non-receivers separately, but pooled across samples Ž
. with separate baselines for the 1990 and 1991 samples . The heterogeneity-corrected estimates in
general show a slight increase in the baseline hazards over the observation period. The reforms all over negative effect on the employment hazard remains unaltered, with a significant drop in employment
risk for receivers from 1990 to 1991. The number of periods where the difference is significant also increases from 12 to 18. Among the non-receivers, there are only two periods where the difference
between 1990 and 1991 are significant at the 5 level. The results are available from the authors upon request.
28
Benefit entitlements are based on income above a minimum level. Since about one-third of the individuals in both samples do not receive benefits, the income is low for quite a large number of the
individuals, and even zero for about 10 of them. Ideally, expected income is the relevant measure of the cost of rejecting a job offer. For example, young people entering the labour market after having
finished their education typically will be registered with low or zero income. Their expected income, on the other hand, and, hence, their search intensity, might still be high. Nevertheless, our estimate of
the effect from income is positive and highly significant, which we take as a support for the use of observed income as an opportunity cost proxy.
E. Bratberg,
K. Vaage
r Labour
Economics 7
2000 153
– 180
170
Table 3 Ž .
a
a Maximum likelihood estimates of g for UB-receivers and non-receivers
t
Ž .
With P-values for equal parameters receivers and non-receivers Wald tests . Period
1990 1991
Without gamma With gamma
Without gamma With gamma
heterogeneity heterogeneity
heterogeneity heterogeneity
UB Non-UB
P UB
Non-UB P
UB Non-UB
P UB
Non-UB P
1 y5.650
y4.440 0.000
y6.147 y4.874
0.000 y6.154
y4.922 0.000
y6.610 y5.320
0.000 2
y4.717 y3.753
0.000 y5.171
y4.077 0.000
y5.313 y4.012
0.000 y5.743
y4.330 0.000
3 y4.551
y4.177 0.000
y4.938 y4.385
0.000 y5.216
y4.325 0.000
y5.609 y4.550
0.000 4
y4.743 y4.538
0.116 y5.066
y4.676 0.006
y5.296 y4.352
0.000 y5.654
y4.505 0.000
5 y4.778
y4.801 0.887
y5.045 y4.890
0.366 y5.398
y4.814 0.000
y5.723 y4.913
0.000 6
y4.712 y4.826
0.521 y4.923
y4.877 0.804
y5.182 y4.762
0.006 y5.472
y4.819 0.000
7 y4.810
y5.050 0.255
y4.968 y5.070
0.640 y5.210
y4.810 0.016
y5.464 y4.825
0.000 8
y4.728 y5.051
0.145 y4.836
y5.044 0.361
y5.243 y4.907
0.066 y5.464
y4.882 0.004
9 y4.924
y5.099 0.475
y4.986 y5.067
0.744 y5.383
y4.597 0.000
y5.573 y4.532
0.000 10
y4.911 y4.897
0.953 y4.932
y4.835 0.691
y5.264 y4.635
0.001 y5.425
y4.528 0.000
11 y4.730
y4.885 0.528
y4.705 y4.793
0.728 y5.341
y5.040 0.194
y5.473 y4.898
0.020 12
y4.778 y4.724
0.823 y4.705
y4.598 0.668
y5.529 y5.070
0.062 y5.636
y4.896 0.005
13 y5.428
y4.830 0.036
y5.320 y4.673
0.026 y5.563
y4.975 0.018
y5.649 y4.771
0.001 14
y5.172 y5.223
0.883 y5.036
y5.044 0.982
y5.528 y5.153
0.190 y5.591
y4.922 0.027
15 y4.983
y5.114 0.702
y4.815 y4.912
0.780 y5.330
y4.933 0.139
y5.368 y4.673
0.015 16
y5.234 y5.543
0.479 y5.034
y5.324 0.513
y5.587 y4.845
0.008 y5.602
y4.555 0.000
17 y5.213
y5.187 0.947
y4.986 y4.949
0.926 y5.682
y5.309 0.285
y5.678 y4.993
0.060 18
y5.184 y5.593
0.390 y4.928
y5.336 0.396
y5.436 y5.336
0.782 y5.411
y5.004 0.277
19 y5.346
y5.748 0.451
y5.065 y5.478
0.441 y5.179
y5.081 0.762
y5.127 y4.724
0.240 20
y5.381 y5.275
0.814 y5.077
y4.988 0.846
y5.478 y4.864
0.051 y5.400
y4.478 0.006
21 y5.246
y5.416 0.726
y4.917 y5.111
0.693 y4.911
y4.940 0.928
y4.803 y4.523
0.413 22
y5.280 y4.894
0.341 y4.927
y4.566 0.381
y5.018 y5.316
0.455 y4.874
y4.874 0.999
23 y5.181
y4.824 0.379
y4.803 y4.464
0.411 y5.241
y4.998 0.507
y5.068 y4.531
0.161 24
y5.164 y5.452
0.594 y4.761
y5.072 0.570
y5.062 y4.814
0.478 y4.859
y4.315 0.137
25 y5.896
y5.418 0.413
y5.476 y5.025
0.445 y5.550
y5.458 0.850
y5.321 y4.932
0.436 26
y5.620 y5.335
0.618 y5.184
y4.921 0.649
y5.450 y5.186
0.557 y5.202
y4.638 0.225
27 y5.374
y5.244 0.818
y4.920 y4.812
0.850 y5.387
y5.569 0.732
y5.117 y5.002
0.834 Pooled test all periods
0.000 0.000
0.000 0.000
Ž
2
. Ž
2
. Ž
2
. Ž
2
. x
s 266.92 x
s 252.3 x
s 502.52 x
s 368.9
27 27
27 27
E. Bratberg,
K. Vaage
r Labour
Economics 7
2000 153
– 180
171
Ž .
