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Data for a Greener World
The book presents a structured discussion of measuring the key economic and financial dimensions of climate change. It combines economic theory and analysis with real world examples of how climate data can be constructed for different country settings, based on existing climate science and economic data. The book will serve as a reference point for the IMF’s Climate Change Indicators Dashboard (CID). A guiding principle of the book is that there are important climate data gaps, but also practical and innovative approaches to close many of them. The book discusses how to track greenhouse gas emissions by production and consumption (Chapters 1-2), which lead to physical risks (Chapters 3-4) and transition risks (Chapters 5-7) and conclude with cross-border dimensions of climate risks (Chapters 8-9).
Measuring the Informal Economy
This paper proposes a framework for measuring the informal economy that is consistent with internationally agreed concepts and methodology for measuring GDP. Based on the proposed framework, the informal economy “comprises production of informal sector units, production of goods for own final use, production of domestic workers, and production generated by informal employment in formal enterprises.” This proposed framework will facilitate preparation of estimates of the informal economy as a component of GDP.
Big Data
Big data are part of a paradigm shift that is significantly transforming statistical agencies, processes, and data analysis. While administrative and satellite data are already well established, the statistical community is now experimenting with structured and unstructured human-sourced, process-mediated, and machine-generated big data. The proposed SDN sets out a typology of big data for statistics and highlights that opportunities to exploit big data for official statistics will vary across countries and statistical domains. To illustrate the former, examples from a diverse set of countries are presented. To provide a balanced assessment on big data, the proposed SDN also discusses the key challenges that come with proprietary data from the private sector with regard to accessibility, representativeness, and sustainability. It concludes by discussing the implications for the statistical community going forward.
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Special Purpose Entities
The Note is meant to assist compilers in the practical application of the agreed defini¬tion to identify resident Special Purpose Entities (SPE) in their jurisdictions and in collecting and reporting SPE-related cross-border data. To this end, these guidelines provide practical advice on the (1) implementa¬tion of the definition of SPEs, (2) possible data sources and processes for collecting and compiling SPE-related statistics, and (3) reporting within the agreed Data Template.
