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The costs from coastal storms and hurricanes are expected to increase with climate change yet populations in coastal areas continue to grow. In this paper, we develop a dynamic spatial simulation model of coastal land and housing markets and study the competing influences of storm risks and amenities. The model is parameterized to the Mid-Atlantic region of the United States, where hurricanes occur relatively infrequently, and then used to assess how spatial patterns of development would change if storm frequency increases. Results show that spatial patterns change very little—approximately 45 percent of the land area in the coastal region is developed by the final model period in both the baseline and high storm risk scenarios and the coast sees more development than inland areas in all scenarios. The countervailing coastal amenity matters more with the percent developed in the coastal region varying between 29 and 51 percent depending on the scenario. Perhaps more importantly, we find that heterogeneous households sort differently on the landscape in our different scenarios. When storms are more frequent, average land prices near the coast are 1.2–11.8 percent lower, which leads to households with lower average incomes locating there. The results highlight the difficulty policymakers may have in altering private land and housing market outcomes to reduce storm costs in coastal regions.

The costs from coastal storms and hurricanes are expected to increase with climate change yet populations in coastal areas continue to grow. In this paper, we develop a dynamic spatial simulation model of coastal land and housing markets and study the competing influences of storm risks and amenities. The model is parameterized to the Mid-Atlantic region of the United States, where hurricanes occur relatively infrequently, and then used to assess how spatial patterns of development would change if storm frequency increases. Results show that spatial patterns change very little—approximately 45 percent of the land area in the coastal region is developed by the final model period in both the baseline and high storm risk scenarios and the coast sees more development than inland areas in all scenarios. The countervailing coastal amenity matters more with the percent developed in the coastal region varying between 29 and 51 percent depending on the scenario. Perhaps more importantly, we find that heterogeneous households sort differently on the landscape in our different scenarios. When storms are more frequent, average land prices near the coast are 1.2–11.8 percent lower, which leads to households with lower average incomes locating there. The results highlight the difficulty policymakers may have in altering private land and housing market outcomes to reduce storm costs in coastal regions.

Bibliography: p. 28-31

Bibliography: p. 28-31

Bibliography: p. 28-31

Cities across sub-Saharan Africa experience rapidly-expanding markets, which serve as major hubs for economic activity across socio-economic classes. Despite tax and state-building potential, markets remain primarily within the informal economy. We examine marketers in Greater Monrovia, Liberia, where the state has attempted to formally register marketers under the Liberia Marketing Association. We conduct focus groups and administer a survey to answer three questions: (1) why do marketers actively choose to evade formalization (i.e., join the Liberia Marketing Association)? (2) when and why do marketers formalize when they do? (3) what are the effects of formalization on marketers' welfare and economic and political behavior? We embed two experimental components in our survey: (1) a conjoint experiment designed to identify formalization's effects on preferences for communal banking solutions (susu groups); and (2) a series of vignettes that probe the mechanisms that drive the choice to formalize.

Drawing on anthropology, historical sociology and social-epidemiology, this multidisciplinary book investigates how pharmaceuticals are produced, distributed, prescribed, (and) consumed, and regulated in order to construct a comprehensive understanding of the issues that drive (medicine) pharmaceutical markets in the Global South today. 　 Based on primary research conducted in Benin and Ghana, and additional data collected in Cambodia and the Ivory Coast, this volume uses artemisinin-based combination therapies (ACTs) against malaria as a central case study. It highlights the influence of the countries colonial and post-colonial history on their models for state regulation, production, and distribution, explores the determining role transnational actors as well as industries from the North but also and increasingly from the South play in influencing local pharmaceutical markets and looks at the behaviour of health care professionals and individuals. Stepping back, the authors then unpick the pharmaceuticalization process and the multiple regulations at stake by looking at the workings of, and linkages between, (biomedical health) pharmaceutical systems, (representatives of companies) industries, actors in private distribution, and consumer practices. 　 Providing a thorough comparative analysis of the advantages and disadvantages of different pharmaceutical systems, it is an important contribution to the literature on pharmaceutalization and the governance of medication. It is of interest to students, researchers and policy-makers interested in medical anthropology, the sociology of health and illness, global health, healthcare management and pharmacy. The Open Access version of this book, available at http://www.taylorfrancis.com/books/9780429329517, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

Drawing on anthropology, historical sociology and social-epidemiology, this multidisciplinary book investigates how pharmaceuticals are produced, distributed, prescribed, (and) consumed, and regulated in order to construct a comprehensive understanding of the issues that drive (medicine) pharmaceutical markets in the Global South today. 　 Based on primary research conducted in Benin and Ghana, and additional data collected in Cambodia and the Ivory Coast, this volume uses artemisinin-based combination therapies (ACTs) against malaria as a central case study. It highlights the influence of the countries colonial and post-colonial history on their models for state regulation, production, and distribution, explores the determining role transnational actors as well as industries from the North but also and increasingly from the South play in influencing local pharmaceutical markets and looks at the behaviour of health care professionals and individuals. Stepping back, the authors then unpick the pharmaceuticalization process and the multiple regulations at stake by looking at the workings of, and linkages between, (biomedical health) pharmaceutical systems, (representatives of companies) industries, actors in private distribution, and consumer practices. 　 Providing a thorough comparative analysis of the advantages and disadvantages of different pharmaceutical systems, it is an important contribution to the literature on pharmaceutalization and the governance of medication. It is of interest to students, researchers and policy-makers interested in medical anthropology, the sociology of health and illness, global health, healthcare management and pharmacy. The Open Access version of this book, available at http://www.taylorfrancis.com/books/9780429329517, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

