Female employment and pre-kindergarten: on the unintended effects of an Italian reform

Transcription

1 Female employment and pre-kindergarten: on the unintended effects of an Italian reform Francesca Carta Lucia Rizzica July 29, 2014 Abstract This paper analyses the relationship between the availability of low cost childcare services and maternal labour supply in Italy. By means of a job search model we show that lowering the price of childcare not only boosts maternal labour market participation, because it increases the value of looking for a job, but also raises the probability of getting a job by decreasing the reservation wage at which the mother is indifferent between accepting a job offer or not. We further investigate how these effects depend on mothers characteristics and local labour market features. We then test our predictions empirically exploiting the discontinuities in the rules that determine children s eligibility to different types of childcare services. Our results show that the possibility of anticipating the child s entry to kindergarten, a much cheaper alternative to daycare, increases both participation to the labour market and the employment probability of mothers, the effect being largest among women who either live in the Northern part of the country or are less educated or belong to less affluent families. Keywords: Childcare, Female Labour Supply, Public Services JEL Classification: J13, J16, H41 The views expressed in the article are those of the authors only and do not involve the responsibility of the Bank of Italy. Bank of Italy, Directorate General for Economics, Statistics and Research, Structural Economic Analysis Directorate, Labour Market Division, and Toulouse School of Economics; francesca.carta@bancaditalia.it Bank of Italy, Directorate General for Economics, Statistics and Research, Structural Economic Analysis Directorate, Economics and Law Division; lucia.rizzica@bancaditalia.it 1

2 1 Introduction Affordable childcare services are unanimously praised for their twofold role of human capital development tool on one side (Cunha and Heckman, 2007), and instrument to reconcile work and family responsibilities thus promoting female labour supply, on the other side. Indeed, there is large evidence that countries in which childcare services are more widespread also exhibit higher rates of female labour participation (Figure 2). On such grounds, both developed and developing countries have adopted policies aimed at improving the availability and affordability of childcare services. Some of these policies consist in providing public financial support to families for their childcare expenses in the form of either vouchers or tax credit; for example, the UK Government recently established that the rate of childcare benefit will raise up to 85% of childcare expenditure by the end of 2016 for low income workers and job seekers. Other countries, instead, opted for the direct provision of services, extending public kindergarten programs to younger children. Aim of this paper is indeed to evaluate the effects on maternal labour market outcomes of a policy of the latter type that was implemented in Italy since We will look not only at the actual employment status, but also at the mother s decision to search for a job, so as to take into account the possible difficulties in finding a job due to the tightness of the local labour market. The policy relevance of this issue has generated a considerable amount of empirical literature on the responsiveness of female labour supply to the cost of childcare (Table 1 summarizes the most recent literature) providing estimates which are generally positive but vary considerably in magnitude depending on the country, the period and the characteristics of the women analysed. Due to data limitations, on the other hand, the Italian context has been little analysed, the only notable contribution, to our knowledge, being Del Boca and Vuri (2007), who used data from 1998 to show that the scarce availability of childcare services, rather than their cost or the tightness of the labour market, would be the main obstacle to maternal labour supply. Indeed, the Italian context represents a particularly interesting setting in which to evaluate the responses of female labour supply to changes in the cost and availability of childcare services, because female participation and employment rates in Italy are among the lowest across Europe and OECD countries, 2 and, at the same time, the public supply 1 As we will explain in Section 3, the introduction of the possibility to anticipate access to kindergarten was not dictated by any particular welfare enhancing motivation but was the mere consequence of the introduction of pre-school for older children. 2 In 2012 the participation rate of Italian women aged was 53.5%, against the EU15 average of 67%; among the EU28 countries, Italy has one of the lowest female participation rates, and the same is 2

3 of childcare services remains scarce with private services being very costly. The causal relationship which goes from affordable childcare to maternal labour supply is exactly what we want to address. We evaluate the impact of the institution of cheaper childcare services on maternal participation and employment by first providing a theoretical contribution, a search model that accounts for the effects of variations in the price of childcare on maternal labour market outcomes, and secondly an empirical analysis that identifies such causal effects. The main merits of the analysis are to develop a unified theoretical framework to read the results of our empirical exercise and provide, for the first time, estimates for Italy, covering a yet under-investigated aspect of the functioning of the Italian labour market. More specifically, in our model mothers take their participation decision at the beginning of the school year when childcare services, as pre-kindergarten, become available. Thus, the cost of childcare is borne not only when employed, but also when searching for a job. In this setting lowering the price of childcare generally boosts both female labour market participation and employment. Nevertheless the effects are heterogeneous depending on local labour market and individual characteristics: women living in regions where more jobs are available show a larger increase in labour market participation and employment, and women who get a higher marginal benefit from a reduction in the price of childcare, for example the least educated or those with lower family income, increase their rate of participation to the labour market more. In the light of such predictions we proceed with the empirical analysis, relying on data drawn from the Italian Labour Force Survey (ILFS). We exploit exogenous variations in price and availability of childcare supply determined by the child s exact date of birth, implementing a Sharp Regression Discontinuity Design (Thistlethwaite and Campbell, 1960). We find that the relevant policy institution is pre-kindergarten, and the estimated effects of pre-kindergarten supply on maternal labour supply confirm our theoretical predictions. Indeed, the possibility of anticipating the child s entry to kindergarten causes an increase in participation of mothers to the labour market of about six percentage points, which translates into an increase in the probability of actually holding a job of about three percentage points. Both effects turn out to be concentrated among mothers living in Northern Italy, where the labour market is more fluid, and among poorer and less educated women, whose propensity to work on the market is generally lower. From a theoretical point of view our approach is innovative since most of the literature, whose main reference is Blau and Robins (1988), has adopted static models of observed for women aged and Also the employment rate was much smaller than the EU15 average (respectively, 46.1 and 59.4%). 3

