price of high-quality daycare and female...

Scand. J. of Economics 112(3), 570–594, 2010DOI: 10.1111/j.1467-9442.2010.01617.x

Price of High-quality Daycare and FemaleEmployment

Marianne Simonsen∗

Aarhus University, DK-8000 Aarhus C, [email protected]

Abstract

Using local variation between municipalities, I analyze the degree to which the price ofhigh-quality publicly subsidized childcare affects female employment following maternityleave. Importantly, prices are income dependent and thus likely endogenous, yet by exploit-ing information on minimum income compensation during non-employment, I bypass thisproblem. The results show that the price negatively affects employment. A price increaseof €1 per month decreases employment by 0.08%, which corresponds to a price elasticityof −0.17. These effects prevail during the first 12 months after childbirth. I also find thatavailability of childcare increases employment.

Keywords: Quasi-experiment; municipality-level variation; maternity leave

JEL classification: J13; J22; J38

I. Introduction

A well-established result in the literature on the female labor supply isthat costly childcare works as a barrier to employment for women inthe US. Examples are Heckman (1974), Connelly (1992), Ribar (1992),Kimmel (1998), and Powell (2002), who all find negative childcare priceelasticities of employment. In addition, using an IV approach, Gelbach(2002) finds that providing free kindergarten increases the employment ofmothers of five-year-old children. Using waiting lists for childcare subsi-dies, Berger and Black (1992) find that a reduced price increases femaleemployment. Similarly, Averett et al. (1997) find that government sub-sidies for childcare increase female employment. Finally, a recent studyby Baker et al. (2008) considers a large-scale change in the childcaresystem in Quebec, Canada. This policy change implies that all five-year-olds have access to full-time kindergarten and that the out-of-pocket pricefor childcare cannot exceed C$5 per day. Exploiting the before–after,

∗I thank the Danish Social Science Research Council (FREJA grant) for financial support,and appreciate helpful input from Mette Ejrnæs, Nabanita Datta Gupta, Siv Gustafsson,Helena Skyt Nielsen, Inga Persson, Lars Skipper, Jeff Smith, Michael Svarer, two anonymousreferees, and numerous seminar and conference participants. The usual disclaimer applies.

C© The editors of the Scandinavian Journal of Economics 2010. Published by Blackwell Publishing, 9600 Garsington Road,Oxford, OX4 2DQ, UK and 350 Main Street, Malden, MA 02148, USA.

Price of high-quality daycare and female employment 571

Quebec-versus-other-regions variation, the authors find that the effects onthe female labor supply of the transition to a regime with universal, highlysubsidized childcare are clearly positive.

US politicians have recently paid much attention to the possible role ofexpanded childcare subsidies and direct provision of public preschool; seeGelbach (2002). In this light, the Nordic countries make for an interestingcase, because high-quality publicly funded daycare and parental cost sub-sidies are already in place.1 As such, the countries provide a laboratoryin which to investigate the effects of such childcare policies.2 A similarargument for Europe in general is made in Ruhm (1998) regarding parentalleave schemes. Additionally, Gustafsson and Stafford (1992) argue that be-cause quality of childcare in the Nordic countries is more homogeneouscompared to, for example, the US,3 estimates of price responsiveness aremore easily uncovered and not as biased by product heterogeneity.

Despite these observations, results on effects of childcare on the femalelabor supply in general in the Nordic countries are sparse. Using a smallersurvey, Gustafsson and Stafford (1992) find that high-quality public child-care in Sweden encourages labor market activity of women with preschoolchildren. Furthermore, by constructing a measure of rationing, they findthat when spaces are not limited, a lower price encourages use.

In this paper, I analyze the Danish set-up using data from 2001.4 Asopposed to Gustafsson and Stafford (1992), I bypass the problem of en-dogenous childcare prices. Estimations are performed on a rich, Danish,register-based dataset consisting of 10% of the population that includeshigh-quality information on demographics and income for both spouses ona yearly basis. In addition, individual event history in terms of employment,unemployment, retirement, maternal leave, publicly subsidized child-rearingleave, education, and the residual category of non-participation is knownon a monthly basis.

A common problem in the literature is identification of prices of child-care, since these are often not directly observed. In the Danish case, thedaycare prices faced by the parents vary deterministically with income,place of living (municipality), and number of siblings in daycare. Yet theproblem of identifying prices remains; I do not observe labor income and

1 See OECD (2001) for an assessment of the quality of Danish childcare.2 A factor that might affect the results for the US and Nordic countries is the time at whichthe parents return to the labor market after giving birth. My calculations show that 96% ofall mothers take all the leave possible (28 weeks in 2001), whereas working mothers in theUS return much earlier after giving birth.3 Also, Ruhm (2004) points out that the average quality of daycare in the US is extremelylow.4 According to Jaumotte (2003), Denmark has by far the highest level of spending onchildcare within the OECD countries, amounting to 2.7% of GDP in 1999.

C© The editors of the Scandinavian Journal of Economics 2010.

572 M. Simonsen

therefore prices for a non-employed woman in the counterfactual case ofemployment. To overcome this problem, I exploit the fact that familieswith incomes above a certain threshold face prices that are independent ofincome. Using information on minimum compensation levels in the non-employment state, I restrict the sample to consist of women for whomprices are independent of income regardless of employment status. Thisgroup includes 59% of all families, representing a wealthier part of thepopulation. Thus, importantly, the estimated parameters are local in thesense that they only hold true for this smaller part of the population.

I find that the price effect is significantly negative. An increase in theprice of childcare of €1 per month will decrease the female employmentrate by around 0.08%. This effect prevails during the first 12 months afterchildbirth. Furthermore, availability of childcare also seems to affect femaleemployment.

The paper is organized as follows. Section II presents the institutionalsettings, Section III discusses the identification and estimation strategy,Section IV presents the data, and Section V presents the results. Finally,Section VI concludes.

II. Institutional Settings

Daycare in Denmark

Daycare in Denmark (along with other Nordic countries) is characterized byhigh expenditure levels per capita compared to other countries within theEuropean Union, and usage is high. According to the Society of DaycareTeachers (2004), about 75% of all children aged 6–9, 96% of children aged3–5, and 61% of children aged 0–2 attended public daycare in 2002. Here,I consider care for the group of 0–2-year-olds.

