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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
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Illuminating Economic Growth.
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Unemployment rates in countries across the world are typically positively correlated with GDP. China is an unusual outlier from the pattern, with abnormally low, and suspiciously stable, unemployment rates according to its official statistics. This paper calculates, for the first time, China's unemployment rate from 1988 to 2009 using a more reliable, nationally representative household survey in China. The unemployment rates we calculate differ dramatically from those supplied in official data and are much more consistent with what is known about China's labor market and how it has changed over time in response to structural changes and other significant events. The rate averaged 3.9% in 1988-1995, when the labor market was highly regulated and dominated by state-owned enterprises, but rose sharply during the period of mass layoff from 1995- 2002, reaching an average of 10.9% in the subperiod from 2002 to 2009. We can also calculate labor force participation rates, which are not available in official statistics at all. We find that they declined throughout the whole period, particularly in 1995-2002 when the unemployment rate increased most significantly. We also report results for different demographic groups, different regions, and different cohorts.
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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
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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
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Unemployment rates in countries across the world are typically positively correlated with GDP. China is an unusual outlier from the pattern, with abnormally low, and suspiciously stable, unemployment rates according to its official statistics. This paper calculates, for the first time, China's unemployment rate from 1988 to 2009 using a more reliable, nationally representative household survey in China. The unemployment rates we calculate differ dramatically from those supplied in official data and are much more consistent with what is known about China's labor market and how it has changed over time in response to structural changes and other significant events. The rate averaged 3.9% in 1988-1995, when the labor market was highly regulated and dominated by state-owned enterprises, but rose sharply during the period of mass layoff from 1995- 2002, reaching an average of 10.9% in the subperiod from 2002 to 2009. We can also calculate labor force participation rates, which are not available in official statistics at all. We find that they declined throughout the whole period, particularly in 1995-2002 when the unemployment rate increased most significantly. We also report results for different demographic groups, different regions, and different cohorts.
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