We develop a multiple-events model and exploit within and between country variation in the timing, type and level of intensity of various public policies to study their dynamic effects on the daily incidence of COVID-19 and on population mobility patterns across 135 countries. We remove concurrent policy bias by taking into account the contemporaneous presence of multiple interventions. The main result of the paper is that cancelling public events and imposing restrictions on private gatherings followed by school closures have quantitatively the most pronounced effects on reducing the daily incidence of COVID-19. They are followed by workplace as well as stay-at-home requirements, whose statistical significance and levels of effect are not as pronounced. Instead, we find no effects for international travel controls, public transport closures and restrictions on movements across cities and regions. We establish that these findings are mediated by their effect on population mobility patterns in a manner consistent with time-use and epidemiological factors.
Keywords: COVID-19, public policies, non-pharmaceutical interventions, mul- tiple events, mobility
A whopping 24% drop in incoming lorries (-22% for outbound) compared to April of 2019 (controlling for number of working days). Larger drop than in the great recession.
Starting in July 2018 the BAG – Bundesamt für Güterverkehr introduced yet another policy change which affected how lorries pay tolls within the MAUT system as well as the data that come out of this process which are used for computing the Toll Index. The change expanded the network of roads in which toll is due by adding all bundesstraßen to it.
While in the long run this is bound to make the Toll Index more accurate in these past twelve months it made it useless for nowcasting. Moreover the BAG had difficulty producing the numbers timely for about year. After July 2019 we can report year on year changes for each month (with a missing value in 2018 for all months from July to December and a missing value in 2019 for all months from January to June.
The TollIndex was first proposed in IZA DP5522 which was published in the Journal of Forecasting. It has been widely covered in national and international media (selection):
The German statistical office, in cooperation with the Bundesamt für Güterverkehr, has taken the MAUT data in its portfolio of data products and their efforts can be found here. The Destatis document describing the data is here and here is their publication calendar for 2019.
How big is the impact of the COVID-19 pandemic on the economy? Here is another measurement to begin to fathom that extend of the damage.
The Toll Index for the month of March, based on fresh data from the German Bundesamt für Güterverkehr, shows a whopping 7.8% drop in inbound border crossing lorries and 10% drop for outbound ones compared to March of 2019 and controlling for number of working days.
The first and biggest drop since 2009 and the story is still developing.
Starting in July 2018 the BAG – Bundesamt für Güterverkehr introduced yet another policy change which affected how lorries pay tolls within the MAUT system as well as the data that come out of this process which are used for computing the Toll Index. The change expanded the network of roads in which toll is due by adding all bundesstraßen to it.
While in the long run this is bound to make the Toll Index more accurate in these past twelve months it made it useless for nowcasting. Moreover the BAG had difficulty producing the numbers timely for about year. After July 2019 we can report year on year changes for each month (with a missing value in 2018 for all months from July to December and a missing value in 2019 for all months from January to June.
The TollIndex was first proposed in IZA DP5522 which was published in the Journal of Forecasting. It has been widely covered in national and international media (selection):
The German statistical office, in cooperation with the Bundesamt für Güterverkehr, has taken the MAUT data in its portfolio of data products and their efforts can be found here. The Destatis document describing the data is here and here is their publication calendar for 2019.
A week’s worth of hourly Google searches across the Globe on the topic of “coronavirus”now (blue) and four weeks ago.
Unemployment
A week’s worth of hourly Google searches across the Globe on the topic of “unemployment benefits”now (blue) and four weeks ago.
Videconferencing
A week’s worth of hourly Google searches across the Globe on the topic of “Zoom videoconferencing” now (blue) and four weeks ago.A week’s worth of hourly Google searches across the Globe on the topic of “Cisco Webex videoconferencing” now (blue) and four weeks ago.A week’s worth of hourly Google searches across the Globe on the topic of “GoToMeeting videoconferencing” now (blue) and four weeks ago.A week’s worth of hourly Google searches across the Globe on the topic of “Skype videoconferencing”now (blue) and four weeks ago.
