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The reality of climate change associated with anthropogenic emissions is now widely acknowledged by the scientific community. Its potential devastating future harms are equally well perceived and as stated in the Copenhagen Accord major nations agree on the need to jointly and urgently combat climate change. The international community is also quite aware that stabilizing atmospheric concentrations of green-house gases (GHG) at supportable levels will require a drastic reduction in GHG emissions within a limited period of time. Undertaking such an enormous effort triggers several interlinked challenges: (1) technically mitigating GHG emissions to the required level; (2) implementing these solutions in countries where the required amount of emission reduction is most realistically and efficiently achievable in particular through involving and using in full the large potential of developing countries; and (3) mobilizing the large amount of financing needed to ensure that the corresponding projects and programs can be effectively implemented. Furthermore, these challenges must be simultaneously addressed in a way that is acceptable to all the parties involved. This means in particulars that any arrangement designed to meet the global GHG emission reduction challenge must be consistent with the principle of the common but differentiated responsibilities of developed and developing countries.

In this study, we present a comparative assessment of simulation-optimization (S-O) models to estimate aquifer parameters such as transmissivity, longitudinal dispersivity, and transverse dispersivity. The groundwater flow and contaminant transport processes are simulated using the mesh-free radial basis point collocation method (RPCM). Four different S-O models are developed by combining the RPCM model separately with genetic algorithm (GA), differential evolution (DE), cat swarm optimization (CSO), and particle swarm optimization (PSO). The objective of the S-O model is to minimize a composite objective function with transmissivity, longitudinal dispersivity, and transverse dispersivity as decision variables. Hydraulic head and contaminant concentration at observation points are the state variables. The S-O models are used to estimate aquifer parameters of a confined aquifer with nine zones. It is found that RPCM-based DE, CSO, and PSO models are more accurate in estimating aquifer parameters than RPCM-GA. However, for noisy observed data, the RPCM-CSO model outperforms other models. The efficiency of the RPCM-CSO model over other models is further established by performing reliability analysis to the noisy observed data set. The comparative study reflects the efficacy of CSO over GA, DE, and PSO.

Understanding the dynamic evolution of the yield curve is critical to many financial tasks, including pricing financial assets and their derivatives, managing financial risk, allocating portfolios, structuring fiscal debt, conducting monetary policy, and valuing capital goods. Unfortunately, most yield curve models tend to be theoretically rigorous but empirically disappointing, or empirically successful but theoretically lacking. In this book, Francis Diebold and Glenn Rudebusch propose two extensions of the classic yield curve model of Nelson and Siegel that are both theoretically rigorous and empirically successful. The first extension is the dynamic Nelson-Siegel model (DNS), while the second takes this dynamic version and makes it arbitrage-free (AFNS). Diebold and Rudebusch show how these two models are just slightly different implementations of a single unified approach to dynamic yield curve modeling and forecasting. They emphasize both descriptive and efficient-markets aspects, they pay special attention to the links between the yield curve and macroeconomic fundamentals, and they show why DNS and AFNS are likely to remain of lasting appeal even as alternative arbitrage-free models are developed. Based on the Econometric and Tinbergen Institutes Lectures,Yield Curve Modeling and Forecastingcontains essential tools with enhanced utility for academics, central banks, governments, and industry.

This study aims to help governments design sustainable Public-Private Partnership (PPP) strategies and projects in the context of the changed circumstances brought on by the global financial and economic crisis that began in the fall of 2008. The study analyses the impact and implication of the crisis on PPP infrastructure projects across the Europe and Central Asia (ECA) region. In the research undertaken for this study, it appears that most crisis-specific issues are cross-sectoral, therefore requiring cross-sectoral responses. The intended audience for this report includes national government stakeholders involved in infrastructure financing, including Ministries in charge of infrastructure, especially transport, energy, and water; state-owned enterprises with operational responsibilities, such as road directorates; and Ministries of Finance and development banks involved in PPP. This report reviewed the region's experience in PPPs in infrastructure before and during the financial crisis period (from late 2006 to 2010). Since not all ECA countries have had successful or ongoing PPP projects during this time, the report draws on lessons from Brazil, India, Spain, and the United Kingdom, countries with established PPP project pipelines to draw on cross-sectoral lessons. The findings can be used by countries wishing to start or re-start their PPP program following the impact of the recent crisis. However, beyond the crisis and its effects, the report can also guide future development of sustainable and crisis-resilient PPP programs. Most of the analysis supporting the report recommendations was undertaken for the highway sector and was financed through from a grant from the transport research support program. Initially, the highway sector was the focus of this study but the scope was later widened to include all infrastructure sectors because most issues facing highway PPP projects are common to other sectors requiring a cross-sectoral approach to PPP. Sector-specific strategies for highways have been documented in a recent World Bank study.

