What do Economists Agree About: Election Issue

Next Tuesday I am speaking at a forum run by U of C Political Science students to inform students for the upcoming general election. There are a series of speakers from across the spectrum talking about “what I will find interesting this election”.

Rather than take a stance from my end of the spectrum, I thought I would lay out some principles that I think all economists should agree on (and that more than 90% would agree on), independent of their underlying values. I am thinking of presenting four general principles that would be relevant to pretty much any election campaign I can recall, and two others specific to the issues of this year’s election:

Timeless Issues:

1. Decide whether what matters to you is what serves your selfish interest or what would serve the social good. If you are genuinely concerned about the social good, you should ask what sacrifices you are being asked to make, not how others are going to pay.
2. Pay no attention to a policy that promises to create jobs or reduce unemployment, unless it specifically mentions labour market policy.  
3. Ignore promise of goodies to be financed by stronger economic growth.  
4. Ignore any policy that labels social spending “investment”.

Issues Specific to this Election:

1. Capital Gains Taxes versus Asset Sales is a false dichotomy.  
2. Removing the GST from fresh fruit and vegetables is a truly horrible idea.

I only have 5 minutes, so I don’t know how far I can expand on these, but the ideas behind each are as follows:

Selfish or Social Motivations: This is a plea for an end to "stealing the other kids bat" smugness.

Jobs: The growth in the number of jobs in an economy pretty much tracks the growth in the number of available workers. There are cyclical and structural factors that affect the gap between the two numbers (unemployment) but fluctuations in this gap are trivial compared to the ongoing growth in the workers and jobs. The debate should be about which policies would create a higher demand curve for labour and hence which will promote higher wages, not about which will produce the most jobs.

Economic Growth: Yes, some policies will be better for growth than others, but we only have best guesses, the growth literature is murky at best, and there are long and variable lags operating. By all means support policies that are likely to support growth, but don’t spend the proceeds till it happens.

Social Spending as Investment: Yes, sometimes an ounce of prevention in penal policy, health policy etc. to save on a pound of cure in the future will provide a return like any investment. But the uncertainty around the effectiveness of different policies councils against funding such putative investments out of borrowing rather than current consumption.

CGT versus Asset Sales: As best I can tell, the parties are not promising radically different paths for the deficit. We therefore need two separate debates: one concerning whether our fiscal position would be better addressed by selling equity rather than debt, and one concerning the mix of taxes. The issues regarding both are technical and complicated; confusing the two does not promote informed debate.

GST: I don’t want to be partisan, but academic integrity compels me to address this issue, previously visited here and here.

Any other election-relevant issues on which I can speak on behalf of the majority of economists? 

Paraphrasing Robert Frank

Will Wilkinson points to the latest from Robert Frank. I'm going to change a couple words in the quote here; you tell me if it still makes sense. If it doesn't, why does it make sense if we switch it back to talking about forced income redistribution rather than forced kidney redistribution?

Each year as the April 15 health filing deadline draws near, healthy older libertarians mount the stump in high dudgeon to denounce the government for seizing kidneys that are rightfully theirs. They might do well to reflect briefly on the fact that no matter how much they've exercised, they wouldn't have had any kidneys to seize in the first place if they'd grown up in a country like Nepal or Somalia; they're already older than the average life expectancy in those countries. The infrastructure that made their health possible was built by those who today need kidneys. Much of that health is thus an unearned return on investments made by others.

Once we start viewing income in excess of that possible in the state of nature as a rent available for redistribution, I don't know what particularly stops the argument's extension over to forced kidney redistribution from those older than the typical life expectancy in the state of nature.

Middle Earth trade politics

I think that Jason Sorens has the stylized facts wrong here:

Seen on an International Political Economy quiz:
The world of Middle-Earth has become largely peaceful, and international trade is growing. The Shire, Gondor, and Mordor are three countries in Middle-Earth. The Shire is abundant in land and scarce in labor and capital; Gondor is abundant in labor and capital and scarce in land; Mordor is abundant in labor and scarce in land and capital. Some of the products these countries trade include Longbottom leaf (produced intensively with land), mithril chain-mail armor (produced intensively with labor and capital), and raw iron ore (produced intensively with labor).

In the period leading up to the events described in the Lord of the Rings, Mordor was clearly capital-intensive. Gondor eschewed physical capital, favouring magic and tradition over technology and research.

Subsequent to the war of Gondorean aggression against the peaceful Orocuens of Mordor, egged on by the Wizards' Council who sought to prevent the coming Industrial Revolution in Mordor which would have forever reduced the relative power of magic, the Elves implemented policies in Mordor that Pol Pot would have supported: destroying any remnant technology and exterminating those with an education, while the Ithilians and Gondoreans tried to salvage some of the technology for their own use. So, post-war, Gondor was relatively abundant in capital (stolen from Mordor). And maybe Mordor was relatively abundant in labour, but only by virtue of its land having previously been turned to salt-pan pre-war by a failed irrigation scheme and its capital having been destroyed more thoroughly than its labour.

Worse, you can't make Mithril chain mail unless you get the Balrog out of Moria. Other sources say that Moria-induced lack of raw material was just a cover for the technology's having been lost - magic is in long term decline.

If you're insufficiently familiar with the true history of Middle Earth and the war of Gondorean aggression, read The Last Ringbearer (pdf), which anticipated a lot of the arguments made by David Brin back in 2002: LOTR was history as written by the victors who demonized their enemies as having been less than human. I wonder whether Brin had read the (1999) Russian version of The Last Ringbearer.

@ModeledBehavior asked if he should read Lord of the Rings. Of course he should. So that he can read The Last Ringbearer.

Leigh on Social Cost

Andrew Leigh weighs in on the Australian alcohol excise tax debates. The anti-alcohol folks have been citing the relatively recent $36 billion alcohol social cost figure; Leigh's comments follow below. But let's have first a quick look at the new cost figure.

At page 7 of the report, they invent, whole-cloth, a new requirement for internalization of intra-family effects: joint ownership of all family resources. Funny enough, I never noticed that part of Becker's Rotten Kid theorem. If Becker could generate intra-family internalization with no such assumption, it hardly seems a necessary condition for internalization of intra-family effects.

I've not gone over their cost estimates with anywhere near the detail I've taken in looking at Collins & Lapsley. Instead, I used my usual approach: find what looks to be one of the biggest cost components and see if it makes any sense. If it doesn't, that probably says something about the quality of the whole report.

