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We establish limitations to the usage of direct revelation mechanisms (DRMs) by corporations seeking decision-relevant information in economies with securities markets. In this environment, posting a DRM increases the informed agent's outside option: if the agent rejects the DRM, he convinces the market he is uninformed, and he can aggressively trade with low price impact, thereby generating large (off-equilibrium) trading gains. This endogenous outside option may make using a DRM to screen uninformed agents impossible. When screening is possible, solely relying on the market for information is optimal if the increase in outside option is sufficiently large. Authors have furnished an Internet Appendix , which is available on the Oxford University Press Web site next to the link to the final published paper online. [ABSTRACT FROM AUTHOR]

We evaluate the effect of climate adaptation infrastructure investments on property transaction prices, using data on over 400,000 property transactions and 162 infrastructure projects in Miami-Dade County, an area that is highly vulnerable to flooding and sea level rise due to climate change. Exploiting the timing and siting of different adaptation projects in Miami-Dade, we are able to identify significant gains in property values after completion of adaptation infrastructure projects. These gains are concentrated in areas close to the project and for projects that are visually identifiable. Our results suggest an aggregate mean benefit, net of adaptation cost, of about $0.68 million per project and almost $300 million in aggregate net benefits for all projects in our sample. Most projects generated positive net benefits, indicating that the vast majority of adaptation efforts are being placed in areas passing a benefit-cost test. [ABSTRACT FROM AUTHOR]

We study the e®ect of privately informed traders on measured high frequency price changes and trades in asset markets. We use a standard market microstructure framework where exogenous news is captured by signals that informed agents receive. We show that the entry and exit of informed traders following the arrival of news accounts for high-frequency serial correlation in squared price changes (stochastic volatility) and grades. Because the bid-ask spread of the market specialist tends to shrink as individuals trade and reveal their information, the model also accounts for the empirical observation that high-frequency serial correlation is more pronounced in trades than in squared price changes. A calibration test of the model shows that the features of the market microstructure, without serially correlated news, accounts qualitatively for the serial correlation in the data, but predicts less persistence than is present in the data.

A standard assumption in integrated assessment models of climate change is that population and productivity are growing, but at a decreasing rate. We explore the signifcance of the assumption of population and productivity growth for greenhouse gas abatement. After all, there has been no long run slow down in the growth of productivity over the past few centuries, and the rate of population growth has actually been increasing for the past 19 centuries. Even if either of these growth rates were expected to slow, by how much is subject to great uncertainty. We show computationally that such continued growth greatly increases the severity of climate change. Indeed we nd that climate change is a problem in large part caused by exogenous population and productivity growth. Rapid reductions in growth make climate change a small problem; smaller reductions in growth imply climate change is a very serious problem indeed. Analogously, reductions in the growth rate of population can be effective in controlling climate change.

This paper concerns computational models in environmental economics and policy, particularly so-called integrated assessment models. For the most part, such models are simply extensions of standard neoclassical growth models, extended by including the environment and pollution generation. We review the structure of integrated assessment models, distinguishing between finite horizon and infinite horizon models, both deterministic and stochastic. We present a new solution algorithm for infinite horizon integrated assessment models, relying on a neural net approximation of the value function within an iterative version of the Bellman equation.

The paper begins with the problem of a firm subject to random productivity shocks drawn from a particular distribution. We are concerned with the case whereby the distribution of the shocks changes without the knowledge of the firm. Over time the firm learns about the nature and extent of the change in the distribution of the shock and adjusts, incurring adjustment costs in the process. The long run loss in profits (Ž) due to the shift in the distribution we term the adaptation costs. The transitory profit loss, incurred while the firm is learning about the distribution shift, is termed the adjustment cost. The theory is developed and then applied to the problem of measuring adaptation and adjustment costs in the face of unanticipated and imperfectly observed climate change in agriculture. The empirical part of the paper involves estimating a supply function for corn that depends on actual weather realizations and expected weather, using county level data for the US. We then simulate the effect of an unobserved climate shock, where learning about the climate shock is by observing the weather and updating prior knowledge using Bayes Rule.

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jet.2004.07.006 Byline: David L. Kelly Abstract: We consider a general equilibrium model with a production externality (e.g. pollution), where the regulator does not observe firm productivity shocks. We examine quantity (permit) regulation and price (tax) regulation. The quantity of permits issued by the regulator are independent of the productivity shock, since shocks are unobserved. Price regulation implies use of the regulated input is an increasing function of the productivity shock because firms take advantage of a good productivity shock by increasing input use. Thus price regulation generates higher average, but more variable, production. Therefore, we show that in general equilibrium the relative advantage of quantity versus price regulation depends not only on the slopes of marginal benefits and costs, but on general equilibrium effects such as risk aversion. The general equilibrium effects are often more important than the slopes of the marginal benefits and cost curves. In the simplest model, a reasonable risk aversion coefficient implies quantity regulation generates higher welfare regardless of the benefit function. Author Affiliation: Department of Economics, University of Miami, Box 248126, Coral Gables, FL 33124, USA Article History: Received 25 November 2003; Accepted 21 July 2004

To link to full-text access for this article, visit this link: http://dx.doi.org/10.1016/j.jeem.2005.02.003 Byline: David L. Kelly (a), Charles D. Kolstad (b)(c), Glenn T. Mitchell (d) Abstract: The paper is concerned with the case whereby the distribution of a firm's productivity shocks changes without the knowledge of the firm. Over time the firm learns about the nature and extent of the change in the distribution of the shock and adjusts, incurring adjustment costs in the process. The long-run loss in profits ([+ or -]) due to the shift in the distribution we term the equilibrium response. The transitory loss in profits, incurred while the firm is learning about the distribution shift, is termed the adjustment cost. The theory is then applied to the problem of measuring adjustment costs in the face of imperfectly observed climate change in agriculture. The empirical part of the paper involves estimating a restricted profit function for agricultural land in a five-state region of the Midwest US as a function of prices, land characteristics, actual weather realizations and expected weather. We then simulate the effect of an unobserved climate shock, where learning about the climate shock is by observing the weather and updating prior knowledge using Bayes Rule. We find adjustment costs to climate change are 1.4% of annual land rents. Author Affiliation: (a) Department of Economics, University of Miami, P.O. Box 248126, Coral Gables, FL 33134, USA (b) Department of Economics, Bren School of Environmental Science and Management, University of California, Santa Barbara, CA 93106, USA (c) University Fellow, Resources for the Future, Washington DC, USA (d) LECG, Los Angeles, CA 90071, USA Article History: Received 5 June 2003

An analysis of the resulting equilibria in a simple one-commodity model of the overlapping generations version of the Shapley-Shubik market game reveals that complex and chaotic equilibrium dynamics are possible. There is also an alternative to the technology-based explanation for the historical fact that the onset of industrialization brings about business cycles.

Many pricing forecasting models use rational expectations equilibrium (REE) as a natural starting point, research shows that the learning rule does not meet the REE in theory and simulations.