Financial markets respond to information virtually instantaneously. Each new piece of information influences the prices of assets and their correlations with each other, and as the system rapidly changes, so too do correlation forecasts. This fast-evolving environment presents econometricians with the challenge of forecasting dynamic correlations, which are essential inputs to risk measurement, portfolio allocation, derivative pricing, and many other critical financial activities. In Anticipating Correlations, Nobel Prize-winning economist Robert Engle introduces an important new method for estimating correlations for large systems of assets: Dynamic Conditional Correlation (DCC). Engle demonstrates the role of correlations in financial decision making, and addresses the economic underpinnings and theoretical properties of correlations and their relation to other measures of dependence. He compares DCC with other correlation estimators such as historical correlation, exponential smoothing, and multivariate GARCH, and he presents a range of important applications of DCC. Engle presents the asymmetric model and illustrates it using a multicountry equity and bond return model. He introduces the new FACTOR DCC model that blends factor models with the DCC to produce a model with the best features of both, and illustrates it using an array of U.S. large-cap equities. Engle shows how overinvestment in collateralized debt obligations, or CDOs, lies at the heart of the subprime mortgage crisis--and how the correlation models in this book could have foreseen the risks. A technical chapter of econometric results also is included.

Housing finance markets have been changing dramatically in both emerging and developed economies. On the one hand, housing finance markets are expanding and represent a powerful engine for economic growth in many emerging economies. However, the unfolding sub-prime mortgage crisis highlights the risks and potential turbulence that this sector can introduce into the financial system when expanding without proper infrastructure and regulation. As housing finance keeps growing in emerging economies to match a rising demand for housing, new risk management approaches, business models, funding tools, and policy instruments can help. Yet many questions remain about the right balance between innovation and regulation, the extent of risks to the financial system, the appropriate role of the state to promote affordable housing, and the effects of the sub-prime crisis. This book provides a guide for policymakers dealing with housing finance in emerging markets. It highlights the prerequisites for an effective housing finance system; it lays out several policy alternatives and models of housing finance; and it explores the role of governments in expanding access to housing finance for lower-income households. There is no \"best\" model set out in this book. The aim is to provide a developmental roadmap that can be tailored and sequenced to each country's situation and timing.

This study documents the effects of the 2008–09 global financial crisis on poverty in Latin America and the Caribbean (LAC). In doing so, it describes and decomposes the effects of the crisis on poverty using data from comparable household budget surveys for Argentina, Brazil, Chile, Colombia, Costa Rica, Dominican Republic, Ecuador, El Salvador, Mexico, Paraguay, Peru, and Uruguay, and labor force surveys for Argentina, Brazil, Chile, Colombia, Ecuador, Mexico, Peru, and Uruguay. The study also provides macro-micro modeling of crisis and no-crisis scenarios for Mexico and Brazil, as well as the big picture and program-specific details of the social protection policy responses for these countries and more. Among the findings are the following. First, the effects of the global financial crisis on those living in poverty were not trivial: more than 3 million people fell into or remained mired in poverty in 2009 as a result of the crisis. Of these, 2.5 million were Mexican. Second, the changes in poverty were driven by changes in labor incomes caused by a variable combination of changes in employment rates and real wages. Third, the macro-micro modeling revealed different adjustment mechanisms but similar final incidence results for Brazil and Mexico. The results were regressive overall, with the middle of the income distribution hit even a bit more than the poor. According to the descriptive results from the larger set of countries, changes in inequality accounted for a tenth to a third of changes in poverty. Fourth, countries were quite active in their social protection policy responses, largely taking advantage of programs built in precrisis years. Social transfers partially offset the lower labor earnings of the poor, although income protection for the unemployed was weak. Finally, overall the policy messages are that good policy helps attenuate the links between a global crisis and poverty in the LAC countries, and many of the important things need to be done ex ante such as dealing with the macro fundamentals and building social protection programs.

