Salonanarchist | Leunstoelactivist

Peak economist

On Friday, the New York Times published an interesting article by Justin Wolfers about the kind of experts the paper mentions. Don’t worry, he’s aware of the methodological issues:

While the idea of measuring influence through newspaper mentions will elicit howls of protest from tweed-clad boffins sprawled across faculty lounges around the country, the results are fascinating.

To summarize: by his measure, economists have become the most influential profession among the social sciences and their influence rises during economic crises. Or at least so in the New York Times. I looked up data for the Dutch newspaper NRC Handelsblad, which has data available from 1990.

Some conclusions can be drawn:

  • The current ranking is the same as for the NYT, with economists heading the list and demographers at the bottom;
  • Apparently, NRC Handelsblad has always had a pretty high regard for historians, but due to the crisis they lost their top position to economists;
  • There was a peak in mentions of psychologist in 2012, but some of that can be ascribed to reports of scientific fraud by psychologist Diederik Stapel.

For comparison, I tried reproducing Wolfers’ NYT chart for the years 1990 - 2014. Here’s what I got:

The sudden increase for all professions in 2014 is unexpected - see Method for possible explanations. If we leave 2014 aside, what emerges is that «peak economist» (to borrow an expression from Wolfers) seems to have happened earlier in the NYT than in NRC Handelsblad. Perhaps something to do with the fact that the crisis hit the US earlier than Europe.


The NYT data were downloaded from the NYT Chronicle Tool (I had to separately download the data for each search term). Data from NRC Handelsblad were downloaded using the website’s search function. In order to get the total numbers per year I also did a search using «de» («the») as a search term («de» is the most frequently used word in written Dutch).

As indicated in the article, I got a steep rise in the percentages for all professions in the NYT in 2014. I manually checked some of the percentages I got against those in the chart of the NYT Chronicle Tool, and these appear to be correct. The spike is not visible in Wolfers’ chart, but that may be due to the fact that he uses three-year averages.

There may be an issue with the denominator, i.e. the total number of articles. The number for total_articles_published in the data I downloaded from the NYT was pretty stable at about 100,000 between 1990 and 2005. Then it rose to about 250,000 in 2013 (perhaps something to do with changed archiving practices, or with online publishing?). However, in 2014, it dropped to about one-third of the 2013 level.

The NRC Handelsblad data also has some fluctuations in the total number of articles per year, but less extreme and at first sight they don’t seem to coincide with unexpected fluctuations in the percentages of articles mentioning professions.

Code is available here.


Are the social-democrats getting enough seats in the Dutch Senate

This weekend, the Dutch social-democrat PvdA will decide on the list of candidates for the Senate election this spring. The party isn’t doing too well in the polls, but it may be facing an additional problem, as the charts below illustrate.

Since the beginning of the 1980s, the PvdA has nearly always had a weaker position in the Senate than in the Lower House. The main exception is 2002, when the Lower House election took place within days after the murder of rightwing populist Pim Fortuyn and the PvdA, seen by many as a symbol of the establishment, temporarily lost half its seats.

The relatively weak position of the PvdA in the Senate may be a coincidence, but it could also be related to turnout. In elections for the provincial councils, which in turn elect the Senate, almost half the voters stay at home (compared to a 75–80% turnout in Lower House elections). It may well be that the way in which the Senate is elected has a negative impact on the outcome for the PvdA.


Data from the Election Council and Wikipedia (e.g., EK and TK). Data and script are available here.



In het ledenblad van de jubilerende Fietsersbond staat een mooi artikel over fietsonderdelen die vroeger vanzelfsprekend waren, zoals witte spatborden, stuurblokjes, buiscommandeurs, pompnokjes en banddynamo’s. Leden krijgen het blad in de bus; wie geen lid is kan dat hier in orde maken.