For the most part, daycare is publicly provided and organized withinDenmark’s 271 municipalities.5 On average only 3.3% of registered careslots are privately provided6 and thus do not generally receive direct pub-lic funding. However, municipalities may decide to subsidize part of theprice should the parents choose a private alternative. Unfortunately, infor-mation about this is not available for the period under consideration. Theregulations of childcare institutions are described in the Law of Service(Serviceloven). All children are eligible for municipality childcare, includ-ing children born to unemployed parents. The only exception occurs if one

5 The Danish population is approximately 5.3 million in 2001. Hence, on average, eachmunicipality has 20,000 inhabitants. The largest municipality is Copenhagen, with about500,000 inhabitants.6 Of course, this excludes the informal sector: for example, grandparents.



of the parents takes formal, publicly supported maternity or childcare leave,as described below.

Municipalities provide both nursery centers (these may be integrated withkindergartens for 3–5-year-olds) and family daycare for children within thisage group, and the local government is free to decide on the distributionof these two types of care within the municipality. Similarly, opening hoursmay vary across municipalities, but must “cover local need”. In general,opening hours during weekdays are between 6.30am and 5.15pm.

Nursery centers may be owned by the municipality. No matter the ownerstatus, the municipalities are required by law to monitor the institutionsclosely with respect to educational content as well as safety and hygiene.Evaluation of the former amounts to ensuring that the personnel have thenecessary qualifications, and the latter includes accident-prevention meas-ures, playgrounds, transport, sleeping facilities, toys, hygiene, and insuranceschemes.

The bulk of the costs of running nursery centers go to teacher wages. Ina typical nursery center, around 80% of the budget is allocated to wages,10% to rent, heating, and water, while the remaining 10% is operating costs(food, toys, sand, etc.). Teacher wages are centrally negotiated; that is, allteachers earn the same basic wage conditional on experience.7 On top ofthe basic wage comes a regional-specific premium, which is dependent oncosts of living in the area.

In contrast, family daycare takes place in private homes, and the carersare directly employed by the municipality. Again, the municipalities mustapprove the facilities and the qualifications of the carer. There may be upto five children in each home, and in some municipalities the carer’s ownchildren under the age of three are allowed to enter into the total numberof children in the family daycare. The carer will then receive compensationfrom the municipality for taking care of his or her own children. Costs ofrunning family daycare are, not surprisingly, also dominated by wages tocarers. Again, carer wages are centrally negotiated and consist of a basicwage and a regional-specific premium.8

Policies

Table 1 summarizes the most important Danish policies in this area. It isseen that price variation stems from three sources: (1) municipalities, (2)parental income, and (3) the presence of other siblings.

Municipalities can choose to provide guaranteed access to daycare(henceforth GADC), either in nursery centers or in family daycare, forall preschool children older than six months, though the parents cannot

7 Management responsibilities are rewarded with a (centrally negotiated) wage premium.8 Carers may receive a smaller qualification bonus if they have special training.


574 M. Simonsen

Table 1. Relevant family-related policies, Denmark 2001

Municipality-specific Childcare PoliciesGuaranteed Access to

Daycare, GADCGuarantee of access to either family daycare or nursery center within

municipality. Parents cannot choose a specific institution. Valid forchildren of six months or older.

Prices, P Price maximum of 33% of total costs in case of GADC vs. 30%with no GADC. Prices reduced with lower income (see Table 2);50% further price subsidy for additional siblings in public care.

National Leave PoliciesMaternity Leave All mothers have the right to 28 weeks of job-protected leave.

Compensation depends on union status and sector of employmentbut minimum €1,800 per month.

Childcare Leave All mothers have the right to 26 weeks of job-protected leavefollowing maternity leave. Compensation €1,100 per month.

themselves decide on a specific institution. When providing GADC, themunicipality is required by law to pay a minimum of 67% of the totalcosts per child. However, if the municipality chooses not to provide theguarantee, it is required to pay at least 70% of the total costs per childin daycare. If a municipality is unable to honor the guarantee, it mustimmediately switch to the higher-cost subsidy. A significant number ofmunicipalities do not, as a matter of fact, provide GADC. In 2001, thisamounted to 19.3% of all municipalities (affecting 25% of the women inthe estimation sample; see Table 3). Thus, the incentive scheme seems tooweak to secure complete immediate publicly provided daycare for all chil-dren. In case of waiting lists, open slots in childcare are allocated accordingto age and length of time on the waiting list.

Depending on household income, municipalities take on an even largerpart of the financing than the minimum 67%/70%. Table 2 shows furthermunicipality subsidies for a family with one child. The critical incomelevels are increased by €1,000 for each additional sibling under the ageof 18. Moreover, parents only pay the full price of daycare for the child

Table 2. Daycare subsidies beyond minimum subsidy, family with one child

Further subsidyFamily income (2001) (% of total costs per child)

€16,215 or below 30%€16,215 to €16,573 28.5%€16,573 to €50,300 Subsidy reduced by 0.285 percentage points when income is

increased by €337€50,300 or above 0%

Note: Critical income levels increased by €1,000 for each additional sibling under the age of 18.Source: http://www.retsinfo.dk.



Table 3. Moving patterns in estimation sample

Share who moves, 1999–2001 0.072

Share who moves, 2000–2001 0.137

Among 2000–2001 movers:Share that stays within the region 0.488

Among 2000–2001 movers, share that move to municipalities where:Price is higher by 0%–10% 0.245 Price is lower by 0%–10% 0.363Price is higher by 10%–20% 0.111 Price is lower by 10%–20% 0.142Price is higher by 20%–30% 0.033 Price is lower by 20%–30% 0.061Price is higher by more than 30% 0.007 Price is lower by more than 30% 0.025

placed in the most expensive type of public childcare. For other siblings inpublic care, they pay 50% of the price. Thus the effective price of enrollingthe youngest child in care depends on whether older siblings are enrolled.If at least one older sibling is enrolled, the incremental cost of enrollingthe younger sibling is the price (given family income) minus half of theprice of the cheaper type of care. Having older siblings enrolled in caretherefore reduces the level as well as the variance of the effective priceof care for the younger child. The average price of daycare without anyfurther subsidies amounts to €280 per month and varies between €160 and€420. In my estimation sample, 0.9% of the women receive full coveragesix months after giving birth, while 17% receive some further subsidy, and82% receive no further subsidy.

