Archive for October, 2009

There is a scene in Don Quixote where the eponymous hero first sets eyes on a majestic line of 30 or 40 windmills in the distance.  Excitedly he turns to his loyal sidekick and announces his intention to slay every single one of them.  He had, of course, mistaken them for giant enemies.

When William Kamkwamba first set eyes on windmills on the cover of a library textbook, he saw not enemies, but inspiration.  Just 14 and without a full education (due to a severe famine in 2001 his parents couldn’t afford to keep him in school), William managed to hack together pieces of wood, PVC piping, old bicycle parts and a rusty car to build himself a working windmill!  He has since built 2 more which power lights, charge mobile batteries, and pump water for the house and to irrigate fields.

I find William’s story completely inspiring in so many ways.  Having grown up in developing countries I have always been interested in international development and the fact that with very little help a 14 year old has managed to change the future of his village completely floors me and fills me with immense hope.  I love the fact that William didn’t let his circumstances tie him down, I love the fact that with his determination he has not only improved his life, but the lives of his fellow villagers, I love the inspiration that this story must give to people in other developing countries.  I especially love that William built windmills, harnessing renewable energy for his village, therefore ensuring that their energy supply was not dependent on resources from the outside.

So what were the costs of building the windmills?

  • 3 months of William’s life, during which he was called a pot-smoking madman by the other people in his village.
  • Windmill parts – these were all scrap parts, so the only real cost here is the time spent looking for these parts which have been included above.

What were the benefits to William and his family and neighbours from the construction of the windmills?

  • Free electricity – dependent only on nature’s forces and not on unreliable infrastructure or deliveries of fuels.  This benefit includes the ability to study/work longer – In building his first windmill William’s main ambition was to power a lightbulb in his room so he could read after dark.  Studies have shown that the supply of electricity increases GDP due to individuals being able to work and study after dark[1].  There are also many studies on how mobile phones in rural areas contribute to better economic conditions[2].
  • Better health for William and his family – William was able to replace his family’s smoky dark kerosene lamps with lightbulbs.  One of his windmills was also used to pump clean water into the house.
  • Greater food reliability – Another windmill pumped grey water out to irrigate the family fields, helping to ensure that farm production could continue even in times of droughts.
  • Inspiration – Even holding a master of science, William’s windmills inspire me and remind me that it is possible to do pretty much anything you can put your mind to.  Imagine how it must make the people of his village and surrounding villages feel!  I would not be surprised to see some sort of entrepreneurial growth in the area around William’s village.

Read more at Wired.com and William’s blog. Watch William on TED

[1]Wolde-Rufael, Yemane 2006. Electricity consumption and economic growth: a time series experience for 17 African countries. Energy Policy 34:10 (1106-1114)

Ferguson, Ross; Wilkinson, William; Hill, Robert, 2000. Electricity use and economic development. Energy Policy 28:13 (923-934).

[2]Bayes, Abdul, 2001. Infrastructure and rural development: insights from a Grameen Bank village phone initiative in Bangladesh. Agricultural Economics 25:2 (261-272)

Google Scholar search: Mobile phones economic development

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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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It’s been an interesting day for us and that’s not even counting the rumours of a new scientific study proving that temperature affects cows and their milk production…they could have just asked me…but of course scientific evidence is important.

No, what has been interesting are the Greenpeace people on the roof of the Parliament. Brave people first of all, I could never have made it up there. Clever people too: amongst their 12 point manifesto [1] there are ‘new pollution taxes’ and ‘new financing mechanisms for green investment’. Greenpeace manifesto refers to the work by Green Alliance [2] and the fact that both NGOs make use of economics is exciting. When I first started burping, it was unthinkable for a campaigning NGO to recommend economic measures. I hope they will be taken up and be as useful for the environment as they are intended to be.

Greenpeace’s timing is superb, with this being the first day of the Parliament and the publication date for the first annual progress report of the Committee on Climate Change[3]. The report reiterates that the Government needs to do more to encourage renewable energy and new energy efficient technologies of transport, energy generation and carbon efficient buildings. The report also looks at the effect of recession on reducing the price of carbon – bad news as the lower the price of carbon the cheaper it will be to just pay the price than to reduce the emissions. There is good news about the recessions too: reduction in economic activity will lead to reduction in emissions. The trick is not to be fooled by that though. We still need to invest in better technologies and processes and control demand for when the economy recovers and activity increases.

I hope the MPs returning to the Parliament today are paying more attention to Greenpeace’s manifesto and CCC’s annual report than whether they have expense recall letters in their inbox.

[1] Greenpeace, 2009. 12 Policies to save the climate and our planet
[2] Green Alliance, 2009. From Crisis to Recovery
[3] Committee on Climate Change, 2009. Progress report to Parliament – 12 October 2009

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Hello and welcome to the brand new calf-like (you know, all long spindly legs and wobbly knees) UK-based environmental economics blog Cow Burps!

Cow Burps is lovingly fed and watered by an environmental economics consultancy (you may have heard of them) based in London, but contributors will drop by from pastures further afield.  If you would like more information on this blog, please check the Why Cow Burps? page.

