In a blog in October 2024, we looked at global uncertainty and how it can be captured in a World Uncertainty Index. The blog stated that ‘We continue to live through incredibly turbulent times. In the past decade or so we have experienced a global financial crisis, a global health emergency, seen the UK’s departure from the European Union, and witnessed increasing levels of geopolitical tension and conflict’.
Since then, Donald Trump has been elected for a second term and has introduced sweeping tariffs. What is more, the tariffs announced on so-called ‘Liberation Day‘ have not remained fixed, but have fluctuated with negotiations and threatened retaliation. The resulting uncertainty makes it very hard for businesses to plan and many have been unwilling to commit to investment decisions. The uncertainty has been compounded by geopolitical events, such as the continuing war in Ukraine, the war in Gaza and the June 13 Israeli attack on Iran.
The World Uncertainty Index (WUI) tracks uncertainty around the world by applying a form of text mining known as ‘term frequency’ to the country reports produced by the Economist Intelligence Unit (EIU). The words searched for are ‘uncertain’, ‘uncertainty’ and ‘uncertainties’ and the number of times they occur as percentage of the total words is recorded. To produce the WUI this figure is then multiplied by 1m. A higher WUI number indicates a greater level of uncertainty.
The monthly global average WUI is shown in Chart 1 (click here for a PowerPoint). It is based on 71 countries. Since 2008 the WUI has averaged a little over 23 000: i.e. 2.3 per cent of the text in EIU reports contains the word ‘uncertainty’ or a close variant. In May 2025, it was almost 79 000 – the highest since the index was first complied in 2008. The previous highest was in March 2020, at the start of the COVID-19 outbreak, when the index rose to just over 56 000.
The second chart shows the World Trade Uncertainty Index (WTUI), published on the same site as the WUI (click here for a PowerPoint). The method adopted in its construction therefore mirrors that for the WUI but counts the number of times in EIU country reports ‘uncertainty’ is mentioned within proximity to a word related to trade, such as ‘protectionism’, ‘NAFTA’, ‘tariff’, ‘trade’, ‘UNCTAD’ or ‘WTO.’
The chart shows that in May 2025, the WTUI had risen to just over 23 000 – the second highest since December 2019, when President Trump imposed a new round of tariffs on Chinese imports and announced that he would restore steel tariffs on Brazil and Argentina. Since 2008, the WTUI has averaged just 2228.
It remains to be seen whether more stability in trade relations and geopolitics will allow WUI and WUTI to decline once more, or whether greater instability will simply lead to greater uncertainty, with damaging consequences for investment and also for consumption and employment.
Articles
Uncertainty Indices
Questions
- Explain what is meant by ‘text mining’. What are its strengths and weaknesses in assessing business, consumer and trade uncertainty?
- Explain how the UK Monthly EPU Index is derived.
- Why has uncertainty increased so dramatically since the start of 2025?
- Compare indices based on text mining with confidence indices.
- Plot consumer and business/industry confidence indicators for the past 24 months, using EC data. Do they correspond with the WUI?
- How may uncertainty affect consumers’ decisions?
Economic growth is closely linked to investment. In the short term, there is a demand-side effect: higher investment, by increasing aggregate demand, creates a multiplier effect. GDP rises and unemployment falls. Over the longer term, higher net investment causes a supply-side effect: industrial capacity and potential output rise. This will be from both the greater quantity of capital and, if new investment incorporates superior technology, from a greater productivity of capital.
One of the biggest determinants of investment is certainty about the future: certainty allows businesses to plan investment. Uncertainty, by contrast, is likely to dampen investment. Investment is for future output and if the future is unknown, why undertake costly investment? After all, the cost of investment is generally recouped over several months or year, not immediately. Uncertainty thus increases the risks of investment.
There is currently great uncertainty in the USA and its trading partners. The frequent changes in policy by President Trump are causing a fall in confidence and consequently a fall in investment. The past few weeks have seen large cuts in US government expenditure as his administration seeks to dismantle the current structure of government. The businesses supplying federal agencies thus face great uncertainty about future contracts. Laid-off workers will be forced to cut their spending, which will have knock-on effect on business, who will cut employment and investment as the multiplier and accelerator work through.
There are also worries that the economic chaos caused by President Trump’s frequent policy changes will cause inflation to rise. Higher inflation will prompt the Federal Reserve to raise interest rates. This, in turn, will increase the cost of borrowing for investment.
