Tuesday, 29 March 2016

Even a deforestation tax might not have saved Easter Island

A couple of weeks ago I reviewed Jared Diamond's 2005 book Collapse. One of the examples he uses in the book is Easter Island. So, I was interested to read this recent paper (sorry I don't see an ungated version anywhere) by Cyrus Chu (Academia Sinica, Taiwan), Ching-Chong Lai (Academia Sinica, National Cheng Chi University, and National Sun Yat-Sen University, Taiwan), and Chih-Hsing Liao (Chinese Culture University, Taiwan).

In the paper, the authors take a theoretical approach to economics and sustainability, illustrated by the idea of Easter Island (but of course, not by empirical data). The premise is of general interest to my ECON100 students, particularly since we will cover economics and sustainability in the final week of the semester.

The traditional idea of why economies (like Easter Island) collapse is because economic agents maximise their own utility from consumption over their own lifetimes, largely ignoring the consumption of future generations. This means that agents have little incentive to leave resources available for the future, so will over-consume those resources now. Of course, this denies any altruistic incentives for agents.

Chu et al. take a more realistic approach, with agents who have preferences for consumption with an infinite time horizon (essentially, more consumption today is good, but more consumption at all possible future times even after the agent is long dead is also good). However, the good news story ends about there.

Chu et al. show using a theoretical (endogenous growth) model that even with these more altruistic (and sustainability-loving) agents, the resulting rate of economic growth may be unsustainable and lead to depletion of the (limited) natural resource. They even show that a deforestation tax might not be able to arrest this unsustainability, if the rate of forest destruction is high (but the tax would be effective if the rate of forest destruction is low). Unfortunately, how high is a 'high deforestation rate' is left unanswered (as is typical of theoretical papers). However, the overall conclusion that even when we want to act sustainably (and the government is incentivising sustainability) we may not be able to have sustainability, is a little disconcerting.

On a good news note though, I also recently read this paper by Charles Kenny of the World Bank (ungated earlier version here). I'm not a believer of Malthusian ideas, and this paper confirmed a lot of my priors. Kenny shows that almost nowhere in the world is consistent with a Malthusian population trap, even in sub-Saharan Africa. I especially like this bit from Kenny's conclusion:
These cases of only incomplete inaccuracy aside, from the time of writing onwards Malthus' Essay on the Principle of Population was almost completely wrong about the future course of human history not just in England or Europe, but worldwide. The greatest reason that Malthus was wrong about the course of global history was that he underestimated the power of technological change to increase output and improve health.
Maybe technology is a path to long-term sustainability, even if government incentives and our own preferences alone are not sufficient to ensure it?

Monday, 28 March 2016

The ecological fallacy, and who votes for fluoridated water

The debate about fluoridation of town water supplies is an ongoing feature in many New Zealand towns and cities (as one example, consider Whakatane District Council, which first voted to remove fluoride from the town water supply, only to reverse their decision two weeks later). Whakatane actually held a referendum in 2013, where some 60.5 percent of those who voted were in favour of fluoridation. I think the science is pretty clear (e.g. see here), so I wonder who votes against fluoridation? Is it just libertarians (who are against fluoridation on principle), or is it more like the anti-vaccine movement?

I read an interesting paper today on the topic, by Philip Hersch and Jodi Pelkowski (both Wichita State University) and published in Applied Economics Letters (sorry I don't see an ungated version anywhere online). In the paper the authors look at voting data from three referendums on fluoridation - two referendums in Wichita, Kansas (in 1978 and 2012) and one in Portland, Oregon (in 2013) - and attempt to determine "the factors driving voter demand for and against fluoridation". Which would be great, if the authors had access to the data from individual voters, but they don't. Instead they use data aggregated to voting precincts. And this makes their interpretation of results susceptible to the ecological fallacy.

The ecological fallacy arises when inferences about individuals are drawn from an analysis of groups to which those individuals belong, or an analysis of geographical areas in which those individuals live. There are a number of papers which explain the fallacy (e.g. try this one (gated), or this one (ungated) for a more mathematical treatment). However, it is simplest to explain with an example.

