Direct poverty estimates from the EU-SILC are only reliable at the statistical area level, and thus at the NUTS-2 level. This complicates the analysis of poverty at more disaggregated levels since the reliability of direct estimates are questionable.
... See More + Data from the Census of Population, Households and Dwellings 2011 coupled with small area estimation techniques aide policy makers overcome the lack of precision at lower geographical levels. The results from the poverty mapping exercise, coupled with spatial analysis reveal the heterogeneity of poverty in Croatia. Results from spatial analysis reveal that there is a cluster of high poverty in the Central and Eastern region of Croatia. There is a clear poverty demarcation in the country, where the Central and Eastern part of the country is clearly doing worse than the rest of the country. Results also reveal that while the Continental NUTS-2 spatial unit, may seem poorer than the Adriatic, the result is mainly driven by the aggregation of the two statistical regions (Northwest, and the Central and Eastern statistical regions). The use of the poverty map in order to assist in the guidance of resource allocation can help policy makers achieve considerable gains in poverty reduction. Additionally, the visual format of the maps is simple to understand which makes it easy for the population at large to take notice of where their community stands compared to the rest of the country. Moreover, because the maps are based on established data sets, these are objective. As a result, the maps may help prevent subjective decision making. Given the mentioned uses of the poverty maps these are valuable component of the policymaker’s tool kit when trying to decide where limited funds can be distributed among the population which needs assistance.
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The 2015 Paris Climate Agreement was the first instance of countries adhering to take a collective action against global warming. More than 190 countries came forward and submitted their contributions in the form of Intended Nationally Determined Contributions, reflective of their ability and capacity to reduce greenhouse gas emissions, as each country set its own targets and actions.
... See More + For some countries, it meant a significant decline in their emissions by 2030, while others, like China, the United States, and India, decided on a more gradual phasing out extending beyond 2030. This paper estimates the economic impacts of implementation of the Paris Climate Agreement in terms of its implications for welfare, gross domestic product, investments, and trade for major countries and regions. It uses a computable general equilibrium framework to model global, regional, and country impacts. The analysis suggests that the economic impacts will be mostly felt in the European Union if the Paris Agreement is fully implemented. The European Union is likely to suffer a welfare loss of 1.0 to 1.5 percent by 2030. Among non-European countries, Australia, New Zealand, and Mexico will also be affected, with an expected welfare loss of about 1.5 percent. Some of the major emitters, such as China and India, will experience minimal impacts to their welfare, and the United States will experience a welfare loss of only about 0.7 by 2030. The sectoral analysis of production and trade suggests a significant loss to fossil fuel–based sectors, while clean energy sectors can experience significant gains.
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Policy Research Working Paper WPS8392 APR 02, 2018
Inclusive and sustainable growth requires innovative methods and policies to overcome unsustainable development practices. Breaking from the historic development model to promote clean growth is necessary to ensure that developing countries do not degrade their environment as their economies grow, yet the measurement of this factor remains elusive in development work.
... See More + To ease a shift in development practices, it is then crucial to develop meaningful measures of green growth to compare economic and environmental change over time. Here, the report presents a multi-stage exercise to understand green growth, beginning with benchmarking national environmental stocks and ambient conditions. The authors then develop an approach to observe decoupling trends between environmental externalities and economic growth to better understand how a country’s environmental and economic performance relate to one another at macroeconomic and sectoral levels. Based on the results of the baseline and decoupling exercises, the authors develop hypotheses to explain the observed relationships between economic and environmental indicators and the foundational factors that may underlie them. The authors explore these hypotheses through policy implications and methodological requirements, with the ultimate goal of explaining relationships related to developmental impacts on ecosystems. To illustrate this process, the authors focus on selected European Union (EU) countries, drawing upon and complimenting World Bank systematic country diagnostic reports for Romania, Croatia, and Poland. Through this exercise, the authors conclude that the examination of baseline conditions and decoupling are useful tools for informed policymaking, and that with the availability of further refined data, green growth analyses can move toward understanding causal relationships between economic growth and environmental impacts.
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