Responses to questions given to a random sample of Michigan households are used to estimate public spending demand functions. While income and price elasticities are similar to those obtained from aggregate data, positive income elasticities appear to arise because public services are distributed in a prorich manner. A relatively small variance in spending demands among urban and suburban communities in metropolitan areas with substantial public service variety suggests that the Tiebout mechanism works. This interpretation is supported by the fact that actual spending conforms substantially to desired levels in urban areas, but less so in rural areas with little public sector choice.

IN recent years empirical studies of local school finance have relied to a large extent on the median voter and related models, tested with data aggregated to the precinct, school district, or local level.1 While there are advantages to using aggregated data, the limited availability of data on the distribution of income, property tax payments, and other variables, as well as the possibility of bias associated with the grouping of households into aggregated units, suggest some important disadvantages.2 This paper attempts to analyze the demand for local public education using individual household data obtained through a survey of voters in two local school elections in a Detroit suburb.3 In section I a model of voting in a school election is presented. The model assumes that individual voters determine their desired level of educational expenditures per pupil by maximizing a utility function subject to a budget constraint. Individuals decide whether to vote for or against a given millage request by comparing their desired expenditure level with the actual and proposed levels. On the basis of some assumptions concerning the stochastic nature of the individual utility functions, our analysis suggests that the probability of a yes or no vote can be estimated using a binary logit form.4 In section II the model variables and estimates of the model parameters are presented and discussed. The estimation results are interpreted in the context of the voting model presented in section I and are compared to the results of several educational expenditure studies. In section III the outcome of the two local elections is analyzed, with an attempt made to explain the passage of the second election, in light of the failure of the first. In particular, the model is used to test the reaction of voters to the state circuit-breaker legislation which was enacted after the first election. Some concluding remarks are presented in the final section. Finally, some tests for the presence of bias in the survey responses are described in the appendix.

In recent issues of this REVIEW, Myrick Freeman and Kenneth Small have helped to clarify some confusion which grew out of a study of air pollution and property values by Ridker and Henning (1967). Ridker and Henning (hereafter referred to as R-H) performed a multiple regression of property values on air pollution, housing characteristics, accessibility, and neighborhood characteristics using cross-section data for the St. Louis metropolitan area. As Freeman (1974a) and Small (1975) point out, the early debate on the R-H study was largely sidetracked with the issue of whether one can predict the aggregate change in property values resulting from an improvement in urban air quality. A more appropriate focus for policy purposes is the question of whether property value data can be used to estimate households' willingness to pay for cleaner air. The R-H study calculated willingness to pay by first multiplying the air pollution coefficient obtained in their linear regression by the change in air pollution estimated for each household, and then summing over all St. Louis households. The air pollution coefficient was thus inteipreted as the average willingness to pay for air quality improvements for all St. Louis households. Freeman (1971) had correctly pointed out in an earlier note that the R-H procedure of calculating willingness to pay is inappropriate because a hedonic housing regression cannot in itself isolate demand and supply elements; and Freeman was not very sanguine about the possibilities of doing so. Without taking a position on whether the true willingness to pay for clean air can be determined empirically, both Freeman and Small put the earlier empirical work into perspective by showing that the pollution coefficient in the housing value regression does provide a correct measure of the 'mnarginal valuation placed by individual consumers on uniform changes in pollution levels (Small, 1975, p. 105). As a theoretical point, this result is reassuring, since it suggests that benefit estimates obtained from studies like that of Ridker and Henning may be reasonable if the air quality improvement is small. Unfortunately, however, the air quality improvements generated by the Clean Air Act Amendments of 1970 and 1977 are distinctly nonmarginal (pollution reductions are often predicted to be 50% or more). No empirical evidence has been available thus far to assess the magnitude of the bias associated with using marginal valuations to estimate the benefits from these nonmarginal pollution reductions.' This note attempts to fill this gap. Several authors have argued as a matter of principle that the willingness to pay for nonmarginal air quality improvements can be obtained from property value data if the proper conceptual procedure is used.2 Using the approach suggested by these papers and an empirical focus suggested by Rosen (1974), we have elsewhere provided estimates of households' willingness to pay for clean air as well as details concerning the nature of the data and possible specification biases (Harrison and Rubinfeld, 1978). In this paper we confine our discussion to the magnitude of the bias that results from using the air pollution coefficient in the hedonic housing price equation directly to estimate the willingness to pay of urban households for a nonmnarginal air quality improvement. Section II summarizes the model we use to estimate the demand for nonmarginal changes in air quality. In section III we distinguish three potential sources of bias in the R-H procedure, and assess the quantitative importance of each with data for the Boston Metropolitan area.

