The mixed preschool market: Explaining local variation in family demand and organized supply

Pergamon

Economics of Education Review, Vol. 15, No. 2, pp. 149-161, 1996 Copyright © 1996 ElsevierScienceLtd Printed in Great Britain.All fights reserved 0272-7757/96 $15.00+0.00 0272-7757(95)00033-X

The Mixed Preschool Market: Explaining Local Variation in Family Demand and Organized Supply JOHN H.Y. EDWARDS,* BRUCE FULLERt and XIAOYAN

LIANOt

*Tulane University, Department of Economics, 206 Tilton Hall, New Orleans, LA 70118-5698, U.S.A. tHarvard University, Graduate School of Education, Cambridge, MA 02138-3704, U.S.A.

Abstract--Prior research reveals wide variation in the number of independent preschools and child-care centers. Some analysts have alluded to supply "shortages", while others attribute "uneven" center distribution to economic and demographically induced variations in demand. Combining a 100-county sample of preschools with 1990 census data, we address this classic identification issue by simultaneously estimating supply and demand. Price shows predictably negative effects on hours demanded. More are purchased in poorer counties with proportionately more black single-parents and rapid population growth. Supply responds to price. Also, hours supplied are greater in counties with more developed public sectors and where richer input mixes are used. Parents accept center accreditation as a quality indicator: it significantly increases demand. In contrast, regulations requiring accreditation depress supply. Finally, our results indicate that public provision crowds-out the number of private hours used, mainly through a weakly negative but significant impact on demand. [JEL I21] Copyright © 1996 Elsevier Science Ltd

I. ~ T R O D U C T I O N GROWTH IN PRESCHOOLSand child-care centers, paralleling the steep rise in mothers' workforce participation, has been phenomenal in recent decades. In 1950, just 14% of mothers with children under the age of six participated in the labor force; by 1990, this proportion had climbed to 58%. Among families with working mothers, 62% relied on spouses or kin members to care for their preschool-age children in 1965; this proportion fell to 47% by 1990. Resulting growth in formal preschools and centers has been equally remarkable, rising from 13,600 licensed organizations in the 1960s to over 80,000 in 1990 (Hofferth, 1989; Wilier et al., 1991). The federal government now provides over $7 billion in annual child-care subsidies, with state governments providing about $I billion in additional funding (Robins, 1991; Barnett, 1992; Blau, 1993). ~ Much of this growth has occurred among inde-

pendent nonprofit and for-profit preschools. This sector, supported both by parental fees and government subsidies for low-income children, represents between 75% and 80% of all formal child-care organizations nationwide, despite rapid growth in federally funded Head Start and public school programs (Wilier et al., 1991; Fuller et al., 1993). Those concerned with family and early-childhood policy express two worries that involve the independent sector. First, is the supply of preschooling and child-care responsive to price, or do market imperfections lead to shortages in local communities which share certain characteristics (e.g. innercity or rural locales)? Do subsidies for low-income parents and children, flowing into the independent sector, boost the quantity of child-care supplied or simply generate economic rents, for instance, leading to higher teacher salaries (Mondale, 1974; National Governors' Association, 1990; Blau, 1992)? And with very rapid growth of Head Start in recent years, a third issue has emerged:

[Manuscript received 6 December 1994; revision accepted for publication 2 August 1995.] 149

150

Economics of Education Review

will expansion of heavily subsidized sectors-particularly Head Start and public-school-based preschools-crowd-out independent, market-oriented preschool organizations? To inform these questions and to assess probable effects of alternative policies, we studied simultaneous demand and supply functions, estimating the number of child-hours provided by independent preschools among 94-100 counties nationwide. Explaining local variation in supply and demand within this mixed market of preschool organizations involves the classic identification problem. Most research in this area has confounded supply and demand forces, as Barnett (1992) emphasizes, rather than identifying the independent influence of each set of factors. Independent preschools provide services in a mixed market, only partially subsidized by government agencies if at all. Thus variability across local areas in service-hours produced stems from factors linked to family demand (fee levels, income, family demographic attributes, available alternatives to independent centers and a priori preferences of parents) and factors linked to supply (fee levels, input costs and mixes, government intervention and proximate preschool alternatives). Only recently have countylevel data on the number of different types of preschools become available (Kisker et al., 1991) which can be merged with 1990 census data to help disentangle supply and demand processes across local jurisdictions. 2. PRIOR RESEARCH ON PRESCHOOL SUPPLY AND DEMAND Earlier empirical work has focused on four related areas. First, labor economists have studied the extent to which child-care organizations free women to enter the workforce. Despite the steady climb in female employment, the high private cost of child-care may hinder labor force entry by additional women, constraining household income. It has been argued that if private costs can be partially offset through subsidies, especially for impoverished mothers, job and income opportunities would become more attractive. The elasticity of quantity of child-care demanded with respect to subsidies has been studied in several settings, including the impact of policy experiments linked to income-maintenance and welfare reform (Blau and Robins, 1988; Heckman, 1974; Michalopoulos et al., 1992). This work shows that demand for preschool services, and subsequent labor force

