Accessible Unlicensed Requires Authentication Published by De Gruyter July 16, 2013

Working Mums and Informal Care Givers: The Anticipation Effect

Evelyn Korn and Matthias Wrede

Abstract

Fertility and the provision of long-term care are connected by an aspect that has not received attention so far: both are time consuming activities that can be produced within the household or bought at the market and are, thus, connected through the intertemporal budget constraint of the household that accounts for time and money. This paper models that link and analyzes the effect of intervention in the long-term-care market on female labor-market related decisions. It shows that women’s fertility and their labor supply when young are affected by such policies. The overall effect can be decomposed into an opportunity-cost effect and a consumption-smoothing effect that each impact fertility as well as labor supply in opposite directions. Using survey data, the paper provides some evidence that in the member states of the European Union the consumption-smoothing effect is dominant.

JEL Classification: J13; D91; I13

Acknowledgments

A previous version of this paper titled “The effect of long-term-care subsidies on female labor supply and fertility” was presented at the CESifo Venice Summer Institute 2012 “The Economics of Long-Term Care” and at the Max Planck Institute for Demographic Research in Rostock. The comments of the participants, especially Eric Bonsang, Robert Fenge, Edward Norton, and Michael Rauscher, the editor of this journal, Helmuth Cremer and two anonymous referees are appreciated with gratitude.

Appendix

Table 5:

Probit model of fertility (marginal effects at the means).

Children≥2 children
Age0.0727***0.151***
(0.0155)(0.0213)
Age2–0.000786***–0.00173***
(0.000208)(0.000282)
Age_education_finished–0.0165***–0.0220***
(0.00266)(0.00362)
Partnership0.230***0.240***
(0.0204)(0.0297)
Rural0.0646***0.0868***
(0.0233)(0.0285)
ltcneed_parents0.02280.0344
(0.0264)(0.0340)
House0.005980.00284
(0.0229)(0.0309)
Native–0.0498–0.105*
(0.0394)(0.0558)
Healthy0.004050.0235
(0.0265)(0.0369)
Life_expectancy–0.00320***–0.00526***
(0.000947)(0.00130)
Low_skilled0.0896**0.121***
(0.0369)(0.0453)
Best_care_children0.003300.0371
(0.0225)(0.0304)
ltcparentspay–0.0342–0.0856**
(0.0249)(0.0334)
Country fixed effectsYesYes
Observations4,0364,036

Notes: Robust standard errors in parentheses, [***], [**], [*].

Table 6:

Probit model of labor supply (marginal effects at the means).

Working
Age0.0184
(0.0182)
Age2–0.000184
(0.000242)
Age_education_finished0.0283***
(0.00395)
Partnership–0.109***
(0.0253)
Rural–0.0263
(0.0244)
ltcneed_parents–0.0711**
(0.0297)
House0.0909***
(0.0263)
Native0.0892*
(0.0460)
Healthy0.170***
(0.0301)
Life_expectancy0.00440***
(0.00114)
Low_skilled–0.127***
(0.0369)
Best_care_children–0.0432
(0.0284)
ltcparentspay0.0460
(0.0299)
Country fixed effectsYes
Observations4,036

Notes: Robust standard errors in parentheses, [***], [**], [*].

Table 7:

IV regressions.

