Salonanarchist | Leunstoelactivist

Executive pay

Last weekend, Senate member Roger van Boxtel criticised trade union FNV’s new central wage demand of 900 euro (which would narrow the gap between low and high incomes), arguing that it’s «really too much». Van Boxtel himself, in his capacity as ceo of the Menzis health insurance company, got a 5,000 euro raise last year, resulting in a remuneration of 389,000 euros.

Over the past year and a half, high-paid executives of (semi) public organisations have been somewhat sheltered from public scrutiny. Because of the introduction of a new norm, the government has suspended its annual publication on excessive pay at (semi) public institutions.

Google Trends data show that there was a peak in searches for «top incomes» in January 2013, when the latest report (on 2011 incomes) was published. Interest in the topic remained, but hasn’t reached the January 2013 level since.

In the meantime, some efforts have been made to analyse data from the annual reports of the institutions themselves. Abvakabo FNV has published its annual Actiz 50, documenting excessive pay at health care institutions. And newspaper de Volkskrant has published an analysis of 119 (semi) public institutions.

The Volkskrant data contain about 40 board members receiving remunerations in excess of the current norm for newly hired executives (230,000 euros). And their list is far from complete: many of the highest-paying institutions in 2011 aren’t even included. Among them Roger van Boxtel’s employer, Menzis.

In short, we won’t have the complete picture until the government publishes a new report, perhaps in a few months.


Cycling against traffic #2

The other day I posted something about cycling against traffic which, it has been claimed, is allowed on 85% of oneway streets in Brussels. I tried to find out the percentage for Amsterdam using Open Street Map, but found that the relevant information is often missing. Or so I thought.

I posted a question on the OSM forum (here and here) and got various helpful answers. Basically, I shouldn’t have looked just for oneway:bicycle=no tags, but also for cycleway=opposite (and perhaps a few more). I was also directed to a web page where cycling tags can be shown on a map.

So does Amsterdam allow cycling against traffic on anyway near the 85% of oneway streets reported for Brussels, if you include the cycleway=opposite tags? Well, no. Then again, looking at a similar map of Brussels, it doesn’t really look like they do any better. Of course, one shouldn’t jump to conclusions:

  • It depends on the part of the city you look at. In Amsterdam, cycling against traffic is more often allowed in the city centre and some other parts like Oost; in Brussels is appears to be more spread out over the city,
  • Perhaps local Open Street Map contributors have different mapping habits.

That said, I was getting curious as to the basis for the 85% claim for Brussels. I found a report from 2010 published by cyclists’ organisation Gracq, which said that 75% of oneway streets in Brussels had sens unique limité (which is apparently a legal requirement on suitable oneway streets). Gracq had contacted local governments by telephone to collect the data.

Can Open Street Map and Qgis show where it’s ok to cycle against traffic

[Update here] - The Italian cities Milan, Bologna and Turin would like to allow cyclists to ride against traffic on some oneway streets. This would help promote environment-friendly modes of transport and it would bring Italian cities in line with many European cities, where this is already allowed. For example, Brussels allows cycling contromano on 85% of oneway streets, they argue.

I was intrigued by that percentage, and curious what the percentage for Amsterdam might be. My first hunch was that it might well be similar, because you sort of expect that cycling in both directions is normally allowed here. Then I realised that the exceptions to this rule include canals, where the streets usually are oneway for cyclists as well. That might cost us percentage points.

I reckoned it should be possible to find out more using Open Street Map, where streets have oneway and oneway:bicycle labels. Unfortunately, the oneway:bicycle information is often missing (dotted lines on the map). This includes streets along canals that are oneway for cyclists, but also streets in neighbourhoods such as the Oosterparkbuurt where cycling in both directions is allowed.

Of course, Open Street Map is a volunteer project, so if information appears to be missing, I guess that’s my responsibility as much as anyone else’s. So here’s my to-do list:

  • Try to find out if I interpreted the oneway:bicycle tag correctly,
  • Figure out how to edit Open Street Map,
  • Add some oneway:bicycle information.

At the very least, it will be a good opportunity to learn something about Open Street Map.

Incidentally, the Italian cities saw their request turned down by minister Maurizio Lupi. Cycling against traffic may work elsewhere, but «we’re in Italy, not Germany», he argues.


Not only am I basically new to OSM; I also don’t have much experience with Qgis, so this was a bit of a trial and error thing. First I tried to define specific types of roads based on this overview of types of oneway roads with cycle lanes. However, trying to create new attributes in Qgis based on these descriptions all but crashed my computer (for some reason using conditions containing AND in the field calculator seems to be problematic). Further, almost no roads in Amsterdam appear to meet these specific criteria.

So instead I took a more basic approach, looking for oneway=yes in combination with different values for oneway:bicycle. Out of more than 11,500 polylines with oneway=yes, 267 had oneway:bicycle=no and five oneway:bicycle=yes (Halvemaansbrug, a nearby bit of Kloveniersburgwal and three unnamed polylines).

Data based on a rectangle comprising the city of Amsterdam, downloaded on 20 September 2014.

