The traditional approach of those working in the field of developmental psychology is to use standardized regression coefficients in hierarchical regression models. These seem quite different from the methods employed by economists, but the full model used is a standard OLS regression model, and the standardized coefficients can be converted into the nonnormalized coefficients more traditional in the economics discipline. Doing so allows us to address the question of the expected change in developmental outcomes of children were quality to be improved based upon standard OLS estimates (see Hanushek and Jackson, 1977).
Using estimates based on NICHD data, we perceive that the quality of child care can indeed make a difference. Table 7 reports on the cognitive and language results for the NICHD samples at ages 15 months, 24 months and 36 months (NICHD Early Child Care Research Network, in press-b). Three outcome measures are used: for the younger two ages, the Bayley, CDI vocabulary production, and CDI vocabulary comprehension tests are used; for the oldest age group (36 months) the Bracken school readiness, Reynell expressive language and Reynell verbal comprehension tests are used. (See above for a more detailed discussion of these tests.) In addition to the measures of child care quality, the model includes measures of parental background, quality of the home, the child care setting, and time spent in child care. These are an attempt to minimize the role of parental selection of child care in order to capture the effects of child care quality differences on measures of child development.
Two models are presented for each age group and outcome measure. The first tests for the effects of the child care quality using a cumulative score of positive caregiving rating, while the second adds a specific measure of language stimulation. Caregivers’ behaviors were assessed during four 44-minute observations over two half-days at 6, 15, 24, and 36 months. These were combined into the cumulative positive caregiving rating.
We converted the standardized coefficients reported in NICHD (in press-b), into nonstandardized coefficients. Table 7 only reports those for child care quality that are statistically significant at the 5 percent level. Combining these with the measures of quality and reinterpreting the standardized coefficients indicates the following effects.
The expected improvement in the CDI vocabulary production test for toddlers aged 15 months, when their care quality shifts from one standard deviation below the mean to one standard deviation above, is nearly 7 points, or 24 percent; if the shift is from the minimum score (5) to the maximum (20) in caregiver rating, the estimated gain is 18 points. (Note that the standard deviation is 2.9, within a range of 5–20.) For the vocabulary comprehension score, shifting from one standard deviation below the mean leads to an expected increase of 8 points; and moving a child from the minimum score to the maximum score in caregiver rating is expected to increase a child’s score by 21.6 points, or 55 percent of the mean.
At age 24 months, statistically significant changes are registered for the Bayley test and the sentence comprehension test. The Bayley estimates produce an expected increase of about 5 points when the shift is from one standard deviation below the mean to one above. The sentence comprehension results produce an expected increase of 7 points. A shift from the lowest caregiver to the highest increases expected performance on the vocabulary test by about 40 percent relative to the mean, but only about 13 percent in the case of the Bayley test. (Note that for the 24 month olds the standard deviation is 2.9 as well, and the range is the same as that for those 15 months old, 5–20.) The expected changes are larger for those aged 36 months than for those aged 24 months.
For the Bracken school readiness test at age 36 months, a shift from one standard deviation below the mean on the caregiving rating to one above is expected to lead to an increase of 6.9 points. (Note that the caregiver rating has a larger range for those aged 36 months, 7–28, while the standard deviation is 3.3.) The same shift in caregiver quality is expected to lead to a 5-point increase in the expressive language score and an 8.6 point increase in the verbal comprehension score, relative to the mean. A shift from the lowest rating to the highest for caregiver rating is expected to result in a shift of about 50 percent relative to the mean for each of these three outcomes. These estimates give us some sense of the magnitude of the possible changes in children’s outcomes as a result of improvements in positive caregiver rating.
We can do a similar exercise with the second measure of quality, language stimulation. This measure is added to the regression in an alternative specification. In most cases the addition of this measure reduces the estimated impact of positive caregiving. (Because language stimulation is a major component of caregiving quality, this is not surprising.) We simulate the impact of language stimulation only for ages 15 months and 24 months, where it is statistically significant for all three of the child development outcome measures.
For children 15 and 24 months of age, having a child care arrangement in which more language stimulation is provided can play a small but significant role in improving all three of the outcome measures. For children of 15 months, simulating an improvement in caregiver language stimulation from one standard deviation below the mean to one above increases performance on the Bayley test by nearly four points, by 12 points on the CDI vocabulary production test and by about 9 points on the CDI sentence comprehension test. At 24 months of age, a child exposed to a level of language stimulation one standard deviation below the average is expected to gain about 5 points on the Bayley test, or about 4 percent relative to the mean, were the child moved to an arrangement with a rating one standard deviation above the norm, or by 61 units (about one third of the full range of 0–180). The same child would be expected to gain 12 points on the CDI sentence comprehension test, or nearly 30 percent relative to the mean. And the same child would be expected to gain about 9 points on the CDI vocabulary production test, or about 20 percent relative to the mean.
The NICHD group also estimated models with both concurrent and lagged quality measures (NICHD, in press-b). Their results suggest that the cumulative impact of child care quality may be far greater than the concurrent impact. In Table 8 we provide two examples, one for children at 24 months of age using caregiver quality measures at 15 and 15–24 months, and one at 36 months of age using quality measures from 15–24 months and 36 months. Only those quality measures which are statistically significant at the 5 percent level are reported. Similar measures for language stimulation are chosen as the cognitive outcome measure. Both sets of results suggest that there is a lagged effect of language stimulation and that the cumulative effect of exposure to higher levels of language stimulation appears to be greater than the concurrent impact alone. In the case of those aged 24 months, the converted results suggest that a child who was in a child care arrangement over this entire period that was one standard deviation below the mean (calculated at both 15 and 24 months) is simulated to gain about 30 points on a CDI vocabulary production test if moved to one above the mean. Looking at only the concurrent language stimulation, an increase of 11 points, or about one-third of the full cumulative gain, is simulated. In the case of 36 those aged months, we find that both language stimulation and overall caregiver quality are significantly associated with performance on the Reynell vocabulary comprehension test measured at 36 months, and that only the lagged measure of language stimulation is statistically significant among the two lagged measures of quality. Among these 36-month-olds, we simulate a combined gain of 11 points on the Reynell vocabulary test if the child moved from one standard deviation below the mean on both quality measures to one above the mean over the entire period from 15 months to 36 months. This far exceeds the simulated increase if only the contemporary measures were modified. The respective means of the outcome measures are shown on the table.
The magnitudes of simulated change are large, but the resulting changes are also rather large, suggesting that caregiver quality can significantly influence these outcomes. All of these estimates are subject to the usual caveat that the underlying estimates may not be causal. We should also note that the measures of quality are based on limited observation, so that the effect captured is likely to underestimate the true effect of quality.
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