≥2 childrenNumber of childrenWorkingWorking hours
ltcparentspay–0.800*–1.805*1.696**60.57*
(0.486)(1.047)(0.686)(31.38)
Age0.116***0.245***0.04070.901
(0.0189)(0.0410)(0.0334)(1.337)
Age2–0.00132***–0.00270***–0.000482–0.0100
(0.000252)(0.000542)(0.000409)(0.0163)
Age_education_finished–0.0142***–0.0421***0.0123***0.503**
(0.00417)(0.0113)(0.00468)(0.241)
Partnership0.217***0.582***–0.127**–5.976***
(0.0333)(0.0740)(0.0622)(2.051)
Rural0.0631***0.0737–0.00325–1.068
(0.0148)(0.0457)(0.0220)(0.843)
ltcneed_parents0.008960.0126–0.0154–0.900
(0.0435)(0.100)(0.0525)(1.624)
House0.05100.0309–6.17e–05–0.650
(0.0556)(0.154)(0.0536)(2.183)
Native–0.0525*–0.0919–0.0166–1.956
(0.0314)(0.113)(0.0608)(2.728)
Healthy0.03400.01430.1083.708
(0.0405)(0.0708)(0.0747)(2.660)
Life_expectancy–0.00536***–0.0129***0.00703***0.287***
(0.00128)(0.00359)(0.00158)(0.0784)
Low_skilled0.0713***0.329***–0.0785–4.249**
(0.0257)(0.103)(0.0763)(2.164)
Best_care_children0.0710***0.188***–0.124***–2.600
(0.0240)(0.0521)(0.0470)(2.176)
Constant–1.077**–1.507–1.287*–40.25
(0.466)(1.026)(0.761)(32.28)
Country fixed effectsYesYesYesYes
Observations3,9833,9833,9833,880

Notes: Robust standard errors in parentheses, [***], [**], [*].

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  1. 1

    Colombo et al. (2011) state that in Germany the shares of people aged over 65 and 80 are 20% and 5%, respectively; the corresponding data for France are 16.9% and 5.5% and those for Sweden are 18% and 5.3%.

  2. 2

    The OECD Secretary General, Angel Gurra made a corresponding statement in January 2009 [see Gurrίa (2009) cited after Fernandez et al. (2011)].

  3. 3

    In some countries, there is a compulsory long-term-care insurance as part of the social security system. However, it covers part of the costs only and is mostly means tested [see Colombo et al. (2011)].

  4. 4

    For a recent overview of these considerations, see, e.g. Fanti and Gori (2012).

  5. 5

    For a unifying approach, see Mookherjee et al. (2012); a recent survey of models that explain the relation between fertility and income is provided by Jones et al. (2011).

  6. 6

    Stern and co-authors [see, for instance, Engers and Stern (2002) and Byrne et al. (2009)] focus on intra-familial bargaining and choose a finer-grained model of the period-2 household production. They do, however, not connect child-care and long-term care. As our model aims at assessing the average effect of an institutional frame and not the intra-familial mechanisms, we omit these aspects. In the same spirit, intra-household time allocation is not included to keep the model as simple and to keep the focus on the (household–external) tradeoff between household time and market time.

  7. 7

    The integer constraint on the number of children is disregarded.

  8. 8

    Derivatives are indicated by subscripts.

  9. 9

    Due to the absence of altruism toward the children, the mother neglects the effect that fertility decisions have on the burden of long-term care services provided by their children.

  10. 10

    If were 0, all these effects would also be 0.

  11. 11

    Since our model makes ambiguous predictions, any result on the relative strength of these effects does not provide an empirical test of the model per se.

  12. 12

    We left out those six women that had no full-time education at all.

  13. 13

    Since Northern Ireland and East Germany are weighted separately, there are 29 country clusters.

  14. 14

    We have not included the wage as more direct control for the opportunity costs of time and the value of the time endowment, because the survey provides only gross income and not enough information to simulate the tax burden. Furthermore, since no information on wages of non-employed women is provided, the number of observations would be much smaller and a selection bias would occur.

  15. 15

    Working hours of formal employment are included in the Eurobarometer 67.3 survey, because the survey focused on health and undeclared work.

  16. 16

    On the effect of social security on fertility see, for instance, Cigno and Rosati (1996), Cigno et al. (2003), and Boldrin et al. (2005).

  17. 17

    According to the OECD’s (2011b) collection of social indicators, the fertility rate in 2009 has been 1.99 in France, 1.36 in Germany, and 1.94 in Sweden.

  18. 18

    Including migrants into the labor market to a bigger extent is another means. However, in a recent OECD study, Keeley (2009) shows the limits of such an inclusion.

  19. 19

    Details on differences in these arrangements are described in Colombo et al. (2011).

Published Online: 2013-7-16

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