And so at Table 9.13, they derive $6.4 billion in intangible harms to the quality of life of those who report knowing heavy drinkers whose drinking has harmed their quality of life. How? They get the average Quality Adjusted Life Year scores for those who report either not knowing a heavy drinker or knowing a drinker whose drinking hasn't negatively affected them, the average QALY score for those reporting knowing a drinker whose drinking has affected them "a little", and the average QALY score for those reporting that a drinker has affected them "a lot". They then monetize the difference under the assumption that knowing a heavy drinker is what's causing the differences in QALY scores.

The problem with this method is that it hopelessly confounds the effects of knowing a nasty drunk with the effects of being in the cohort of people most likely to know a nasty drunk.

Suppose, for argument's sake, that the average person who knows somebody whose heavy drinking has imposed costs on him differs from the average person who doesn't for reasons other than knowing somebody who's a nasty drunk. There are plenty of reasons to expect that such differences might exist. Off the top, I'd be willing to bet that people more likely to be adversely affected by a harmful drunk are also more likely to be unemployed, have lower education, have lower income, and so on. Yes, it's entirely a stereotype to say that these things don't happen in more privileged families - all kinds of bad outcomes happen there too. But it's the averages that matter here. And the kinds of things that give rise to having a social network more likely to include a nasty drunk also, on average, seem rather likely to give rise to other adverse outcomes independently of whether you wind up knowing a nasty drunk. But the report happily takes the whole $6.4 billion monetized difference as being due to alcohol. That's a sixth of the report's total.

Back to Andrew Leigh:

Mr Leigh, the member for Fraser in the ACT, said the consequence of introducing policies to protect people's future selves from their current selves “could actually be bigger than all the other social harms put together”.
“The one thing I'm still puzzled about and could use some assistance on is how much we should be concerned about an alcoholic's damage to their future selves” he told a national alcohol forum sponsored by the Australian Medical Association.
“If we go by standard rational economics, it isn't a social cost if I drink myself to an early death, but I think working through that rigorously, either empirically or theoretically, is useful.”

If we go by standard, rational economics, it isn't a social cost if someone drinks himself to death. Exactly right. Costs to the drinker are internal, not external.

Leigh's also right that setting policy to control internalities - costs individuals may impose on their future selves - could have very broad consequence. Glen Whitman outlined some of the problems here.

Leigh continues:

Mr Leigh, considered a rising talent in Labor ranks and who was representing the government's viewpoint at the conference, said he was frustrated there was not enough evidence to show whether a volumetric tax would work in cutting problem drinking.
And he said a volumetric tax on wine would have social equity consequences because it would hit low income earners the hardest.

This is a problem both for considering changes in the tax mix in Oz, and for discussions of minimum pricing regimes elsewhere. It isn't just the folks looking to get drunk as cheaply as possible who go for lower cost alcoholic beverages; plenty of poorer moderate drinkers go for cask wines too. Any gains from reducing the harms imposed by the drunks would need to be weighed against the consumer surplus losses accruing to moderate drinkers. Both of these need be evaluated at the margin; estimates of total costs aren't entirely helpful with that.

NZ Youth - increasingly rational

I, for one, celebrate the increasing rationality of today's youth:

Two months from the November 26 general election, one in four New Zealanders aged 18-29 aren’t enrolled to vote – something Electoral Enrolment Centre National Manager Murray Wicks is trying to change.
He says low enrolment “is the norm”, but this election the figures are skewed towards “an over-representation… in the 18-29 age group”.
The reasons are different for each person, Mr Wicks says, but two dominate.
“Voting’s not cool, it’s something that grown-ups do, it’s something that adults do, and it’s not interesting,” he says.
“There’s also that they just haven’t got around to it."

I've not yet seen a plausible instrumental story about why any individual should vote. Plenty of good non-instrumental stories - some folks think it's fun for its own sake, and who am I to question their utils?

He says young people need to be aware that their vote counts and will influence election results. “Their vote is important, their voice is important,” he says. “Whatever they choose to vote they’re making the decision for New Zealand and for themselves, rather than leaving it to other people to vote for them.”

That may be true of youth voters as a block, but it isn't true of any individual in that group. If iPredict's saying there's a 94% chance National forms the next government, the odds of any individual vote changing that are pretty slim. So too are the odds of any voter pushing any minor party from being just under to being just over the quotient for another list seat.

Elections NZ gives the St Laguë quota numbers from the 2002 election. The system divides each eligible party's vote by sequential odd numbers: 1, 3, 5, ... 53, ... 105. The largest quotient gets the first list seat, the second largest quotient gets the second list seat, and so on.

The last allocated list seat in that election went to National: their 425,310 votes divided by 53 gave the 120th largest quotient: 8024.717. Had there been a 121st seat, it would have gone to United Future, whose 135,918 votes gave it a quotient of 7995.176 when divided by 17. How many more votes would United Future have needed to have taken that 120th seat from National? 502. If some group of 500-odd National voters had stayed home, that 120th seat could have flipped over to United Future. Would that have changed the election outcome? No. Peter Dunne still would have gone into coalition with Helen Clarke.

To change the outcome of an MMP election, you either have to be the pivotal voter in a pivotal district like Ohariu-Belmont or Epsom, where a minor party's election lets it bring in a few other MPs, or be the voter who changes the quotient on the 121st list seat sufficiently to flip the ordering of the 120th and 121st quotients, or be a pivotal voter in a district that generates an overhang. And, on top of that, the change in the composition of Parliament has to be sufficient to either change the governing coalition or the substantive power of members of the coalition. In the 2002 example above, Peter Dunne's jumping from 8 seats to 9 is unlikely to have had any substantive effect.

Alas, most folks prefer the veil of self-deception, imagining that their vote really does make a difference. No Right Turn says voting is a weapon youths can use against their failing elders. Maybe. But it's a weapon not unlike a one-use eyedropper when trying to drown an elephant.

