Posts filed under Politics (187)

May 3, 2017

A century of immigration

Given the discussions of immigration in the past weeks, I decided to look for some historical data.  Stats NZ has a report “A Century of Censuses”, with a page on ‘proportion of population born overseas.” Here’s the graph

nz-oseas-born

The proportion of immigrants has never been very low, but it fell from about 1 in 2 in the late 19th century to about 1 in 6 in the middle of the 2oth century, and has risen to about 1 in 4 now. The increase has been going on for the entire lifetime of any NZ member of Parliament; the oldest was born roughly at Peak Kiwi in the mid-1940s.

Seeing that immigrants have been a large minority of New Zealand for over a century doesn’t necessarily imply anything about modern immigration policy — Hume’s Guillotine, “no ought deducible from is,” cuts that off.  But I still think some people would find it surprising.

 

April 26, 2017

Simplifying to make a picture

1. Ancestry.com has maps of the ancestry structure of North America, based on people who sent DNA samples in for their genotype service (click to embiggen)ncomms14238-f3

To make these maps, they looked for pairs of people whose DNA showed they were distant relatives, then simplified the resulting network into relatively stable clusters. They then drew the clusters on a map and coloured them according to what part of the world those people’s distant ancestors probably came from.  In theory, this should give something like a map of immigration into the US (and to a lesser extent, of remaining Native populations).  The map is a massive oversimplification, but that’s more or less the point: it simplifies the data to highlight particular patterns (and, necessarily, to hide others).  There’s a research paper, too.

 

2. In a satire on predictive policing, The New Inquiry has an app showing high-risk neighbourhoods for financial crime. There’s also a story at Buzzfeed.

sub-buzz-24605-1493145131-7

The app uses data from the US Financial Regulatory Authority (FINRA), and models the risk of financial crime using the usual sort of neighbourhood characteristics (eg number of liquor licenses, number of investment advisers).

 

3. The Sydney Morning Herald had a social/political quiz “What Kind of Aussie Are You?”.

1486745652102

They also have a discussion of how they designed the 7 groups.  Again, the groups aren’t entirely real, but are a set of stories told about complicated, multi-dimensional data.

 

The challenge in any display of this type is to remove enough information that the stories are visible, but not so much that they aren’t true– and not everyone will agree on whether you’ve succeeded.

April 25, 2017

Electioneering and statistics

In New Zealand, the Government Statistician reports to the Minister of Statistics, currently Mark Mitchell.  For about a decade, the UK has had a different system, where the National Statistician reports to the UK Statistics Authority, which is responsible directly to Parliament. The system is intended to make official statistics more clearly independent of the government of the day.

An additional role of the UK Statistics Authority is as a sort of statistics ombudsman when official statistics are misused.  There’s a new letter from the Chair to the UK political parties

The UK Statistics Authority has the statutory objective to promote and safeguard the production and publication of official statistics that serve the public good.

My predecessors Sir Michael Scholar and Sir Andrew Dilnot have in the past been obliged to write publicly about the misuse of official statistics in other pre-election periods and during the EU referendum campaign. Misuse at any time damages the integrity of statistics, causes confusion and undermines trust.

I write now to ask for your support and leadership to ensure that official statistics are used throughout this General Election period and beyond, in the public interest and in accordance with the principles of the Code of Practice for Official Statistics. In particular, the statistical sources should be clear and accessible to all; any caveats or limitations in the statistics should be respected; and campaigns should not pick out single numbers that differ from the picture painted by the statistics as a whole.

I am sending identical letters to the leaders of the main political parties, with a copy to Sir Jeremy Heywood, Cabinet Secretary.

We don’t have anyone whose job it is to write that sort of letter here, but it would be nice if the political parties (and their partisans) still followed this advice.

March 9, 2017

Causation, correlation, and gaps

It’s often hard to establish whether a correlation between two variables is cause and effect, or whether it’s due to other factors.  One technique that’s helpful for structuring one’s thinking about the problem is a causal graph: bubbles for variables, and arrows for effects.

