A second wave comes crashing down

Markets have been unsettled for some time about the prospect of a second Covid wave and they finally capitulated this week. The market collapse on Wednesday, which saw the S&P500 fall more than 3.5% and the DAX fall more than 4%, came on the day that Germany introduced a stringent set of national lockdown restrictions involving a one-month shutdown of bars and restaurants which is due to come into effect on Monday. France also announced a national lockdown which came into effect today. It may not be quite as stringent as that enforced earlier in the year but it is still pretty drastic. As President Macron said in his TV address, “the virus is circulating in France at a speed that even the most pessimistic forecast didn’t foresee … The measures we’ve taken have turned out to be insufficient to counter a wave that’s affecting all Europe.” Given the renewed spread of the disease, it seems only a matter of time before the UK is forced to follow suit.

What does a second wave mean for the global economy? Throughout this year, most reputable forecast institutions have presented a range of alternative scenarios around the baseline and it is worth digging into some of the details of the IMF’s forecast released last week. The IMF baseline looks for a 4.4% contraction in global GDP this year followed by a rebound of 5.2% in 2021 (in my humble opinion this sounds like a stretch since it implies that all the damage done to output in 2020 will be recouped next year). However, whilst the downside scenario garnered rather fewer headlines it was nonetheless illustrative. It is based on the assumption that Covid proves difficult to contain, with a significant drag on activity in the second half of 2020 extending into 2021. In addition, the IMF assumes that progress on finding effective treatment is rather slower than currently assumed, with a delay in the process of finding a vaccine and the requirement that social distancing measures have to remain in place for a long time to come.

Under these circumstances the global growth rate next year could come in as low as 0.9% versus the baseline projection of 5.2% and it takes until 2025 before output is back on the path implied by the baseline (chart 1). It is also notable that in this scenario emerging markets take a larger than proportional hit. This accords with my long held view that since EMs are acutely dependent on a recovery in their main export markets, the IMF is too optimistic on how quickly output in Asia will rebound in the baseline projection.

As far as markets are concerned , we have been here before. The equity declines registered on Wednesday may not be the biggest daily falls this year but they are not far away from some of the dramatic swings recorded in March. On the one hand there is some scope for cautious optimism in that we have a rather better idea of what we are letting ourselves in for. Accordingly, equity indices may not fall as sharply since we are operating in less unfamiliar territory. Against that, markets may be on the verge of capitulation as the pandemic proves not to be the short, sharp shock that was expected in the spring. As is usual at times of equity market stress the tech sector comes in for the closest scrutiny (chart 2). In addition to concerns that the pandemic may take the edge off demand, the fact that Apple’s iPhone sales and Twitter’s user growth both missed estimates added to the sense of market uncertainty. Next week’s US Presidential election may have longer-lasting consequences for the tech sector if Joe Biden is elected to the White House and embarks on a programme of cutting the tech companies down to size.

However, for the time being I tend to take a more optimistic line. For one thing we should not read too much into equity volatility just a few days ahead of the most important US election for years. Part of the recent wobbles may reflect some position squaring ahead of the main event. Moreover,  central banks are pumping in liquidity on an unprecedented scale. The Fed has increased its balance sheet by two trillion dollars this year, primarily due to purchases of Treasury securities which will suffice to keep bond yields at ultra-low levels. Here in Europe, current estimates suggest that EMU governments will issue €1.2 trillion of gross debt next year but maturing bonds and interest payments could reduce the net figure to €405bn. Even without the promised monetary expansion the ECB is expected to buy €460bn of debt in the secondary market – more than planned issuance. This downward pressure on global yields when plugged into a simple discounted cash flow model ought to be enough to put a floor under equity markets.

But even if markets do hold up, the economy will take a long time to recover from the scarring effects of Covid. In the US, for example, the unemployment rate currently stands at 7.9%, twice as high as in February prior to the pandemic whilst employment is around 11 million below pre-recession levels. What makes me somewhat uneasy is that we have entered a period where there is a mounting disparity between what is happening to markets and conditions in the real economy which underpin them.

