Economics studies the choices people make. ‘Rational choice’ involves the weighing up of costs and benefits and trying to maximise the surplus of benefits over costs. This surplus will be maximised when people do more of things where the marginal benefit exceeds the marginal cost and less of things where the marginal cost exceeds the marginal benefit. But, of course, measuring benefits and costs is not always easy. Nevertheless, for much of the time we do make conscious choices where we consider that choosing to do something is ‘worth it’: i.e. that the benefit to us exceeds the cost.
When we make a choice, often this involves expenditure. For example, when we choose to buy an item in a shop, we spend money on the item, and also, perhaps, spend money on transport to get us to the shop. But the full opportunity cost includes not only the money we spend, but also the best alternative activity sacrificed while we are out shopping.
Then there are the benefits. Not all pleasurable activity costs us money. The sight of beautiful contryside or the pleasure of the company of friends may cost us very little, if anything, in money terms. But they may still be very valuable to us.
If we are to make optimal decisions we need to have some estimate of all costs and benefits, not just ones involving the payment or receipt of money. This applies both to individual behaviour and to collective decisions made by governments or other agencies.
Cost–benefit analysis seeks to do this to help decisions about new projects, such as a new road, a new hospital, environmental projects, and so on. But just how do we set about putting a value on the environment – on the pleasure of a walk in bluebell woods, on protecting bird life in wetlands or sustaining ecosystems?
For the first time there has been a major study that attempts to value the environment. According to the introduction to the report:
The UK National Ecosystem Assessment (UK NEA) is the first analysis of the UK’s natural environment in terms of the benefits it provides to society and the nation’s continuing prosperity. Carried out between mid-2009 and mid-2011, the UK NEA has been a wide-ranging, multi-stakeholder, cross-disciplinary process, designed to provide a comprehensive picture of past, present and possible future trends in ecosystem services and their values; it is underpinned by the best available evidence and the most up-to-date conceptual thinking and analytical tools. The UK NEA is innovative in scale, scope and methodology, and has involved more than 500 natural scientists, economists, social scientists and other stakeholders from government, academic and private sector institutions, and non-governmental organisations (NGOs).
The following podcast and webcast look at the report and at some of the issues it raises in terms of quantifying and incorporating environmental costs and benefits into decision taking.
Podcast and Webcast
‘The hidden value’ of our green spaces BBC Today Programme, Tom Feilden (2/6/11)
Report puts monetary value on Britain’s natural assets BBC News, Jeremy Cooke (2/6/11)
Articles
NEA report highlights need for biodiversity Farmers Guardian, Ben Briggs (2/6/11)
Nature is worth £19bn a year to the UK economy – report Energy & Environmental Management Magazine (2/6/11)
In praise of… the unquantifiable Guardian (3/6/11)
Priceless benefits of bluebell woods Guardian letters, Dr Bhaskar Vira and Professor Roy Haines-Young (4/6/11)
Nature ‘is worth billions’ to UK BBC News, Richard Black (2/6/11)
Putting a price on nature BBC News, Tom Feilden (2/6/11)
Value of Britain’s trees and waterways calculated in ‘ground-breaking’ study The Telegraph, Andy Bloxham (2/6/11)
Nature worth billions, says environment audit Financial Times, Clive Cookson (2/6/11)
Nature gives UK free services worth billions Planet Earth, Tom Marshall (3/6/11)
UK scientists put price on nature with National Ecosystem Assessment GreenWise, Ann Elise Taylor (2/6/11)
Report
UK National Ecosystem Assessment: link to report DEFRA
UK National Ecosystem Assessment (June 2011)
The UK National Ecosystem Assessment: Synthesis of the Key Findings
Questions
- How would you set about valuing the benefits of woodlands?
- According to the report, the health benefits of living close to a green space are worth up to £300 per person per year. How much credance sould we attach to such a figure?
- What do you understand by the ‘ecosystem approach’ and the term ‘ecosystem services’?
- Explain Figure 2 on page 3 of Chapter 2 of the report.
- Should decision makers quantify only those benefits of ecosystems experienced by humans? Would all environmentalists agree with this approach?