Minimum penalties and prosecutorial power [Updated]

A reasonable critique of minimum sentencing laws, and consequently of three-strikes legislation: they let prosecutors force plea bargains for offences without such minima because accused parties fear erroneous conviction and high penalties. Here's the New York Times (HT: all over Twitter)

“We now have an incredible concentration of power in the hands of prosecutors,” said Richard E. Myers II, a former assistant United States attorney who is now an associate professor of law at the University of North Carolina. He said that so much influence now resides with prosecutors that “in the wrong hands, the criminal justice system can be held hostage.” One crucial, if unheralded, effect of this shift is now coming into sharper view, according to academics who study the issue. Growing prosecutorial power is a significant reason that the percentage of felony cases that go to trial has dropped sharply in many places. Plea bargains have been common for more than a century, but lately they have begun to put the trial system out of business in some courtrooms. By one count, fewer than one in 40 felony cases now make it to trial, according to data from nine states that have published such records since the 1970s, when the ratio was about one in 12. The decline has been even steeper in federal district courts.

I wonder whether this effect has contaminated the studies on California's Three Strikes law. Recall that we've seen a big decline in strikeable offences and a smaller increase in non-strikeable offences. The argument has been that some of the decline in strikeable offences has been due to criminals substituting into offences carrying lesser potential sentence. Some of that substitution could just be the exercise of prosecutorial discretion in coercing a guilty plea on a non-strikeable offence where the accused fears the risk of taking a potential strikeable charge to trial. The effect can't be that large though: if it were all that kind of prosecutorial substitution, we'd expect the increase in non-strikeable offences to be larger relative to the decline in strikeable offences. UPDATE: Iyengar's work uses arrest data rather than conviction, and Shepherd's is all on crime rates. So unlikely to be a problem. See comments below, thanks to Lemmus!

I don't know the extent to which plea bargain is used in New Zealand. But this will be something to watch for as our three-strikes legislation becomes binding on more accused.

Previously:

• Is three strikes working?
• Marginal deterrence for the incarcerated
• A good strike
• Against the death penalty
• In favour of flogging

Death penalty

I used to hold the position that the death penalty was wrong, despite that it likely deterred around eight murders per execution, on the basis that the State ought not have that right. I suppose if the likely deterrent effect were really large, I'd be pluralist enough for the utilitarian side to beat the libertarian side. But not at that deterrent rate.

Wolfers and Donohue had previously shown much of the empirics on the death penalty are fragile.

The latest from Manski and Pepper (HT: Chris Blattman) shows the results more fragile than I'd thought: you can pretty much choose your conclusion through appropriate choice of identifying assumptions.

...we study the identifying power of relatively weak assumptions restricting variation in treatment response across places and time.  The results are findings of partial identification that bound the deterrent effect of capital punishment.  By successively adding stronger identifying assumptions, we seek to make transparent how assumptions shape inference.  We perform empirical analysis using state-level data in the United States in 1975 and 1977.  Under the weakest restrictions, there is substantial ambiguity: we cannot rule out the possibility that having a death penalty statute substantially increases or decreases homicide.  This ambiguity is reduced when we impose stronger assumptions, but inferences are sensitive to the maintained restrictions.  Combining the data with some assumptions implies that the death penalty increases homicide, but other assumptions imply that the death penalty deters it.

And so I revise: the death penalty is wrong, and it also likely has little measurable deterrent effect. There may still be a deterrent effect; we just can't show one given available data.

Update: Chris Auld has a nice intuitive explanation of the paper's results.

Gresham's Seed

There are lots of ways to clear a market. Specify two countries, D and N. In D, quality differentiation within a product category is allowed to generate price dispersion. Even still, some product grades face so little demand that wholesalers refuse suppliers offering it; the processing costs faced by the wholesaler would swamp potential returns. In N, not only can wholesalers not pay suppliers, suppliers are also faced with potential liability for the use of their product even when the product is exactly as was promised and performs exactly to expectation.

And so we get these fun bits of news. In Denmark:

Ole Schou, Cryos's director, said that there had been a surge in donations in recent years, allowing the facility to become much more picky about its donors. [They're turning down red-headed donors.] ...Cryos pays donors up to $500 (£316), and sends its semen to over 65 countries worldwide.

Meanwhile, in New Zealand:

While one of the world's largest sperm banks has reportedly rejected sperm from red haired men because of little demand, New Zealand sperm banks welcomed swimmers from most men, and were definitely not putting a ban on redheads, Dr Richard Fisher said. Fisher, who works for the country's largest fertility clinic Fertility Associates, said there had always been a shortage of sperm donors in New Zealand.

...But when it came to sperm donors in New Zealand, Fisher said recipients had "very little choice". He said fertility clinics in New Zealand found it particularly difficult to recruit sperm donors who were willing for their sperm to go to a lesbian couple or a single woman. It was easier to get men to donate sperm to heterosexual couples, but there still wasn't enough to meet demand. New Zealand sperm banks did not offer money to donors, which is one of the reasons why supply did not meet demand, Fisher said.

He said it wasn't a case of turning down donors in New Zealand that was an issue, but recruiting them in the first place. "It's almost as easy to get egg donors as it is to get sperm donors," he said. "And egg donors have to go through an in vitro fertilisation cycle, whereas men just have to donate their sperm."

... Sperm donors were required by law to be identifiable. Children who have been conceived via sperm donation could access their donor's details when they reached 18 years.

When you force donation price to zero and saddle donors with potential for resource extraction eighteen years down the line, donors are going to be less likely to provide samples to riskier bets; things clear by recipient queuing. Who might then donate? Maybe foreign tourists who are less likely to be hit up eighteen years later for college money. Maybe ginger donors who felt rejected in their home country and want to feel loved. Alas, Google tells me Denmark hasn't a team in the Rugby World Cup (and yes, I did have to check).

In the absence of red-headed Danish tourists, folks here in need would be stuck with local supply where a version of Gresham's Law will apply.

Previously:

• Price dispersion in gamete market surprisingly low, but still too high for some ethicists.
• Veil arguments and anonymous donation.

Shambolic

What a shambolic disappointment.

I've argued that ACT would do best to return to its classical liberal roots - that there's an unserviced space that's relatively liberal on economic and on social issues. As a right-wing rump to National, more liberal on economics but conservative on social issues, they'd be bound in the spot occupied by the Greens on the left - forever taken for granted by the dominant coalition partner because they couldn't plausibly bring down the government in favour of a coalition led by the main party on the other side. And, I've also thought that staking out a position on marijuana legalization could be a good way of signalling a move to that space. It would confound the usual narrative dominated by right-left thinking and, in so doing, bring a lot of positive press for ACT as it moves into a different space.