entry by mothers, is moderately price-elastic among low-income families, especially when nonformal child-care options are unavailable (i.e. care by spouse, kin member, or family day-care home). Second, evidence is emerging on supply effects of raising subsidies, especially as government programs target child-care subventions on a widening range of low-income and working-class families, and organizations serving these groups. Blau (1993), for example, argues that shortages do not appear to exist, given that wages and entry requirements for preschool teachers and (uncredentialed) classroom aides are low in most states. Blau also finds that the elasticity of childcare labor supply is quite high (centering at 2.0 under various specifications). Over the past decade, salaries have remained flat in current dollars, with climbing subsidies effectively boosting organized supply (see also, Blau, 1992). In a related finding based on their national survey of 2089 preschool organizations, Kisker et al. (1991) found that many preschools enroll fewer children than the number for which they are licensed to serve, confirming earlier findings that shortages may not be severe overall. Sub-markets with particular characteristics, however, deserve further study, especially innercity and rural communities. The study of supply carried out by Siegel and Loman (1991) in Chicago revealed several zipcode areas without even one child-care organization, despite large numbers of women receiving AFDC (Aid to Families with Dependent Children) and childcare subsidies. Relatedly, Congressional debate in 1990 over enactment of the first national child-care program focused on what form of federal subsidy is optimal. This involves the on-going issue of whether continued expansion of Head Start and public-schoolbased preschools will crowd-out, or artificially underprice, nonprofit independent preschools and childcare centers. The compromise agreed upon in 1990 was to provide grants to states to support child-care expansion but require that funding be allocated directly to parents in the form of vouchers. Debate continues over how various subsidy streams shape the mix of preschools available for differing families (Chira, 1993; Robins, 1991; Samuelson, 1986). Third, the uneven distribution of preschool enrollment across regions and local communities has received empirical attention in recent years. Initial work suggested that families in the South had a greater propensity to use formal preschools, given greater rates of family poverty and thus higher sub-

The Mixed Preschool Market

sidies per capita for child-care since the 1960s (e.g. Hofferth and Wissoker, 1992). But if one excludes Washington, DC from the calculation of regional means, per capita use of preschool services in the South is somewhat less. 2 Overall, child-care use appears to be highest in the Northeast and lowest in the West and Midwest. The lower propensity of Latino families to enroll their children in formal centers and preschools, relative to White and African-American families, helps to explain lower utilization in western states (West et aL, 1993). Note that variation in the level of preschool enrollment may be jointly determined by family-level demand and the institutional environment contributing to supply. Variation in preschool enrollment among local counties is much greater than across broader national geographic regions. For instance, if the 100 counties selected by Kisker et al. (1991) are ranked on the basis of average household income, the most affluent quartile of counties has just over 20% more preschools operating per 1000 children, age 3-5, than the least affluent quartile of counties. The wealthiest counties possess 64% more preschool class groups, compared to the poorest counties (Fuller and Liang, 1993). This analysis is now possible, given that Kisker and her colleagues built lists of all known preschools organizations operating in 100 randomly selected counties, using these data in the sampling frame for their 1990 national survey (Kisker et al., 1991). Further descriptive analyses of these data appear below. The findings on Latino families exemplify a fourth line of research: household-level studies that estimate which families are more likely to enroll their young children in preschools. This area is related to the first line, studies focusing on decision-making pertaining to maternal employment. But researchers working from economic and social theories have begun to identify demographic attributes of the family that relate to their propensity to use preschool organizations, either examining variability in a priori preferences or in specifying social constraints on family decision-making. These demographic processes and predictors include family size and human-capital investment in a fewer number of children (Becker, 1981). Indeed, parents with fewer children do utilize preschool organizations at a higher rate, although whether this tendency remains after controlling on covariates is not known (Hofferth et al., 1991). African-American households and (nonteenage) single parents appear to utilize formal centers and pre-

151

schools at a higher rate (Coelen et al., 1979; West et al., 1993). But here too, we do not know whether this is an artifact of supply, since more subsidies are available for these groups, or whether their demand is greater, due to higher rates of maternal employment. At the household level, Hofferth and Wissoker (1992) found that the (institutionally shaped) quality of local preschools also influences parents propensity to enroll their children. In sum, we have consistent evidence on the demand side, at least for low-income families, that reducing private cost raises their propensity to use preschool programs. Supply elasticity appears to be moderately high: initial evidence showing that subsidies appear to boost provision of preschool slots and pull additional staff into the sector, rather than simply raising the cost of inputs and teacher salaries. We know that wide disparities in the distribution of preschool organizations and child-spaces per capita persist between low-income and affluent communities. And initial evidence suggests that different families with differing demographic characteristics exercise varying propensities to utilize preschools. However, we know little about the simultaneous influence of demand and supply processes on the availability of independent preschools among local areas. Without this knowledge, it remains unclear whether some families simply prefer not to use preschools (opting for care by spouses, kin members, family day-care homes), or whether supply imperfections are inequitably constraining the provider market. In addition, the simultaneous processes of family demand and organized supply clearly operate differently within different subsectors. Head Start, for example, provides fully subsidized preschools for families below the poverty line. Input prices are essentially regulated from Washington by setting salary scales, staff training requirements, and distributing curricular materials. Prior research fails to disaggregate the particular preschool subsector within which empirical claims about demand and supply processes are being made. 3 And prior work usually confounds family-level and institutional processes which together may shape demand and supply patterns within particular markets or subsectors. Our study focuses on independent preschools and child-care centers operating within a mixed market: generating revenues solely from parental fees or in combination with government subsidies. This excludes fully subsidized centers that may serve very low-income families, such as Head Start or fully