This will be manifest in elevated P/E ratios. I have frequently referred to the Shiller trailing 10-year P/E ratio for the S&P500 as a measure which smooths out cyclical variations and have noted that over recent years it has remained very high in a historical context (chart 3). In just the last few months it has rebounded back to pre-recession highs following a dip in the wake of market panic in March. This is a clear illustration of the extent to which traditional valuation metrics no longer apply and for the foreseeable future the equity market will be running on the back of the support given by central banks. Given the lack of clarity from the normal pricing metrics it could be a very bumpy few months for markets.

Learning to live with the economics of Covid

Without any shadow of a doubt the biggest problem governments face at present is how to balance the benefits from measures to curb the pandemic against the economic costs of efforts to limit its spread. As the second wave of Covid-19 emerges it is clear that countries have coped in different ways. But what are the factors underpinning the differing performances and have countries learned from past mistakes which will prevent a repeat of the surge in mortality rates that we saw during the first wave?

An excellent paper in The Lancet looked at the varying approaches to assessing the criteria adopted by a number of industrialised economies for introducing lockdowns in the first place and the criteria for easing them. As is apparent from the differing infection and mortality rates across countries, there has been a wide diversity of responses. The authors of the study identify a number of factors which are necessary to ensure effective control of the spread. In the first instance we need some idea of the current status of infection rates which requires a surveillance system to be in place allowing us to track the reproduction number (R number) in real-time. A second prerequisite is community engagement which gives greater flexibility to local communities to take decisions to protect themselves. This has become a particularly fraught issue in the UK where government is highly centralised but where the four nations have increasingly adopted different approaches to easing the lockdown. Even in England there is now increasing tension between the London government and urban areas in the north, which threatens to have significant long-term political repercussions.

The authors note that “with few exceptions, such as Germany, New Zealand, Norway, Scotland, and South Korea, political leaders have struggled to secure public trust and thus support for continued lifestyle changes. More generally, countries with female leaders have done better at securing public confidence and adherence to new measures than have countries with male leaders.” Readers interested in the latter point can refer to the original paper (here).

One of the features of the past seven months across many countries has been the series of mixed messages which have sown confusion. This is evident, for example, in advice on how many people can congregate in confined spaces. More particularly it is evident in advice on wearing face coverings. At the start of the pandemic the World Health Organisation argued that masks would encourage a false sense of security and would deprive medical professionals of badly needed protective equipment. It also argued that there was insufficient evidence to suggest that healthy people should wear them. The WHO finally changed this advice in June. Whilst numerous Asian countries long ago adopted the practice of wearing masks in public places, it has been slower to catch on in Europe and North America and we have witnessed demonstrations in a number of countries against the requirement to wear a face covering. To add insult to injury, the UK government has recently confirmed that it will end the VAT waiver on personal protective equipment from 1 November. British households will thus have to pay 20% more for the masks which they are legally obliged to wear in shops and on public transport.

But by far the biggest factor determining the differences in performance across countries is the capacity of the heath system, most notably the track and trace system. Singapore and South Korea have mortality rates of 0.5 and 0.9 per 100,000 of population respectively compared with 66.9 in the UK, 68.1 in the US and 93.0 in Belgium. Singapore has a rigorously enforced system which has led some to complain about its personal data implications but its success cannot be denied. South Korea has introduced a mass testing regime and uses electronic health records, credit card transactions data and mobile phone-based GPS data to determine peoples’ movement. It also relies on tracers with detailed local knowledge to observe localised outbreaks. The UK’s experience has been much less impressive: after it abandoned its initial attempts at track and trace it attempted to develop its own smartphone app but later abandoned this approach and switched to an Apple–Google system – an approach which cost valuable time.

As the second wave intensifies, many industrialised countries have taken on board the lessons learned during the spring. Full lockdowns did prove to be effective in curbing the spread of the disease but they come at an enormous economic cost and they would only be repeated as a very last resort. There is thus a general recognition that over the coming winter, we are going to have live with Covid and keep the economy afloat as best we can, for even if we are close to a breakthrough in finding a vaccine it is not going to be widely available until the second half of 2021 at the earliest.

