Oligarchs, political regime changes, and firm valuation

This paper examines the impact of a regime shift on the valuation of politically powerful oligarch firms. Focusing on the Yeltsin-Putin regime shift in Russia, we find that the valuations of outside shareholders claims are significantly higher under the Putin regime than under the Yeltsin regime after controlling for industry and time effects. The findings suggest that the increasing cost of extracting private benefits outweigh the reduction in the value of political connections following the political regime change. The results are also consistent with changes in the risk of state expropriation. Our results show that effects driven by the political regime change complement the traditional view stating that increased ownership concentration improved the performance of Russian oligarch firms.

Evolution of extrafloral nectaries: adaptive process and selective regime changes from forest to savanna

Much effort has been devoted to understanding the function of extrafloral nectaries (EFNs) for antplantherbivore interactions. However, the pattern of evolution of such structures throughout the history of plant lineages remains unexplored. In this study, we used empirical knowledge on plant defences mediated by ants as a theoretical framework to test specific hypotheses about the adaptive role of EFNs during plant evolution. Emphasis was given to different processes (neutral or adaptive) and factors (habitat change and trade-offs with new trichomes) that may have affected the evolution of antplant associations. We measured seven EFN quantitative traits in all 105 species included in a well-supported phylogeny of the tribe Bignonieae (Bignoniaceae) and collected field data on antEFN interactions in 32 species. We identified a positive association between ant visitation (a surrogate of ant guarding) and the abundance of EFNs in vegetative plant parts and rejected the hypothesis of phylogenetic conservatism of EFNs, with most traits presenting K-values < 1. Modelling the evolution of EFN traits using maximum likelihood approaches further suggested adaptive evolution, with static-optimum models showing a better fit than purely drift models. In addition, the abundance of EFNs was associated with habitat shifts (with a decrease in the abundance of EFNs from forest to savannas), and a potential trade-off was detected between the abundance of EFNs and estipitate glandular trichomes (i.e. trichomes with sticky secretion). These evolutionary associations suggest divergent selection between species as well as explains K-values < 1. Experimental studies with multiple lineages of forest and savanna taxa may improve our understanding of the role of nectaries in plants. Overall, our results suggest that the evolution of EFNs was likely associated with the adaptive process which probably played an important role in the diversification of this plant group.

Temporal changes in plankton of the North Sea: community shifts and environmental drivers

This paper analyses long-term and seasonal changes in the North Sea plankton community during the period 1970 to 2008. Based on Continuous Plankton Recorder (CPR) data covering 38 yr, major changes in both phytoplankton and zooplankton abundance and community structure were identified. Regime changes were detected around 1978, 1989 and 1998. The first 2 changes have been discussed in the literature and are defined as a cold episodic event (1978) and a regime shift towards a warm dynamic regime (1989). The effect of these 2 regime changes on plankton indicators was assessed and checked against previous studies. The 1998 change represents a shift in the abundance and seasonal patterns of dinoflagellates and the dominant zooplankton group, the neritic copepods. Furthermore, environmental factors such as air temperature, wind speed and the North Atlantic water inflow were identified as potential drivers of change in seasonal patterns, and the most-likely environmental causes for detected changes were assessed. We suggest that a change in the balance of dissolved nutrients driven by these environmental factors was the cause of the latest change in plankton community structure, which in turn could have affected the North Sea fish community.

Price discovery using a regime-sensitive cointegration approach

This work proposes a method to examine variations in the cointegration relation between preferred and common stocks in the Brazilian stock market via Markovian regime switches. It aims on contributing for future works in "pairs trading" and, more specifically, to price discovery, given that, conditional on the state, the system is assumed stationary. This implies there exists a (conditional) moving average representation from which measures of "information share" (IS) could be extracted. For identification purposes, the Markov error correction model is estimated within a Bayesian MCMC framework. Inference and capability of detecting regime changes are shown using a Montecarlo experiment. I also highlight the necessity of modeling financial effects of high frequency data for reliable inference.

Visualisation of complex flows using texture-based techniques

Complex flow datasets are often difficult to represent in detail using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows (i.e., complex dynamics and time-dependent). In this paper, we review two popular texture-based techniques and their application to flow datasets sourced from real research projects. The texture-based techniques investigated were Line Integral Convolution (LIC), and Image-Based Flow Visualisation (IBFV). We evaluated these techniques and in this paper report on their visualisation effectiveness (when compared with traditional techniques), their ease of implementation, and their computational overhead.

Visualisation of complex flows using texture-based techniques

Detailed representations of complex flow datasets are often difficult to generate using traditional vector visualisation techniques such as arrow plots and streamlines. This is particularly true when the flow regime changes in time. Texture-based techniques, which are based on the advection of dense textures, are novel techniques for visualising such flows. We review two popular texture based techniques and their application to flow datasets sourced from active research projects. The techniques investigated were Line integral convolution (LIC) [1], and Image based flow visualisation (IBFV) [18]. We evaluated these and report on their effectiveness from a visualisation perspective. We also report on their ease of implementation and computational overheads.

