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Papers written by Author(s): 'Brian McCall'

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  • Working Paper

    DO PUBLIC TUITION SUBSIDIES PROMOTE COLLEGE ENROLLMENT? EVIDENCE FROM COMMUNITY COLLEGE TAXING DISTRICTS IN TEXAS

    September 2014

    Working Paper Number:

    CES-14-32

    This paper estimates the effect of tuition rates on college enrollment using data for Texas from the 1990 and 2000 Censuses and the 2004 ' 2010 American Community Surveys and geographical data on Community College Taxing Districts. The effect of tuition on enrollment is identified by the facts that tuition rates for those living within a taxing district are lower than those living outside the taxing district and in Texas not all geographic locations are in a taxing district. While the estimated effect of tuition on enrollment depends on the sample used, it is negative and mostly statistically significant in the samples of iadults 18 and older and negative and sometimes statistically significant in the samples of traditional age students 18 to 24. The estimated effect of tuition on enrollment, however, is found to vary considerably by poverty level status with an increase in tuition rates having a statistically significant negative effect on college enrollment for those with household incomes that are at least 200% of the poverty level both for traditional aged students 18 to 24 years old and all adults 18 and older.
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  • Working Paper

    Decomposing the Sources of Earnings Inequality: Assessing the Role of Reallocation

    September 2010

    Working Paper Number:

    CES-10-32

    This paper uses matched employer-employee data from the U.S. Census Bureau to investigate the contribution of worker and firm reallocation to changes in wage inequality within and across industries between 1992 and 2003. We find that the entry and exit of firms and the sorting of workers and firms based on underlying worker skills are important sources of changes in earnings distributions over time. Our results suggest that the underlying dynamics driving changes in earnings inequality are complex and are due to factors that cannot be measured in standard cross-sectional data.
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