4 labour supply to illustrate the effect of a price subsidy to child care (or free child care) on mothers working hours, focusing only on the intensive margin of maternal labour supply. On the other hand, the empirical literature in Table 1 has found a negligible effect of lowering the cost of childcare on mothers hours of work vis à vis a sizable effect on participation and employment. 3 Our point is to focus on the extensive margin, abandoning the static labour supply framework in which the individual takes consumption and leisure decisions, and adopting a dynamic search framework to account also for the possible difficulties in finding a job due to the tightness of the labour market. Indeed, we believe that this approach is more suitable to illustrate the Italian case, where participation and employment rates are particularly low, while the number of hours worked conditionally on being employed is in line with that of the other main European economies. From an econometric point of view, we rely on an identification strategy that is similar to those of Fitzpatrick (2010), Goux and Maurin (2010) and Berlinski et al. (2011), in that we exploit exogenous discontinuities in the price and availability of childcare supply determined by the child s exact date of birth. In particular, by exploiting different thresholds of date of birth which determine access to different types of childcare services, we shed light on the effectiveness of policy measures which differed in terms of costs, quality and availability. The paper is organized as follows: Section 2 introduces our theoretical framework; the Italian institutional context is then presented in Section 3; Section 4 provides a short description of the dataset and illustrates the main features of our sample; our empirical strategy is then explained and discussed in Section 5, and in Section 6 we report the results of the empirical analysis; Section 7 provides some specification checks, and finally Section 8 concludes. 2 Theoretical framework 2.1 The basic set-up In this section we develop a simple search model to explain how the provision of cheaper child care services may affect maternal labour market participation and employment; then, we investigate how these effects may depend on mothers characteristics and on local labour market features. Our main reference for the model we develop below is Pissarides (2000). 3 It is crucial to highlight that most of these works focus on children aged 4 to 5, only Goux and Maurin (2010) look at 2-3 year olds as we do. 4

5 We consider a population of mothers having one young child aged 0-3 and assume that they are the only ones responsible for caring the child. To build a model consistent with our empirical strategy we assume the following timing of events (Figure 1): at time t = t 0 the school year starts and the mother decides whether to participate or not to the labour market. The participation decision is taken at this time since access to childcare services is available only at the beginning of the school year; the mother incurs in the cost of childcare before knowing whether she will get a job or not. 4 At time t = t e we observe her labour market status; 5 she can be (i) non-participant; (ii) job searcher (or unemployed); or (iii) employed. Conditional on participation, a mother may be employed in any period t q [t 0 ; t e ] in which she receives and accepts an offer; in case of rejection she is unemployed and keeps looking for a job. The problem consists in taking two decisions: first, the mother chooses to participate or not given her her expected job opportunities; second, conditional on participation, once the job offer arrives she decides to accept it or not. Assuming that during the period [t 0 ; t 1 ] no structural change occurs in the labour market, at t = t 0 the mother determines her participation status and her accepting rule. The mother aims to maximize her life-time utility: (1 r) t u (c t ) (1) t=0 where c t is actual consumption, which differs according to the mother s labour market status, and 0 r < 1 is the discount rate. The function u(c t ) is the instantaneous utility from consumption, it is assumed to be increasing and concave in c t. is: The value function of a mother choosing to stay out of the labour force (non-participant) rv o = u (δ o ) (2) where δ o is the stream of real returns from non-participation; these can be thought of as the value of home production. By staying at home she directly provides care to the child 4 The type of care we are considering is formal childcare and we assume that free childcare is not available. An extension of the model consists in distinguishing between formal childcare, accessible only at the beginning of the year and before the job search outcome is known, and informal childcare, needed only in case of employment. In this simplified version we assume the mother prefers formal care, even if she faces the risk of not finding a job, than informal care. 5 In the empirical part this will be the three quarters of the school year. 5

6 and no external care is needed. We assume that δ o is a drawing from a distribution with cumulative density G (δ o ) defined over the support [ δ, δ ]. Looking for a job is costly since formal childcare has to be paid at the unit price p. However, we assume that only a fraction s of the full price is paid when unemployed; for example, unemployed mothers might have access to discounts or lower tariffs or they may use only part-time childcare services. 6 Moreover, we assume that looking for a job does not prevent from carrying out domestic production for consumption needs. Being active and looking for a job exposes the individual to receive a job offer with some probability λ. The job offer is described by a wage w drawn from a cumulative distribution F (w); if the offer is accepted the individual becomes employed, otherwise she continues to look for a job. We rule out the possibility of recalling a job offer. As in Pissarides (2000) the return from being unemployed for a given working mother is the sum of the flow of real returns of job seeking and the expected value from moving into employment: [ ] rv s = u (δ o sp) + λmax V e (x) df (x) V s ; 0. (3) w If the mother is employed she inelastically supplies one unit of labour at wage w and has to buy an equivalent amount of childcare. Since she devotes all the time to market work, household production is null. 7 Moreover, we do not allow for the possibility of layoffs nor on-the-job search. 8 The value function of being employed is: rv e = u (w p). (4) where w p > δ o > δ o sp, otherwise there is not incentive for the mother to participate. 2.2 The participation decision The analytical problem related to the participation decision is static and the decision is taken once and for all: there is no economic reason in moving in (even if possible) or out of participation in any period subsequent to t 0. At t = t 0 the maximum expected value 6 The fraction s could indeed be interpreted as a constant time cost of search, s < 1, where total time endowment is normalized to 1; childcare has to be bought only for the time in which the mother is looking for a job. For example, the unemployed mother uses part-time formal childcare paying only a fraction of its full cost. 7 The main assumption is that free childcare is not available; this is quite realistic given geographical mobility and pension reforms: parents live away from grandparents and they cannot rely on their help. 8 We believe that this assumption is not unrealistic in our context since we are looking at short run effects of reducing childcare price on maternal participation and employment. The time span is nine months. 6

7 function of being non participant is: V o = max [V s ; u (δ o ) + (1 r)v o ]. (5) The condition for participation simply requires V s u(δo) and, if at t = t r 0 it is optimal to look for a job, so it will be in the following periods. To inspect the participation condition it is necessary to solve for V s. Combining equations 3 and 4 yields: V s = u (δ o sp) + λ u (x p) df (x) r w r + λ = u s + λ r E (u e) r + λ (6) where u s = u (δ o sp) is the per-period utility of consumption if unemployed and E (u e ) = u (x p) is the expected utility of consumption in case of employment. w A mother participates if V s V o, and the size of the labour supply is H (rv s ), 9 which increases with the value of unemployment in 6. It is straightforward to derive our first set of results. Proposition 1 A reduction in the price of childcare increases maternal participation since: V s p = su s + λe r (u e) r + λ < 0. (7) Participating to the labour market is like a lottery: the mother pays the cost sp for participation with the aim of increasing her consumption possibilities from δ o to w p. The lower the price p, the more participation is worthwhile: the participation fee of the lottery is lower and the net expected benefit is higher, thus creating incentives to exit from the non-participation status. Proposition 2 When the probability of finding a job is higher, the effect of a reduction of p on maternal participation maybe larger or smaller, depending on the fraction s of the full price of childcare paid in case of unemployment: 2 V s p λ = E (u e) su s (r + λ) 2 = 0 if s E(u e) u s > 0 if s > E(u e ). 9 Function H is the monotonic transformation of G determined by u. u s 7

