While researchers continue to explore why childcare choices vary and how they vary systematically by different immigration context, it is evident that the current literature tends to view parental immigration status and other immigrant indicators simply as contributing factors into the childcare choice decision. It does not sufficiently disentangle the multifaceted nature of being immigrant parents in the childcare choice context. These studies are limited with regards to three aspects, which I will address in this study—lack of a more realistic framework (section
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2.4.1), need for a more comprehensive data set (section 2.4.2), and a more appropriate empirical model (section 2.4.3).
2.4.1 Need for a new conceptual framework
As discussed earlier, the reality facing families in need of childcare is more complex than what a set of observed family-level attributes can describe, an approach commonly used in developmental psychology. Similarly, when adding the immigrant context into the childcare choice context, there is a need for a more thoughtful framework rather than just including
immigrant indicators (parental immigration status, region of origin, etc.) into the childcare choice equation. I would speculate that this common approach to handle the immigrant context in the current childcare choice literature is in part due to the lack of a more comprehensive and realistic approach accounting for the supply side to begin with.
This study addresses the complexity by building upon the heterogeneous availability of alternatives framework from the field of labor economics. It also addresses the lack of an appropriate immigration theory in the immigrant childcare choice literature by adapting the spatial assimilation framework. The heterogeneous availability of alternatives framework
acknowledges the constraints individuals often face when making decision among a set of choice alternatives, which is often individual specific, random, and latent. It is applicable to the
childcare choice situation wherein parents, acting as decision-makers, have access to only a limited set of childcare alternatives as a result of family attributes, preferences, and supply constraints.
The spatial assimilation theory posits that children of immigrants’ socioeconomic outcomes are in part affected by the residential locations their immigrant parents settled in. The emphasis on geography linking the immigrant residential location to perceived opportunities and
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constraints for children of immigrants is relevant for the problem of childcare choices among immigrant families, where access to formal childcare or lack thereof can be viewed as
opportunities or constraints to the benefits of preschool education. In this framework, parental immigration status and its impact on childcare choices are characterized as resulting from the residential location immigrant parents choose.
2.4.2 Data limitations
Constraining researchers’ abilities to study childcare choices is data availability in the field of early childhood education. Most studies that examine childcare choices lack measures of the supply. While the commonly used ECLS data sets include a rich set of family- and child- level characteristics from nationally representative samples, they do not provide much information on the supply of childcare. Data from individual states often do incorporate
condition of the childcare supply within the state (e.g., Hatfield et al., 2015; Herbst & Barnow, 2008); however, studies that use them often lack information of individual families and their actual childcare choices. As a result, our ability to study the link between the childcare supply and family childcare choices has been limited.
A second issue related to data limitations has been the use of proxy variables in the study of childcare supply. There have been efforts to use proxy variables for specific childcare
alternatives, but they are less than ideal. One common practice to study the influence of the supply side is to use the number of childcare workers in a center setting or in a licensed family childcare home, collected by the Census Bureau, as proxy for the supply of available center or family childcare homes within a specified geographic location (Tang et al., 2012). It rises two issues. First, this proxy can not tell us the capacity (available slots) of centers or family childcare homes within the family’s proximity, because the teacher-child ratios vary by age and care type
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under state and local contexts. In addition, when it comes to measuring individual care providers, it has always been difficult to capture measures that proximate their availability, such as the number of individual provider locations (Herbst & Barnow, 2008).
Another proxy variable researchers have used for childcare supply is public funding levels (Greenberg, 2010; Magnuson et al., 2007). However, this measure can be problematic too when used in cross-state studies, because it assumes that state pre-K slots are funded with equal amounts across states. States vary greatly in their per-pupil expenditures for state pre-K. Even when studying pre-K within the same state, most studies do not differentiate the amounts of public funding allocated, which may vary by community characteristics, and assume instead that public funded preschool spots are equally distributed across communities regardless of the local socio-economic conditions. In addition, states’ expenditures on state pre-K programs do not necessarily correlate with the number of state pre-K slots because some expenditures may be targeted at quality improvement or integration efforts to link pre-K data with K-12 data, rather than program expansion. Therefore, state funding may not be a good indicator for the quantity of state pre-K provision at the community level.
In this study, I used physical locations of state pre-K and Head Start, in addition to supply measures of other childcare alternatives (discussed in Chapter 4), to reflect the density of service provision each parent has access to within the community. This addressed data limitations in two ways. First, I created a comprehensive data set that has measure for each childcare alternative. Second, this supply-side measure can be linked to family-level attributes, allowing me to study how supply affects childcare choices.
37 2.4.3 Methodological constraint
In addition to data limitations that may have constrained the ability of prior research to link childcare supply to individual families’ childcare choices, there is a need for an empirical model that can account for supply-side attributes, such as the number of service providers, and the real choice situation. Among existing studies, researchers have predominantly employed the multinomial logistic model (MNL) to predict childcare choices. Similar to constraints cast by data limitations, the MNL does not control for attributes of the choices themselves. In other words, using an MNL approach, one could only predict childcare choices based on family-level attributes. In this study, I used a conditional logit model (CLM) to address this issue. From a conceptual perspective, the CLM is a discrete choice model that allows me to account for attributes of the choice alternatives, which may be individual specific and vary across
alternatives. From a methodological perspective, it is also subject to fewer assumptions than the MNL model, as described in more detail in Chapter 4.
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