The epidemiologists who authored The Lancet article thus make a series of recommendations for the conduct of Covid policies:

i)             In the first instance governments should be transparent about which factors are being taken into account when assessing the threat level and “ideally, these … should explicitly state the levels or phases of easing restrictions, the criteria for moving to the next level or phase, and the containment measures that each level or phase entails.”

ii)            Lockdowns should not be eased until the infection situation can be adequately monitored which requires an emphasis on local conditions rather than simply the national average picture.

iii)           Since it is obvious that distancing restrictions will have to remain in place for quite some time to come, “governments should educate, engage, and empower all members of society, especially the most vulnerable, to participate in the pandemic response. Rather than crafting these measures on the basis of assumptions about what communities can or cannot accept, citizens should be directly involved in the process of coproducing tailored solutions appropriate for the local context.”

iv)           Most importantly, it is crucial to introduce an effective track, trace and isolate system. As the authors point out, “preliminary data for testing suggests that identifying and isolating mild and asymptomatic cases can significantly reduce R, health-care burden, and overall fatality.” Once the system is in place, it is important to ensure effective takeup, with some research suggesting that an overall participation rate of 56% is sufficient to stop transmission.

European governments have largely learned the importance of adhering to these conditions although they are complicated by differing forms of government with countries with decentralised government (e.g. Germany and Switzerland) posting better outcomes than more centralised systems such as France and the UK. 

They may also work better if people find it in their interests to comply with more rigorously enforced rules when they have a stake in their success. An under-appreciated economic consequence is the distributional impact of lockdown measures with some sectors expected to take a much bigger hit than others. As MPC member Gertjan Vlieghe noted in a speech last week “we are really not all in this together. It is far, far worse for some than for others.” Accordingly, the measures may be more likely to work if governments can give reasonable assurances that there will be work for people to go back to when the pandemic subsides. That alone may be a good reason for governments to continue providing labour market support over the winter months.

The IMF and economic support: It's Mainly Fiscal

On a day when the UK reported another eye-wateringly high level of government borrowing, one MP tweeted that “the state of the public finances should alarm everyone who understands them.” My advice would be let’s not get too alarmed just yet. It is also the advice given by the IMF in its latest Fiscal Monitor (FM) published this week. Politicians’ views are usually based on the assumption that public finances can be equated with household finances thus prompting howls of outrage when deficits and debt are deemed to be “too high” because they look at the monetary amount of the deficit or debt without putting it into some form of economic context.

When it comes to debt, what matters is the ability to service it in the short-term and reduce the burden it poses on the economy in the longer-term. Admittedly the UK’s public debt now exceeds 100% of GDP which is higher than we would ideally like but as I have pointed out previously, many countries have lived with higher debt ratios. To the extent that GDP represents a measure of annual income, the UK (in common with many other European economies) has a debt level which exceeds its annual income. But households routinely borrow significant multiples of their annual income to buy a house, and for the record the UK household sector has debt equivalent to 139% of its annual income. Calls for the government to cut back on the support it provides, despite the fact that the Covid pandemic is getting worse rather than better, are thus deluded.

The IMF points out that in a global context, “public debt is expected to stabilize at about 100 percent of GDP until 2025, benefiting from negative interest-growth differentials. These high levels of public debt are hence not the most immediate risk. The near-term priority is to avoid premature withdrawal of fiscal support.” A crucial reason for this is that fiscal measures have undoubtedly “saved lives, supported vulnerable people and firms, and mitigated the fallout on economic activity” and unsurprisingly the IMF advocates devoting considerable fiscal resources to health. But “further support is necessary to protect people who cannot make a living under the current circumstances” (a message which might be directed at UK the government following the heated discussions regarding how much support it should be expected to provide to those regions of the country which have been subjected to a more intense lockdown).

Quite how long the pandemic will last is obviously unknown, and this explains why governments are not willing to make open-ended commitments. On the basis that eventually we will overcome the worst effects of Covid-19, governments will have to make some important decisions about when and how to reduce their fiscal support. But the IMF, which has undergone a form of Damascene conversion on fiscal policy since the 2008 crisis, argues that governments should continue a programme of public investment even after the worst of the crisis has passed. It makes the point that the bang for the buck from higher public investment is larger during times of economic uncertainty (i.e. the fiscal multiplier is higher) than during more “normal” times. Moreover, low interest rates, high precautionary savings and weak private investment are strong arguments for boosting public investment to “crowd in” private investment. This is all a long way from the IMF’s advice in October 2008 when it suggested “policymakers must be very careful about how stimulus packages are implemented, ensuring that they are timely and that they are not likely to become entrenched and raise concerns about debt sustainability.”