In the period under consideration, mothers had the right to a maximum of28 weeks of job-protected maternity leave, and the vast majority of motherstook full advantage of this; see footnote 2. The degree of compensationwhile on maternity leave varied with sector of employment and unionmembership, but with a legally ensured lower bound on benefits receivedamounting to 100% of unemployment insurance benefits, or approximately€1,800 per month in 2001. In addition to maternity leave, parents had theright to 26 weeks of paid childcare leave before the child’s first birthday.While on childcare leave, parents received 60% of unemployment insurance,or about €1,100 per month in 2001. Some municipalities provided a limitedsupplement to these benefits amounting to a maximum of €400 per month.Unfortunately, only information on whether the supplement is provided, andnot the exact amount, is available.9,10 Thus, potential provision of GADC

9 Including a dummy for leave supplement in the estimations below does not change theconclusions regarding the other parameters of interest in the paper. Results are available onrequest.10 Childcare leave from employment is job-protected. Childcare leave during unemploymentprolongs the period of unemployment insurance benefit entitlement and temporarily delaysworkfare participation.


576 M. Simonsen

coincided with the expiration of formal maternity leave, but mothers ofchildren who were not granted a slot in daycare had the possibility oftaking childcare leave.

III. Identification and Estimation Strategy

In this section, I will discuss the objectives of the econometric analysis andnotation. I then consider the parameters of interest along with the identi-fication and estimation strategy. The aim of the evaluation is to measurethe impact of a given treatment on an outcome variable. Here, the treat-ment is childcare prices, and the outcome of interest is female employmentstatus in the period after giving birth. Let Y ∗ be the underlying utilityof employment net of costs. I follow Connelly (1992), Ribar (1992), andKimmel (1998) with respect to the behavioral model forming the basis forthe empirical analysis. That is, Y ∗ is linear and additively separable:

Y ∗ =β0 + β1 P + γ X + u, (1)

where P is the price to the parents of placing a child in daycare, andthis price P is a function of municipality policy, parental income, numberof older siblings, and whether siblings are placed in public daycare. I donot have information on whether children are actually placed in daycare.Therefore, to construct the price for a child, I assume that parents do notplace the youngest in daycare and at the same time keep older preschoolsiblings at home after birth. This assumption does not seem too strict giventhe share of children in public daycare, as shown earlier.

X is a set of conditioning variables including GADC, regional dummies,labor market experience information, labor market interruption information,woman’s education, husband’s income, and number of siblings in differentage groups. Furthermore, even though operating procedures for publiclyprovided childcare are highly regulated, municipalities do have some dis-cretion. To account for potential quality differences, I therefore conditionon the child–teacher ratio in nursery centers on the municipality level.11 SeeTable 3 for a detailed description of the variables used in the estimations.I do not explicitly include expected wages in the participation equation,since the parameters of interest are related to childcare policies and notwages.12 However, I do include determinants of the wage.13 I assume u to

11 Some of the variables in the conditioning set are potentially endogenous. For example,mother’s leave-taking as well as child–teacher ratios may be problematic. In the sensitivityanalysis below, I re-estimate my models excluding these variables.12 Estimating a Heckman selection model a la Kimmel (1998) does not change the conclu-sions from the analysis presented below. Results are available on request.13 This means, for example, that the estimated parameter from level of experience andeducation includes both a wage effect and a participation effect; see also Tekin (2004).



be a standard normally distributed random variable, and the parameters of(1) can then be estimated using a probit where

Y ={

1 if Y ∗ > 0;

0 otherwise.

Clearly, to avoid selection bias in the estimation of the effects of childcarepolicy, there must be no dependence between the explanatory variables andu. In other words, there must be no unobserved factors that explain bothlabor force participation and policy. Conditioning on X is meant to capturesuch correlation between policy variables and u; the variables in X arenot of interest by themselves. Furthermore, there cannot be any settlementeffects; that is, couples must not move because of lower childcare prices.Is this likely and, if so, is it possible to counterbalance such effects?First, note that according to Norstrand and Andersen (2002), Danes mainlysettle in connection with their choice of educational institution. After thisinitial settlement, they rarely move between municipalities and hardly everbetween regions; see Dilling-Hansen and Smith (1996). Table 3 shows thatapproximately 7% of the women in my sample move between 2000 and2001, and 14% move between 1999 and 2001. Of the women who movebetween 2000 and 2001, 49% stay within the region (see Table 5 fordefinitions of regions), suggesting strong geographical ties. Furthermore,moves are most often associated with smaller changes in childcare prices:61% move to a municipality where the 2001 price lies within 10% ofthe 2001 price of the old municipality, and 86% move to a municipalitywhere the price lies within a 20% bandwidth. Second, there is municipality-specific variation in prices over time. A couple therefore cannot be surethat a municipality will not change its policy. Table 4 documents this.

Third, it is unlikely that the childcare price is the main driver for set-tlement when compared to job opportunities and prices of real property.A back-of-the-envelope calculation shows that the gain from a 20% price

Table 4. Price variation in municipalities, 1997–2003

Share of muncipalities withAverage price (€)

(municipality Average Higher than Higher thanYear level) growth average price average growth

1997 206 · for 7 years 0.163 ·1998 215 0.041 for 6 years 0.059 0.0041999 224 0.045 for 5 years 0.089 0.0522000 235 0.048 for 4 years 0.056 0.2302001 253 0.079 for 3 years 0.107 0.3112002 269 0.062 for 2 years 0.083 0.2742003 283 0.053 for 1 year 0.130 0.111

in 0 years 0.300 0.018


578 M. Simonsen

Table 5. Detailed description of variables

Variable Description Source

Employment, month5–15

Employed in month 5–15 followingchildbirth. Includes part-timeemployment, excludes self-employment,Jan.–Dec. 2001

Statistics Denmark

GADC Whether a municipality expects to provideguaranteed access to daycare in 2001

Ministry of the Interior

P Monthly family-specific € price of familydaycare in municipality, 2001


Child–teacher ratio Child–teacher ratio in nursery centers, 2001 Ministry of the InteriorHusband’s income Yearly € income of husband in 2000 Statistics DenmarkOwn income Yearly € income in 2000 Statistics DenmarkLabor market

experienceActual years of experience prior to birth Statistics Denmark

Region 1 Residing in county of Copenhagen, 2001 Statistics DenmarkRegion 2 Residing in counties of Frederiksborg and

