What can we learn from previous recessions about the COVID-19 economic crisis?

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By Richard Lewney 
Cambridge Econometrics

Is this time different?

Tolstoy famously began Anna Karenina with the sentence: ‘All happy families are alike; each unhappy family is unhappy in its own way.’ Is that true of periods of economic prosperity and recessions? Is today’s recession so different in character that past experience is irrelevant as a guide to how the present crisis may play out?

Figure 1: UK macroeconomic and sectoral indicators in past recessions

Source: ONS

Recessions have different triggers…

Figure 1 shows the experience of previous recessions. The 1990 recession began with the bursting of the bubble by a sharp policy reversal when the interest rate brake was applied sharply from mid-1988. The first casualties were over-extended borrowers, especially in the property market. The 2008 recession was triggered by a global banking crisis: bank lending and credit markets seized up in the face of the threat of insolvency. GDP fell much more sharply than in 1990, both because the recession was global and because of the credit crunch. The start of the COVID-19 recession has been different again. It is global, but it was not triggered by a banking crisis and nor was there much of a speculative bubble to burst. Instead, production and consumption in activities that require social proximity were shut off by lockdown policies.

… but a similar self-reinforcing pattern

Initially, therefore, the character of the recession reflected the nature of the particular trigger. But past experience shows that once a recession takes hold, some typical reactions produce common consequences. Households experience a fall in wage and dividend incomes and then move quickly to restore their financial wealth, reining in spending sharply.  Economists who assume that households are well-informed and forward-looking emphasise the role of imperfect capital markets in preventing consumption smoothing: some (poor) households lack access to credit.  But it’s not just about imperfect markets: fundamental uncertainty has a critical impact on the decisions of households and banks.

The chart in the top left corner of Figure 1 shows how, in aggregate, households increased their ‘net lending’ during the recession, meaning that collectively they spent (whether on consumer products or housing) less than their income.  While they may run up debts in the very short term, poorer households are unable to access extended credit and richer households act in a precautionary way to rebuild financial wealth.  This shows up in large reductions in spending on discretionary items: housing, holiday travel, appliances, entertainment and private healthcare.  Business also cuts its discretionary spending, chiefly investment.  Together, the result is large reductions in output in the industries that supply investment products, consumer durables and income-elastic consumer services.

We manage uncertainty by deferring spending

In the COVID-19 recession, the lockdown has seen large falls in sales of social consumption items, including some that are not normally particularly income-elastic such as haircuts. But we are also seeing output cuts in sectors linked to discretionary spending, such as cars, which may not bounce back to ‘normal’ as showrooms reopen. Even with substantial government support for incomes, it is likely that households will, collectively, rebuild wealth as typically happens in a recession rather than return spending quickly to pre-recession levels. How many are requesting refunds rather than rebooking holidays?

How productivity will recover

The chart in the bottom left corner of Figure 1 shows the strong cyclical effects on labour productivity in a recession: employers respond with a lag to the fall and then recovery in output growth so that labour productivity slumps and then recovers. The difference in the 2008 recession was that the scale of job shedding was surprisingly modest and, in the recovery, productivity growth resumed the long-term slowdown seen since the mid-1990s. In the COVID-19 recession, we should not be concerned about the heavy cyclical fall in labour productivity: the loss of output during lockdown was unavoidable and the government’s wage subsidy has the goal of limiting job shedding. The question is whether the subsequent recovery in productivity will be achieved by a recovery in consumer and investment spending or by sluggish GDP growth and cuts in job

The Usefulness of Applying Macro-Sector Results to Regional Levels

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By Ben Gardiner
Cambridge Econometrics

Context – the lack of timely economic statistics recording local impacts of Covid-19, and the desire to fill that gap

The spatial economic impact of Covid-19 is still emerging, and will do for some time to come. Early indicators such as the unemployment rate are not perfect due to distortions caused by the government’s furlough scheme uptake and other measurement issues, while in most other cases it is still too early to register local impacts.

This has led to a number of attempts (Centre for Cities[1], Centre for Progressive Policy[2], etc) to ‘localise’ impacts on the basis of macro-sector results or assumptions, by taking sector results (such as those produced by the OBR or a macroeconomic model) at national level and assuming that activities in each region behave the same way, with the same growth rates, and then aggregating the results to give an effective average (top-down) average set of results.

But how useful is this method, or to put it another way, how accurate are top-down assumptions when predicting regional and local outcomes in a recession?

Clearly, we don’t yet even know national-sector outcomes, let along local ones, but what if there were a way to assess how accurate the former were in predicting the latter, with perfect foresight?