Kilts or inequality

On 18 September, Scotland may vote for independence. My understanding is that the referendum isn’t necessarily about kilts and haggis, but rather about left-leaning Scots who are fed up with London’s neoliberal policies. Policies that have caused, among other things, a widening gap between the rich and the rest of society. In fact, the Scottish referendum has been called the «world’s first vote on economic inequality».

One way in which inequality manifests itself is geographically. An interesting question is whether income and political power coincide. In some countries such as Germany and the Netherlands, the seat of government is in a region with a GDP comparable to the rest of the country. More often, governments are in high-income regions. For example, France’s richest region is Hauts-de-Seine (with business district la Défense), followed on its heels by Paris itself. Both have a GDP almost three times as high as the national GDP.

But the widest gap is to be found in the UK. Across Europe, only three out of 1357 regions have a GDP per inhabitant that is more than 3 times as high as their national GDP. For Polish boomtown Warsaw, the ratio is just above 3. For the German region of Wolfsburg, where VW has its headquarters, the ratio is 3.4. But the list is headed by the UK, where the «Inner London - West» region has a GDP as much as 5.8 times as high as the national GDP.

All in all, Scots who are dissatisfied with the distribution of income in the UK clearly have a point. Should the No camp find itself looking for someone to blame on 19 September, then perhaps Ms. Thatcher might qualify.

Map of all of Europe here.


I used Eurostat data on gross domestic product per inhabitant by NUTS 3 regions in 2011. NUTS 3 are the smallest regions used by Eurostat and have populations ranging from 150,000 to 800,000. 2011 is the most recent year for which data are available. The map is from EuroGeographics. The R code for the analysis is available here.

Of course, comparing regional GDP to national GDP is just one way of measuring inequality; other measures may produce somewhat different outcomes. It would be interesting to use wealth rather than income data, but I doubt that wealth data are available for regions.


Turnout and population size

The Dutch minister of the interior, Ronald Plasterk, has asked the Bureau for Economic Policy Analysis (CPB) to evaluate the declining turnout in local elections. This is an important issue, given how inequality and low turnout are related.

More specifically, Plasterk would like to know: first, if turnout is correlated to population size and second, what effect do municipal mergers have on turnout (one suspects a lobby of local governments opposed to mergers behind these questions).

As for the first question, that’s an easy one: yes. Smaller cities tend to have higher turnout. I looked it up, and the correlation’s actually pretty strong, if declining: 0.62 in 2002; 0.59 in 2006 and 0.50 in 2010 (somehow I couldn’t download data from the Kiesraad website, so I used the data I had downloaded some time ago, not including 2014 yet). I think political scientists will not be shocked by these outcomes.

More interesting is what kind of recommendations the CPB will come up with. Somehow I don’t think they’ll recommend cutting up large municipalities. Perhaps they should consider recommending a reintroduction of compulsory voting.


Cycling and income in the Netherlands

In Nickel and Dimed, her book on going undercover in low-wage America, Barbara Ehrenreich describes how not owning a car is one of the many factors making it difficult for low-paid workers to find better jobs. «Some of my co-workers, in Minneapolis as well as Key West, rode bikes to work, and this clearly limited their geographical range», she adds.

I was reminded of Ehrenreich’s book when I read a blog post by Michael Andersen. He argues that Denmark’s good quality bicycle infrastructure has contributed to the country’s egalitarian nature by making it easier to escape poverty. Danes with low incomes make a high share of their trips by bicycle. Rich Danes cycle too, but make far more trips by car.

In the comments to the blog post there’s a suggestion that in Amsterdam, it’s mainly the wealthy who ride bicycles. I couldn’t find recent data for Amsterdam, but geographical patterns may play a role. In the central area, where density is high and where the high-income districts Zuid and Centrum are located, people cycle more. In the peripheral districts, where distances to shops and other facilities tend to be longer, fewer trips are made by bicycle. Some of the poorest neighbourhoods are located there.

Statistics Netherlands (CBS) has data for the entire country, as well as for the cities with the highest addresses per surface area ratio. These include Amsterdam, Rotterdam, the Hague, Utrecht and a number of smaller cities. The main conclusions:

  • Like in Denmark, cycling infrastructure benefits all kinds of people, but low-income people even more so;
  • In high-density cities, not just the lowest income groups, but also the richest are more likely to take advantage of cycling infrastructure.

Incidentally, this doesn’t mean that cyclists get the space they should get. In a recent opinion article in NRC Handelsblad, writer Fred Feddes says that bicycle lanes make up 11% of public space in Amsterdam’s inner city, but parked cars probably far more.

Detailed data can be found here (I took this as an opportunity to practice the knitr skills taught in the Reproducible research course).

Update 20 August - Someone at the Fietsersbond dug up this (pdf) publication of the Amsterdam Municipality from 2010 which compares the mobility of Amsterdammers over the period 1986-1991 to 2005-2008. It suggests that cycling patterns in Amsterdam may in fact differ from the general pattern in high-density cities, with more cycling among high-income residents (as suggested by the commenter quoted above):

As for the development per income class, it turns out there are substantial differences. Among high-income residents the share of cycling in the total number of trips has more than doubled (from 15% to 33%), whereas the growth is only modest among low-income residents (from 26% to 33%). This means that relatively speaking, wealthy Amsterdammers today cycle more than low-income residents.