So I was really pleased to hear Don Brash musing about marijuana decriminalization over the weekend. Sure, decriminalization hardly goes far enough: if the trade remains illegal but possession legal, production remains split between informal household production among those into gardening, friendly informal supply among friends (albeit with risk that comes with growing more plants than is needed for personal use), and the gangs. Cactus Kate is right: full legalization is better.

In a fully legal and regulated market, we could move to supply under conditions similar to alcohol regulation with age controls and excise taxation to internalize whatever minor external harms come from marijuana use; alternatively, a higher than economically optimal tax could be set if necessary to build the coalition to move from prohibition to legalization - keeping retail price roughly constant but with the deadweight losses of the informal market turned into tax revenues. I've ballparked potential excise revenues at around $100-$300 million if taxes were set to hold consumer prices constant across regime change; actual figures would depend on potential economies of scale in production in a legalized market. If we were to take the $116 million spent by police on marijuana busts and instead devote it to violent crime, we could expect social cost savings on the order of about $275 million.

I'd thought that Brash's trial balloon was floated with his having secured at least minimal support from the Party apparatus. And so I was really optimistic - he had sold the party on a move towards liberalism despite John Banks being the candidate in Epsom. Alas, I must have been smoking something.

In a speech on law and order to party supporters in Auckland yesterday, Brash said he had serious questions about New Zealand's current marijuana laws and gave his personal endorsement to at least a debate over cannabis law reform.

However ACT president Chris Simmons today said decriminalising the class-C drug wouldn't be the party's policy next year, in 2014 or even 2017.

Simmons said the party's board wouldn't support decriminalisation, which was a "step too far." But he said it was important for party members to be asking questions and raising new ideas.

John Banks, the party's Epsom candidate and a former police minister, today said he could not support cannabis decriminalisation.

The party is polling well below the 5 per cent threshold to be guaranteed seats in Parliament, and is expected to depend on Banks winning Epsom.

This weekend also brought the shock resignation of parliamentary leader John Boscawen. Boscawen insisted he wasn't quitting over Brash's speech, but because he wanted to spend more time with his family. He made his decision on Friday.

He said his ''personal views'' on drug law reform weren't important but the issue should be debated, especially the $100m cost to the taxpayer of enforcing the laws. Decriminalisation wasn't ACT policy, he stressed.

Brash tried to pull the Party to the liberal side - a move that makes sense, but is hard given ACT's starting point. It wasn't made easier by that a bunch of people who claim to support marijuana decriminalization started piling on making fun of Brash's policy move. Yeah, you know who you are. It's all hip to make fun of the 70-year-old who's obviously hardly come within smelling distance of pot and pretend that he's a dope-head for advocating policy change. But, as best I understand things, it's that fear of being labelled "the marijuana guy" that effectively stopped Rodney Hide from pushing for greater consideration of the Law Commission's recommendations on marijuana. If the result of pushing for rational policy discussion is to be made a laughingstock even by those who purport to support rational policy, it ain't hard to figure out the likely effect on the supply of rational policy discussion.

The issue's now dead. And ACT probably is too. They could have staked out a defensible position in liberal space. But the conservative side has won. Worse, the party comes out as incoherent on core guiding principles: ACT is the party where economic liberals who are socially conservative get to fight publicly with economic liberals who are socially liberal. And whether or not Banks gets Epsom, that likely dooms the party in the long run.

Meanwhile, the online poll at newspaper site Stuff.co.nz has support for decriminalization ahead at 73% in favour to 27% against.

I really really wish that the NZES folks would include some questions about marijuana law in their 2011 survey. There's no way that the politicians will lead public opinion on this one, but there's good chance they'd follow. If even the pundits who agree with legalization make fun of the politicians who support it, no chance of any kind of policy move until there's obvious public support.

More things that aren't externalities

Roommates impose costs on each other; the decision to flat with someone and the agreements governing that arrangement internalize those costs. Nuisance costs roommates impose on each other are not an externality of any policy relevance.

I hope they don't come up with a policy solution to this one:

Using census data and analysis of an informal pricing survey of 114 users of [excised].com (a “share bills” app for roommates which I co-founded), I estimate that solving the loud sex problem alone would be worth $1.1-1.9 billion per year to the US market. Mitigating all unpleasant noises would represent a market of around $12 billion per year for the population we considered.

Ok, maybe they're just thinking of how much they could earn selling noise-reduction devices and taking a pretty high upper bound. But:

What is to be done about this cacophony of copulation? Noise machines and comfortable headphones would probably be the cheapest way to solve to problem, but these solutions are unlikely to be sufficient. Improved building codes in areas with high population density would put the burden on developers, but perhaps construction could be stimulated with tax incentives. Or perhaps creating a standardized rating system would be a good way to bring sound isolation issues out of the closet and let the market decide how much peace and quiet is worth.

Or, we could just leave people to choose their roommates based on a broad bundle of characteristics and to sort out amongst themselves how to deal with disputes.

Again, as helpful reminder: building owners install any feature, including noise-proofing, up to the point where the discounted value of the increase in expected rental flow matches the cost of the building feature. Tenants sort based on cost and on disutility of noise. If asymmetric information between landlord and potential tenant on noise issues were sufficiently large and if enough potential tenants cared, buildings would already be third party certified for noise characteristics.

It's a bit embarrassing that Forbes gave space to what's effectively an advertorial for the roommate bill-splitting website on the hook of a big dodgy cost number extrapolated from 114 users of a website designed for folks who can't otherwise figure out how to split their own bills without rancor.

Informal NZ politics

Add this to the list of "Never would happen in America".

The Prime Minister visited campus [unbeknownst to folks my side of campus]. The Mechanical Engineering students' computer lab overlooked the spot where he was meeting with folks outside. They put a sign in the window inviting him to "come up for a yarn with the country's future engineers." So he headed up. When one of the students invited him to put his best security guy up against their best arm-wrestler, he accepted; they all headed over to the students' arm-wrestling desk. And "Mad Dog" soundly beat the guy from the security detail.


The video seems to be from a student's phone cam; John Key notices the students somewhere around the 2:20 mark then heads on over.