152

Economics o f Education Review

state-funded preschool organizations. Head Start serves an overlapping yet distinct market of parents: families that must be impoverished to participate. Head Start centers offer half-day programs and display lower public costs, due mainly to low teacher salaries, compared to the independent preschools which serve a much wider variety of households. 4 But by focusing on independent preschools in the mixed market, we can appropriately identify demand and supply factors that may shape availability for the great majority of families using preschools and formal child-care organizations. Head Start does remain in our models, assessing whether it does act organizationally to crowd-out independent preschools. 3. CONCEPTUAL F R A M E W O R K AND DATA We first report descriptive findings on independent preschools, focusing on their distinguishing characteristics and on variability in child-hours provided among different types of local counties. Then, we report results from our simultaneous estimation of family demand for, and supply of, preschooling provided by independent organizations. We estimate supply and demand at the county level. The type of data that was available forces us to ignore variations in preschool quality within counties and concentrate instead on the considerable variation in average quality characteristics across counties. This is not an exercise in general equilibrium modelling. Rather our equations should be understood as reduced forms that are broadly consistent with individual maximizing behavior and the estimation results should be seen as a first pass at some interesting data that we hope will add a factual basis to the on-going debate about how the independent preschool market functions and how it interacts with some important aspects of the local regulatory and institutional environment. Note that inferences from this approach are subject to the caveats associated with a study based on aggregated data. We do assume that the demand and supply equations estimated are consistent with individual profit and utility maximizing behavior, respectively. Specifically, household decision-makers are assumed to maximize a utility function of the form: U = U(H, G, L)

(1)

where H is the human capital of preschool-age children, G is a composite consumption good, and L is

parental leisure time. The household decision-maker faces the following constraints: T = L + E + C

(2)

H = H(C, S)

(3)

T¢ = C + S

(4)

Y* + w E = G + P • S.

(5)

The first is a time constraint, where T is number of hours per calendar unit, L is leisure, E is time spent in formal employment and C is time spent on the care of preschool-age children. The second constraint in (2) is in the form of a production function for the human capital of preschool children, assumed to depend on parental child-care and on time spent in formal preschools or centers (S). The child's time (T¢) is spent either in family care or in formal preschool centers. In equation (5), the sum of income exogenous to the time allocation decision (I"*) and labor income at hourly wage (w) together constrain total household consumption of schooling and of other goods (G). P is the price of formal preschooling. Individual family demand for independent preschool services can be derived from equations (1) and (2)-(5). The county-level function expressing demand for preschooling will be interpreted as broadly consistent with this individual framework, but also will depend on local idiosyncrasies. The county-level demand function is thus assumed to be of the form: Qo = Q(P, Y, D, O),

(6)

where Y is mean household income, D is a vector which represents the social or demographic character of the county and vector O describes the quality of independent preschools (recognized by parents in the aggregate) and the level of institutional alternatives available, in particular the variable extent of Head Start and public-school-based preschools across counties. On the supply side, independent preschools are assumed to operate competitively and in a manner consistent with profit maximization. The quantity of preschool services provided responds to the price per hour charged in the local market (P), to a vector of local input prices (R), and to a vector of regulatory and other local constraints on provision which determine the technology (T) with which preschool services of varying quality are produced. The countylevel supply function is thus of the general form:

The Mixed Preschool Market Qs = Qs( P, R, T).

(7)

3.1. County-level Preschool and Census Data for 1990 Two sources provided the data utilized in estimating the model. First, lists of all known preschool and child-care organizations were developed for 100 county units by Kisker et al. (1991) as they constructed their sampling frame. They then conducted phone interviews during 1990-91 with 2089 directors of these organizations to collect information on program size and quality. Second, county-level data from either 1988 or 1990 were gathered from census sources to obtain the economic and demographic variables required for the two models (Bureau of the Census, 1988; Bureau of the Census, 1993).

3.2. Principal Dependent Variable: County-level Aggregates of Preschool Service-hours Provided Sampled preschool directors were asked to report the number of children attending their program by different categories of hours per week (e.g. 20 children attending 40 h per week; 40 children attending 25 h per week). This allowed calculation of total child-hours of service provided by sampled independent preschools. This mean for each of the 100 counties was then multiplied by the number of independent preschools, obtained from the universe counts of preschools (by type) for each county. This yields the total number of child-hours provided each week by independent preschools per 1000 children residing in the county, age 5 years or younger. A second method for estimating child-hours provided was utilized, drawing on another part of the director interview. These estimations were very close to the first method but data were less complete for many centers. We recognize that child-care services provided to infants and toddlers, under age 3, differ relative to preschool services for youngsters, 3-5 years. But we aimed for the most inclusive definition of hours of service provided, and the same preschool organizations often provide care for both groups of children. 5

153

price variables were then aggregated to the county level, based on means calculated separately for each county from the sampled independent preschools. Mean family-income values come from census data for each county (Bureau of the Census, 1993). Closely related to overall income, we also entered county-level poverty rates into the demand model. The bulk of child-care subsidies are targeted to lowincome and working-class families, providing income supplements (Robins, 1991).6 Demographic and institutional characteristics of local counties, represented in equation (6) above, were measured in several ways. Overall population size and growth rate for the period 1980-1990 were pulled from census data. The percentage of the county's population that is 5 years of age or younger was included. The maternal employment rate was included in the demand model (women with preschool-age children, age 5 or younger, active in the labor force). We also studied demand effects of maternal employment in specific occupational sectors, but the overall rate proved to have a more stable influence (sector results appear in authors' citation). The share of households headed by single parents and the percentage of county population, African-American, were highly correlated (r = 0.87). These values were standardized and combined into an index. Three additional demographic variables were investigated but dropped from the final model, due to colinearity with related predictors or to consistent lack of effects: percentage of county population, Latino, divorce rate, and mean family size. To assess possible effects from the local institutional environment, an indicator of preschool service quality was included in the demand model: the share of preschools that are accredited by the leading professional organization (National Association for the Education of Young Children, NAEYC). Here we assume that parents accept the vector of quality indicators used by this accrediting agency. To study possible effects from crowding-out by competing preschool networks at the county level, we entered the percentage of preschools operated by Head Start and by local public schools.