Are parked cars really dominating Amsterdam’s public space

In an intriguing opinion article in Thursday’s NRC Handelsblad, an author named Fred Feddes suggests banning parked cars from Amsterdam’s city centre. He argues that the current 15,000 parking spaces in the inner city take up 18ha, amounting to as much as 40% of the 45ha public space.

Sure, parked cars use lots of space, but 40%? Apparently, I wasn’t the only one to find that figure incredible. Council member Zeeger Ernsting tweeted:

As much as I endorse the viewpoint, the figure of 40% parking can’t possibly be right.. But indeed, cars [are] still far too dominant

I couldn’t immediately trace Feddes’ source and I’m sure there will be more debate on the issue. For now, here’s a quick and dirty calculation:

  • According to this (pdf) document of the Centrum district, «traffic areas» and green areas amount to 86ha. That’s more than Feddes’ 45ha, although I think the green areas may include some non-public space.
  • The district’s open data site has data on parking spaces (dating from 2010). All types combined, there were some 16,000 of them, slightly more than Feddes’ estimate.
  • Assuming that one parking space takes up 12 to 14m2, this would amount to 19 to 22ha; again slightly more than Feddes’ 18ha.

Perhaps Ernsting could ask the local government to shed some more light on this issue. Meanwhile, my provisional conclusion is that Feddes’ estimate doesn’t seem as incredible as I initially thought. And even if parked cars use only about 25% of public space, that’s still an enormous amount of space if you think about it.

Update 3 January 2015 - in a new article on the issue, Feddes provides more detail on the data he uses. The 45ha public space refers to «traffic terrain» (verkeersterrein) in 2009. CBS data for 2008 also put that number at 45ha. A more recent table (xlsx) indicates that this has since grown to 58ha. Interestingly, these more recent data also differentiate between types of traffic space. Apparently, railways take up 19ha (and according to this pdf, tram and metro tracks haven’t even been included in that category since 1993), leaving only 40ha for road traffic. On the basis of that number, the share of space dominated by (parked) cars would be even larger. Amazing.


Identifying «communists» at the New York Times, by 1955 US Army criteria

A while ago, Open Culture wrote about a 1955 US Army manual entitled How to spot a communist. According to the manual, communists have a preference for long sentences and tend to use expressions like:

integrative thinking, vanguard, comrade, hootenanny, chauvinism, book-burning, syncretistic faith, bourgeois-nationalism, jingoism, colonialism, hooliganism, ruling class, progressive, demagogy, dialectical, witch-hunt, reactionary, exploitation, oppressive, materialist.

What happened in the 1950s is pretty terrible, but that doesn’t mean we can’t have a bit of fun with the manual. I used the New York Times Article Search API to look up which of its writers actually use terms like hootenanny, book-burning and jingoism. The results are summarised below.

Interestingly, many of the users of «communist» terms are either foreign correspondents or art, music and film critics. While it’s possible that people who have an affinity with the arts tend to sympathise with communism, an alternative explanation would be that critics have more freedom than «regular» journalists to use somewhat exotic and expressive terms like the ones the US Army associated with communism.

Also of interest is that one of the current writers on the list is Ross Douthat, the main conservative columnist of the New York Times. In his articles, he uses terms like materialist, oppressive, reactionary, exploitation, vanguard, ruling class, progressive and chauvinism. Surely he wouldn’t be a reformed communist - would he?


The New York Times Article Search API is a great tool, but you have to keep in mind that digitising the archive isn’t an entirely error-free process. For example, sometimes bits of information end up in the lastname field that don’t belong there (e.g. "lastname": "DURANTYMOSCOW"). While it’s possible to correct some of these issues, it’s likely that search results will in some way be incomplete.

To get a manageable dataset, I looked up all articles containing any combination of two terms from the manual. I then calculated a score for each author by simply counting the number of unique terms they have used.

An alternative would have been to correct for the total number of articles per author in the NYT archive. It took me a while to figure out how to search by author using the NYT API. It turns out you can search for terms appearing in the byline using ?fq=byline:("firstname middlename lastname") - even though this option isn’t mentioned in the documentation. I’m not entirely sure such a search will return articles where the byline/original field is empty.

As you might expect, there’s a correlation between the number of articles per author and the number of unique terms this author has used.

All in all, it would be possible to calculate a relative score, for example number of terms used per 1,000 articles, but this may have unintended consequences. To take an extreme example: an author who has written one article which happened to contain three terms would get a score of 3,000 using this method, whereas an author who has thousands of articles and consistently uses a broad range of terms but not at a rate of three per article would get a (considerably) lower score.

I decided to stick with the absolute number of unique terms per author. This has the disadvantage that authors who have written few articles are unlikely to show up in the analysis, but I’m not sure that this problem can be adequately solved by calculating a relative score.

The Python and R code used to collect and analyse the data is available on Github.