- What are the advantages and disadvantages of quantifying all costs and benefits in money terms?
- Compare the consequences over the next 50 years of a ‘world markets’ scenarios with that of a ‘nature at work’ scenario.
- What policy implications follow from the report?
Inequality is growing in most countries. This can be illustrated by examining what has been happening to countries’ Gini coefficient. The Gini coefficient measures income inequality, where 0.00 represents perfect equality, with everyone in the country earning the same, and 1.00 represent perfect inequality, with one person earning all the country’s income. (Note that sometimes it is expressed as the ‘Gini index’, with 100 representing perfect inequality). In virtually all countries, the Gini coefficient has been rising. In the OECD countries it has risen by an average of 0.3% per annum over the past 25 years. The OECD average is now 0.31.
But despite the fact that the Gini coefficient has been rising, its value differs markedly from one country to another, as does its rate of change. For example, Finland’s Gini coefficient, at 0.26, is below the average, but it has been rising by 1.2% per annum. By contrast, Turkey’s Gini coefficient, at 0.41, is above the average and yet has been falling by 0.3% per annum.
The most unequal of the developed countries is the USA. According to OECD data, its Gini coefficient is 0.38, well above the values in the UK (0.34), Japan (0.33), Germany (0.30) France (0.29) and Denmark (0.26). What is more, inequality in the USA has been increasing by an average of 0.5% per annum since the mid 1980s.
According to the United Nations’ Human Development Report 2010, the USA’s Gini coefficient is even higher, at 0.41 (see Table 3 of the report). But this is still below that of Russia, with a figure of 0.44, a figure that has markedly worsened over time, along with those of other former Soviet countries. According to the report (page 72):
The worsening is especially marked in countries that were part of the former Soviet Union – which still have relatively low Gini coefficients because they started with low inequality. Transition has eroded employment guarantees and ended extensive state employment. Before the fall of the Berlin Wall, 9 of 10 people in socialist countries were employed by the state, compared with 2 of 10 in Organisation for Economic Co-operation and Development economies. While the privileged elite (the nomenklatura) often attained higher material well-being, the measured differences in income were narrow.
The Gini coefficient for Russia is the same as the average of the 39 developing countries with the lowest level of human development &nbash; and developing countries are generally much less equal than developed ones. Of course, some developing countries have an even higher Gini coefficient: for Angola the figure is 0.59; for Haiti it is 0.60.
The following three webcasts look at aspects of the growing inequality in Russia.
Webcasts
Gap between rich and poor widens in Russia BBC News, Jamie Robertson (29/5/11)
Corruption slows Russian modernisation BBC News, Emma Simpson (29/5/11)
Corruption and poverty in Russia’s far east Al Jazeera (28/2/11)
Articles
Russia’s rich double their wealth, but poor were better off in 1990s Guardian, Tom Parfitt (11/4/11)
Russia’s growing wealth gap BBC News, Jamie Robertson (28/5/11)
A Country of Beggars and Choosers Russia Profile, Svetlana Kononova (16/5/11)
Rich and poor, growing apart The Economist (3/5/11)
Data
Distribution of family income – Gini Index CIA World Factbook (ranked by country in desending order)
Society at a Glance 2011 – OECD Social Indicators OECD: see particularly the Excel file 6. Equity Indicators: Income inequality (click on No if prompted about a linked workbook)
Russia Distribution of family income – Gini index Index Mundi
Chart of the week: inflation stoking inequality in China and India Financial Times, Andrew Whiffin (24/5/11)
List of countries by income equality Wikipedia
Reports
Growing Income Inequality in OECD Countries: What Drives it and How Can Policy Tackle it? OECD Forum on Tackling Inequality (2/5/11)
Human Development Report 2010 United Nations Development Programme
Questions
- Explain what is meant by the Gini coefficient. How does it relate to the Lorenz curve? What does a figure of 0.31 mean?
- Why has income inequality been growing in most countries of the world? Has the process of globalisation dampened or exacerbated this trend?
- What specific factors in Russia can explain the growing inequality?
- How is privatisation likely to affect income distribution??