A model of consumption of residential energy in dwellings is developed, distinguishing between attributes of housing that provide direct benefits to consumers and attributes that serve as inputs in the production of final goods, for example, the thermal comfort of dwellings. Empirical estimates are made of the mode, based upon the Annual Housing Survey, and the results are used to calculate the effects of changes in energy prices on the consumption of housing, residential energy, and other goods. The analysis suggests that the adjustment process within the housing market permits a great deal of substitution in response to energy price changes. Copyright 1989 by MIT Press.

Academic journal publishing has evolved rapidly in the past two decades. Prices, ownership concentration, the number of journals, and the means of distribution have all changed dramatically. Substantial price increases have been the norm. Average prices have risen severalfold over this period, with prices climbing the most at forprofit journals, where these prices are now as much as 500 percent higher than nonprofits (Gail Yokote, 2003). The price difference between forprofit and nonprofit academic journals is particularly striking, given that these journals are generally similar in format and editorial processes, and that for-profit journals do not appear to be of higher quality (Theodore C. Bergstrom, 2001 p. 183). Increased concentration provides one possible explanation for why prices of for-profit journals are so high. To take one example, measured by revenue, in 2001 Elsevier Science had a 22.9percent share of the Science, Technology, and Medicine (STM) industry, with Kluwer at 11.7 percent, and Thomson at 10.7 percent. But concentration offers at best only a partial answer. Bundling offers another, potentially more significant explanation, particularly for recent increases. The prices of for-profit journals could not be high and increasing without significant structural barriers to entry. Recently, however, a new strategic barrier has emerged. Major publishers have been offering libraries packages of journals that are bundled across journals and across print and electronic versions. The exact terms have varied from publisher to publisher, but a contract (sometimes called a “Big Deal” by librarians) typically involves a library entering into a long-term arrangement to get access to a large electronic library of journals at a substantial discount, in exchange for a promise not to cut print subscriptions (whose prices will increase over time); in this sense print and electronic are bundled. Since the electronic library becomes much less expensive when ordered in quantity, there is likewise bundling across electronic journals. Bundling can be seen as a device that erects a strategic barrier to entry. At a simple level of analysis, the Big Deal contracts leave libraries few budgetary dollars with which to purchase journals from new entrants. Looking one level deeper, we see that bundling entails average prices that exceed marginal prices, and this creates a barrier to entry if entrants compete with the marginal journal. Other things equal, bundling practices are likely to be anticompetitive to the extent that they allow for the maintenance of supracompetitive average prices that limit usage of academic journals by scholars and/or distort library choices between journals and monographs and books. There are, however, pro-competitive benefits associated with bundling. Recent deals have provided scholars with extra access to journals; moreover, when electronic databases contain journals not included in the libraries’ print collections, the collections expand. Finding an economic approach that analyzes a range of bundling practices and evaluates them by appropriately balancing benefits and costs † Discussants: V. Kerry Smith, North Carolina State University; Robert Hall, Stanford University.

President in April 1994. This paper argues that the federal form of governance, which allowed for locally elected provincial governments with significant fiscal policy responsibilities, was essential for this successful transition. An appropriately structured federal constitution can allow for democratic rule by the (often poor) majority, while protecting to a significant degree the economic interests of the previous ruling (usually rich) minority. A federal constitution must resolve three

Responses to questions given to a random sample of Michigan households are used to estimate public spending demand functions. While income and price elasticities are similar to those obtained from aggregate data, positive income elasticities appear to arise because public services are distributed in a prorich manner. A relatively small variance in spending demands among urban and suburban communities in metropolitan areas with substantial public service variety suggests that the Tiebout mechanism works. This interpretation is supported by the fact that actual spending conforms substantially to desired levels in urban areas, but less so in rural areas with little public sector choice.

The prices of for-profit academic journals have increased rapidly over the past decade (Barbara Albee and Brenda Dingley, 2001). There remains substantial debate as to the explanation for these increases. Among those put forward are the increased concentration of the journal industry (see e.g., McCabe, 2002) and the relatively recent effort by major publishers to bundle print and electronic journals (Aaron S. Edlin and Rubinfeld, 2004). While both explanations are undoubtedly important, what is missing is the significant role of the primary customers of journal publishers—the academic libraries. As agents of college and university faculties, libraries serve the interests of their principals while having only limited information about faculty journal demands. Facing little or no hard budget constraint, faculty are unlikely or unwilling to make difficult allocative choices. As a result, libraries have been making hard choices for years (between journals and books, and among journals), in a world of increasing budgetary pressure. Given that electronic transmission of knowledge is becoming increasingly important, an understanding of the reasons for the increases in journal prices is a vital element in the ongoing discussion of best mechanisms by which scholarly communications can be disseminated. In this paper, we formulate a model of library journal demand and suggest how it can be used to analyze the optimal pricing of journals by publishers. This represents part of a larger project whose long-range goal is to explain the pattern of journal pricing over time, and to