Category: Essential Economics for Business: Ch 01

Economic assessment of real-world issues relies heavily on data. It is the same with economic policy recommendations. Both public- and private-sector organisations gather data, which are then used for analysis, often presented in a report. These reports are then often used as the basis for policy, whether by the government, local authorities or the private sector. Sometimes the data are those collected by national statistical agencies, such as the Office for National Statistics (ONS) in the UK; sometimes they are collected by private agencies; sometimes by individual researchers.

Clearly the analysis and the suitability of any policy recommendations depend on the quality of the data. But how much can we rely on the data? A problem is that people have an interest in gathering and/or selecting data that support their opinions. As a result, the data used for analysis and policy recommendations may be unreliable and incomplete.

This is not to say that the data collected by reputable agencies such as the ONS are wrong. Rather, it is the selective use of them that can be highly misleading. Sometimes, however, the data that some agencies produce may indeed be unreliable, with too small or unrepresentative samples. If they rely on surveys, the survey questions may be poorly framed or lead the respondent into giving a particular answer.

Newspapers make use of data and reports all the time to make a particular case – a case in line with the newspaper’s political stance. The lesson for economic students is that we need to be alert all the time as to just how reliable data are; and to whether the conclusions drawn from them are correct.

The following two articles by Ben Goldacre, from the Guardian’s Bad Science series, look at the misuse of data. The first looks at the case of the Health Service; the second at the possibility of savings by local government in their procurement activities.

Articles
How far should we trust health reporting? Guardian, Ben Goldacre (17/6/11)
Misleading money-saving claims help no one Guardian, Ben Goldacre (24/6/11)

Report
Realising Savings through Procurement Optimisation Opera Solutions

Questions

  1. According to the first article above, how much newspaper reporting based on the use of data is unreliable?
  2. What are the reasons for the unreliability of newspaper reporting?
  3. For what reasons might the ONS and other reputable agencies periodically have to amend time series data?
  4. “Council incompetence ‘costs every household £452 a year'”. Critically examine this claim by the Daily Mail.
  5. Why may Opera Solutions be seen as not wholly independent in reporting the possibilities of cost savings by local government?
  6. In the absence of reliable data, can any economic policy conclusions be drawn from economic models? Explain.

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

  1. How would you set about valuing the benefits of woodlands?
  2. 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?
  3. What do you understand by the ‘ecosystem approach’ and the term ‘ecosystem services’?
  4. Explain Figure 2 on page 3 of Chapter 2 of the report.
  5. Should decision makers quantify only those benefits of ecosystems experienced by humans? Would all environmentalists agree with this approach?
  6. What are the advantages and disadvantages of quantifying all costs and benefits in money terms?
  7. Compare the consequences over the next 50 years of a ‘world markets’ scenarios with that of a ‘nature at work’ scenario.
  8. 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

  1. Explain what is meant by the Gini coefficient. How does it relate to the Lorenz curve? What does a figure of 0.31 mean?
  2. Why has income inequality been growing in most countries of the world? Has the process of globalisation dampened or exacerbated this trend?
  3. What specific factors in Russia can explain the growing inequality?
  4. How is privatisation likely to affect income distribution??
  5. Why is it difficult to quantify the extent of inequality in Russia?
  6. What maxim of taxation has been used in setting income tax rates in Russia?
  7. What role does corruption play in determining the degree of inequality in Russia?
  8. 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

  1. What specific economies of scale are achieved through cloud computing?
  2. Why might the minimum efficient scale of cloud computing services be above the level of output of many companies?
  3. What are the downsides to cloud computing?
  4. How would you set about assessing the statement that we are on the brink of a fundamental revolution in business computing?
  5. Why are customer-heavy sectors, such as financial services, utilities, governments, leisure and retail, expected to buy into the concept fastest?
  6. How can product life cycle analysis help to understand the stages in the adoption of cloud computing?

We’ve had numerous examples in recent years of the economic turmoil that natural disasters can have and unfortunately, we have another to add to the list: the Japanese earthquake and tsunami. As Japan tries to take stock of the damage and loss of life, the economic consequences of this disaster will also need considering. The previous Kobe earthquake cost the economy an estimated 2% of GDP, but this did hit a key industrial area. The economic consequences of the 2011 earthquake were originally not thought to be as bad, but the economy will undoubtedly suffer.

The Japanese economy, like the UK, shrank in the final quarter of 2010, but was expected to return to growth. The devastation of the earthquake and tsunami is now likely to delay this economic recovery. Many car companies are based in Japan and are expected to take some of the biggest hits. Nomura analysts suggested that annual operating profits of companies such as Toyota, Nissan and Honda would be dented by between 3% and 8%. You only have to look at some of the footage of the disaster to see why this is expected. Supply chains will undoubtedly be disrupted, many of whom are located in the exclusion zone and financial markets across the world have fallen, as the possibility of a nuclear disaster threatens. As Louise Armistead writes:

‘By lunchtime in Britain £32bn had been knocked off the value of the FTSE-100 dropped, which fell by more than 3pc in early trading but recovered later to close down 1.38pc at 5,695.28. Germany’s DAX plunged 3.19pc, recovering from a 4.8pc fall, and France’s CAC ended the day 3.9pc lower, while on Wall Street, the Dow Jones Industrial Index dropped 2pc shortly after opening.’

A key question will be whether Japanese reconstruction will push the economy out of its deflationary spiral or make it even worse.

GDP measures the value of output produced within the domestic economy, but it is by no means an accurate measure of a country’s standard of living. Whilst it will take into account new construction that will be required to rebuild the economy, it doesn’t take into account the initial destruction of it. As output and growth are expected to fall in the immediate aftermath, we may see a boost to growth, as reconstruction begins.

The problem of scarcity is becoming more and more apparent to many survivors, as they begin to run short of basic necessities, which has led to various rationing mechanisms being introduced. Despite the devastating conditions which survivors now find themselves in, when supplies are delivered, the efficiency of Japan is still very evident. As noted by BBC Radio 4 coverage, as soon as the supplies arrived, a line was in place to unload the van in minutes. Teams have been set up to help everyone get through the tragedy. Even in the most devastating of times, Japanese efficiency still shines through and undoubtedly this will be a massive aid in the huge re-construction projects that we will see over the coming months and even years. Analysts say that there will be short term pain, but that the investment in construction will boost the economy later in the year.

Japanese earthquake: Markets shed £1trillion amid nuclear fears Telegraph, Louise Armistead (16/3/11)
Panic over Japan triggers market turmoil Independent, Nikhil Kumar (16/3/11)
Japan quake: Economy ‘to rebound’ after short term pain BBC News (14/3/11)
Japan disaster: The cost of a crisis Guardian (16/3/11)
Global stock markets tumble in ‘perfect storm’ amid fears of nuclear disaster Mail Online, Hugo Duncan (16/3/11)
Japan’s earthquake will cause a global financial aftershock Guardian, Peter Hadfield (15/3/11)
Economists’ estimate of Japan quake impact Reuters (16/3/11)
Fukishima factor adds pressure to economic fallout from Japan’s crisis Guardian, Larry Elliott (15/3/11)

Questions

  1. What is the likely impact on Japan’s GDP?
  2. Why is the potential disruption to the supply chain important for a firm?
  3. How and why will this catastrophe affect global financial markets?
  4. What are some of the main problems of using GDP as a measurement for growth? Think about the impact on GDP of Japan’s destruction and their future re-construction.
  5. What types of production methods etc have Japan implemented to allow them to become so efficient in production?
  6. What are the arguments to suggest that this disaster might help the Japanese economy recover from its deflationary spiral? What are the arguments to suggest that it might make it worse?
  7. What are some other examples of natural disasters or human errors that have also had economic consequences?