Sevillanas. The Spanish punk

Update 11 January: Spotify data added.
According to the English Wikipedia page, «Generally speaking, a sevillana is very light hea[r]ted, happy music». There’s certainly some bland stuff around, but many sevillanas are explosive and raw. In fact, sevillanas are the punk of Spanish music.

I wanted to back this claim up by pointing to the length of the songs on the legendary Sevillanas de los Cuarenta album. It’s a known fact that punk is a genre with very short songs: on average 2:58 according to this analysis by blogger Dale Swanson. It’s the shortest of all the genres he analysed. Well, the average song length on the Sevillanas de los Cuarenta album is 2:44.

However, there may be some problems with this argument. First, some of the songs on the album have a haunting quality about them (for example, A flamenca no me ganas by Gracia de Triana), which makes you wonder if they haven’t been played too fast when they were recorded for CD. This may be an issue, but even if you correct for this the songs on Sevillanas de los Cuarenta would still be shorter than punk songs (for details see below, Method).

More problematic is the fact that short songs appear to have been normal in the 1940s. According to this analysis by Rhett Allain, average song lengths rarely exceeded 3 minutes until the end of the 1960s (see also the debate in the comments on possible explanations). So the shortness of the songs on the Sevillanas de los Cuarenta album isn’t that impressive. In fact, a (possibly non-representative) sample of 1970s sevillanas has an average song length of 3:22, which appears to be quite typical for the 1970s judging by Allain’s data.

The Musicbrainz database used by Allain doesn’t seem to contain many sevillanas. However, the Discogs website, which has data on millions of songs, does contain a few hundred sevillanas. Since posting the first version of the article, I realised metadata can also be obtained from Spotify. Spotify has over 2,500 songs with «sevillanas» in the title but only a few hundred songs per genre for other genres (probably the genre tags aren’t applied consistently). Below is the song length of a number of genres in the Discogs and Spotify databases.

For especially jazz and house, Spotify has other durations than Discogs. Other than that, median song durations are very similar. This is actually quite remarkable given the differences between the datasets. In both datasets, sevillanas tend to be somewhat longer than punk songs, but shorter than the other genres in the analysis.

An analysis by year might be interesting, but tricky: first because the release year in the Discogs data may refer to the year in which an album or song was re-released and second because the number of sevillanas tracks with sufficient information isn’t large enough for that level of precision. The Spotify dataset has no information on the release year of tracks (I guess if I really wanted I could have looked up the release date of the album each track is on).

All in all, the average sevillanas may be somewhat longer than a punk song. But you can still argue that a sevillanas song is in fact a series of even shorter songs, as illustrated by the plot of ¡Ay Sevilla! by Los de la Trocha shown above. The typical sevillanas is a series of short bursts of music that can be as abrupt as any punk song.


Scripts for the analyses are available here.

Songs on Sevillanas de los Cuarenta too fast?
Spotify has three versions of A flamenca no me ganas: the one from Sevillanas de los Cuarenta (2:29 on cd) and two others lasting 2:37 and 2:41. This suggests it’s possible that the «correct» version is up to 8% longer than the one on Sevillanas de los Cuarenta. Even if you assume all the songs on the album should last 8% longer, the average length would become 2:56, still less than for punk. On the other hand, it’s doubtful that all songs on Sevillanas de los Cuarenta are too short. For example, Sevillanas del Espartero by Concha Piquer lasts 2:57 on Sevillanas de los Cuarenta, but Spotify has versions lasting only between 2:27 and 2:35.

1970s sevillanas
The sample of 1970s songs is from albums C, D and F of the HISPAVOX Sevillanas de Oro collection (cd versions), containing songs by los Marismeños, Amigos de Gines and others (not all Sevillanas de Oro albums contain the release year of the songs, but these do).

Discogs data
The Discogs data are available through an API and as monthly data dumps. I thought I’d spare myself the trouble of figuring out how the API works, so I opted for the data dump (the one for 1 December 2014). The downside is that the data is 2.8 GB zipped and 19.2 GB unzipped, so downloading and analysing the data takes a while.