Method – learning from the outcomes of the last (Great) recession

There is a way, of sorts. If we look back to the past (the Great Recession) and in particular the period of negative national GDP growth during 2008 and 2009, we know what the outcome was for macro-sector growth of GVA, employment, and productivity, and their sub-national equivalents at all spatial levels.

If we take these macro-sector results and apply them in the same top-down way as others are doing for the current Covid-induced crisis, what do we observe?

What happened during 2008-09 at the national-sector level?

Firstly, the chart below shows output (real GVA) and employment growth over the two-year period, 2008 and 2009. Areas of productivity increase or decrease are also highlighted (where output increases are relatively larger than employment) and the 45-sector disaggregation being used[3] is grouped across broad aggregates. We observe the following:

– A wide spread of sector outcomes, although as it is a recessionary period most sectors are clustered in negative quadrants.

– Of the larger sectors, those within manufacturing were among the hardest hit (four of the largest negative GVA growth rates are all in this activity), while non-market services (and some business services) are among those sectors that managed to maintain positive growth.

– For employment, the outturn broadly followed that of output but not completely (the correlation between the two sets of growth rates is around 0.5). There are some quite major differences, e.g. Pharmaceuticals, Electricity & Gas, and Architecture and Engineering Services, where output and employment moved in opposite directions.

What happens when you apply these results to different spatial levels?

To find this out, we took the same 45-sector structure at three regional aggregations:

(i) NUTS1 (old RDA regions – 11 for Britain)

(ii) NUTS2 (36 British regions, either counties or small groups thereof)

(iii) Local Authority Districts (371 areas in England, Scotland and Wales)

We then applied the above-mentioned growth rates and compared this with what actually happened to output, employment, and productivity. The results are shown in the charts below for the first two indicators.

NUTS1 Regions

NUTS2 Regions


Conclusions – beware of top-down sector-based predictions!

The main findings are that, even with perfect foresight, when applying a top-down approach:

– Given the increasingly similar sectoral structure of places around Britain (due to de-industrialisation and the rise of the service-sector economy) there is not much variation in the projected changes.

– The smaller the spatial level you are disaggregating to (i.e. the more local you get) the more likely it is that specific characteristics and heterogeneity will play an important role in determining outcomes, so the top-down predictions will be less accurate. For example, the tasks and functions undertaken within a sector will also play an important role in which areas do better or worse than the national average[4], as would other characteristics such as the degree of urbanisation[5].

– It is more difficult to predict employment outcomes than it is those for output. Indeed, below NUTS1 level there is really no association between prediction and outcome at all. This implies that local characteristics are dominant in determining employment outcomes than they are for output, as well that the types of job themselves are important determining factors.

– For productivity, whatever the spatial scale, there is no association between actual and projected growth. In other words, using a top-down method to predict what would have happened, even with perfect knowledge of the macro-sector outcomes, would be of no use at all.

We know the coming recession will be different in terms of the speed of its onset, the sectors which are affected (due to the nature of the shock) and the duration. No shock is exactly alike in its cause and effect. And perhaps this time, with wide-spread sectors so badly affected such as tourism, a top-down sectoral approach may be more accurate as, to some extent, everywhere is being affected in similar ways.

However, what we can learn from the past is that this isn’t usually the case. The devil is in the detail, and a place-based approach is really needed to understand the likely reaction, response, and effects that will, eventually, be observed.



[3] Based on Cambridge Econometrics’ local area database, which is itself based on official ONS data.

[4] For example, see other analysis undertaken by Cambridge Econometrics on this topic –

[5] Such investigations are beyond the remit of this blog, but would present an interesting research topic.

Why Cleantech Investment Should be a High Priority Now and after COVID-19

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By Dr Robyn Owen (Middlesex University London) &
Theresia Harrer at the Centre for Enterprise and Economic Development Research (CEEDR) and Centre for Understanding Sustainable Prosperity (CUSP).   

The COVID-19 crisis threatens all of our lives. Understandably, it is currently the central focus of government policy globally. Yet history tells us that post-crisis economic reconstruction is most successful where investment is greatest in new emerging sectors. It is crucial, therefore, that investment in the UK is directed towards globally leading innovations for environmentally sustainable development, rather than simply to become more efficient at producing and selling more of the same.

Prior to the COVID crisis, progression to Net Zero carbon neutral emissions was rising to the top of the policy agenda in many countries. There was a widespread declaration of the climate crisis and climate war and a proliferation of Green New Deals – overarching policies for an integrated government-led approaches to delivering reduction in carbon use and emissions.