One of the most widely cited examples of the ecological fallacy is drawn from the work of Emile Durkheim on suicide in 19th Century Prussia. Durkheim found that suicide rates were higher in provinces that had higher proportion of Protestants in the population (and lower proportion of Catholics). If we infer from this result that Protestants were at higher risk of committing suicide, we would be committing the ecological fallacy (by inferring that the group-level analysis tells us something about the individuals belonging to each group). It may be that Catholics living in provinces surrounded by many Protestants were more likely to commit suicide. The group-level (province-level) analysis cannot distinguish these two possibilities (or indeed, a number of other possible explanations).

Coming back to the fluoridation voting paper, because the analysis was conducted at the voting precinct level, nothing can be inferred about individual voters' preferences based on the precinct-level analysis. Hersch and Pelkowski are generally pretty good, however not always so. For example, they say:
%College is strongly positive in all regressions, indicating that educated voters are more likely to subscribe to the mainstream science.
No, this is the ecological fallacy. What they should have said was: "%College is strongly positive in all regressions, indicating that voters who live in voting precincts that have a more educated population are more likely to subscribe to the mainstream science". Notice the difference?

Similarly, where Hersch and Pelkowski  conclude:
Fluoride support is weaker among residents known to have been raised in a nonfluoridated environment, than for residents who were born elsewhere.
They should instead have said: "Fluoride support is weaker in voting precincts where a greater proportion of the population is known to have been raised in a nonfluoridated environment, than in voting precincts where a greater proportion of residents were born elsewhere".

The takeaway message here is that, as researchers we need to be careful when we do analyses using geographical-level averages (as in my work on alcohol outlet density with Bill Cochrane, Michael Livingston and others), that we do not fallaciously draw inferences at the individual level from our results.

Finally, the results from the Hersch and Pelkowski article are interesting. Sticking with results that are common across all three referendums, voting precincts that have a higher proportion of people with a college education, and those that have a lower proportion of the population born in that state, are more likely to vote for fluoridation. The results for political affiliation were more mixed, with some suggestive results that voting precincts with a higher proportion of libertarian and conservative voters (in Wichita 1978) and precincts with a higher proportion of Green Party voters (in Portland 2013) having lower proportions of voters in favour of fluoridation. Of course, we can't directly infer anything from the this last result about the voting preferences of libertarians or Green Party supporters. We would need individual voter-level data to do so.

Sunday, 27 March 2016

The great dairy price conspiracy?

Let's say that your country was the world's largest consumers of an agricultural product (or at least, the largest buyers on the international market for that product), and that changes in your country's demand for that agricultural product were enough to produce significant shifts in the world price of that product. Now say your long-term goal was to move from being a global consumer of this product, to being a producer (or at least, securing your own supply so that you wouldn't have to rely on the world market any longer). How would you go about achieving this goal?

One way might be to invest in production capacity in your own country, or to purchase land and production facilities in other countries at market rates. It might take a while, but you might eventually purchase enough capacity to become self-sufficient (but at a high cost).

But wait... your demand for the agricultural product is so important to the world market that you can influence the prices (you have market power). So, if you decrease your demand for the agricultural product, then the world price will fall. The profits of farmers in other countries will decrease, and the value of land and production facilities will fall (because the demand for productive land is determined by the value of the marginal product of land - that is, by how much value that land can generate - and that value has fallen because the agricultural product it produces now receives a lower price). So, with lower demand for the agricultural product and lower land prices, you can buy the land and production facilities at a lower price.

But will farmers sell? Farmers with a long-term perspective will surely recognise that your lower demand for the agricultural product is temporary, and will be willing to endure some short-term pain in anticipation that your demand will return to normal in the future.

Realising this, you need to find some way of forcing farmers to sell. What if you first increased the demand for the agricultural product, buying lots of it on the world market, and driving up the price? This would give you a good buffer stock of the product before you moved onto Stage 2 of the plan (lowering demand). 

Even better, with prices high farm profits will be high and land prices will also be high. So, every time a farm changes hands it will do so at a high price, and since most farmers do not have large amounts of financial capital to spare, this price will be paid for by the new farm owners taking on debt.

So, when you lower your demand for the agricultural product and the world price falls, the indebted-and-vulnerable farmers who are faced with lower profits will be unable to meet their debt repayments. You'll get double-value if some other countries are simultaneously increasing their supply of the agricultural product when you reduce your demand, since the world price of the agricultural product will fall even further.

