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This paper examines the status of GDP compilation in 189 economies against six key criteria that describe national accounts compilation practices: whether the benchmark year is up to date, the availability and timeliness of annual and quarterly GDP, whether GDP by production and expenditure approaches are compiled independently to allow for comparisons, whether estimates by the income approach are available, and the vintage of the System of National Accounts (SNA) applied. We used publicly available information including from the IMF’s Dissemination Standards Bulletin Board (DSBB), and, for 108 developing economies, information provided by the IMF’s real sector advisors stationed in the Fund’s 10 Regional Technical Assistance Centers (RTACs). The data were compared with the UNSD and World Bank databases. We find that 50 percent of economies have acceptable benchmark years, 72 percent report timely annual GDP data, while 55 percent of economies report timely data for quarterly GDP. The study presents some conclusions for priorities of capacity development.

Macroeconomics --- Public Finance --- Measurement and Data on National Income and Product Accounts and Wealth --- Environmental Accounts --- General Aggregative Models: General --- National Government Expenditures and Related Policies: General --- Public finance & taxation --- National accounts --- GDP measurement --- Expenditure --- National income --- Expenditures, Public --- Afghanistan, Islamic Republic of --- Gdp measurement

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This paper seeks to illuminate the uncertainty in official GDP per capita measures using auxiliary data. Using satellite-recorded nighttime lights as an additional measurement of true GDP per capita, we provide a statistical framework, in which the error in official GDP per capita may depend on the country’s statistical capacity and the relationship between nighttime lights and true GDP per capita can be nonlinear and vary with geographic location. This paper uses recently developed results for measurement error models to identify and estimate the nonlinear relationship between nighttime lights and true GDP per capita and the nonparametric distribution of errors in official GDP per capita data. We then construct more precise and robust measures of GDP per capita using nighttime lights, official national accounts data, statistical capacity, and geographic locations. We find that GDP per capita measures are less precise for middle and low income countries and nighttime lights can play a bigger role in improving such measures.

Economic development --- Development, Economic --- Economic growth --- Growth, Economic --- Economic policy --- Economics --- Statics and dynamics (Social sciences) --- Development economics --- Resource curse --- Evaluation. --- Macroeconomics --- Measurement and Data on National Income and Product Accounts and Wealth --- Environmental Accounts --- Macroeconomics: Production --- Methodological Issues: General --- Personal Income, Wealth, and Their Distributions --- Informal Economy --- Underground Econom --- General Aggregative Models: General --- Aggregate Factor Income Distribution --- Economics of specific sectors --- GDP measurement --- Personal income --- Informal economy --- National accounts --- Income --- Economic sectors --- National income --- Informal sector --- United States --- Gdp measurement

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Comprehensive coverage of national accounts estimates is important; however, it is often thwarted by gaps in the recording of economic activity – the so-called “unrecorded economy”. This paper sets out pragmatic statistical approaches for incorporating the unrecorded economy in the national accounts. It describes sources and methods to capture the unrecorded economy and discusses specific issues that arise from the use of indirect sources and techniques. Furthermore, the paper elaborates approaches for collecting data on the unrecorded economy, particularly on economic activities of the household sector.

Macroeconomics --- Databases --- Survey Methods --- Methodology for Collecting, Estimating, and Organizing Macroeconomic Data --- Data Access --- Measurement of Economic Growth --- Aggregate Productivity --- Cross-Country Output Convergence --- General Aggregative Models: General --- Labor Economics: General --- Data Collection and Data Estimation Methodology --- Computer Programs: General --- Macroeconomics: Consumption --- Saving --- Wealth --- Measurement and Data on National Income and Product Accounts and Wealth --- Environmental Accounts --- Labour --- income economics --- Data capture & analysis --- National accounts --- Labor --- Data collection --- Consumption --- GDP measurement --- National income --- Labor economics --- Economic statistics --- Economics --- Gdp measurement --- Income economics

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Forecasting a macroframework, which consists of many macroeconomic variables and accounting identities, is widely conducted in the policy arena to present an economic narrative and check its consistency. Such forecasting, however, is challenging because forecasters should extend limited information to the entire macroframework in an internally consistent manner. This paper proposes a method to systematically forecast macroframework by integrating (1) conditional forecasting with machine-learning techniques and (2) forecast reconciliation of hierarchical time series. We apply our method to an advanced economy and a tourism-dependent economy using France and Seychelles and show that it can improve the WEO forecast.

Seychelles --- Macroeconomics --- Economics: General --- Exports and Imports --- Forecasting and Other Model Applications --- General Aggregative Models: Forecasting and Simulation --- Forecasting and Simulation: Models and Applications --- Current Account Adjustment --- Short-term Capital Movements --- Measurement and Data on National Income and Product Accounts and Wealth --- Environmental Accounts --- General Aggregative Models: General --- Economic & financial crises & disasters --- Economics of specific sectors --- International economics --- Current account balance --- Balance of payments --- GDP measurement --- National accounts --- Currency crises --- Informal sector --- Economics --- National income --- Gdp measurement

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This paper presents a novel framework to estimate the elasticity between nighttime lights and quarterly economic activity. The relationship is identified by accounting for varying degrees of measurement errors in nighttime light data across countries. The estimated elasticity is 1.55 for emerging markets and developing economies, ranging from 1.36 to 1.81 across country groups and robust to different model specifications. The paper uses a light-adjusted measure of quarterly economic activity to show that higher levels of development, statistical capacity, and voice and accountability are associated with more precise national accounts data. The elasticity allows quantification of subnational economic impacts. During the COVID-19 pandemic, regions with higher levels of development and population density experienced larger declines in economic activity.

China, People's Republic of --- Macroeconomics --- Economics: General --- Diseases: Contagious --- Demography --- Econometrics --- Econometric and Statistical Methods: General --- Measurement and Data on National Income and Product Accounts and Wealth --- Environmental Accounts --- Size and Spatial Distributions of Regional Economic Activity --- Health Behavior --- General Aggregative Models: General --- Demographic Economics: General --- Time-Series Models --- Dynamic Quantile Regressions --- Dynamic Treatment Effect Models --- Diffusion Processes --- Economic & financial crises & disasters --- Economics of specific sectors --- Infectious & contagious diseases --- Population & demography --- Econometrics & economic statistics --- COVID-19 --- Health --- National accounts --- GDP measurement --- Population and demographics --- Vector autoregression --- Econometric analysis --- Currency crises --- Informal sector --- Economics --- Communicable diseases --- National income --- Population --- Covid-19 --- Gdp measurement