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B. Head Start Funding Data

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Head Start funding data are drawn from the National Archives and Records Adminis- tration Community Action Program (NACAP) electronic files (Community Services Administration 1981).8 The NACAP files consist of two record types. First are records for all 4,769 organizations receiving any Community Action Program grant between 1965 and 1981, and among other items these grantee-level records contain the recipi- ent organization’s county. Second is a record for each specific grant action, such as a disbursement, extension, renewal, or termination. This grant action-level data contain information on total federal grant dollars, the service delivery county (which in a limited number of cases differs from the grant recipient’s county), and the year of disbursement. The grant action-level records also contain a brief project description that indicates whether the grant was for a Head Start program. The information in these two sets of NACAP records is used to calculate aggregate

federal Head Start grant dollars at the county–year level. Most of the utilized county– year Head Start funding data were assembled and generously shared by Bailey and Goodman-Bacon (2015), with some supplemental data collection by the author from the primary NACAP records. I then divide the annual federal Head Start grant totals for each county by the number of children in the county who were ages three to six in each year (which as noted above was the age range of Head Start participants in this period) and express these grant amounts per child aged three to six in 2012 dollars.9

To construct a measure of Head Start exposure for individual NLSY79 respondents, I calculate the average level of Head Start funding per child aged three to six that occurred in each NLSY79 respondent’s county of birth during the three calendar years that they were ages three to four, four to five, and five to six. For instance, respondents born in calendar year 1961 are assigned the mean of the Head Start spending that occurred in their county of birth during calendar years 1965 (when they were ages three to four), 1966 (when they were ages four to five), and 1967 (when they were ages five to six). One important feature of measuring exposure as the mean of local funding levels

during the three calendar years when each respondent was ages three to six is that greater weight is given to funding levels occurring at ages four and five than at ages three and six. This occurs because both of the calendar years in which an individual was ages four and five are included in this measure, but only one of the two calendar years in which they wereagesthreeand six.IbelievethisisappropriategiventhedatainTable1 indicating that 60–80 percent of participants in early Head Start implementations were ages four or five, with smaller numbers of three- and six-year-olds participating. In Section VI below, I also present results that estimate the effects of funding levels at each age separately, and the strongest effects are found for ages four and five. Anotherimportantconsequence ofconstructing theHeadStart exposurevariableinthis

way is that it results in a continuous treatment measure, as opposed to a binary indicator of whether a program existed in a given county–year. This is especially important given that I do not reliably observe actual Head Start enrollments in the NLSY79 because higher per-capita funding levels are likely indicative of higher enrollment rates, making it more

8. The electronic NARA archives can be accessed at http://aad.archives.gov/aad/series-description.jsp?s=536& cat=TS16&bc=,sl (accessed June 21, 2017). 9. County population totals are drawn from the decennial censuses with linear interpolations for noncensus years.

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likely that children from counties with higher per-capita funding actually participated. Lower per-capita funding levels are also likely indicative of summer-only programs rather than more expensive full-year programs, and the current measure allows for this variable treatment intensity to be taken into account. Results using binary treatment measures are presented below and result in much less precise estimates.10

It is essential for the validity of the analysis that the utilized NACAP Head Start funding data be accurate. Given this, I have cross-validated the NACAP data using two additional, independent sources of information on early Head Start funding levels. First are county level data for 1968 and 1972 from the Federal Outlays System Files, as assembled by Ludwig and Miller (2007), which report federal expenditures on various programs, including Head Start.11 There is a high level of agreement between the Federal Outlays data and the NACAP grant records used here, with a simple correlation between the two measures of 0.893 for 1968 and 0.875 for 1972. An additional cross-validation of the NACAP grant data was performed using transcriptions of state-level Head Start expenditure totals reported in the OEO’s first, second, and fourth annual reports to Congress (OEO 1965, 1966, 1968).12 The state aggregates in these reports for 1966 and 1968 correspond quite closely to those generated from the NARA grant records, with simple correlation coefficients of 0.896 for 1966 and 0.962 for 1968.13

While these strong correlations between independently collected funding measures for 1966 and 1968 are reassuring, there are large discrepancies in 1965 funding levels between the NACAP grant records and the state aggregates from the 1965 OEO annual report, with much lower levels in the NACAP records. Bailey and Duquette (2014) also note this discrepancy, and they suggest it is potentially related to the fact that in 1965 Head Start existed only as a summer program, and the NACAP grant record dating (which was initially performed in fiscal years) may have charged these summer expenditures to 1966. This explanation is especially plausible given that in this period the federal fiscal year began on July 1, making it ambiguous which fiscal year summer Head Start expendi- tures should be assigned to. Regardless of the root cause of these discrepancies, since no reliable 1965 Head Start funding data are available, 1965 funding levels are set to zero in

10. The use of a three-year average to define Head Start exposure also helps account for ambiguity that arises from a lack of information on the exact birthday cutoffs used to determine age-based eligibility for local Head Start programs. For instance, a child born in June of 1964 would have been age two (and presumably not eligible for Head Start) for approximately six months of 1966, but would then be age three (and potentially eligible) for the other six months of 1966. The evolving mix of summer and full-year programs during the study period introduces additional imprecision in the assignment of funding data to individual NLSY79 respondents, since some summer participants may have attended a full-year program as well, while for others no full-year program was available, which also makes the more flexible three-year average exposure definition attractive. 11. As discussed in greater detail in Ludwig and Miller (2007), the authors determined that the Federal Outlays data for Head Start were unreliable for years other than 1968 and 1972. 12. The OEO’s third annual report to Congress, OEO (1967), did not disaggregate Head Start expenditures from expenditures on other CAP activities. Also note that the online data appendix for Bailey and Duquette (2014) reports a similar validation of the NACAP grant figures using OEO annual reports, but does so for total CAP spending rather than for Head Start specifically and reports high levels of agreement. 13. A related data quality concern is that some counties with active Head Start programs may have been recorded as not receiving any Head Start funding in the NACAP grant data because of incompleteness in how the NACAP data treated recipients providing services in multiple counties. However, there is a very high level of agreement between the NACAP data and the FederalOutlays datawithrespect tothe number of counties receivingHead Start funding in each state–year, with simple correlations of 0.99 in 1968 and 0.98 in 1972. It should be cautioned, however, that Ludwig and Miller (2007) indicate that the Federal Outlays data may also be flawed in accounting for agencies providing Head Start services in multiple counties, making this exercise less than conclusive.

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the working data set. While not ideal, the practical consequences of this are likely to be minimal given how the utilized Head Start exposure measure is constructed. In par- ticular, most children who attended a 1965 summer program, but are not coded as such due to missing summer 1965 data, will still be assigned positive exposure due to positive funding levels in years 1966 and beyond. Figure 1 uses the NACAP grant data to map the timing of Head Start program

introductions from 1966–1970, which is the range of years with valid data that poten- tially impacted NLSY79 respondents.14 Of the approximately 3,000 counties in the United States, 1,439 introduced a Head Start program during this period, and Figure 1 indicates a relatively uniform distribution of introduction timing across the relevant years, which will produce ample variation in program exposure within the NLSY79 sample. While counties in Appalachia and the coastal states appear somewhat more likely to have introduced Head Start programs in this period, which is in line with historical accounts, no dramatic geographic patterns are apparent. Since the estimation sample in my baseline models is approximately 2,700 individ-

uals, while there are approximately 3,000 counties in the United States, small within- county sample sizes are a potential concern. However, the working sample contains 61 counties with 10–19 individual observations, 19 counties with 20–29 individual ob- servations, and 15 counties with 30 or more individual observations

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