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  • 1
    Online Resource
    Online Resource
    Credit Worthy : ESG Factors and Sovereign Credit Ratings (2022)
    Washington, D.C : The World Bank
    Details
    UID:
    b3kat_BV049080755
    Format: 1 Online-Ressource
    Series Statement: Other papers
    Content: The increasing role of the financial sector in the move toward a more sustainable economic model continues apace. The Coronavirus (COVID-19) shock shone a light on the need for all society to correct course, and the financial sector is responding. The pace of environmental, social, and governance (ESG) integration into investment decisions, which has become the prevalent form of sustainable finance, continues to accelerate. These developments reflect changing societal perspectives that challenge the traditionally ingrained investment approaches that have evolved over many decades. Against this backdrop, various financial sector stakeholders continue to evaluate how their role, products, and tools should adapt to this evolving landscape. This paper focuses on sovereign credit ratings and empirically assesses how broad sovereign ESG factors as well as the ESG factors specific to a country's national wealth and management of risks and opportunities related to so-called stranded assets like fossil fuel resources are manifested in sovereign credit rating assessments
    Language: English
    DOI: 10.1596/36866
    DOI: 10.1596/36866
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Deutschlandweit zugänglich
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    UB Potsdam
    EUV Frankfurt
    HTW Berlin
    MPI Bildungsforschung
  • 2
    Online Resource
    Online Resource
    Natural Capital and Sovereign Bonds (2021)
    Washington, D.C : The World Bank
    Details
    UID:
    b3kat_BV049081861
    Format: 1 Online-Ressource (44 Seiten)
    Content: Natural capital is related to government bonds through the macroeconomy and credit risks. This paper estimates this relationship from the long-term, between-country view and the short-term, within-country view. The paper cautions against the former, as it is dominated by income differences. These are de facto ingrained, as they cannot be overcome by short-term policy efforts. The within-country view is unaffected by the ingrained income bias and leaves room for recent natural capital changes to affect bond yields. The paper finds that non-renewables (fossil fuels and mineral assets) raise bond yields, possibly due to the resource curse. Renewables (forests and agricultural wealth) lower borrowing costs because they are economically worthwhile investments. Protected areas are more likely to be luxury investments
    Language: English
    DOI: 10.1596/1813-9450-9606
    DOI: 10.1596/1813-9450-9606
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Deutschlandweit zugänglich
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    UB Potsdam
    EUV Frankfurt
    HTW Berlin
    MPI Bildungsforschung
  • 3
    Online Resource
    Online Resource
    Demystifying Sovereign ESG (2020)
    Washington, D.C : The World Bank
    Details
    UID:
    b3kat_BV049081666
    Format: 1 Online-Ressource
    Series Statement: Other Environmental Study
    Content: The evolution of sustainable finance to mainstream finance has been motivated by a growing demand for the financial sector to play a greater role in the transformation of the current economic model into a more sustainable one. The introduction of the United Nation's (UN) Sustainable Development Goals and the Paris Agreement on climate change in 2015 have helped galvanize a societal shift to ensure a sustainable future and to fight climate change in particular. As a result, the pace of environmental, social, and governance (ESG) integration, which has become the most prevalent form of sustainable finance, has accelerated in recent years. Market participants continue to grapple with adapting the ESG framework to the sovereign context, despite significant progress of ESG integration in the corporate bond and equity asset class. This challenge is due to the multifaceted nature of ESG-related issues facing governments in relation to corporate entities, as well as a more complex transmission mechanism of the sovereign debt asset class to sustainable outcomes in the real economy. This paper demystifies sovereign ESG as a distinct segment of the ESG sector by assessing the major sovereign ESG providers that have laid the foundation for the operationalization of ESG investing in sovereign fixed income markets
    Language: English
    DOI: 10.1596/35586
    DOI: 10.1596/35586
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Deutschlandweit zugänglich
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    MPI Bildungsforschung
  • 4
    Online Resource
    Online Resource
    A New Dawn : Rethinking Sovereign ESG (2021)
    Washington, D.C : The World Bank
    Details
    UID:
    b3kat_BV049081559
    Format: 1 Online-Ressource
    Series Statement: Other Environmental Study
    Content: Environmental, social, and governance (ESG) investing is quickly becoming ordre du jour in sovereign debt investing. There remains, however, lack of clarity around frameworks for scoring sovereign ESG performance, industry practices, and the definition of sustainability itself. This World Bank publication consists of two independent reports. The first part is written by the World Bank and takes stock of the current sovereign ESG investing framework and proposes improvements. The second part presents a survey on ESG practices among emerging market (EM) sovereign debt investors conducted by J.P. Morgan (JPM), which launched the first EM sovereign ESG index in 2018. This publication is a result of the World Bank's proactive engagement with stakeholders on pertinent sovereign ESG issues and is part of a publication series under the auspices of the Global Program on Sustainability (GPS)