Roskilde, 2001Statistics Denmark

Region 3 Residing in counties of Western Sealandand Storstroem, 2001

Statistics Denmark

Region 4 Residing in county of Funen, 2001 Statistics DenmarkRegion 5 Residing in counties of Southern Jutland

and Ribe, 2001Statistics Denmark

Region 6 Residing in counties of Vejle andRingkoebing, 2001

Statistics Denmark

Region 7 Residing in counties of Aarhus and Viborg,2001

Statistics Denmark

Region 8 Residing in county of Northern Jutland,2001

Statistics Denmark

High school 10–12 years of education Statistics DenmarkShort further education 13–14 years of education Statistics DenmarkMedium further

education15–16 years of education Statistics Denmark

Long further education More than 16 years of education Statistics DenmarkLong-term unemployed Unemployed more than 26 weeks in year

prior to giving birthStatistics Denmark

Medium-termunemployed

Unemployed 13–25 weeks in year prior togiving birth

Statistics Denmark

Long-term leave On publicly funded leave more than 26weeks in year prior to giving birth

Statistics Denmark

Medium-term leave On publicly funded leave 13–25 weeks inyear prior to giving birth

Statistics Denmark

No. of siblings,0–2 years

No. of siblings age 0–2 years prior to birth Statistics Denmark

No. of siblings,3–6 years


No. of siblings7–9 years



No. of siblings age 10–14 years prior tobirth

Statistics Denmark


No. of siblings age 15–17 years prior tobirth

Statistics Denmark

Unemployment rate Share of unemployed among women inmunicipality, 16–49 years, 2001


Continued



Table 5. (Continued)

Variable Description Source

Single-parent children Share of single-parent children 0–17 yearsold in municipality, 2001


Asylum seekers No. of asylum seekers per 10,000inhabitants in municipality, 2001


Third-world immigrants No. of third-world immigrants per 10,000inhabitants in municipality, 2001


Social Democrats Largest party in 1997 municipality electionis Social Democrats

Statistics Denmark

Conservatives Largest party in 1997 municipality electionis Conservatives

Statistics Denmark

Liberals Largest party in 1997 municipality electionis Liberals

Statistics Denmark

Child families Share of families with children among allhouseholds in municipality

Statistics Denmark

decrease in the average price for a family with two children in public carefor five years is just below the broker costs of selling an average housein Denmark (the actual costs of moving are more than simply the brokercosts).14 I realize, though, that childcare policy is likely to be correlatedwith other municipality-specific characteristics. These may affect, on theone hand, the woman’s (or couple’s) decision about where to live and, on theother hand, the municipality’s capability of providing services in general.Short of perfect measures for this, the conditioning set is augmented withmunicipality characteristics (as in Gustafsson and Stafford, 1992), includingthe level of female unemployment rates for the age group under consider-ation, the share of single parents, the share of third-world immigrants, aswell as the share of asylum seekers. Finally, to account for voter prefer-ences for family-friendly policies, I condition on the outcome of the mostrecent municipality election (largest party being Social Democrats, Con-servatives, or Liberals) as well as the share of families with children outof all households in the municipality. A similar issue is whether the mostcareer-oriented families use their voice to affect childcare prices. One wayto address this is to estimate conditional correlations between family typesand prices. A negative correlation between measures of career-mindednessand prices may be indicative of such a problem. In particular, I run a simpleregression of log prices (municipality level) on the full set of explanatoryvariables in my main analysis below. This regression suggests that nei-ther level of education nor labor market experience correlate with prices.

14 Here I assume no discounting, and house prices are set equal to the tax authorities’evaluation, which systematically lies below sales prices; see http://www.skat.dk. The averageprice in 2001 was about €190,000. Broker costs are assumed to be 4% of the sales price.This corresponds to the average in Denmark; see http://www.familieadvokaten.dk


580 M. Simonsen

The only exceptions are registered for individuals with more than 16 yearsof education (compared to less than 12 years), which is associated witha slightly higher price (2.4%) and husband’s income, which is associatedwith a 0.02% higher price for every additional €1,000 income. Importantpredictors of prices are the child–teacher ratio (+), largest political party,and the share of families with children in the municipality (−).

A separate issue is that having older siblings reduces the effective priceof childcare for the youngest child. The problem is that fertility is unlikelyto be exogenous in this setting. For example, daycare arrangements maydirectly affect the number of children in a family. The optimal solutionwould be to have an instrument available. Since such a variable is not onhand, I pursue two other solutions. First, in my estimations, I condition onthe number of older siblings in each of five different categories (a descrip-tion of variables follows). This effectively steals all the price variation dueto family composition such that the estimated price effects are only drivenby price variation across municipalities. Second, I perform a sensitivityanalysis, dividing my sample into families with only one child and familieswith more than one child to investigate whether the results are driven bydifferences in intra-family fertility.

Unfortunately, it is impossible to identify P for all women in both coun-terfactual states, since (family) income depends on the employment de-cision. One strategy would be to perform a Heckman-type estimation topredict labor market income and thus P. This would, however, require anexclusion restriction in the employment equation to avoid strong relianceon functional form assumptions. Such a variable is not at my disposal;therefore, I rely on an alternative strategy. I limit the sample to a group ofwomen for whom P is independent of income by excluding those whosecompensation does not exceed the upper limit in Table 1 (€50,300 cor-rected for number of siblings), both when employed and not employed.This requires information about the woman’s compensation in both states,while the husband’s income, H INC, is taken as given. Unemployed in-dividuals receive unemployment insurance benefits, UI , or approximately€21,800 per year in 2001. All the individuals in my sample will be eli-gible for UI benefits after the expiration of childcare leave. As describedearlier, compensation during childcare leave amounts to 60% of UI ,15 orapproximately €13,100 per year in 2001. I assume that compensation inthe state of employment always exceeds this lower bound. Therefore, thesmallest level of compensation during non-employment is 60% of UI , andfamily income, F INC, will at least equal minimum income, MIN INC, forall mothers during both employment and non-employment:

MIN INC ≡ H INC + 0.6 · UI � F INC.

15 See earlier discussion of childcare leave during unemployment.



For the subsample of individuals with MIN INC (and therefore family in-come) always above the appropriate upper limit, P is independent of in-come. In principle, more individuals belong to this group (82% of allmothers six months after childbirth). For example, some women can beobserved in non-employment with a family income higher than the up-per limit. Assuming that income in employment always exceeds incomein non-employment, these women could be included. The problem, how-ever, is that I do not observe income in non-employment for employedwomen. Such an inclusion will therefore treat non-employed and employedwomen asymmetrically, whereas imposing a common minimum incomeduring non-employment will not. Obviously, the selection procedure meansthat the estimated parameters only hold true for this group consisting ofapproximately 60% of mothers following childbirth.