Dynamic Bayesian network inferencing for non-homogeneous complex systems

Dynamic Bayesian Networks (DBNs) provide a versatile platform for predicting and analysing the behaviour of complex systems. As such, they are well suited to the prediction of complex ecosystem population trajectories under anthropogenic disturbances such as the dredging of marine seagrass ecosystems. However, DBNs assume a homogeneous Markov chain whereas a key characteristics of complex ecosystems is the presence of feedback loops, path dependencies and regime changes whereby the behaviour of the system can vary based on past states. This paper develops a method based on the small world structure of complex systems networks to modularise a non-homogeneous DBN and enable the computation of posterior marginal probabilities given evidence in forwards inference. It also provides an approach for an approximate solution for backwards inference as convergence is not guaranteed for a path dependent system. When applied to the seagrass dredging problem, the incorporation of path dependency can implement conditional absorption and allows release from the zero state in line with environmental and ecological observations. As dredging has a marked global impact on seagrass and other marine ecosystems of high environmental and economic value, using such a complex systems model to develop practical ways to meet the needs of conservation and industry through enhancing resistance and/or recovery is of paramount importance.

Recovery of fish and crustacean communities during remediation of tidal wetlands affected by leachate from acid sulfate soils in north-eastern Australia.

In the 1970s, acid sulfate soils (ASS) distributed within about 720 ha of predominantly mangrove and salt pan wetlands at East Trinity in north Queensland were developed after the area was isolated from tidal flooding by a surrounding seawall and the installation of tidal gates on major drainage creeks. Following drainage and oxidation of these estuarine acidic sediments, resultant acid leachate caused considerable, ongoing environmental problems including regular fish kills. A rehabilitation program covering much of these former tidal wetlands commenced in 2000 using a lime-assisted tidal exchange management regime. Changes in the established populations of estuarine fish and crustaceans were monitored in the two creeks (Firewood and Hills Creeks) where tidal flows were reinstated. In Firewood Creek between 2001 and 2005, there was a progressive increase in fish species richness, diversity and abundance. The penaeid prawn Fenneropenaeus merguiensis was a major component of the cast net catches in the lower sections of both Firewood and Hills Creeks but its relative abundance decreased upstream of the tidal gates on the seawall. Well established stocks of predominantly juvenile, male Scylla serrata resident upstream of the tidal gates indicated suitable habitats with acceptable water and sediment quality and adequate availability of food. The regular fish kills that occurred prior to the management regime abated and, overall, the implementation of the rehabilitation program is yielding positive benefits for the local fisheries.

Mass Distribution Studies in Effervescent Sprays

An experimental study on liquid mass distribution in effervescent sprays using water and air as working fluids is presented in this paper. Optical patternation and techniques of image processing are employed for analyzing the spray. The flow regime inside the effervescent atomizer largely dictates the mass distribution patterns. The patterns are seen to vary from concentrated, poorly atomized liquid lumps to uniformly distributed, fine droplets as the flow regime changes from bubbly flow to annular flow. A large variety of instantaneous spray patterns are observed in bubbly flow regime indicating a highly unsteady atomization process. However, relatively better consistency in spray patterns is observed at higher gas flow rates. Thus, the degree of unsteadiness gradually diminishes as gas flow rate is increased. The axial evolution of the spray in annular mode shows good mixing of liquid and gas across the interface.

The changing behaviour of the term structure of post-war US

Using U.S. interest rate data covering the period 1950:1-1992:7, this paper tests the rational expectations model of the term structure of interest rates. We show evidence that the rational expectations model of the term structure is supported by the data during the seventies and a period lasting from the mid-eighties to the end of the sample. However, during the …fties, sixties and a period that covers most of the Volcker’s office term (from September 1979 to April 1986) the term structure model is rejected by the data. Moreover, wefind evidence of regime changes in the short-term rate process and the term structure of interest rates. These regime switches roughly coincide with changes in the Federal Reserve chairman. The switches in monetary policy taking place when the chairmanship of the Federal Reserve changes therefore seem to play an important role in characterizing the term structure of interest rates.