8 We shall observe a stronger effect of a reduction in the price of childcare on maternal participation in regions where the probability of finding a job is higher. 10 The lower price of childcare increases the mother s utility both when she is unemployed, by su s, and when she has a job, by E (u e). If the utility gain is higher when the mother works, women living in regions with higher probability of finding a job will participate more than those living in regions with a lower probability. Since E (u e) < u s by definition, to have that the utility gain associated to the lower childcare price is higher in case of employment, the cost of childcare when unemployed has to be sufficiently low, as expressed in proposition 2. Assuming that firms are atomistic and in equilibrium pay a wage equal to the individual marginal productivity of labour, α, plus a random component, w = α + ɛ. If individuals differ in terms of their marginal productivity of labour (for example more educated vs. less educated) we establish the following result. Proposition 3 The effect of reducing p on participation is larger for less educated mothers. Indeed equation 7 is increasing, in absolute value, in the expected marginal benefit from employment, E (u e). This result is driven by the concavity of the function u and by the assumption that less educated women face lower expected wages, which reflects their corresponding productivity. The higher is the expected wage, the smaller is the benefit of a reduction of p in terms of utility. Consider now the case in which mothers have some non-labour income available for consumption, thus the argument of the utility function becomes c t + y t (for example, it is the spouse s labour income). If women are heterogeneous with respect to y t, this will affect their response to the price reduction. Proposition 4 The higher is non-labour income y the smaller is, in absolute value, the effect of a reduction in the price of childcare on the propensity to participate to the labour market (equation 7) : 2 V s p y = su s + E (u e) > 0. r + λ Again, the result is driven by the concavity of of the function u. The higher is the non-labour income, the smaller is the benefit of a reduction of p in utility terms. 10 Here we are interpreting λ independent of individual characteristics and determined by demand-side variables. 8

9 2.3 The employment decision A reduction of the fixed cost of participation, i.e. of childcare, not only makes participation less costly, but also affects the decision rule related to accepting a job offer or not. The decision rule is based on the definition of a reservation wage, R, the wage at which the agent is indifferent between accepting the offer or keep searching and waiting for another offer: u (R p) r = V s. (8) Replacing 8 in equation 3 and after some manipulations, we get the following condition: u (R p) u (δ o sp) = λ r w R [u (x p) u (R p)] df (x) (9) which becomes, in the more familiar case of a linear utility function: R δ o (1 s)p = λ r w R (x R) df (x). (10) Equation 9 (or 10) is the key optimality condition for sequential search. On the right hand side there is the discounted expected benefit of another period of search. On the left hand side there is the opportunity cost, in the form of foregone earnings, of searching for another period. Since the first is increasing in R while the second is decreasing, the existence of a unique solution of 9 (or 10) is guaranteed. The price of childcare affects both terms: R p = u (R p) su (δ o sp) λ r w R [u (x p) u (R p)] df (x) u (R p) [. (11) 1 + λ (1 F (R))] r Indeed, lowering the price of childcare has a unambiguously negative effect on the discounted expected benefit of searching for another period, since the incentive to wait for a better offer is lower. The result is driven by the concavity of the utility function and reduces the reservation wage (the last term in equation 11). The effect on the opportunity cost of search for another period is ambiguous, and again depends on the relative gain in terms of utility associated to a lower price of childcare in the case of employment and unemployment. If the cheaper childcare benefits more the employed mother, the cost of waiting for a better offer is higher and this will push the mother to accept a lower wage offer, thus reducing her reservation wage (the difference term in 11). Again, this happens for sufficiently low values of s. If, instead, the cheaper childcare benefits more the unemployed mother, we have that the opportunity cost of searching for another period is lower and increases the reservation wage. The net effect in 11 would be ambiguous. 9

10 If we consider the case of linear utility, since the discounted expected benefit of further search is constant with respect to p, lowering the price of childcare reduces the reservation wage: 11 R p = 1 s > 0. (12) 1 + λ (1 F (R)) r The probability of being employed is h = λf (R), which is the probability of receiving an offer larger than the reservation wage. The following propositions summarize how the lower price of childcare affects the probability of being employed and how such effect depends on λ. Proposition 5 In the case of linear utility, or for sufficiently low values of s, the probability of getting employed is decreasing in the price of childcare h p = λf (R) R p < 0; Proposition 6 When the probability of finding a job is higher (higher λ) the effect of a reduction of the price of childcare is larger in absolute value: [ 2 h p λ = f (R) R ] p λ 2 R = (1 s) [1 + λ2 p λ r f (R) R ] < 0 λ since R = w R (x R)dF (x) > 0. λ r+λ(1 F (R)) 3 Institutional setting Early access to kindergarten was regulated, for the first time, in 2003 by Law n. 53/2003, known as Riforma Moratti, from the name of the Ministry of Education of the time. Differently from what happened in other countries, in Italy the introduction of prekindergarten was not driven by the idea of taking care of early childhood development, nor of encouraging female labour market participation. It was, instead, at least at the beginning, a mere consequence of the introduction of early access to primary school: in the attempt to reduce the age of high school completion from 19 to 18 years old, so as to align the Italian school system to the other European ones, access to primary education 11 Only if s = 1 the employment decision does not depend on the price of childcare. However, it is realistic that looking for a job requires to rely on childcare services less than when working, since some search activities might be combined with taking care of the child (for example being at home and searching on internet). 10