I estimate female employment propensities on a monthly basis from fivemonths after childbirth. Month five is included as a (weak) consistencycheck. Since daycare is not provided in any municipality before month six,a significant effect will indicate a misspecification of the model and/or thatthe analysis has excluded factors that simultaneously explain a municipal-ity’s choice of policies in general and female employment.

IV. The Data

I employ register-based data maintained by Statistics Denmark along withmunicipality information supplied by the Ministry of the Interior from2001. The register dataset contains information on a representative sampleof 10% of all Danish individuals in the age bracket 15–74. Informationstems from several registers maintained by Statistics Denmark. The regis-ters include yearly information on income and demographics. Furthermore,the individual event history in terms of periods of employment, unemploy-ment, retirement, maternal leave, publicly subsidized leave (childrearingor sabbatical), education, and the residual category of non-participation isknown on a monthly basis. A woman is coded as employed only if she isworking. Importantly, a child register provides exact information about thedate on which women in the sample give birth. This information allows foridentification of the labor market status of a woman in each month aftergiving birth.

The information from the Ministry of the Interior includes the femaleunemployment rates, the share of single parents, the share of third-worldimmigrants, the share of asylum seekers, the municipality-specific pricesof childcare, and whether the municipality expects to be able to provideGADC. This last piece of information is reported to the Ministry of theInterior as part of the municipality budget requirements.


582 M. Simonsen

Table 5 gives a detailed description as well as the timing of measurementand the source of the variables used in the estimations. Self-employedindividuals, women with no labor market insurance, women with earlyretirement, and women enrolled in the educational system are excludedfrom the analysis in order to secure a homogeneous estimation samplerepresenting women for whom the choice of being employed is real. Thisexcludes 10% of the full sample.

To estimate the effect of childcare policies on the female labor supplyfive months after giving birth, I choose as my outcome variable the labormarket status in January 2001 for women giving birth in July 2000, thelabor market status in February 2001 for women giving birth in August2000, and so forth. To estimate the effect of childcare policies six monthsafter giving birth, I use labor market status in January 2001 for womengiving birth in June 2000, labor market status in February 2001 for womengiving birth in August 2000, etc. The estimation samples used to evaluatethe decisions 7–15 months after childbirth are constructed analogously.Note that the monthly samples only partly overlap. As will become clear,it is possible to establish a distinct pattern of the effects of the policieswithin the first 15 months after childbirth. Effectively, considering only thisage range also excludes the possibility of younger siblings, which wouldgreatly complicate not only the modeling of mothers’ choices but also howto determine the price of childcare.16 Therefore, I limit the analysis to cover

16 The limited available information on childcare policies restricts me from meaningfully es-timating a discrete time duration model. Assume that I were to construct a flow sample to beused for duration analysis. The starting point (in real time) would be January 2001. Here, toconsider the decision to return five months after childbirth, I could include children born inJuly 2000 and subsequently include mothers of children that flow into the sample (those withchildren born from August 2000 through June 2001). Therefore, the sample used to considerthe decision to return to the labor market after five months would be the same in the twotypes of models (contributions from 12 calendar months in total). To consider the decisionto return to the labor market six months after giving birth in the duration model set-up, how-ever, I could only use children born from July 2000 through May 2001 (contributions from11 calendar months) as opposed to the larger sample used in the paper. Including mothers ofchildren born in June 2000 as well (or equivalently, to change the real-time starting point toDecember 2000) is not possible because the children would be six months old in December2000, for which I do not have the necessary childcare policy information. To consider thedecision to return to the labor market 15 months after childbirth, I would only be able toexploit information for mothers of children born in July and August 2000. In addition, inthe discrete time duration model, only the at-risk population is used for identification. Thusthe effective sample used to estimate the decision to return after 15 months would be evensmaller. Moreover, apart from only using the at-risk population, a discrete time durationmodel where one allows the coefficient estimates of the explanatory variables to vary everymonth is actually very similar to the approach taken in the paper as it stands. Finally, Figure 2shows that women enter employment relatively quickly after the expiration of formal mater-nity leave, indicating little risk of duration dependence. See also Lechner (2000) and Larsson(2003) for examples of papers evaluating period-specific effects.



Table 6. Comparison, excluded and included groups, six months after childbirth

Excluded group Included group

Average Std. dev. Average Std. dev.

GADC 0.77 0.42 0.77 0.42Age 30.06 4.77 31.43 4.12No. of siblings 0–2 years 0.13 0.34 0.13 0.34No. of siblings 3–6 years 0.39 0.58 0.47 0.58No. of siblings 7–9 years 0.14 0.37 0.13 0.37No. of siblings 10–14 years 0.10 0.35 0.07 0.30No. of siblings 15–17 years 0.02 0.14 0.01 0.12Own income (€) 25,528 9,691 29,932 12,129Husband’s income (€) 24,355 12,649 58,451 32,776Childcare price, P—family-specific (€) 169 87 209 75Childcare price—municipality level (€) 287 27 282 29Child–teacher ratio 3.56 0.36 3.56 0.37High school 0.15 0.36 0.11 0.32Short further education 0.35 0.48 0.42 0.49Medium further education 0.18 0.38 0.32 0.42Long further education 0.06 0.23 0.12 0.32Long-term unemployed 0.02 0.13 0.02 0.13Medium-term unemployed 0.05 0.21 0.04 0.20Long-term leave 0.02 0.13 0.01 0.12Medium-term leave 0.51 0.50 0.59 0.49Single-parent children 0.15 0.05 0.14 0.04Asylum seekers (per 10,000) 21 76 19 69Third-world immigrants (per 10,000) 354 239 326 217Unemployment rate 6.12 1.86 5.76 1.77Social Democrats 0.67 0.47 0.58 0.49Conservatives 0.06 0.24 0.10 0.30Child families 0.23 0.05 0.23 0.04

Observations 2,037 2,883Share of all 0.41 0.59

Note: Bold indicates a significant difference between the two groups at the 5% level.

this period. I have about 5,000 observations for each month. As explainedin Section III, in order to identify P when a woman is employed and alsoin the counterfactual case, I am forced to consider only women for whomP is independent of income. This step also excludes single women (i.e.,women who are neither cohabiting nor married) since 60% of UI obviouslydoes not exceed the appropriate upper limit in Table 2. The final sampleconsists of 3,000 observations for each month.