3.3. Demand-side Predictors Consumer prices were calculated from directorreported hourly fees charged to parents. The subsidized or public price was calculated from the reported share of income stemming from government subsidies, either subventions to the preschool or via parental vouchers supported by welfare programs. These

3.4. Supply-side Predictors In addition to private and public (subsidy) prices, we studied possible supply effects of technological constraints on preschool inputs, assumed to stem from the local institutional context. The cost of inputs included average teacher salaries across all inde-

Economics of Education Review

154

pendent preschools in the county (similarly building from the sample data), the ratio of credentialed teachers to classroom aides, and the percentage preschools reporting that they must be licensed by state government. Possible effects from additional inputs and technology were studied but yielded no significant effects or destabilized the model due to colinearity: provision of health benefits to preschool staff, percentage of teachers with less than 2 years of college training, use of a formal curricular program in the preschool, and share of time that children spend in educational activities. While independent preschools react to purely economic variables, we assume that their behavior is also constrained by the demographic, institutional, and regulatory context in which they operate. To assess these constraints we also included in the supply model county population size and growth rate. Size of the public sector also was represented, from equation (4), by percentage of all adults employed by government and spending on K-12 education per capita by local education agencies. The percentage of adults voting in the last presidential election was entered to tap into whether county residents are placing demands on the public sector, in general, rather than the independent or private sector. Crowding-out variables also were included on the supply side: percentage of preschools in each county operated by Head Start or public schools.

4. DESCRIPTIVE FINDINGS Descriptive statistics for variables included in our county-level demand and supply models are reported in Table 1. Complete data on basic indicators of preschool availability come from 99 of the 100 original counties. To contrast the location and characteristics of independent preschools, we have included the same statistics for Head Start centers. For example, the first row provides data on our dependent measure of child-hours of service provided among counties. Independent preschools provided about 1841 h each week per 1000 children, age 5 years or younger, on average, compared to just over 100 h provided by Head Start centers. The latter network is generally serving only families below the poverty line. 7 We also split counties by quartiles based on their mean family-income level. In the 25 poorest counties (columns 3 and 4) we see that independent preschools provided 1294 h versus 163 h offered by Head Start centers. Almost twice as many child-hours are provided by independent centers in the 25 most affluent counties, and Head Start is less present (columns 5 and 6). These patterns are similar when we l o o k at related indicators of availability: mean number of children served, number of class-groups, and number of preschool organizations operating. Many independent preschools are operating in low-income counties, where about 30% of their revenues come from government subsidies. Yet independent pre-

Table L Indicators of preschool and child-care center availability among local counties All counties (n = 99)

Independent Mean child-hours provided countywide (per 1000 children, age 0-5 years) Mean number of children enrolled (per 1000 children, age 0-5 years) Mean number of class-groups operating (per 1000 children, age 0-5 years) Mean number of preschool organizations operating (per 1000 children, age 0-5 years)

Low-income counties (25th High-income counties percentile, n = 25) (75th percentile, n = 25)

Head Start Independent

Head Start Independent

Head Start

1841.7

100.9

1294.7

163.5

2398.9

57.1

327.7

24.9

203.9

45.6

476.3

14.3

10.8

1.0

6.3

1.1

14.4

0.9

4.6

0.4

3.8

0.5

5.9

0.3

The Mixed Preschool Market

155

ively. The mean fee charged to parents equals $0.98 per h in the lowest-income counties (column 1), compared to $1.72 in the highest quartile (column 2). The ratio of income from parental fees per hour ("consumer price", row 1) to subsidies ("subsidy price", ro~v 2) equals 2.2:1 in low-income counties, versus 4.1:1 in high-income counties. At the same time, parental fees charged by independent preschools are almost identical in counties where their presence

schools-both nonprofit and for-profit centers-are more abundant in the wealthier counties,s Table 2 reports descriptive findings for predictors used in our demand and supply models, splitting counties by high-low quartiles for mean household income (columns 1 and 2) and by independent preschool hours provided (columns 3 and 4). Again, we see evidence that independent preschools tend to serve more affluent families, although not exclus-

Table 2. Demand and supply factors: mean levels split between counties with high and low household income preschool child-hours provided

1. Prices per hour of preschooling (dollars) -consumer/private price -subsidy/public price 2. Mean household income (dollars) 3. Poverty: percent of families below poverty line 4. Family demographics and employment -maternal employment rate (women with children age 6 or younger) -single-parent/black household index -percentage county population age 5 or younger -divorce -percentage of work force in professional or technical jobs -percentage of families Latino -mean number of persons residing in the household -median county population -population growth 5. Preschool inputs and quality indicators -mean teacher salary (dollars) -ratio of children to teachers -ratio of teacher to aides -mean number of classes per preschool -percentage of preschools accredited by a professional association -percentage of preschools requiring licensure by state government 6. Organizational context and preschool alternatives -government size (% of adults employed by the public sector) -government spending on education, per capita (dollars) -percentage of adults voting (1988 presidential election) -percentage of county's preschools independent -percentage of county's preschools Head Start -percentage of county' s preschools public schools