I’ve written about the correlation between chocolate consumption and number of Nobel prizes for countries.  The ‘chocolate leads to Nobel Prizes’ hypothesis would be drawn like this:

chocolate

One of several more-reasonable alternatives is that variations in wealth explain the correlation, which looks like

chocolate1

As another example, there’s a negative correlation between the number of pirates operating in the world’s oceans and atmospheric CO2 concentration.  It could be that pirates directly reduce atmospheric CO2 concentration:

pirates

but it’s perhaps more likely that both technology and wealth have changed over time, leading to greater CO2 emissions and also to nations with the ability and motivation to suppress piracy:

pirates1

The pictures are oversimplified, but they still show enough of the key relationships to help with reasoning.  In particular, in these alternative explanations, there are arrows pointing into both the putative cause and the effect. There are arrows from the same origin into both ‘chocolate’ and ‘Nobel Prizes’; there are arrows from the same origins into both ‘pirates’ and ‘CO2‘.  Confounding — the confusion of relationships that leads to causes not matching correlations — requires arrows into both variables (or selection based on arrows out of both variables).

So, when we see a causal hypothesis like this one:

paygap

and ask if there’s “really” a gender pay gap, the answer “No” requires finding a variable with arrows into both gender and pay.  Which in your case you have not got. The pay gap really is caused by gender.

There are still interesting and important questions to be asked about mechanisms. For example, consider this graph

paygap1

We’d like to know how much of the pay gap is direct underpayment, how much goes through the mechanism of women doing more childcare, and how much goes through the mechanism of occupations with more women being  paid less.  Information about mechanisms helps us think about how to reduce the gap, and what the other costs of reducing it might be.  The studies I’ve seen suggest that all three of these mechanisms do contribute, so even if you think only the direct effects matter there’s still a problem.

You can also think of all sorts of things and stuff I’ve left out of that graph, and you could put some of them back in

paygap2

But you’re still going to end up with a graph where there are only arrows out of gender.  Women earn less, on average, and this is causation, not mere correlation.

August 17, 2016

Official statistics

There has been some controversy about changes to how unemployment is computed in the Household Labour Force Survey. As StatsNZ had explained, the changes would be back-dated to March 2007, to allow for comparisons.  However, from Stuff earlier this week:

In a media release Robertson, Labour’s finance spokesman, said National was “actively massaging official unemployment statistics” by changing the measure for joblessness to exclude those using websites, such as Seek or TradeMe.

Robertson was referring to the Household Labour Force Survey, due to be released on Wednesday, which he says would “almost certainly show a decrease in unemployment” as a result of the Government “manipulating official data to suit its own needs”.

Mr Robertson has since withdrawn this claim, and is now saying

“I accept the Chief Statistician’s assurances on the reason for the change in criteria but New Zealanders need to be aware that National Ministers have a track record of misusing and misrepresenting statistics.”

That’s a reasonable position — and some of the examples have appeared on StatsChat — but I don’t think the stories in the media have made it clear how serious the original accusation was (even if perhaps unintentionally).

Official statistics such as the unemployment estimates are politically sensitive, and it’s obvious why governments would want to change them. Argentina, famously, did this to their inflation estimates. As a result, no-one believed Argentinian economic data, which gets expensive when you’re trying to borrow money. For that reason, sensible countries structure their official statistics agencies to minimise political influence, and maximise independence.  New Zealand does have a first-world official statistics system — unlike many countries with similar economic resources — and it’s a valuable asset that can’t be taken for granted.

The system is set up so the Government shouldn’t have the ability to “actively massage” official unemployment statistics for minor political gain. If they did, well, ok, it was hyperbole when I said on Twitter ‘we’d need to go through StatsNZ with fire and the sword’, but the Government Statistician wouldn’t be the only one who’d need replacing.

July 27, 2016

In praise of NZ papers

I whinge about NZ papers a lot on StatsChat, and even more about some of the UK stories they reprint. It’s good sometimes to look at some of the UK stories they don’t reprint.  From the Daily Express

express

The Brexit enthusiast and cabinet Minister John Redwood says “The poll is great news, well done to the Daily Express.” As he seems to be suggesting, you don’t get results like this just by chance — having an online bogus poll on the website of an anti-Europe newspaper is a good start.

(via Antony Unwin)

July 19, 2016

Polls over petitions

I mentioned in June that Generation Zero were trying to crowdfund an opinion poll on having a rail option in the Auckland’s new harbour crossing.

Obviously they’re doing this because they think they know what the answer will be, but it’s still a welcome step towards evidence-based lobbying.