    Language: English
    DOI: 10.1596/35753
    DOI: 10.1596/35753
    URL: Volltext  (URL des Erstveröffentlichers)
    URL: Deutschlandweit zugänglich
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  • 5
    Online Resource
    Online Resource
    Stochastic Modeling of Food Insecurity (2020)
    Washington, D.C : The World Bank
    Details
    UID:
    b3kat_BV048274852
    Format: 1 Online-Ressource (30 Seiten)
    Series Statement: World Bank E-Library Archive
    Content: Recent advances in food insecurity classification have made analytical approaches to predict and inform response to food crises possible. This paper develops a predictive, statistical framework to identify drivers of food insecurity risk with simulation capabilities for scenario analyses, risk assessment and forecasting purposes. It utilizes a panel vector-autoregression to model food insecurity distributions of 15 Sub-Saharan African countries between October 2009 and February 2019. Statistical variable selection methods are employed to identify the most important agronomic, weather, conflict and economic variables. The paper finds that food insecurity dynamics are asymmetric and past-dependent, with low insecurity states more likely to transition to high insecurity states than vice versa. Conflict variables are more relevant for dynamics in highly critical stages, while agronomic and weather variables are more important for less critical states. Food prices are predictive for all cases. A Bayesian extension is introduced to incorporate expert opinions through the use of priors, which lead to significant improvements in model performance
    Additional Edition: Erscheint auch als Druck-Ausgabe Wang, Dieter Stochastic Modeling of Food Insecurity Washington, D.C : The World Bank, 2020
    Language: English
    DOI: 10.1596/1813-9450-9413
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 6
    Online Resource
    Online Resource
    Predicting Food Crises (2020)
    Washington, D.C : The World Bank
    Details
    UID:
    b3kat_BV048274851
    Format: 1 Online-Ressource (35 Seiten)
    Series Statement: World Bank E-Library Archive
    Content: Globally, more than 130 million people are estimated to be in food crisis. These humanitarian disasters are associated with severe impacts on livelihoods that can reverse years of development gains. The existing outlooks of crisis-affected populations rely on expert assessment of evidence and are limited in their temporal frequency and ability to look beyond several months. This paper presents a statistical foresting approach to predict the outbreak of food crises with sufficient lead time for preventive action. Different use cases are explored related to possible alternative targeting policies and the levels at which finance is typically unlocked. The results indicate that, particularly at longer forecasting horizons, the statistical predictions compare favorably to expert-based outlooks. The paper concludes that statistical models demonstrate good ability to detect future outbreaks of food crises and that using statistical forecasting approaches may help increase lead time for action
    Additional Edition: Erscheint auch als Druck-Ausgabe Andree, Bo Pieter Johannes Predicting Food Crises Washington, D.C : The World Bank, 2020
    Language: English
    DOI: 10.1596/1813-9450-9412
    URL: Volltext  (URL des Erstveröffentlichers)
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  • 7
    Online Resource
    Online Resource
    Pollution and expenditures in a penalized vector spatial autoregressive time series model with data-driven networks (2019)
    Washington, DC, USA : World Bank Group, Environment and Natural Resources Global Practice
    Details
    UID:
    gbv_1666260363
    Format: 1 Online-Ressource (circa 57 Seiten) , Illustrationen
    Series Statement: Policy research working paper 8757
    Content: This paper introduces a Spatial Vector Autoregressive Moving Average (SVARMA) model in which multiple cross-sectional time series are modeled as multivariate, possibly fat-tailed, spatial autoregressive ARMA processes. The estimation requires specifying the cross-sectional spillover channels through spatial weights matrices. the paper explores a kernel method to estimate the network topology based on similarities in the data. It discusses the model and estimation, focusing on a penalized Maximum Likelihood criterion. The empirical performance of the estimator is explored in a simulation study. The model is used to study a spatial time series of pollution and household expenditure data in Indonesia. The analysis finds that the new model improves in terms of implied density, and better neutralizes residual correlations than the VARMA, using fewer parameters. The results suggest that growth in household expenditures precedes pollution reduction, particularly after the expenditures of poorer households increase; that increasing pollution is followed by reduced growth in expenditures, particularly reducing the growth of poorer households; and that there are significant spillovers from bottom-up growth in expenditures. The paper does not find evidence for top-down growth spillovers. Feedback between the identified mechanisms may contribute to pollution-poverty traps and the results imply that pollution damages are economically significant
    Additional Edition: Erscheint auch als Druck-Ausgabe Andree, Bo Pieter Johannes Pollution and Expenditures in a Penalized Vector Spatial Autoregressive Time Series Model with Data-Driven Networks Washington, D.C : The World Bank, 2019
    Language: English
    Keywords: Graue Literatur
    DOI: 10.1596/1813-9450-8757
    URL: Volltext  (lizenzpflichtig)
    URL: Deutschlandweit zugänglich
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    UB Potsdam
    MPI Bildungsforschung
