Wednesday, 31 August 2016

Is the race-to-the-bottom over for Ireland?

In ECON110 this week, we talked about the debate over globalisation. One aspect we discussed (albeit briefly as I was running out of time) was the 'race to the bottom'. This is a form of Tiebout competition (though Tiebout was writing about local governments rather than national governments). National governments want to attract multinational corporations to locate their production (or other) activities in their country rather than other countries. This creates jobs and keeps the population happy, and increases the chances that the government gets re-elected (if the country is democratic). Alternatively, it offers the chance for corrupt politicians to enjoy kickbacks and place their cronies in positions of power in the local subsidiary firm. Either way, there are incentives for the government to attract multinationals to locate in their country.

But, lots of countries have the same incentives here. They need to compete for the attention of the multinational. In order to ensure that the factory (for example) is built in their country, the government will need to offer a more attractive package than other countries. This package might include tax breaks, priority access to land, generous subsidies, and so on. Once one country starts to offer these inducements, other countries will need to do so to have any chance of attracting the factory to locate in their jurisdiction. This is the 'race to the bottom' - essentially a race towards zero corporate taxes (or even negative corporate taxes, if subsidies are eventually included in the offers).

And so, we end up with the situation where Apple apparently pays a 0.0005 per cent tax rate in Ireland. As reported in Stuff yesterday (and widely reported elsewhere):
The European Union says Ireland has given illegal tax benefits worth up to 13 billion euros (NZ$20.08bn) to Apple and must now recover the unpaid back taxes from the US technology company, plus interest.
EU Competition Commissioner Margrethe Vestager said: "Member states cannot give tax benefits to selected companies - this is illegal under EU state aid rules."
The announcement was made on Tuesday night, NZ time.
She said a three-year investigation found Ireland granted such lavish tax breaks to Apple over many years that the multinational's effective corporate tax rate on its European profits dropped from one per cent in 2003 to a mere 0.0005 per cent in 2014.
The race-to-the-bottom may have reached its limits. The big question for me is now: will the EU also take a closer look at the tax arrangements in Luxembourg as well? Watch this space.

[HT: David in the Waikato EDG Facebook group]

Monday, 29 August 2016

Why restricting natural gas exports is not a good idea

This week in ECON110 we are covering international trade (and globalisation). The arguments against free trade often focus on the harms to workers (and firms) in import-competing industries - that is, those firms where jobs would be lost by having to compete with lower-cost foreign producers. The counter-argument is that consumers are made better off in these markets by being able to buy the imported products at much lower prices (increasing their consumer surplus).

Much less attention is focused on the impacts of trade restrictions on exporting industries. Consider for example, this 2013 New York Times story about the exporting of natural gas in the U.S.:
As Dow Chemical’s chief executive, Andrew N. Liveris has made himself into something of an outcast among his fellow business leaders.
The reason? He is spearheading a public campaign against increased exports of natural gas, which he sees as a threat to a manufacturing renaissance in the United States, not to mention his own company’s bottom line. But many others say such exports would provide far more benefits to the country than drawbacks, all part of a transformation that promises to increase the nation’s weight in the global economy...
By 2020, new oil and gas production could increase the country’s economic output by 2 to 4 percent beyond what it otherwise would be, add as many as 1.7 million jobs and perhaps reduce the bill for energy imports to zero, according to a report by the McKinsey Global Institute.
“This is a giant turnaround,” said Daniel Yergin, a longtime energy expert and author of a recent book, “The Quest: Energy, Security and the Remaking of the Modern World.” “This is fundamentally improving the competitive position of the United States in the world economy.”
But that windfall is at risk if the government permits natural gas exports to increase quickly, Mr. Liveris warns.
Natural gas is valuable, and on the surface the argument to restrict exports of natural gas in order to keep the value in the U.S. economy makes some intuitive sense. But it would also be quite wrong, and actually make the U.S. worse off.

To see why, let's take a step back and compare an exporting country with trade and without trade. Consider the diagram below, and we'll assume that the U.S. has a comparative advantage in producing natural gas - that means that the domestic price of natural gas (PD) would be below the price of natural gas on the world market (PW). This indicates that U.S. natural gas producers can produce and sell natural gas at a lower cost than foreign producers. Because the domestic price is lower than the world price, if the country is open to trade there are opportunities for traders to buy natural gas in the domestic market (at the price PD), and sell it on the world market (at the price PW) and make a profit (or maybe the suppliers themselves sell directly to the world market for the price PW). In other words, there are incentives to export natural gas. The domestic consumers would end up having to pay the price PW for natural gas as well, since they would be competing with the world price (and who would sell at the lower price PD when they could sell on the world market for PW instead?). At this higher price, the domestic consumers choose to purchase Qd0 natural gas, while the domestic suppliers sell Qs0 natural gas (assuming that the world market could absorb any quantity of natural gas that was produced). The difference (Qs0 - Qd0) is the quantity of natural gas that is exported. Essentially the demand curve with exports follows the red line in the diagram.


We can also use the diagram to demonstrate the gains from trade for an exporting country. Without trade, the market would operate at the domestic equilibrium, with price PD and quantity Q0. Consumer surplus (the gains to domestic natural gas consumers) would be the area AEPD, the producer surplus (the gains to domestic natural gas producers) would be the area PDEF, and total welfare (the sum of consumer surplus and producer surplus, or the gains to society overall) would be the area AEF. With trade, the consumer surplus decreases to ABPW, the producer surplus increases to PWCF, and total welfare increases to ABCF. Since total welfare is larger (by the area BCE), this represents the gains from trade. So, the U.S. is better off with trade, because the total welfare is larger than it is without trade.

Now consider an intermediate case. Instead of having no trade, or having unlimited trade, what would happen if the government allows trade up to some limit? In other words, what happens when there is an export quota? This is demonstrated in the diagram below. Whereas previously, we assumed that the world market could absorb any quantity of exports of natural gas, now the quantity of exports is limited to the agreed quota amount. Let's say that the export quota is limited to the amount between B and G (about half the amount of unrestricted exports). Importantly, the export quota is implemented using licenses - only holders of export licenses are allowed to export natural gas.