Tariff uncertainty
Perhaps the biggest uncertainty for business concerns the imposition of tariffs. Many US businesses rely on imports of raw materials, components, equipment, etc. Imposing tariffs on imports raises business costs. But this will vary from firm to firm, depending on the proportion of their inputs that are imported. And even when the inputs are from other US companies, those companies may rely on imports and thus be forced to raise prices to their customers. And if, in retaliation, other countries impose tariffs on US goods, this will affect US exporters and discourage them from investing.
For many multinational companies, whether based in the USA or elsewhere, supply chains involve many countries. New tariffs will force them to rethink which suppliers to use and where to locate production. The resulting uncertainty can cause them to delay or cancel investments.
Uncertainty has also been caused by the frequent changes in the planned level of tariffs. With the Trump administration using tariffs as a threat to get trading partners to change policy, the threatened tariff rates have varied depending on how trading partners have responded. There has also been uncertainty on just how the tariff policy will be implemented, making it more difficult for businesses to estimate the effect on them.
Then there are serious issues for the longer term. Other countries will be less willing to sign trade deals with the USA if they will not be honoured. Countries may increasingly look to diverting trade from the USA to other countries.
Video
Articles
- Trump’s erratic trade policies are baffling businesses, threatening investment and economic growth
Associated Press, Paul Wiseman, Anne D’innocenzio and Mae Anderson (6/3/25)
- The world is beginning to tire of Trump’s whiplash leadership
CNN, Stephen Collinson (6/3/25)
- US stocks slide and Nasdaq enters correction as chaos over Trump’s tariffs intensifies
CNN, John Towfighi (6/3/25)
- Trump’s Tariffs And Trade: Uncertainty, Chaos Or Brilliance?
Forbes, Mike Patton (6/3/25)
- How Trump’s second term might affect the market and your finances
The Conversation, Art Durnev (4/3/25)
- US corporate bond investors cautiously navigate trade war uncertainty
Reuters, Matt Tracy (6/3/25)
This week in Trumponomics: Playing chicken with marketsYahoo Finance, Rick Newman (8/3/25)
- Measuring fear: What the VIX reveals about market uncertainty
The FRED Blog, Aakash Kalyani (13/2/25)
- Trump shrugs off stock market slump, but economic warning signs loom
The Conversation, Conor O’Kane (17/3/25)
Data
Questions
- Find out what tariffs have been proposed, imposed and changed since Donald Trump came to office on 20 January 2025.
- In what scenario might US investment be stimulated by Donald Trump’s policies?
- What countries’ economies have gained or are set to gain from Donald Trump’s policies?
- What is the USMCA agreement? Do Donald Trump’s policies break this agreement?
- Find out and explain what has happened to the US stock market since January 2025. How do share prices affect business investment?
- Which sector’s shares have risen and which have fallen?
- Using the Data link above, find out what has been happening to the US Policy Uncertainty Index since Donald Trump was elected and explain particular spikes in the index. Is this mirrored in the global Policy Uncertainty Index?
- Are changes in the Policy Uncertainty Index mirrored in the World Uncertainty Index (WUI) and the CBOE Volatility Index: VIX?
We continue to live through incredibly turbulent times. In the past decade or so we have experienced a global financial crisis, a global health emergency, seen the UK’s departure from the European Union, and witnessed increasing levels of geopolitical tension and conflict. Add to this the effects from the climate emergency and it easy to see why the issue of economic uncertainty is so important when thinking about a country’s economic prospects.
In this blog we consider how we can capture this uncertainty through a World Uncertainty Index and the ways by which economic uncertainty impacts on the macroeconomic environment.
World Uncertainty Index
Hites Ahir, Nicholas Bloom and Davide Furceri have constructed a measure of uncertainty known as the World Uncertainty Index (WUI). This tracks uncertainty around the world using the process of ‘text mining’ the country reports produced by the Economist Intelligence Unit. The words searched for are ‘uncertain’, ‘uncertainty’ and ‘uncertainties’ and a tally is recorded based on the number of times they occur per 1000 words of text. To produce the index this figure is then multiplied up by 100 000. A higher number therefore indicates a greater level of uncertainty. For more information on the construction of the index see the 2022 article by Ahir, Bloom and Furceri linked below.