Indeed in October 2012, the IMF concluded that it had systematically underestimated fiscal multipliers since the start of the Great Recession by between 0.4 and 1.2. Thus, if we thought pre-crisis that the multiplier was around 0.5, it would in fact be more likely to be in the range 0.9 to 1.7 (a figure greater than unity implies that a fiscal expansion of x% of GDP would lead to an increase in output of more than x%). Subsequent IMF research also suggested that fiscal multipliers are significantly larger in times of a negative output gap than when the output gap is positive (I was not very popular amongst my German colleagues in 2015 for pointing this out). In the latest FM, the IMF’s empirical results suggest that an increase of public investment equivalent to 1% of GDP increases the level of output by a factor of more than two in a high uncertainty environment versus 0.6 in the baseline case (chart below).

However, much of the public debate proceeds on the basis that all government spending is somehow equal and that as long as “something is done” all will be well. This is not the case. As Chris Giles pointed out in the FT last week, the UK government spent 0.6% of GDP on its much-vaunted Covid track and trace system in the expectation that this would allow the economy to reopen safely with the result that the economic benefits would significantly outweigh the costs. The project has not worked out like that and it currently looks like an expensive failure. It may yet match expectations with additional outlays but the point is made that public projects have to be carefully scrutinised to ensure that they generate decent rates of return (either social or financial). BoE Governor Andrew Bailey made this point to a parliamentary Economic Affairs Committee last week, noting that investment “has to be in projects that earn a rate of return. History is quite mixed on that front.”

The IMF notes that in “advanced economies that do well on the World Economic Forum’s index of government-spending wastefulness, public investment has been found to have a fiscal multiplier of 0.8 in the first year and above 2.0 at the four-year horizon.” For the record, the UK ranks 34 out of 136 countries behind Germany (20) and Japan (22) but ahead of France (73) and the US (74). Whilst it is all very well arguing for higher public investment, there is a question of where it should be targeted. Aside from health, education is high up the priority list since it results in significant externalities which produce very high rates of social return (although these returns tend to accumulate only over long horizons). I have increasingly become an advocate of investing in climate-proofing the economy where the evidence suggests that returns are often in excess of 100%, and well above this in regions particularly exposed to extremes of weather. Investment in digital infrastructure is another area likely to generate significant returns in the near future and I will undoubtedly return to these issues another time.

Governments have clearly learned from past experience that they have to step in to make up for a shortfall in private demand in times of extreme crisis such as we are experiencing today. Whether they will learn from the experience of the past decade remains to be seen. Too many governments were quick to turn off the taps following the GFC in a bid to improve their fiscal position. The trick in coming years will be to recognise that this cannot be achieved in a matter of a few years – this is a multi-decade problem which will be made all the easier by policies which support growth rather than hinder it.

Moody and petulant

Over the course of recent months I have expressed concerns at the quality of governance, particularly in the UK, and nothing that has happened recently has prompted a change of view. If anything, quite the opposite. These concerns were picked up by the ratings agency Moody’s following Friday’s decision to downgrade the UK’s sovereign credit rating by another notch to Aa3, citing the “fractious policy environment.” As a rule I do not set much store by the macro views of ratings agencies, largely because they tell us what we already know. More importantly their raison d’être is to assess the likelihood of default, and whatever else might be wrong with the UK it is less likely to default than any euro zone country because it issues debt in a currency it controls whereas euro zone countries do not. That said, we should take the comments on governance seriously.

According to Moody’s, the UK’s failure “to manage change in a predictable and confidence-building manner is evident with respect to the UK’s approach to Brexit, in its inability to achieve an outcome which meaningfully replicates the benefits of EU membership and in its approach to implementing the agreement reached with the EU to date.” It went on to add that “Even if there is a trade deal between the UK and EU by the end of 2020, it will likely be narrow in scope, and therefore the UK’s exit from the EU will … continue to put downward pressure on private investment and economic growth.” Anyone who has read anything I have written on this subject will know that this has long been my view, so on the one hand I ask myself what took them so long to catch up, although on the other it is nice to be vindicated. 