Now that there is a quota on exports, consider what happens to the demand curve (including exports). The upper part represents the domestic consumers with high willingness-to-pay for natural gas. Then there is a limited quantity of export demand, at the world price PW. After that, there are still profit opportunities for domestic suppliers (that is, there are still some domestic consumers who are willing to pay more than what it costs the suppliers to produce natural gas). So, the demand curve (including the export quota) pivots at the point G, and follows a parallel path to the original demand curve (i.e. the demand curve including exports follows the red line in the diagram). The domestic price is the price where supply is equal to demand (P1). Export license holders can purchase natural gas at this price, and then sell it on the world market and receive the higher world price (PW), and pocket a profit. The domestic consumers choose to purchase Qd1 natural gas at the price P1, while the domestic suppliers sell Qs1 natural gas at that price. The difference (Qs1 - Qd1) is the quantity of exports (which is also the quantity of the quota).


Now the consumer surplus is larger than it was without the export quota (it is now the area AJP1), the producer surplus is smaller than it was without the export quota (it is now the area P1HF). The export license holders now receive a surplus (profit), equal to the area KLHJ. Total welfare (which is now made up of the consumer surplus, producer surplus, and license holder surplus) is smaller than without the export quota (it is now the area AJHF+KLHJ). There is a deadweight loss (a loss of total welfare arising from the export quota) equal to the area [BKJ + LCH] - these areas were part of total welfare with trade and no export quota, but have now been lost.

Importantly though, note that the total welfare area is larger with the export quota (AJHF+KLHJ) than with no trade at all (AEF). So, the argument that restricting exports of natural gas makes the U.S. better off and will "fundamentally improve the competitive position of the U.S. economy" is simply untrue. Up to the point where the market-determined quantity of natural gas is exported, there are gains to be had from additional exports. That doesn't mean that more exports are always better. For instance, export subsidies that increase exports beyond the quantity shown in the first diagram above are also bad. And, you might want to restrict natural gas production for environmental reasons (which haven't been accounted for in the diagrams above). But those are stories for another day.

Read more:


Friday, 26 August 2016

Sustainable kereru harvesting

Protecting threatened and endangered species is hard. That's because they are common resources - resources that are rival and non-excludable. Rival resources are those where one person's use of the good reduces the amount available to everyone else, i.e. in this case one hunter killing a threatened animal reduces the number of those animals available to everyone. Non-excludable resources are those where you cannot easily prevent a person from obtaining the benefit from them, i.e. in this case it is difficult to stop the hunters from hunting.

There are many proposed solutions to solving the common resources problem (see some of my previous posts on common resources for some examples). However, the most sustainable solution is likely to be making the species excludable, rather than non-excludable. If you can prevent the hunters from hunting, then sustainability of animal populations will be much easier to attain. But how do you achieve excludability?

One option is farming. Have you ever considered why many bird species are threatened or endangered, but chickens are not? It's because most bird species are non-excludable (it's difficult to stop someone shooting or trapping a bird in the forest), but chickens are excludable because people own them (and presumably, chicken farmers watch their chickens at least closely enough that hunters wouldn't try to hunt them). Farmers also have large incentives to ensure that they keep their flocks sustainable (by taking out only the number of chickens that leaves a reasonably stable, or even growing, population).

However, for most birds farming is not an option. Some don't do well in captivity, and most of us would probably prefer that wild populations are kept sustainable, rather than developing increasingly in-bred farmed populations. So, we need an alternative option.

Fisheries in many countries are managed through transferable quota systems. Quotas regulate the number of fish that are allowed to be removed from the sea in a given period of time. The total quota is set by determining a total allowable catch for a year (in theory at least this is roughly equal to the growth in the fishery stock), with some allowance made for recreational fishing. Quotas work well because they make fish excludable (no quota means no fishing) and are backed up by monitoring and enforcement.

So I found this article from last week by Len Gillman (head of science at AUT) interesting. Gillman notes:
The kereru is a native New Zealand species protected under legislation, but despite this protection it has continued to decline in abundance since European colonisation. As an iconic native species, it is treasured by many Maori and Pakeha as something that must be preserved at all costs...
The main cause of kereru decline is predation and competition from mammalian pests, not hunting, and controlling these pests with natural poisons such as 1080 has been shown to promote their recovery. With ongoing predator control, populations increase until they reach a point where, limited by resources, surviving fledglings entering the local population roughly equal those leaving the population due to emigration and mortality.
When a population reaches stability, small harvests can be made without affecting the total number of birds, because those removed by harvest allow more fledglings to survive. This concept is known as a sustainable harvest - it allows a small ongoing harvest without affecting the size of the population. Harvesting quotas would need to be based on kereru numbers and age distributions, considering young birds learn survival skills from older birds, but sustainable harvesting holds great promise.
There are a couple of points to add to this. First, once the sustainable harvest number of kereru have been determined, how would the harvest be allocated? In other words, who would determine who has the rights to harvest kereru, and for how many birds? This sort of allocation problem is key (see here for a similar example relating to water).

Second, to ensure efficiency the rights should be transferable between parties in a voluntary exchange. Assuming that the rights to harvest kereru are only provided to iwi, and can only be transferred between iwi, this would still ensure that iwi who have the most to gain from harvesting kereru would be those that did the harvesting (since they would be willing to buy the rights off other iwi who valued the harvest less). This would ensure the maximum net gain for society (as a whole) from the limited (and sustainable) kereru harvest.