Figure 1 (click here for a PowerPoint) shows the WUI both globally and in the UK quarterly since 1991. The global index covers 143 countries and is presented as both a simple average and a GDP weighted average. The UK WUI is also shown. This is a three-quarter weighted average, the authors’ preferred measure for individual countries, where increasing weights of 0.1, 0.3 and 0.6 are used for the three most recent quarters.
From Figure 1 we can see how the level of uncertainty has been particularly volatile over the past decade or more. Events such as the sovereign debt crisis in parts of Europe in the early 2010s, the Brexit referendum in 2016, the COVID-pandemic in 2020–21 and the invasion of Ukraine in 2022 all played their part in affecting uncertainty domestically and internationally.
Uncertainty, risk-aversion and aggregate demand
Now the question turns to how uncertainty affects economies. One way of addressing this is to think about ways in which uncertainty affects the choices that people and businesses make. In doing so, we could think about the impact of uncertainty on components of aggregate demand, such as household consumption and investment, or capital expenditures by firms.
As Figure 2 shows (click here for a PowerPoint), investment is particularly volatile, and much more so than household spending. Some of this can be attributed to the ‘lumpiness’ of investment decisions since these expenditures tend to be characterised by indivisibility and irreversibility. This means that they are often relatively costly to finance and are ‘all or nothing’ decisions. In the context of uncertainty, it can make sense therefore for firms to wait for news that makes the future clearer. In this sense, we can think of uncertainty rather like a fog that firms are peering through. The thicker the fog, the more uncertain the future and the more cautious firms are likely to be.
The greater caution that many firms are likely to adopt in more uncertain times is consistent with the property of risk-aversion that we often attribute to a range of economic agents. When applied to household spending decisions, risk-aversion is often used to explain why households are willing to hold a buffer stock of savings to self-insure against unforeseen events and their future financial outcomes being worse than expected. Hence, in more uncertain times households are likely to want to increase this buffer further.
The theory of buffer-stock saving was popularised by Christopher Carroll in 1992 (see link below). It implies that in the presence of uncertainty, people are prepared to consume less today in order to increase levels of saving, pay off existing debts, or borrow less relative to that in the absence of uncertainty. The extent of the buffer of financial wealth that people want to hold will depend on their own appetite for risk, the level of uncertainty, and the moderating effect from their own impatience and, hence, present bias for consuming today.
Risk aversion is consistent with the property of diminishing marginal utility of income or consumption. In other words, as people’s total spending volumes increase, their levels of utility or satisfaction increase but at an increasingly slower rate. It is this which explains why individuals are willing to engage with the financial system to reallocate their expected life-time earnings and have a smoother consumption profile than would otherwise be the case from their fluctuating incomes.
Yet diminishing marginal utility not only explains consumption smoothing, but also why people are willing to engage with the financial system to have financial buffers as self-insurance. It explains why people save more or borrow less today than suggested by our base-line consumption smoothing model. It is the result of people’s greater dislike (and loss of utility) from their financial affairs being worse than expected than their like (and additional utility) from them being better than expected. This tendency is only likely to increase the more uncertain times are. The result is that uncertainty tends to lower household consumption with perhaps ‘big-ticket items’, such as cars, furniture, and expensive electronic goods, being particularly sensitive to uncertainty.
Uncertainty and confidence
Uncertainty does not just affect risk; it also affects confidence. Risk and confidence are often considered together, not least because their effects in generating and transmitting shocks can be difficult to disentangle.
We can think of confidence as capturing our mood or sentiment, particularly with respect to future economic developments. Figure 3 plots the Uncertainty Index for the UK alongside the OECD’s composite consumer and business confidence indicators. Values above 100 for the confidence indicators indicate greater confidence about the future economic situation and near-term business environment, while values below 100 indicate pessimism towards the future economic and business environments.
Figure 3 suggests that the relationship between confidence and uncertainty is rather more complex than perhaps is generally understood (click here for a PowerPoint). Haddow, Hare, Hooley and Shakir (see link below) argue that the evidence tends to point to changes in uncertainty affecting confidence, but with less evidence that changes in confidence affect uncertainty.
To illustrate this, consider the global financial crisis of the late 2000s. The argument can be made that the heightened uncertainty about future prospects for households and businesses helped to erode their confidence in the future. The result was that people and businesses revised down their expectations of the future (pessimism). However, although people were more pessimistic about the future, this was more likely to have been the result of uncertainty rather than the cause of further uncertainty.
