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What happens if an employer cuts wages by one cent? Much of labor economics is built on the assumption that all the workers will quit immediately. Here, Alan Manning mounts a systematic challenge to the standard model of perfect competition.Monopsony in Motionstands apart by analyzing labor markets from the real-world perspective that employers have significant market (or monopsony) power over their workers. Arguing that this power derives from frictions in the labor market that make it time-consuming and costly for workers to change jobs, Manning re-examines much of labor economics based on this alternative and equally plausible assumption. The book addresses the theoretical implications of monopsony and presents a wealth of empirical evidence. Our understanding of the distribution of wages, unemployment, and human capital can all be improved by recognizing that employers have some monopsony power over their workers. Also considered are policy issues including the minimum wage, equal pay legislation, and caps on working hours. In a monopsonistic labor market, concludes Manning, the \"free\" market can no longer be sustained as an ideal and labor economists need to be more open-minded in their evaluation of labor market policies.Monopsony in Motionwill represent for some a new fundamental text in the advanced study of labor economics, and for others, an invaluable alternative perspective that henceforth must be taken into account in any serious consideration of the subject.

This book looks at the distribution of income and wealth and the effects that this has on the macroeconomy, and vice versa. Is a more equal distribution of income beneficial or harmful for macroeconomic growth, and how does the distribution of wealth evolve in a market economy? Taking stock of results and methods developed in the context of the 1990s revival of growth theory, the authors focus on capital accumulation and long-run growth. They show how rigorous, optimization-based technical tools can be applied, beyond the representative-agent framework of analysis, to account for realistic market imperfections and for political-economic interactions. The treatment is thorough, yet accessible to students and nonspecialist economists, and it offers specialist readers a wide-ranging and innovative treatment of an increasingly important research field. The book follows a single analytical thread through a series of different growth models, allowing readers to appreciate their structure and crucial assumptions. This is particularly useful at a time when the literature on income distribution and growth has developed quickly and in several different directions, becoming difficult to overview.

This book shows how current and recent market prices convey information about the probability distributions that govern future prices. Moving beyond purely theoretical models, Stephen Taylor applies methods supported by empirical research of equity and foreign exchange markets to show how daily and more frequent asset prices, and the prices of option contracts, can be used to construct and assess predictions about future prices, their volatility, and their probability distributions. Stephen Taylor provides a comprehensive introduction to the dynamic behavior of asset prices, relying on finance theory and statistical evidence. He uses stochastic processes to define mathematical models for price dynamics, but with less mathematics than in alternative texts. The key topics covered include random walk tests, trading rules, ARCH models, stochastic volatility models, high-frequency datasets, and the information that option prices imply about volatility and distributions. Asset Price Dynamics, Volatility, and Predictionis ideal for students of economics, finance, and mathematics who are studying financial econometrics, and will enable researchers to identify and apply appropriate models and methods. It will likewise be a valuable resource for quantitative analysts, fund managers, risk managers, and investors who seek realistic expectations about future asset prices and the risks to which they are exposed.

Understanding the mechanisms driving biological diversity remains a central problem in ecology and evolutionary biology. Traditional explanations assume that differences in selection pressures lead to different adaptations in geographically separated locations. This book takes a different approach and explores adaptive diversification--diversification rooted in ecological interactions and frequency-dependent selection. In any ecosystem, birth and death rates of individuals are affected by interactions with other individuals. What is an advantageous phenotype therefore depends on the phenotype of other individuals, and it may often be best to be ecologically different from the majority phenotype. Such rare-type advantage is a hallmark of frequency-dependent selection and opens the scope for processes of diversification that require ecological contact rather than geographical isolation.

Quantification of the disease burden caused by different risks informs prevention by providing an account of health loss different to that provided by a disease-by-disease analysis. No complete revision of global disease burden caused by risk factors has been done since a comparative risk assessment in 2000, and no previous analysis has assessed changes in burden attributable to risk factors over time. We estimated deaths and disability-adjusted life years (DALYs; sum of years lived with disability [YLD] and years of life lost [YLL]) attributable to the independent effects of 67 risk factors and clusters of risk factors for 21 regions in 1990 and 2010. We estimated exposure distributions for each year, region, sex, and age group, and relative risks per unit of exposure by systematically reviewing and synthesising published and unpublished data. We used these estimates, together with estimates of cause-specific deaths and DALYs from the Global Burden of Disease Study 2010, to calculate the burden attributable to each risk factor exposure compared with the theoretical-minimum-risk exposure. We incorporated uncertainty in disease burden, relative risks, and exposures into our estimates of attributable burden. In 2010, the three leading risk factors for global disease burden were high blood pressure (7·0% [95% uncertainty interval 6·2–7·7] of global DALYs), tobacco smoking including second-hand smoke (6·3% [5·5–7·0]), and household air pollution from solid fuels (4·3% [3·4–5·3]). In 1990, the leading risks were childhood underweight (7·9% [6·8–9·4]), household air pollution from solid fuels (HAP; 6·8% [5·5–8·0]), and tobacco smoking including second-hand smoke (6·1% [5·4–6·8]). Dietary risk factors and physical inactivity collectively accounted for 10·0% (95% UI 9·2–10·8) of global DALYs in 2010, with the most prominent dietary risks being diets low in fruits and those high in sodium. Several risks that primarily affect childhood communicable diseases, including unimproved water and sanitation and childhood micronutrient deficiencies, fell in rank between 1990 and 2010, with unimproved water and sanitation accounting for 0·9% (0·4–1·6) of global DALYs in 2010. However, in most of sub-Saharan Africa childhood underweight, HAP, and non-exclusive and discontinued breastfeeding were the leading risks in 2010, while HAP was the leading risk in south Asia. The leading risk factor in Eastern Europe, Andean Latin America, and southern sub-Saharan Africa in 2010 was alcohol use; in most of Asia, most of Latin America, North Africa and Middle East, and central Europe it was high blood pressure. Despite declines, tobacco smoking including second-hand smoke remained the leading risk in high-income north America and western Europe. High body-mass index has increased globally and it is the leading risk in Australasia and southern Latin America, and also ranks high in other high-income regions, North Africa and Middle East, and Oceania. Worldwide, the contribution of different risk factors to disease burden has changed substantially, with a shift away from risks for communicable diseases in children towards those for non-communicable diseases in adults. These changes are related to the ageing population, decreased mortality among children younger than 5 years, changes in cause-of-death composition, and changes in risk factor exposures. New evidence has led to changes in the magnitude of key risks including unimproved water and sanitation, vitamin A and zinc deficiencies, and ambient particulate matter pollution. The extent to which the epidemiological shift has occurred and what the leading risks currently are varies greatly across regions. In much of sub-Saharan Africa, the leading risks are still those associated with poverty and those that affect children. Bill & Melinda Gates Foundation.