Tuesday, 23 August 2016

Wage segregation, asymmetric information and inequality

Samuel Hammond wrote a post for the Niskanen Center blog that might be one of the clearest and most insightful blog posts I've ever read. Hammond writes about increasing wage segregation in the U.S. labour market, but the insightful bit is to link it to reductions in information asymmetry between employers and workers. I'll refrain from wholesale copying-and-pasting most of the post, which you should read! Here is the most important bit:
How does this apply to technological change, wages, and inequality?
Think back to the naive insurer attempting to “pool” high and low risk types under one premium. Now substitute insurer with employer, and high and low risk types with low and high productivity workers, and the flat premium with a relatively flat wage structure.
Our nostalgic vision of the mid-20th century’s strong middle class is a memory of a wage pooling equilibrium that eventually unraveled. Behemoth corporate employers priced labor in a relatively naive way, given an inability to observe the heterogeneity of individual productivity moment by moment, and the role of labor unions in negotiating wages as a collective. While there was still a premium on things like seniority and higher education, wages were nevertheless fairly compressed.
For workers who contributed substantially more value to the company than they were being paid for, this was a raw deal. Conversely, it was great deal for workers whose productivity lagged. In other words, high productivity workers bore a negative externality by having to partially subsidize low productivity workers due to the inherent opacity of who-contributes-what within team production.
That has changed with information technology that makes it easier than ever to observe and measure individual worker productivity and screen for it accordingly (which may be why the premium from working at larger firms has also diminished).
Wage segregation is of course important because it is one of the causes of the recent increase in inequality observed in the U.S. The previous pooling equilibrium led both high and low productivity workers to have roughly the same wages, because it was difficult for employers to tell them apart. With the (technological) ability to more closely monitor and measure worker performance, the high and low productivity workers can be separated, allowing firms to reward the high productivity workers with higher wages (and not reward low productivity workers).

Now, having said all that it makes me wonder - why isn't inequality increasing in New Zealand for the same reason? As Eric Crampton has noted many times, inequality has barely changed in New Zealand since the mid-1990s. Surely we must have wage segregation here as well? What gives?

Monday, 22 August 2016

Profiting from death arbitrage

Add this one to the unintended consequences file. Matt Levine writes in this Bloomberg article:
The normal way to shift the risk of death is life insurance -- you die, the insurance company gives you money -- but there are other, more esoteric versions, and they are more susceptible to arbitrage. One version involves "medium and long-term bonds and certificates of deposit ('CDs') that contain 'survivor options' or 'death puts.'" Schematically, the idea is that a financial institution issues a bond that pays back $100 when it matures in 2040 or whatever. But if the buyer of the bond dies, he gets his $100 back immediately, instead of having to wait until 2040. He's still dead, though. 
But the bond can be owned jointly by two people, and when one of them dies, the other one gets the $100 back. If you and your friend buy a bond like that for $80, and then your friend dies, you make a quick $20.
But what are the odds of that? "Pretty low" was presumably the thinking of the companies issuing these bonds.
At this point you can probably see where this is headed:
 But they didn't reckon with Donald F. "Jay" Lathen Jr. and his hedge fund Eden Arc Capital Management: 
"Using contacts at nursing homes and hospices to identify patients that had a prognosis of less than six months left to live, and conducting due diligence into the patients’ medical condition, Lathen found Participants he could use to execute the Fund’s strategy. In return for agreeing to become a joint owner on an account with Lathen and/or another individual, the Participants were promised a fixed fee—typically, $10,000."
The problem is that the bond issuers priced the bonds as if they were dealing with bondholders of average lifespan. If people of shorter-than-average lifespan are buying the bonds, then the risk of early repayment is much higher than estimated and the bonds are underpriced, providing a profit opportunity. All Lathen did was take advantage of the underpricing of the bonds to pocket some profits, which is exactly what we would expect any rational and fully-informed market participant to do.

Read the full story to hear about the Securities and Exchange Commission crying foul and how they are fighting back. How often would you expect to see the SEC
protecting financial institutions from the negative consequences of the terms and conditions in their own contracts?

[HT: Marginal Revolution]

Sunday, 21 August 2016

Harry Potter and the chamber of scalpers

The Economist had an interesting story this week about ticket scalping, particularly related to the new stage show Harry Potter and the Cursed Child. Scalping is a regular favourite topic for economics teachers, as I have noted before. From The Economist story:
TICKETS to “Harry Potter and the Cursed Child”, the latest, on-stage instalment in the magically lucrative series, have proved harder to grasp than the golden snitch. After 250,000 tickets released on August 4th sold out within hours, fans’ disappointment turned to outrage as stubs with a face value of £15-70 ($20-90) started popping up on resale websites for more than £8,000.
In line with the howls of outrage, the play’s producers called the secondary ticket market an “industry-wide plague” and asserted their contractual right to refuse entry to people turning up with a resold ticket...
Rather than allowing touts to profit, the play’s producers could take a cue from “Hamilton”, a wildly successful Broadway musical, and raise prices for the premium seats until demand falls in line with supply (even at up to $849 per ticket, some argue that “Hamilton” is too cheap). But the Potter producers seem to be more worried about impecunious wizarding fans losing out than about the prospect of touts swiping surplus.
If you are trying to provide tickets at below-equilibrium prices to fans, then you have to expect the entrepreneurial types to buy some (maybe most) of those tickets for re-sale to fans who are willing to pay more than the face price but would have missed out otherwise. The interesting thing is that the actions of the ticket scalpers doesn't change economic welfare in total, they simply redistribute the welfare.

Consider the diagram below. The supply of tickets to the Harry Potter show S0 is fixed at Q0 - if the price rises, more tickets cannot suddenly be made available because the capacity of the theatre is fixed (note the diagram assumes that the marginal cost of providing tickets up to Q0 is zero).


Demand for tickets is high (D0), leading to a relatively high equilibrium price (P0). However, tickets are priced at P1, below the equilibrium (and market-clearing) price. At this lower price there is excess demand for tickets (a shortage) - the quantity of tickets demanded is Qd, while the quantity of tickets supplied remains at Q0.

