Toll Index October 2020

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 this introduced a discontinuity. The BAG even 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 Toll Index 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.

Toll Index September 2020

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 this introduced a discontinuity. The BAG even 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 Toll Index 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.

Toll Index August 2020 – COVID-19 in lorries’ rear-view mirror

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 this introduced a discontinuity. The BAG even 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 Toll Index 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.

Toll Index July 2020

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 Toll Index 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.

Toll Index June 2020 – not quite V-shaped recovery

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 Toll Index 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.

Toll Index May 2020 – COVID-19 eases up

Inbound and outbound lorries in May were down by 9% and 8% respectively compared to May 2019. The pandemic’s economic impact eases up a bit compared to the April drop of 24% and 22% respectively.

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 Toll Index 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.

Flattening the COVID-19 curve: What works

“…policies preventing close contacts in large groups, such as public events, private gatherings, and schools are the most effective in reducing new infections… mediated by changes in population mobility patterns, which are consistent with time-use and epidemiological factors…

From our column at voxeu.org on our paper (joint with K. Tatsiramos and B. Verheyden)

On google scholar (all sources).

Lockdown Strategies, Mobility Patterns and COVID-19

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

JEL codes: I12, I18, G14

Download from IZA Discussion Paper Series.

Toll Index April 2020 | 24% drop!

corrected: 20200518-15:50hrs

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 Toll Index 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.

Toll Index March 2020 – sizing COVID-19

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 Toll Index 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.

An internet picture of labor under COVID-19

COVID-19 pandemic

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.

Will video kill the academic research seminar?

The COVID-19 pandemic is impacting academic activity in a massive way. Conferences are cancelled for months in the future and research seminars are halted. Research seminars are starting to recover by moving online and future events are being re-designed as online meetings.

The website of the American Economic Association features a list of world wide, open, online seminars and events. The reason people are opening their seminar is because a typical payment plan of a video streaming platform will throw in unlimited scale for free with a moderately priced subscription. So seminar organizers feel that they can maximize the reach of their seminar for free. Make no mistake: it may well be that there is no substitute for a face to face but scale and cost reductions are interesting and hence online meetings might stay with us even after the coronavirus pandemic.

What does a world in which all seminars are online and open look like? If I can attend any seminar in the world from my home office does it even make sense that I too organize one? After all the reason I pay to fly out a speaker is to expose my local research group to quality research but now this exposure is abundant.

What does it mean for me as a presenter to present in one seminar and not another if seminars are online and open? As a presenter I choose where to present based on the perks of flying out (flight class, hotel, restaurants, museums, culture) and the quality of the place I am visiting i.e. of its local audience. But now the former is gone and I can get any audience anywhere without (alas) unfortunately knowing who is or will be in the audience…

People use a handful of video streaming platforms most of which are in the AWS cloud. So this is almost as if they use one single platform. Soon we will have to have a directory of the seminars as well (like AEA did) so your seminar will be just another entry in a calendar with a speaker and your logo. You cannot even be sure that your own researchers will attend yours and not another. So why would people still organize them?

If organizations continue to see a benefit competing for speakers (something unclear as yet) a compensation system for speakers might emerge to offset the absence of traveling perks. But why will organizations do so? A single platform might emerge facilitating the matching of seminar speakers to “research seminars” where speakers are compensated financially for a “performance” and an institution (the “organiser”) pays a fee to advertise on the stream thus also acquiring the right-off way for its own local research groups to interact with the speaker whereas all others are passive attendants…

Video might indeed kill the academic research seminar as we know it.

  • Update1: 20200328: HELP! “a weekly Zoom seminar where scholars present their ideas”

Coronavirus, telecommuting and the labor market

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?

Toll Index February 2020

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 Toll Index 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.

Python & Stata Workshop – German Stata Conference – Frankfurt | 4-5 June 2020

In the case of natural languages you swear in your mother tongue, write papers in English and when in Rome it helps to speak a little bit of Italian. Being a polyglot promotes communication, understanding and expression but it also sometimes increase the probability of confusion. One thing is for certain: in a globalized world for most of us our mother tongue will not suffice.

In the case of programming languages it is very much the same. The workshop is meant for those whose mother tongue is Stata but want to explore the added value of learning python or the reverse.

Besides an introduction to Python the workshop will demonstrate how to use the Stata SFI api to embed python code in a stata program and pass data between stata and python. Examples of when such an embedding is advantageous will be discussed and demonstrated. These include: text mining (python regular expressions), web scraping (programming a web browser in python), using web APIs to get data (e.g. Google Trends, Yahoo finance etc), speeding up with python multiprocessing (e.g. parallelize a for loop), unsupervised learning (e.g. python implementation of Luvain clustering algorithm) etc.

If you want to join here is the conference web page with a registration link and if you do register and have any extra wishes tweet them to me and I will do my best to include them.