The data dump is xml (the API should return json). I’m not really familiar with xml so I used some not very sophisticated, but effective, regex to sort it out. The data is organised in releases (e.g., albums) that have tags (e.g., for the year in which it was released and for genres and styles). The releases contain tracks that have their own tags, including duration. In order to filter out excessive track lengths I ignored any release containing the string mix and tracks with a duration longer than one hour.

Discogs uses hundreds of genre and style tags including some quite specific ones like ranchera and rebetiko, but not sevillanas. I decided to include only tracks with sevillanas in the title. This will exclude some legitimate sevillanas, but I reckon there probably won’t be too many false positives.

Spotify data
I accessed the Spotify data through their web api. As indicated in the article, genre searches resulted in only a few hundred results per genre, which suggests these tags are often omitted.

Plotting a waveform
Based on this discussion, plotting a waveform from a .wav music file using Python should be simple, but saving the plot turned out to be a problem (googling the error message OverflowError: Allocated too many blocks taught me I’m not the only one having that problem but I didn’t find a solution that worked for me). Instead I turned to R and found that the tuneR package will let you read and plot .wav files without a problem.

Organisations demand raw data of controversial survey

In November, a survey was published which found that 80% of Dutch youth with a Turkish background would not have a problem with the use of violence in jihad and 90% would think that Dutch Muslims who fight in Syria are heroes.

While some were shocked by the findings, others expressed doubts about the methodology of the survey or simply thought the results were improbable. Among other things, the survey was not based on a random sample and non-response wasn’t reported. The researchers did try to recruit a sample that was representative of the wider population on a number of background variables through quota sampling (discussions in Dutch here, here and here; research method here).

A Motivaction spokesperson said the way in which the research had been done was «acceptable» from a social sciences perspective.

Now a group of Turkish organisations demands that Minister Lodewijk Asscher, who contracted the survey, order Motivaction to release all results so they can ask an independent expert to review the study. If necessary, they may go to court to get the data.

I don’t know how likely it is the organisations will get the original data and if they do, it may still be difficult to demonstrate sampling bias. Still, if this is a step towards introducing principles of reproducible research in contracted policy research, then that’s an interesting development.


Criticising charts

I missed this one: in October, Dutch economics journal ESB published an article that critically reviews all the charts in a report of the CPB (the semi-offical neoliberal economic institute that dominates Dutch policy debates). Authors Frank Kalshoven and Peter van Bergeijk find that on average, as many as four out of eight aspects of the charts have been done badly.

The authors invented a scale to assess charts, using the following criteria: the title describes what the chart shows; abbreviations and terms are explained; axis units are clearly described; axes are aligned; the source is explicitly mentioned; charts tell a clear story; charts contain little «noise» and there’s an explicit relation between panels in a chart.

One of the charts discussed is the one shown above. Among other things, the source is missing. Further, the y-axes of the bottom panels aren’t aligned, wrongly suggesting that taxes (bottom right panel) are often higher than collective expenditures, whereas in fact expenditures are higher than taxes (note that the government also has other sources of income).

Kalshoven and Van Bergeijk’s analysis seems to be strangely unconnected to the broader universe of data visualisation critique (interestingly, one of their sources of inspiration has - somewhat harshly - been described as «a horrible example of economists not recognizing that outsiders can help them»). Some of the most popular topics of chart criticism are missing from Kalshoven and Van Bergeijk’s article: use of colour; if and when it’s ok to truncate y-axes; legends versus labels; and if and how to use the area size of bubbles or icons to represent quantity.

Frank Kalshoven and Peter van Bergeijk, Datavisualisatie in de MEV onvoldoende. ESB 99, nr 4696. Online version here


As trade unions consider merger, the Dutch want their unions to take a much tougher stance

A large majority has voted in favour of the merger - A plan to create a new Dutch union with about 1 million members was put on hold in October, when the plan just failed to get a two-thirds majority at the convention of FNV Bondgenoten, one of the unions involved in the merger plans. A new vote will take place on 26 November.