– The entire pasture

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Last week, Daisy went to a business reception organised by the Government Office for London to introduce the UKCIP. This was part of a series of local events around the country explaining the projections, impacts and implications of the UK CIP to different types of stakeholders.

Daisy wanted to learn more about UKCIP and, admittedly also, to see which kind of businesses we could perhaps work for in future. Technical presentation on the UKCIP was excellent and so were the talks by the Environment Advisor of the Mayor  and one of the Directors of Forum for the Future. The most engaging talk was by the Climate Change manager of Marks & Spencer.  It turns out the effect of weather on retailers is larger than Daisy realised…you put salads on the shelves on days predicted to be sunny but if the day turns out cloudy people want to buy steaks not salads…a lot of wasted product and of course lost profit.  Increased unpredictability is what concerns them most – and of course the welfare of their suppliers worldwide the speaker was eager to add.

Otherwise, it was a typical business reception…nice wine, nice nibbles and a difference this time – a model of the whole of City of London and its glamorous new buildings illuminated. Chatting while hovering over the model to a Councillor of the City, Daisy suggested that the first and the simplest thing the City could do was to convince the businesses not to leave the lights of their sky scrapers on over night. The Councillor was quick to respond defensively saying that they didn’t have the legal power to do this.


If the public sector does not have the persuasive power (if not the legal one) to get the businesses to do something that will not cost them anything and in fact save them money, what good is having more and better quality information like UKCIP?  How can we get over the lethargy that prevents even such simple behaviour change?

Booo says Daisy.

– Daisy

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We wanted to start Cow Burps off with a post explaining what it is that environmental economists do and why we do what we do through the use of the topical example of a rising demand for beef.

As this is a life-or-death matter in more ways than one, this post has turned out to be much longer than we anticipated. But please excuse us for this; we promise all other Cow Burps posts will be much shorter!

Currently, the worldwide population of cattle stands at around 1.5 billion, providing humans with milk, meat, and leather.  However, this number may be set to rise with a growing human population and as more of the developing world earn higher incomes, enabling them to afford more meat within their diets (there are other types of food of course but here we stick with beef as part of the theme).

An increase in the demand for beef is likely to increase the prices in the short term, which will encourage cattle farmers to increase their stock and perhaps other people to try their hand at cattle farming, as they try to cash in on the price increase. The cycle of demand and supply does not end here of course but let’s have a look at what happens at this point.

This extremely simplistic scenario should mean good news for meat-eaters everywhere but, if cattle farmers don’t change the way they rear cattle, this means bad news for the environment. Two popular examples of how more cows can be bad for the environment are:

  1. More cows produce more methane (that’s burps to you!) which is a greenhouse gas over 20 times more potent than carbon dioxide; and
  2. Making way for more cows means converting land that may be environmentally valuable into cattle farms.  For example, between 1996 and 2006, the area of land occupied by cattle ranching in the Legal Amazon more than doubled from 23 million to 55 million hectares [1].

(while there are other ways in which more cows mean more trouble for the environment, we won’t go into them now, however if you do want to read a short summary, this article from The Independent is not bad).

So as demand for beef goes up, it makes financial sense for cattle farmers to raise more cows, but it may not make economic sense for society once you take the environmental impacts into account.  This unwillingness (or ‘failure’) of farmers to take into account the environmental costs of their actions, which could very well outweigh the financial benefit, is termed as a market failure by environmental economists. For the example of increased methane emissions described above, this is because farmers do not factor in their contribution to climate change and the costs of climate change (Lord Nicholas Stern says: potentially a lot [2]).  For the problem of land conversion, this is because farmers only value land at what can be produced on the land and sold at markets.

We all know, however, that these global costs are mounting up and becoming increasingly apparent, and that the full value of most types of land is greater than the value of what can be produced on it.  For instance, land values also include the benefits that humans receive from biodiversity, carbon storage and the protection of water sources, to name a few of the environmental ones.  While these may seem like intangible services or concepts that can be difficult to value, environmental economists work to generate precisely this type of data so that those who make decisions cannot use lack of evidence as an excuse.

Of course farmers are not the only ones who are unwilling to think about their impact on the environment and to be honest so long as the global cost does not affect them directly, we cannot expect many to be willing. So, environmental economists also work on how we can use the information about environmental values to create incentives to change the way we use the environment – how to convince farmers to raise less cows for example (if that is the indeed the answer).

This post doesn’t answer the question of how many cows is the ‘efficient’ (optimal) number of cows to service the human population.  However we hope that by reading this, you will get a better sense of how we all, as a society, can find a better answer, rather than falling back on the financially efficient answer, which, as we have seen, is not the economically (i.e. taking into account all values, not just financial values) efficient answer.

– Daisy and Betsy

[1] Greenpeace, 2008. Amazon Cattle Footprint – Matto Grosso: State of Destruction. http://www.greenpeace.org/raw/content/international/press/reports/amazon-cattle-footprint-mato.pdf

[2] BBC News, 2006. At-a-glance: The Stern Review. BBC News Online http://news.bbc.co.uk/1/hi/business/6098362.stm

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