Household income

Independent preschool hours per 1000 children age 0-5

25th percentile 75th percentile

25th percentile 75th percentile

0.98 0.44 9549 14.3

1.72 0.42 17,318 6.6

1.34 0.85 12,279 9.8

1.33 0.45 14,961 7.7

52.9

57.9

53.1

61.2

0.58 8.0 5.43 13.6

-0.18 6.6 5.48 28.2

-0.10 7.8 4.1 16.3

0.10 6.8 5.9 25.4

6.0 2.76

7.3 2.56

3.2 2.78

6.3 2.55

1,032,431 0.15

903,641 0.012

721,850 0.20

9413 12.5 4.4 3.45 17.1

12,933 14.2 2.7 4.4 22.7

10,411 15.8 2.25 3.45 15.7

11,762 12.1 3.45 4.91 20.6

89.3

95.9

90.1

92.3

6.8

6.0

5.8

6.0

450.0

458.7

520.2

417.0

45.1

53.2

51.4

48.0

75.8 10.3 13.9

85.7 4.0 10.2

71.4 12.1 16.5

88.2 3.8 7.9

101,988 0.07

Note: Means and standard deviations for final variables appear in Table 3.

156

Economics of Education Review

is lowest ($1.34, column 3) and where they are most abundant ($1.33, column 4). Additional comparisons of counties with a low, versus high, presence of independent preschools (again, columns 3 and 4) show that the latter counties are characterized by a higher maternal employment rate (61.2% versus 53.1%), greater percentage of the workforce in professional or technical jobs (25.4% versus 16.3%), and a higher population growth rate (20% versus 1%). Independent preschools operating in high-income counties display different input mixes, relative to preschools in low-income counties (section 5 of Table 2). Average teacher salaries are 37% higher in the top income quartile ($12,933), relative to salaries in the poorest income quartile ($9,413). The child:teacher ratio is somewhat larger among independent preschools located in higher-income counties (14.2:1), compared to low-income counties (12.5). But in the former, it appears that these centers rely on additional classroom aides, given that the teacher:aide ratio is 2.7:1, versus 4.4:1 in the bottom quartile. Preschools in the top quartile also tend to be larger, comprised of 4.4 class-groups on average, relative to 3.4 classgroups among preschools in the lowest-income quartile. Finally, the share of all preschools that are Head Start equals 10.3% in low-income counties, versus just 4.0% in high-income counties. The difference for public-school-based preschools is not as great (13.9% in low, versus 10.2% in high-income counties). 5. ESTIMATION RESULTS The specified system of equations was estimated with three-stage least-squares (3SLS), since an endogenous variable (price) appears on the right-hand side of both the supply and the demand equation, and because equation-specific errors are likely to be correlated. Coefficient estimates, t-statistics, and P-values are reported in Table 3. Coefficients for the typical economic variables show expected signs in both the demand and supply equations. Price and income in the demand equation and price in the supply equation are all significant at P < 0.10 or better. Both "sides" of the market are found to be very sensitive to parental fee levels. A $1.00 increase in price is found to reduce by about 1.8 the number of hours of preschooling demanded per child in the average county (elasticity at the mean = - 1.59), and to raise the quantity of hours supplied by about 1.3 h (elasticity at the mean = 1.17). A $1000 increase in per-capita income is associated

with a 0.13 h increase in hours demanded (elasticity at the mean = 1.13). The maternal employment rate, also predictably, holds a positive influence on aggregate demand. Beyond the findings for strictly pecuniary variables, several additional patterns emerge. In the demand model, we see that the index of single-parent and black households is positively related to demand. Counties with younger age structures are experiencing significantly lower demand, while counties with higher population growth over the 1980s are witnessing higher aggregate demand for independent preschool services. In the discussion section we speak to why this may the case, based on related empirical studies. We also tested the assertion that direct government provision of preschool and child-care services may crowd-out independent centers. While this belief is ubiquitous, the argument has not been empirically assessed to our knowledge. Discussion in the Congress, in recent years, has focused on relative spending levels across three very different subsidy strategies: the centralized Head Start program, the decentralized child-care block grant program (primarily parental vouchers), and tax expenditures on the federal tax credit (Robins, 1991). Results in Table 3 support the contention that government provided preschools are weakly crowding-out independent organizations, with the effect appearing most markedly on the demand side. A 1% increase in the average county's share of preschools provided by Head Start and the public schools reduces demand for independent programs by 0.028 and 0.018 h, respectively (elasticities at the mean of -0.14 and -0.054). Similar patterns are seen in the supply equation, although the coefficients are not statistically significant. The finding for percentage of preschools accredited, in raising aggregate demand, is notable. It appears that the presence of higher quality independent preschools-to the extent that parents share the same indicators of quality utilized by the accreditation agency-spurs greater demand. In contrast, the supply model reveals that the share of preschools requiring licensing by the state (where a variable share of public-school or church-based preschools are exempt' from state licensing procedures; Morgan, 1987) is negatively related, apparently operating as a technological constraint on independent preschool provision. Input mixes are related to the supply of preschool child-hours to a lesser extent than might be expected.