With the low ticket price P1, the consumer surplus (the difference between the price the consumers are willing to pay, and the price they actually pay) is the area ABCP1. Producer surplus (essentially the profits for the theatre) is the area P1CDO. Total welfare (the sum of producer and consumer surplus) is the area ABCDO. At the higher price P0 due to the actions of scalpers (buying at P1 and selling at P0), the consumer surplus decreases to ABP0, while producer surplus remains unchanged. The scalpers gain a surplus (or profit) of the area P0BCP1, and total welfare (the sum of producer and consumer surplus, and scalper surplus) remains ABCDO. So the ticket scalpers don't reduce total welfare - their actions don't result in a deadweight loss.

If the ticket sellers want to cut out the scalpers, they need to either raise prices (so that the scalpers can no longer profit), or undertake costly measures to destroy the secondary market for tickets. From The Economist article:
Restricting the secondary market is possible, but only with great effort. The government’s review reported that the Glastonbury model, where festival-goers must show proof of identity alongside their ticket, works, but only because the organisers have such tight control over everything about the process, from ticketing to the venue.
I note that the NFL has its own ticket exchange, where ticket holders can on-sell their tickets to other fans (other sports teams are increasingly doing the same). This doesn't stop the scalping, it just shifts it online and allows the teams to take a cut. Perhaps theatre companies need to do the same. If you can't beat them, join them?

Saturday, 20 August 2016

When avocado demand outstrips supply

'Demand outstripping supply' is one of those emotive and overly used phrases in the media. Sometimes it makes sense, but often not. Take for example this article from last week's New Zealand Herald, on the market for avocados, and in particular this bit:
A smaller crop size and high demand last season saw avocado prices reach a record high of up to $5 each, sparking a thriving blackmarket [sic] for the fruit.
A number of thefts from orchards across New Zealand were also reported as demand outstripped supply, with several being hit multiple times.
I have a couple of points to make on this. First, if demand is 'outstripping' supply, then to me that implies excess demand (a shortage) - that is, there aren't enough avocados to satisfy everyone who wants to buy them. In that case then prices should rise (which they did - as noted above to a record high of $5 each). However, as the price rises the quantity of avocados demanded will reduce (fewer consumers are willing and able to buy avocados at higher prices). If given long enough to adjust the price of avocados will reach a new equilibrium, where quantity demanded is equal to quantity supplied. That is, there is no longer any 'demand outstripping supply' if the price has fully adjusted.

You might suggest that perhaps the price has not fully adjusted. But in that case, then what are the retailers doing? They're just giving away profits. They could have sold those avocados for an even higher price. Their shareholders/owners should be on the warpath. We should expect that 'demand outstripping supply' will always be a very short-lived phenomenon. Particularly if there was a black market (where low priced fruit purchased from a retailer are re-sold at a price much closer to, if not at, the equilibrium price).

Second, the last sentence also shows the role of incentives. This relates back to an post of mine from last year (on rational onion thefts; just substitute 'onion' for 'avocado' in this explanation):
...when the price of onions increases, we might expect to see more onion thefts. Why? The benefits of onion theft have increased, while the costs (in terms of the risk of punishment) probably haven't much changed. We can describe two mechanisms for why this would increase onion thefts. First, career vegetable burglars (or maybe just the generally criminally-inclined) recognise that there are larger profits to be had by stealing onions for resale. So, they steal more onions (or maybe they start stealing onions). Second, ordinary people now face higher costs of purchasing onions. So, perhaps stealing onions becomes a lower cost alternative for them, so they steal rather than purchase.
Note that the first explanation has little to do with 'demand outstripping supply', and is purely a result of higher avocado prices. 'Demand outstripping supply' would only be a direct cause for avocado thefts if it was avocado consumers committing the thefts, which seems unlikely.

Wednesday, 17 August 2016

The case against privatisation

This week in ECON110 we finished up discussing the economics of government by looking at public goods, and public provision of goods and services. In the case of the latter, Diane Coyle (in her excellent book which shares the name of my blog) discusses three principles that almost always apply when the government provides goods or services:

  1. The government can almost always raise large amounts of money more cheaply than the private sector (because the government is in most cases lower risk than private firms, it pays a lower interest rate on borrowings);
  2. The government is almost always worse at running things than the private sector (think about the difference in service quality in particular); and
  3. Whenever the good has a large externality, or is a public or merit good, the government is almost always going to have to be involved anyway.
I like to add to that last point that, with quasi-rational decision makers who heavily discount the future (present bias), then the government is likely to need to be involved in provision of goods and services that have long-term payoffs (e.g. education).

The elephant in the room in this discussion of course is privatisation, which we didn't touch on (surprisingly - in most semesters at least one student would bring it up). Coyle's three principles would seem to argue for privatisation. In the case of infrastructure for example, the principles suggest that the government can fund the development of the infrastructure (which can be paid for with lower interest costs), then privatise to avoid much of the problems of the second principle (except in cases where there isn't a strong externality or public or merit good argument for continued government provision).

Which is why I really liked this Christopher Niesche piece in the New Zealand Herald earlier this month, which makes a strong case against privatisation based on comments from Rod Sims (chair of the Australian Competition and Consumer Commission):

For many years politicians and business people have told us privatisations are good.
Selling government-owned assets to the private sector makes them more efficient, to the benefit of us all, they have said.
It was a view shared by Rod Sims, chair of the Australian Competition & Consumer Commission, but he's now on the verge of changing his mind, saying privatisations are pushing up prices for consumers and damaging the economy...
He now argues that, instead of privatising assets such as ports, airports and power infrastructure to boost economic efficiency, Governments are just trying to maximise their profits. They do this by selling monopolies to the private sector without enough regulation to rein in excessive price hikes, thereby making the sale price higher...
But left-wing fogeys shouldn't get too carried away by Sims' comments. He is still in favour of the "theory" of privatisations: that they generally increase economic efficiency and bring down prices for consumers.
He points to the privatisations of Telecom (now Telstra) and Qantas. We do indeed have cheaper phone services and air travel but this is largely because Telstra and Qantas were privatised about the same time their industries were deregulated, introducing the disciplines of competition into the equation as well.
Privatising a monopoly is different altogether.
Indeed. If the argument for privatisation is based (in large part) on the private sector being better at running things than the government, it is hard to make a case where creating a monopoly is necessarily better. For instance, we know that monopolies are X-inefficient - relative to firms in more competitive markets, monopolies have less incentive to innovate or improve customer service, leading to relatively worse quality of products and service over time (compared with a firm in a more competitive environment). Government-owned monopolies are X-inefficient as well of course, but you don't solve that problem by privatisation, you solve it by increasing competition.