The great bluff revisited 

It is no coincidence that this downgrade took place on the day the British government announced that the UK should prepare for EU trading arrangements “that are more like Australia’s, based on simple principles of global free trade.” In other words, a no-deal Brexit. But as Simon Hix of the LSE pointed out in a Tweet, “Australia has a range of agreements with the EU. No Deal is more like an ‘Afghanistan style deal’.” Anyone who thinks that a no-deal Brexit is a good outcome has not been paying attention. Indeed back in 2017 the then-trade secretary Liam Fox argued that securing a trade deal with the EU would be the “easiest in human history” and only last year Boris Johnson promised the electorate that he had “an oven ready deal”.  There are doubtless some who still believe that leaving the EU at any price is worthwhile but mainstream politicians have gone rather quiet on this front and a no-deal Brexit is welcomed only by those who don’t know any better.

For all my reservations about Johnson and his suitability for the highest office, I do not believe he is a stupid man (even though he often acts like one). Accordingly I still maintain that this action represents the highest stakes yet in a campaign of brinkmanship that has characterised the whole negotiating process. But what is a cause for concern is that Johnson’s statement risks triggering a miscalculation which makes a no-deal Brexit outcome more likely. After all, the EU only has to take him at his word and end negotiations and the whole edifice comes crashing down around the UK’s ears. As if to illustrate this, media reports suggest that the UK’s decision to break off talks are the result of a misunderstanding. This followed the EU’s decision to delete from the statement issued after last week's summit a pledge to intensify negotiations. According to the EU, this was designed to reduce the pressure on Michel Barnier to find a breakthrough in the discussions. The British side saw it as unwillingness on the EU’s part to make concessions. 

France and fisheries 

Matters have not been helped by comments by the French government. Having inflamed tensions by suggesting that UK has a choice between accepting the EU’s conditions or getting no deal at all, Emmanuel Macron reminded us that “The British, no matter what was said to them during the referendum campaign, need the European single market … They are much more dependent on us than we are on them.” Whilst this is not news to anyone it does nothing to assuage the hardliners in the British government who refuse to accept they are the weaker partners in the negotiations.

Fisheries remain one of the key sticking points. For the French, Dutch and Belgian fishing industries based in Channel ports, access to UK territorial waters is vital to their continued survival and the French government has increasingly adopted a hard line on this issue. It does seem a remarkably trivial issue over which to scupper a trade deal but this is the strange world of Brexit where rationality long since departed the stage. The German government has reportedly tried to intercede in order to persuade the French government to soften its position but apparently has had little impact so far. It may require some deft diplomacy on the part of the EU to take matters forward, as my reading of the German position is that they see little point in allowing negotiations to fail over a fishing dispute.

Quite why fisheries occupy such a totemic place in the Brexit debate has always escaped me since they account for less than 0.1% of UK GDP. But for those who care about these things they are a symbol of the EU’s encroachment on the ability to set domestic policy. The setting of quota limits in Brussels has coincided with a decline in the British fishing industry over the past 40 years. But the industry would have struggled anyway due to the fact that overfishing would have reduced the catch. Nonetheless, blaming the EU is a convenient narrative. Interestingly, one of my colleagues, who I should point out is an ardent Remainer, recently suggested to me that he had some sympathy for the position of the Brexiteers. As he pointed out, there seems little point in taking back control of your sovereignty if you are forced to concede access to French fishermen. But this is to miss the point. The British are seeking tariff free access to the wider European market and have to give something back in return. In my view, fishing concessions have such a small aggregate economic impact that it is a price worth paying to ensure the continued survival of the car industry. 

Domestic politics will force the UK to do a deal 

A no-deal Brexit is unlikely to play well at home.  On the one hand the survey evidence suggests, for what it is worth, that a rising proportion of those surveyed believe that the decision to leave the EU was wrong (see chart below). Even more significantly, like other European countries, the UK is suffering from a sharp rise in Covid infection rates. Not only is the government’s handling of the Covid crisis causing significant domestic political tension but the prospect of additional lockdown measures will place an additional burden on the economy, with current policies setting us up for a big rise in unemployment. Some simulation analysis I conducted in 2018 suggested that a no-deal Brexit could result in a 1.5% decline in GDP in the first quarter after leaving the EU. Adding the Covid burden on top of this would result in economic outcomes that would almost certainly hit the Conservatives at the ballot box by the time of the next election. A rational government would surely not want to take that risk.