Working in teams online, collaborating
A week’s worth of hourly Google searches across the Globe on the topic of “Slack”now (blue) and four weeks ago.A week’s worth of hourly Google searches across the Globe on the topic of “Microsoft Teams”now (blue) and four weeks ago.A week’s worth of hourly Google searches across the Globe on the topic of “G Suite” now (blue) and four weeks ago.
Traffic congestions moves from the road to the internet
A week’s worth of hourly Google searches across the Globe on the topic of “Traffic Congestion” now (blue) and four weeks ago.A week’s worth of hourly Google searches across the Globe on the topic of “Speedtest.net”now (blue) and four weeks ago.
Before the coronavirus pandemic nobody wrote the words “social” and “distancing” in the same Google search query. Now there is a Google topic called “social distancing” and starting in March 9 as much as about 20% of all search queries which contained the word “social” also contained the word “distancing” in the US. Similarly with the words “rules” and “lockdown”.
In fact chances are that as you are reading this your are in some form of lock-down (make sure you know your regional rules) and most certainly your are practicing some form of telecommuting. I studied the regularity by which Germans log Google search queries containing the word “stau” (traffic jam) in a paper published at PLOS ONE. They type it together with a source of traffic jam information (e.g. radio or tv station or a website), or together with a highway number revealing their itinerary in some way. Here is what this looked like the last seven days on an hourly basis now (blue) and the same time interval three weeks ago:
On the average this is about a threefold reduction in such searches (more on the peaks) which correlates well with the fact that driving on German highways has been much more pleasant of late.
Similarly there is a 57% reduction in flights world wide! If we could find a way to fly less without affecting productivity we might even save the planet.
On the other hand Google search interest in telecommuting has surged world wide as you can see in the comparative graph below, which shows ninety days of searches on the topic of “telecommuting” now (in blue) and a year ago. There is as much as an eight-fold surge as one can see by just eyeballing the graph.
As a result “traffic jams” moved from the road to the internet, a fact which has led Netflix and Youtube to lower video quality in Europe in order to not overload infrastructure. I think in the weeks ahead as more and more people join the ranks of home-office (not every socioeconomic entity was able to respond as quickly to the coronavirus shock) we might see the investment gap exposed, especially in Germany.
First signs show the coronavirus pandemic already impacting the labor market worldwide. In the graph below we see 90 days of searches on the topic of “unemployment benefits” world wide now (in blue) and a year ago.
In the US from March 14 to March 21 there has been a surge of 1064% in Initial Unemployment claims (that’s one thousand and sixty four percent)!
Those who want to make the argument that less driving and less flying will benefit the planet as we are doing home office ought to factor in that video-conferencing and all digital tech is based on large farms of servers running 24/7. It would be interesting to estimate the numbers so here is an interesting research question: what is the net environmental benefit (say in terms of CO2 emissions), per unit of welfare produced, from reducing traveling while increasing compute-center electricity consumption to offset that reduction?
Starting in July 2018 the BAG – Bundesamt für Güterverkehr introduced
yet another policy change which affected how lorries pay tolls within
the MAUT system as well as the data that come out of this process which
are used for computing the Toll Index. The change expanded the network
of roads in which toll is due by adding all bundesstraßen to it.
While in the long run this is bound to make the Toll Index more accurate in these past twelve months it made it useless for nowcasting. Moreover the BAG had difficulty producing the numbers timely for about year. After July 2019 we can report year on year changes for each month (with a missing value in 2018 for all months from July to December and a missing value in 2019 for all months from January to June.
The TollIndex was first proposed in IZA DP5522 which was published in the Journal of Forecasting. It has been widely covered in national and international media (selection):
The German statistical office, in cooperation with the Bundesamt für
Güterverkehr, has taken the MAUT data in its portfolio of data products
and their efforts can be found here. The Destatis document describing the data is here and here is their publication calendar for 2019.