The Mixed Preschool Market

157

Table 3. Demand and supply of independent preschool child-hours provided. Three-stage least squares estimalions (n = 94 counties) Parameter estimate (t statistic)

Probability of t statistic

Mean of X (SD)

Demand equation 1. Intercept 2. Price (total) 3. Household income (thousands) 4. Poverty (% households below poverty line) 5. Family demographics -maternal employment rate -black/single-parent household (index) -percentage population under age 5 -total population, 1990 (thousands) -population growth rate 6. Preschool quality and organizational alternative -percentage of preschools accredited by professional organization -percentage of preschools, Head Start -percentage of preschools, public school

2585.87 ( 1.63) - 1774.52 (-3.43) 129.94 ( 1.94) -12.23 (-0.40)

0.107

26.33 (2,09) 142.56 (2.28) -253,11 (-2.60) -0,026 (-0.33) 21.87 (3.21)

0.040

16.07 (2.27) -27.91 (-1.71) -18.35 ( - 1.98)

0,026

0.001

1.33

(0.46) 0.055 0,691

12.98 (2.85) 9.21

(4.80)

0.030

0.011 0,744 0.002

0,091 0.051

55.92 (7.34) 0.05 (1.96) 7.45 (1.03) 728.14 (1,158.76) 10.46 (16.52) 17.19 (12,79) 7.52 (5.89) 11.78 (9.49)

Supply equation 1. Intercept 2. Prices -consumer/private price -subsidized/public price 3. Input costs and mixes -mean teacher salary (thousands)

3525.20 (2.59)

0.011

1302.90 (I .84) 56.34 (I.30)

0.069 0.200

1.51 (3.37)

- 16.59

0.734

I 1.22 (2.68) 2.61 (1.76) 91.57 (11.49)

(-0.34) -ratio teachers:aide -percentage of preschools under state licensing procedures 4. Demographic charac~ristics and context -total population, 1990 (thousands) -population growth rate 5. Organizational context -government size (% adults employed by public sector) -local government spending on education per capita -percentage of adults voting -percentage of preschools, Head Start -percentage of preschools, public school Mean of dependent variable System-weighted R square = 0.54

1.33

(0.46)

135.18 ( 1.84) -12.18 (-1.11)

0.070

-0.020 (-0.20) 17.79 (2.07)

0.845

61,76 (2.76) -2.66 (-2.28) -55.34 (-2.23) -27.12 (-1.19) -6.76 (-1.19)

0.007

0.269

0.041

0.025 0.029 0.239

0.638

728.14 (1158.76) 10.46 (16.52) 7.22 (5.22) 449.47 (122.94) 37.76 (8.10) 7.52 (5.89) 11.78 (5.89) 1448.09 (1131.70)

158

Economics o f Education Review

Teacher salary levels, for instance, are of the sign one would expect, but the coefficient is not statistically significant. This is, however, consistent with Blau's (1991) finding that salaries, even in current dollars, have remained remarkably constant as the supply of formal child-care programs has risen. Supply of independent child-hours is higher in counties with a higher ratio of teachers to classroom aides (although the coefficient is significant only at P < 0.07 level), a variable we interpret as reflecting local regulations on permissible adult to child ratios. In Table 2 we saw that this ratio was higher in low-income counties, presumably in more laxly regulated independent preschools that can not afford to hire more classroom aides. The supply model also reveals that provision of independent child-hours is higher in counties with a larger government sector overall (9 = 61.76, P < 0.007). But supply is lower when local government spending on K-12 education is higher and voter turnout is higher. This may indicate that the independent preschool sector is larger in urban counties with higher levels of poverty and thus subsidies. But after taking this effect into account, counties that invest more heavily in their local schools prefer public-sector child-care services. More work is required to disentangle how the local strength of government per se may constrain the size and growth of the independent preschool sector. Overall, this system of demand and supply equations is quite efficacious in explaining variation among counties in child-hours provided by the independent preschool sector, with the system-weighted R 2 equalling 0.54. 6. CONCLUSIONS AND POLICY IMPLICATIONS Many independent preschools and centers appear to operate within segmented markets, particularly those serving more affluent communities and dependent largely upon revenues from parental fees. A large number of independent preschools do receive subsidies, either directly through government contracts or via child-care vouchers and other income supplements received by the parents. This latter group of preschools operates in a highly variable mixed-market, serving low-income and working-class children, and drawing revenues from a blend of parental fees and subsidies. The local environments in which independent preschools operate overlap with communities

served by Head Start and public schools. But often the two markets do not coincide; in fact they appear to be competing with each other. The segmentation of preschool markets and subsectors represents important scope conditions under which supply and demand processes likely differ. In reviewing our empirical results, let us focus on policy implications. Within this mixed-market context, we found expected negative effects from price on independent preschool child-hours demanded. Counties with more single-parent and African-American families-those families receiving a high share of available child-care subsidies-also display greater aggregate demand. And even though the independent sector is stronger in affluent counties overall, subsidies obviously support the many nonprofit independent preschools found in low-income communities (evidenced in Table 1). These findings are consistent with earlier research showing that parents tend to choose formal preschools and centers (rather than kin members or less-expensive family day-care) when targeted income supplements offset private costs (Heckman, 1974; Hofferth and Wissoker, 1992). Predictably, we find that the maternal employment rate is positively related to preschool demand, the reciprocality of which has received empirical attention elsewhere. In sum, these findings suggest that policy efforts aimed at raising household income will spur greater expressed demand for preschools and formal child-care services. Counties with younger age structures (i.e. higher proportions of preschool-age children) have significantly lower levels of preschool demand. This may be explained by the fact that fertility rates are relatively high in many rural and working-class areas where a priori parental preference for, or availability of, formal child-care programs is lower (Fuller and Liang, 1993). Enrollment in preschools of 3-5 yearold children may free a mother's time for labor force participation. But if additional preschool-age children are in the household, the private cost of entering the child-care market may become daunting. 9 Furthermore, while enrollment may or may not benefit the child, enrolling one child when infants remain at home will not free the mothers' time to participate in the labor force. Thus, incorporating the time constraints from (2)(5) into equation (1) and differentiating with respect to S and letting subscripts denote partial derivatives, we can obtain

The Mixed Preschool Market Us = UH Hs + Uo(w -

P) + ULLs.