Privatising a monopoly is very attractive to investors - monopolies can make big profits, which can mean good returns on investment. But simply being able to extract money from privatisation doesn't mean that privatisation is always the right approach for government to take.

Sunday, 14 August 2016

A torturous average vs. marginal tax rates example

In ECON110 last week, we ran out of time to go fully through an example on the difference between average and marginal tax rates, and the difference between progressive and regressive taxes. Fortunately, in the last week Jodi Beggs at Economists Do It With Models has just written a couple of posts on taxes (see here and here). So, I'm going to borrow from her second post to illustrate.

Jodi outlines an income tax regime that works as follows:
  • 10% for income $0 to $9,275
  • 15% for income $9,275 to $37,650
  • 25% for income $37,650 to $91,150
  • 28% for income $91,150 to $190,150
  • 33% for income $190,150 to $413,350
  • 35% for income $413,350 to $415,050
  • 39.6% for income $415,050+
Now, let's think about three taxpayers. Taxpayer 1 has income of $30,000; Taxpayer 2 has income of $90,000; and Taxpayer 3 has income of $450,000. What are their average and marginal tax rates, and why does it matter?

The average tax rate is just the proportion of income that is paid in tax. That can be calculated as [Tax Paid]/[Income]. When the tax system is not straightforward then calculating the tax paid can take multiple steps (see below). The marginal tax rate is just the proportion of the next dollar earned that would be paid in tax. The difference between the two rates is important, and people don't always appreciate why. It's the marginal tax rate that matters for decision-making, since we make decisions at the margin. If we are thinking about whether to work another hour or not, the tax we pay on that next hour of wages is the relevant tax rate. However, as Jodi notes:
...while you mainly want to keep your marginal tax rate in mind for decision-making purposes, I guess it could make you feel better to calculate your average tax rate and be reminded that the federal government isn’t taking all of your money in income taxes.
Back to our example. The tax paid by Taxpayer 1 (on their income of $30,000) is $4,036.25. They pay $927.50 on their first $9,275 of income ($9,275 * 10%), and then $3,108.75 on the remaining $20,725 of income between $9,275 and $30,000 ($20,725 * 15%). The average tax rate for Taxpayer 1 is 13.45% ($4,036.25 / $30,000). Their marginal tax rate is 15% (if they earned one more dollar, that's the rate of tax they would pay on that dollar).

The tax paid by Taxpayer 2 (on their income of $90,000) is $18,271.25. They pay $927.50 on their first $9,275 of income ($9,275 * 10%), then $4,256.25 on the next $28,375 of income up to $37,650 ($28,375 * 15%), and then $13,087.50 on the remaining $52,350 of income between $37,650 and $90,000 ($52,350 * 25%). The average tax rate for Taxpayer 2 is 20.30% ($18,271.25 / $90,000). Their marginal tax rate is 25%.

Finally, the tax paid by Taxpayer 3 (on their income of $450,000) is $134,370. They pay $927.50 on their first $9,275 of income ($9,275 * 10%), then $4,256.25 on the next $28,375 of income up to $37,650 ($28,375 * 15%), then $13,375 on the next $53,500 of income up to $91,150 ($53,500 * 25%), then $27,720 on the next $99,000 of income up to $190,150 ($99,000 * 28%), then $73,656 on the next $223,200 of income up to $413,350 ($223,200 * 33%), then $595 on the next $1,700 of income up to $415,050 ($1,700 * 35%), and then $13,840.20 on the remaining $34,950 of income between $415,050  and $450,000 ($34,950 * 39.6%). The average tax rate for Taxpayer 3 is 29.86% ($134,370 / $450,000). Their marginal tax rate is 39.6%.

Phew! You might think that the above example was difficult. That's why we have tax software to do the work. But this example is relatively straightforward when you compare with the complex system of rebates and tax deductions that most tax systems include (in New Zealand we have low income rebates, Working for Families credits, as well as social security payments and accommodation supplements, all of which decrease as more income is earned). Once we factor in decreases in government transfers, rebates, and entitlements, we are calculating what we call the effective marginal tax rate.

Notice that in the case of all three taxpayers the marginal tax rate is greater than the average tax rate. That characterises an income tax system that is progressive. This is a tax system where, as incomes increase, the proportion of the income paid in tax increases. In contrast, for a regressive tax system the marginal tax rate is less than the average tax rate (and higher incomes are associated with a lower proportion of income paid in tax), while for a proportional tax system the marginal and average tax rates are the same (and the proportion of income paid in tax is the same at all levels of income).

Saturday, 13 August 2016

How a (property transfer) tax could lower prices

Last week, Vancouver introduced a new property transfer tax for foreign buyers. As reported in the New Zealand Herald:
Foreign nationals buying Vancouver real estate will pay an additional property transfer tax of 15 per cent as part of an effort to address high real estate prices and low vacancy rates.
Wait - don't taxes raise prices? Won't taxing foreign buyers make prices even higher? No it won't - and here's why. Consider the property market as two submarkets - the submarket for sales to domestic buyers, and the submarket for sales to foreign buyers. These two markets are represented in the diagrams below. Note that a seller will be indifferent between selling to a domestic or a foreign buyer - it doesn't matter to them who the buyer is. So, the price is the same (P0) in both submarkets. However, note that demand in the foreign buyer submarket is more elastic (flatter), because foreign buyers have many more options (they can buy in Australia, Canada, New Zealand, Uruguay, etc.), so more substitutes are available.