  • 8
    Online Resource
    Online Resource
    Could Sustainability-Linked Bonds Incentivize Lower Deforestation in Brazil's Legal Amazon? (2023)
    Washington, D.C : The World Bank
    Details
    UID:
    gbv_1865873179
    Format: 1 Online-Ressource (34 pages)
    Content: This paper proposes a new relative evaluation and benchmarking framework for performance linked financing instruments. It argues that the carrots and sticks of sustainability-linked bonds should not use key performance indicators which are solely tied to outcomes. Instead, they should be based on its issuer's level of performance with respect to a target. The paper defines performance as the part of the outcome that the issuer can influence. Otherwise, the issuer may be rewarded or penalized for factors outside their control. In such a case, principal-agent theory would predict a dilution of the performance-based instrument's incentives. This framework is then applied to deforestation in Brazil's Legal Amazon and estimate performance by accounting for the real effective exchange rate, global commodity prices, and prevalent deforestation trends. The results show that policy efforts helped lower deforestation in the 2000s, even after accounting for external factors. The trend reversal and acceleration in deforestation since 2012 are partly due to weaker policy and macroeconomic factors. Based on these results, the paper proposes an Amazon sustainability-linked bond, which could allow for a more effective mechanism to incentivize policy efforts. The paper also introduces the feasibility and ambitiousness matrix to set sustainability performance targets. The matrix is used to define the terms low-hanging fruits and long shots and to discuss why such targets are subject to the risk of greenwashing
    Additional Edition: Erscheint auch als Druck-Ausgabe Wang, Dieter Could Sustainability-Linked Bonds Incentivize Lower Deforestation in Brazil's Legal Amazon? Washington, D.C. : The World Bank, 2023
    Language: English
    DOI: 10.1596/1813-9450-10558
    URL: Deutschlandweit zugänglich
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    UB Potsdam
    MPI Bildungsforschung
  • 9
    Online Resource
    Online Resource
    Predicting food crises (2020)
    [Washington, DC, USA] : World Bank Group, Fragility, Conflict and Violence Global Theme & Development Economics Vice Presidency
    Details
    UID:
    gbv_1743503679
    Format: 1 Online-Ressource (circa 35 Seiten) , Illustrationen
    Series Statement: Policy research working paper 9412
    Content: Globally, more than 130 million people are estimated to be in food crisis. These humanitarian disasters are associated with severe impacts on livelihoods that can reverse years of development gains. The existing outlooks of crisis-affected populations rely on expert assessment of evidence and are limited in their temporal frequency and ability to look beyond several months. This paper presents a statistical foresting approach to predict the outbreak of food crises with sufficient lead time for preventive action. Different use cases are explored related to possible alternative targeting policies and the levels at which finance is typically unlocked. The results indicate that, particularly at longer forecasting horizons, the statistical predictions compare favorably to expert-based outlooks. The paper concludes that statistical models demonstrate good ability to detect future outbreaks of food crises and that using statistical forecasting approaches may help increase lead time for action
    Additional Edition: Erscheint auch als Druck-Ausgabe Andree, Bo Pieter Johannes Predicting Food Crises Washington, D.C : The World Bank, 2020
    Language: English
    Keywords: Graue Literatur
    DOI: 10.1596/1813-9450-9412
    URL: lizenzpflichtig
    URL: Deutschlandweit zugänglich
    Author information: Kraay, Aart
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    MPI Bildungsforschung
  • 10
    Online Resource
    Online Resource
    Stochastic modeling of food insecurity (2020)
    [Washington, DC, USA] : World Bank Group, Fragility, Conflict and Violence Global Theme
    Details
    UID:
    gbv_174350389X
    Format: 1 Online-Ressource (circa 30 Seiten) , Illustrationen
    Series Statement: Policy research working paper 9413
    Content: Recent advances in food insecurity classification have made analytical approaches to predict and inform response to food crises possible. This paper develops a predictive, statistical framework to identify drivers of food insecurity risk with simulation capabilities for scenario analyses, risk assessment and forecasting purposes. It utilizes a panel vector-autoregression to model food insecurity distributions of 15 Sub-Saharan African countries between October 2009 and February 2019. Statistical variable selection methods are employed to identify the most important agronomic, weather, conflict and economic variables. The paper finds that food insecurity dynamics are asymmetric and past-dependent, with low insecurity states more likely to transition to high insecurity states than vice versa. Conflict variables are more relevant for dynamics in highly critical stages, while agronomic and weather variables are more important for less critical states. Food prices are predictive for all cases. A Bayesian extension is introduced to incorporate expert opinions through the use of priors, which lead to significant improvements in model performance
    Additional Edition: Erscheint auch als Druck-Ausgabe Wang, Dieter Stochastic Modeling of Food Insecurity Washington, D.C : The World Bank, 2020
    Language: English
    Keywords: Graue Literatur
    DOI: 10.1596/1813-9450-9413
    URL: lizenzpflichtig
    URL: Deutschlandweit zugänglich
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    UB Potsdam
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