(8)

In the multi-child framework, the one-to-one link between hours of school enrollment and hours freed for labor or leisure is broken, unless the child enrolled is the one that required the maximum number of hours of care. If we explicitly allow for more than one child and different care requirements across children, and joint production of care for all children, the mothers' time constraint is replaced by T = L + E + max(C),

(9)

where i indexes the children. For all but the child requiring most care, the second and third terms in (8) vanish. Since both of these terms were positive, the marginal propensity to enroll a child is diminished by the presence of a second child in the home that requires more care. The extent to which working-class families respond to increasing child-care subsidies, particularly via the new block-grants to states, will be important to watch. Also, counties experiencing more rapid population growth are showing stronger demand for preschools and child-care centers. This can be seen where migration into suburban counties by young professionals and middle-class families-groups with higher propensities to use formal preschools (West et al., 1993)-appear to further boost aggregate demand. This suggests that as suburban areas become more diverse demographically, differences in the distribution of preschool enrollment may decline, at least at the county level and outside of rural and innercity areas. The institutional and regulatory context faced by independent preschools exerts two important influences. First, demand is stronger when a higher proportion of preschools seek and obtain accreditation from the leading professional organization (NAEYC). The estimated coefficient on the percent of preschools that are accredited indicates demand is sensitive to this characteristic, with an elasticity at the mean of 0.19. This suggests that parents are attentive to qual-

159

ity and appear to accept accreditation as one indicator of quality. In contrast, our estimates weakly support the hypothesis that regulations which require preschool accreditation are a binding constraint on private providers, apparently adding to operating costs and reducing supply, ceteris paribus. In studying the supply effects of regulation it is only fair to caution that the most aggressive states in terms of regulatory practices are comprised of more urban, higher-income counties where the independent sector is most robust. It is, therefore, difficult to fully disentangle demand effects resulting from family income, and the related demographic forces included in our models, from the discrete effects of regulation on supply. Second, counties with strong public sectors also have a more vigorous independent preschool sector. However, when counties have concentrated investments in public schools, Head Start centers, and public-school-based preschools, the independent preschool sector provides f e w e r child-hours of service. We have identified the main channel of this crowding-out of the independent sector as operating primarily through substitution in demand, where larger market-shares held by Head Start and public schools reduced aggregate demand for independent preschooling. As more political leaders call for "full funding" of Head Start, this finding has important implications. It shows that growth in one heavily subsidized preschool sector will likely suppress the vitality of the independent sector; and that independent preschools have the capacity to operate within low-income communities, mixing private and public revenue sources, and tend to be of higher quality (along several indicators; Fuller et al., 1993); policy options that would constrain this sector's growth and vitality should be evaluated carefully.

Acknowledgements--We thank Ellen Kisker and Valarie Piper, Mathematica Policy Research, for sharing their time and much of the data analyzed in this paper. Comments by W. Steven Barnett and Richard Murnane on an earlier version were very helpful. This study was supported by the Spencer Foundation and the Packard Foundation's Center for the Future of Children.

NOTES 1. We use the terms preschool and child-care center synonymously. The earlier distinction between purely "custodial" day-care versus educationally intensive preschooling has blurred considerably (Kisker et al., 1991). This paper only deals with preschools and centers serving children 5 years of age or younger, and excludes after-school programs for school-age chilaren. 2. We estimated regional availability levels in an earlier paper, including, then excluding, Washington, DC in the southern region, drawing from the Kisker et al. (1991) universe data. Washington is a high

160

Economics o f Education Review outlier in terms of child-care availability. The weighted mean number of preschool organizations per 1000 children, age 5 or younger, for the South (including DC), Northeast, Midwest, and West equals 6.1, 6.0, 3.9, and 4.1, respectively. But when DC is shifted to the Northeast, means for the South and Northeast move to 5.8 and 6~4, respectively. In terms of the number of preschool classes available per 1000 children, age 3-5 years, the Northeast leads, even when DC remains sorted into the South. For South, Northeast, Midwest, and West: 21.9, 27.8, 16.8, and 14.9 classes, respectively (authors' citation). 3. Two studies have focused on family day-care homes, usually women who take into their own home 3-5 children each day. Walker (1992) estimated prices charged by family day-care providers. Barnett (1992), also focusing on family day-care, shows higher levels of demand among parents with younger children, 3 years of age or younger. Barnett also argues that parents express demand for preschool services to allow the mother to work and to invest in their child's development, perhaps two distinct demand processes. He also discusses the interaction between rising government-provided supply and the squeezing-out of independent providers and family (private) spending on child-care, which is likely to be the result. 4. To be enrolled in Head Start, parents must be close to or below the poverty line and able to arrange care in the afternoon after the half-day program ends. About 28% of all parents earning less than $10,000 annually with a preschool-age child utilize Head Start. Another 15% to 20% of this eligible population enroll their child in an independent nonprofit preschool (West et al., 1993; Hofferth, 1994). Just under 40% of all Head Start parents use wrap-around services of some kind to cover the afternoon time. In addition, many parents selecting independent preschools do not enroll their child full-time (more than 35 h per week), similar to parents in the overlapping Head Start "market". Among nonemployed mothers, center-care is used 14 h per week, complemented with kin or informal care for another 16 h per week, on average for youngsters, age 3-4. In sum, Head Start versus independent preschools do tend to serve the most impoverished and more middle-class families, respectively, but they also have overlapping clienteles within low-income communities. 5. One EER reviewer also points out that the regulatory environment differs in some states for infant/toddler versus preschool-age children. However, our two measures of "regulation" pertain to accreditation by a professional organization (NAEYC) and the variable extent to which states exempt certain preschools from government regulation. These measures pertain to preschool organizations (Morgan, 1987; Kisker et al., 1991). 6. The major exception to the targeting of child-care subsidies is the largely untargeted federal tax credit, providing about $3 billion in annual tax spending each year to families earning less than $80,000 (Barnett, 1992). 7. Cities or social service agencies purchase slots at Head Start centers to serve, for example, foster children or youngsters under the state's care who may not be residing with guardians who are below the poverty line. 8. Nationwide over half (54%) of all child-care and preschool directors report receiving no government subsidies; 21% report that between 1% and 80% of their revenues come from subsidies; and 25% report that subsidies comprise more 80% of their total revenues (Fuller et al., 1993). 9. For example, Edwards et al. (1994) find that in Honduras, where the independent preschool market is almost entirely absent and there are no public preschools, the probability of enrolling an under-age children in primary school is increased if this child is the youngest one in the home.