Credibility and Signaling in Disinflation- a Cross Country Examination

This paper develops a model of money demand where the opportunity cost of holding money is subject to regime changes. The regimes are fully characterized by the mean and variance of inflation and are assumed to be the result of alternative government policies. Agents are unable to directly observe whether government actions are indeed consistent with the inflation rate targeted as part of a stabilization program but can construct probability inferences on the basis of available observations of inflation and money growth. Government announcements are assumed to provide agents with additional, possibly truthful information regarding the regime. This specification is estimated and tested using data from the Israeli and Argentine high inflation periods. Results indicate the successful stabilization program implemented in Israel in July 1985 was more credible than either the earlier Israeli attempt in November 1984 or the Argentine programs. Government’s signaling might substantially simplify the inference problem and increase the speed of learning on the part of the agents. However, under certain conditions, it might increase the volatility of inflation. After the introduction of an inflation stabilization plan, the welfare gains from a temporary increase in real balances might be high enough to induce agents to raise their real balances in the short-term, even if they are uncertain about the nature of government policy and the eventual outcome of the stabilization attempt. Statistically, the model restrictions cannot be rejected at the 1% significance level.

Permutation entropy based real-time chatter detection using audio signal in turning process

Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).

The effect of doubled CO2 and model basic state biases on the monsoon-ENSO system. II: Changing ENSO regimes

Integrations of a fully-coupled climate model with and without flux adjustments in the equatorial oceans are performed under 2×CO2 conditions to explore in more detail the impact of increased greenhouse gas forcing on the monsoon-ENSO system. When flux adjustments are used to correct some systematic model biases, ENSO behaviour in the modelled future climate features distinct irregular and periodic (biennial) regimes. Comparison with the observed record yields some consistency with ENSO modes primarily based on air-sea interaction and those dependent on basinwide ocean wave dynamics. Simple theory is also used to draw analogies between the regimes and irregular (stochastically forced) and self-excited oscillations respectively. Periodic behaviour is also found in the Asian-Australian monsoon system, part of an overall biennial tendency of the model under these conditions related to strong monsoon forcing and increased coupling between the Indian and Pacific Oceans. The tropospheric biennial oscillation (TBO) thus serves as a useful descriptor for the coupled monsoon-ENSO system in this case. The presence of obvious regime changes in the monsoon-ENSO system on interdecadal timescales, when using flux adjustments, suggests there may be greater uncertainty in projections of future climate, although further modelling studies are required to confirm the realism and cause of such changes.

Thermodynamic analysis of snowball Earth hysteresis experiment: Efficiency, entropy production and irreversibility

We present an extensive thermodynamic analysis of a hysteresis experiment performed on a simplified yet Earth-like climate model. We slowly vary the solar constant by 20% around the present value and detect that for a large range of values of the solar constant the realization of snowball or of regular climate conditions depends on the history of the system. Using recent results on the global climate thermodynamics, we show that the two regimes feature radically different properties. The efficiency of the climate machine monotonically increases with decreasing solar constant in present climate conditions, whereas the opposite takes place in snowball conditions. Instead, entropy production is monotonically increasing with the solar constant in both branches of climate conditions, and its value is about four times larger in the warm branch than in the corresponding cold state. Finally, the degree of irreversibility of the system, measured as the fraction of excess entropy production due to irreversible heat transport processes, is much higher in the warm climate conditions, with an explosive growth in the upper range of the considered values of solar constants. Whereas in the cold climate regime a dominating role is played by changes in the meridional albedo contrast, in the warm climate regime changes in the intensity of latent heat fluxes are crucial for determining the observed properties. This substantiates the importance of addressing correctly the variations of the hydrological cycle in a changing climate. An interpretation of the climate transitions at the tipping points based upon macro-scale thermodynamic properties is also proposed. Our results support the adoption of a new generation of diagnostic tools based on the second law of thermodynamics for auditing climate models and outline a set of parametrizations to be used in conceptual and intermediate-complexity models or for the reconstruction of the past climate conditions. Copyright © 2010 Royal Meteorological Society

Wildfire responses to abrupt climate change in North America

It is widely accepted, based on data from the last few decades and on model simulations, that anthropogenic climate change will cause increased fire activity. However, less attention has been paid to the relationship between abrupt climate changes and heightened fire activity in the paleorecord. We use 35 charcoal and pollen records to assess how fire regimes in North America changed during the last glacial–interglacial transition (15 to 10 ka), a time of large and rapid climate changes. We also test the hypothesis that a comet impact initiated continental-scale wildfires at 12.9 ka; the data do not support this idea, nor are continent-wide fires indicated at any time during deglaciation. There are, however, clear links between large climate changes and fire activity. Biomass burning gradually increased from the glacial period to the beginning of the Younger Dryas. Although there are changes in biomass burning during the Younger Dryas, there is no systematic trend. There is a further increase in biomass burning after the Younger Dryas. Intervals of rapid climate change at 13.9, 13.2, and 11.7 ka are marked by large increases in fire activity. The timing of changes in fire is not coincident with changes in human population density or the timing of the extinction of the megafauna. Although these factors could have contributed to fire-regime changes at individual sites or at specific times, the charcoal data indicate an important role for climate, and particularly rapid climate change, in determining broad-scale levels of fire activity.