Conclusion
For economists and policymakers alike, indicators of uncertainty, such as the Ahir, Bloom and Furceri World Uncertainty Index, are invaluable tools in understanding and forecasting behaviour and the likely economic outcomes that follow. Some uncertainty is inevitable, but the persistence of greater uncertainty since the global financial crisis of the late 2000s compares quite starkly with the relatively lower and more stable levels of uncertainty seen from the mid-1990s up to the crisis. Hence the recent frequency and size of changes in uncertainty show how important it to understand how uncertainty effects transmit through economies.
Academic papers
- The World Uncertainty Index
National Bureau of Economic Research, Working Paper 29763, Hites Ahir, Nicholas Bloom and Davide Furceri (February 2022)
- The Buffer-Stock Theory of Saving: Some Macroeconomic Evidence
Brookings Papers on Economic Activity, Christopher D Carroll (Vol 2, 1992)
- Macroeconomic uncertainty: what is it, how can we measure it and why does it matter?
Bank of England Quarterly Bulletin, 2013 Q2, Abigail Haddow, Chris Hare, John Hooley and Tamarah Shakir (13/6/13)
Articles
Data
Questions
- (a) Explain what is meant by the concept of diminishing marginal utility of consumption.
(b) Explain how this concept helps us to understand both consumption smoothing and the motivation to engage in buffer-stock saving.
- Explain the distinction between confidence and uncertainty when analysing macroeconomic shocks.
- Discuss which types of expenditures you think are likely to be most susceptible to uncertainty shocks.
- Discuss how economic uncertainty might affect productivity and the growth of potential output.
- How might the interconnectedness of economies affect the transmission of uncertainty effects through economies?
In the third of our series on the distinction between nominal and real values we show its importance when analysing retail sales data. In the UK, such data are available from the Office for National Statistics. This blog revisits an earlier one, Nominal and real retail sales figures: interpreting the data, written in October 2023. We find that inflation-adjusted retail sales data reveal some stark patterns in the sector. They help contextualise some of the challenges faced by high streets up and down the UK.
The Retail Sales Index
Retail sales relate to spending on items such as food, clothing, footwear and household goods. They involve sales by retailers directly to final consumers, whether in store or online. Spending on services such as holidays, air fares and train tickets, insurance, banking, hotels and restaurants are not included, as are sales of motor vehicles. The Retail Sales Index for Great Britain is based on a monthly survey of around 5000 retailers across England, Scotland and Wales and is thought to capture around three-quarters of turnover in the retail industry.
Estimates of retail sales are published in index form. There are two indices published by the ONS: a value and volume measure. The value index reflects the total turnover of business, while the volume index adjusts the value index for price changes. Hence, the value estimates are nominal, while the volume estimates are real. The key point here is that the nominal estimates reflect both price and volume changes, whereas the real estimates adjust for price movements to capture only volume changes.
The headline ONS figures for May 2024 showed a rise by 2.9 per cent in the volume of retail sales, following a 1.8 per cent fall in April. In value terms, May saw a 3.3 per cent rise in retail sales following a 2.3 fall in March. Monthly changes can be quite volatile, even after seasonal adjustment, and sensitive to peculiar factors. For example, the poor weather in April 2024 helped to depress retail spending. It is, therefore, sensible to take a longer-term view when looking for clearer patterns in spending behaviour.
Growth of retail sales
Chart 1 plots the monthly value and volume of retail sales in Great Britain since 1996. (Click here to download a PowerPoint of the chart). In value terms, monthly spending in the retail sector has increased by 169 per cent since January 1996, whereas in volume terms, spending has increased by 77 per cent. Another way of thinking about this is in terms of the average annual rate of increase. This shows that the value of spending has risen at an annual rate of 3.5 per cent while the volume of spending has risen at an annual rate of 2.0 per cent. This difference is to be expected in the presence of rising prices, since nominal growth, as we have just noted, reflects both price and volume changes.
Chart 1 helps to identify two periods where the volume of retail spending ceased to grow. The first of these is following the global financial crisis of the late 2000s. The period from 2008 to 2013 saw the volume of retail sales stagnate and flatline, with a recovery in volumes only really starting to take hold in 2014. Yet in nominal terms retail sales grew by around 14 per cent.