The fact that the EU plans to continue talks with the UK next week suggests that a deal can be salvaged in the coming weeks. My long held view is that the UK has no interest in walking away without one. But the atmosphere of mistrust on both sides might act as an obstacle to progress and there is always a risk that at some point the EU may call the UK’s bluff. However, with both sides having narrowed their differences on many other issues (aside from fisheries) it is likely that they will try to keep negotiating lines open. On the basis that in EU negotiations “nothing is agreed until everything is agreed” they may yet surprise us.

The last days of empire?

Most of us are not privileged to witness major historical events at close hand. Even if we did, we would be unlikely to fully understand their significance. Imagine being present at the signing of the Magna Carta in 1215, little knowing that it would represent one of the first attempts to codify individual freedoms that would echo down the centuries. Nor would many people have seen the Ninety-five Theses supposedly pinned to the door of All Saints' Church in Wittenberg by Martin Luther in 1517, but we are all familiar with the resultant splits within the Catholic Church which were arguably a first step on the road to the Age of Enlightenment.

I raise these points because it is impossible to know whether what we are experiencing today reflects a fundamental shift in the way our societies and economies will operate in future or whether it is minor diversion on a path we have been following for the past 75 years. One of the motivating factors for thinking about this was an excellent article on the Mother Jones website by the historian Patrick Wyman who looked at the decline of empire. As Wyman put it, “the fall of an empire …looks more like a cascading series of minor, individually unimportant failures than a dramatic ending that appears out of the blue.” He also makes the point that whilst all societies face challenges and setbacks, what determines the survival of the status quo is the quality of the institutions which are able to define a response. At issue in large parts of the west today is whether the institutional framework is sufficiently robust to face up to the challenges of the 21^st century.

Just weeks away from the US election the world looks on to see whether the Donald Trump experiment will be brought to a halt or whether the process of institutional erosion will be given free rein to continue. In Wyman’s view, the future popular narrative of the relative demise of the US will pin the blame on Trump, “but it’s far more likely that the real meat of the issue will be found in a tax code full of sweetheart deals for the ultra-wealthy, the slashed budgets of county public health offices, the lead-contaminated water supplies. And that’s to say nothing of the decades of pointless, self-perpetuating, and almost undiscussed imperial wars that produce no victories but plenty of expenditures in blood and treasure, and a great deal of justified ill will.” This may not be the version of the US that you recognise or accept. But the wider point is that a country as institutionally strong as the US does not suddenly go from being the only superpower to sharing the stage with others in just four years. Other factors are at play. 

Why the economics matters 

The Nobel Prize winning economist Joseph Stiglitz points to “the growing concentration of market power, which allows dominant firms to exploit their customers and squeeze their employees.” This in turn has allowed shareholders and company managers to expropriate a bigger slice of the pie, leading to widening inequality and further fuelling the sense of resentment which led to Trump being elected in the first place. In Stiglitz’s view a small number of firms dominate key sectors of the US economy, which has allowed them to attain disproportionate political influence “and as the system has become more rigged in business’s favor, it has become much harder for ordinary citizens to seek redress for mistreatment or abuse.” 

To compound these problems, evidence compiled by the World Economic Forum suggests that US social mobility has slowed and maybe even gone into reverse. For generations, workers tended to earn more than their parents. However, the evidence suggests that those born in the 1980s whose parents were in the middle of the income distribution only have a 45% chance of earning more than their parents compared to 59% for those born in the 1970s and 95% for those born in the 1940s (chart below). This is not what the American Dream is made of.

One of the factors underpinning this result is the sluggish pace of wage growth. Real hourly earnings, for example, have increased by only 11.7% since the mid-1960s despite a significant increase in productivity. Moreover there has been particularly rapid growth in the price of services such as health and education. Consumers thus have to devote a much higher slice of their disposable income to educate themselves and maintain their health than they did 50 years ago. The income distribution has also become increasingly skewed in favour of the well-off. According to data from the Pew Research Center households towards the upper end of the income distribution have increased their share of wage income over the past 50 years, from 28% to 48%, at the expense of those in the middle, whose share fell from 62% in 1970 to 43% by 2018 (chart below).

