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5  Results

Parameters of the preference functions are estimated using imputed wage values for non-workers as described in Section 2.2. The next subsection presents the results of the labour supply models for both couples and single adult units. In the second subsection, the estimated results are used to predict labour supply probabilities so that predicted and actual results can be compared.

5.1  Discussion of the Estimated Parameters

To show how the results of a model as discussed in section 4 are interpreted, we first discuss the parameters of two-adult income units. Table 2 gives the parameter estimates of the quadratic specification of the utility function for a model with six discrete labour supply points for men and eleven points for women. The location of the points is defined in a footnote to the table.

The linear terms

The effects of different characteristics on the preference for leisure of both adults in the household are the first results to be discussed. We only discuss those parameters that are significant at the 5-percent level.

To begin with the parameterised preference for work for the male adult, a significant positive effect[17] is found for the linear term of age. This means that older men have a higher preference for work and thus a lower preference for leisure. However, on the other hand the quadratic term for age seems to have a significant negative effect on the preference for work, which combined with the linear effect of age means that the preference for work increases for men up to around 36 years of age after which it decreases with age. Thus young men and older men have a lower preference for labour supply. A positive effect is further observed for households where the man has a higher level of education. The partner’s education tends to increase male labour supply as well, with the exception of partners with a postgraduate degree, the presence of which decreases the preference for work. There also seems to be an increase in the preference for work over time even after controlling for unemployment levels. It may be partly due to the change in the age of eligibility for the New Zealand Superannuation. This effect may not have been completely captured by the approximating variable constructed by us. None of the variables related to the number and age of dependent children in the household influence the preference for work.

The current unemployment rate amongst men has a negative effect on the preference for work. This is probably mostly due to involuntary unemployment but it could also be partly due to a discouraged worker effect, as may for example be reflected in early retirement decisions. Being older than 60 years of age has a negative effect in addition to the negative age squared term. More interestingly however, those who are eligible for the New Zealand Superannuation clearly have a lower preference for work than others even after controlling for being over 60.[18] The policy change has had a substantial effect. There even seems to be some effect from the partner’s eligibility as well, which is however only significant at the 10-percent level.

Table 2 – Estimated Parameters of the Utility Function for Couples a
  Estimated coefficient z-valueb
Quadratic terms    
income × 100,000 -0.0177 -4.13
Labour supply husband × 100 -0.4990 -17.06
Labour supply wife × 100 -0.1339 -16.48
Crossproduct    
Inc. & lab. Sup. Husband × 10,000 -0.3826 -12.59
Inc. & lab. Sup. Wife × 10,000 -0.1930 -9.76
labour supply Husband & wife × 100 -0.0728 -11.52
Linear terms    
Income × 100    
constant 0.5215 20.13
Number of children -0.0030 -1.20
Labour supply husband    
constant 0.2945 12.23
Youngest child <1 yr old 0.0039 1.31
Youngest child 1-3 yrs old 0.0036 1.49
Youngest child 4-5 yrs old 0.0005 0.16
Youngest child 6-9 yrs old 0.0033 1.23
Number of children -0.0012 -1.09
Age/10 0.0487 8.94
Age squared/100 -0.0067 -9.79
Vocational education 0.0165 9.87
Certificate 0.0125 5.93
Bursary/scholarship 0.0135 4.96
Postgraduate degree/other 0.0127 2.41
Bachelor degree 0.0180 5.96
Postgraduate 0.0213 4.50
Vocational education (partner) 0.0020 1.07
Certificate (partner) 0.0076 4.31
Bursary/scholarship (partner) 0.0108 4.40
Postgraduate degree/other (partner) 0.0020 0.39
Bachelor degree (partner) 0.0017 0.52
Postgraduate (partner) -0.0146 -2.68
Time trend 0.0009 2.12
Quarterly male unemployment rate -0.0016 -2.89
Aged 60 or over -0.0078 -2.01
Eligible for New Zealand Superannuation -0.0236 -5.13
Partner is eligible for New Zealand Superannuation -0.0096 -1.79
Labour supply wife    
constant 0.0465 3.33
Youngest child <1 yr old -0.0637 -11.62
Youngest child 1-3 yrs old -0.0672 -18.67
Youngest child 4-5 yrs old -0.0584 -12.90
Youngest child 6-9 yrs old -0.0383 -11.56
Number of children -0.0058 -6.54
Age/10 0.0385 7.07
Age squared/100 -0.0064 -9.22
Vocational education 0.0201 10.17
Certificate 0.0133 7.12
Table 2 – Continued a
  Estimated coefficient z-valueb
Labour supply wife    
Bursary/scholarship 0.0164 7.22
Postgraduate degree/other 0.0277 5.72
Bachelor degree 0.0298 9.69
Postgraduate 0.0410 7.81
Vocational education (partner) -0.0081 -4.58
Certificate (partner) -0.0039 -1.77
Bursary/scholarship (partner) -0.0042 -1.58
Postgraduate degree/other (partner) -0.0123 -2.42
Bachelor degree (partner) -0.0189 -7.07
Postgraduate (partner) -0.0226 -5.76
Time trend 0.0006 1.41
Quarterly female unemployment rate -0.0009 -1.20
Aged 60 or over -0.0034 -0.54
Eligible for New Zealand Superannuation -0.0268 -2.58
Partner is eligible for New Zealand Superannuation -0.0017 -0.45
Fixed cost husband/100 18.7221 14.50
Fixed cost wife/100    
Constant 8.0863 18.81
Youngest child <1 yr old 1.3763 3.20
Youngest child 1-3 yrs old -0.7997 -2.97
Youngest child 4-5 yrs old -1.7622 -4.92
Youngest child 6-9 yrs old -1.8085 -6.02
Live in Wellington/Auckland 0.0962 0.78
Unobserved heterogeneity    
Variance in income parameter 0.0000 0.33
Variance in husband’s labour supply 0.0000 0.00
Variance in wife’s labour supply 0.0000 0.00
Variance in wife’s fixed cost 0.0030 0.46
Log likelihood -30565  