Drawing on anthropology, historical sociology and social-epidemiology, this multidisciplinary book investigates how pharmaceuticals are produced, distributed, prescribed, (and) consumed, and regulated in order to construct a comprehensive understanding of the issues that drive (medicine) pharmaceutical markets in the Global South today. 　 Based on primary research conducted in Benin and Ghana, and additional data collected in Cambodia and the Ivory Coast, this volume uses artemisinin-based combination therapies (ACTs) against malaria as a central case study. It highlights the influence of the countries colonial and post-colonial history on their models for state regulation, production, and distribution, explores the determining role transnational actors as well as industries from the North but also and increasingly from the South play in influencing local pharmaceutical markets and looks at the behaviour of health care professionals and individuals. Stepping back, the authors then unpick the pharmaceuticalization process and the multiple regulations at stake by looking at the workings of, and linkages between, (biomedical health) pharmaceutical systems, (representatives of companies) industries, actors in private distribution, and consumer practices. 　 Providing a thorough comparative analysis of the advantages and disadvantages of different pharmaceutical systems, it is an important contribution to the literature on pharmaceutalization and the governance of medication. It is of interest to students, researchers and policy-makers interested in medical anthropology, the sociology of health and illness, global health, healthcare management and pharmacy. The Open Access version of this book, available at http://www.taylorfrancis.com/books/9780429329517, has been made available under a Creative Commons Attribution-Non Commercial-No Derivatives 4.0 license.

Cover title

Cover title

Cover title

This paper initiates a study into the century-old issue of market predictability from the perspective of computational complexity. We develop a simple agent-based model for a stock market where the agents are traders equipped with simple trading strategies, and their trades together determine the stock prices. Computer simulations show that a basic case of this model is already capable of generating price graphs which are visually similar to the recent price movements of high tech stocks. In the general model, we prove that if there are a large number of traders but they employ a relatively small number of strategies, then there is a polynomial-time algorithm for predicting future price movements with high accuracy. On the other hand, if the number of strategies is large, market prediction becomes complete in two new computational complexity classes CPP and BCPP, which are between P^NP[O(log n)] and PP. These computational completeness results open up a novel possibility that the price graph of an actual stock could be sufficiently deterministic for various prediction goals but appear random to all polynomial-time prediction algorithms.

In this paper, we use the generalized Hurst exponent approach to study the multi- scaling behavior of different financial time series. We show that this approach is robust and powerful in detecting different types of multiscaling. We observe a puzzling phenomenon where an apparent increase in multifractality is measured in time series generated from shuffled returns, where all time-correlations are destroyed, while the return distributions are conserved. This effect is robust and it is reproduced in several real financial data including stock market indices, exchange rates and interest rates. In order to understand the origin of this effect we investigate different simulated time series by means of the Markov switching multifractal (MSM) model, autoregressive fractionally integrated moving average (ARFIMA) processes with stable innovations, fractional Brownian motion and Levy flights. Overall we conclude that the multifractality observed in financial time series is mainly a consequence of the characteristic fat-tailed distribution of the returns and time-correlations have the effect to decrease the measured multifractality.

In this paper, we use the generalized Hurst exponent approach to study the multi- scaling behavior of different financial time series. We show that this approach is robust and powerful in detecting different types of multiscaling. We observe a puzzling phenomenon where an apparent increase in multifractality is measured in time series generated from shuffled returns, where all time-correlations are destroyed, while the return distributions are conserved. This effect is robust and it is reproduced in several real financial data including stock market indices, exchange rates and interest rates. In order to understand the origin of this effect we investigate different simulated time series by means of the Markov switching multifractal (MSM) model, autoregressive fractionally integrated moving average (ARFIMA) processes with stable innovations, fractional Brownian motion and Levy flights. Overall we conclude that the multifractality observed in financial time series is mainly a consequence of the characteristic fat-tailed distribution of the returns and time-correlations have the effect to decrease the measured multifractality.

In this paper, we use the generalized Hurst exponent approach to study the multi- scaling behavior of different financial time series. We show that this approach is robust and powerful in detecting different types of multiscaling. We observe a puzzling phenomenon where an apparent increase in multifractality is measured in time series generated from shuffled returns, where all time-correlations are destroyed, while the return distributions are conserved. This effect is robust and it is reproduced in several real financial data including stock market indices, exchange rates and interest rates. In order to understand the origin of this effect we investigate different simulated time series by means of the Markov switching multifractal (MSM) model, autoregressive fractionally integrated moving average (ARFIMA) processes with stable innovations, fractional Brownian motion and Levy flights. Overall we conclude that the multifractality observed in financial time series is mainly a consequence of the characteristic fat-tailed distribution of the returns and time-correlations have the effect to decrease the measured multifractality.