Now when the banks start to foreclose on debt-burdened farmers, those farms will come up for mortgagee sale (and at a low price because of the low price of the agricultural product), and your country can swoop in to secure the land and your own supply of the agricultural product at a much lower price.

So, is there a great dairy price conspiracy? Maybe all these things are coincidence:
  • Global Dairy Trade Index in April 2013 = 1573; Global Dairy Trade Index in March 2016 = 628 (globaldairytrade.info)
  • The Reserve Bank "...said many indebted farms were coming under increased pressure, which would be made worse if dairy prices remained low or if dairy farm prices fell significantly." (New Zealand Herald)
  • "The [REINZ] institute said its dairy farm price index fell by 14.3 per cent in the three months to February compared with the three months to January. Against February 2015, the index was down by 20.9 per cent." (New Zealand Herald)
You be the judge.
 

Saturday, 26 March 2016

Cauliflower prices

It's nice when the things we talk about in ECON100 or ECON110 classes are illustrated by real-world examples. Last week, cauliflower prices hit $10 at some stores. The New Zealand Herald reports:
Kiwi classic cauliflower cheese is becoming an expensive luxury - with cauliflowers selling for around $10 each at several grocers.
St Heliers Bay Fruit Market owner Kamal Duggal said he was forced to put prices up, as cauliflowers were becoming hard to come by.
"There's a big shortage at the moment. It's cost me $8.50 plus GST each to buy them in the past couple of weeks..."
When there is a shortage of a good, we expect prices to rise. Why is there a shortage? The Herald explains:
The price was affected by a market shortage of cauliflower due to recent adverse weather conditions, the [Foodstuffs] spokeswoman said.
So, there has been a decrease in supply of cauliflower in the market. We can illustrate what is going on with a simple diagram, as below (ignoring the effect of GST, for simplicity). Supply of cauliflower has decreased from S0 to S1. At the previous equilibrium price of P0, there is now a shortage of cauliflower (the difference between the quantity of cauliflower demanded at that price, Q0, and the quantity of cauliflower supplied at that price, Q2). The price will start to rise, until it reaches the new equilibrium price of P1 (with Q1 cauliflower traded).


The transition in the equilibrium price from P0 to P1 can be explained through the combination of the actions of buyers and sellers. Some buyers, who are willing to pay more than the old market price, would miss out on the good because of the shortage at that price. To avoid missing out, some of them will find sellers and offer those sellers slightly higher prices, bidding the price up. Sellers might not even have to wait for buyers to find them and bid prices up - recognising the shortage, they can raise prices in anticipation of the bidding up of prices by buyers.

Finally, with the higher price, fewer cauliflowers are sold (Q1 rather than Q0 in the diagram above). And indeed this is what is observed:
"Not many people are buying them. I bought five or six on Monday and have only sold two or three."
And:
"They've been very hard to sell. Restaurants still buy them because they need them, but regular customers haven't been."
So, even with cauliflowers at $10 per head, the quantity sold doesn't fall to zero (because at least some people are willing to pay the higher price), but fewer people do buy (those people whose willingness-to-pay for cauliflower is less than $10).

Wednesday, 23 March 2016

Try this: Worldwide cost of living index

A couple of weeks ago, The Economist posted a graphic which summarises the cost of living for 133 cities around the word, based on a report by the Economist Intelligence Unit. The report explains:
The Worldwide Cost of Living is a twice yearly Economist Intelligence Unit survey that compares more than 400 individual prices across 160 products and services. These include food, drink, clothing, household supplies and personal care items, home rents, transport, utility bills, private schools, domestic help and recreational costs.
Essentially the index summarises the cost of living for "expatriates and business travellers", and is "designed to help human resources and finance managers calculate cost-of-living allowances and build compensation packages".

Interestingly, the graphic lets you compare the cost of living changes from one year, five years, and ten years ago. All are relative to the costs of New York City (where the index is set to equal 100 for September 2015).

Singapore was the most expensive city last year, followed by Zurich and Hong Kong (second equal). Of New Zealand cities, the report includes only Auckland (ranked 38th equal, along with Brussels, Madrid, and Barcelona) and Wellington (ranked 42nd equal, along with Noumea, Stockholm, and Seattle). Interestingly, both Auckland and Wellington were more expensive than New York City, up until this year.

Try it out for yourself!

Tuesday, 22 March 2016

Economics and the war on drugs

Last week in the Waikato Economics Discussion Group, the students debated legalisation of marijuana. I'm really enjoying the informal debate style we have adopted, where students are randomly assigned to one side or the other, and might have to develop arguments counter to their prior beliefs. I think the pro-legalisation group came out slightly ahead on the day.

However, this post is less about EDG or marijuana legalisation, and more about the war on drugs more generally. Last month, Tom Wainwright wrote a piece in the Wall Street Journal on "How economists would wage the war on drugs". Essentially, the war on drugs is being lost. Badly. As Wainwright notes:
The number of people using cannabis and cocaine has risen by half since 1998, while the number taking heroin and other opiates has tripled. Illegal drugs are now a $300 billion world-wide business, and the diplomats of the U.N. aren't any closer to finding a way to stamp them out.
This failure has a simple reason: Governments continue to treat the drug problem as a battle to be fought, not a market to be tamed. The cartels that run the narcotics business are monstrous, but they face the same dilemmas as ordinary firms--and have the same weaknesses.
So, what's the deal here? Why is the war on drugs going so badly? The war on drugs is essentially based on restricting the supply of drugs, whether by destroying drug crops or manufacturing activities, intercepting drugs in transit, or jailing drug dealers and bosses, etc. The fundamental problem with targeting supply is that, if effective, it results in higher drug prices, as shown in the diagram below. Reducing drug supply from S0 to S1 does reduce the amount of drugs consumed (from Q0 to Q1), but increases the price from P0 to P1. The higher price provides incentives for other suppliers to enter the drug market, shifting the supply curve back to the right (towards S0), and undoing any good that might have come from the reduction in supply.


However, supply of drugs might not even be appreciably reduced when drug crops are targeted. Wainwright points out that:

  1. Drug cartels are a monopsony - they are a single buyer of Andean coca leaves, so they have market power over the price of leaves (i.e. the cartels have the ability to strongly influence the market price of coca leaves). So if some crops are wiped out, the price is unlikely to rise because of the cartels' market power.
  2. The price of cocaine is so much higher than the crop input costs that even a large increase in crop prices would have little effect on the market price of cocaine (i.e. even a big increase in the price of coca leaves would lead to only a small shift in the supply curve for cocaine).
A further problem arises because demand is relatively inelastic - the quantity of drugs demanded does not reduce by much even if the supply reduces (this is why the demand curve is relatively steep in the diagram above). So any reduction in supply is translated into price changes rather than quantity changes.

A more effective approach then, may be to target demand (as I've noted before). Reducing demand, from D0 to D1 in the diagram below, reduces both the quantity of drugs consumed (from Q0 to Q1), and the price (from P0 to P1). Even though this change results in the same quantity reduction as the supply shift shown in the diagram above, it is likely to be more effective in the longer term as the lower price reduces the incentive for other suppliers to enter the market and undo the good work of reducing demand.


How then, to reduce demand? Wainwright writes:
Demand-side interventions are not only more effective, they're also considerably cheaper than playing about with helicopters in the Andes. A dollar spent on drug education in U.S. schools cuts cocaine consumption by twice as much as spending that dollar on reducing supply in South America; spending it on treatment for addicts reduces it by 10 times as much. Rehab programs for prescription-painkiller users might seem costly, but they prevent those people from slipping into the colossally more expensive problem of heroin addiction. Where demand cannot be dampened, it can be redirected toward a legal source, as a few U.S. states have done with marijuana--a development that has inflicted bigger losses on the cartels than any supply-disruption policy.
So, if an economist was running the war on drugs, it would likely look a lot different - more rehab programmes and fewer helicopter gunships.

On a final note, Tom Wainwright has a new book, entitled "Narconomics: How to Run a Drug Cartel", which I've just ordered a copy of. I look forward to reviewing it in a later blog post.

Read more:



Tuesday, 15 March 2016

Changing incentives and piracy at sea

In ECON100 and ECON110, we discuss rational (and in ECON110, quasi-rational) decision-makers, who make decisions based on costs and benefits. If the costs and/or benefits change, that provides incentives for people to change their behaviour. If the costs of an activity rise, or the benefits received from that activity fall, then people will engage in less of that activity.

Which brings me to pirates. Quartz reports:
Over the past six months, the price of oil has plunged due to a global oversupply. And for some pirates, it’s just not worth stealing it any more.
“With oil at a low bottom price of below $30 per barrel, piracy is no longer such a profitable business as it was when prices hit $106 a barrel a few years ago,” said Florentina Adenike Ukonga, the executive secretary of the Gulf of Guinea Commission—a regional body that exists to promote cooperation between West African states, many of which export oil via tanker—in an interview with Bloomberg.
Piracy is costly - speedboats, guns, ammunition, manpower, not to mention the possibility of being killed or captured by the authorities. So, when the benefits of hijacking an oil tanker fall substantially, you'll avoid tankers and look for other targets. Meaning fewer hijacking attempts on oil tankers.

However, overall we should expect less hijacking of other ships (not just oil tankers), because the costs of piracy have been increasing. There are now many more armed guards on-board ships to protect them, and there are many more international naval ships patrolling areas of pirate activity. This increases the chances of being killed or captured, and so increases the probability-weighted costs of pirate activity. The increase in costs of pirate activity probably goes a long way towards explaining the overall decline in pirate attacks on shipping between 2010 and 2014 (per this report by the ICC International Maritime Bureau).

[HT: Marginal Revolution]

Monday, 14 March 2016

The ongoing contingent valuation debate

Economists tend to value goods and services at their market value. There is some intuitive sense to this - the value of a good or service is whatever someone is willing to pay for it. However, not all goods and services can be valued in this way, because not all things of value are able to be traded in markets (e.g. clean air) or are not traded because they don't exist yet (e.g. vaccines for HIV). In these cases, we need to use non-market valuation techniques if we want to derive estimates of value.

One non-market valuation technique that we discuss in ECON110 is the contingent valuation method (CVM) - a survey-based stated preference approach. We call it stated preference because we essentially ask people the maximum amount they would be willing to pay for the good or service (so they state their preference), or the minimum amount they would be willing to accept in exchange for foregoing the good or service. This differs from a revealed preference approach, where you look at the actual behaviour of people to derive their implied willingness-to-pay or willingness-to-accept.

As I've noted before, I've used CVM in a number of my past research projects, including this one on landmine clearance in Thailand (ungated earlier version here), this one on landmines in Cambodia (ungated earlier version here), and a still incomplete paper on estimating demand for a hypothetical HIV vaccine in China (which I presented as a poster at this conference).

The CVM has faced a number of critics over the years. The criticisms are essentially based on whether the estimates provided by the method are fit-for-purpose. That is, does the CVM actually measure the values that it sets out to measure?

The latest contributions to the CVM debate were published in the latest issue of Applied Economic Perspectives and Policy, with the concluding paper titled "Interesting questions worthy of further study: Our reply to Desvousges, Mathews, and Train’s (2015) comment on our thoughts (2013) on Hausman’s (2012) update of Diamond and Hausman’s (1994) critique of contingent valuation". Before I get to that paper though, it's worth me backtracking a bit to earlier in the debate.

Jerry Hausman (MIT) has been one of the staunchest critics of the CVM, and re-sparked the debate with this 2012 article in the Journal of Economic Perspectives (ungated version here). In the article, Hausman reiterates a number of his earlier critiques. Hausman notes there are three long-standing problems with the CVM:
1) hypothetical response bias that leads contingent valuation to overstatements of value; 2) large differences between willingness to pay and willingness to accept; and 3) the embedding problem which encompasses scope problems.
He further argues that:
respondents to contingent valuation surveys are often not responding out of stable or well-defined preferences, but are essentially inventing their answers on the fly, in a way which makes the resulting data useless for serious analysis.
The hypothetical response bias arises because survey respondents are being asked hypothetical questions - usually they are being asked about their willingness-to-pay for goods that are not traded (perhaps through a small increase in taxes), or for goods that do not yet exist. Because these questions are hypothetical, there is little incentive for respondents to answer in a way that is consistent with what they would do if actually faced with the choice.

The differences between willingness to pay (WTP) and willingness to accept (WTA) are common to CVM studies (e.g. my co-authors and I found this difference in a study of landmine clearance in Thailand (ungated earlier version here)). For rational decision-makers the difference between willingness-to-pay to receive a benefit, and willingness-to-accept a payment in exchange for not receiving that same benefit should be the same. But it turns out that WTP is generally lower than WTA. Many argue that this is consistent with quasi-rational decision-making, i.e. loss aversion leads us to be willing to pay less for something we don't have than what we would be willing to accept to give up that same item - an endowment effect.

Scope problems arise when you think about a good that is made up of component parts. If you ask people how much they are willing to pay for Good A and how much they are willing to pay for Good B, the sum of those two WTP values often turns out to be much more than what people would tell you they are willing to pay for Good A and Good B together. This issue is one I encountered early in my research career, in joint work with Ian Bateman and Andreas Tsoumas (ungated earlier version here).

Fast-forward to 2013, and this article in Applied Economic Perspectives and Policy, by Timothy Haab (Ohio State), Matthew Interis and Daniel Petrolia (both Mississippi State), and John Whitehead (Appalachian State). Haab et al. respond to each of Hausman's critiques. In terms of the first critique, they note that current approaches are reducing hypothetical bias using a range of methods, including asking respondents to sign an 'oath' before responding to the survey. In terms of the WTP-WTA difference, they note (as I did above) that the existence of endowment effects makes these differences consistent with behavioural economic theory. And in terms of scope problems, they note that issues of scope are consistent with diminishing marginal utility (the WTP for Good A depends on whether Good B is already provided or not) and substitution between market and non-market goods. Haab et al. conclude:
in direct response to Hausman’s selective interpretation of the literature, we believe that the overwhelming amount of evidence shows: (1) the existence (or nonexistence) of hypothetical bias continues to raise important research questions about the incentives guiding survey responses and preference revelation in real as well as hypothetical settings, and contingent valuation can help answer these questions; (2) the WTP-WTA gap debate is far from settled and raises important research questions about the future design and use of benefit cost analyses in which contingent valuation will undoubtedly play a part; and (3) CVM studies do, in fact, tend to pass a scope test and there is little support for the argument that the adding up test is the definitive test of CVM validity.
And onto the latest contributions to the debate. This paper (sorry I don't see an ungated version) by William Desvousges and Kristy Mathews (both consultants), and Kenneth Train (University of California, Berkeley) responds to Haab et al., argues against a number of specific statements in the Haab et al. paper. They argue that they are highlighting "the limitations of current approaches to guide future research".

Finally, Haab et al. respond (in the paper with the beautifully long title cited above, no ungated version available that I can see), noting that their responses in the earlier piece were based on 'best' practice, not current practice. That is a bit of an indictment of current CVM practice - if 'best' practice is known but not currently followed, then questions would rightly be raised about the reliability of the results of CVM studies.

However, I'm not convinced that in all cases 'best' practice has yet been identified. As Haab et al. note, these issues (especially dealing with hypothetical bias and scope issues) are interesting, and worthy of future study. Especially since at least one of my PhD students will be using CVM in their current research.

Read more:

Sunday, 13 March 2016

The undercover economist strikes back, collapse, and the doomsday myth

Late last year a couple of students suggested I should do more book reviews. This is something I've been very lax about, and not necessarily because I haven't been reading much of late. So instead of separate book reviews, I've collated three of my recent reads together into a single post.

The first book is The Undercover Economist Strikes Back, the latest book by Tim Harford. Harford's previous 'pop econ' books have focused on microeconomics, but this one is macroeconomics. I'm not much into macroeconomics (despite having taught introductory macro in the past), but I found a lot to like in this book. Harford adopts as a narrative style a conversation with a reader naive to the ways of macroeconomics, and for the most part the style works (although personally, I preferred the style of the previous Undercover Economist books).

In particular, there are good sections on sticky prices, commitment strategies, and the problems with relative poverty measures, that I will put to use in my own teaching. Overall the best part of the book is the end - not because that meant I didn't need to read any more of it, but because Harford discusses the future of macroeconomics. I recommend this book for students starting out in macroeconomics, as well as those looking for a nice refresher.

The second and third books are probably best reviewed together, given that they come at similar topics, but from quite different angles and with very different conclusions. Collapse, by Jared Diamond, looks (as the title suggests) at the failure of a number of past societies, focusing on environmental factors as a commonality among the failures he describes. The collapses include obvious choices like Easter Island, the Mayans, and Norse Greenland, but also more contemporary examples like the Rwandan genocide. Despite the fact that Diamond argues that he is not promoting the idea of environmental determinism and he tries to be more upbeat in the concluding chapters, it is hard to avoid adopting an almost fatalistic interpretation of these collapses. Diamond argues that the choices of leaders can often make environmental issues worse, rather than better, but he ignores the role of markets in solving problems of resource allocations.