The second of the two periods is from 2021. Chart 2 helps to demonstrates the extent of the struggles of the retail sector in this period. It shows a significant divergence between the volume and value of retail sales. Indeed, between April 2021 and October 2023, while the value of retail sales increased by 8.0 per cent the volume of retail sales fell by 11.0 per cent.
The recent value-volume divergence reflects the inflation shock that began to emerge in 2021. This saw consumer prices, as measured by the Consumer Prices Index (CPI), rise across 2022 and 2023 by 9.1 per cent and 7.3 per cent respectively, with the annual rate of CPI inflation hitting 11.1 per cent in October 2022. Hence, while inflation was a drag on the volume of spending it nonetheless meant that the value of spending continued to rise. Once more this demonstrates why understanding the distinction between nominal and real is important. (Click here to download a PowerPoint of the chart).
To illustrate the longer-term trend in the volume of retail spending alongside its volatility, Chart 3 plots yearly retail sales volumes and also their percentage change on the previous year.
The chart nicely captures the prolonged halt to retail sales growth following the global financial crisis, the fluctuations caused by COVID and then the sharp falls in the volume of retail spending in 2022 and 2023 as the effects of the inflationary shock on peoples’ finances bit sharply. This cost-of-living crisis significantly affected many people’s disposable income. (Click here to download a PowerPoint of the chart).
Categories of retail sales
We conclude by considering categories of retail spending. Chart 4 shows volumes of retail sales by four broad categories since 1996. (Click here to download a PowerPoint of the chart). These are food stores, predominantly non-food stores, non-store retail and automotive fuel (i.e. sales of petrol and diesel “at the pumps”).
Whilst all categories have seen an increase in their spending volumes over the period as a whole, there are stark differences in this rate of growth. Perhaps not surprisingly, the most rapid growth is in non-store retail. This includes online retailing, as well as market stalls and catalogues.
The volume of retail spending in the non-store sector has grown at an average annual rate over this period of 6.3 per cent, compared with 2.6 per cent for non-food stores, 1.2 per cent for predominantly food stores and 1.0 per cent for automotive fuels. The growth of non-store retail has been even more rapid since 2010, when the average annual rate of growth in the volume of purchases has been 10.2 per cent, compared to 1.8 per cent for non-food stores, 1.0 per cent for automotive fuels and zero growth for food stores.
If we focus on the most recent patterns in the categories of retail sales, we see that the monthly volume of spending in all categories except non-store retail is now lower than the average in 2019. Specifically, when compared to 2019 levels, the volume of spending in non-food stores in May 2024 was 2.6 per cent lower, while that in food stores was 4.4 per cent lower, and the volume of spending on automotive fuels was 10.8 per cent lower. In contrast, spending in non-store retail was 21.2 per cent higher. Yet this is not to imply that this sector has been immune to the pressures faced by their high-street counterparts. Although it is difficult to disentangle fully the effects of the pandemic and lockdowns on non-store retail sales data, the downward trajectory in the volume of retail sales in the sector that occurred as the economy ‘reopened’ in 2021 and 2022 continued into 2023 when purchases fell by 3.5 per cent.
Final thoughts
The retail sector is an incredibly important part of the economy. A recent research briefing from the House of Commons Library reports that there were 2.7 million jobs in the UK retail sector in 2022, equivalent to 8.6 per cent of the country’s jobs with 314 040 retail businesses as of January 2023. Yet the importance of the retail sector cannot be captured by these statistics alone. Some would argue that the very fabric and wellbeing of our towns and cities is affected by the wellbeing of the sector and, importantly, by structural changes that affect how people interact with retail.
Articles
Research Briefing
Statistical bulletin
Data
Questions
- Which of the following is/are not counted in the UK retail sales data: (i) purchase of furniture from a department store; (ii) weekly grocery shop online; (iii) a stay at a hotel on holiday; (iv) a meal at your favourite café or restaurant?
- Why does an increase in the value of retail sales not necessarily mean that their volume has increased?
- In the presence of deflation, which will be higher: nominal or real growth rates?
- Discuss the factors that could explain the patterns in the volume of spending observed in the different categories of retail sales in Chart 4.
- Discuss what types of retail products might be more or less sensitive to changes in the macroeconomic environment.
- Conduct a survey of recent media reports to prepare a briefing discussing examples of retailers who have struggled or thrived in the recent economic environment.
- What do you understand by the concepts of ‘consumer confidence’ and ‘economic uncertainty’? How might these affect the volume of retail spending?
