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Past studies on the relationship between electricity consumption and temperature have primarily focused on individual countries. Many regions are understudied as a result of data constraint. This paper studies the relationship on a global scale, overcoming the data constraint by using grid-level night light and temperature data. Mostly generated by electricity and recorded by satellites, night light has a strong linear relationship with electricity consumption and is correlated with both its extensive and intensive margins. Using night light as a proxy for electricity consumption at the grid level, we find: (1) there is a U-shaped relationship between electricity consumption and temperature; (2) the critical point of temperature for minimum electricity consumption is around 14.6°C for the world and it is higher in urban and more industrial areas; and (3) the impact of temperature on electricity consumption is persistent. Sub-Saharan African countries, while facing a large electricity deficit already, are particularly vulnerable to climate change: a 1°C increase in temperature is estimated to increase their electricity demand by 6.7% on average.

Brazil --- Investments: Energy --- Macroeconomics --- Environmental Economics --- Demography --- Climate --- Natural Disasters and Their Management --- Global Warming --- Regional Economic Activity: Growth, Development, and Changes --- Size and Spatial Distributions of Regional Economic Activity --- Electric Utilities --- Macroeconomics: Consumption --- Saving --- Wealth --- Demographic Economics: General --- Aggregate Factor Income Distribution --- Investment & securities --- Climate change --- Population & demography --- Electricity --- Consumption --- Population and demographics --- Income --- Electric utilities --- Economics --- Climatic changes --- Population

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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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To reach the global net-zero goal, the level of carbon emissions has to fall substantially at speed rarely seen in history, highlighting the need to identify structural breaks in carbon emission patterns and understand forces that could bring about such breaks. In this paper, we identify and analyze structural breaks using machine learning methodologies. We find that downward trend shifts in carbon emissions since 1965 are rare, and most trend shifts are associated with non-climate structural factors (such as a change in the economic structure) rather than with climate policies. While we do not explicitly analyze the optimal mix between climate and non-climate policies, our findings highlight the importance of the nonclimate policies in reducing carbon emissions. On the methodology front, our paper contributes to the climate toolbox by identifying country-specific structural breaks in emissions for top 20 emitters based on a user-friendly machine-learning tool and interpreting the results using a decomposition of carbon emission ( Kaya Identity).

United Kingdom --- Macroeconomics --- Economics: General --- Environmental Conservation and Protection --- Environmental Policy --- Environmental Economics --- Taxation --- Intelligence (AI) & Semantics --- 'Panel Data Models --- Spatio-temporal Models' --- Econometric Modeling: General --- Climate --- Natural Disasters and Their Management --- Global Warming --- Environmental Economics: Government Policy --- Taxation and Subsidies: Externalities --- Redistributive Effects --- Environmental Taxes and Subsidies --- Technological Change: Choices and Consequences --- Diffusion Processes --- Environmental Economics: General --- Economic & financial crises & disasters --- Economics of specific sectors --- Climate change --- Environmental policy & protocols --- Public finance & taxation --- Machine learning --- Environmental economics --- Greenhouse gas emissions --- Environment --- Climate policy --- Carbon tax --- Taxes --- Technology --- Currency crises --- Informal sector --- Economics --- Greenhouse gases --- Environmental policy --- Climatic changes --- Environmental impact charges --- Panel Data Models --- Spatio-temporal Models

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This paper explores the evolution of informality in Greece as it is widely considered one of the major structural impediments to fiscal capacity and sustainable growth. It finds that informality has dropped significantly in Greece in recent years, although there were temporary increases during the sovereign debt crisis and the COVID-19 pandemic. Lower informality is also found to be associated with higher subsequent per capita GDP growth and higher tax revenue. Moreover, Greece’s significant recent progress in digitalization appears to have helped reduce informality. There remains scope to further reduce informality by accelerating digitalization and the ongoing pro-growth structural reforms.

Aggregate Human Capital --- Aggregate Labor Productivity --- Diffusion Processes --- Digitalization --- Economic sectors --- Economic theory --- Economics of specific sectors --- Economics --- Employment --- Formal and Informal Sectors --- Income economics --- Industries: Information Technololgy --- Informal Economy --- Informal economy --- Informal sector --- Information technology industries --- Information technology --- Institutional Arrangements --- Intergenerational Income Distribution --- International agencies --- International Agreements and Observance --- International Economics --- International institutions --- International organization --- International Organizations --- Labor --- Labour --- Monetary economics --- Monetary Policy --- Monetary policy --- Money and Monetary Policy --- Public employment --- Public finance & taxation --- Public Finance --- Public Goods --- Regional Economic Activity: Growth, Development, and Changes --- Revenue administration --- Revenue --- Shadow Economy --- Tax Evasion and Avoidance --- Tax evasion --- Tax planning and compliance --- Taxation --- Taxation, Subsidies, and Revenue: General --- Technological Change: Choices and Consequences --- Technology --- Underground Econom --- Unemployment --- Wages --- Greece

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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.

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 --- China, People's Republic of