Which brings me to The Doomsday Myth, by Charles Maurice and Charles Smithson. When I bought and started reading this book, I had no idea how dated it was (published in 1984), but it still raises some interesting counterpoints to Diamond's Collapse. Maurice and Smithson look instead at a series of purported crises arising from resource shortages, and demonstrate that the operation of markets and price adjustments provided the incentives for the crisis to be overcome. Their examples include the rubber crisis in the early 20th Century, whale oil in the mid-19th Century, and the Black Death in Europe, among others. In each case, the market has adjusted or new substitute products have been developed, that meant the predicted crisis never eventuated. The takeaway message is that governments should leave markets to their own devices, rather than intervening and making the situation worse. Towards the end of reading this book, I wondered what Maurice and Smithson would have made of the Global Financial Crisis some 25 years after writing their book.

In any case, these two books both adopt what I feel is an untenable position. I would argue that markets can neither be ignored, nor can they be entirely left alone. Both books are interesting reads, but the smart reader will probably spend a lot of their time considering the counter-arguments to those proposed by the authors, particularly in the concluding chapters in both cases.

Saturday, 12 March 2016

Demand, supply, and hotel rooms

Last week in ECON100 we covered demand and supply. There's no shortage of real-world examples to illustrate markets, but this New Zealand Herald story from Tuesday is well-timed:
New Zealand hotel prices jumped by 6 per cent during the the past year, well ahead of the average prices paid around the world, according to new research.
So, hotel room prices have risen, and faster than the general inflation rate (so it is a 'real' price increase). The hotel price increase could happen primarily as a result of an increase in demand for hotel rooms, or a decrease in the supply of hotel rooms. The article also provides us with the answer as to which is more likely:
"The growth in domestic hotel prices comes off the back of a record-breaking year for international visitors to New Zealand in the year ending December 2015, with a 9.6 per cent increase in total arrivals on the previous year," Hotels.com said.
So, an increase in demand led to the increase in hotel room rates (maybe it was because of Lord of the Rings?). This is shown in the diagram below, where demand increases from D0 to D1, and the equilibrium price increases from P0 to P1. Notice that the equilibrium quantity of hotel rooms increases, but not by much (from Q0 to Q1) - that's because even when the price increases, there isn't much scope for more hotel rooms to be made available (perhaps some additional B&B rooms or AirBnB or similar, or perhaps some rooms that would have undergone maintenance have that maintenance deferred so that they are available, but the quantity will be small). Because quantity supplied doesn't respond much to the change in price, we say that supply is relatively inelastic (we'll cover elasticity in ECON100 in a couple of weeks time).


Will the higher hotel room prices endure? Steven will talk more about the dynamics of supply and demand in ECON100 this coming week (if he hasn't already). In short, higher prices mean higher profits for hotels. That makes the hotel industry more attractive for other firms (and existing firms might want to expand as well), so we might expect more hotels in the future (if firms believe that the increase in demand will persist). And indeed it appears that is what is happening:
"This is a promising sign for the local tourism industry and, with many major hotel development projects in the pipeline, we'll see increased supply in the long term, which will be welcome news to holidaymakers planning a trip in New Zealand," she [Katherine Cole, regional director, Australia, New Zealand & Singapore for the Hotels.com brand] said.
So, we should expect an increase in supply, as shown in the diagram below. Supply increases from S0 to S2, leading the equilibrium price to fall from P1 to P2, and the equilibrium quantity of hotel rooms to increase from Q1 to Q2. The lower price will certainly make holidaymakers happier, as noted above, and provided the increase in demand holds up, the hotel operators will be better off (compared with before the increase in demand) as well.