This matters because it is this sense of dissatisfaction that Trump tapped into in 2016. But what is driving it? It may partly be due to the decline in trade union membership since the 1980s which has prevented organised labour from acting as a counterweight to rent seeking company owners. The application of new technology further adds to the pressure by pushing down on the wages of the less well educated segment of the labour force. Of course, these issues are not merely confined to the US – this sense of dissatisfaction was a driving force behind the Brexit referendum result in the UK – but they are more extreme on the other side of the Atlantic. The extent to which politicians are willing to tackle these problems will play a big role in determining how Anglo Saxon society and its economy will look in future and whether it will still be held an example for others to follow. 

And why the response of politicians matters even more 

According to Stiglitz “US corporate executives made sure that the vast majority of the benefits from the [2017] tax cut went into dividends and stock buybacks, which exceeded a record-breaking $1.1 trillion in 2018.” This reinforces the sense that Trump’s economic policies have benefited the rich at the expense of those who voted for him. Yet there is a good reason why this should be the case: Presidential hopefuls require a big war chest, to which big business is more likely to contribute if their interests will be served by the candidate. As the experience of Bernie Sanders illustrates, politicians who are prepared to tackle the redistribution question are unable to generate sufficient buy-in to be elected. Nor is the business capture problem confined to the US. Michel Cames and Eckard Helmers argue (here) that “the European oil industry co-initiated the shift to diesel cars in the 1980s and 1990s in order to find outlets for middle distillates [diesel]” and they did so in tandem with the European Commission by selling it as a way to meet CO₂ reduction targets. Never mind the fact that it raised nitrous oxide levels, with all the attendant health consequences.

The danger in all this is that rising economic inequality and the capture of the political decision making process by big business threatens to further raise the degree of anger at the status quo. This could be used by future generations of nationalist politicians to pursue an agenda which makes that of Trump seem tame. The long-term health of the Anglo Saxon economy and the society which underpins it depends on it being seen to serve the interests of voters. After a decade of uncertainty in the wake of the financial crisis of 2008, and even more so at a time of the unprecedented Covid pandemic, the US and UK are crying out for someone to deliver genuine leadership and make voters believe that the economic system works for them. Failure to act before it is too late risks condemning the Anglo Saxon model to irrelevance. We may not understand the slow process of erosion as we live through it but it will surely be clear to future generations of historians.

How not to Excel

The UK authorities continue to demonstrate imaginative ways to screw things up in ways which would be laughable were they not so serious. The recent news that the number of reported Covid-19 cases jumped by 85% on Saturday and by another 78% on Sunday to leave them more than three times the figure reported on Friday has been blamed on a computer error. But it was not a major system failure arising from the complexity of the infrastructure. It was one of those dumb things that happen from time to time, like when the Mars Climate Orbiter was lost in 1999 after one piece of software provided output in imperial units to a routine that was expecting them in metric units.

In this instance, the agencies responsible for collecting the swabs for the Covid track and trace system delivered data in a CSV file, whose length is theoretically unlimited, to Public Health England (PHE) which imported it into an Excel spreadsheet. Unfortunately PHE failed to realise that a spreadsheet is limited to 1,048,576 row entries and 16,384 column entries. Data which exceed these limits are simply ignored, hence 15,841 positive test results were overlooked – as were the details of those with whom they had been in contact. As someone with a lot of hands-on experience handling datasets which regularly exceed Excel limits, I was very surprised that an organisation handling such volumes of data made such a basic error (for a small consultancy fee I will happily teach the health authorities to handle such datasets). 

Better tools for the job 

The issue resonated with me because over the course of recent months I have become very interested in the appliance of data science techniques to the collection and analysis of large datasets, particularly real time data. Whilst I am no expert, I know enough to recognise that Excel is not the appropriate tool. There are much better resources to handle data. If it is storage that the authorities are concerned with, a low cost solution would be to use a dedicated database such as Microsoft Access. Excel is great for dealing with relatively small datasets but it is completely the wrong tool for dealing with big data. Jon Crowcroft, Professor of Communications Systems at the University of Cambridge, was quoted as telling the BBC that “Excel was always meant for people mucking around with a bunch of data for their small company to see what it looked like … And then when you need to do something more serious, you build something bespoke that works - there's dozens of other things you could do. But you wouldn't use XLS. Nobody would start with that."