The 2008 financial crisis has highlighted the challenges associated with global financial integration and emphasized the importance of macro financial linkages. In the financial sector, attention is being directed toward macro prudential regulations that are geared toward the stability of the financial system as a whole. The Third Basel Accord (Basel III) aims to dampen the pro-cyclicality of the financial sector and to reduce cross sectional systemic risks partly by introducing measures to address liquidity and issues of banks being too big to fail. In the macro arena, the facts that price stability was not sufficient to guarantee macroeconomic stability and that financial imbalances developed despite low inflation and small output gaps have highlighted the need for additional tools (macro prudential policies) to complement monetary policy in countercyclical management. Emerging markets face different conditions and have key structural features that can have a bearing on the relevance and efficacy of the measures. The chapters in this volume discuss the challenges of dealing with macro financial linkages and explore the policy toolkit available for dealing with systemic risks with particular reference to emerging markets. This report is organized as follows: chapter one is adapting macro prudential approaches to emerging and developing economies; chapter two is adapting micro prudential regulation for emerging markets; chapter three presents capital flow volatility and systemic risk in emerging markets: the policy toolkit; chapter four presents monetary policy and macro prudential regulation: whither emerging markets; chapter five deals with macro prudential policies to mitigate financial vulnerabilities in emerging markets; chapter six presents sailing through the global financial storm; and chapter seven presents operation of macro prudential policy measures.

Portfolio risk forecasting has been and continues to be an active research field for both academics and practitioners. Almost all institutional investment management firms use quantitative models for their portfolio forecasting, and researchers have explored models' econometric foundations, relative performance, and implications for capital market behavior and asset pricing equilibrium.Portfolio Risk Analysisprovides an insightful and thorough overview of financial risk modeling, with an emphasis on practical applications, empirical reality, and historical perspective. Beginning with mean-variance analysis and the capital asset pricing model, the authors give a comprehensive and detailed account of factor models, which are the key to successful risk analysis in every economic climate. Topics range from the relative merits of fundamental, statistical, and macroeconomic models, to GARCH and other time series models, to the properties of the VIX volatility index. The book covers both mainstream and alternative asset classes, and includes in-depth treatments of model integration and evaluation. Credit and liquidity risk and the uncertainty of extreme events are examined in an intuitive and rigorous way. An extensive literature review accompanies each topic. The authors complement basic modeling techniques with references to applications, empirical studies, and advanced mathematical texts. This book is essential for financial practitioners, researchers, scholars, and students who want to understand the nature of financial markets or work toward improving them.

This country program evaluation (CPE) evaluates World Bank Group (International Bank for Reconstruction and Development (IBRD), or the Bank, International Finance Corporation (IFC), and Multilateral Investment Guarantee Agency (MIGA) operations in Brazil from FY2004 through FY2011. It seeks to answer two questions: to what extent was the Bank Group program relevant to Brazil's development needs?, and how effective were Bank Group operations in helping to accelerate economic growth and making growth more inclusive and environmentally sustainable? The period reviewed was covered by two country strategies, one for FY2004-07 and the other for FY2008-11. The evaluation comments on aspects of the country partnership strategy (CPS) FY2012-15 with particular reference to its relevance and design. The report aims to extract lessons relevant to future Bank Group operations in Brazil. The study also examines the synergies between lending and knowledge services and the effectiveness of collaboration within the Bank Group and with external development partners. This report has five chapters. Chapter one gives purpose and country context. Chapter two summarizes the Bank Group operations and examines trends and patterns during the evaluation period. Chapters three and four assess the relevance and contributions of these operations to the objectives stated in the country strategies. The concluding chapter draws lessons and recommendations for the Bank Group's future engagement in Brazil.