We have argued that an essential element of climate change policies is a recognition that investing in early stage SME Cleantech innovators is crucial. These are companies developing technologies that lower carbon use and which are key to reaching the ambitious goals of an at least 40% reduction in greenhouse gas emissions set by the UNFCCC Paris Agreement of 2015. However, the costs and risks of investments in the cleantech sectors such as renewable energy, transport, building and communications infrastructure are high. Government interventions have been necessary to attract a greater quantum of private investment more rapidly into the sector through inducements such as co-investments, niche loans, grants, tax incentives and green tariff payments.

However, a great deal of this government intervention has been directed at headline large infrastructural schemes such as UK Green Investment Bank investments into Wind Farms and Global Climate Partnership Fund renewable energy projects. An examination of the UK Green Finance Strategy  (2019) underpins this work with commitments to spending billions on further, very necessary, infrastructural works to create low carbon environmental efficiency.

It is a concern, however, that relatively little attention has been given to creating an effective financing system to support the role of the innovative Cleantech SMEs. In fact, it is barely mentioned in the UK Green Finance Strategy. This is worrying, since these companies are acknowledged as one of the key leaders in delivering the global low carbon solutions that can win the war on climate change.

A caveat here is the aforementioned high cost and risk of investments in the Cleantech sector which is most acute in terms of the poor risk reward balance during the so-called ‘valley of death’ period of R&D and early commercialisation, where funding so frequently runs out. The notorious 2016 MIT study of US cleantech failure during the Global Financial Crisis period suggested that venture capital (VC) alone is not the solution, whilst more recent studies suggest an improving Cleantech investment market, prior to COVID. Here it is important to recognise that Cleantech investment is not just about quick win returns from digital technologies (such as smart metres and software Apps), but the willingness to finance sufficiently for the long horizon engineering and bio-science, more capital intensive Cleantech innovations.

The familiar danger signs of another post economic crisis collapse of VC investment are here. This could put back the fight to tackle climate change, since we are now very aware that economic recessions reduce investment liquidity and increase the timelines on successful innovation investment exits by several years.

Now, at this time of deep crisis, we must not lose focus on the fundamental need for a better funded systematic government-led Green Deal approach to early stage Cleantech funding. Such an approach requires government financial intervention policy and targeted programmes to support and encourage environmental impact investing and to ensure that the right types of Cleantechs are properly assisted and fully funded for success, rather than the current disjointed and under-funded efforts which in the UK have led to a culture of funding for failure and sub-optimal trade sale exits – often to foreign investors.

So, even in this crisis period, it is vital for the UK government not to lose sight of the bigger, longer term picture, and the need to improve early stage Cleantech SME innovation finance and support to tackle climate change.

A current study for the ESRC funded UK Productivity Insights Network (PIN) by Middlesex University, Centre for Understanding Sustainable Prosperity (CUSP) researchers, alongside partners from SQW, St John’s Innovation Centre and the UK Green Angel Syndicate is exploring the relationship between early stage Cleantech investing in the UK and its potential environmental sustainability impacts. The aim is to radically disrupt current thinking about the role of innovation in economic productivity measures and demonstrate the crucial importance of early stage impact investing into Cleantech innovation. Early findings demonstrate a paucity of useful data, due to the lack of standard industrial classification sector matching for Cleantech activities. They further demonstrate that, despite years of advice, the development of an effective, efficient UK Cleantech investment funding escalator -which progresses early innovation Cleantechs through for example grants for early proof of concept to significant Series A+ VC rounds and to successful commercialisation – is far from in place.

We welcome feedback and collaboration with our research team from Cleantech investors, SMEs, support services and policymakers. Together we can improve the system and put the UK at the forefront of the globally important Cleantech sector, which can be a key driver for future economic and environmental well-being.

For further information on the Middlesex University PIN project please contact Dr Robyn Owen, or Theresia Harrer at the Centre for Enterprise and Economic Development Research (CEEDR) and Centre for Understanding Sustainable Prosperity (CUSP).

Does productivity still matter?

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By Vania Sena (University of Sheffield)

As we start the seventh week of lockdown, it is probably a good time to take stock of the impact of the COVID-19 outbreak on the economy. So, what has happened so far? The outbreak has generated a contraction of the aggregate demand worldwide which according to almost all commentators will be even larger than the one experienced during the 2008-2009 financial crisis. Initial estimates from the OBR suggest that, in the UK social distancing measures may result in up to 35 percent drop in economic activity during the second quarter and a yearly contraction of anything between 7% and 15%, depending on the speed of recovery. Revenues have disappeared from one day to the other in a number of industries and reserves have been dried up to pay salaries, many of which are being covered by government schemes.