Table 6 compares the characteristics of the excluded and included groupsof women six months after childbirth. Note that the price variation is stillconsiderable within the included group.17 Clearly, the included group of

17 The mean family-specific price in included families with only one child is €283, andthe standard deviation is €30. The corresponding figures in included families with more


584 M. Simonsen

0

0.2

0.4

0.6

0.8

5 6 7 8 9 10 11 12 13 14 15

Months after childbirth

Employment propensity

Fig. 1. Employment propensity after childbirth, estimation sample, 2001

women has different characteristics compared to the excluded group. Inparticular, husbands’ income is higher among the included women due tothe selection criteria. In addition, the group of included women comprisesindividuals who are older, have slightly more children, have higher educa-tion, have higher income, are more likely to have been on leave, and live inmunicipalities with lower social costs (single-parent children, asylum seek-ers, and third-world immigrants) and unemployment rates. In this sense,the 41% of women excluded from the analysis have less favorable socio-economic characteristics than those included. Therefore, their reactions tochanges in policies may potentially differ from those of the included pop-ulation. With the available data, however, this cannot be investigated.

Figure 1 depicts female employment 5–15 months after giving birth forthe included group. We see that only 4% of women are employed fivemonths after giving birth.18 Hereafter, we observe a gradual increase inthe female employment propensity. After 14 months, the profile levels outat 71%. This corresponds to the average propensity for Danish women.Table 7 gives information on regional variations in childcare policies.

V. Estimation Results

This section presents selected results from the analysis discussed inSection III. The full set of estimation results conditioning on the set ofvariables described in Table 5 is shown in Tables A1–A4. The price ofchildcare seems to be very important for the female employment propensity

than one child are €158 and €49. Clearly, part of the total variation in prices stems fromdifferences in intra-family fertility, yet there is still substantial variation in the price afterconditioning on the number of children.18 During the first four months after childbirth, the share of women participating in the labormarket is even smaller.



Table 7. Regional variation in childcare policies

Average family- Min. family- Max. family-Share of Share with specific price, specific price, specific price,

Region population GADC P (€) P (€) P (€)

1 0.23 0.43 190 0 3562 0.12 0.58 198 0 4143 0.09 0.69 169 0 2994 0.09 0.95 160 0 3025 0.09 0.99 173 0 3256 0.12 0.88 182 0 3217 0.17 0.92 178 0 2998 0.18 1.00 182 0 316

Note: For definition of regions, see Table 3.

in the short term. Figure 2 shows the marginal effects (evaluated at thesample mean) of increasing monthly family-specific prices by €1. Themarginal effects of a price increase on the female labor supply are sig-nificantly negative and vary between −0.0006 and −0.0012 8–12 monthsafter childbirth. This should be seen in a context where the standard de-viation in observed prices is €75 and the average employment rate inthe period increases from 0.36 eight months after childbirth to 0.58 12months after childbirth. The marginal effects correspond to average cross-price elasticities (the percentage change in the propensity for women to beemployed as per a percentage change in the price of childcare) between−0.13 and −0.25. Interestingly, there is a negative effect of increases inprices during the months where women have the possibility of taking child-rearing leave. This option makes it much less costly to temporarily opt outof employment because leave is job-protected. At the child’s first birthday,the only alternatives to employment are non-participation and (voluntary)unemployment. Hence, it makes perfect sense that women are less price-responsive from 13 months after childbirth onwards.

The (short-term) cross-price elasticities for Danish cohabiting mothersturn out to be in the lower end compared with cross-price elasticities foundin the literature for the US. Yet the estimates remain close. Given thecross-country differences in childcare regimes and compensation schemesduring parental leave, some disparity is expected. Among papers compara-ble in terms of the underlying model, Connelly (1992) finds a cross-priceelasticity of −0.20 (a replication by Kimmel, 1998, including a richer setof conditioning variables results in an elasticity of −0.42), Ribar (1992)finds an elasticity of −0.74, and the results from Kimmel (1998) indicatea cross-price elasticity of −0.92 for married mothers. The other Nordicresults differ to some extent from the findings of this paper. Gustafssonand Stafford (1992) consider families with precisely one child and find an


586 M. Simonsen

–0.0020

–0.0015

–0.0010

–0.0005

0.0000

0.0005

5 6 7 8 9 10 11 12 13 14 15


Marginal effects

Fig. 2. Marginal effects on female employment propensity of childcare prices after child-birthNote: With 95% confidence bounds (based on normal approximation).

elasticity of −0.06 for all individuals and −1.88 for those not subject torationing.19

Sensitivity Analysis

Extensive sensitivity analysis has been performed to check the validity ofthe results. I find that the parameters of interest are extremely robust tothe choice of specification. However, the precision of the estimates is af-fected when considering smaller subsamples; see Table A5 for the results.First, I investigate whether the estimated parameters vary across familieswith different numbers of children (see previous discussion). Specifically,I re-estimate my model using only one-child families and families withmore than one child. Also, because the price sensitivity may be differentin municipalities with and without GADC, the model is re-estimated forGADC and non-GADC municipalities. Further, one might hypothesize thatlabor markets in larger cities are different from those of the provinces,and that this may affect childcare policies as well. To address this point, Ire-estimate the model, first excluding the municipality of Copenhagen (theDanish capital and largest city, with 500,000 inhabitants), and next exclud-ing both Copenhagen and Aarhus (the second-largest city, with 280,000 in-habitants).20 Finally, I exclude potential endogenous variables from my con-ditioning set. In particular, I drop (a) lagged endogenous variables, such asinterruption information (unemployment and leave-taking), (b) interruption

19 In the following section, I re-estimate my model using only one-child families. The resultsare not sensitive to this.20 This is more flexible than just including a dummy for living in a large city.



information as well as labor market experience, (c) child–teacher ratios,and (d) all municipality-level information (including child–teacher ratios).None of the above sensitivity checks affect the main conclusions of theanalysis, and none of the estimated marginal effects of price increases arestatistically significantly different from the results presented above.21

Effects of GADC

This subsection investigates whether availability of childcare leads womento return to the labor market earlier after giving birth; see also Gustafssonand Stafford (1992). In particular, I analyze the effects of providing GADC.The effect of living in a municipality providing GADC should be interpretedas the effect of having daycare available when the mother wants to returnto the labor market compared to a situation where daycare is possibly notavailable until a later (undefined) point in time.22 Clearly, the effects of thepolicy depend on the length of the waiting lists in municipalities that donot provide the guarantee. See Simonsen (2005) for descriptive evidenceon the samples of women living in the two types of municipalities.