Now introduce a tax, but only in the foreign buyer submarket. For simplicity, assume that the tax is paid by the sellers (since the seller is collecting money from the buyer anyway, their lawyers can simply collect more and pass the tax onto the government). This situation is shown in the diagram below - the Si+tax curve represents the effect of the tax on the market [*]. Note that the price that the foreign buyers have to pay increases to Pi. However, the effective price that sellers receive (after paying the tax to the government) falls to Ps. The difference between Pi and Ps is the tax. Note that the effect of the tax on the price is larger for the sellers than for the buyers - the price the buyers pay only increases a little, but the sellers are made much worse off. In other words, the burden of the tax on foreign buyers actually falls mostly on the sellers. So, because sellers are made (much) worse off by selling to foreign buyers, they would now prefer to sell to domestic buyers instead (where they can receive the higher price P0).


So, what happens next is that sellers start offering more houses to domestic buyers, increasing supply in the domestic buyer submarket to S1. (as shown in the diagram below). This lowers the price in that submarket to P1. Simultaneously, because there is more supply into the domestic buyer submarket, there must be less supply into the foreign buyer submarket - supply there decreases to Si1 (and note that the effect of the tax is now represented by Si1+tax). These shifts in supply in the two markets continue until eventually the price received by the sellers is the same in both submarkets (P1). The foreign buyers pay the higher price (Pi1), and after paying the tax the sellers in that submarket receive the price P1, which is the same as they would receive in the domestic buyer submarket. Importantly, note that the effect of the tax is to lower the price for domestic buyers, which is what was intended.


Having said that, it's only a partial solution to the unaffordability of housing. My preferred solution to housing is still to introduce stamp duty and use the proceeds to scale up house construction.

*****

[*] Note that I have shown the tax in these diagrams as a specific tax (i.e. a constant value per house) rather than an ad valorem tax (a tax that is some percentage of the value of the house), purely for simplicity. The overall effect on the submarkets is qualitatively the same for both types of tax.

More from my blog on Auckland housing:

Thursday, 11 August 2016

Distance matters less for students going to high quality universities

A new paper published in the journal Spatial Economic Analysis (sorry I don't see an ungated version anywhere) by John Cullinan and Jim Duggan (both National University of Ireland, Galway) uses gravity modelling to investigate the factors associated with student flows from secondary schools to tertiary institutions in Ireland. I really like gravity modelling, and it's an approach that I've been applying to internal migration flows in New Zealand in two MBIE-funded projects (see here and here), and a Marsden-funded project (see here). Cullinan and Duggan's paper was the first time I have seen it applied to student flows to universities (though it is not the first paper to do this).

Essentially, a gravity model suggests that the flow (of migrants, trade, or students) between two places is positively related to the 'economic' size of the origin (more potential migrants, or more things to trade), the economic size of the destination (more opportunities for migrants, or more demand for tradeable goods), and negatively related to the distance between the two places (since movements over longer distances are more costly). The gravity modelling approach does a pretty good job of explaining trade and migrant flows, even without including any other variables - whether they be factors in the origin that 'push' migrants out, or factors in the destination that 'pull' them in.

Cullinan and Duggan include both school-level variables (push factors) and tertiary-institution-level variables (pull factors) in their models. They find that:
...school size, girls-only schools, mixed-gender schools and Catholic schools are associated with higher students flows, all else being equal. On the other hand, schools with DEIS [disadvantaged] status are found to be associated with lower student flows. The effect for schools located in more deprived areas is somewhat surprising, suggesting flows are lower from schools located in more affluent areas.
Given that they have already controlled for schools that are considered disadvantaged, that last result might not be as surprising as it seems. The size of the effect is tiny. They also note that:
...HEIs [Higher Education Institutions] located in Dublin are found to have lower predicted student flows once the other factors are accounted for, an effect that may be driven by the higher costs of living in the capital city.
It might also be because the top two universities (Trinity College Dublin and University College Dublin) are both located there, and will be the most selective in terms of their student intakes. Finally, one other result I found particularly interesting (though not necessarily surprising):
...the average [distance] elasticity masks considerable variation both within and across HEI types, suggesting that students are much more willing to travel further to attend some HEIs than others.
Specifically, the distance elasticities were lowest for Trinity College Dublin and University College Dublin, as you might expect for the highest quality universities.

It would be really interesting to repeat a similar analysis for New Zealand, and I expect the IDI holds the necessary data (it certainly has tertiary data and secondary school data - the question is whether they are easily linked). This would be even better than the Irish study, as there are many years of data available, rather than just a single cross-section. There's definitely a potential future Honours or Masters project in that.

Wednesday, 10 August 2016

Rational cheating at self-service checkouts

I really enjoyed this article by David Glance (University of Western Australia) on cheating at self-service checkouts. Glance wrote:
Despite some technological safeguards, self-service checkout machines in supermarkets rely heavily on customer honesty to scan, and pay for, their shopping. It turns out however, that around a third of all customers “cheat” the machines in some way...
Nobel prize winning economist Gary Becker has proposed the “Simple Model of Rational Crime” to explain this type of behaviour. He put forward the view that people do a simple “cost-benefit analysis” of every given situation to decide whether they are going to be dishonest. In deciding whether to park illegally for example, they will weigh the benefits of free parking against the risk of getting caught and the consequences of a fine if that does, in fact, happen.
Under Becker's model, in the case of supermarket self-checkout cheating the chance of being caught is probably fairly low (the employees aren't watching everything you do), and the penalty is likely to be low as well (probably you get let off with a warning unless your cheating is particularly egregious). So the explicit costs of this behaviour are pretty low, relative to the benefits. Remember that a rational decision maker will do an action if the expected benefits outweigh the costs. Even if the monetary benefits outweigh the costs though, not everyone cheats because there are still moral incentives (based on what you believe about right and wrong) and social incentives (based on what other people perceive as right and wrong) that also affect our behaviour.