Unsurprisingly, the priority for the government has been to stabilize the economy where possible. However, the question more people are now asking is: what are the implications of COVID-19 for the long-term growth prospects of the economy? The UK economy will need to grow at a rate that allows it to address the challenges associated with the management of large government debt while improving the performance of the labour market. This would require a strong recovery in productivity growth to a level that predates the 2008 financial crisis. In addition, the characteristics of COVID-19 (i.e. the fact that the current outbreak is not a one-off but several outbreaks are expected for the next eighteen months) implies that building up the foundations for strong productivity growth is intertwined with building up resilience in the economy. In other words, building up resilience in the economic system has to become one of long-term objectives of economic policy along with strong productivity growth.

But what is resilience exactly? According to the definition from a dictionary, resilience refers to the ability of individuals or organizations to recover quickly from shocks. However, in the context of COVID-19, it has become clear there is no consensus on what resilience implies in practice. We all agree that public services need to build up excess capacity to be able to cope with future outbreaks; at the same time, it has been argued that excess capacity will be artificially generating inefficiencies that may eventually hamper productivity growth. Is this really the case?

Let us start from the fact that productivity may grow because of technological progress and of changes in efficiency; in turn these can be spurred by changes in the scale and scope of operations as well as variations in the usage of inputs. Importantly, organizations do not need to experience all of them to be able to increase their efficiency: for instance, for a given level of inputs’ usage, efficiency can be improved by changing the scale of the operations or its operations. In other words, developing excess capacity to be able to cope with future outbreaks implies rethinking the size and scope of the organizations. Increases in the scale of operations in such a way that organizations may find themselves exploiting increasing returns to scale may be helpful to increase efficiency while smart diversification or consolidation of activities increases the conditions to exploit economies of scope which can translate into efficiency gains, for a given level of capacity (whether in excess or not). So, large organizations with excess capacity can be better positioned to generate the productivity growth that the economy needs as well as to cope with the costs associated to excess capacity.

What are the implications of all this for economic policy? On the one hand, we will see an increase in concentration in some industries as large and productive firms will end up dominating a number of industries (where economies of scale and scope will permit it). Clearly, there is scope for regulators to monitor the process to ensure that building up resilience does not translate into inefficient outcomes for consumers and suppliers. On the other hand, there is a need to develop a fresh approach to business support. Clearly a model where large and productive firms are surrounded by micro firms (whether suppliers or competitors) which cannot cope with major shocks is not sustainable in an economy where resilience is a key objective. In this case, the sustainable scaling up of micro firms is the policy priority: all the standard tools of industrial policies (from finance to business support programmes) need to be geared towards companies that have the potential for scaling up and thrive so that industries can be dominated by a mix of firms which can be productive and resilient at the same time.

The bottom line is that productivity growth as a policy goal still matters but more importantly, aiming for productivity is not at odds with creating a resilient economy which can cope with major economic shocks.

Small Business in the Time of Covid-19

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By Andrew Henley (Cardiff University) and Tim Vorley (University of Sheffield)

Across the world, as the Covid-19 pandemic is raging, the disruptive impact on small businesses has been without precedent. Immediate commentary documenting both scale and specific examples of this impact is not in short supply. This blog post offers some preliminary thoughts and reflections on performance and productivity for small businesses. While it is too soon to provide any hard assessment of the impact of the current crisis on business performance, so our purpose here is comment on some emerging themes based on current knowledge and ongoing responsive research.

The economic impacts of the crisis are likely to be multidimensional. These include differences between short-term and medium-to-long term impacts, variations across different sectors, the differential spatial impacts of the crisis. At the same time the resilience of small businesses and their ability to survive the crisis has demanded business models be redesigned. Many of the issues that small businesses face and their capacity to respond are determined by their response at the onset of the crisis – and so the immediate decisions of owner managers will have longer term implications.

In the short-term it is inevitable that productivity will take a further significant hit – a conclusion that is particularly unwelcome given the ever-widening UK productivity gap. This is because in a recession businesses generally attempt to retain employees with skills, especially if those skills are scarce or central to the firm. Employee absence due to illness or quarantining is hitting many SMEs, especially small and micro-businesses, very hard, since business-critical skills coverage is not “de-risked” across a large employee pool.

Labour hoarding sees the productivity numerator (turnover or value-added) fall more quickly than the denominator (labour input). If firms have flexibility to reduce hours, then the adverse impact on productivity per hour worked may be less severe than on productivity per employee. Recent emergency policy announcements on wage subsidies under the job retention scheme are specifically designed to maintain employee attachment and therefore indirectly to lower productivity.