- Why is it difficult to quantify the extent of inequality in Russia?
- What maxim of taxation has been used in setting income tax rates in Russia?
- What role does corruption play in determining the degree of inequality in Russia?
- What policy measures, if any, could realistically be adopted in Russia to reduce inequality? What constraints are there on adopting such policies?
“There are ‘incredible economies of scale in cloud computing’ that make it a compelling alternative to traditional enterprise data centers.” According to the first article below, cloud computing represents a step change in the way businesses are likely to handle data or use software. Rather than having their own servers with their own programs, they use a centralised service or ‘public cloud’, provided by a company such as Microsoft, Google or Amazon Web Services. The cloud is accessed via the Internet or a dedicated network. It can thus be accessed not only from company premises but by mobile workers using tablets or other devices and thus makes telecommuting more cost effective.
There are considerable economies of scale in providing these computing services, with the minimum efficient scale considerably above the output of individual users. By accessing the cloud, individual users can benefit from the low average costs achieved by the cloud provider without having to invest in, and frequently update, the hardware and software themselves.
In the case of large companies, rather than using a public cloud, they can use a ‘private cloud’. This is hosted by the IT department in the company and achieves economies of scale at this level by removing the need for individual departments to purchase their own software and servers. Of course, the costs of providing the cloud is borne by the company itself and thus the benefits of lower up-front IT capital costs are reduced. This is clearly a less radical development and is really only an extension of the policy of many companies over the years of having centralised servers holding data and various software packages.
In autumn 2010, EMC Computer Systems commissioned economists at the Centre for Economics and Business Research (cebr) to quantify the full impact that cloud computing will have over the years ahead. According to the report, The Cloud Dividend:
The Cebr’s research calculates that €177.3 billion per year will be generated by 2015, if companies across Europe’s five largest economies continue to adopt cloud technology as expected.
The Cebr found that the annual economic benefit of cloud computing, by 2015, will be:
• France – €37.4 billion
• Germany – €49.6 billion
• Italy – €35.1 billion
• Spain – €25.2 billion
• UK – €30.0 billion
Will the ability of cloud computing to drive down the costs of IT mean that a new revolution is underway? Just how significant are the economies of scale and are they likely to grow as cloud providers themselves grow in size and experience? The following articles look at some of the issues.
Articles
Reports and information
Questions
- What specific economies of scale are achieved through cloud computing?
- Why might the minimum efficient scale of cloud computing services be above the level of output of many companies?
- What are the downsides to cloud computing?
- How would you set about assessing the statement that we are on the brink of a fundamental revolution in business computing?
- Why are customer-heavy sectors, such as financial services, utilities, governments, leisure and retail, expected to buy into the concept fastest?
- How can product life cycle analysis help to understand the stages in the adoption of cloud computing?
Anyone investing in commodities over the past few weeks will have been in for a bumpy ride. During the first part of 2011, commodity prices have soared (see A perfect storm brewing?). This has fuelled inflation and has caused the Bank of England to revise upwards its forecast for inflation (see Busy doing nothing see also Prospects for Inflation).
But then in the first week of May, commodity prices plumetted. On the 5 May, oil prices fell by 7.9% – their largest daily amount since January 2009. Between 28 April and 6 May silver prices fell from $48.35 per ounce to just over $33.60 per ounce – a fall of over 30%. And it was the same with many other commodities – metals, minerals, agricultural raw materials and foodstuffs.
Many financial institutions, companies and individuals speculate in commodities, hoping to make money buy buying at a low price and selling at a high price. When successful, speculators can make large percentage gains in a short period of time. But they can also lose by getting their predictions wrong. In uncertain times, speculation can be destabilising, exaggerating price rises and falls as speculators ‘jump on the bandwagon’, seeing price changes as signifying a trend. In more stable times, speculation can even out price changes as speculators buy when prices are temporarily low and sell when they are temporarily high.
Times are uncertain at present. Confidence fluctuates over the strength of the world recovery. On days of good economic news, demand for commodities rises as people believe that a growing world economy will drive up the demand for commodities and hence their prices. On days of bad economic news, the price of commodities can fall. The point is that when undertainty is great, commodity prices can fluctuates wildly.
