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Using the standard real business cycle model with lump-sum taxes, we analyze the impact of fiscal policy when agents form expectations using adaptive learning rather than rational expectations (RE). The output multipliers for government purchases are significantly higher under learning, and fall within empirical bounds reported in the literature, which is in sharp contrast to the implausibly low values under RE. Positive effects of fiscal policy are demonstrated during times of economic stress like the recent Great Recession. Finally, it is shown how learning can lead to consumption and investment dynamics empirically documented during some episodes of “fiscal consolidations.”

The Randolph Glacier Inventory (RGI) is a globally complete collection of digital outlines of glaciers, excluding the ice sheets, developed to meet the needs of the Fifth Assessment of the Intergovernmental Panel on Climate Change for estimates of past and future mass balance. The RGI was created with limited resources in a short period. Priority was given to completeness of coverage, but a limited, uniform set of attributes is attached to each of the ~198 000 glaciers in its latest version, 3.2. Satellite imagery from 1999–2010 provided most of the outlines. Their total extent is estimated as 726 800 ± 34 000 km2. The uncertainty, about ±5%, is derived from careful single-glacier and basin-scale uncertainty estimates and comparisons with inventories that were not sources for the RGI. The main contributors to uncertainty are probably misinterpretation of seasonal snow cover and debris cover. These errors appear not to be normally distributed, and quantifying them reliably is an unsolved problem. Combined with digital elevation models, the RGI glacier outlines yield hypsometries that can be combined with atmospheric data or model outputs for analysis of the impacts of climatic change on glaciers. The RGI has already proved its value in the generation of significantly improved aggregate estimates of glacier mass changes and total volume, and thus actual and potential contributions to sea-level rise.

A superlayer test has been adapted for the measurement of the fracture energy between epoxy thin films and self-assembled monolayers (SAM's) on Au/Ti/Si substrates. The “arrest” mode of analysis has been shown to provide consistent results, particularly when relatively wide lines are used to encourage lateral decohesions. The fracture energy, Γi, of the interface between the monolayer and the epoxy is varied by adjusting the ratio of COOH/CH3 terminal groups. Connections among Γi, the surface energies, and the inelastic deformations occurring in the epoxy are explored upon comparison with interface crack growth simulations.

There were four 1.5-hour sessions of Division I business meetings during the XXVIIth IAU General Assembly. The first three were devoted to the reports of Commissions, Working Groups and services associated with the Division, discussion about plans for the next triennium and future structure of the Division. Scientific presentations on the future space astrometric mission Gaia were made at the fourth session.

We study how the use of judgment or “add-factors” in forecasting may disturb the set of equilibrium outcomes when agents learn by using recursive methods. We isolate conditions under which new phenomena, which we call exuberance equilibria, can exist in a standard self-referential environment. Local indeterminacy is not a requirement for existence. We construct a simple asset-pricing example and find that exuberance equilibria, when they exist, can be extremely volatile relative to fundamental equilibria.

By endowing his agents with simple forecasting models, or representations, M. Woodford (“Learning to Believe in Sunspots,” Econometrica 58, 277–307, 1990) found that finite state Markov sunspot equilibria may be stable under learning. We show that common factor representations generalize to all sunspot equilibria the representations used by Woodford. We find that if finite state Markov sunspots are stable under learning then all sunspots are stable under learning, provided common factor representations are used.

Rare pebbles of granite have been discovered in the raised Patella beach at Butterslade, Gower, South Wales. Their petrography, trace element geochemistry and the Rb/Sr whole rock age of 55 ± 5 Ma confirm that they are derived from the Lundy granite which is about 49 km to the southwest of Gower. Amino acid analyses of fossil gastropods in the Patella beach have provided an age of 210000 years. Various hypotheses of transportation of pebbles from Lundy and Pembrokeshire to Butterslade are considered. Erratics from Pembrokeshire were probably transported by Pleistocene ice into the area while clasts of Lundy granite were moved by progradation of beach deposits northeastwards towards Gower during glacio-eustatic marine transgressions in the Pleistocene.

We investigate both the rational explosive inflation paths studied by McCallum (2001), and the classification of fiscal and monetary policies proposed by Leeper (1991), for stability under least squares (LS) learning of the rational expectations equilibria (REE). Our first result is that the explosive fiscalist REE is not locally stable under LS learning. In contrast, in Leeper's setting, there are policy regimes for which the fiscalist solution, in which fiscal variables affect the price level, can be a locally stable outcome under LS learning. However, for other policy regimes the monetarist solution is, instead, the locally stable REE.

The rational expectations hypothesis swept through macroeconomics during the 1970s and permanently altered the landscape. It remains the prevailing paradigm in macroeconomics, and rational expectations is routinely used as the standard solution concept in both theoretical and applied macroeconomic modelling. The rational expectations hypothesis was initially formulated by John F. Muth Jr. in the early 1960s. Together with Robert Lucas Jr., Thomas (Tom) Sargent pioneered the rational expectations revolution in macroeconomics in the 1970s.