These initiatives are likely to be more crucial to business survival for less well-capitalised, and less profitable SMEs, and speedy policy implementation here is of the essence. Survey data collected in mid-March 2020 by the University of Sheffield with Small Business Britain bears this out – almost three quarters of SMEs surveyed expected revenues to fall by over half.[1] One emerging recommendation relates to the urgency of making relief available: roll the policy out and worry about deadweight losses later, which might be partially recoverable through business and self-assessment tax systems.

Early research indicates that since the Government announced the measures available that there is considerable local variation in the administration and access to support. These difficulties are compounded by the eligibility, or perceived eligibility, meaning that not all micro businesses will benefit as intended and as entitled. This reflects another major perennial challenge for small businesses policy, which is encouraging the take-up of government programmes, as 82% of firms surveyed have not previously sought business support.

Some firms simply won’t survive. In the medium-longer-term, if the crisis persists beyond two quarters into late summer and autumn, the least resilient SMEs will shut down, that is those least well capitalised or those seeing the biggest falls in revenue. As recovery returns this shake out process could then see a productivity bounce, although this will have been at a very high price in terms of firm failures.

In the UK the most immediate distress has been seen amongst those businesses which provide non-essential face-to-face physical service delivery in leisure, hospitality, transport services and non-food retailing. In advance of the shutdown and lockdown, these sectors had already been earmarked for support by the Chancellor in the Budget on 15th March 2020. As well as these sectors, places such as historic city centres and coastal resort towns have been hit hard, as the demand shock of ‘social distancing’ is seeing some consumers deferring discretionary spending on non-essential items. The societal importance of supporting these firms is important for safeguarding the efforts and livelihoods of small businesses through this crisis, and will help ensure the future vitality of these hard hit places.

However, despite the early and enhanced support for these sectors many are in the so-called ‘long tail’[2], and while making an important contribution to localities are unlikely to be the engines of recovery and future growth. Naturally, there are some firms are adapting to new realities by shifting their business models with and without the help of government support. The study highlighted that as well as those businesses already working online, many of whom have been less affected, many other owner managers have sought to take their businesses online. The shift from bricks to clicks presents an opportunity for productivity gains as revenue streams shift on-line, with online sales are twice as productive as offline[3] .

Even a cursory glance at the business pages of the news media reveals some significant changes to working practices and business models. At this stage, however, it is unclear to what extent these changes to working practices and business models represent temporary ‘work-arounds’ or whether they are genuinely new-to-business innovation. Where effective these reforms have the potential to promote future resilience and enhance productivity, especially if they result in significant and permanent reductions in cost associated with activities such as business travel etc.

At the other end of the spectrum knowledge based and services businesses, for example software development, are likely to be more resilient and may even see some productivity gains from costs savings associated with remote working and the of closing physical office space. What is as yet unknown is the extent to which SMEs are at risk from collapse in the supply chains in which they sit, especially in sectors such as manufacturing , construction or business-to-business service provision. This potentially threatens the so-called ‘tradeable’ as well as ‘non-tradable’ businesses.

Recent analysis by Brookings highlights the likely differential spatial impact of the crisis, arising from the uneven spatial distribution of SMEs by sector.[4] In the UK the South West, in particular, is exposed to distress in the accommodation, food and drinks sectors, accounting for almost 10% of private sector employment, although this sector is also relatively larger in London. Retailing is another low productivity sector that also accounts for a large employment share in the North and in Wales compared to the Midlands and London. On the other hand knowledge based and services businesses, which might be more resilient to disruption, account for less than 3% of private sector employment in the North East, North West, Yorkshire and Humber, East and West Midlands and Wales, but nearly 8% in London.[5]

So, to conclude, the short-term damage to productivity looks likely to be significant, and in the context of the UK’s persistent and widening productivity gap this is highly unwelcome. However, where micro businesses have the ability to transform and adapt there is the potential for enhance resilience and productivity gains over the longer term where they are able to implement permanent changes to ways of doing business.

One Way Ticket?

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By Iain Docherty (Dean of the Institute for Advanced Studies at the University of Stirling)
and Tom Forth (Head of Data at the Open Data Institute Leeds, and led the PIN project on Real City Size.

“In all affairs it’s a healthy thing now and then to hang a question mark on the things you have long taken for granted.”
― Bertrand Russell

We have become used to astounding numbers in the economic news due to the COVID-19 pandemic. A 35% fall in quarterly GDP, an increase in public sector net borrowing of 14% of GDP in a single year, the potential trebling of unemployment. But perhaps the most astonishing figure concerns the use of public transport. The number of people in the UK travelling by rail and tube is down by 97%. Declines in bus use are likely to be similar.