a Six discrete points of labour supply are distinguished for each man: 0 hours for non-participants and people working less than 2.5 hours, 10 hours for people working from 2.5 to 15 hours, 20 hours for people working from 15 to 25 hours, 30 hours for people working from 25 to 35 hours, 40 hours for people working from 35 to 45 hours, and 50 hours for people working more than 45 hours. Eleven discrete points of labour supply are distinguished for each woman: 0 hours for non-participants and people working less than 2.5 hours, 5 hours for people working from 2.5 to 7.5 hours, 10 hours for people working from 7.5 to 12.5 hours, 15 hours for people working from 12.5 to 17.5 hours, 20 hours for people working from 17.5 to 22.5 hours, 25 hours for people working from 22.5 to 27.5 hours, 30 hours for people working from 27.5 to 32.5 hours, 35 hours for people working from 32.5 to 37.5 hours, 40 hours for people working from 37.5 to 42.5 hours, 45 hours for people working from 42.5 to 47.5 hours, and 50 hours for people working more than 47.5 hours.

b The z-value indicates the level of significance of the estimated coefficients. A value of 1.96 or more means that the parameter is significantly different from zero at the 5% level at least. The higher the z-value the more precise the estimated coefficient.

According to expectation, the preference for work of the female adult seems to be lower than that of her male partner, at least as far as this is reflected in the size of the constant term of β2. A significant positive effect is observed for women with higher education levels. The effect of education seems more important for women than for men. This could be caused by the fact that almost all men are working or looking for work, whereas women’s labour supply is more variable. Additionally, if the partner’s education level is higher, then a woman’s preference for work is reduced to some extent. However, the effects are smaller than those resulting from her own education. From the linear and quadratic age parameters it can be derived that the maximum preference for work is around 30 years of age.

All variables relating to children have a significant negative effect on a married woman’s preference for work. The effect for children between six and nine years old is much smaller than for younger children. As expected, and as is seen in many other studies (Australian examples are Eyland, Mason and Lapsley, 1982; Ross, 1986; Murray, 1996; and Kalb, 2002), having a pre-school child under four years of age has a large negative effect on the female preference for work. Children of primary school age affect the mother’s preference for work to a smaller extent. Finally, women with more children have a lower preference for work.

Similar to the effect for men, the eligibility for the New Zealand Superannuation clearly affects women’s preferences for work as well. The partner’s eligibility seems irrelevant for women.

To keep the model manageable the preference for income only depends on the number of children, which was significant for Australian data (Kalb, 2002). Similar to the Australian case a lower preference for income is estimated with an increase in household size, but the effect is not significant.[19]

The results for single men, single women and sole parents are presented in Table 3 and are discussed more briefly.Comparing the effects found for couples with those for singles and sole parents, similar variables are found to be important. High education levels increase the preference for work for all groups. The effect on the preference for income is less clear; higher education levels increase the preference for some whilst decreasing it for others.

The effect of age on the preference for work for single men is similar to that for married men. The preference is at a maximum around 35 years of age. Furthermore, single women’s maximum preference for work occurs around 29 years of age, which is close to the age at which this occurs for married women. For sole parents, neither age nor age squared are significant. Similar effects are found for Australia (Kalb, 2002).

Comparing the effect of children for sole parents and married women it is obvious that the age of the youngest child is important for both groups. However, for sole parents the effect decreases much less than for married mothers when the youngest child’s age increases, with the exception of moving from having a newborn child to having a 1 to 3 year old child (the effect of having a newborn child is not significant however). On the other hand, their preference for income is also at its highest when they have children in this age group, but this effect is insignificant as well.

The time trend is nearly significant for sole parents, indicating an increase in the preference for work over time, similar to the effect for married men and women. The unemployment rate is nearly significant for single men. Eligibility for the New Zealand Superannuation is significant for all groups and it reduces the preference for work, as it did for married men and women.

The models for one-adult households include an additional variable, which indicates whether the individual lives with one or both parents. Surprisingly, the effect is only significant for single men and the sign is opposite to expectations. The preference for income is higher when a single man lives with his parents. Perhaps this picks up a motivational effect where individuals who have a high preference for income, are more likely to be frugal and save for future events, which can be achieved by living at home with their parents and thus saving on living expenses. The effect for single women is positive as well but insignificant. Although insignificant, the coefficient in the preference for work parameter has the expected sign for sole parents, indicating a larger preference for work when living with one’s parents, possibly because of the potential childcare that can be provided by the parents.

Notes

  • [17]This indicates a higher preference for work and thus a smaller taste for leisure.
  • [18]This parameter is a mixture of the effect of superannuation income and a change in preferences directly caused by the eligibility for New Zealand Superannuation. The HES data does not provide enough detail on age to determine eligibility for all individuals with certainty in TaxMod. As a result, net income cannot be determined with certainty at all discrete labour supply points and thus the effect of eligibility per se and the effect through changed net incomes cannot be separated completely.
  • [19]This negative effect is likely to be a spurious relationship reflecting the often-observed correlation between low income and the number of children, which may be driven by similar household and personal characteristics.
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