Glance continues:
What behavioural economist Dan Ariely has discovered however, is that cheating is an irrational process that a large number of us will actually do. However, this type of dishonesty is always for small amounts. Ariely calls this amount the “fudge factor”. It can be dismissed as being inconsequential in comparison to the overall amount of a transaction. This type of cheating is independent of the potential reward and the likelihood of being caught, undermining Becker’s rational model of crime...
This is exactly the same type of behaviour that is seen when people download movies, get around a new’s [sic] site’s firewall, or even cheat in an online test. 
I'm not convinced that Ariely's work necessarily undermines Becker's model. At least, not to the extent that the model needs to be thrown away. Moral and social incentives are important here. If many people are cheating, and few people see cheating as a problem, then the social incentives to avoid cheating are relatively weak, and more people will cheat. Observing a lot of cheating in lab experiments is not surprising - in the lab there are very weak moral and social incentives not to cheat (since lab experiments are like a game). I'm not knocking Ariely's work, which is important and credible. It just doesn't mean that the rational crime model is necessarily completely wrong. Really Ariely and Becker have provided complementary explanations.

However knowing this, what can be done? Glance says:
Because this behaviour is irrational, it can be manipulated to reduce its happening. Ariely has found that if you get people to simply sign a statement saying that they will behave morally and won’t cheat, they do in fact cheat less...
What is important with this practice however is that it needs to be done before the task is carried out and only has a limited time that its effect will last. Asking students to agree to act honestly before an online quiz is likely to be effective, whereas getting them to sign a statement after they have written an essay and attach it to their submitted work, is not. In the case of the self-service checkout systems, a simple introductory screen that asked shoppers to agree that they will be honest would likely be effective in reducing cheating at the checkout. Another way would be to have a staff member who greets every shopper as they come to the checkout and reminds them that they will be there to help if needed.
Reminding people about right and wrong impresses on them the moral and social incentives to 'do the right thing'. It makes those incentives more salient in the decision about whether to cheat or not, so both rational and quasi-rational people will be less likely to cheat. It won't work for everyone, but you shouldn't expect any solution to be a silver bullet.

[HT: New Zealand Herald]

Tuesday, 9 August 2016

Footballer earnings, superstar and tournament effects

In ECON110, we talk about the reasons that not all workers in the same labour market receive the same wage. In the 1980s, Sherwin Rosen identified 'superstar effects', where if a worker can satisfy the demand from many consumers, they get paid a higher wage. Essentially, the worker is rewarded for generating high revenues for their employer, as you would expect. This explains much of the rise in salaries over time for top sportspeople - as television (and more recently internet) viewership has grown, the value generated by a top sportsperson (in terms of the number of viewers they attract) has grown, and their salaries have grown as a result.

Rosen, along with Ed Lazear, also described 'tournament effects'. With tournament effects, people are paid a 'prize' for their relative performance (that is, for winning the 'tournament'). The prize may take the form of a bonus, a raise, or a promotion. The point is that each worker only needs to be a little bit better than the second best worker in order to 'win' the tournament.

As an example of tournament effects, consider a team of 20 players, who are all roughly equally talented but can be ranked from 1st to 20th in terms of their ability to attract consumers to buy products that they have endorsed. Let's assume that each player can endorse no more than two products (due to time constraints). Now say that there are 20 firms willing to pay the players to endorse their products, and we can rank the companies by their willingness-to-pay. The firm with the highest willingness-to-pay is willing to pay $20 million, and the second $19 million, the third $18 million, and so on down to the last firm which is willing to pay just $1 million. What happens?

The top player receives endorsements of $39 million (from the two firms willing to pay the most), the second player receives $35 million (from the third and fourth firms), the third player receives $31 million (from the fifth and sixth firms), and so on. The table below shows player earnings for all 20 players (ranked from 1st to 20th). Notice that the top earning players earn a lot, but half of the players earn nothing. This arises even though the players are all roughly equally talented, and leads to a highly skewed earnings distribution.


Obviously the example above is totally made up and very simplistic, but it's not so far from what we observe in the real world. Consider the earnings of top footballers. Even if we consider only the top ten players (by earnings, according to Forbes' 2016 list), this is what we see:


It would be difficult to argue that Ronaldo or Messi generate more than twice as much value as the others on this list, so the difference must be generated by something other than just superstar effects; that is, tournament effects. That is, when we look at players at a similar level of play, the difference in earnings is mostly tournament effects. In contrast, the difference in average salaries in England between Premier League footballers (£1.7 million) and League Two footballers (£40,350) is likely to be a mix of superstar effects (Premier League footballers generate more value for their employers than League Two footballers) and tournament effects (there's a limited number of places for Premier League footballers, so slightly worse players end up in lower divisions paying less).

One last point: It's been argued (I saw this argument first in Tim Harford's book The Logic of Life) that the size of the 'prize' for a tournament will be larger the more luck is involved. That is, if the difference between the tournament 'winner' and the others is mostly luck, the size of the bonus for working hard to win the tournament must be high in order to sufficiently incentivise the worker to work hard. So, if you buy that the difference in the graph above is mostly a tournament effect, does that mean that the earnings difference between Ronaldo and Messi at the top, and Neymar in third, is mostly down to luck?

Sunday, 7 August 2016

Maybe there's one less worry about measures of happiness

Measures of happiness or subjective wellbeing essentially come down to responses to a question like: "Overall, how satisfied are you with your life at the moment?" There are a number of problems with that sort of question, not least of which is that it can be influenced by recent and usually unobserved factors such as the weather. That is, if the day is sunny and warm (but not too hot) you probably feel a bit happier than on a cold, rainy day, and most studies would not be able to control for the effect of the weather on your happiness. So that would lead to omitted variable bias in any analysis of the factors associated with happiness.