11 was allowed to children who turned 6 by the 30th of April of the year after enrolment (thus enlarging the number of school eligible pupils). Early access to primary education, though, entailed the risk of emptying kindergartens so, to avoid this, the Ministry decided to apply the same anticipation rule to allow 2-year old children to access kindergarten. 12 Kindergartens, yet, had to give priority to regular students, but no skills requirements were introduced. In a first phase, from the school year to , early kindergarten was quite used. In early students were 49 thousands, 9.1 % of 2 year olds, while in they were 71 thousands, around 13%. Among early students, most of them were located in the Southern regions and went to private kindergartens (Istituto Degli Innocenti, 2011). The positive result registered brought the legislator to think about the pedagogical and educational content of pre-kindergarten. Since it did not feature any special program for the youngest, it was perceived as a way of forcing children s natural development pattern. For this reason pre-kindergarten was abolished in and replaced by a new educational service for children aged 24 to 36 months, called Sezioni Primavera (SP), which was instead created within the nurseries. The Sezioni Primavera acted as a bridge between the nursery and kindergarten, with a specific pedagogical curriculum and a set of rules different from those of kindergartens. Even if the new service was considered qualitatively superior to pre-kindergarten, the number of children enrolled was lower (25 thousands less), presumably because the service was only scatteredly activated because of its high costs. Indeed, while private schools managed to offer a number of places similar to the one guaranteed by early access to kindergarten, public institutions activated only one quarter of the places available through early access to kindergarten. Pre-kindergarten was thus reintroduced in with the aim of meeting the demand for childcare that had emerged during the first years, while still providing a service of good quality (as in the Sezioni Primavera). Indeed it was established that kindergartens offering early access had to offer suitable places and equipment for 2-year old children, while still giving priority access to regular children. 12 Early access to kindergarten was ruled exactly like early access to school: it extended the possibility of enrolling to children who turned 3 by April of the school year, while previously children would be accepted into kindergarten if they turned three by December of the school year. 13 Financial Law 296/2006; the last school year of application was Decree of the President of the Republic 89/

12 The new phase of pre-kindergarten was characterized by: (i) an increase in the number of children who used the service; there were 83 thousands of them in 2010 (15% of 2 year olds), 86 thousands in 2011 (15,1%); (ii) a prevalence of public schools against the private ones (differently from the first phase), in particular there was a sharp decrease in the use of private schools in the South; (iii) a marked concentration of pre-kindergarten users in the South, which counted almost 50 out of a national total of 86 thousand early students (58 per cent); if one considered only the public schools, this proportion would even raise to 67 per cent. More in detail, in 2011 the take-up rate of early access eligible pupils was inversely related to the availability of alternative child care services 15 as shown in Figure 4. The coverage rate was between 14 and 17% in the North and in the Centre, while it ranged between 3.5 and 6% in the South. Inversely, the take up rate by eligible children reached 60% in the Southern regions, while it remained below 30% in the Centre and in the North (Istituto Degli Innocenti, 2011). 4 Data and descriptive statistics Our study relies on data drawn from the Italian Labour Force Survey (ILFS), which is a quarterly rolling panel dataset collected by the Italian Statistical Office (Istat). The dataset contains about 250,000 households, 600,000 individuals per wave, for whom detailed information about their labour market status, but also their family structure and other socio-economic characteristics is collected. We use data that span from 2005 to 2013 and build a sample of mothers aged 15 to 60, whose youngest child is 2 to 3 years old in the corresponding academic year (we exclude the summer quarter from the analysis). Because our independent variable, namely eligibility to childcare services, does not vary during the academic year, we collapse our sample so as to observe each mother only once during each school year. We end up with about 5,000 women per year, whose main characteristics are summarized in Table 2. The data confirm the widely known fact that Italian mothers are relatively old compared to continental Europe s ones, indeed the average age of mothers in our sample is above 34 years old. 16 Secondly, the size of the households is small: on average there are 15 This is measured by Istat as the number of places in kindergarten or daycare services over the reference population, and is referred to as Coverage Rate. 16 According to OECD data, the average age of first child bearing in Italy was in years old, the second highest after Germany and the UK (30 years old). The average across all OECD countries was instead

13 less than four people in the household, which suggests not only that couples often have only one child, but also that it is rare that grandparents live in the same household. With respect to the geographical distribution of the respondents, this appears to be in line with the data from the national Census: about 46% of women aged between 15 and 60 live in the Northern regions, 17% live in the Centre and 37% in the South. In terms of education, it appears that more than one third of the women in the sample have at most reached the compulsory school leaving level (age 14), 45% of them have a high school diploma and about 20% have a college or higher education degree. Table 2 then contains information about the labour market status of the women in our sample: 62.6% are either searching for a job or employed (labour market participants), of these 84% are employed while the others are unemployed. A very large share (38%) of women then just work inside the household and define themselves as housewives, while about 3% are either searching for their first occupation or still studying. 5 Empirical Strategy 5.1 Identification The structure of the policy scheme allows us to implement a Sharp Regression Discontinuity Design (SRD) based on the date of birth of the youngest child in the household. Indeed, eligibility to kindergarten, pre-kindergarten and Sezione Primavera is determined by the child s date of birth through a discontinuous rule. For example, for the case of pre-kindergarten the law provided that while a child born on the 30th of April could enroll to kindergarten when he is 29 months old, a child born the day after, could only go to kindergarten one year later (equation 13) 1 if dob i <= 30/04/t 3 P K it =. (13) 0 otherwise Figure 3 provides a graphical representation of the eligibility rules for the three types of childcare services: all children turning three in the solar year of the beginning of the academic year were entitled to enroll to regular kindergarten; all those born between January and April of the following year could enroll to pre-kindergarten in the same year, conditional on availability of places, or could go to Sezioni Primavera; while those born between April and December could only go to Sezioni Primavera. Exploiting this assignment rule we aim at comparing children whose date of birth falls within a small interval of the cutoff point (30/04/t 3 for the case of pre-kindergarten, 13

