Stats Chat

Simon Collins (and Chris Knox) at the NZ$ Herald have an interesting piece about the relative incomes of university graduates and other people. It’s definitely worth reading (even though you can’t look up Statistics or Data Science or Journalism).  However, there’s a built-in assumption of causation that is not entirely justified

Getting a degree can earn you a cool $1.3 million more over your lifetime than leaving school and going straight into work – but the gains vary wildly depending on what subject you study.

One of the irritating features of Graduation at the University of Auckland is that the Chancellor’s speech always includes a similar claim

We know that, compared to those whose formal education ends in high school, graduates have lower unemployment rates, higher salaries, better career prospects, and better health outcomes.

I actually used this as the topic for an exam question on causal inference in first semester.  The preamble to the question says

Team Ratings for Round 9

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 47 matches played, 34 of which were correctly predicted, a success rate of 72.3%.
Here are the predictions for last week’s games.

Predictions for Round 9

Here are the predictions for Round 9. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 6

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 27 matches played, 19 of which were correctly predicted, a success rate of 70.4%.
Here are the predictions for last week’s games.

Predictions for Round 6

Here are the predictions for Round 6. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

So, there’s good news about the Pfizer vaccine.  Some context:

1. What we have now is just a press release. However, the analysis and criteria were specified in advance, and we actually have that document, so it’s less fuzzy than it might be
2. Data are still coming in, so the estimate of vaccine efficacy will change over time to some extent.  In particular, we wouldn’t have heard anything if the estimated efficacy wasn’t at least 63%, so the current estimate is likely a bit too high.  The current estimate is so far above the threshold of 63% that this bias shouldn’t be huge
3. The trial focuses on preventing symptomatic infection. We haven’t heard anything about the impact on serious disease or on asymptomatic disease. The impact on serious disease is, oddly, less important, since the vaccine is good enough for herd immunity. However, if the vaccine (a bit implausibly) had no effect on serious disease and just made symptomatic infections asymptomatic, it wouldn’t be that much use.  Pfizer are collecting this information; it just wasn’t in the press release.
4. The next important step isn’t peer-reviewed publication, it’s the FDA external advisory committee meeting. These are public and involve scientists and doctors external to the FDA who get to ask Pfizer questions and have them answered.  If the advisory committee is strongly in favour of emergency authorisation, I would expect Medsafe to reach the same conclusion.
5. Duration of effect matters.  We cannot possibly know for another year whether protection lasts for a year (which would be plenty).  Very short duration of protection would still have some use for making travel safer and for ring-fencing small outbreaks, but it wouldn’t have much impact on the pandemic
6.  New Zealand is in line for enough vaccine for  750,000 people, and Megan Woods says it could arrive early next year.  That’s not enough to have any noticeable impact on population spread, but it is enough to reduce transmission to border staff and healthcare workers. It might even allow some increase in the safe admission to NZ of temporary workers or students — the government needs to decide how to allocate the vaccine.  Expanding on this: a vaccine could be used to reduce the probability of an outbreak, to increase travel and help the economy, or to reduce the harm of an outbreak (eg vaccinating elderly people). These are all worthwhile and the detailed choice is a policy question.
7. Mass vaccination won’t happen for a while.  Even if other candidate vaccines are effective (increasing the number of suppliers), mass vaccination in NZ is probably at least a year away
8. If the current estimate holds up, the vaccine is effective enough that we might get reasonable herd immunity by vaccinating only people who actually want to be vaccinated, which would make life simpler.
9. The Covid vaccines seem to have a higher rate of mild adverse effects than most vaccines we’re used to. It’s important not to deny these, and it would be useful if there were careful monitoring of adverse event rates in the first wave of NZ vaccine recipients by, eg, the NZ Pharmacovigilance Centre

Team Ratings for Round 6

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 14 matches played, 10 of which were correctly predicted, a success rate of 71.4%.
Here are the predictions for last week’s games.

Predictions for Round 6

Here are the predictions for Round 6. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 10

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 63 matches played, 40 of which were correctly predicted, a success rate of 63.5%.
Here are the predictions for last week’s games.

Predictions for Round 10

Here are the predictions for Round 10. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 5

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 23 matches played, 15 of which were correctly predicted, a success rate of 65.2%.
Here are the predictions for last week’s games.

