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Some baseline considerations in the design of a Universities-coordinated West Yorkshire Economic Recovery Plan

By Andrew Brown and Gary Dymski [1],
Economics Division, Leeds University Business School, University of Leeds 

For the second time in 13 years, the United Kingdom has experienced a ‘black swan’ (or tail-risk) event that has ruptured economic relations and threatened the collapse of the cash-flows and asset values on which the reproduction of everyday capitalism depends. [2] The 2007-08 financial crisis has been followed by the 2020 Coronavirus pandemic. The latter has both resulted in significant loss of life and necessitated an extended lockdown that fully halted most aspects of both aggregate supply and demand to a halt for an extended period.

A challenge has been presented to the University of Leeds and other universities in West Yorkshire: to develop a plan for the post-lockdown economic recovery in West Yorkshire. Growth strategies are routinely developed by units of government, often relying on advice provided by professional-service firms (consultancies) optimized for this purpose. So what value can a university add? Government plans reflect political judgements and values (‘inclusive growth’, for example), while consultancies specialize in producing, at speed, analysis of the latest empirical measures of the drivers of economic activity. Universities’ core consists of their academic faculties, whose members’ research plugs into reservoirs of accumulated and emerging knowledge across academic disciplines.

These faculty members’ value added is their capacity to combine core theoretical insights and available evidence – quantitative, institutional, and historical – into proposals for new concepts, processes, products, programs, or institutions. This is their unique value in policy deliberations – the capacity to show how policy choices can break new ground. Yet, at the same time, academics’ ideas about policy can often derided as ‘blue sky’.

Avoiding the perception of academic research is always to be dismissed as ‘blue sky’ and unusable depends on both sides to the policy discussion – both the engaged academics and the public policy-makers – being tolerant and flexible in communicating with one another. These qualities are always important in good policy-relevant work, but the unique ‘multi-dimensional’ circumstances of the current scenario make them especially crucial in these exchanges. The multiple dimensions in question involve both time and space. We elaborate these before proceeding.

A ‘black swan’ strategic response in a country with a multi-level governance structure  

An economic strategy to achieve a given goal in any regional or national socio-economy must bring together three distinct components: the substantive issues to be addressed; the policy structures in place that can implement whatever actions are decided upon (and which determine which actions can and cannot be taken); and the relationships between those charged with policy implementation, those charged with  initiating or expanding economic activity (employment and business creation), and the communities of academic and policy experts available to provide guidance.

Assembling a useful West Yorkshire economic recovery plan must then involve these three components. But there are several special features about the challenge involved that require special attention. First, the pandemic has occurred at a global scale; it is not just a local problem or deficit requiring attention. As such, the lockdown required by the pandemic has shocked, and even halted, the global economy.

This leads to the second unique feature: the grinding halt of economic activity – and the quickly mounting costs of subsidizing workers’ incomes and firms’ lifeline expenses – has pushed forward the priority of restoring normality. The usual goal-seeking aspect of economic strategies – ‘inclusive growth’ or ‘sustainability’ – is replaced now by the need to ‘build back better’.

This gives us the third feature: huge expenditures of government financing have been needed to avoid collapse to this point, and much more will be needed. Normally, financing at this scale would be associated with grand investment plans for new industries or new housing estates, etc.

However, lurking behind both of these unique features is that the Yorkshire region – indeed, the UK, and the world as a whole – had already fixed on the need to prioritize new investments to meet two global challenges – stopping climate change and meeting the sustainable development goals (SDGs). In the G20’s June 2018 ‘blended finance’ plan for SDGs, national governments would finance the measures needed to attain these targets, with underwriting provided by multi-lateral development banks and the World Bank. The Covid-19 crisis has laid waste to that plan, as national governments around the globe have had to use whatever policy space they can find to sustain their residents in safety.  So does this mean that SDGs and climate change are off the agenda? Not if the issue of recovery can be melded together with these longer-term priorities.

This leads to the next defining feature for this strategic problem. What it means to ‘address’ the issues at hand is itself problematic: policy solutions can range from ‘fixes’ to permanent shifts toward sustainable ‘steady-states’.[3] A ‘fix’ only restores a baseline that was already inadequate from an SDG and climate-change perspective. The material issues behind the Black Lives Matter movement have highlighted that the concentration of BAME residents in certain neighborhoods has led to systematic violations of some of the SDG categories, along racial and ethnic lines. To finance recovery with money that was never intended for ‘staying in place’ purposes will only feed populist anger and resentment, on all sides.

