تجدید نظر تعارض بین نسلی:ساختار جمعیت شناسی بخش و تقاضا برای آموزش عمومی

The observation that the elderly may be less willing to support K-12 education than other voters raises the specter of decreasing support for schools as the US population ages. In this article, we examine that support using a national panel of counties over time. Building on earlier models estimated for state level data, we conclude that the direct differential effect within each county of the presence of elderly households is not distinguishable from zero but that the elderly have the potential to affect spending on education indirectly through where they live. To the extent that the elderly live in counties with low proportions of children, the tax price of education in other counties is higher which could in turn reduce financial support for education in those counties. Thus one cannot predict the impact of an increasing share of the elderly on education spending without paying attention to how the elderly are likely to be distributed among counties relative to children.

The aging of the baby boom population in the US and elsewhere raises the spectre of increasing intergenerational conflict over the disposition of limited resources. To the extent that older people vote in their narrowly defined self interest they may secure a share of public resources that rises even faster than their increasing share of the population. Policymakers and researchers have devoted significant attention to the impact of the increasing numbers of elderly on the solvency of federal programs such as Social Security and Medicare. However, the changing demographics are also an important concern for state and local governments. One potential implication of the shift in political power from the working population to the elderly is the possibility that disproportionately fewer public resources will be available for services for children, including elementary and secondary education. A long literature suggests that the elderly tend to vote in their narrowly defined self-interest. Various researchers have documented that, compared to younger groups, the elderly appear to have weaker preferences for K-12 education (Vinovskis, 1993 and Rubinfeld, 1977); that they were less willing to vote favorably on certain school bond referenda (Button, 1992) or more willing to support tax property tax limitations (Ladd & Wilson, 1983); and that, other factors held constant, school districts in New York with larger shares of the elderly spent less per pupil on education than other districts (Inman, 1978). Most recently James Poterba, has considered the experiences of all states between 1961 and 1991 to examine how the changing share of the elderly affects the willingness of states to support elementary and secondary education (Poterba, 1997). His preferred empirical findings indicate that, other factors held constant, the higher the proportion of people over 65 in a state, the lower the amount the state spends (including both state and local spending) per child on K-12 education. In addition the greater the difference between the share of the elderly who are white in the state and the share of the youth who are minority, the lower is the support for education. One limitation of viewing the intergenerational conflict at the state level is that it ignores differences across communities within states that affect both the location decisions of the elderly and educational spending. This article builds on Poterba's approach and extends it in two interrelated directions. First, it provides a richer, more disaggregated analysis by shifting the unit of observation away from states to local counties. In contrast to Poterba's findings our analysis of local jurisdictions suggests that rising shares of the elderly exert no direct downward pressure on K-12 education spending. However, like Poterba, we do find a reduction in per-child education spending when the adults and the school-age population are members of different racial groups. Second, this article provides new insight into the implications of funding education at the state or at the local level. With extensive local funding of education, older households are able to avoid some of the financing burden by sequestering themselves in local communities with few children. With extensive state funding, their opportunities for avoiding the burden are more constrained. By improving our understanding of both the local spending decision and the residential location patterns of the elderly, this article sheds new light on these differing funding arrangements. In Section 2, we specify the data used for this analysis and describe how the elderly are distributed across counties and how those patterns have been changing over time. In Section 3, we provide the conceptual foundation for our analysis of the impact of rising elderly share on the willingness to support K-12 education. We present our county-level results in Section 4 and attempt to reconcile them with the state-level results in Section 5. The article ends with a brief conclusion.

This article represents an initial exploration of a number of issues that deserve further research. Its primary contribution is the finding that county-level estimates of the effects of the elderly on support for education are smaller than those that emerge from the state-level study by James Poterba. Although we do not claim to have fully sorted out why the different effects emerge, we believe that our focus on how the elderly are distributed relative to children among counties is a solid start towards a better understanding of a complicated phenomenon. Worthwhile next steps should include more attention to the institutional details of the division of state and local financing responsibilities among states, to testing some of the hypotheses discussed in Section 3 about why the elderly might support spending on education, and most importantly, to developing a more complete model of the sorting process of elderly and other households among counties and across states. In terms of substance, we end up somewhat less pessimistic than Poterba about how an aging society is likely to affect support for K-12 education. As we noted in the previous section, his estimates of the effects of a rising elderly share overstate the negative effects of age on spending to the extent that increases in the elderly share are accompanied by greater dispersal of the elderly among local school districts. However, one disturbing element emerges in both the state-level and the county-level studies, namely that the greater is the mismatch between the race of the children in a jurisdiction and the race of the elderly (or other adults), the lower is the willingness to support education spending. How such effects can be moderated should be high on the agenda for future research.