As government begins turning policy attention towards an ‘exit strategy’ from the current severe restrictions on economic and social life, transport will present one of the most difficult challenges. Whatever decisions are taken will have impacts everywhere, though particularly in our towns and cities.

Our response to the pandemic has shown how quickly society can make extreme changes when it needs to. It is a lesson worth learning. 5 years ago, a group of us were wrapping up a large project on transport disruption. Our headline finding was that by observing how people changed their behaviours in response to disruptions such as flooding or the sudden closure of a bridge, we could estimate the potential for radical change at other times. We hoped that governments would use this insight to make transport more resilient, more sustainable, and less carbon intensive even in the absence of disruption. Today we have more extreme disruption than we ever considered.

There have been some important quick wins for more sustainable transport during lockdown. Cities from Berlin to Bogotà have quickly reallocated road space, giving greater priority to pedestrians and cyclists. Reluctance to conduct virtual meetings has been overcome, leading to an exponential increase in the use of video conferencing software as organisations try to maintain their productivity despite the elimination of the majority of travel.

It is far from certain that longer term trends will be as positive. Business travel, and with it emissions, might bounce back as people tire of Zoom. The novelty of working from home will wear off for many who are missing the social contact of the workplace. The 97% fall in the use of public transport will not endure, but what part of it will?

Given the protracted and potentially stop-start exit from lockdown that faces us over the coming months, how many will feel safe using buses and trains again? Will sensible precautions such as requiring passengers to wear face masks scare people off public transport, or help them feel safe to return? Will journeys not taken by public transport be replaced by journeys by car or bicycle, on foot, or not taken at all? What will happen to demand for ride sharing services?

Such significant changes in the future of travel demand are important for two main reasons. First, because decarbonising transport at the rate required to meet the Paris Agreement on climate change necessitates not only adopting zero-emission vehicle technologies universally over the next decade or so, but also reducing the overall size of the vehicle fleet by around one third. A greater adoption of home working would help to achieve this goal. Any lasting shift away from public transport to increased car use would do the opposite, probably by much more.

Second, many of our assumptions about the productivity benefits of transport investments depend on people choosing to live, work, and socialise at high densities in city centres, enabled by mass transit. If fewer people choose to live in this way then the economic case for many large infrastructure investments will crumble. The use of appraisal techniques that claim to assume how society and the economy will work up to 60 years into the future will come under renewed scrutiny.

For all the difficulties that the transport sector will have in adapting to a post COVID-19 world, it has a significant advantage. We have been here before.

In the 1950s, the ‘dispersal’ of American cities into much more expansive, less dense forms was seen as a defence strategy against potential Soviet nuclear attack. Following 9/11, there was renewed debate in the US about whether a form of ‘anti-urbanism’ would take hold in which people were more hostile to the very idea of congregating in huge numbers in the largest cities.

The UK has avoided this level of drama in its debate about the future of cities and their role in socio-economic organisation. But we also have precedents to learn from. For example the July 2005 terror attacks in London prompted an instant decline in demand for tube travel of almost a third. This effect proved short lived with growth recovering to trend within months, although the important increase in cycling seen at the same time lasted.

We don’t know what the long-term effect of the COVID-19 pandemic on transport will be. It is possible that it will be a single discontinuity in longer term trends, similar to the disruption caused by terror attacks. But it could be a once-in-a-century rupture of those trends similar to the mass adoption of the motor car. Such a disruption would be so large that our assumptions about where, how and when we travel changes completely. The impact on the infrastructure we would need to build and maintain would be huge and only part of the wider implications for how we go about urban planning and economic development more generally.

Lessons from the past: how might productivity policy learn from the policy changes of the past 20 years

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By Jonathan Cook

There have been a significant number of changes to policies and programmes over the last 20+ years. But how far have these changes been material and what might we learn for the future of productivity policy, including in the context of the coronavirus pandemic?

Our chapter in the recently-published book, Productivity Perspectives, reviewed the changes in aspects of productivity policy from 1997 to 2018, a period which included the global financial crisis. This traced the overarching narrative associated with productivity policy, and focussed in on policies relating to innovation, business support, skills and regional development.

Our review identified significant change in programmes and policies, which often related to nomenclature or changes in targeting. We found that, whilst programmes and policies may seem to be new, they have historically not been much more than repackaging of old initiatives with some changes in the emphasis of branding.

Another aspect that we identified was the institutional churn over the period, and this coincided with changes in programmes. For example, consecutive waves of institutional reforms brought about regionalisation of programmes in the 2000s, a subsequent centralisation after 2010, and then (as we have recently experienced) a shift towards localism. As well as changes in the regional and local institutions, including the coming and going of Regional Development Agencies, we have seen significant adjustments to the skills landscape with a plethora of new and then disbanded or rebadged agencies.