And this leads in turn to the next unique aspect that has to be baked into a recovery strategy: while appropriate and accessible solutions to the ‘black swan’ coronavirus event have proven elusive to date, the same can be said for SDG and climate-change targets. The problem of assuring adequate nutrition for all residents of the UK is not solved; nor is the problem of providing adequate and safe housing for all in the UK has not be solved; nor of access to education and health for all; and so on. And on top of these unknown paths lie the barely explored routes to climate sustainability. We have no maps for how to journey along these pathways. So it means that possibly deep disagreements will occur about what roads to follow, and why. Even the experts are guessing. It must not be forgotten for those engaging in this exercise that policy solutions at scale are expected, even demanded, by political leadership, not successful partial demonstrations. The experts relied on to think about the issues involved have to take this on board and be tolerant and flexible in their mutual discussions.

The sixth defining feature of the Covid-19 regional recovery challenge is that it will unfold in a multi-level fiscal structure, in which only a few of the controls over the resources needed to establish local policy are accessible to sub-national policy-makers. Coordination amongst the various levels of public expenditures and revenues is crucial. But the rules and fiscal purse-strings for governance have been held centrally in the UK since time immemorial. The ‘devolution’ effort to localize structures of governance and public accountability has been unfolding at an uncertain pace for nearly a decade, but is very far from complete.

And this brings us to the final defining feature: the UK government has, since 2009, been committed to austerity fiscal (macroeconomic) policy. So the NHS, social welfare expenditures, school spending, and so on, have been at levels that have left many residents and regions in personal or economic deficit. This has been picked up in reports done by the UK2070 Commission, the Commission on a Gender Equal Economy, and the Runnymede and Joseph Roundtree Foundations. The fact that fiscal rules have been suspended in the immediate wake of the Covid-19 lockdown does not mean that austerity is behind us: to the contrary, many political front-benchers have been insisting that fiscal discipline must be restored as soon as lockdown ends. But since the levels of human need and economic hardship have increased dramatically since March, a return to normal levels of fiscal commitment will lead to further unanticipated human deprivation.

What not to do: the pandemic and the US’s multi-level structure of governance

In the spirit of Monty Python’s ‘how not to be seen’ sketch, it might be useful to consider how the policy response has gone wrong in another country with a multi-level structure of governance. The country in question is, of course, the United States. While newspaper accounts set out the specifics of the policy car-crash unfolding there in real-time detail, author Michael Lewis already identified the problem in a book based on his research in the year after the current US President took office.

In The Fifth Risk, Lewis describes the collision between the immensely complicated federal departments of the US government – focusing on the Department of Energy, which manages all aspects of nuclear strategy and supports or houses much of the US ‘Big Science’ establishment – and the incoming Trump Administration. As Lewis tells the story, the Trump Administration’s appointees are few and far between, and those put in place have typically been ideologues uninterested in the substantive issues handled on an ongoing basis by federal agencies. His ‘fifth risk’ is ‘project management’ – by which he means the oversight and guidance of longer-term programs such as nuclear-waste management, pandemic prevention and response, wildfire control, and so on.

The outstanding example of a policy failure due to this widespread indifference is the Coronavirus pandemic. The Trump Administration did not name a director for the Centers for Disease Control for months after the February 2017 inauguration, did not name replacements for the many appointees whose term of office concluded with the departure of the Obama Administration, and so on. Subsequently, the CDC has had its budget slashed and is now being blamed (among others) for the severity and duration of the crisis. President Trump has made it clear that the federal government no longer is responsible for further responses for testing and control of this pandemic in the US: it is now the responsibility of the 50 governors of the individual states of the Union.

Bottom-up, top-down, and ‘levelling up’? The UK’s unsolved multi-level governance challenge

The challenge of multi-level governance is evident in this US case study. The problems there involve unresolved questions over the structure of government: how resources (even medical equipment) are to be shared out between the federal government and the states; the ability of local authorities to refuse participation in national programs (notably, at the moment, the Affordable Care Act passed into law during the Obama Administration); the expanding power of the Executive Branch in decreeing national policy without recourse to Congressional law-making processes. The chaotic policy response to Covid-19 in the US has led to more and more finger-pointing, and most recently to protests and violence on a scale not seen since the 1960s.