14 31/12/t 2 for the case of SP), the underlying idea being that these children, and their mother will be identical for all characteristics, with the exception of eligibility to prekindergarten or SP. We decide to focus on the youngest child in the family because that is the relevant margin for a mother who has to decide whether to participate to the labor market or not: if she has a younger child who still needs to be looked after, the fact that the older one can be enrolled to pre-kindergarten or SP will not affect her labour market participation decision. We thus regress the probability of the mother of child i being employed (or in search of a job) on a running variable that we build as the distance in days between the child s date of birth and the cutoff point. This distance will be positive for children born before the cutoff date (thus eligible) and negative for children born after (thus not eligible). Let EM i = 1 if the mother of child i (who has no younger children in the household) is employed, and let dobscore i be a continuous variable measuring the number of days of distance between the child s date of birth and the cutoff point of the 30/04/t 3 (or 31/12/t 2), we can then estimate a regression of the type: P r(em it ) = f(dobscore i ) + β P K it + ɛ it (14) where f( ) is a smoothing function and the parameter β will provide an estimate of the causal effect of eligibility to pre-kindergarten of the youngest child in the household on the mother s probability of being employed. For the case of pre-kindergarten, we get: ˆβ SRD = lim E (EM it dob i ) lim E (EM it dob i ). (15) dob i 30/04/t 3 dob i 30/04/t 3 + We run the same regressions also on a labour market participation indicator, so as to account for the fact that not all women who decide to work actually manage to find a job. Unfortunately, the Labour Force Surveys contain no information about the actual enrollment of the child to pre-kindergarten or SP so that we are only able to identify the effect of pre-kindergarten or SP eligibility rather than the effect of actual enrollment. This means that, provided that not all mothers whose youngest child was eligible to prekindergarten actually used the service, the treatment effect that we estimate will need to be weighted by the (inverse of the) take-up rate or rate of compliance in order to retrieve the actual treatment effect. The figures from Section 3 showed that the take up rate was particularly high in the most recent phase of the policy (see Figure 4) so that we can be confident that our eligibility effect is not too far from the actual treatment effect (this 14

15 will anyway be larger in magnitude than the estimated parameter). On the other hand, the parameter that we estimate represents an Intention To Treat effect and can thus be particularly interesting from a policy perspective: as pre-kindergarten is not compulsory, the policy maker will be most interested in the effect of providing families with the possibility of sending the child to school one year earlier. 5.2 Estimation The intuition behind a SRD is that comparing the pool of individuals in a small enough neighborhood of the discontinuity is similar to a randomized experiment at the cutoff point because individuals below and above the cutoff point are essentially the same. In this paper we report estimates of the β coefficients based on both parametric and non parametric specifications of the conditional mean of the outcomes. As for the parametric specification, in the tables we present results for linear and quadratic specifications allowing the slope and the concavity of the function to change independently on each side of the cutoff. On the other hand, we also present estimates based on a non parametric specification, which allows us to relax most of the assumptions required by the parametric models (most importantly the choice of the order of polynomial). Following Hahn et al. (2001), we employ a non parametric local linear regression (LLR) to approximate the function f( ) of equation 14 as the forcing variable approaches the cutoff point; as for the parametric case, the difference between the two functions at the cutoff point will provide the estimate of the treatment effect. For all three specifications we decided to trim the data at 6 months from the cutoff, which leaves us with samples of about 10,500 mothers for each cutoff. The LLR on the two sides of the cutoff is estimated using Triangular Kernel weights so that observations which are closer to the cutoff point will carry a larger weight: Fan and Gijbels (1996) proved that Triangular Kernel weighted local linear regression performs optimally at the window boundary and thus also at the cutoff where the SRD requires most precision. The only choice required in the LLR estimation remains that of the bandwidth: a larger bandwidth would improve the precision of the estimates (lower variance) but return more biased estimates of the treatment effect. In this paper we do not use the optimal bandwidth derived by Imbens and Kalyanaraman (2010) through plug-in methods (this minimizes the Expected Squared Error Loss around the cutoff point) because this produces under-smoothing and thus very noisy and unstable estimates. We rather decide to allow for the risk of having more bias and rather improve the smoothness of the relationship between the child s date of birth and the mother s employment status by choosing a 15

16 larger bandwidth. Anyway, in the specification checks, we will show that our main results do not vary when we change the value of the bandwidth employed. Finally, we account for time trends and geographical disparities in the labour market by clustering standard errors at the level of region and year. 6 Results The first variable that we consider is whether the mother participates to the labour market, i.e. whether she is looking for a job (unemployed or first job seeker) or employed. Figure 5 shows the discontinuities in such probability for the three relevant cutoff dates: 31/12/t 3, 30/04/t 3 and 31/12/t 2, which respectively determine admission to kindergarten, pre-kindergarten and Sezioni Primavera in the academic year t/t + 1. The horizontal axis represents the distance from the cutoff date of birth, observations to the right of the cutoff correspond to children who were born before the cutoff, i.e. are old enough to be eligible to attend the childcare service, observations to the left of the cutoff, conversely, represent children who were born after the relevant cutoff date, and so are too young to be eligible. The first row of graphs shows the results of the parametric second order polynomial, while the second row of graphs shows the same discontinuities but estimates are based on local linear regression with triangular Kernel weights and a bandwidth of 60 days to sufficiently smooth the function f( ). The dots of the underlying scatterplots show the mean outcome in bins of one week width (Lee and Lemieux, 2010). The discontinuities showed in the graphs correspond to the estimates reported in table 3. The reported ITT coefficient measures the height of the jump at the cutoff point, the baseline is instead the value of the outcome variable at the discontinuity for the non eligible individuals (the left hand side of the discontinuity). The estimates reported in the table show that eligibility of the youngest child in the household to pre-kindergarten increased the likelihood that the mother actively participates to the labour market by 4.4 to 5.6 percentage points over a baseline of about 61%, thus confirming our first theoretical prediction of proposition 1. We then turn to the analysis of the effects of eligibility to the various types of childcare services on actual employment of the mothers (proposition 5): the results, illustrated in Figure 6 and detailed in Table 4, show that the overall impact of eligibility to childcare on maternal employment was not statistically significant in most cases, but that it was still consistently positive across the various specifications for the case of eligibility to pre- 16