Nor is it necessarily the right tool for many economic applications. Back in 2013, it was revealed that a paper by Carmen Reinhart and Ken Rogoff contained a spreadsheet coding error which invalidated their result that GDP growth declines once public debt exceeds 90% of GDP. For years academic economists have been using systems such as Matlab and Gauss for much of their quantitative work. Whilst they are excellent for handling data matrices underpinning most econometric analysis, they come with a high price tag. This limits their use to those who have stumped up the licence fee and discourages those who merely wish to engage in low cost experimentation. 

Increasingly, however, the economics profession is moving towards the use of systems which can store data and conduct advanced analytics. Two of the most popular are the R software environment and the Python programming language. Both are free to download and each has a huge volume of online libraries which users can integrate into their own system. So far as most economic applications are concerned, the likelihood is that someone has already written a library to do the analysis you are interested in or there is something sufficiently close that minimal code changes are required. Since both can do what Matlab and Gauss can do, and they can be downloaded for free, what’s not to like? 

The cost of change 

Unfortunately, financial costs are not the only issue: a major investment in time is required in order to become proficient in any system. Since neither R nor Python are particularly user friendly at first glance, it is easy to understand why people are daunted by the prospect of getting stuck into what looks like some heavy duty coding. Moreover, those who many years ago invested time and effort in learning other systems need to be persuaded that the benefits of switching are worthwhile. In my case, I have yet to come across a system that handles structural macroeconomic models better than the Aremos system, whose roots extend back almost 50 years (a view that may not be shared by everyone but it is a system which has worked well for me for many years). However R and Python do a lot of other things far better so I have been experimenting with both. 

Examples: (i) Big data sets

At the outset I should declare my preference for R. This is primarily due to a number of system-related reasons, but Python can do all the things I am about to describe. A good place to start is the analysis of big data sets and anyone who has looked at the Google mobility data will run into the same problem as PHE did when looking at Covid data. Whilst it is possible to download the CSV file from Google’s website containing 2,621,847 records (as of today) it is not possible to load it into Excel. But R can handle vectors of more than 2.1 billion records so it is straightforward to download the data and do any required data manipulation before exporting it in the format of your choice. 

(ii) Natural language processing 

Another thing that R does well – although probably not as well as Python – is natural language processing. I may look at this topic in more detail another time, but suffice to say that last year I did some work in R to analyse the communication content of the Bank of England MPC minutes. Amongst other things, the analysis looks at the readability of the minutes by calculating the Flesch ease of reading index. We can also attempt to define particular keywords in context by identifying those words which are most closely associated with a specific term. Thus, for example, we can identify how often the word “inflation” is associated with those words representing concern (“worries”, “problems” etc.) thus allowing us to quantify the extent to which the BoE is currently worried about inflation (we can add further filters to determine whether the concerns are about overly-high or overly-low inflation). 

(iii) Scraping the web 

A lot of data sit on websites which in the past might have had to be typed in manually. Those days are long behind us. Numerous libraries exist in both R and Python which allow users to grab data from online sources. We can, for example, import data from Twitter which opens up numerous possibilities for analysing tweet patterns. One of the routines I regularly undertake is to scrape four-hourly data on UK electricity generation directly from Twitter as an input into my real-time economic analysis 

(iv) A bit of statistical fun 

For anyone who may be daunted by the thought of using systems such as R, the best way to get acquainted is to run some existing code and experiment with it yourself – something made more palatable if it happens to coincide with a subject that interests you. I will thus leave you with an example in the form of code (below) designed to extract data from the Fantasy Premier League database to predict my points score for last weekend’s fixtures. The top panel shows the code and the bottom panel displays the output. For anyone with a team entered in the Fantasy Premier League (and there are more than 6 million people around the world), all you have to do to customise the code by substituting your own team number into line 8 in the top panel (“entryid=…”). For the record I was predicted to score 54 points but in the end I scored a miserable 36. The code worked fine – the problem was that the algorithm which produced my expected points score was an exogenous variable over which I had no control thus highlighting the old computing adage of “garbage in, garbage out.”

Last word 

Whilst Excel is a fantastic tool for many of the day-to-day tasks we undertake, it is limited in what it can do. You can be sure that PHE will not make the same data mistake again. But the point of this post is to demonstrate that there are more appropriate tools for the job they are trying to undertake. You don’t have to be a rocket scientist to figure that out. The appliance of data science will suffice.