a
Ž .
b Maximum likelihood estimates of g from pooled estimation of 1990 and 1991 samples without heterogeneity
t
Ž .
With P-values for equal parameters receivers and non-receivers Wald tests UB
Non-UB 1990
1991 1990
1991 Coefficient
SE Coefficient
SE P
Coefficient SE
Coefficient SE
P 1
y5.650 0.194
y6.154 0.195
0.067 y4.440
0.182 y4.922
0.185 0.064
2 y4.717
0.180 y5.313
0.182 0.018
y3.754 0.176
y4.012 0.175
0.297 3
y4.550 0.179
y5.216 0.181
0.009 y4.177
0.181 y4.325
0.179 0.562
4 y4.742
0.182 y5.296
0.183 0.032
y4.540 0.199
y4.352 0.186
0.492 5
y4.777 0.184
y5.398 0.186
0.018 y4.802
0.220 y4.814
0.207 0.969
6 y4.711
0.185 y5.182
0.185 0.072
y4.828 0.231
y4.762 0.213
0.833 7
y4.809 0.189
y5.210 0.187
0.132 y5.052
0.254 y4.810
0.220 0.473
8 y4.727
0.189 y5.243
0.189 0.054
y5.054 0.263
y4.907 0.232
0.676 9
y4.923 0.196
y5.383 0.194
0.095 y5.101
0.279 y4.597
0.222 0.157
10 y4.910
0.198 y5.264
0.193 0.200
y4.900 0.271
y4.635 0.230
0.455 11
y4.729 0.196
y5.341 0.196
0.027 y4.888
0.279 y5.040
0.266 0.693
12 y4.778
0.199 y5.529
0.203 0.008
y4.725 0.275
y5.070 0.274
0.374 13
y5.428 0.226
y5.563 0.206
0.658 y4.832
0.294 y4.975
0.273 0.721
14 y5.172
0.218 y5.528
0.208 0.238
y5.225 0.357
y5.153 0.306
0.879 15
y4.982 0.214
y5.330 0.204
0.240 y5.116
0.357 y4.933
0.293 0.692
16 y5.234
0.230 y5.587
0.216 0.263
y5.545 0.441
y4.845 0.292
0.185 17
y5.212 0.232
y5.682 0.223
0.144 y5.189
0.390 y5.309
0.356 0.821
18 y5.183
0.235 y5.436
0.215 0.427
y5.596 0.477
y5.336 0.371
0.668 19
y5.346 0.250
y5.179 0.209
0.610 y5.750
0.527 y5.081
0.343 0.287
20 y5.380
0.257 y5.478
0.225 0.774
y5.277 0.441
y4.864 0.322
0.449 21
y5.245 0.252
y4.911 0.205
0.304 y5.418
0.477 y4.940
0.343 0.416
22 y5.279
0.260 y5.018
0.213 0.436
y4.897 0.391
y5.316 0.412
0.460 23
y5.180 0.260
y5.241 0.227
0.860 y4.827
0.391 y4.998
0.371 0.751
24 y5.163
0.266 y5.062
0.222 0.770
y5.455 0.527
y4.814 0.356
0.314 25
y5.895 0.346
y5.550 0.254
0.421 y5.421
0.527 y5.458
0.476 0.958
26 y5.619
0.325 y5.450
0.253 0.682
y5.338 0.527
y5.186 0.440
0.824 27
y5.373 0.309
y5.387 0.251
0.972 y5.248
0.527 y5.569
0.526 0.666
Pooled test 0.000
0.030
2 2
Ž .