But isn’t change good? Shouldn’t policy experiment and adapt? Yes, but experimenting and adapting are different from much of the change that we have witnessed. They are, or should be, about trying things, learning from them, keeping what works and amending things that don’t work. It does not necessarily require constant reinvention and institutional reform, and arguably such change works against the principles that are required for testing and learning. Churn is not good for maintaining institutional memory, nor for having a long-term perspective, which is important for many of the challenges we face such as productivity, and, in the coming months and years, supporting an economic recovery due to the coronavirus pandemic.

Our chapter did, nevertheless, identify some positive examples where there has been developmental change. One of these areas is the role of innovation programmes in stimulating solutions to market or societal challenges. Indeed, the current Industrial Strategy Challenge Fund programmes in part reflect the way in which innovation support has evolved since the 2008 Innovation Nation White Paper.

Productivity cuts across many issues and requires a policy approach that works across silos, and flexibility to take advantage of the intersections. In this way, it is a complex issue. Productivity Perspectives includes a chapter by Tim Vorley and Jen Nelles that discusses the role of a systems approach to conceptualising, designing and implementing productivity policy. As they argue, productivity policy has too often been developed as a collection of policies intended to stimulate productivity improvements: some policies on skills, others on innovation and technology development, yet others on infrastructure etc. However, these are all interdependent, and so the intersections need to be considered, understood (as far as possible) and policy developed in a way that can maximise potential synergies.

Therefore, in the coming months as the UK hopefully starts to turn its attention to industrial policy to support economic recovery, it needs to create the right environment for an adaptive policy response. This requires consistency, which means avoiding the constant churn and chopping and changing of programmes and institutions. It also needs to encourage comprehensiveness to integrate thinking across policy domains. Four key features to this are as follows:

• Patience and flexibility: policy makers and funders should manage their expectations in relation to short-term results. Addressing complex challenges often requires time to understand the issues, develop appropriate initial actions, and then test, learn and amend them. A failure of policy is to abolish something just as we have learned from its initial mistakes and developed it into a working solution.

• Longer-term funding: commitments of funding for longer periods of time give opportunities to consider actions with longer-term benefits (as opposed to looking just for the quick wins), and to adapt actions in response to early learning. Funding should also be sufficiently flexible to be used in ways that can cut across traditional policy domains.

• Appraisal and evaluation that is appropriate for systems change: by the very nature of complex challenges and systems approaches, complete and very clear assessments of the benefits are more challenging than for simple interventions. Therefore, it is important that appraisal and evaluation approaches, and the demands placed upon them, are appropriate.

• Appropriate decision-making and governance: structures should be in place that can help mitigate against the risk of the short-term decisions that can occur, for instance due to the length of policy and political cycles. Balanced representation of different stakeholder interests, and the role of independent bodies, can assist with this.

How will COVID-19 affect productivity in the UK?

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Featured Image: by Fusion Medical Animation on Unsplash

by Richard Harris,
Durham University Business School

The impact of the current world pandemic looks set to have an unprecedented impact on the world economy. The secretary-general of the OECD stated on the 23 March that a global recession looks “increasingly likely” in the first half of this year, “and we must act now to avoid a protracted recession”. According to IMF chief Kristalina Georgieva, the global economy contracted by 0.6% in 2009 as a result of the 2008 global financial crisis, but major emerging markets like China and India at the time were growing at a rapid rate; in contrast, some forecasters believe that the current the downturn could be 1.5%. Following restrictions on the opening of pubs, bars and restaurants (3 days ahead of the now even wider restrictions on movement announced on the 23 March), it was being predicted by the Unite union in that up to a third of the UK’s 3.2 million hospitality jobs are under threat.

What is likely to be the impact on productivity in the UK? Obviously, it is too early to make any definite or accurate predictions, so here the intention is to look to the 2008-09 recession as a possible benchmark for what is about to unfold. Chart 1 (see begins with putting the 2008-09 Great Recession into historical perspective. It shows the growth of GDP per capita each quarter relative to the start of each major recession in the last one hundred years. While, the 1920-21 recession was deeper in the first year (noting that this took place in the immediate period after the post-WW1 flu pandemic of 1918-20 which killed between 20-40 million worldwide), the UK economy recovered to its pre-recession level after around 4½ years (18 quarters). However Chart 1 shows the 2008-09 recession impacted for over 7½ years (30 quarters). Given the comments of the OECD and IMF, this suggests the UK is facing perhaps a decade or longer to make-up ground on what is likely to unfold in the next few months.

