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.

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

We examine the effects of urban form and public transit supply on the commute mode choices and annual vehicle miles traveled (VMTs) of households living in 114 urban areas in 1990. The probability of driving to work is lower the higher are population centrality and rail miles supplied and the lower is road density. Population centrality, jobs-housing balance, city shape, and road density have a significant effect on annual household VMTs. Although individual elasticities are small absolute values (≤0.10), moving sample households from a city with the characteristics of Atlanta to a city with the characteristics of Boston reduces annual VMTs by 25%.

We examine how the market's ability to assess the truthfulness of management earnings forecasts affects how managers bias their forecasts, and we evaluate whether the market's response to management forecasts is consistent with it identifying predictable forecast bias. We find managers' willingness to misrepresent their forwardlooking information as a function of their incentives varies with the market's ability to detect misrepresentation. We examine incentives induced by the litigation environment, insider trading activities, firm financial distress, and industry concentration. With regard to the stock price response to forecasts, we find the market varies its response with the predictable bias in the forecast. The efficiency of the market's response, however, varies with the forecast news.

In a market experiment, buyers respond to sellers' disclosures of one of the two potential outcomes of a risky prospect. Buyer reactions reflect two separate disclosure phenomena that heretofore have not been considered jointly. First, consistent with cognitive predictions that users tend to anchor on explicit one-sided disclosures, buyers pay more relative to expected value when the seller discloses the higher of the two potential outcomes than when the seller discloses the lower potential outcome. Second, consistent with the incentive-driven predictions of information economics, buyers systematically discount bids when sellers choose which potential outcome they wish to disclose, relative to bids in a control condition in which the seller is constrained to disclose randomly. Both findings are robust to each other, addressing qualifications in prior research about generalizing cognitive disclosure phenomena to a strategic disclosure environment. One implication supported by the data is that if cognitive information processing limitations are robust to a strategic environment, then strategic agents can exploit these limitations when choosing disclosures.

We model a dynamic limit order market as a stochastic sequential game with rational traders. Since the model is analytically intractable, we provide an algorithm based on Pakes and McGuire (2001) to find a stationary Markov‐perfect equilibrium. We then generate artificial time series and perform comparative dynamics. Conditional on a transaction, the midpoint of the quoted prices is not a good proxy for the true value. Further, transaction costs paid by market order submitters are negative on average, and negatively correlated with the effective spread. Reducing the tick size is not Pareto improving but increases total investor surplus.

We present a model embodying moderate amounts of nominal rigidities that accounts for the observed inertia in inflation and persistence in output. The key features of our model are those that prevent a sharp rise in marginal costs after an expansionary shock to monetary policy. Of these features, the most important are staggered wage contracts that have an average duration of three quarters and variable capital utilization.

Performance-measure weights for incentive compensation are often determined subjectively. Determining these weights is a cognitively difficult task, and archival research shows that observed performance-measure weights are only partially consistent with the predictions of agency theory. Ittner et al. (2003) have concluded that psychology theory can help to explain such inconsistencies. In an experimental setting based on Feltham and Xie (1994), we use psychology theories of reasoning to predict distinctive patterns of similarity and difference between optimal and actual subjective performance-measure weights. The following predictions are supported. First, in contrast to a number of prior studies, most individuals' decisions are significantly influenced by the performance measures' error variance (precision) and error covariance. Second, directional errors in the use of these measurement attributes are relatively frequent, resulting in a mean underreaction to an accounting change that alters performance measurement error. Third, individuals seem insufficiently aware that a change in the accounting for one measure has spillover effects on the optimal weighting of the other measure in a two-measure incentive system. In consequence, they make performance-measure weighting decisions that are likely to result in misallocations of agent effort.

We present a new method for solving asset pricing models, which yields an analytic price-dividend function of one state variable. To illustrate our method we give a detailed analysis of Abel's asset pricing model. A function is analytic in an open interval if it can be represented as a convergent power series near every point of that interval. In addition to allowing us to solve for the exact equilibrium price-dividend function, the analyticity property also lets us assess the accuracy of any numerical solution procedure used in the asset pricing literature. Copyright The Econometric Society 2005.