How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19?
This paper presents evidence on the extent to which a set of real-time indicators tracked changes in gross domestic product across 142 countries in 2020. The real-time indicators include Google mobility, Google search trends, food price information...
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okr-10986-375492022-07-07T14:34:35Z How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19? Ten, Gi Khan Merfeld, Josh Newhouse, David Pape, Utz Tafere Hirfrfot, Kibrom COVID-19 REAL-TIME DATA GDP IMPACT ESTIMATION BIG DATA GOOGLE SEARCH TERM ANALYSIS ECONOMIC INDICATORS FROM BIG DATA AGGREGATED DATA ANALYSIS ANNUAL GDP VARIATION DATA GOOGLE MOBILITY DATA PANDEMIC AIR QUALITY IMPROVEMENT ECONOMIC COST OF COVID This paper presents evidence on the extent to which a set of real-time indicators tracked changes in gross domestic product across 142 countries in 2020. The real-time indicators include Google mobility, Google search trends, food price information, nitrogen dioxide, and nighttime lights. Google mobility and staple food prices both declined sharply in March and April, followed by a rapid recovery that returned to baseline levels by July and August. Mobility and staple food prices fell less in low-income countries. Nitrogen dioxide levels show a similar pattern, with a steep fall and rapid recovery in high-income and upper-middle-income countries but not in low-income and lower-middle-income countries. In April and May, Google search terms reflecting economic distress and religiosity spiked in some regions but not others. Data on nighttime lights show no clear drop in March outside East Asia. Linear models selected using the Least Absolute Shrinkage and Selection Operator explain about a third of the variation in annual gross domestic product growth rates across 72 countries. In a smaller subset of higher income countries, real-time indicators explain about 40 percent of the variation in quarterly gross domestic product growth. Overall, mobility and food price data, as well as pollution data in more developed countries, appeared to be best at capturing the widespread economic disruption experienced during the summer of 2020. The results indicate that these real-time indicators can track a substantial percentage of both annual and quarterly changes in gross domestic product. 2022-06-15T01:22:26Z 2022-06-15T01:22:26Z 2022-06 Working Paper http://documents.worldbank.org/curated/en/099348106132213539/IDU034674d8d08ccf04d860b5170b3cb8446db97 http://hdl.handle.net/10986/37549 English Policy Research Working Papers;10080 CC BY 3.0 IGO http://creativecommons.org/licenses/by/3.0/igo World Bank World Bank, Washington, DC Policy Research Working Paper Publications & Research |
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COVID-19 REAL-TIME DATA GDP IMPACT ESTIMATION BIG DATA GOOGLE SEARCH TERM ANALYSIS ECONOMIC INDICATORS FROM BIG DATA AGGREGATED DATA ANALYSIS ANNUAL GDP VARIATION DATA GOOGLE MOBILITY DATA PANDEMIC AIR QUALITY IMPROVEMENT ECONOMIC COST OF COVID |
spellingShingle |
COVID-19 REAL-TIME DATA GDP IMPACT ESTIMATION BIG DATA GOOGLE SEARCH TERM ANALYSIS ECONOMIC INDICATORS FROM BIG DATA AGGREGATED DATA ANALYSIS ANNUAL GDP VARIATION DATA GOOGLE MOBILITY DATA PANDEMIC AIR QUALITY IMPROVEMENT ECONOMIC COST OF COVID Ten, Gi Khan Merfeld, Josh Newhouse, David Pape, Utz Tafere Hirfrfot, Kibrom How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19? |
relation |
Policy Research Working Papers;10080 |
description |
This paper presents evidence on the
extent to which a set of real-time indicators tracked
changes in gross domestic product across 142 countries in
2020. The real-time indicators include Google mobility,
Google search trends, food price information, nitrogen
dioxide, and nighttime lights. Google mobility and staple
food prices both declined sharply in March and April,
followed by a rapid recovery that returned to baseline
levels by July and August. Mobility and staple food prices
fell less in low-income countries. Nitrogen dioxide levels
show a similar pattern, with a steep fall and rapid recovery
in high-income and upper-middle-income countries but not in
low-income and lower-middle-income countries. In April and
May, Google search terms reflecting economic distress and
religiosity spiked in some regions but not others. Data on
nighttime lights show no clear drop in March outside East
Asia. Linear models selected using the Least Absolute
Shrinkage and Selection Operator explain about a third of
the variation in annual gross domestic product growth rates
across 72 countries. In a smaller subset of higher income
countries, real-time indicators explain about 40 percent of
the variation in quarterly gross domestic product growth.
Overall, mobility and food price data, as well as pollution
data in more developed countries, appeared to be best at
capturing the widespread economic disruption experienced
during the summer of 2020. The results indicate that these
real-time indicators can track a substantial percentage of
both annual and quarterly changes in gross domestic product. |
format |
Working Paper |
author |
Ten, Gi Khan Merfeld, Josh Newhouse, David Pape, Utz Tafere Hirfrfot, Kibrom |
author_facet |
Ten, Gi Khan Merfeld, Josh Newhouse, David Pape, Utz Tafere Hirfrfot, Kibrom |
author_sort |
Ten, Gi Khan |
title |
How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19? |
title_short |
How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19? |
title_full |
How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19? |
title_fullStr |
How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19? |
title_full_unstemmed |
How Well Can Real-Time Indicators Track the Economic Impacts of a Crisis Like COVID-19? |
title_sort |
how well can real-time indicators track the economic impacts of a crisis like covid-19? |
publisher |
World Bank, Washington, DC |
publishDate |
2022 |
url |
http://documents.worldbank.org/curated/en/099348106132213539/IDU034674d8d08ccf04d860b5170b3cb8446db97 http://hdl.handle.net/10986/37549 |
_version_ |
1764487437949599744 |