Posts filed under Just look it up (210)

July 1, 2014

Does it make sense?

From the Herald (via @BKDrinkwater on Twitter)

Wages have only gone up $34.53 annually against house prices, which are up by $38,000.

These are the findings of the Home Affordability Report quarterly survey released by Massey University this morning.

At face value, that first sentence doesn’t make any sense, and also looks untrue. Wages have gone up quite a lot more than $34.53 annually. It is, however, almost a quote from the report, which the Herald embeds in their online story

 There was no real surprise in this result because the average annual wage increase of $34.53 was not enough to offset a $38,000 increase in the national median house price and an increase in the average mortgage interest rate from 5.57% to 5.64%. 

If you look for income information online, the first thing you find is the NZ Income Survey, which reported a $38 increase in median weekly salary and wage income for those receiving any. That’s a year old and not the right measure, but it suggests the $34.53 is probably an increase in some measure of average weekly income. Directly comparing that to the increase in the cost of house would be silly.

Fortunately, the Massey report doesn’t do that. If you look at the report, on the last page it says

Housing affordability for housing in New Zealand can be assessed by comparing the average weekly earnings with the median dwelling price and the mortgage interest rate

That is, they do some calculation with weekly earnings and expected mortgage payments. It’s remarkably hard to find exactly what calculation, but if you go to their website, and go back to 2006 when the report was sponsored by AMP, there is a more specific description.

If I’ve understood it correctly, the index is annual interest payment for an 80% mortgage  on the median house price at the average interest rate, divided by the average weekly wage.  That is, it’s the number of person-weeks of average wage income it would take to pay the mortgage interest for a year.  An index of 30 in Auckland means that the mortgage interest for the first year on 80% mortgage on the median house would take 30 weeks of average wage income to pay. A household with two people earning the average Auckland wage would spend 15/52 or nearly 30% of their income on mortgage interest to buy the median Auckland house.

Two final notes: first the “There was no real surprise” claim in the report is pretty meaningless. Once you know the inputs there should never be any real surprise in a simple ratio. Second, the Herald’s second paragraph

These are the findings of the Home Affordability Report quarterly survey released by Massey University this morning.

is just not true. Those are the inputs to the report, from, respectively, Stats New Zealand and REINZ. The findings are the changes in the affordability indices.

June 26, 2014

Slightly too Open Data

  1. The Atlantic published some visualisations of taxi rides in New York
  2. Chris Whong asked for the data under Freedom-of-Information laws, and got it. Of course, the taxi and driver ids were anonymized
  3. Vijay Pandurangan noticed that the driver id and taxi id were really, really weakly anonymised.
  4. You can find out a lot once you know the taxi id.


The NY Taxi & Limousine Commission had run the ids through a cryptographic hash function, MD5. Hash functions are designed so that if you don’t know anything about the input you can’t reconstruct it from the output, but if you know the input exactly, you can verify easily that it gives the same output.  The problem comes when you know a lot about the input, but not everything.  In this case, there are only about two million possible id numbers, and you can just try them all. Once you have the ids, you can look up.

Even if the taxi authorities had done the anonymisation correctly — replacing each id with a random number — it would inevitably have been possible to extract some of the ids with a bit of work.  That’s not the same as being able to extract all of them with a few hours’ computer time.

June 11, 2014

But did he ever return?

An excellent visualisation of very detailed data from the Boston subway system:

Boston’s Massachusetts Bay Transit Authority (MBTA) operates the 4th busiest subway system in the U.S. after New York, Washington, and Chicago. If you live in or around the city you have probably ridden on it. The MBTA recently began publishing substantial amount of subway data through its public APIs. They provide the full schedule in General Transit Feed Specification (GTFS) format which powers Google’s transit directions. They also publish realtime train locations for the Red, Orange, and Blue lines (but not Green or Silver lines). The following visualizations use data captured from these feeds for the entire month of February, 2014. Also, working with the MBTA, we were able to acquire per-minute entry and exit counts at each station measured at the turnstiles used for payment.

[No, he never returned]

June 8, 2014

Foreign drivers

From the ChCh Press

Foreign drivers cause more fatal and injury crashes in the South Island than the national average – and the West Coast is the worst spot.

They don’t actually mean “more,” they mean “a higher proportion of”.

New Zealand Transport Agency (NZTA) safety directions chief adviser Lisa Rossiter said its crash statistics for the past 10 years showed foreign drivers were involved in about 6 per cent of all fatal or injury crashes in New Zealand, and were at fault in about 2 per cent.

On average, short-term visitors make up roughly 2.5% of people in New Zealand (2.78 million visitors in the year to April 2014, median visit of 9 days, so I’m guessing mean visit about two weeks). About another 2% of people in New Zealand are international students, who are at least sometimes counted as foreign drivers.