REFERENCES

BARNETT, W.S. (1992) An introduction to the economics of family home day care. In Family Day Care (Edited by Peters, D. and Pence, A.). New York: Teachers College Press. BECKER, G. (1981) A Treatise on the Family. Cambridge: Harvard University Press. BLAB, D. (1992) The child care labor market. J. Human Res. 27, 9-39. BLAB, D. (1993) The supply of child care labor. J. Labor Econ. 11, 324-347. BLAB, D. and ROBINS, P. (1988) Child care costs and family labor supply. Rev. Econ. Stat. 70, 374-381. BUREAU OF THE CENSUS (1988) County and City Data Book. Washington, DC: Government Printing Office. BUREAU OF THE CENSUS (1993) Census of population and housing: equal employment opportunity file [CD90-EEO, cd-rom form]. Washington, DC. CHIRA, S. (1993) Working-class parents face shortage of day care centers. New York Times September 14, p. 20. COELEN, C., GLANTZ, F. and CALORE, D. (1979) Day Care Centers in the United States: A National Profile, 1976-1977. Boston: Abt Books. EDWARDS, J.H.Y., GASTON, N.G. and TUNALI,I. (1994) Under-age primary school enrollment as hidden demand for day-care. Tulane University, mimeo.

The Mixed Preschool Market FULLER, B. and LIANG, X. (1993) The Unfair Search for Child Care: Working Moms, Poverty, and the Unequal Supply of Preschools across America. Cambridge, MA: Harvard University. FULLER, B., RAUDENBUSH,S., WEI, L. and HOLLOWAY,S. (1993) Can govei-nment raise child-care quality? The influence of family demand, poverty, and policy. Educ. Eval. Policy Anal. 15, 255-278. HECKMAN, J. (1974) Effects of child-care programs on women's work effort. J. Pol. Econ. 82, 2 supplement, 136-163. HOEEERTH, S. (1989) What is the demand and supply of child care in the United States? Young Children (July) 28-33. HOFFERTH,S. (1994) Who enrolls in Head Start? A demographic analysis of Head Start eligible children. Early Childhood Research Quarterly 9, 243-268. HOFEERTH, S., BRAYEIELD,A., DEICH, S., and HOLCOMB,P. (1991) National Child Care Survey, 1990. Washington, DC: Urban Institute Press. HOFFERTH, S. and WISSOI,:ER,D. (1992) Price, quality, and income in child care choice. J. Human Res. 27, 70-111. KISKER, E., HOFFERTH,S., PrIILLIeS,D. and FARQUHAR,E. (1991) A Profile of Child Care Settings: Early Education and Care in 1990. Princeton, NJ: Mathematica Policy Research. MICHALOeOULOS,C., ROBINS,P., and GARFINKEL, I. (1992) A structural model of labor supply and child care demand. J. of Human Res. 27, 166-203. MONDALE, W. (1974) Legislating child development. In Perspectives on Child Care (Edited by Wright Edelman, M.). Washington, DC: National Association for the Education of Young Children. MORGAN, G. (1987) The National State of Child Care Regulations 1986. Watertown, MA: Work/Family Directions. NATIONALGOVERNORS'ASSOCIATION(1990) Who Cares for Our Children? Washington, DC. ROBINS, P. (199l) Child care policy and research: an economist's perspective. In The Economics of Child Care (Edited by Blau, D.). New York: Russell Sage Foundation. SAMUELSON,R.J. (1986) Pitfalls of family policy. Young Children, November. SIEGEL, G. and LOMAN, A. (1991) Child Care and AFDC Recipients in Illinois: Patterns, Problems and Needs. St. Louis, MO: Institute of Applied Research. WALKER, J. (1992) New evidence on the supply of child care: A statistical portrait of family providers and an analysis of their fees. J. Human Res. 27, 40-49. WEST, J., HAUSKEN,E. and COLLINS,M. (1993) Profile of Preschool Children's Child Care and Education Program Experience. Washington, DC: National Center for Educational Statistics (Series no. NCES 93-133). W1LLER, B., HOFFERTH,S., KISKER,E., DIVINE-HAWKINS,P., FARQUHAR,E. and GLANTZ, F. (1991) The Demand and Supply of Child Care in 1990. Washington, DC: National Association for the Education of Young Children.

161