• There is, effectively, no security while the PM wanders among a pile of Engineering students and hangs out for a short visit. No pre-clearing the room, no background checks for the folks he could potentially meet.
• I love the informality of NZ politics:
• The Prime Minister tells the students a story about a friend of his, an underachiever in high school who went to Canterbury to do Mechanical Engineering. I'm transcribing from the video, but I think this is what he said: "...when he came to Canterbury, his old man really got stuck into him just before he came in and said, 'Shit, you've got to pull your finger out and do some work,' and so every grade, every subject, an A+. So get off your ass!"
• The guy from the PM's security detail admits his "left arm is stuffed" and so only challenges with the right.
• It's not quite Bart vs Australia, but close.
• In 2005, when then Prime Minister and Labour Leader Helen Clark visited the University of Canterbury and gave an address outside the library promoting her bribe the students zero interest student loan policy, she faced a pretty mixed reaction. Some supporters, some loud angry boos, and one wag waving a sign reading "Gerry Brownlee will eat us all!" Now, Key gets a big cheer when he enters the room. National is probably underpriced at 95% likely to win the next election.

Unemployment and the youth minimum wage

I'd noted, initially with a couple errors, some of the differences between my findings and Hyslop and Stillman's on youth minimum wages. Where I'd found big effects of the youth minimum wage change on the youth unemployment rate, they found only small and statistically insignificant changes on the percentage of youths who are unemployed. I was a bit puzzled why they ran things on the latter measure - percentage of youths unemployed is hardly a headline HLFS result. But, thinking more on it, and subsequently clarified by email with Steven, there's really good reason for it.

Hyslop and Stillman start by asking what the effects of the youth minimum wage change are on the likelihood of being employed (recall that they're using individual-level data at a StatsNZ data centre, not aggregates). They find a reasonably large and statistically significant decrease in the likelihood of a 16 or 17 year old's being employed consequent to the change in legislation - about a six percentage point decline, or about a 9,600 person decrease in employment.

They then ask what happened to those kids - if the employment rate is down, where are they? The percentage of youths unemployed is the best way of answering that question. The likelihood of being unemployed went up a couple of percentage points, but the result wasn't statistically significant. They find instead that most of the effect was reduction in the employment rate of students who had been working part time, who would then drop out of the labour force rather than show up as unemployed or as "inactive".

As Matt Nolan over at TVHE points out, the welfare effects of this are a bit more ambiguous than the Greens have been suggesting. The Greens have been arguing that the minimum wage increase was great - no significant increase in unemployment and more kids stay in school. But that's entirely too quick. The drop, according to Table 6, has mostly been among students who combined work and study. So students are perhaps shifting to a stronger focus on their studies, but they're also going to be poorer and they're not going to be accumulating human capital in the form of experience that may well be complementary to human capital gained through education.

If our working model is that kids are short-sighted idiots (possible) who ought to be forced to accumulate human capital in the form of education only rather than in the form of work experience mixed with education, even if they have demonstrated that they believe the work experience to be valuable, then the change might not be awful.  If our working model is that kids are heterogeneous in converting education and experience into human capital, and have reasonable expectations about their individual marginal human capital increase coming from education or from work experience, pushing kids from higher valued work experience into lower valued education isn't all that great a deal.

Hyslop and Stillman also find significant negative effects on hours worked for 16-17 year olds in 2009 and 2010 on the order of 1-2 hours per week. While they're earning more per hour, they're getting fewer hours.

It's a bit fun to compare the number they get with the fancy techniques and individual-level data with what I get with my low-tech approach and aggregate data.

Again, I regress outcomes for 16 & 17 year olds on outcomes for other cohorts for the period prior to the minimum wage change then predict outcomes subsequent to the change given the performance of the comparison cohort. When I use 18 & 19 year olds as comparison cohort (Hyslop & Stillman use both 18 & 19 and 20 & 21 year olds; I haven't the latter data), I get a nine percentage point drop in the employment rate in 2010.

If you work backwards from their figures, you can piece out the expected change in the unemployment rate among 16 & 17 year olds - it looks to be about a four percentage point increase that's due to the youth minimum wage if you use average 2007 against average 2010, or five points if you use Q4 in each. Their result on unemployment isn't significant but their result on employment is; I'm not sure whether they'd then have a significant result on the unemployment rate driven by the likely significant drop in the denominator.

When I run things against 20-24 year olds, I get a 10.5 percentage point increase in the unemployment rate for 16 & 17 year olds in 2010; against 18-19 year olds, I get a 10 percentage point increase.

There are a few reasons for the difference. First, I always get larger effects when I use all adults as the baseline comparison rather than the 20-24 year old cohort. It's not crazy to then expect smaller effects if I were able to use a baseline cohort of 20-21 year olds.

Instead of conditioning a model on the early period and projecting forward, I've also run things using dummy terms and interactions for different regimes. Specify three regime periods and two regime variables. Regime 1 runs 1986 through 2001Q2. The second regime begins 2001Q2 - 18 and 19 year olds become subject to the adult minimum wage. Finally, regime three begins 2008Q2 - 16 and 17 year olds become subject to the adult minimum wage. I'm dropping the squared terms from the specifications because there are only thirteen quarters in the final regime period. And here's what I get*:

	(1)
	Unemployment rate, 16-17
Unemployment rate, 20-24	0.808***
	(9.42)
ur2024 * Regime2	-0.284
	(-0.81)
ur2024 * Regime 3	1.471***
	(4.76)
Regime 2	2.028
	(0.74)
regime 3	-9.816*
	(-2.37)
Constant	8.714***
	(8.59)
Observations	102
t statistics in parentheses * p < 0.05, ** p < 0.01, *** p < 0.001

In 2010, when the unemployment rate among 20-24 year olds averaged 12%, the effect of being in Regime 3 was (1.471*12) - 9.816 = a 7.9 percentage point increase in the youth unemployment rate for 16 and 17 year olds. In 2010Q4, when the unemployment rate among 20-24 year olds was 11.2%, the effect was a 6.7 percentage point increase. And that's close to the 5 percentage point increase you can back out of the Hyslop and Stillman figures for 2010Q4. [Note: if I drop the regime2 variables so I can keep the squared terms on unemployment, the effect of Regime 3 gets bigger, not smaller - a ten percentage point increase.]

I'm still a bit puzzled by a couple of things. Why does the percentage of cohort unemployed stay roughly constant while cohort labour force participation plummets? In other words, why is it the employed that jumped over into education rather than the unemployed? I've been saying about 10 points of the run-up in unemployment has likely been due to changes in the youth minimum wage; Hyslop and Stillman say about five points (though that may not be statistically significant). If Hyslop and Stillman are right, what then accounts for the massive disproportionate increase in the youth unemployment rate relative to the older cohorts' rates in this recession as compared to prior ones?