So, the risk seems to be a bit higher for foreign drivers, but probably not twice as high. Some of the excess can probably be explained by age: international students, backpackers, and drunk Australians in Queenstown are younger than the population average.

It’s different in parts of the South Island

The tourist hot spots of Otago and the West Coast fared worst.

A foreign driver was identified as a factor in 13 per cent of fatal crashes on the coast, and 5 per cent of fatal crashes in Otago from 2004 to 2013.

A lot of this must be because tourists are over-represented in tourist hot spots: that’s what ‘tourist hot-spot’ means. The proportion of short-term visitors is about 2.5% nationwide, but it’s probably rather lower that than in Gisborne and rather higher on the West Coast.

It’s also worth noting that “identified as a factor” is fairly weak. If you go to the Ministry of Transport reports and add up the percentage of times different factors were involved in a crash, you get a lot more than 100% (for the 2010 report I get 225% for fatal crashes and 185% for injury crashes)

For crashes involving a tourist driver and more than one car, the foreign driver was fully or partly responsible two out of three times.

This at least gets rid of the denominator problem, but the “partly” responsible is still a problem. We aren’t told what proportion of the time the local driver was fully or partly responsible — based on the information given, that could also be two out of three times.

It’s quite likely that foreign drivers are at higher risk, especially those from countries that drive on the right, but the problem is not a big fraction of the NZ road toll. It’s worth considering things that can sensibly be done to reduce it — which doesn’t include withdrawing from the U.N. Convention on Road Traffic — but if you’re trying to stop road deaths it may be more effective to concentrate on interventions that don’t just affect foreign drivers.  Clearer signage, guard rails and median barriers, separated bike lanes, improved public transport… there are many things that might knock a percentage point off road deaths more easily than targetting foreign drivers.

June 5, 2014

NZ interactive graphic examples


  • From The Wireless, a story with maps of voter turnout and registration rates for younger people (RadioNZ might not be where you expect interactive graphics, but there it is). If I were being picky, I would say the popup labels are too big relative to the size of the map window.
May 23, 2014

Is Roy Morgan weird?

There seems to be a view that the Roy Morgan political opinion poll is more variable than the others, even to the extent that newspapers are willing to say so, eg, Stuff on May 7

The National Party has taken a big hit in the latest Roy Morgan poll, shedding 6 points to 42.5 per cent in the volatile survey.

I was asked about this on Twitter this morning, so I went to get Peter Green’s data and aggregation model to see what it showed. In fact, there’s not much difference between the major polling companies in the variability of their estimates. Here, for example, are poll-to-poll changes in the support for National in successive polls for four companies



And here are their departures from the aggregated smooth trend



There really is not much to see here. So why do people feel that Roy Morgan comes out with strange results more often? Probably because Roy Morgan comes out with results more often.

For example, the proportion of poll-to-poll changes over 3 percentage points is 0.22 for One News/Colmar Brunton, 0.18 for Roy Morgan, and 0.23 for 3 News/Reid Research, all about the same, but the number of changes over 3 percentage points in this time frame is 5 for One News/Colmar Brunton, 14 for Roy Morgan, and 5 for 3 News/Reid Research.

There are more strange results from Roy Morgan than for the others, but it’s mostly for the same reason that there are more burglaries in Auckland than in the other New Zealand cities.

Distrust the center

Automated location information can be very useful, but if the ‘location’ is an area and the automated result is a single point, it’s easy to get misled.

May 21, 2014

Explaining income tax shares

Following up on the “net tax” tangle, Keith Ng has a step by step explanation of how income tax and income distribution has changed over recent years in NZ.

You can also play with the visualisation yourself. Or, if you want to see the arguments about it, they’ll be on his Public Address post.

May 15, 2014

Budget visualisation

Keith Ng has his annual interactive graphic of budget changes up at Public Address, and will soon have a graphic showing how overall forecasts have changed over time.

[update] And Harkanwal Singh has his version up at the Herald

May 12, 2014

Resources in education

Attention conservation notice: I have to write this post because I’ve spent too much time on it otherwise. You don’t have to read it.

There was an episode of “Yes, Prime Minister” where the term “Human Resource Rich Countries” was being posed as a replacement for “Less Developed Countries”, meaning “poor”. “Resources” is a word that can mean lots of different things, which is why I spent more time than was strictly sensible investigating the following graph



The graph appeared in my Twitter feed last Monday. It’s originally from a campaign to give Australia a school funding model a bit more like NZ’s decile system, as recommended by a national review panel, so it is disturbing to see New Zealand almost at the bottom of the world.