Figure 3 shows the distribution of prices in the two types of municipal-ities. We see that the distribution of prices in municipalities that do notprovide GADC has fatter tails. More municipalities within this categoryhave both very low and very high prices. Therefore, although municipal-ities with GADC have significantly lower prices of daycare, there is nosystematic relationship between the provision of unrestricted access to day-care and price structure. It should thus be possible to identify both an effectof GADC and a price effect.

Figure 4 depicts the marginal effects (evaluated at the sample mean)on the female employment propensity of providing GADC 5–15 monthsafter childbirth. We see that the provision of GADC has a positive andsignificant effect on the female employment propensity 8–13 months afterchildbirth. The effect is relatively large. During this period, women inGADC municipalities have around a 6% higher employment propensity.Unrestricted access to daycare therefore seems to enable women to returnto employment after childbirth.

21 It may be surprising that the price sensitivity does not vary between GADC and non-GADCmunicipalities. A possible explanation is that the effect of GADC is still relatively small,compared to the share employed in each month (e.g., 6.1 percentage points in month ninecompared to an average employment propensity of 0.4), and any differences in price sensi-tivity must be driven by women affected by GADC.22 The same is true, for example, for most studies attempting to evaluate the effects oflabor market training: individuals do not participate in training in a given period but mayparticipate at a later (undefined) point in time.


588 M. Simonsen

Fig. 3. Distribution of monthly prices of daycare (€) in municipalities with and withoutguaranteed access to daycare

–0.05

0.00

0.05

0.10

0.15

5 6 7 8 9 10 11 12 13 14 15


Marginal effects

Fig. 4. Marginal effects on female employment propensity of providing guaranteed accessto daycare after childbirthNote: With 95% confidence bounds (based on normal approximation).

Note that there is no statistically or economically significant effect ofthe policy before month six. Similarly, the effect of GADC dies out overtime. If the effects of GADC did not die out with time, it could eitherbe because of very long waiting lists in non-GADC municipalities, orbecause women who reside in municipalities that provide GADC haveunobserved characteristics that increase their employment propensity in alltime periods.



VI. Discussion

This paper presents empirical evidence on the effects of increases in themarginal childcare price following expiration of formal maternity leave sixmonths after childbirth. The sample consists of women living in couples. Ianalyze the case of Denmark, where the quality of public daycare is con-sidered high in an international comparison. I exploit price variation acrossmunicipalities. To overcome the problem of identifying childcare prices fornon-employed women, I exploit the fact that families with incomes above acertain threshold face prices that are independent of income. The downsideof this approach is that the estimated parameters only hold true for thewealthier part of the population.

The results show that the price effect is significantly negative. An in-crease in the price of childcare of €1 per month will decrease femaleemployment by around 0.08%, corresponding to a cross-price elasticityof −0.17. This effect prevails during the first 12 months after childbirth.That is, using data from a regime like the Danish with highly subsidizedpublic childcare, to uncover effects of childcare on female employment re-veals a considerable price sensitivity. Also, the size of the effects, thoughshort-lived, is in the lower end, but still comparable to effects found inother papers for other countries. Also, availability of childcare seems to beimportant for women’s return to the labor market.

An important policy question is, of course, whether public provisionof high-quality highly subsidized childcare “pays off” in the sense that itimproves welfare. Clearly, the analysis in this paper is not sufficient toanswer this ambitious question, but it does, nonetheless, provide importantinput for a future cost–benefit analysis.

Appendix A

Table A1. Marginal effects and asymptotic standard errors from employmentprobit, 5, 6, and 7 months after childbirth

5 months 6 months 7 months

Marg. Std. Marg. Std. Marg. Std.Variable effect error effect error effect error

GADC 0.003 0.009 0.011 0.020 0.018 0.023P (€10) 0.001 0.001 −0.002 0.002 −0.006 0.003Child–teacher ratio −0.020 0.006 −0.033 0.015 −0.034 0.018Experience (1,000 years) −0.005 0.003 0.014 0.006 0.026 0.007Experience (10,000 years) squared 0.029 0.014 −0.039 0.034 −0.066 0.039Medium-term unemployed −0.007 0.017 −0.179 0.029 −0.147 0.069Long-term unemployed · · −0.054 0.038 0.020 0.049Medium-term leave 0.016 0.036 −0.122 0.039 −0.272 0.032Long-term leave 0.001 0.008 0.048 0.017 0.086 0.019

Continued


590 M. Simonsen

Table A1. (Continued)



Husband’s income (€100,000) 0.004 0.009 0.007 0.022 −0.071 0.033High school 0.023 0.020 0.037 0.035 0.032 0.038Short further education 0.005 0.013 0.024 0.027 −0.006 0.031Medium further education 0.015 0.016 0.030 0.030 −0.002 0.033Long further education 0.038 0.022 0.049 0.036 0.059 0.040No. of siblings 0–2 years 0.007 0.015 −0.065 0.033 −0.047 0.040No. of siblings 3–6 years −0.010 0.014 −0.008 0.027 −0.095 0.033No. of siblings 7–9 years 0.006 0.009 −0.010 0.020 −0.041 0.023No. of siblings 10–14 years 0.005 0.011 0.024 0.025 −0.023 0.030No. of siblings 15–17 years 0.007 0.037 −0.020 0.072 0.086 0.095Unemployment rate −0.001 0.003 0.006 0.007 0.001 0.008Single-parent children 0.003 0.002 −0.003 0.004 −0.003 0.005Asylum seekers (per 1,000,000) −0.005 0.007 0.013 0.011 0.015 0.013Third-world immigrants (per 1,000,000) 0.002 0.003 0.005 0.007 −0.002 0.008Social Democrats 0.003 0.009 0.007 0.020 0.003 0.024Conservatives −0.014 0.010 −0.032 0.029 0.019 0.036Child families −0.055 0.152 −0.154 0.309 0.348 0.357

No. of observations 2,835 2,931 2,937Employment propensity 0.044 0.212 0.326Pseudo-R2 0.038 0.028 0.044

Notes: Regional dummies are included; bold coefficients are significant at the 5% level; Huber–White robuststandard errors. Results robust to clustering at the municipality level.