Articles
Commodities plunge: Blip or turning point? BBC News, Laurence Knight (6/5/11)
Commodity hedge fund loses $400m in oil slide Financial Times, Sam Jones (8/5/11)
Commodities: ‘epic rout’ or the new normal? BBC News blogs: Stephanomics, Stephanie Flanders (6/5/11)
Commodities Still a Bubble – But Prices May Continue to Rise Seeking Alpha, ChartProphet (9/5/11)
When a sell-off is good news The Economist, Buttonwood (6/5/11)
Gilt-edged argument The Economist, Buttonwood (28/4/11)
Commodities: What volatility means for your portfolio Reuters blogs: Prism Money (9/5/11)
Gold, silver rise again on debt, inflation concerns Reuters, Frank Tang (10/5/11)
Commodities After The Crash, No Way But Up The Market Oracle, Andrew McKillop (9/5/11)
Outlook 2011:Three Dominant Factors Will Impact Precious Metals in 2011 GoldSeek (9/5/11)
Energy bills set to rise sharply next winter, Centrica warn Guardian, Graeme Wearden (9/5/11)
Dollar triggered commodities ‘flash crash’, not Bin Laden The Telegraph, Garry White, and Rowena Mason (9/5/11)
The outlook for commodity prices Live Mint@The Wall Steet Journal, Manas Chakravarty (11/5/11)
Three ways to play the next commodities bubble Market Watch, Keith Fitz-Gerald (11/5/11)
Data
Commodity Prices Index Mundi
Commodities Financial Times
Commodities BBC Market Data
Questions
- Why did commodity prices fall so dramatically in early May, only to rise again rapidly afterwards?
- Why do commodity prices fluctuate more than house prices?
- What is the relevance of price elasticity of demand and supply in explaining the volatility of commodity prices?
- Under what circumstances is speculation likely to be (a) stabilising; (b) destabilising?
- To what extent are rising commodity prices (a) the cause of and (b) the effect of world inflation?
- If commodity prices go on rising every year, will inflation go on rising? Explain.
Business leaders and politicians pay a great deal of attention to economic forecasts. And yet these forecasts often turn out to be quite wrong. Very few economists predicted the banking crisis of 2008 and the subsequent credit crunch and recession. And the recently released 2010 Q4 growth figures for the UK economy, which showed a decline in real GDP of 0.5%, took most people by surprise.
What is more, forecasters often disagree. If, for example, you look at the forecasts made by various panel members for Consensus Forecasts, you can see the divergence between their various predictions.
So why is economic forecasting so unreliable? Is it the fault of economic models? Or are there too many unpredictable factors that can impact on economies – factors such as business and consumer confidence, or political events, or natural disasters, such as the recent floods in Australia, South Africa and Brazil? Will economic forecasting always be a very inexact science?
Articles
Davos 2011: Why do economists get it so wrong? BBC News, Tim Weber (27/1/11)
Popular Semi-Science Slate, Robert J. Shiller (24/1/11)
Fed Often Gets It Wrong In Its Forecasts on US Economy American Public Media, Justin Wolfers (26/1/11)
Don’t bet on economic forecasting CNBC, Jeff Cox (21/9/10)
Forecasts
Forecasts for the UK economy HM Treasury
Econ Stats: The Economic Statistics and Indicators Database Economy Watch (large database of worldwide annual statistics, including forecasts to 2015)
World Economic Outlook IMF (follow link in right-hand panel)
OECD Economic Outlook: Statistical Annex OECD
European Economic Forecasts European Commission, Economic and Financial Affairs DG
Questions
- For what reasons may economic forecasts turn out to be wrong?.
- To what extent is economic forecasting like weather forecasting? Which is harder and why?
- Wo what extent can the poor accuracy of economic forecasts be blamed on the application of the ‘wrong type of economics’?
- How much variation is there in the independent forecasts of the UK economy reported by the Treasury (see HM Treasury link above)?
- Using the HM Treasury link, compare the forecasts made of 2010 in January 2010 with those made of 2010 in January 2011. Attempt an explanation of the differences.