Computation and Analysis of Multiple Structural-Change Models

In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T 2) for any number of breaks. Our method can be applied to both pure and partial structural-change models. Secondly, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. We present simulation results pertaining to the behavior of the estimators and tests in finite samples. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program available upon request for non-profit academic use.

Social change models in social marketing

'This is essential reading for social marketing practitioners, researchers and students. the book describes a comprehensive range of behavior change theories of relevance to social marketing and is complemented with illustrative case ...

Multiple structural change models:a simulation analysis

In a reccnt paper. Bai and Perron (1998) considcrccl theoretical issues relatec\ lo lhe limiting distriblltion of estimators and test. statist.ics in the linear model \\'ith multiplc struct ural changes. \Ve assess. via simulations, the adequacy of the \'arious I1Iethods suggested. These CO\'er the size and power of tests for structural changes. the cO\'erage rates of the confidence Íntervals for the break dates and the relat.Í\'e merits of methods to select the I1umber of breaks. The \'arious data generating processes considered alIo,,' for general conditions OIl the data and the errors including differellces across segmcll(s. Yarious practical recommendations are made.

Why have land use change models for the Amazon failed to capture the amount of deforestation over the last decade?

Land cover change in the Neotropics represents one of the major drivers of global environmental change. Several models have been proposed to explore future trajectories of land use and cover change, particularly in the Amazon. Despite the remarkable development of these tools, model results are still surrounded by uncertainties. None of the model projections available in the literature plausibly captured the overall trajectory of land use and cover change that has been observed in the Amazon over the last decade. In this context, this study aims to review and analyze the general structure of the land use models that have most recently been used to explore land use change in the Amazon, seeking to investigate methodological factors that could explain the divergence between the observed and projected rates, paying special attention to the land demand calculations. Based on this review, the primary limitations inherent to this type of model and the extent to which these limitations can affect the consistency of the projections will also be analyzed. Finally, we discuss potential drivers that could have influenced the recent dynamic of the land use system in the Amazon and produced the unforeseen land cover change trajectory observed in this period. In a complementary way, the primary challenges of the new generation of land use models for the Amazon are synthesized. (c) 2014 Elsevier Ltd. All rights reserved.

Climate change, water resources, and the politics of adaptation in the Middle East and North Africa

Through an examination of global climate change models combined with hydrological data on deteriorating water quality in the Middle East and North Africa (MENA), we elucidate the ways in which the MENA countries are vulnerable to climate-induced impacts on water resources. Adaptive governance strategies, however, remain a low priority for political leaderships in the MENA region. To date, most MENA governments have concentrated the bulk of their resources on large-scale supply side projects such as desalination, dam construction, inter-basin water transfers, tapping fossil groundwater aquifers, and importing virtual water. Because managing water demand, improving the efficiency of water use, and promoting conservation will be key ingredients in responding to climate-induced impacts on the water sector, we analyze the political, economic, and institutional drivers that have shaped governance responses. While the scholarly literature emphasizes the importance of social capital to adaptive governance, we find that many political leaders and water experts in the MENA rarely engage societal actors in considering water risks. We conclude that the key capacities for adaptive governance to water scarcity in MENA are underdeveloped. © 2010 Springer Science+Business Media B.V.

Impacts of the Oceans on Climate Change

The oceans play a key role in climate regulation especially in part buffering (neutralising) the effects of increasing levels of greenhouse gases in the atmosphere and rising global temperatures. This chapter examines how the regulatory processes performed by the oceans alter as a response to climate change and assesses the extent to which positive feedbacks from the ocean may exacerbate climate change. There is clear evidence for rapid change in the oceans. As the main heat store for the world there has been an accelerating change in sea temperatures over the last few decades, which has contributed to rising sea‐level. The oceans are also the main store of carbon dioxide (CO2), and are estimated to have taken up ∼40% of anthropogenic-sourced CO2 from the atmosphere since the beginning of the industrial revolution. A proportion of the carbon uptake is exported via the four ocean ‘carbon pumps’ (Solubility, Biological, Continental Shelf and Carbonate Counter) to the deep ocean reservoir. Increases in sea temperature and changing planktonic systems and ocean currents may lead to a reduction in the uptake of CO2 by the ocean; some evidence suggests a suppression of parts of the marine carbon sink is already underway. While the oceans have buffered climate change through the uptake of CO2 produced by fossil fuel burning this has already had an impact on ocean chemistry through ocean acidification and will continue to do so. Feedbacks to climate change from acidification may result from expected impacts on marine organisms (especially corals and calcareous plankton), ecosystems and biogeochemical cycles. The polar regions of the world are showing the most rapid responses to climate change. As a result of a strong ice–ocean influence, small changes in temperature, salinity and ice cover may trigger large and sudden changes in regional climate with potential downstream feedbacks to the climate of the rest of the world. A warming Arctic Ocean may lead to further releases of the potent greenhouse gas methane from hydrates and permafrost. The Southern Ocean plays a critical role in driving, modifying and regulating global climate change via the carbon cycle and through its impact on adjacent Antarctica. The Antarctic Peninsula has shown some of the most rapid rises in atmospheric and oceanic temperature in the world, with an associated retreat of the majority of glaciers. Parts of the West Antarctic ice sheet are deflating rapidly, very likely due to a change in the flux of oceanic heat to the undersides of the floating ice shelves. The final section on modelling feedbacks from the ocean to climate change identifies limitations and priorities for model development and associated observations. Considering the importance of the oceans to climate change and our limited understanding of climate-related ocean processes, our ability to measure the changes that are taking place are conspicuously inadequate. The chapter highlights the need for a comprehensive, adequately funded and globally extensive ocean observing system to be implemented and sustained as a high priority. Unless feedbacks from the oceans to climate change are adequately included in climate change models, it is possible that the mitigation actions needed to stabilise CO2 and limit temperature rise over the next century will be underestimated.