Chart 2 uses a slightly different ONS dataset (see ONS 2020a, 2020b) to show the impact of the 2008-09 financial crisis. Labour productivity was growing at around an average of 1.96% p.a. during 1990-2007, and following the recessionary dip the trend has been closer to 0.5% p.a. on average. Thus, Chart 2 shows the extrapolation of what would have happened to productivity if the 1990-2007 trend had continued; by the end of 2019 a gap of around 17 percentage points had emerged in what might be considered ‘lost’ productivity in the UK economy.

Chart 2 also shows the two series that make up labour productivity (output per worker); the drop in productivity post 2007 was mainly due to a fall in the production of goods and services (as is typical of all recessions), accompanied by a much smaller fall in employment. Thus, what was different about the 2008-09 recession was the ‘hoarding’ of jobs relative to previous recessions, such that it has taken productivity much longer to recover to pre-2008 levels.

Chart 3 makes this clearer by taking just the recessionary period shown in Chart 2. Here can be seen the shallow dip in employment and its levelling off before a slow growth back to pre-recessionary levels, while output fell by significantly more and only returned to its pre-recessionary level in 2013 Q1. Consequently, productivity only fully recovered to pre-2008 levels by 2012 Q3, i.e., 4½ years (18 quarters) later.

Chart 4 shows this same recessionary period in terms of growth rates (Chart 3 is in levels); it is comparable to Chart 1. It re-emphasises that losses in productivity were mostly caused by output falls not compensated by cuts in employment. As stated above, this was somewhat unusual in that most recessions see the immediate fall in output later matched by employment falls, with the latter typically then having a greater ‘depth’ and lasting longer.  Indeed, many firms use recessions to ‘cleanse’ inefficiencies and introduce new (often labour-saving) technologies. In short, recessions typically impact in the short-run by reducing labour productivity, but in the long-run introduce structural changes that increase economic resilience. This did not happen post 2008-09.

Will the current crisis be like the 2008-09 recession or more typically follow earlier patterns where productivity levels recovered much faster (and usually to pre-recession trends)? Given that the immediate response of government has been (understandable) supply-side measures to try to protect jobs (through employment subsidies), and given the dramatic fall in demand for certain service sector industries (such as the distribution, transport, and accommodation & food sectors), it seems very likely that employment levels are likely to receive greater ‘protection’ than the production of goods and services, and the trends seen in Charts 1-4 are more likely to be repeated in productivity terms (albeit with greater negative consequences).

Indeed, Chart 5 shows what happened to productivity in the production (with construction) vis-à-vis service sectors, while Chart 6 shows separately the results for 5 sectors that were particularly ‘hard hit’ by the 2008-09 recession. The production sector took a larger hit earlier on, but recovered faster, while it took services much longer to return to pre-2008 levels. Chart 6 shows that in especially the arts & entertainment sector and transportation services, there was still an important gap over 5 years after the start of the recession (together with the fall in productivity having been much more severe in these sectors). Charts 7 and 8 show that most of the change in productivity was the result of output changes (while jobs were largely maintained at pre-recession levels, or saw only relatively small declines which recovered more quickly – that is, similar to the pattern shown in Charts 3 and 4 for the whole economy). And output only recovered to 2008 Q1 levels in 2013 Q3 for distribution (i.e., 5 years later), while it took until 2014 Q3, 2015 Q1 and 2019 Q1 for arts & entertainment, accommodation & food, and transportation services, respectively (an average of nearly 9 years for these sectors as a sub-group).


The impact on the world economy of the current world pandemic is predicted to be severe, perhaps 2 – 3 times more severe than in 2008-09. Using the 2008-09 recession as a guide of what might happen, where labour productivity moved to a new, much lower growth trajectory, and took a much longer time to recover to pre-recession levels compared to recessions that took place in the 20th century, it seems likely that the UK will follow the same pattern as post-2007 but with deeper ‘cuts’ in productivity and a longer recovery time to follow. In part this is because the government (for clear and obvious reasons) is seeking to protect employment levels, which is the main feature of what happened to productivity following the financial crisis in 2008-09. Sectors like construction, distribution,  accommodation & food, transportation services, and arts & entertainment are likely to face the brunt of what is about to impact on the UK (and world) economy.


The return of the Fourth Horseman: How the current pandemic might re-shape our world

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Featured Image as per the original post on

by Dr Ekkehard Ernst
Chief Macroeconomic Policy Unit, International Labour Organisation, Geneva

Dr Ekkehard Ernst provides a thought-provoking blog on the transformative force of the COVID-19 outbreak and how the current events might affect our economic system in the longer term.

Read the full blog post here: