Posts Tagged ‘economics’

The recently-finished Medmerry managed realignment scheme, on the South Coast, is an excellent example of how society can work with nature for the benefit of all parties.

The £28m scheme involved building 7km of sea walls up to 2km inland and then  ‘making a hole’ in the existing sea wall, thus allowing the seawater to naturally come into the land. This will now protect over 300 homes, local caravan parks and businesses, a water treatment plant and a main road from a once-in-a-thousand year flood. This area was previously prone to flooding; therefore the avoided damage from this scheme will be valuable.

An important reason for the water being allowed to come inland was to create a 180Ha saltwater marshland, thus offsetting the habitats that were lost in the flood protection projects of larger cities such as Southampton and Portsmouth. The creation of this rare saltwater marsh will bring in numerous species. As well as the wildlife reserve, footpaths, cycle paths and bridleways will be opened. As a result, nature-based tourism in the area is hoped to increase, which will benefit the local economy.

By working with nature, rather than against it, the project has benefited both humans and the environment. The scheme has given a home, or resting spot, to wildlife, whilst providing recreational, protection, participation, and tourism benefits to the local community. It is an excellent example of how incorporating nature-based values into decision making can improve society as a whole.

This is the biggest scheme of its kind in the UK to date and it will be observed closely to see if it can be applied to other regions that are threatened by rising waters.

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Looking back at working on its nature policies for a week, Colombia holds a concentration of humanities challenges, from melting ice (Colombia is losing its glaciers) to poverty and conflict. Their responses to these challenges reveals the best and worst of the effects of economics on the environment.

The worst is the rapid expansion of mining in response to global metal price rises in the last decade (e.g. gold). This market signal has stimulated production at the cost of colossal externalities from mining, often carried out illegally in nature reserves, but also creating huge health problems. Small scale gold mining uses mercury to separate gold from its ore, but the final stage of burning to separate the mercury (which vapourises at a lower temperature) and the gold is usually undertaken in towns due to the risks of being robbed at rural mine locations. This results in mercury exposure not just to the miners, but to their neighbours in towns. The highest environmental concentration of mercury ever recorded was in Colombia; freshwater biodiversity is suffering.

On the other hand, Colombia is proud of its mega-biodiverse natural environment. It has several policies that earmark resources to conserve the natural environment (e.g. spending part of license fees for companies on forest restoration). So in these cases, economics provides the structure to transfer resources to enhance the environment. It’s a microcosm of how, as an environmental economist, I view the global economy: most markets don’t reflect environmental costs and collectively cause colossal damage, but without markets how can we reallocate resources to protect nature?

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I recently attended the ZSL symposium on “Economics as if life mattered: Can we shape economic policy to save species”.  It was an enjoyable event that raised some interesting points of discussion. Robert Alexander’s talk on the Pros and Cons of Trade Bans was a particular highlight. An economic approach to wildlife conservation and bans that argued for tackling the root causes of biodiversity loss.

A general theme of the day was criticism of mainstream economics/economists. Although I would not bracket myself as a ‘mainstream’ economist, the criticisms focused on some egregious examples of economic thinking while ignoring the benefits that market economies have brought the world. A coherent alternative to market economies was not discussed.

Yes, the current market  system we have has resulted in huge environmental and distributional problems and some assumptions of economic theory are highly improbable. But an economic system based on markets is likely to be in place for the foreseeable future even if there is a bigger role for the state (See this Anatole Kaletsky interview for some thoughts and recommended reading). As environmental/ecological economists we try to shift this system in such a way that recognises the importance of the environment.

Valuation came in for some stick on the day, some of the concerns were understandable. There are moral and methodological concerns that arise out of environmental valuation. But to quote Ice T “Don’t hate the playa, hate the game”. Policy makers all value the environment in some shape or form, and to echo political quote mentioned in the conference “if you are not at the table you are on the menu”. Valuation helps bring the environment to the table and gives it a voice amongst development threats.

I took away from the conference that environmental economists need to communicate more clearly, but also with a mind to allay the scepticism and fear surrounding economics.

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(or, Betsy attempts to explain the concepts of baselines and additionality by explaining how the writers of Doctor Who failed to account for either concept within the latest series)

(Small) spoiler alert: In the following blog post in order to make a point I may include a spoiler or two, but they are early on in the series and are neither very big nor very important.

For anyone who doesn’t follow the show, the latest Doctor Who series finished on Saturday.  The series mainly revolved around a mysterious crack in a little girl’s bedroom wall – which turned out to be a crack in the universe.  This crack in the universe (let’s call it the CitU from now on) would swallow things and anything it swallows is wiped from the universe and ceases to exist, not only in the present and future, but the past as well.

Throughout the series the CitU managed to swallow up multiple people wiping out their lives from the history of the universe.

While I enjoyed the series (the first one I’ve ever watched), my main gripe is that as individuals were wiped out of existence the writers did not consider ‘ripple effects’.  For example, think of Frank Capra’s “It’s a wonderful life”.  When George Bailey gets shown what would have happened were he never to be born, he sees that his entire town and the lives of people he loves would be very different had he not lived (it would make a very boring movie if they were the same)!

In other words, when wielding the CitU, the writers were not taking into account the concept of ‘additionality’ – an issue in economics where the question is basically “If there had been no intervention, would it have happened anyway?” (i.e., “What is the future baseline?”)

So, for example, in the episode ‘Flesh and Stone’ soldiers were set the task of guarding Amy (who is one of the main characters).  One by one, they disappear into the CitU and Amy is eventually left alone.  So, if we account for the baseline, we should ask “If the people who were guarding Amy in their capacity as a soldier were never born, would that mean there would be no soldiers guarding Amy?”  Almost certainly not, there would be other people who would have been made soldiers were it not for the ones occupying the role, or other soldiers who would have been sent on the mission and set the task of guarding Amy.  The task of guarding Amy was not (or at least shouldn’t have been!) ‘additional’ to those original soldier’s existences.

Coming from another angle, and using an example in the same episode where the writers actually get it right, you could ask “If a creature that had infected someone (let’s say it is a very unique infection) were wiped out from ever existing, would that person still be infected?” No – that (unique) infection is additional and depends on the existence of that creature.

So how do baselines and additionality apply to economics?  They are actually very important concepts in the created markets side of environmental economics. Imagine for example that you bought carbon credits to offset a year of driving your car.  These credits can then either help fund a project that would happen anyway without the funding (the project is not additional), or a project that would not happen without the funding (the project is additional) depending on the baseline.  Finding out where the baseline is and hence whether a project is additional or not can lead to allocating the money you paid for carbon offsets to where it makes the most difference.

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Elsea and I attended a talk on Monday hosted by the Westminster Skeptics in the Pub, where Professor Brian Cox (of BBC’s Wonders of the Solar System fame) and Dr Evan Harris (Liberal Democrat and member of the science and technology committee) gave a talk on science policy in the coming general elections.

There was a lot of talk about something Brian Cox called the ‘impact agenda’, which basically covers the notion that funding for scientific research should be given on the basis of the ‘impact’ it will have on society, in other words the amount of ‘benefit’ that would ensue from the research.  Generally, in a big picture kind of way, I personally feel that this is a good thing, as this is an effort to ensure that science spending is targeted in a way that provides the most benefit to us.

However, and this is a point that Brian Cox stressed, it is very difficult to measure the full benefits of any particular science research before it happens.  Benefits can be very wide ranging and difficult to capture.

Many people felt (and still feel) that the US wasted a lot of money ($25 billion in the 1960s, worth about $100 billion today) sending men to the moon.  “How did it benefit us?” is a very valid question, one which Chase Econometric Associates attempted to answer in 1976.  They came up with a ratio of 14:1… that is that for every dollar spent on the Apollo mission, the US public received a benefit of $14.  By 1976, research from the moon mission had already benefitted the aereospace industry, computer industry, car industry and international communications industry, just to name a few.  I have no doubt that technological advances of today  still owe their existence to the Apollo mission (and we haven’t even covered the scientific research and technology that we currently have that were discovered and invented by little boys and girls who watched the moon landing and grew up wanting to be physicists or engineers, or the little boys and girls that they have inspired in turn).

I doubt people at the time could have predicted that the $25 billion they had spent sending men to the moon would bring so much benefit to those of us living in their future and similarly, it is very difficult for us to imagine the benefits that so-called ‘blue skies’ research can bring to people  in the future.

Scientists can and by all means should make an attempt to value the end products of research, to make themselves accountable to the public and show them what they are doing and the benefits they can expect to glean from it.  However, the value of the potential of blue skies research is much greater than what we can currently define and value; the blue skies research of the last three centuries has completely changed the human race’s way of living. While the benefits that can be identified now are limited by what we think is applicable today, the greater benefits of scientific research are likely to go beyond our current imagination.

As Brian Cox said, economic analysis of the benefits of scientific research is difficult, if not impossible. But economic analysis is never intended to be the only input decision-making but simply one of the inputs. Therefore, the impossibility of identifying all the likely benefits of research that has not yet carried out, and the difficulties of estimating the economic value of those that are identified should not hinder science funding. The intention is that valuing what benefits that can be identified helps make a supporting case for research.

Coming up next in Big Bang for your Buck – Part II:  Elsea explores how we can get the cow to jump over the moon without re-breaking the bank(s).

Explore further:

The Economic Impacts of the US Space Program

Petition decries ‘impact’ agenda in research

Westminster Skeptics in the Pub

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Some undetermined time ago, around the autumn of 2009, my family and I drove up to some undetermined location to visit a couple of my parents’ friends…. and to view the birthing of adorable little seal pups.

“How come I have never heard of this before?” I hear you ask as you open up a new browser window to search for the location and attempt to remember to visit next year, “and why is Betsy being annoying by saying ‘undetermined’ a lot?” you add as an afterthought.

Well, see, I could give you the location and time of my visit; however those in charge would rather I didn’t.  Which is rather silly, I must admit, but I may as well play along, at least until they get themselves sorted, while I explain to you why they’d rather I not tell you but also why this is all rather silly.

As you can expect with their wide eyes and roly-poly natures, birthing seal pups are quite an attraction to the general public, enough of an attraction, at least, to draw thousands to the beach to watch them this year.  The local farmer who owns the land where people parked their cars probably made a nice tidy profit charging just £1 per car.

However, this kind of popularity causes problems for those who are attempting to preserve the area to allow the seals to continue doing their thing.  Unless properly controlled, huge crowds may disturb the seals and children (and adults) reaching through fences to pet seal pups and leaving the human scent on them may cause these pups to be abandoned by their mothers.  The footpaths which also serve as viewing areas are quite narrow, and although the day I went was quite cold and slightly wet, they were getting pretty full by the time we left.

After a conversation with our parents’ friends who live nearby, it became clear to me that seal-watching is growing exponentially in popularity every year and that the conservation group’s attempts to keep viewing numbers low are failing.  People are telling people who are telling more people.

How else can they control numbers?  There is a simple solution: by charging entry fees.  Entry fees that are high enough would lower viewing numbers by discouraging people who do not want to see the seal pups enough to pay the entry fee from visiting the site, while people who really want to see the seal pups would be willing to pay the entry fees and would be able to see them with less disturbance.

A common argument against an entry fee scheme to lower numbers is that it is pricing people out of seal-watching.  However, I would argue that the current scheme (of no charge and futile attempt to keep it a secret) is actually worse – increasing visitors to this ‘free’ activity may price the seals out!

Furthermore, the conservation group would be able to use the income generated from viewers on conservation programmes and to improve the site and possibly make it easier to accommodate more viewers without disturbance to the seals.

The only question left here, I guess, is how much should the entrance fee be?  The fee should capture the benefit that people receive from viewing the seals, but also take into account any other costs they have incurred along the way.  A survey of visitors (and would-be visitors) could find out how much people value the experience and  identify the additional benefits over incurred costs.

Incidentally, these costs that people have already incurred serve as a good estimate of the minimum benefit that people receive from viewing the seals.  For example, counting for only the fuel my parents spent £40 to get four of us to the seals and back.  That spending on petrol reveals an average minimum value of £10 per family member to see the seals (and my parents’ friends).  The actual benefit will be more than the minimum spend…a survey will have to be used to figure out how much more!

...because you can never have too many cute seal photos in a blog post!

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As you may have read earlier, Ermintrude and I attended Tim Harford’s talk at 1 Alfred Place last Thursday.  Following on from Ermintrude’s post about the first half of Tim Harford’s talk where he engaged us with the economics of happiness; I thought I’d fill you in on the second half of the talk which was even juicier… involving the economics of dating!

It may seem a bit strange upon first consideration that there have been studies carried out on dating, as economists ideally need large amounts of data in order to come up with any substantial conclusions.  However, it turns out that the invention of speed dating has saved economists from turning up on their mates’ dates dressed in lab coats and toting clipboards.  Vast amounts of data have been generated by speed dating events in the following way:

1)      Potential participants sign up for the events, and in the process provide information about themselves in the form of gender, education, height, and earnings, etc.

2)      Participants turn up to the event, and spend five minutes (or some other such short amount of time) chatting with each of the participants of the opposite sex, in short, having a ‘speed date’.

3)      At the end of a speed dating event, participants turn in their dating cards, where they tick either one of two boxes: ‘yes’ or ‘no’, for each person they met.  If they ticked a ‘yes’ for someone who has also ticked a ‘yes’ for them, they will receive each other’s contact details, and vice versa.  A ‘no’ from either person means that neither of them would receive contact details.

This process, theoretically, keeps our daters honest.  There may be a compulsion to tick ‘yes’ to every box to check who else has said ‘yes’ to them, but this would mean their contact details would be received by people they may not have liked.  On the other hand, if participants are shy and tick ‘no’ for someone they did like, they’d never get the chance to see them again.  Even if they ticked ‘yes’ and the other person ticked ‘no’, the other person need never know that they were chosen by our ‘shy’ participant.

So what did economists find out?  Unsurprisingly and unfortunately, stereotypes rule.  Both men and women prefer non-smokers with higher educations.  Women prefer taller men with higher incomes, while men prefer slimmer women. 

The results also show that no matter the calibre of men available at the event, women by and large ticked about 10% of their ‘yes’ boxes.  For example, for every 20 men, women will always tick ‘yes’ to an average of 2 men, whether the group of men are shorter and less educated with low incomes, or the group consists of taller, higher income men with IQs over 130.  Men ticked a higher percentage of ‘yes’ boxes, however this percentage also did not change across different groups of women.

Tim referred to this last phenomenon as a victory for the economists over the romantics – with the romantic ideal of ‘the one’ or ‘the select few’, and the economist’s view that the dating scene is, in short, a market, with consumers selecting the best of what is currently available at any point in time.

I took time out to test this theory with the other heifers in the pasture, at least one of whom has participated in speed dating events in the past.  We came up with a few counter-points:

1)      The way that speed dating companies set up the particular rules of the events can affect the data. For instance, one heifer pointed out that on her event, in order to find out how many men had ticked ‘yes’ to her, she had to tick at least one ‘yes’ herself, and this curiosity drove her to tick that box for the least offensive man.  It also helped that instead of full contact details, our heifer only had to offer up her e-mail address; emails can easily be ignored and an email address is changeable as a last resort.

2)      Participants who turn up to events where the participants of the opposite sex are less/more desirable according to the usual statistics, may themselves be less/more desirable, and their standards higher/lower accordingly.  For instance, the type of people that would turn up to a speed dating event hosted by a university would be different from the type of people that would turn up to a speed dating event hosted by a pub.

3)      The dataset is necessarily biased, as it is data based on a subset of the entire dating population, that is, the subset that would go on a speed dating event.  Presumably the more romantically minded would not attend such an event, preferring instead to leave their chances of meeting their love of their life to serendipity.

I, Betsy, admit that although I would like to think of myself as an economist, I am of the more romantically minded (some people would call me hopeless, really).  However, I do like the concept of using economics to make decisions in everyday life, in much the way that Tim Harford utilises economics in his FT column, “Dear Economist”.  Therefore I propose a tongue in cheek question to all other romantic economists out there:

Would open relationships produce the most efficient pairings?  If you are locked into a relationship, you are essentially monopolised, unable to try other ‘products’ on the ‘market’, which invariably leads to an inefficient market.  What do you think?

For more information, read Tim Harford’s blog post on the economics of dating here: http://timharford.com/2007/11/business-life-the-economics-of-dating/

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Yesterday evening Betsy and I had the pleasure of hearing a talk by Tim Harford, better known as the undercover economist.  During which we covered the banking crisis, the economics of dating and happiness.  It is this last point that I wish to share with you.  There is a huge amount of literature relating to ‘happiness’ and ‘being happy’ most of which I am going to bypass as Tim Harford or as we like to call him Hooford has gone through the process of picking out some of the most interesting bits and covering them in his talk.  During a study conducted in the 1990s individuals were asked about their happiness.  The results found those who rated themselves most happy were married, had no children, were women, had a high level of education and were employed however, it was stressed that these links were not causal.  Anyway it got me to thinking am I the happiest cow in the pasture?

So being the curious type I decided to check whether this was indeed the case by comparing my answer to the question, “how happy with life are you on a scale of 1-7 with 7 being very happy?” with the answer from the other cows in the pasture.  Being economists however they bombarded me with a series of further questions relating to the exact definition of happiness, what the counterfactual or baseline was and accusations that as I was asking on a Friday and we’d be able to roam free in the pasture over the weekend everyone would be happy.

I decided to press on and gave the following definitions:

Happy 7 = like getting up in the morning and looking forward to every day

6= like getting up in the morning and looking forward to some days

5 = like getting up in the morning and looking forward to the occasional day

4= no feeling either way about getting up and getting through each day

3= occasionally do not want to get out of bed and don’t look forward to the occasional day

2=often do not want to get out of bed and don’t look forward to most days

1=never want to get out of bed and don’t look forward to every day

So did the model work?

The predicted outcome in terms of happiness rankings in the pasture would be

Ermintrude (happiest),

Daisy, Elsea, Buttercup,

Aberdeen Angus, Limu,

And finally, Hickory Smoked Prime Rib (least happy).

The actual rankings were

Elsea (happiest),


Aberdeen Angus,

Hickory Smoked Prime Rib,



Daisy (least happy).

So how why did the model’s predictions fall foul of the field.  Well it seems that all cows in the field were extremely happy with mere decimal points separating some contenders.  In addition, some cows gave error bars relating to their rankings that were not taken into account during this rough and ready process.  However, the main issues can be split into two camps one to do with framing the question and the other to do with unobserved factors.  My definition of the ‘happiness’ question and the scale used were both open to interpretation, with the happiness scale potentially differing between all of us.  Unobserved factors – such as my long commute home and subsequent lack of sleep following last night’s talk may have impacted how ‘happy’ I felt this morning.  Likewise, cows concluding projects, not getting sleep when their calves wake them up, and a general dislike of mornings all contribute to this variable but were not accounted for in the model.

To find out more about the economics of happiness and Tim Harford’s talk please check out his blog http://timharford.com/2009/09/the-economists-guide-to-happiness/

– Ermintrude

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