Which makes this recent paper from the journal The Manchester School (sorry I don't see an ungated version anywhere) by Franz Buscha (University of Westminster) potentially quite important. In the paper, Buscha uses data from the British Household Panel Survey, which allowed him to identify the day and location of each interview, and therefore match weather data to each observation. Past studies have sometimes shown relationships between weather and various measures of subjective wellbeing, but in this case the results were very weak:
Results suggest that, in general, there is little correlation between measures of well-being and the weather. None of the correlation coefficients exceed an absolute value of 0.05, which suggests that, at least in a descriptive setting, there is little interaction between weather and well-being responses.
When using more robust regression methods:
...results suggest that the causal effect of weather on individual measures of well-being is generally statistically insignificant. 
There were some weak statistically significant relationships, but the size of the effects were tiny. So, overall this suggests that we may have little to worry about in terms of whether the weather is causing problems for happiness studies. However, this study was in Britain, and most interviews were in the autumn, and the weather in Britain in autumn is typically rubbish (according to the paper "[t]he ‘average autumn day’ ... includes a gentle breeze, some low-intensity rainfall, moderate temperatures and roughly half sunshine/half cloudy weather"). Perhaps a further study in a more varied (and nicer) climate is required?

Thursday, 4 August 2016

Stocks vs. flows, example #515

Every now and again (and far too often for my liking), the media demonstrate their lack of basic economic literacy and come up with another example of my pet peeve - inappropriately comparing a stock (e.g. a firm's market capitalisation) with a flow (e.g. a country's GDP). The latest example comes from this opinion piece in the New Zealand Herald by Juha Saarinen:
Don't forget that Uber is valued at $82.3 billion currently.
In comparison, Statistics NZ pegs the local economy this year at around the $240b mark. Uber is bigger than our entire, $65b export sector.
Taking Uber's market capitalisation as $82.3 billion - that's the total value of all shares of Uber, and as good a measure as any of the total value of the firm. New Zealand's GDP is $240 billion according to Saarinen (actually more like $250 billion now, but let's not quibble). That's not a measure of the total value of the New Zealand economy. It's a measure of the total market value of goods and services produced by the economy in one year. It measures the value added by the New Zealand economy in one year. A better comparison is between New Zealand's GDP and Uber's net revenue (estimated at a not insubstantial US$1.5 billion for 2016). So, the New Zealand economy is about 120 times bigger than Uber (at current exchange rates). A similar comparison should be made with exports (which are measured in value-added terms). Uber is not bigger than the entire export sector - the New Zealand export sector is some 30 times bigger than Uber.

In essence, it isn't necessary to overstate the size of Uber by making inappropriate comparisons. We get the picture. Uber is a big firm. It just isn't as big as our entire economy (or even our entire export sector).

Wednesday, 3 August 2016

Arguing from a quantity change... Shrimponomics edition

Yesterday I set out a list of the best bits from the new Levitt and Dubner book "When to Rob a Bank", but I held one bit back for today. When teaching introductory microeconomics (ECON100 and ECON110), we try to teach our students not to argue starting from a price or quantity change, and instead start from a change in demand or supply. This is challenging for them, because when we look at markets we see prices (and to a lesser extent quantities). So it's tempting to jump straight to interpreting any change in the market first as a price change (or a quantity change).

Which made the discussion in this post on Shrimponomics from the book interesting to me:
A few days back I posed the question “Why are we eating so much shrimp?” Between 1980 and 2005, the amount of shrimp consumed per person in the U.S. has nearly tripled...
I asked the question because Shane Frederick, a marketing professor at MIT’s Sloan School, had contacted me with an intriguing hypothesis. He wrote about a striking regularity in the responses he got when he asked different people why we are eating so much shrimp:
"Psychologists (indeed, probably all non-economists) give explanations that focus on changes in the position of the demand curve — changes in preferences or information etc., like:
1) People are becoming more health conscious and shrimp are healthier than red meat;
2) Red Lobster switched ad agencies, and their ads are now working;
and so on.
Economists, by contrast, tend to give explanations that focus on “supply,” like:
1) People have designed better nets for catching shrimp;
2) Weather conditions in the Gulf have been favorable for shrimp eggs;
and so on."
I found Shane’s hypothesis compelling. When I teach intermediate microeconomics, the students seem to understand demand a lot more easily than supply, even though (1) they see demand first, and (2) the graphs and the equations are almost identical for supply and demand, except that the labels on the variables change. Most of us have a lot more experience being consumers than producers, so we tend to view things through the lens of demand rather than supply. We need to have an appreciation of supply factors trained into us by economists.
I wonder what my students would have made of this question? Maybe I should include it in a future test or exam? I have to admit that my initial reaction to the question was wanting to also know what happened to price (not just quantity).

Knowing what happens to price would allow us to sort out the competing explanations. An increase in quantity traded over time is consistent with any of three basic possibilities: (1) an increase in demand (in which case price should rise); (2) an increase in supply (in which case price should fall); or (3) both (in which case the change in price could be in either direction). [*]

Which of the above is correct? According to Levitt, it turns out probably (2):
I’m not exactly sure, but here is what I can glean from the Internet. A key factor is that prices have dropped sharply. According to this academic article, the real price of shrimp fell by about 50 percent between 1980 and 2002. When quantity rises and prices are falling, that has to mean that producers have figured out cheaper and better ways to produce shrimp. This article in Slate argues that there has been a revolution in shrimp farming. Demand factors may also be at work, but they don’t seem to be at the heart of the story.
Although an absence of evidence on an increase in demand doesn't mean it didn't also happen, so (3) remains a possibility too.

*****

[*] There are two other possibilities of course - a relatively large increase in supply coupled with a relatively smaller decrease in demand (and price would fall); and a relatively large increase in demand coupled with a relatively smaller decrease in supply (and price would rise).

Tuesday, 2 August 2016

A collection of the best bits from "When to Rob a Bank"

I've just finished reading the latest book by Steven Levitt and Stephen Dubner, "When to Rob a Bank ... and 131 More Warped Suggestions and Well-Intended Rants". Essentially it's a collection of their best blog posts from the Freakonomics blog. They rightly point out in the opening section that collecting blog posts together into a book is a bit like selling bottled water - selling something that can be obtained for free (or at least with a low opportunity cost).

To save you at least some of the opportunity cost of reading the whole book (which I do recommend - it's a much better read than their previous book), I've collected here links to what I think are the best bits from the book:

Enjoy!