The course will be a series of live demonstrations using Jupyter notebooks and the course material will be shared with all participants. For active participation you will need a Laptop (hopefully we will have local wifi) with Stata16 and Anaconda3 (with Python 3.7 or so). If you want to run the Stata Jupyter notebooks you need to have installed the Stata Kernel for Jupyter (alternative you copy paste the code from Jupyter notebooks to Stata16.

PS: Two modules written for the course use the Stata16 sfi to import (some of the) functionality of python modules to Stata. If you have Stata 16 try:

  • Stata command to get stock prices from Yahoo finance

. ssc install stockquote, replace and then run it as follows:

. stockquote AAPL, start_date(2020-01-01) end_date(2020-01-30)

to get 30 days worth of Apple stock price information. The module wraps itself around Python’s yfinance module and uses the following stata/python classes: sfi.Macro and sfi.Data, sfi. Datetime.

  • Stata command to find communities in weighted networks:

. ssc install louvain

. man louvain

On the help page follow the example by clicking on the commands. You will cluster a weighted graph of all numbers from 1 to 10 where two numbers are connected iff they are not coprime. When they are connected the weight is their gcd minus one. It wraps around the python modules python-louvain and uses stata frames and the stata sfi classes: sfi.Data, sfi.Macro and sfi.Frame.

Toll Index January 2020

Annual January to January changes of inbound or outbound lorries (after accounting for working day differences) are rarely non-positive. The drop of 2.1% for inbound and 1.8% for outbound traffic in the first month of 2020 should therefore be seen as a rare and hence significant fact.

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 Toll Index 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.

Toll Index December 2019

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. Since July 2019 each month is now comparable to the value of the same month in 2018. Of course we have a missing value for 2018 since it is not comparable to 2017 due to the policy change.

The Toll Index 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.

Toll Index July-November 2019

Monthly German border crossing activity by lorries has stalled on a year on year basis (accounting for working day differences) from July to November.

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. Since July 2019 each month is now comparable to the value of the same month in 2018. Of course we have a missing value for 2018 since it is not comparable to 2017 due to the policy change.

The Toll Index 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.

Toll Index November 2019 – stalled

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. Since July 2019 each month is now comparable to the value of the same month in 2018. Of course we have a missing value for 2018 since it is not comparable to 2017 due to the policy change.

The Toll Index 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.

UK elections 2019 – Odds, Polls, Google buzz

Based on Google Trends data  the Conservative party will beat the Labour party by about 7 percentage points in terms of the popular vote while the LibDems will trail the Conservatives by about 35 points.

The pollsters have the Conservatives leading Labour by anywhere between 6 and 15 percentage points in 14 polls in December with the average prediction at 9.5 pct points.

The bookies have the odds at 1/33 for a Conservative victory and 2/5 for an overall Conservative majority.

In Google search the footprints of Labour, Conservative and LibDems in the last seven days average to 42, 30 and 20 points respectively.

Labour always leads the Conservatives in Google buzz most likely due to demographics

 

We can still use the elections of 2015 and 2017 to take out party composition fixed effects from the Google data. When we do so we project that Labour will fall 5.4 to 8.5 percentage points behind the Conservatives in the popular vote while the LibDems will trail by 33.3 to 36.4 points.

Toll Index October 2019

Starting in July 2018 the BAG – Bundesamt für Güterverkeht introduced yet another policy change which affected how lorries pay tolls within the MAUT system as well as the data the come out of this process which is 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. Even the BAG had difficulty producing the numbers timely. September 2019 is now comparable to September 2018 values. Of course we have a missing value for September 2018 since it is not comparable to “September 2017” due to the policy change.

The Toll Index was first proposed in IZA DP5522 which ws 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.

Taxing times

Taxing times, by Michael Gold – The Economist Intelligence Unit

Contains a reference to my data tax idea, some quotes of mine and is an interesting read in its own right.

I have written about the Data Tax in:

#BREXIT: Vox Populi

Why the parliament expresses the “will of the people” better than any of its MPs including its PM and better than the brexit referendum

In 1907 Francis Galton published a paper in Nature titled Vox Populi. In it he discusses how the collective judgement of the crowd is better than that of the average individual (a fact which goes back to a simple mathematical identity, also known as diversity prediction theorem, which states that the squared error of the average of all predictions is smaller than or equal to the average squared error of all prediction because from the latter we need to subtract the diversity of the individual predictions to get the former). In what we would, today, call policy recommendations of his paper, Galton states:

The result is, I think, more creditable to the trustworthiness of a democratic judgement than might have been expected.

On the other hand, consider as Marquis de Condorset might have done in the 18th century, three voters Peter, Paul and Mary ordering three different alternatives, let’s say: Remain, Deal Brexit and No Deal Brexit. Here is how their preferences might be:

Peter: Remain, Deal Brexit, No Deal Brexit

Paul: Deal Brexit, No Deal Brexit, Remain

Mary: No Deal Brexit, Remain, Deal Brexit

All three are opinionated “patriots” who want “the best” for the UK. Peter wants to remain but if not feasible he wants an amicable divorce. Paul wants a divorce but if possible an amicable one and Mary wants no compromises: either leave “proud” or don’t try it at all.