GADC 0.047 0.023 0.061 0.024 0.058 0.025P (€10) −0.006 0.003 −0.008 0.003 −0.010 0.003Child–teacher ratio −0.023 0.018 −0.007 0.019 −0.021 0.019Experience (1,000 years) 0.020 0.007 0.031 0.007 0.036 0.008Experience (10,000 years) squared −0.040 0.040 −0.089 0.040 −0.106 0.042Medium-term unemployed −0.191 0.069 −0.157 0.083 −0.204 0.083Long-term unemployed −0.016 0.049 −0.103 0.038 −0.134 0.053Medium-term leave −0.304 0.028 −0.344 0.033 −0.399 0.033Long-term leave 0.079 0.020 0.094 0.020 0.115 0.021Husband’s income (€100,000) −0.128 0.036 −0.110 0.036 −0.083 0.038High school 0.029 0.038 0.049 0.040 0.020 0.040Short further education −0.003 0.031 0.029 0.033 0.034 0.034Medium further education −0.011 0.033 0.016 0.035 0.025 0.036Long further education 0.067 0.041 0.134 0.042 0.185 0.041No. of siblings 0–2 years −0.075 0.043 −0.118 0.047 −0.125 0.051No. of siblings 3–6 years −0.109 0.034 −0.135 0.036 −0.169 0.038No. of siblings 7–9 years −0.051 0.023 −0.065 0.024 −0.078 0.025

ContinuedC© The editors of the Scandinavian Journal of Economics 2010.





No. of siblings 10–14 years −0.046 0.031 −0.073 0.032 −0.094 0.033No. of siblings 15–17 years 0.068 0.092 0.072 0.091 0.016 0.091Unemployment rate −0.002 0.008 −0.002 0.009 0.003 0.009Single-parent children −0.003 0.005 0.003 0.006 0.000 0.006Asylum seekers (per 1,000,000) 0.009 0.013 −0.006 0.015 0.011 0.015Third-world immigrants (per 1,000,000) −0.005 0.009 −0.015 0.009 −0.005 0.009Social Democrats 0.002 0.024 −0.015 0.025 −0.021 0.026Conservatives −0.007 0.036 −0.029 0.037 −0.016 0.038Child families 0.515 0.365 1.179 0.395 0.883 0.403






GADC 0.061 0.025 0.052 0.026 0.079 0.026P (€10) −0.011 0.003 −0.008 0.003 −0.007 0.003Child–teacher ratio −0.031 0.020 −0.028 0.020 −0.003 0.020Experience (1,000 years) 0.039 0.008 0.046 0.008 0.061 0.008Experience (10,000 years) squared −0.108 0.043 −0.123 0.042 −0.174 0.042Medium-term unemployed −0.243 0.086 −0.224 0.091 −0.249 0.094Long-term unemployed −0.167 0.055 −0.170 0.057 −0.167 0.057Medium-term leave −0.390 0.048 −0.427 0.053 −0.396 0.066Long-term leave 0.127 0.021 0.133 0.021 0.109 0.021Husband’s income (€100,000) −0.098 0.039 −0.110 0.038 −0.124 0.037High school 0.025 0.040 0.023 0.039 0.021 0.038Short further education 0.048 0.034 0.044 0.034 0.049 0.033Medium further education 0.065 0.036 0.084 0.034 0.108 0.033Long further education 0.211 0.039 0.198 0.036 0.222 0.031No. of siblings 0–2 years −0.207 0.056 −0.204 0.057 −0.229 0.060No. of siblings 3–6 years −0.191 0.039 −0.165 0.039 −0.162 0.038No. of siblings 7–9 years −0.096 0.025 −0.101 0.025 −0.115 0.024No. of siblings 10–14 years −0.104 0.033 −0.124 0.032 −0.131 0.031No. of siblings 15–17 years −0.024 0.082 0.010 0.075 −0.017 0.072Unemployment rate −0.003 0.009 −0.014 0.010 −0.010 0.009Single-parent children −0.002 0.006 −0.005 0.006 −0.007 0.006Asylum seekers (per 1,000,000) 0.026 0.016 0.020 0.016 0.017 0.018Third-world immigrants (per 1,000,000) 0.002 0.009 0.009 0.009 0.008 0.009Social Democrats −0.019 0.027 −0.020 0.027 −0.006 0.027

Continued


592 M. Simonsen




Conservatives −0.036 0.038 −0.005 0.038 0.018 0.038Child families 0.522 0.395 0.462 0.401 0.315 0.386



Table A4. Marginal effects and asymptotic standard errors from employmentprobit, 14 and 15 months after childbirth

14 months 15 months

Marg. Std. Marg. Std.Variable effect error effect error

GADC 0.027 0.025 0.037 0.026P (€10) −0.006 0.003 −0.003 0.003Child–teacher ratio −0.008 0.019 −0.015 0.018Experience (1,000 years) 0.062 0.007 0.063 0.007Experience (10,000 years) squared −0.162 0.040 −0.179 0.041Medium-term unemployed −0.302 0.094 −0.198 0.092Long-term unemployed −0.179 0.058 −0.142 0.059Medium-term leave −0.523 0.061 −0.534 0.060Long-term leave 0.134 0.020 0.124 0.019Husband’s income (€100,000) −0.157 0.036 −0.140 0.036High school 0.023 0.037 −0.007 0.036Short further education 0.024 0.031 0.048 0.030Medium further education 0.119 0.030 0.157 0.027Long further education 0.201 0.027 0.229 0.023No. of siblings 0–2 years −0.244 0.061 −0.227 0.064No. of siblings 3–6 years −0.122 0.038 −0.104 0.038No. of siblings 7–9 years −0.108 0.023 −0.092 0.022No. of siblings 10–14 years −0.100 0.028 −0.082 0.028No. of siblings 15–17 years 0.040 0.062 0.025 0.060Unemployment rate −0.009 0.009 −0.010 0.009Single-parent children −0.003 0.005 −0.001 0.005Asylum seekers (per 1,000,000) 0.015 0.016 0.026 0.018Third-world immigrants (per 1,000,000) 0.002 0.009 0.002 0.009Social Democrats 0.017 0.026 0.014 0.026Conservatives 0.007 0.037 −0.027 0.039Child families −0.069 0.371 −0.017 0.377

No. of observations 2,899 2,868Employment propensity 0.669 0.676Pseudo-R2 0.166 0.166



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594 M. Simonsen

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First version submitted June 2007;final version received February 2010.


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