17 kindergarten, which determined an increase in female employment of about 3 percentage points over a baseline employment rate of 52%. Such effect is slightly smaller than those estimated in the existing literature and reported in Table 1, though the difference is in most cases not significant in statistical terms. In turn, our results show that pre-kindergarten was the only relevant policy that significantly affected the propensity of mothers to participate to the labour market. The absence of any significant discontinuity at the point of eligibility to kindergarten is a mere consequence of the fact that families could now anticipate the entry of their kids to kindergarten so that a child born on 1/1/t 2 did not anymore have less chances of getting into kindergarten than a child born on 31/12/t 3. On the other hand, with respect to SP, we suggest that its introduction was ineffective because the service was very little activated within the public (thus low cost) facilities; as we described in Section 3 the public structures offered through SP only one fourth of the places that had been made available through pre-kindergarten. The fact that only the private institutions provided an adequate supply of this service likely explains why we hardly see any effect on the mothers labour market outcomes. Having established that pre-kindergarten was the only policy which influenced the labour market decisions of mothers, we explore various dimensions of heterogeneous effects. First, in Table 5, we consider geographical heterogeneity splitting our sample in three macro areas. Because the Italian labour market is characterised by strong geographical disparities, with the Northern part of the country displaying a much more dynamic labour market than the Southern part, this exercise can be viewed as a test of our propositions 2 and 6. Indeed this analysis reveals that the effect of increasing the provision of low cost childcare services was entirely concentrated among mothers living in Northern Italy, where the increase in participation was between 8.1 and 12.4 percentage points and that in actual employment between 5.7 and 10.3 percentage points. Such magnitudes are very much in line with those of the effects estimated for the US (Cascio, 2009; Barua, 2011), as are indeed the baseline participation and employment rates. Following the prescriptions of our model, the second dimension of heterogeneity that we consider is the level of education of the mothers (proposition 3); we thus split the sample in three subsamples depending on the highest level of education the mother achieved. It now appears that the magnitude of the effect of pre-kindergarten availability was higher the less educated were the mothers, so that women who had at most completed compulsory schooling increased their rate of participation to the labour market by 6.9 to

18 percentage points, while those who had completed high school experienced a significant increase of 5.3 to 6.9 percentage points, and those who had some higher education degree were instead not affected at all by the expansion of kindergarten supply. On the other hand, the effects on the probability of holding a job were only relevant for women with a high school degree, thus suggesting that, differently from the least educated ones, these women have good chances of finding a job once they enter the labour market. Finally, we test our proposition 4 by splitting the sample on the basis of the household labour income that is not derived from the woman s own work, in most of the cases this is thus simply the husband s monthly wage. This exercise confirms that the effects of lowering the price of childcare on women s participation to the labour market was larger when these had low levels of non own labour income, in line with our theoretical predictions. 7 Specification Checks In order for the Regression Discontinuity Design to yield consistent estimates we require the counter factual conditional distribution of the outcome variable to be smooth over the date of birth, i.e. that the probability that a mother decides to search for a job and finds it is, in the absence of the policy, continuously related to the age of the child (if we were to look at a wider window, we would expect such probabilities to be increasing over the age of the child, while they appear essentially flat when we restrict our attention to a one year of age window). While this assumption cannot be tested directly, it is common practice to assess its feasibility by checking that other variables which are usually associated to the outcome of interest do not also vary discontinuously at the threshold (Imbens and Lemieux, 2008). Figure 7 and table 8 show that the estimated discontinuities for the main socio economic characteristics of the mothers are not statistically significant. 17 Secondly, one may be concerned that the results of the SRD exercise are driven by some manipulation of the forcing variable so that individuals would self select into the eligible group in order to benefit from the policy intervention. If this was the case, the 17 One may be concerned about the geographical distribution of the individuals; it appears indeed that at the cutoff there are less women from the South on the right hand side of the cutoff (eligible) than on the left hand side. If anything, this would bias downward our results because it lower the weight of the eligible individuals in the South. Yet, as we showed that the overall result is driven by women in the North and that the effect was essentially null in the South, we can be quite confident that such small discontinuity will not bias our main results. 18

19 SRD results would be biased and likely overestimate the impact of the policy (under the assumption that those who deliberately self selected into the eligible group were the most sensitive to the policy intervention). In this setting, a manipulation of the running variable would mean that mothers strategically choose when to deliver their baby so as to benefit from the possibility of anticipating his entry to kindergarten. Although this may seem unlikely, we formally test for the presence of manipulation of the forcing variable using the test designed by McCrary (2008). This is based on estimating the discontinuity at the cutoff in the density function of the running variable through Local Linear Regression techniques with triangular Kernel weights. Figure 8 shows the estimated discontinuity in the density of the forcing variable and confirms that the population density is smooth across the cutoff. Our third robustness check is then a test of the sensitivity of our non parametric results to the choice of the bandwidth. Figure 9 shows that the estimated coefficients, both for participation and for employment, are very unstable and noisy for small values of bandwidth and then stabilise for quite large values (above 90 days). In particular the figures show that our most preferred non parametric specification is likely to provide just a conservative estimate of the true effect as this actually appears to get larger and statistically significant for values of the bandwidth larger that the one we employed. In Figures 10 and 11 and in Table 9 we report the results of a further robustness check: the estimation of the treatment effect through differences in discontinuities which allow identifying the Average Treatment on the Treated effect when different policies share the same threshold for eligibility (Grembi et al., 2012). In our setting problems could arise because the same threshold, though later in life, applies for kids to enter pre-school when they are 5 year old. As suggested by Fitzpatrick (2010), because the eligibility date of birth for pre-kindergarten and pre-school is the same, without the use of a control group, it would not be possible to distinguish pre-kindergarten effects from enrolment effects resulting from a child s eligibility to preschool in three years time. Indeed, parents choices may be just driven by the desire to enrol the child to pre-school in the future, and for this reason, exploit also the availability of pre-kindergarten to make sure the kid attends three years of kindergarten before going to school. To rule out this possibility we exploit the fact that pre-kindergarten was not in place in the school years 2006/07 to 2008/09 (while pre-school was) to create a suitable control group. Comparing the discontinuities at the pre-kindergarten cutoff between the period 19

20 in which pre-kindergarten was in place and that in which only SP we active, we estimate that the effect of pre-kindergarten availability on mothers labour market participation and employment was even slightly higher than that previously estimated through standard regression discontinuity. The effect on participation, which ranged between 4.4 and 5.6 percentage points, is now between 5.8 and 10.2 percentage points (and highly significant), while that on employment, which was between 1.1 and 3.2 percentage points, is now between 2.2 and 3.8 percentage points. Thus, again, our main econometric specification turns out to be conservative as of the magnitude of the estimated effects. Finally, we run a falsification test and reestimate all the main results at a false cut off point, which we take as May, 31st (one month after the real cutoff). The estimates reported in Table 10 confirm that the relevant point of discontinuity was indeed the 30th April and thus confirm that the effects identified are due to the policy implementation. 8 Conclusions The female participation rate to the labour market in Italy is among the lowest across Europe and OECD countries. At the same time the supply of childcare services, either public or private, remains extremely scarce. Despite the clear positive correlation between these two variables, it remains unclear whether it is the undersupply of childcare services which induces mothers to stay home and look after their children, or instead, whether it is the inadequate provision of childcare services that is caused by a lack of demand for such services, because women prefer to look after their children themselves. Our paper delves into this relationship providing first a theoretical contribution, a job search model that accounts for variations in the price of childcare services on maternal labour supply, and secondly a robust empirical analysis that allows us to identify such causal effects. To our knowledge, we are the first to provide such estimates for Italy. From a theoretical perspective we depart from the standard approach adopted by the literature, which analysed the effect of lowering the cost of childcare on mothers working hours, to focus on the effect on participation and employment decisions. In particular, we show under which conditions a reduction of the price of childcare increases maternal participation and employment and how this effect interacts with the mother s socio-economic characteristics and the local labour market features. To account for different effects on participation and employment, we assume that the mother has to incur in child care 20

