Elections are times of peak deception. Political parties have several ways in which they can use data to persuade people to vote for them. At one extreme, they can simply make up ‘facts’ – in other words, they can lie. There have been various examples of such lies in the run-up to the UK general election of 12 December 2019. The linked article below gives some examples. But data can be used in other deceptive ways, short of downright lies.
Politicians can use data in two ways. First, statistics can be used to describe, explain and interpret the past. Second, they can be used as the basis of forecasts of the future effects of policies.
In terms of past data, one of the biggest means of deception is the selective use of data. If you are the party currently in power, you highlight the good news and ignore the bad. You do the reverse if you are currently in opposition. The data may be correct, but selective use of data can give a totally false impression of events.
In terms of forecast data, you highlight those forecasts, or elements of them, that are favourable to you and ignore those that are not.
Politicians rely on people’s willingness to look selectively at data. People want to see ‘evidence’ that reinforces their political views and prejudices. News media know this and happily do the same as politicians, selectively using data favourable to their political leanings. And it’s not just newspapers that do this. There are many online news sites that feed their readers with data supportive of their position. And there are many social media platforms, where people can communicate with people in their political ‘bubble’.
Genuine fact-checking sites can help, as can independent forecasters, such as the Institute for Fiscal Studies. But too many voters would rather only look at evidence, genuine or not, that supports their political point of view.
This can make life hard for economists who seek to explain the world with an open mind, based on a non-biased use of evidence – and hard for economic forecasters, who want to use full and accurate data in their models and to make realistic assumptions, emphasising that their forecasts are only the most likely outcome, not a certainty. As the article states:
Economic forecasts are flawed and their limitations should be acknowledged. But they should not be blindly dismissed as fake facts. And as far as political debate and discourse is concerned, in the long run, the truth may will out.
- Give some specific examples of ways in which politicians misuse data.
- Give some specific examples of ways in which politicians misuse the analysis of economists.
- Distinguish between positive and normative statements? Should economists make policy recommendations? If so, in what context?
- Why are economic forecasts flawed, but why should they not be dismissed as ‘fake facts’?
- Examine the manifestos of two political parties and provide a critique of their economic analysis.
Here’s a quiz for you. What one chart would you chose as an illustration of the most significant economic event(s), trends or data of the year? You could search out a chart, perhaps by looking through the news items on this site. Or you could construct a chart of you own in Excel or PowerPoint using economic data from a data site. You can find links to a whole range of data sites here.
To give you some ideas, the link to the BBC site below gives the charts selected by a range of eminent economists.
Top economists reveal their graphs of 2011 BBC News (13/12/11)
- Look through each of the 11 charts in the link above and explain their significance.
- Why did you choose the chart you did?
- Name five other economic events or trends during 2011 that you would consider to be highly significant and say why.
- Identify three likely economic events in 2012 that would, if they came true, prove significant and say why? Just how likely are they?
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.
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)
Realising Savings through Procurement Optimisation Opera Solutions
- According to the first article above, how much newspaper reporting based on the use of data is unreliable?
- What are the reasons for the unreliability of newspaper reporting?
- For what reasons might the ONS and other reputable agencies periodically have to amend time series data?
- “Council incompetence ‘costs every household £452 a year'”. Critically examine this claim by the Daily Mail.
- Why may Opera Solutions be seen as not wholly independent in reporting the possibilities of cost savings by local government?
- In the absence of reliable data, can any economic policy conclusions be drawn from economic models? Explain.