Flotation process modelling is not a simple task, mostly because of the process complexity, i.e. the presence of a large number of variables that (to a lesser or a greater extent) affect the final outcome of the mineral particles separation based on the differences in their surface properties. The attempts toward the development of the quantitative predictive model that would fully describe the operation of an industrial flotation plant started in the middle of past century and it lasts to this day. This paper gives a review of published research activities directed toward the development of flotation models based on the classical mathematical rules. The description and systematization of classical flotation models were performed according to the available references, with emphasize exclusively given to the flotation process modelling, regardless of the model application in a certain control system. In accordance with the contemporary considerations, models were classified as the empirical, probabilistic, kinetic and population balance types. Each model type is presented through the aspects of flotation modelling at the macro and micro process levels.

Statistics in Medicine, Third Edition makes medical statistics easy to understand by students, practicing physicians, and researchers.The book begins with databases from clinical medicine and uses such data to give multiple worked-out illustrations of every method.

Dreams, conceived as conscious experience or phenomenal states during sleep, offer an important contrast condition for theories of consciousness and the self. Yet, although there is a wealth of empirical research on sleep and dreaming, its potential contribution to consciousness research and philosophy of mind is largely overlooked. This might be due, in part, to a lack of conceptual clarity and an underlying disagreement about the nature of the phenomenon of dreaming itself. InDreaming, Jennifer Windt lays the groundwork for solving this problem. She develops a conceptual framework describing not only what it means to say that dreams are conscious experiences but also how to locate dreams relative to such concepts as perception, hallucination, and imagination, as well as thinking, knowledge, belief, deception, and self-consciousness.Arguing that a conceptual framework must be not only conceptually sound but also phenomenologically plausible and carefully informed by neuroscientific research, Windt integrates her review of philosophical work on dreaming, both historical and contemporary, with a survey of the most important empirical findings. This allows her to work toward a systematic and comprehensive new theoretical understanding of dreaming informed by a critical reading of contemporary research findings. Windt's account demonstrates that a philosophical analysis of the concept of dreaming can provide an important enrichment and extension to the conceptual repertoire of discussions of consciousness and the self and raises new questions for future research.

Anomalies of the El Niño/Southern Oscillation in the Pacific Ocean and the Indian Ocean Dipole often occur simultaneously. An analysis of observations and models suggests that, in addition, the negative phase of the Indian Ocean Dipole tends to occur 14 months before an El Niño event, with implications for El Niño predictability. El Niño-Southern Oscillation (ENSO) consists of irregular episodes of warm El Niño and cold La Niña conditions in the tropical Pacific Ocean 1 , with significant global socio-economic and environmental impacts 1 . Nevertheless, forecasting ENSO at lead times longer than a few months remains a challenge 2 , 3 . Like the Pacific Ocean, the Indian Ocean also shows interannual climate fluctuations, which are known as the Indian Ocean Dipole 4 , 5 . Positive phases of the Indian Ocean Dipole tend to co-occur with El Niño, and negative phases with La Niña 6 , 7 , 8 , 9 . Here we show using a simple forecast model that in addition to this link, a negative phase of the Indian Ocean Dipole anomaly is an efficient predictor of El Niño 14 months before its peak, and similarly, a positive phase in the Indian Ocean Dipole often precedes La Niña. Observations and model analyses suggest that the Indian Ocean Dipole modulates the strength of the Walker circulation in autumn. The quick demise of the Indian Ocean Dipole anomaly in November–December then induces a sudden collapse of anomalous zonal winds over the Pacific Ocean, which leads to the development of El Niño/La Niña. Our study suggests that improvements in the observing system in the Indian Ocean region and better simulations of its interannual climate variability will benefit ENSO forecasts.

This book provides the first clear, comprehensive, and accessible account of complex adaptive social systems, by two of the field's leading authorities. Such systems--whether political parties, stock markets, or ant colonies--present some of the most intriguing theoretical and practical challenges confronting the social sciences. Engagingly written, and balancing technical detail with intuitive explanations,Complex Adaptive Systemsfocuses on the key tools and ideas that have emerged in the field since the mid-1990s, as well as the techniques needed to investigate such systems. It provides a detailed introduction to concepts such as emergence, self-organized criticality, automata, networks, diversity, adaptation, and feedback. It also demonstrates how complex adaptive systems can be explored using methods ranging from mathematics to computational models of adaptive agents. John Miller and Scott Page show how to combine ideas from economics, political science, biology, physics, and computer science to illuminate topics in organization, adaptation, decentralization, and robustness. They also demonstrate how the usual extremes used in modeling can be fruitfully transcended.