Targeting Fertility and Female Participation Through the Income Tax Ghazala Azmat (Universitat Pompeu Fabra) Libertad González (Universitat Pompeu Fabra) Thursday 11th December 2008 SAE 2008

OECD Participation and Fertility Most OECD countries have experienced substantial increases female labour market Accompanied by a persistent decline in fertility rates Striking feature is the disparity in the participation and fertility rates. –Ahn and Mira (2002)

Female Participation (Ahn and Mira, 2002)

Fertility Rates in Participation Subgroups (Ahn and Mira, 2002)

The Reversal Participation differences persist across countries The relationship with fertility in these subgroups reverses. –High participations, initially low fertility, have highest fertility –Low participations, initially high fertility, have lowest fertility

The Case of Spain Spain is one of the countries that finds it difficult to reconcile motherhood with female participation Spain has one of the lowest female participation rates in the OECD Spain has one of the lowest (and declining) fertility rates –Between 1976 and 1999 TFR decreased from 2.7 to 1.07 (One of the lowest in the world)

OECD Participation Rates Countries Sweden United Kingdom Unites States Portugal Germany France Norway Canada Belgium Ireland Italy Netherlands Spain

OECD Fertility Rates (1997) CountriesTFR Norway1.86 Sweden1.51 Canada1.6 France1.7 Belgium1.6 Netherlands1.54 Italy1.17 Ireland1.91 Germany1.35 United States2.03 United Kingdom1.73 Portugal1.46 Spain1.17

Dealing with the Dual Problem The Spanish Government introduced reforms in 2003 that addressed both female participation and fertility The income tax reform had the following components: 1.Fertility: Substantially increasing child deduction with supplements for young children 2.Participation: Tax Credit, contingent on work, for mothers of young children

Aim of this Paper I To understand the effectiveness of this policy on participation and fertility (direct effects) At first glance, the policy appears to be conflicting However, we see that the target group for each policy component is different –Participation is a bigger problem amongst low educated mothers –Fertility is a bigger problem amongst highly educated women attached to the labour market

Aim of this Paper II There may, however, still exists policy interaction –Policy targeting fertility also affects participation –Policy targeting participation also affects fertility How do we disentangle? –Use earlier reforms, where child deduction changed and no tax credit existed –Estimate indirect effect of “fertility policy” on participation

Spanish Income Tax Reforms

Spanish Income Tax Reform (2003) Several important changes in the income tax schedule in 2003 Aimed at increasing fertility and female employment (in particular mothers) The reform had two main components: 1.Child deductions 2.Tax Credit

1. Child Deductions Specified amounts could be deducted from annual taxable income Varied with: –Age and number of children –Tax bracket For example, a family with two children (one under three year) could deducted as much as 800 euros extra per year

2. Tax Credit Creation of a new tax credit for mothers with children under the age of three years Contingent on work, she was eligible for a 100 euros per month

Policy Interaction The reform had two components with two objectives: –One directly targeting fertility –One directly targeting participation However, we may expect indirect effects of each component on to the other objective For instance, child deduction affects participation negatively via: 1.Income effect 2.Unobservable differences of mothers

Disentangle Difficult to separate direct from indirect effect. We go some way by using reforms that took place in 1998 The tax reform substantially altered the child deduction benefits but At this time there was no tax credit Thus, we can estimate the effect of this policy on participation → estimate of the indirect effect of child deduction on participation (Drawback: we cannot do the reverse)

Child Deduction Reform 1998 This reform implied substantial increases in after-tax income associated with having an extra child Depend on the number of children and tax bracket Tax savings as much as 2,500 euros

Data & Results

Data Use the Spanish Labour Force Data (EPA) Quarterly cross-sectional dataset on households, individuals and families We pool data from , inclusive Restrict attention to married women (18 to 45 year) Resulting sample: 1,179,478

Descriptive Statistics - Fertility New Born (Birth=1)No New Born (Birth=0) MeanStd. Dev.MeanStd. Dev. Age Participation Employment No. Children (0-2) No.Children (3-5) No. Children (6-15) No. Children (16-30) Dropout High School Edu University Immigrant N. Observations

Descriptive Statistics - Participation Mothers (0-2)All other women MeanStd. Dev.MeanStd. Dev. Age Participation Employment No. Children (0-2) No.Children (3-5) No. Children (6-15) No. Children (16-30) Dropout High School Edu University Immigrant N. Observations

Estimation: Fertility Estimate: X= age, age2, no. of other children, education, unemployment etc Post = takes value 1 starting the first quarter of 2003 Thus δ captures change in fertility trend given 2003 reform

Estimation: Participation Use standard regression based difference-in- difference: T= Women eligible for the tax credit, i.e. mothers of children under the age of three C= All other women X= age, age2, no. other children, education, etc Thus γ captures change in participation trend of T given 2003 reform

Estimation: Policy Interaction Two Stage Procedure: 1.Participation change for women with children relative to women without, given 1998 child deduction reform –Use data up to 2000 –Find estimate of effect 2.Use the estimates of effect as a measure of “indirect” effect when estimating the effect of 2003 reform –Use data

Results: Fertility (δ) CoefficientStandard Deviation Basic specification0.0041[0.0006]** By number of previous children [0.0019]** [0.0111]** [0.0178]** [0.0364] By education Dropout0.004[0.0009]** High School0.0044[0.0008]** University0.0044[0.0018]* By age Old (>30)0.0024[0.0004]** Young (<30)0.011[0.0029]**

Results: Participation (γ) ParticipationEmployment CoefficientS.D.CoefficientS.D. Basic specification0.0163[0.0041]**0.0127[0.0043]** By number of previous children [0.0064]0.0046[0.0066] [0.0066]**0.0123[0.0067] [0.0149]0.0065[0.0142] [0.0365]0.0053[0.0329] By education Dropout0.0181[0.0107] [0.0107]** High School0.0099[0.0051] [0.0053]+ University0.0088[0.0059]0.0023[0.0076] By age Old (>30)0.0213[0.0051]**0.0192[0.0052]** Young (<30)0.0133[0.0087]0.0088[0.0091]

Results: Control for Policy Inter. 2nd StageOriginal (Treat*Post2002) [0.0064]**[0.0041]** Treat [0.0157]**[0.0051]** Post [0.0029][0.0019]** Observations

Main Results Fertility: Fertility increased by 5 to 6 births per 1,000 women, for an average of 37 Strong effect on women who already have children and those with low education Participation: Impact of around 1.6 percentage points for an average of 52 percent. Strong effect on those with low levels of education Participation is significantly dampened by the “indirect” effect from the fertility policy

Conclusion We find that the 2003 had an important impact Fertility increased but effects on participation much more apparent Perhaps due to nature of policy: –Universal rather that targeted –Cash rather than assistance Moreover: One we control for the “indirect” effect, the child deductions significantly dampen participation effect –There exists some policy trade-off

EXTRA SLIDES

Participation Rates

Fertility Rates