Climate Change Adaptation for Conservation in Madagascar

Madagascar's imperilled biota are now experiencing the effects of a new threat—climate change (Raxworthy et al. 2008). With more than 90% endemism among plants, mammals, reptiles and amphibians, the stakes are high. The pristine landscapes that allowed this exceptional biodiversity to survive past climate changes are largely gone. Deforestation has claimed approximately 90% of the island's natural forest (Ingram & Dawson 2005; Harper et al. 2007) and what remains is highly fragmented, providing a poor template for large-scale species range shifts. The impacts of current and future climate change may therefore be much different than past impacts, with profound implications for biodiversity.
We review evidence of past response to climate change, models of future change and projected biological response, developing insights to formulate adaptation actions for reducing extinction in Madagascar's biota. We then explore the cost of implementing actions and examine new income opportunities developing through efforts to mitigate climate change.

Linking student evaluations to institutional goals : a change story

For the past 30 years, beginning with the seminal work of Herbert Marsh in Australia and New Zealand, institutions of higher education have developed internal practices and procedures to collect and analyse student evaluations of teaching and learning. However, the question remains: has this development resulted in the achievement of institutional goals that maximise learning across all teaching contexts? As is the case in many other countries, a recent review of Australian national student evaluation data failed to conclude that student evaluations have improved overall teaching. However, these data have made student perceptions of teaching and learning more salient in the minds of tertiary educators. Certainly, teaching staff are aware of the impacts of student evaluations on informed decision-making, such as the continuation or discontinuation of courses, and on their promotion processes. This paper will review student evaluation practices according to criteria used in change theories, such as the transtheoretical change model (TTM). TTM construes organisational change as a process involving progress through a series of five stages: precontemplation, contemplation, preparation, action and maintenance. This paper will focus on organisational and behavioural outcomes that can be linked to the use of student data. It will recommend strategies for better aligning evaluation results to the stages of change.

The Effects of Climate Change on Algae in the Denver Metro Area's Drinking Water Reservoirs

Six Denver metro water reservoirs were sampled to see what types of algae were found, and what impact the algae would have on drinking water reservoirs in the event of a bloom caused by warming water temperatures. Each sample contained algae. Toxic cyanobacteria, filamentous green algae, and different species of diatoms were found in the samples. Current climate change models show the temperature along the Front Range is rising and will continue to rise. With an increase in climate change and an increase in population, humans and animals will be at a greater risk of ingesting or coming into contact with toxic algae.

The environmental impacts of technical change

The thesis is concerned with relationships between profit, technology and environmental change. Existing work has concentrated on only a few questions, treated at either micro or macro levels of analysis. And there has been something of an impasse since the neoclassical and neomarxist approaches are either in direct conflict (macro level), or hardly interact (micro level). The aim of the thesis was to bypass this impasse by starting to develop a meso level of analysis that focusses on issues largely ignored in the traditional approaches - on questions about distribution. The first questions looked at were descriptive - what were the patterns of distribution over time of the variability in types and rates of environmental change, and in particular, was there any evidence of periodization? Two case studies were used to examine these issues. The first looked at environmental change in the iron and steel industry since 1700, and the second studied pollution in five industries in the basic processing sector. It was established that environmental change has been markedly periodized, with an apparently fairly regular `cycle length' of about fifty years. The second questions considered were explanatory - whether and how this periodization could be accounted for by reference to variations in aspects of profitability and technical change. In the iron and steel industry, it was found that diffusion rates and the rate of nature of innovation were periodized on the same pattern as was environmental change. And the same sort of variation was also present in the realm of profits, as evidenced by cyclical changes in output growth. Simple theoretical accounts could be given for all the empirically demonstrable links, and it was suggested that the most useful models at this meso level of analysis are provided by structural change models of economic development.

Enfoque da estatística espacial em modelos dinâmicos de mudança do uso do solo.

O atual nível das mudanças uso do solo causa impactos nas mudanças ambientais globais. Os processos de mudanças do uso e cobertura do solo são processos complexos e não acontecem ao acaso sobre uma região. Geralmente estas mudanças são determinadas localmente, regionalmente ou globalmente por fatores geográficos, ambientais, sociais, econômicos e políticos interagindo em diversas escalas temporais e espaciais. Parte desta complexidade é capturada por modelos de simulação de mudanças do uso e cobertura do solo. Uma etapa do processo de simulação do modelo CLUE-S é a quantificação da influência local dos impulsores de mudança sobre a probabilidade de ocorrência de uma classe de uso do solo. Esta influência local é obtida ajustando um modelo de regressão logística. Um modelo de regressão espacial é proposto como alternativa para selecionar os impulsores de mudanças. Este modelo incorpora a informação da vizinhança espacial existente nos dados que não é considerada na regressão logística. Baseado em um cenário de tendência linear para a demanda agregada do uso do solo, simulações da mudança do uso do solo para a microbacia do Coxim, Mato Grosso do Sul, foram geradas, comparadas e analisadas usando o modelo CLUE-S sob os enfoques da regressão logística e espacial para o período de 2001 a 2011. Ambos os enfoques apresentaram simulações com muito boa concordância, medidas de acurácia global e Kappa altos, com o uso do solo para o ano de referência de 2004. A diferença entre os enfoques foi observada na distribuição espacial da simulação do uso do solo para o ano 2011, sendo o enfoque da regressão espacial que teve a simulação com menor discrepância com a demanda do uso do solo para esse ano.