The results are out, in a poll conducted by UMR. Well, a summary of the results is out, in a story at The Spinoffand we can hope the rest of the information turns up on Generation Zero’s website at some point. A rail crossing is popular, even when its cost is presented as part of the question:

HarbourCrossingGraph

The advantage of proper opinion polls over petitions or other sort of bogus polls is the representativeness.  If 50,000 people sign a petition, all you know is that the true number of supporters is at least 50,000 (and maybe not even that).  Sometimes there will be one or two silent supporters for each petition vote (as with Red Peak); sometimes many more; sometimes fewer.

Petitions do have the advantage that you feel as if you’re doing something when you sign, but we can cope without that: after all, we still have social media.

May 26, 2016

Budget visualisations

This will likely be updated as I find them

  1. From Keith Ng. Budget now and over time. This gets special mention for being inflation-adjusted (it’s in 2014 dollars). Doesn’t work on my phone, but works well on a small laptop screen
  2. NZ Herald. Works (though hard to read) on a mobile. Still hard to read on a small laptop screen, but attractive on a large screen. I still have reservations about the bubbles.
  3. Stuff has a set of charts. The surplus/deficit one is nicely clear, though there’s nothing about the financial crisis/recession as an explanation for a lot of it.
  4. The government has interactive charts of Core Crown Revenue, Core Crown Expenditure, and breakdown for a taxpayer. On the last one, they lose points for displaying just income tax, when the Treasury are about the only people who could easily do better.
April 29, 2016

Looking up the index

 

Q: Did you hear that Auckland housing affordability is better now than when the government came to office?

A: No. Surely not.

Q: That’s what Nick Smith says: listen, it’s at 4:38. Is it true?

A: Up to a point.

Q: Up to what point?

A:  As he says, the Massey University Housing Affordability Index for February 2016 is lower than it was for November 2008, for Auckland and everywhere else in the country. For Auckland it was 38.44 then and is 33.8 now.

Q: But The Spinoff says one of the people behind the Index says Nick Smith is wrong, that housing isn’t more affordable than it was then.

A: Indeed she does. That’s because housing isn’t more affordable.

Q: But you said the index was lower?

A: Yes, it is.

Q: And lower is supposed to be better?

A: Yes.

Q: But how can the Housing Affordability Index be lower when housing isn’t more affordable? What is the index?

A: If it’s the same as it was is 2006 (which would make sense) it’s median selling price multiplied by a weighted-average interest rate and divided by the mean individual weekly earnings.

Q: Can you translate that?

A: Roughly,  the number of weeks of average earnings you’d need to pay the first year’s interest on a 100% mortgage.

Q: So if it’s 34, and you’ve got two people making the average, it’s 17 weeks each out of 52 going to mortgage interest? About 32% of income?

A: That’s right, only you don’t get 100% mortgages, so it’s more like 26% of income. And there’s taxes and insurance and you actually pay off a bit of the principal even in the first year, so it’s more complicated. But it’s a simple summary of the interest cost.

Q: And that’s lower now than in November 2008?

A: So it seems. I wasn’t living in New Zealand then, but it looks like mortgage interest rates were near 9%. The combination of the increase in incomes and the fall in interest rates has been slightly more than the increase in house prices, even in Auckland.

Q: But what if rates go back up?

A: Then a lot of houses will retroactively become much less affordable.

Q: And what about saving for down payments? That’s what all the snake people have been complaining about, and low interest rates don’t help there.

A: Down payments don’t go into the affordability index

Q: But they go into actual affordability!

A: Which is presumably why the Minister was talking about the affordability index.

 

April 28, 2016

Marking beliefs to market

Back in August, I wrote

Trump’s lead isn’t sampling error. He has an eleven percentage point lead in the poll averages, with sampling error well under one percentage point. That’s better than the National Party has ever managed. It’s better than the Higgs Boson has ever managed.

Even so, no serious commentator thinks Trump will be the Republican candidate. It’s not out of the question that he’d run as an independent — that’s a question of individual psychology, and much harder to answer — but he isn’t going to win the Republican primaries.

Arguably that was true: no serious commentator, as far as I know, did think Trump would be the Republican candidate.  But he is going to win the Republican primaries, and the opinion polls haven’t been all that badly wrong about him — better than the experts.