Predictions for Round 5

Here are the predictions for Round 5. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

From a story by Eva Corlett at Radio NZ

Property Investors Federation’s executive officer Sharon Cullwick argued while property investors may not be helping the housing supply problem, they aren’t hindering it.

But she said first home buyers are, when it comes to purchasing rentals off the market.

“If a first home buyer purchases a property that was a rental property, then you’ll need another house to house the extra people living in that rental house.”

“So every time a first home buyer buys a house even though it’s great they are getting into the market – it actually makes the housing crisis worse,” she said.

This is obviously a convenient thing for the Property Investors Federation to believe, so it’s worth looking at the evidence.  It’s true that property investors, as investors, aren’t reducing the housing supply (just the housing for sale and perhaps its affordability).  But are first home buyers?

Clearly^{[citation needed]}  rental houses don’t just disappear, like those mysterious shops selling magical artefacts, when the renters move out and buy a house.  For every rental house that we lose, an owner-occupied house is created; to first order, nothing changes.

The claim being made is more subtle. We know that owner-occupied homes have fewer people living in them, on average, than rented homes.   If that difference is directly caused by being owner-occupied, then having more home owners would cause a reduction in average household size. While it wouldn’t cause a decrease in housing supply, it would increase the gap between demand and supply.

We can assume for the sake of argument that this isn’t primarily due to different sorts of homes being rented vs owner-occupied and say that, on average, a given home will have more people (or, at least, more adults) living in it if it is being rented than if it is being occupied by the owner.  Even stipulating all that doesn’t actually settle the question.

What we’re talking about here is the process of household formation. In the traditional Hallmark/Disney version, people start off living with their parents, they proceed through a stage of living with friends (or at least with flatmates), and then end up living in couples who eventually have 2.3 kids.   The number of adults per household tends to decrease as you go from the flatting stage to the couple stage, and also there i traditionally a progression from renting to owning your home. Because these transitions both happen over broadly the same age range, there’s an automatic tendency for them to be correlated. At 20, people are more likely  to be both renting and living in large households than at 40.

Here, though, we have a stronger claim, that buying a house is, in Auckland, the immediate cause of smaller households, or the even stronger claim that this is necessarily true.  The strongest version is clearly wrong: it is quite possible for people to form small, stable adult households while living in rental accomodation or, conversely, to buy a house but still have flatmates to help pay the bills. Data on household sizes are not what you’d need to settle the intermediate claim. It could be true, but it could also be false.

But suppose, again for the sake of argument, that the Property Investors Federation was correct: that there is a genuine causal connection and that buying (rather than renting) real estate is an unavoidable step in household formation for many people. To the extent that buying a house is inextricably linked to household formation, blaming first-home buyers is as inappropriate as blaming babies or immigrants or people moving from the rest of NZ or people with home offices. The housing crisis is the problem: it’s impeding adult household formation, and preventing families with kids getting enough space, making it harder to work from home, and making it harder for people to move to Auckland from the rest of NZ or the rest of the world.

Auckland has a housing crisis because there aren’t enough homes. This has not largely been due to changes in ownership distribution: we used to have more young homeowners, not fewer. Rules and procedures designed to impede building new homes have been a bigger contributor.

Team Ratings for Round 8

This is a new competition which I have had in mind for some time since it is one of the three top European competitions, the other two being the English Premiership and the Pro 14 (not solely European usually but happens to be this year so far).

I ran through the predictions for the first 7 rounds to get to this round but decided not to publish them. You will have to take it on trust that I didn’t fake it. I can report that the first couple of rounds were pretty dodgy, starting with only 50% correct. I expect to get a bit over 70% correct longer term in this competition based on my computations. I have data from the 2012-2013 season through to the incomplete 2019-2020 season which I used to create my initial ratings and to select parameters for the model.

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 41 matches played, 29 of which were correctly predicted, a success rate of 70.7%.
Here are the predictions for last week’s games.

Predictions for Round 8

Here are the predictions for Round 8. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.

Team Ratings for Round 5

The basic method is described on my Department home page.
Here are the team ratings prior to this week’s games, along with the ratings at the start of the season.

Performance So Far

So far there have been 11 matches played, 8 of which were correctly predicted, a success rate of 72.7%.
Here are the predictions for last week’s games.

Predictions for Round 5

Here are the predictions for Round 5. The prediction is my estimated expected points difference with a positive margin being a win to the home team, and a negative margin a win to the away team.