21 expenses also when looking for a job, because the decisions of whether to search for a job and that of enrolling the child to pre-kindergarten are to be pretaken contemporaneously. We further show that in this setting a reduction in the price of childcare services has a stronger effect on female participation when the probability of finding a job is higher, since this acts as a multiplier effect. Moreover, the effect is stronger among those mothers who marginally benefit the most from the price reduction, typically the least educated and the poorest. We then turn to the empirical analysis, which rests on a Sharp Regression Discontinuity Design: exploiting the rules of eligibility to access to childcare services based on the child s date of birth, we manage to identify which mothers could benefit from low cost childcare services, in particular pre-kindergarten, and which could not. We thus estimate that the possibility of using low cost childcare services, specifically of anticipating the child s entry to kindergarten, caused an increase of participation of mothers to the labour market of about six percentage points, which translated into an increase in the probability of actually holding a job of about three percentage points. These effects turn out to be concentrated among mothers living in Northern Italy, where the labour market is more fluid, and among less educated and poorer women, whose propensity to work on the market is generally lower. In conclusion, the present paper provides strong and robust evidence of the fact that increasing the provision of low cost childcare services does generate a significant increase in female labour supply, especially among those categories that are most underrepresented in the labour force (women with low levels of education or belonging to less affluent households). Yet, it appears that such increase is completely offset in places with poor labour market opportunities (as Southern Italy) and only benefits women with a relatively low propensity to participate to the labour market; for the other women, the provision of low cost childcare services would instead represent a kind of income subsidy and not induce any positive effect in terms of stimulating labour supply. Still, the possibility of attending childcare facilities, rather than being grown up inside the household is likely to have positive effects on children s development, as suggested by the most recent literature (Havnes and Mogstad, 2011; Herbst, 2013). For this reason an exhaustive analysis of the overall welfare effects of increasing the supply of public childcare facilities would call for studying the effects on children as well, which we are currently leaving to our future research agenda. 21

22 Table 1: Effect of public school/pre-school attendance on maternal labour supply Authors Country Children s age Empirical Strategy Labour supply measure Effect on mothers labour supply Baseline Gelbach (2002) US 5 IV (quarter of birth) Employment +4 p.p. 70% Berlinski and Galiani (2007) Argentina 3-5 DD Employment p.p. 36% Cascio (2009) US 5 DD Employment +7.5 p.p. (single mothers only) 58% Goux and Maurin (2010) France 2-3 Fuzzy RDD (date of birth) Participation +3.6 p.p. (single mothers only) 79.7% 22 Fitzpatrick (2010) US 4 Combined Sharp RDD and DD (date of birth) Employment Null 56% Schlosser (2011) Israel (Arabs) 2-4 DD Participation p.p. 6% Barua (2011) US 5-6 IV (quarter of birth) Employment and participation +11 p.p. no effect on part. (married women only) 59% Berlinski et al. (2011) Argentina 5 Fuzzy RDD (date of birth) Employment +6.6 p.p. 37% Havnes and Mogstad (2011) Norway 3-6 DD Employment Null 24.5% Herbst (2013) US 0-12 DDD Participation 0.1 pp 15.9%

23 Figure 1: Timing of events t 0 t q t e t participation decision if job offer acceptance decision labour market status is observed Figure 2: Childcare Availability and Maternal Employment Employment Rate - Mothers of <3 year olds Netherlands Cyprus Portugal (5,6) Luxembourg Lithuania Austria Belgium Germany Ireland United Kingdom Spain Italy Finland Poland Greece Latvia Estonia Czech Republic Hungary Slovak Republic Slovenia France Sweden Denmark Childcare Coverage Notes:: Maternal employment rates refer to 2009 and are computed among mothers whose youngest child was less than three years old; source: European Union Labour Force Surveys (EULFS) ( ). Childcare Coverage is computed as the number of places available in either public childcare or publicly financed day care facilities over the reference population in 2004; source: European Commission. 23

24 Figure 3: Eligibility to public childcare services in academic year t/t+1 Kindergarten PK +SP Sezione Primavera 1/1/t-3 31/12/t-3 30/4/t-2 31/12/t-2 Nursery or other daycare services dob Figure 4: Take-up and childcare services coverage rates, 2011 Notes: Take up rate is computed as the number of children born between January 1st and April 30th 2008 who enrolled to prekindergarten, divided by one third of the total number of children born in Data on enrollments to pre-kindergarten are taken from Istituto Degli Innocenti (2011). Coverage rate is computed by Istat as the number of 2 years old children attending public childcare facilities, divided by the number of 2 years old children. 24

25 Table 2: Descriptive Statistics Kindergarten Pre-kindergarten Sezioni Primavera Total Age (6.564) (5.244) (5.910) (5.870) Single (0.375) (0.364) (0.378) (0.374) Household size (1.073) (0.913) (0.983) (0.981) North (0.499) (0.500) (0.500) (0.500) Centre (0.381) (0.380) (0.381) (0.381) South (0.479) (0.472) (0.473) (0.474) Compulsory school or less (0.478) (0.463) (0.467) (0.468) High School (0.497) (0.499) (0.498) (0.498) Higher Education (0.402) (0.410) (0.415) (0.411) Labour market participation (0.480) (0.477) (0.481) (0.480) Employed (0.500) (0.498) (0.499) (0.499) Unemployed (0.345) (0.324) (0.328) (0.330) First job seeker (0.158) (0.156) (0.147) (0.152) Student (0.0704) (0.0624) (0.0834) (0.0750) Housewife (0.482) (0.481) (0.483) (0.482) Observations mean coefficients; sd in parentheses 25