Ž .
x s 75.5
x s 42.4
27 27
a
Log of the integrated periodic specific hazard.
E. Bratberg,
K. Vaage
r Labour
Economics 7
2000 153
– 180
172
Table 4 Maximum likelihood estimates of covariate effects
With asymptotic standard errors and P-values. 1990
1991 Without heterogeneity
With heterogeneity Without heterogeneity
With heterogeneity Coefficient
SE P
Coefficient SE
P Coefficient
SE P
Coefficient SE
P Income
1.49E-06 3.22E-07
0.000 2.37E-06
4.68E-07 0.000
7.03E-07 3.04E-07
0.021 1.04E-06
3.91E-07 0.008
Female 0.227
0.044 0.000
0.310 0.059
0.000 y0.089
0.042 0.035
y0.106 0.052
0.043 Spouse inc.
y1.08E-06 6.97E-07
0.120 y1.57E-06
9.52E-07 0.099
y5.85E-07 5.75E-07
0.309 y8.49E-07
7.51E-07 0.258
Spouse inc.=Female 6.42E-07
7.90E-07 0.416
1.16E-06 1.08E-06
0.286 1.94E-06
6.80E-07 0.004
2.37E-06 8.76E-07
0.007 Childr -11
0.062 0.048
0.199 0.047
0.064 0.462
y0.018 0.044
0.682 y0.034
0.057 0.553
Ch 11,-18 y0.050
0.064 0.441
y0.054 0.085
0.528 0.171
0.051 0.001
0.214 0.068
0.002 Childr -11=Female
y0.234 0.060
0.000 y0.267
0.078 0.001
y0.176 0.058
0.002 y0.210
0.072 0.004
Ch 11,-18=Female 0.308
0.078 0.000
0.385 0.105
0.000 y0.036
0.073 0.621
y0.072 0.092
0.433 Education
0.092 0.010
0.000 0.117
0.014 0.000
0.093 0.009
0.000 0.116
0.013 0.000
Exper. 1 0.027
0.005 0.000
0.036 0.007
0.000 0.028
0.005 0.000
0.036 0.007
0.000 Exper. 2
0.381 0.037
0.000 0.474
0.050 0.000
0.247 0.034
0.000 0.302
0.044 0.000
Age 17–20 0.382
0.102 0.000
0.508 0.133
0.000 0.661
0.101 0.000
0.786 0.128
0.000 Age 21–25
0.557 0.087
0.000 0.716
0.118 0.000
0.691 0.086
0.000 0.830
0.112 0.000
E. Bratberg,
K. Vaage
r Labour
Economics 7
2000 153
– 180
173 Age 26–35
0.192 0.067
0.004 0.255
0.089 0.004
0.420 0.067
0.000 0.505
0.086 0.000
Age 46–55 y0.138
0.079 0.080
y0.178 0.102
0.081 y0.077
0.073 0.289
y0.110 0.091
0.223 Age 56–62
y0.192 0.118
0.104 y0.207
0.153 0.177
y0.710 0.127
0.000 y0.858
0.156 0.000
Age 63–67 y1.664
0.268 0.000
y2.043 0.317
0.000 y1.951
0.323 0.000
y2.294 0.359
0.000 Married
0.178 0.099
0.072 0.252
0.134 0.059
0.149 0.090
0.096 0.196
0.116 0.092
Prev. marr. y0.207
0.070 0.003
y0.276 0.090
0.002 y0.136
0.064 0.033
y0.171 0.079
0.031 Married=Female
y0.053 0.129
0.678 y0.138
0.173 0.424
y0.520 0.127
0.000 y0.605
0.159 0.000
Region 2 y0.011
0.049 0.829
y0.065 0.064
0.309 0.116
0.045 0.009
0.135 0.055
0.015 Region 3
0.046 0.044
0.298 0.030
0.057 0.596
0.152 0.042
0.000 0.179
0.052 0.001
Region 4 y0.017
0.054 0.753
y0.073 0.070
0.296 0.140
0.050 0.005
0.163 0.062
0.008 Unemp.rate
y0.039 0.009
0.000 y0.044
0.011 0.000
y0.023 0.008
0.006 y0.030
0.010 0.003
Non-Scand y0.341
0.138 0.013
y0.427 0.173
0.013 y0.260
0.139 0.061
y0.331 0.168
0.048
2
s 1.049
0.254 0.000
0.910 0.267
0.001 Log likelihood
y14 748.05 y14 737.09
y17 515.20 y17 507.51
N 9936
12 054
Fig. 4.