- Discuss the proposition that the retail sales data cast doubt on whether people are ‘forward-looking consumption smoothers’.
The distinction between nominal and real values in one of the ‘threshold concepts’ in economics. These are concepts that are fundamental to a discipline and which occur again and again. The distinction between nominal and real values is particularly important when interpreting and analysing data. We show its importance here when analysing the latest retail sales data from the Office for National Statistics.
Retail sales relate to spending on items such as food, clothing, footwear, and household goods (see). They involve sales by retailers directly to end consumers whether in store or online. The retail sales index for Great Britain is based on a monthly survey of around 5000 retailers across England, Scotland and Wales and is thought to capture around 75 per cent of turnover in the sector.
Estimates of retail sales are published in index form. There are two indices published by the ONS: a value and volume measure. The value index reflects the total turnover of business, while the volume index adjusts the value index for price changes. Hence, the value estimates are nominal, while the volume estimates are real. The key point here is that the nominal estimates reflect both price and volume changes, whereas the real estimates adjust for price movements to capture only volume changes.
The headline ONS figures for September 2023 showed a 0.9 per cent volume fall in the volume of retail sales, following a 0.4 per cent rise in August. In value terms, September saw a 0.2 per cent fall in retail sales following a 0.9 per cent rise in August. Monthly changes can be quite volatile, even after seasonal adjustment, and sensitive to peculiar factors. For example, the unusually warm weather this September helped to depress expenditure on clothes. It is, therefore, sensible to take a longer-term view when looking for clearer patterns in spending behaviour.
Chart 1 plots the value and volume of retail sales in Great Britain since 1996. (Click here for a PowerPoint of this and the other two charts). In value terms, retail sales spending increased by 165 per cent, whereas in volume terms, spending increased by 73 per cent. This difference is expected in the presence of rising prices, since nominal growth, as we have just noted, reflects both price and volume changes. The chart is notable for capturing two periods where the volume of retail spending ceased to grow. The first of these is following the global financial crisis of the late 2000s. The period from 2008 to 2013 saw the volume of retail sales stagnate and flatline with a recovery in volumes only really starting to take hold in 2014. Yet in nominal terms retail sales grew by around 16 per cent.
The second of the two periods is the decline in the volume of retail sales from 2021. To help illustrate this more clearly, Chart 2 zooms in on retail sales over the past five years or so. We can see a significant divergence between the volume and value of retail sales. Between April 2021 and September 2023, the volume of retail sales fell by 11%. In contrast, the value of retail sales increased by 8.4%. The impact of the inflationary shock and the consequent cost-of-living crisis that emerged from 2021 is therefore demonstrated starkly by the chart, not least the severe drag that it has had on the volume of retail spending. This has meant that the aggregate volume of retail sales in September 2023 was only back to the levels of mid-2018.
Finally, Chart 3 shows the patterns in the volumes of retailing by four categories since 2018: specifically, food stores, predominantly non-food stores, non-store retail, and automotive fuel. The largest fall in the volume of retail sales has been experienced by non-store retailing – largely online retailing. From its peak in December 2020, non-store retail sales decreased by almost 20 per cent up to September 2023. While this needs to be set in the context of the volume of non-store retail purchases being 14% higher than in February 2020 before the pandemic lockdowns were introduced, it is nonetheless indicative of the pressures facing online retailers.
Importantly, the final chart shows that the pressures in retailing are widespread. Spending volumes on automotive fuels, and in food and non-food stores are all below 2019 levels. The likelihood is that these pressures will persist for some time to come. This inevitably has potential implications for retailers and, of course, for those that work in the sector.
Articles
Statistical bulletin
Data
Questions
- Why does an increase in the value of retail sales not necessarily mean that their volume has increased?
- In the presence of deflation, which will be higher: nominal or real growth rates?
- Discuss the factors that could explain the patterns in the volume of spending observed in the different categories of retail sales in Chart 3.
- Discuss what types of retail products might be more or less sensitive to the macroeconomic environment.
- Conduct a survey of recent media reports to prepare a briefing discussing examples of retailers who have struggled or thrived in the recent economic environment.
- What do you understand by the concepts of ‘consumer confidence’ and ‘economic uncertainty’? How might these affect the volume of retail spending?
- Discuss the proposition that the retail sales data cast doubt on whether people are ‘forward-looking consumption smoothers’.