* esttab in Stata is awesome. You type "esttab, label html" and it spits out html code for regression tables.

Insurance problems

Christchurch is going to have to face higher insurance costs for a while. Earthquake risk here is now revealed to be higher than we had previously expected. We're now less likely to get major quakes than we were a year and a half ago, but we're probably more likely to get them than we had expected we were as of a year and a half ago. And so the risk payment goes up not because the actual risk has increased but because we have better expectations of the real risk.

John Pagani argues for the nationalisation of AMI, the big Canterbury insurer that had to be bailed out when it was revealed to have insufficient re-insurance for the series of major Christchurch earthquakes. And he makes some reasonable arguments: if the government's going to be liable for bad outcomes, it ought to have some hand in making sure it doesn't happen again. And, he's right that there are moral hazard problems with the big private insurers perhaps banking on the potential for bailout; I know that I didn't worry about checking into AMI's asset and risk structure because they had so substantial a Canterbury presence that, even if they tanked in an earthquake, there was no way the government would fail to bail them out.

But I'm not sure what problem nationalization solves. You can make a good case for that companies with exposure to concentrated correlated risks buy more reinsurance than those having a diversified customer base, and that regulations could be tighter around that. But whether AMI is private or public, it will still have to buy reinsurance on the global reinsurance market. And if that market has seized up, I'm not sure how changes in AMI's public or private status affects things.

I remain a bit perplexed about why people can't get new policies. You can't insure against a certain risk, but if the risk of another February hitting Christchurch is around 5%, you'd think reinsurers would be happy enough to issue cover at a fairly high premium. Some potential explanations:

• Reinsurers fear being saddled with the costs of prior quakes in any new event if a full assessment of a property's prior damage hasn't been completed
• But then, why is there difficulty in getting coverage for new builds?
• Uncertainty over what portion of future claims will be covered by EQC if the EQC fund is exhausted,
• But then, wouldn't we expect solution through better insurance contracts? 
• Reputational costs of actuarially fair pricing would swamp potential returns
• But reputation accrues mostly to the local agent, not the big reinsurer; for those, reputation is determined, I would have thought, by track record in paying out.

I think we need a fair bit better understanding of what's going on before we start nationalizing insurance companies. 

Fatter

I've wondered whether the drop in smoking rates has anything to do with the rise in obesity rates.

A new NBER working paper says it does:

An increasing number of Americans are obese, with a body mass index of 30 or more. In fact, the latest estimates indicate that about 30% of Americans are currently obese, which is roughly a 100% increase from 25 years ago. It is well accepted that weight gain is caused by caloric imbalance, where more calories are consumed than expended. Nevertheless, it is not clear why the prevalence of obesity has increased so dramatically over the last 30 years.

We simultaneously estimate the effects of the various socio-economic factors on weight status, considering in our analysis many of the socio-economic factors that have been identified by other researchers as important influences on caloric imbalance: employment, physical activity at work, food prices, the prevalence of restaurants, cigarette smoking, cigarette prices and taxes, food stamp receipt, and urbanization. We use 1979- and 1997-cohort National Longitudinal Survey of Youth (NLSY) data, which allows us to compare the prevalence of obesity between cohorts surveyed roughly 25 years apart. Using the traditional Blinder-Oaxaca decomposition technique, we find that cigarette smoking has the largest effect: the decline in cigarette smoking explains about 2% of the increase in the weight measures. The other significant factors explain less.

In New Zealand, there's a strong income gradient in obesity and in smoking prevalence. The government's been pushing hard on anti-tobacco measures.  More poor people in absolute numbers will be quitting smoking than will rich folks, even if richer folks are more responsive to anti-smoking messages, just due to base rates. And so we expect the income gradient to get stronger (poorer people get fatter) as the government keeps ramping up restrictions on smokers. Net effects on health are probably still positive - smoking is still probably worse for you than obesity.* But whatever the estimated benefits of policy, they're overestimated if they don't account for the consequent rise in obesity.

For those reckoning that this just means we need to stomp on unhealthy foods while we stomp on smokers, do note that their results on obesity suggest that food prices have very little effect on obesity rates. They say that because the effects of food stamp programmes and of urbanization on obesity have been very small (for the worse), the effects of weighting food stamp programmes towards healthier options or of building more bike paths are similarly likely to be small. They note further, and specifically, that fat taxes are likely to be ineffective: they find no evidence that food prices (regional variation in foot-at-home or fast-food prices) or of restaurant prevalence have effects on weight.

* Which one generates larger negative technological externalities is difficult to determine a priori.

Game Theory Naming Rights (geek post) UPDATED

We have added lecture time and content to our intermediate micro sequence this year, and as a result I find myself teaching basic game theory for the first time in 15 years. I have some old notes that introduces a number of canonical games using simple examples of 2x2 simultaneous games: these include a couple of versions of Pure Coordination, a zero-sum game (which I call Pure Conflict), Battle of the Sexes and, of course, The Prisoner’s Dilemma.

These are all standard textbook games. I also have three non-standard games. The first, which I call PureHarmony, has the following form:         

PH	C1	C2
R1	(2,2)	(2,1)
R2	(1,2)	(1,1)

It involves a dominant-strategy equilibrium in which either player’s choice of strategy has no impact on the other’s payoffs. This is a totally uninteresting game, except as a kind of dog that didn’t bark in the night: That is, it is a game with neither conflict nor a need for coordination, the two things that make game theory interesting.

The other two non-standard games are variants on the Prisoner’s Dilemma. I call the first of these Selfishness is ts Own Reward. I don’t have a name for the second, and so I am offering up naming-rights to anyone who can come up with a good story to motivate it. The Prisoner’s Dilemma, Selfishness is its Own Reward, and the final game have the following forms:

PD	C1	C2
R1	(2,2)	(4,1)
R2	(1,4)	(3,3)

SoR	C1	C2
R1	(3,3)	(4,1)
R2	(1,4)	(2,2)

?	C1	C2
R1	(2,2)	(4,1)
R2	(1,3)	(3,4)

Selfishness is its Own Reward has most of the attributes of a Prisoner’s Dilemma: a dominant strategy equilibrium in which the dominant strategy for each player imposes costs on the other player. But in SoR, unlike the PD, the selfish benefits to oneself arenot outweighed by the costs imposed by the other player, so that the equilibrium Pareto dominates the outcome in which both players behave non-selfishly. An example is a two-firm advertising game in which each firm’s advertising both takes market share from the other and brings new consumer’s into the market, with the benefit of the new consumers outweighing the cost of the advertising. SoR is also useful as an illustration for how Kant's categorical imperative removes a sort of technical loophole from the Biblical golden rule. Taken literally, do unto others as you would have them do unto you  would imply both players playing Strategy 2 in Selfishness is its own Reward, but the categorical imperative would not.