Gender and some family relevant factors have effects that vary across the samples somewhat surprisingly. The effect of being female is significantly positive
Ž .
in the 1990 sample, and negative but smaller in the 1991 sample. Spouse income Ž
. is negative but not significant in both groups, but the gender interaction term is
significantly positive only in the 1991 sample. The latter result may suggest that the partner’s income is positively correlated with the employment hazard for
women, but negatively for men. The interaction terms between being female and the number of children below 11 years are negative and significant for both
samples, which may suggest a greater tendency toward labour market withdrawal for women with little children. On the other hand, the negative interaction between
marriage and gender is significant only for the 1991 sample. It is hard to draw conclusions from this sample difference, but it may reflect hardening labour
market conditions for women: it has become generally harder to get a job
Fig. 5.
Ž .
negative coefficient on female , and married women to a larger extent retreat to Ž
. non-market activities negative coefficient on the marriage interaction term .
The fact that we could not verify any significant rise in the employment hazard before benefit expiration in the 1990 sample, makes it less of a surprise that we
did not find that the 1992 reform changed behaviour around benefit expiration. There are several potential explanations. Even before the policy change, benefit
duration was rather long, 80 weeks compared to, e.g., 60 weeks in Sweden. Combined with the opportunities to relief jobs and other labour market pro-
grammes, the potential effect of benefits cease may have been weakened. Also, means tested social benefits are available, although there is considerable local
variation. We have already noted that the modest difference between the samples
in the out-of-unemployment-register Kaplan–Meier hazard at 80 weeks may show that information about the policy change is less than perfect among the receivers.
Furthermore, if there are some unobserved factors characterising people who have a hard time finding a job, these could dominate the potential incentive effects —
after 80 weeks, there might be a majority of ‘‘hard’’ cases. The same goes for ‘‘true’’ duration dependence — if the employment probability deteriorates over
time due to, e.g., loss of human capital, that effect may wash out the incentive effect under study here.
Besides the explanations offered above, there is a fundamental problem with the kind of data that are available. Ideally, one would wish to have data on persons
who differ considerably with respect to UB receipts, but are comparable on other dimensions. As UB is related to individual earnings histories, typically this will
not be the case. The uniformity of the Norwegian unemployment insurance system, which makes the potential benefit duration identical across individuals,
and also prevents people from opting out of the insurance system, strengthens this general problem. Our data suffer from lack of the variation in benefit rules that can
Ž .
be found, for instance, in those of Katz and Meyer 1990 . Reminding the reader of the introductory discussion in Section 1, our findings
are not completely at odds with existing empirical research. Narendranathan and Ž
. Stewart
1993a report that in the UK, the effect of unemployment income
Ž .
declines with the length of the spell. Fallick 1991 draws similar conclusions from Ž
. US data. Carling et al. 1996 do find positive exhaustion effects on the hazards
into employment and labour market programmes. However, only the effects on exits to labour market programmes are significant at the 5 level. The data and
specification employed by the different authors may not be directly comparable with the present analysis,
29
but they express a common tendency — the potential exhaustion effects of a fixed benefit period may be hard to detect. This does not
imply that such effects are non-existing. They have, however, turned out to be hard to identify in several investigations. It may be tempting to conclude that the
lack of the incentive effects in the present study is due to disincentives caused by the extensive use of labour market programmes. We think that some caution is
called for here. Maybe the effect of a decline in the reservation wage becomes
Ž .
dominated by a reduced job offer probability long before 80 weeks of unemploy- ment duration. If so, it would not be enough to reverse the liberalisation of 1991
and 1992 to observe the incentive effect. It would also be necessary to reduce the 80 weeks period of benefits entitlement. Comparing with the Swedish study in
29
Ž .
Ž .
Fallick 1991 and Narendranathan and Stewart 1993a; b let the hazard vary with benefits over the course of the spell, the first author uses a flexible baseline, whereas the others use a time-varying
Ž .
coefficient on actual benefit income. Carling et al. 1996 use data and specification similar to the present, except that they estimate competing risks to work and labour market programmes.
Ž .
Carling et al. 1996 one cannot be quite certain that even reducing the period to 60 weeks would give clear effects.
In addition to the exhaustion effects, the prospect of benefit cuts should lead to increased search efforts in the entire unemployment period of the first sample
compared to the second one. This form of disincentive effect from the abolition of fixed benefit durations appears to be present in our material. For nearly the whole
first year of the search period the hazard to employment for UB receivers is significantly lower for the 1991 compared to the 1990 sample, while there is no
such effect for non-receivers. In conclusion, therefore, the incentive effect of a fixed benefits period is not rejected by this analysis.
5. Concluding remarks
