13 Results

Dados Observacionais Financial Sector

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  • Dataset

    By Department of Research and Chief Economist (VPS/RES/RES)
    This is the data used for the estimation of the GVAR model as in "China's Emergence in the World Economy and Business Cycles in Latin America" (access the study in the related URL Section). The dataset includes quarterly data for twenty-five major advanced and emerging economies plus the euro area, covering more than 90 percent of world GDP. The variables included in the dataset are real GDP, CPI inflation, real equity prices, real exchange rates, short-term and long-term interest rates, and the price of oil. Updates of this dataset -together with the baseline GVAR code- can be found in the Related URL section below. Years covered: 1979 - 2009.
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  • Dataset

    By Department of Research and Chief Economist (VPS/RES/RES)
    This dataset contains the tables and figures for the 2016 edition of Development in the Americas. Book description: Why should people--and economies--save? The typical answer usually focuses on the need to protect against future shocks, to smooth consumption during hard times, in short, to save for the proverbial rainy day. This book approaches the question from a slightly different angle. While saving to survive the bad times is important, saving to thrive in the good times is what really counts. People must save so they can invest in their own and their children's health and education, live productive fulfilling lives, and end their days in comfort and peace. Firms must save so they can grow productive enterprises that employ more workers in better jobs to produce quality goods for domestic and international markets. Governments must save to build bridges, highways, and airports that support a productive economy, to provide quality services such as education, health, water, and...
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  • Dataset

    By Health, Nutrition and Population Division (VPS/SCL/HNP)
    The Technical Note "Setting Targets for Results-Based Financing Programs: A Simple Cost Benefit Framework" is accompanied by this Excel tool for the calculation of targets according to the simple framework presented. As an example, the case of El Salvador from the Salud Mesoamerica 2015 initiative is used in the file. The sources of information for this particular example were the latest available at the time of the exercise.
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  • Dataset

    By Fiscal Management Division (VPS/IFD/FMM)
    The database allows estimating structural fiscal balances for 20 countries in the region under different assumptions regarding the output gap and commodity structural prices. It is a unique database of its kind since: 1) It takes into consideration the distinct responsiveness of different types of revenues to changes in the output gap: In order to adjust for the impact of the business cycle on revenues, we calculate individual elasticities for each source of revenue (i.e. direct taxes, indirect taxes, revenues from non-renewable resources, etc.). Since the different types of revenues in the region have different sensitivities to changes in the output gap, this disaggregated approach allows for a more fine-tuned adjustment. 2) It includes estimations of SFBs based on output gaps projections available in real time. In addition to giving estimations of the actual SFBs, we provide with estimations of the SFBs that would have resulted should the projections on output gaps available to...
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  • Dataset

    By IDB Lab (IDB Lab)
    This benchmarking index evaluates the legal, regulatory and operating environments for public-private partnerships in transport and water infrastructure for 19 Latin American and Caribbean countries. The analysis and scores in the model provide a comparable assesssment of individual countries' readiness and facility for PPP project design and implementation. They also provide a regional ranking for each country, allowing investors and policy advocates to focus on strengths and weaknesses.
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