The final game has the same outcome as a Prisoner’s Dilemma—the unique equilibrium is Pareto dominated by one in which the players behave non-selfishly, but the equilibrium is arrived at by iterated elimination of dominant strategies, rather than both players having a dominant strategy. In a separated Prisoner’s context, Column would not benefit from finking on row if he thought Row would not fink, but knowing that finking is a dominant strategy for Row, finking is still the optimal strategy for Column.

So I have two questions for the game theory geeks among you. First, has anyone seen either Pure Harmony or Selfishness is its Own Reward before, and if so what have those games been called. And second, can anyone think of a good economic example that has the structure of the final game, and if so, what should it be called?

UPDATE:  A correspondent who could not access the comments has tweeted to suggest that the final game has the form of the Stag Hunt. It is close to a stag hunt, but not exactly. The Stag Hunt is what I have called Pure Coordination II in my notes—a game in which there are multiple, but Pareto rankable, Nash equilibria. The unnamed game above has a Pareto dominated Nash equilibrium but it is a unique equilibrium without the Prisoner’s Dilemma attributed of dominant strategies for both players.

Technical difficulties, technical Blogger bleg

Please bear with us as we work through some technical difficulties here at Offsetting. I updated a post late last night using the Blogger Android app. And that wound up putting everything that was in the pretty right hand column down to the bottom of the page. When I go over into the settings layout menu, it looks like the gadgets should be on the right hand side. They just don't appear there in preview or in live. And I haven't a clue how to fix that.

In the interim, I've set posts to take the whole blog width and moved all the gadgets to the bottom. And it's ugly. If anybody has a clue how to fix this, please let me know in comments. Yes, I've already tried going to a blank template with no right hand bar then putting the right hand column back in. It shows up in template and designer; it just doesn't show up in live.

And now I expect Chris Masse to hassle me about switching over to WordPress.

Hyslop and Stillman [updated]

Dean Hyslop and Steve Stillman have updated their prior work on the youth minimum wage in New Zealand to look at the most recent changes.

Here's the briefest synopsis of why I think we find divergent results on unemployment. Where I have everywhere been using the unemployment rate - the fraction of those in the labour force who are unable to find work - they are instead using the percentage unemployed - the fraction of the population cohort who are unable to find work, regardless of what proportion of that population wishes to be in work. As the labour force participation rate among sixteen and seventeen year olds over the period did not drop as quickly as did employment, the unemployment rate increased greatly relative to the percentage unemployed. The two measures answer very different questions. But skip straight to the end for the graphs showing this.

Recall that their prior study found no particularly bad outcomes consequent to the year 2000 changes to the youth minimum wage that brought 18 and 19 year olds up to the adult rate, despite some evidence of employment decreases among that group by 2003.

In the current study, they find that bringing 16 and 17 year olds up to the adult minimum wage resulted in substantial decreases in employment - they say 20-40% of the drop in employment among that age cohort, or between 4,500 and 9000 jobs losses, can be chalked up to the regulatory change. But, they argue this had no significant effect on percentage of unemployed 16 and 17 year olds because most of the employment losses were among students combining study and part time work. They've a rather more complicated econometric model than the simple one I've been using; my simple one finds substantial increases in unemployment among 16 and 17 year olds as well as decreases in employment.

First, a quick tour through the main results I've been finding and posting here on the blog before going through Hyslop and Stillman's.

Until very recently, I was using HLFS data on the 15-19 year old cohort for youth unemployment; I hadn't access to more finely grained data. But, StatsNZ kindly sent over data splitting each age group in that cohort. Here's what the unemployment numbers look like.

The red line hits at 2008Q2 - the first quarter in which 16 & 17 year olds are subject to the same minimum wage as that facing workers in all older cohorts. The blue line traces the unemployment rate for that group. Do note that the gap between the blue and red lines - divergent outcomes between 16 & 17 year olds and 18 & 19 year olds - only became persistently large starting around 2010Q3. Since that quarter, 16 and 17 year olds' unemployment rate has been ten points larger than that experienced by 18 and 19 year olds; the largest gap prior to 2008Q2 was about eight points in 1986. This will matter later when we look at the period of analysis in Hyslop and Stillman's paper. Note also that, according to the numbers Stats NZ gave me, the current unemployment rate for 16 & 17 year olds is higher than 30%.

What about employment rates? 

Youth employment rates tank after 2008Q2. Some of this is just the recession. But note how little the adult employment rate has moved compared to that for those aged 16 and 17. 

The very very simple model I've been running has taken unemployment outcomes for youths as a function of adult unemployment rates and the square of adult unemployment rates. I estimate the model over the period from 1986 through and including first quarter 2008. After that point, sixteen and seventeen year olds become subject to the adult minimum wage. I then ask Stata to predict the youth unemployment rate given the adult unemployment rate, both for the period of estimation and for the post-estimation period. The gap between the estimated and the actual unemployment rate is the residual. I do the same again for employment rates.

Now there can be a few problems with this kind of very very simple model. First off, out-of-sample prediction is always a bit of a mess; we need to check that the method isn't throwing spurious results. I do this by taking, in turn, each age cohort's unemployment rate as the dependent variable and putting the "everybody except for that cohort" unemployment rate (and its square) over on the right hand side. If the predicted unemployment rate diverges wildly from that observed for the post-2008 period, then I have a problem with my method. If the predicted unemployment rate only goes haywire for the group affected by the minimum wage changes, that lends weight to my method. If the predicted unemployment rate goes most haywire for the 16-17 year olds, rises less for 18-19 year olds, and rises less again for 20-24 year olds, that suggests, to me, that two things are going on: the youth minimum wage has worsened unemployment outcomes for the 16-17 cohort, and that groups with the highest proportion of members on the minimum wage have worse outcomes when the recession hits late in 2008. While 18 and 19 year olds have been subject to the adult minimum wage since 2001, overall unemployment rates were very very low through most of the 2000s. Once unemployment rose, the previously non-binding minimum wage on 18-19 year olds became binding. 