Wednesday, 9 March 2016

Incentives and the loss of the Kiwisaver kick-start

Sometimes I wonder. Do politicians really not understand the role of incentives? Or are they deliberately ignoring them. Exhibit A is the daft statement by John Key about removing the $1000 Kiwisaver kick-start in last year's Budget: the change will "...not make a blind bit of difference to the number of people who join." Well, it turns out the change did make a blind bit of difference, as this New Zealand Herald article notes:
The number of people signing up to KiwiSaver has slowed significantly since the removal of the $1000 kick-start...
Analysis by the Herald shows the average number of people signing up to KiwiSaver per month was 15,029 in the year to June 2015 and 16,976 in the year to June 2014.
But since finance minister Bill English scrapped the kick-start incentive in last year's May Budget sign-ups have fallen to an average of 8996 per month with the lowest sign-up level, in October, below 8000.
None of this should be a surprise. Rational (and quasi-rational) decision-makers weigh up the costs and benefits of their decisions. If you remove the $1000 kick-start from Kiwisaver, then this reduces the benefits of joining, while the costs remain the same (lower consumption today), and at the margin at least some people will choose not to join. It turns out that 'some' people is actually quite a lot of people - nearly half of those who would have joined. [*]

Moreover, quasi-rational decision-makers are affected by present bias - they weight costs and benefits that occur now much more heavily (compared with costs and benefits that occur in the future) than they should (e.g. what economists refer to as hyperbolic discounting). So, that $1000 lost benefit carries much more weight in the decision about joining Kiwisaver (or not) than it should. The benefit is still lower and highly salient even if you point out that there are significant other benefits of joining Kiwisaver. For example, from the same article:
Matthews said the trend was disappointing but not a surprise given human behaviour.
"To me what that signals clearly is a lack of financial literacy because within two years you have $1000 from the government in terms of the member tax credit.
"Over the life of KiwiSaver, $1000 is insignificant."
Those other benefits were present before the kick-start was removed, and are present after. So, nothing has changed in that respect. So if a person hadn't already joined Kiwisaver, they probably aren't going to change their minds in a hurry as a result of benefits that were already present. What changed was the kick-start benefit was lost, and as the data show pretty clearly, the numbers signing up for Kiwisaver declined substantially. Incentives matter!

*****

[*] Now, a reduction in signups could be expected because as a higher proportion of the population join Kiwisaver, there are fewer non-members left in the population to sign up. But, it's unlikely to have had that dramatic and sudden an effect!

Monday, 7 March 2016

Paid parking and the value of student time

I'm back at work after a week away at my son's school camp, and the first thing I noticed when I arrived was... the amount of spare parking in the Gate 10 car park. In contrast, the streets leading up to the car park (e.g. Carrington Ave) were thronged with parked cars. It's interesting what a large effect on behaviour a small change in incentives can have.

I've written before about the introduction of paid parking on campus. Increasing the monetary cost changes the incentives for those who were previously driving to campus. Some will choose to walk or cycle or take public transport. Others will continue to drive, but park on suburban streets rather than in the car park. The choice a rational (or quasi-rational) person will make will depend on the costs and benefits of the different options. Assuming the benefit is the same regardless of how they travel (the benefit being that they get to campus), whichever option presents the lowest cost will be the option the driver will choose. Costs may be monetary, or time or inconvenience.

Thinking purely among those who continue to drive to campus after the introduction of paid parking, the choice of whether to park on-campus (and incur the parking fee) or park on a suburban street (and incur no fee, but face extra walking time) has interesting implications for the value of student time. Let's take the example of students parking on Carrington Ave, in preference to Gate 10. Carrington Ave is about an extra three minutes of walking time from campus, compared with the Gate 10 car park. By parking there though, a student saves the $2 parking fee. So, that implies that the $2 saved must be at least as valuable to these students as six minutes of walking time (three minutes each way). In other words, students who park on Carrington Ave are suggesting that their time is worth $20 per hour (or less) - if their time was worth more than $20 per hour, it would be less costly for them to park in the car park and save the six minutes of extra walking time instead.

In contrast, students who park in the Gate 10 car park must value their time as being $20 per hour (or more). If their time was worth less than $20 per hour, they would be better off parking on the suburban street (and incurring the extra six minutes of walking time instead).

Of course, the analysis above is simplified. I haven't taken into account the possibility of parking fines for Carrington Ave (I don't think it has time limited parking... yet; but when it does that will increase the potential costs of parking there), and the offsetting health benefits arising from any extra walking. But I think the overall point still stands - the choice of where to park provides us with some clues as to the value of student time.

So, when considering how much to pay my teaching or research assistants in the future, perhaps I should be inquiring whether they park in the car park or on the street, to see what they think they are worth?

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