It is irrelevant who is “right” or “wrong” but we can assume whatever contributes to the opinion of each individual does so consistently. In other words they might change their minds but each time you ask them they have an ordering which puts the three options in order. Their personality, gender, hormonal levels, socioeconomic status, childhood etc all might play a role. Now let’s examine which option has majority. Remain is preferred over Deal Brexit by a 2/3 majority (Peter and Mary), Deal Brexit is preferred over No Deal Brexit by a 2/3 majority (Peter and Paul), No Deal Brexit is preferred over Remain by a 2/3 majority (Paul and Mary). So the “democratic process” picks Remain over Deal, Deal over No Deal (hence Remain is better than No Deal) but it also prefers No Deal over Remain. So it prefers Remain over No Deal and No Deal over Remain!

So what gives? The mess the UK is in has some simple mathematics which if paid attention to could help bring emotions down and make some very simple thoughts which might lead to some very reasonable decisions. A referendum is too crude a tool to use to make important decisions especially with a turnout of 72% and a Leave to Remain outcome of 51.89% to 48.11%. Marquis de Condorcet will tell you that when the Leavers say that the referendum is “the will of the people” they are just bullshitting the public opinion. If you posed seemingly equivalent formualtions of the same question you could very well get contradictory outcomes such as leaving is better than remaining and remaining is better than leaving. On the other hand Galton will tell you that the parliament as a collective has a better chance at figuring things out than any MP (or citizen) including the PM.

Toll Index September 2019: inbound -1.8% | outbound -4.3%

For the first time after the Great Recession we are measuring a September-to-September drop in German border crossing lorries: -1.8% for inbound and -4.3% for outbound.

Starting in July 2018 the BAG – Bundesamt für Güterverkeht introduced yet another policy change which affected how lorries pay tolls within the MAUT system as well as the data the come out of this process which is 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. Even the BAG had difficulty producing the numbers timely. September 2019 is now comparable to September 2018 values. Of course we have a missing value for September 2018 since it is not comparable to “September 2017” due to the policy change.

The Toll Index was first proposed in IZA DP5522 which ws 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.

Toll Index August 2019

Starting in July 2018 the BAG – Bundesamt für Güterverkeht introduced yet another policy change which affected how lorries pay tolls within the MAUT system as well as the data the come out of this process which is 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. Even the BAG had difficulty producing the numbers timely. August 2019 is now comparable to August 2018 values. Of course we have a missing value for August 2018 since it is not comparable to “August 2017” due to the policy change.

The Toll Index was first proposed in IZA DP5522 which ws 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.

“European way of life” damaged by opinion copula

Ursula von der Leyen will be the next president of the European Commission and she is already drawing a shit storm of criticism, among other things, because she was never a “Spitzenkandidat”, something which, as some say, creates issues with democratic transparency.

 

One of Von der Leyen’s top team appointments, announced on Tuesday, included responsibility for migration in the remit of Greece’s commissioner-designate, Margaritis Schinas, under a newly created “Protecting the European Way of Life” portfolio. Because the phrase “protecting the European way of life” is considered a “dog-whistle” phrase used by the far right a new shit storm broke out.

Is Von der Leyen’s understanding of our “European ways” one that excludes migration? Is it a right wing one? It remains to be seen. What this incident is however is an instant of “opinion copula” which I studied here.

In principle the desire to protect your ways is not necessarily wrong if they are virtuous. Also what your ways include is not affected by your desire to protect them or not. The phrase “protect the European way of life” however is being used by those who think of “our ways” differently than others, in a way that excludes migrants etc. and hence as soon as Von der Leyen wants to protect our ways she is also assigned a particular understanding of our European values. Why? Because the phrase is copulated with far right opinions.

The open question, besides what Von der Leyen really believes, is: how would you express your desire to protect our European ways if your version of these “ways” includes compassion, migration, protection of human rights of refugees etc. If the bad guys hijacked the sequence of words “protecting the European way of life” what would we say to mean the same thing if your and my version includes migration?

Askitas N (2017) Explaining opinion polarisation with opinion copulas. PLoS ONE 12(8):
e0183277.
https://doi.org/10.1371/journal.pone.0183277

Toll Index July 2019 (we are back) – a slow down

Starting in July 2018 the BAG – Bundesamt für Güterverkeht introduced yet another policy change which affected how lorries pay tolls within the MAUT system as well as the data the come out of this process which is 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. Even the BAG had difficulty producing the numbers timely. Today for the first time after a year we seem to be back to the old rhythm and we can compare the July 2019 to July 2018 values. Of course we have a missing value for July 2018 since it is not comparable to “July 2017” due to policy change.

After five years of uninterrupted July-to-July growth in border crossing lorry activity we have a slightly negative data point which is in line with current fears of an approaching “technical recession” in Germany.

The Toll Index was first proposed in IZA DP5522 which ws 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.