26 Figure 5: Effect of eligibility to childcare services on mothers labour market participation Notes: Each dot represents children born in one week. Dots to the right of the cutoff are children eligible for the specific childcare service. Graphs in the first row show second order polynomial approximations, while graph on the second row show local linear regression approximations with bandwidth of 60 days. Table 3: Effect of eligibility to childcare services on mothers labour market participation Kindergarten Pre-Kindergarten Sezione Primavera (1) (2) (3) (4) (5) (6) (7) (8) (9) 1st order 2nd order Local Linear 1st order 2nd order Local Linear 1st order 2nd order Local Linear polynomial polynomial Regression polynomial polynomial Regression polynomial polynomial Regression ITT *** 0.056* (0.019) (0.028) (0.036) (0.016) (0.029) (0.037) (0.021) (0.029) (0.036) Baseline Observations R Notes: Robust standard errors clustered at region-year level in parentheses. *** p<0.01, ** p<0.05, * p<0.1. ITT is the estimated coefficient for Eligibility. The bandwidth used for non parametric estimation is 60 days. Baseline is the level of the outcome variable at the discontinuity for non eligible individuals. 26

27 Figure 6: Effect of eligibility to childcare services on mothers employment Notes: Each dot represents children born in one week. Dots to the right of the cutoff are children eligible for the specific childcare service. Graphs in the first row show second order polynomial approximations, while graph on the second row show local linear regression approximations with bandwidth of 60 days. Table 4: Effect of eligibility to childcare services on mothers employment Kindergarten Pre-Kindergarten Sezione Primavera (1) (2) (3) (4) (5) (6) (7) (8) (9) 1st order 2nd order Local Linear 1st order 2nd order Local Linear 1st order 2nd order Local Linear polynomial polynomial Regression polynomial polynomial Regression polynomial polynomial Regression ITT * (0.022) (0.030) (0.037) (0.016) (0.030) (0.038) (0.020) (0.030) (0.038) Baseline Observations R Notes: Robust standard errors clustered at region-year level in parentheses. *** p<0.01, ** p<0.05, * p<0.1. ITT is the estimated coefficient for Eligibility. The bandwidth used for non parametric estimation is 60 days. Baseline is the level of the outcome variable at the discontinuity for non eligible individuals. 27

28 Table 5: Effect of eligibility to pre-kindergarten on mothers labour market status by geographical area Participation North Centre South (1) (2) (3) (4) (5) (6) (7) (8) (9) 1st order 2nd order Local Linear 1st order 2nd order Local Linear 1st order 2nd order Local Linear polynomial polynomial Regression polynomial polynomial Regression polynomial polynomial Regression ITT 0.081*** 0.124*** 0.095* (0.021) (0.033) (0.051) (0.038) (0.074) (0.083) (0.031) (0.059) (0.066) Baseline Observations R Employment ITT 0.058** 0.103*** (0.022) (0.036) (0.053) (0.038) (0.079) (0.088) (0.033) (0.061) (0.064) Baseline Observations R Notes: Robust standard errors clustered at region-year level in parentheses. *** p<0.01, ** p<0.05, * p<0.1. ITT is the estimated coefficient for Eligibility. The bandwidth used for non parametric estimation is 60 days. Baseline is the level of the outcome variable at the discontinuity for non eligible individuals. Table 6: Effect of eligibility to pre-kindergarten on mothers labour market status by educational level Participation Compulsory school or less High school Higher education (1) (2) (3) (4) (5) (6) (7) (8) (9) 1st order 2nd order Local Linear 1st order 2nd order Local Linear 1st order 2nd order Local Linear polynomial polynomial Regression polynomial polynomial Regression polynomial polynomial Regression ITT 0.069* 0.103* *** (0.036) (0.057) (0.067) (0.023) (0.040) (0.053) (0.026) (0.046) (0.056) Baseline Observations R Employment ITT * (0.032) (0.054) (0.062) (0.025) (0.040) (0.055) (0.029) (0.049) (0.066) Baseline Observations R Notes: Robust standard errors clustered at region-year level in parentheses. *** p<0.01, ** p<0.05, * p<0.1. ITT is the estimated coefficient for Eligibility. The bandwidth used for non parametric estimation is 60 days. Baseline is the level of the outcome variable at the discontinuity for non eligible individuals. 28

29 Table 7: Effect of eligibility to pre-kindergarten on mothers labour market status by family income Participation Low Family Income High Family Income (1) (2) (3) (4) (5) (6) 1st order 2nd order Local Linear 1st order 2nd order Local Linear polynomial polynomial Regression polynomial polynomial Regression ITT 0.077*** (0.024) (0.041) (0.049) (0.026) (0.044) (0.055) Baseline Observations R Employment ITT (0.026) (0.046) (0.051) (0.025) (0.044) (0.056) Baseline Observations R Notes: Robust standard errors clustered at region-year level in parentheses. *** p<0.01, ** p<0.05, * p<0.1. ITT is the estimated coefficient for Eligibility. The bandwidth used for non parametric estimation is 60 days. Baseline is the level of the outcome variable at the discontinuity for non eligible individuals. 29

30 Figure 7: Discontinuities in baseline covariates Table 8: Discontinuities in baseline covariates (1) (2) (3) (4) (5) (6) (7) (8) (9) Household Compulsory High Higher Age Single Size North Centre South Education School Education or less ITT (0.415) (0.025) (0.077) (0.034) (0.024) (0.035) (0.031) (0.037) (0.031) Baseline Observations Notes: Robust standard errors clustered at region-year level in parentheses. *** p<0.01, ** p<0.05, * p<0.1. ITT is the estimated coefficient for Eligibility. The bandwidth used for non parametric estimation is 60 days. Baseline is the level of the outcome variable at the discontinuity for non eligible individuals. 30

31 Figure 8: Test of manipulation of the running variable Figure 9: Sensitivity to choice of bandwidth 31

32 Figure 10: Difference in Discontinuities estimates. Effect on participation. Notes: Bandwidth used for non parametric estimation is 60 days. Figure 11: Difference in Discontinuities estimates. Effect on employment. Notes: Bandwidth used for non parametric estimation is 60 days. 32