What happens when I check? Here's a plot of the residuals for each age cohort. The red line marks the start of the out-of-sample prediction period - 2008Q2 onwards. The blue line that reaches for the sky is the residual on the 16-17 year old unemployment rate. The red line that also tracks upward, albeit not dramatically, is the residual on the unemployment rate for 18-19 year olds. There's a slight increase in the residual for 20-24 year olds. If the blue and red lines weren't there, you would really not be able to tell that the red line marked the start of an out-of-sample prediction. So I'm pretty sure that the method I'm using isn't throwing up artefacts. 

Hyslop and Stillman use the unemployment rate among 20-21 year olds as the basis for their difference-in-difference estimation technique; I'm using the unemployment rate among everyone who isn't 16-17. Is that what's driving differences? No. Or, at least, I don't think so. I'm not sitting on a StatsNZ Data Centre,  as I expect Dean Hyslop was for rather a while while doing up this study, and so I don't have access to data on the unemployment rate facing 20 and 21 year olds. But I can run a set of other potential baselines for the simple regressions: the unemployment rate among everyone who isn't 16 or 17, the unemployment rate among everyone over the age of 19, the unemployment rate among 20-24 year olds, and the unemployment rate among 18-19 year olds. They all track pretty similarly, though the residuals are smaller in the post-2008 period when I use younger reference cohorts.

It's really not going to matter much which non-youth unemployment rate I use to predict the unemployment rate experienced by 16 and 17 year olds.

It's also worth noting that my simple technique is, nevertheless, a difference-in-difference technique. I'm looking at what happens to the youth unemployment rate relative to the adult rate (or various older cohort rates) subsequent to a policy change particularly affecting 16 and 17 year olds.

What happens when I do all the same fooferah for employment rates rather than unemployment rates? Recall that employment rates aren't just the inverse of unemployment rates; rather, the denominator is cohort population including those outside of the labour force while the unemployment rate counts only those in the labour force in the denominator. Well, here the choice of comparison group starts to matter. Here are the residuals:

Here, when I use employment rates among everyone else or among adults as baseline, relative employment rate outcomes for youths are worse in the post-2008 period than when I'm using younger cohorts as baseline. Either way, though, we get big declines in employment rates among 16 and 17 year olds, even relative to 18 and 19 year olds, in the period from 2008Q2 onwards.

So all my cards are on the table. Here's my .do file. And here's my .dta file. I don't think Hyslop and Stillman can put theirs up since they're using confidential HLFS individual-level data.

What do Hyslop and Stillman do? Instead of running a cohort's unemployment rate as the dependent variable the way I have, they set things up as a panel. Then, the unit of observation is the cohort-quarter with one observation for 16-17 year olds, one for 18-19 year olds, one for 20-21 year olds, and observations on others used to get business cycle effects. They then run panel techniques with age fixed effects, quarter fixed effects, and an indicator variable for whether the cohort was subject to the adult minimum wage. That's a lot of fixed effects to be throwing around when there are only twelve quarters of treatment period in their study. [No it isn't. They're using individual level data on thousands and thousands of individuals.]

But, as best I can tell, Hyslop and Stillman aren't testing the unemployment rate in any of their work. They're testing the fraction of unemployed in the cohort population. Those are not the same thing. The unemployment rate takes as denominator the number of people of the age cohort that are in the labour force. They're instead using the ratio of the number of cohort unemployed to the total number of people in that cohort. The difference matters a lot. Here's a short plot of the two series.

The unemployment rate among 16 and 17 year olds spiked massively after 2008Q2 but the cohort's percentage of unemployed persons did not climb very much. Honestly, the only way I noticed that they were using the percentage of unemployed rather than the unemployment rate was because the summary stats reported at page 10 were just so way out from the dataset I've been using. They report an increase in the percentage unemployed from 8.1% to 13.5%; meanwhile, the unemployment rate increases from 14% to 27% over the same period. How do we get the divergent series results? The labour force participation rate among 16 and 17 year olds had to have been dropping less quickly than were the number of kids in employment. 

If I re-run stuff using the percentage unemployed as dependent variable rather than the unemployment rate, and take the 20-24 cohort as the basis for predicting outcomes here's the comparative residual plots:

I've added in a second red vertical line here. Why? Because Hyslop and Stillman only consider a two year window subsequent to the law change. The red lines mark the start and end of that period, inclusively. The red line traces residuals using the Hyslop and Stillman specification that has the percent unemployed as the outcome variable of interest. [Update: They run things through Q42010; their window is wider than I'd thought on a first reading] The blue line does the same for unemployment rates. After the second red line, outside the period of their analysis, the youth unemployment rate continues to skyrocket relative to expectations given the unemployment rate among 20-24 year olds. The percent unemployed climbs back up to the high levels experienced for some, but not all, of the period inside the red lines.

And that's why we get different results. I don't think it has anything to do with their fancier econometric techniques. If I thought that "number of unemployed over total population" were something more economically relevant than "number of unemployed over total labour force", then I'd also conclude that there wasn't a big effect. The residual jumps up, but hardly enough to make anything of. The residual over their estimation period is 2.2 points - the percentage of 16 and 17 year olds unemployed in that two year window is two percentage points higher than we would have expected over the prior period. If we extend the window to include all the potential observations (I have no clue why they truncate to a two year window either side when sufficient data is available for a three year window), the residual increases to 2.7 points.

I really am not sure why Hyslop and Stillman chose to use the percent unemployed rather than the unemployment rate. They're top notch guys and must have had a good reason for it. [Updated post follows here: they had good reason.] The two measures answer different questions. Their measure tells us "What is the effect of increasing the youth minimum wage on the percentage of sixteen and seventeen year olds who are unemployed?" My measure tells us "What is the effect of increasing the youth minimum wage on the percentage of sixteen and seventeen year olds who are unable to find work, among those who wish to be in work?" The latter tends, I would have thought, to be the more interesting question as the expectation of a higher potential wage will increase the number of kids (attenuate the decline in the number of kids) wishing to be in the labour force. The unemployment rate tells you the fraction of those whose wishes for employment are thwarted. The percent unemployed tells you the fraction of those in an age bracket who are unemployed, but without any measure of what portion of those in that cohort wish to be in employment. 

And now I expect political debate about the youth minimum wage to turn into quibbles about which definition of unemployment matters most: the one that StatsNZ regularly reports, or the one Hyslop and Stillman were commissioned to use.