Representatives of employers’ organisations expressed disappointment at the initial rejection of the merger. They had been hoping the merger would result in a stable trade union that will play a constructive role in the elaborate social dialogue institutions of the Dutch «polder model».

In fact, that’s exactly what Dutch unions have been doing over the past decades, as evidenced by their low strike rates. But with growing inequality and an erosion of the welfare state going on, doubts arise whether social dialogue is enough. Some groups of workers, like cleaners and health care workers, have successfully resorted to more assertive campaign methods to fight for decent pay and better working conditions.

Since 2007, researchers of the University of Tilburg have been asking a panel of about 6,000 respondents what they expect of unions. More specifically, they have asked respondents whether they agree that «Trade unions should take a much tougher political stance, if they wish to promote the workers’ interests». In the latest edition of the study, 44% (strongly) agree and only 13% (strongly) disagree.

If anything, support for tougher unions seems to have grown over the past years. Surprisingly, even among the self-employed and among people who voted for neoliberal parties like VVD and D66 in 2012, more respondents agree than disagree that unions should take a much tougher stance. High-income respondents are among the few groups that are not so keen on tougher unions.

Last weekend, chairman Ton Heerts explained the position of the FNV to the Telegraaf newspaper: «I think we’ve proven over the past year that it’s quite possible to combine substance, dialogue and action. With the current wave of right-wing policies, the emphasis will be more on actions. That’s fine.»

An earlier version of this analysis was published here


Second jobs - job erosion or appetite for consumption

Last year, a spokesperson of the German federal government suggested the explosive growth of Zweitjobs (second jobs) could have various explanations. Yes, people may be forced to take on second jobs out of financial necessity and because of the flexible labour market; but it could also have something to do with an increased «appetite for consumption» (Konsumlust). The suggestion immediately resulted in 2,000 sarcastic tweets.

The Netherlands has also seen a substantial growth in the number of people with second jobs, as new data from Statistics Netherlands illustrate. The chart shows the total number of employees (blue); employees with non-permanent jobs such as temp jobs and zero-hours contracts (red) and employees with a second job (green, all index 2002 = 100).

The green and red lines show a quite similar pattern. One might try arguing that the crisis caused a dip in the appetite for consumption, but more likely there’s a broader pattern of job erosion going on, temporarily slowed down when employers shedded their «flexible skin» (Dutch jargon for the precarious workers employers use) during the crisis.


Scooters often faster than cars

Minister Schultz wants to allow Amsterdam to ban scooters from cycle paths and make them use the road, wearing a helmet. This should make cycle paths safer for cyclists and reduce their exposure to air pollution. However, car and scooter lobbyists argue that the speed difference between scooters and cars is too large for scooters to ride safely on the road, with motorists driving 50 kmph.

So do motorists really make 50 kmph in Amsterdam? «Cycling professor» Marco te Brömmelstroet has tweeted a map showing rush hour speeds far below 50 kmph.

As part of its open data initiative, Amsterdam has released some 5 million speed measurements at the «Hoofdnet Auto» (the network of major roads for cars) during the month of January 2014. The histogram above shows that even at these main roads, the majority of measurements recorded a speed below 50 kmph, with a median speed of 31 kmph. Average speeds during afternoon rush hour were about 5 kmph lower than at night.

A 2011 study by cyclists’ organisation Fietsersbond found found an average speed for scooters on Amsterdam’s cycle paths of 36.9 kmph. The map shows roads where motorists drive on average at least 36.9 kmph (thin red line) or 50 kmph (thick red line). Note that the method by which the Fietsersbond measured scooter speed may be different from the method used to measure car speed.

There have been jokes that scooter riders don’t want to use the road because this would force them to reduce their speed. The data of the Amsterdam government show there’s actually some truth to this.

Scripts for processing the data can be found here.