The political relationships of national government with local authorities, and of political parties to political power, is quite different in the UK than in the US. Nonetheless, when the Covid-19 lockdown hit, the country had many unresolved issues involving core political economic issues: the locus of public budget control, the country’s surplus-transfer mechanisms (from wealthier to poorer regions and districts), the relationship of the nation to its trading partners in Europe and in the rest of the world, and the future of immigration and of migrant workers, to name several. These unresolved issues were already heading for a collision. The adverse GDP shock anticipated from Brexit was already on course to capsize or stall the completion of plans for the ‘devolution’ of governmental policy controls before the lockdown. Plans to reduce the public footprint of nation-defining institutions such as the NHS and BBC have been pulled back in the emergency; but no political declarations of restorative public support beyond the lockdown have been made.

This uncertainty, worsened in the past four years by Brexit, has undercut investment generally, and flatlined UK productivity. Infrastructural and green-economy investments would be ‘smart responses’ to the Covid crisis; but these must work together with restoring the resilience and financial ‘health’ of both household and business sectors across the country. This has not been done.

Instead, the Covid-19 crisis has exposed many ‘holes’ in the planning, accountability, and delivery architectures in the UK, as it has in the US. Multi-level governmental structures, such as that of the UK and US, can carry on in normal times without the pressure points or unresolved linkages in those structures coming to light. In the UK, local authorities’ staff capacity and resources for analyzing, planning, and implementing socio-economic policies on behalf of their regions have been squeezed by years of macro austerity policy.

As long as promised human services have been provided to a minimal standard, and as long as educational, employment, and entrepreneurial processes have produced cash-flows sufficient for social reproduction (‘provisioning’), the ‘holes’ that this has left in local authorities’ capacity has been relatively invisible. The gap has been made up, in part, by fee-for-services offered to these authorities by consultancies. This is where a key difference emerges between the US and UK multi-level governance structures. The 50 states of the United States, together with local units of government (counties, cities, districts, others), account for approximately 50% of all revenues collected annually in the United States. Most public services are provided with intermixed state and federal funding. Some states with higher income levels – including California, Washington, New York, and Massachusetts – have adopted relatively high, progressive state income taxes so as to securely fund those services. And these are states that typically transfer a portion of their net taxes collected to lower-income states.

Scale-appropriate, flexible ‘blue sky’ thinking: how universities can help local authorities

Of course, the local authorities in the UK have nothing like this sort of fiscal autonomy. And the UK lacks the scale and resources to permit the emergence of adversarial politics as bitter and unresolvable as those that have gripped the US at least since the 1980s – if not since the 1964 passage of the Civil Rights Act. Severe societal crises require responses at scale and at speed by those responsible for societal governance. Multi-level structures of governance must, to avoid political ruptures, transmit policy responses and resources smoothly from central to local levels. There is a desperate need in the UK in the current moment of pandemic-driven crisis for policies that respond to local needs.

This is likely to require structural governance reforms. It is likely that UK economic policy approach must make a clearer distinction between meeting human and social needs (indeed, the SDG goals), on one hand, and encouraging innovation, inclusive growth, and competitiveness, on the other. This will likely require a real rebalancing of fiscal policy responsibilities and revenues between national and local levels, along with a clearer delineation of the rules under which surplus recycling amongst regions should occur.

These sorts of fundamental changes may or may not require a wholesale turnover of the national government. What is crucial is that these sorts of questions about economic policy-formation processes and structures not become political footballs between contending rivals. A structure strong enough to sustain changes of government is in order if the UK is to have the stability to steer its own economic course once the invisible backbone provided by its EU membership has been removed from the body politic.

Current events are vividly making this point. The limits on what is acceptable to the current government have already been tested and stretched by the pandemic. The period of recovery from the pandemic, which will be accompanied by an adverse-macro-shock Brexit, will test those limits further. The question is whether the further policy shifts made to avoid national economic depression during the long period of recovery will reflect local needs and political consensus.

This is the context in which University advice for local and combined authorities – in the case of the University of Leeds, for West Yorkshire Combined Authority – must take place. The entire unfolding scenario of fundamental policy debate needs a fair and impartial space for debating the issues; and it needs access to a fairly-mediated evidence base, and it needs well-umpired debates amongst those with different theoretical points of view. The local authorities are too thinly staffed to hire and retain the experts who can provide that space. The university sector, alone among UK institutions, can provide this space. It has survived the turn to fee-based support without surrendering its broader public mission.[4]

The universities can play this role not by turning within, and seeking the advice of their most elite and renowned voices, but by opening up. On one hand, universities should open more fully to what might be termed ‘everyday impact’ – encouraging academic and research staff to come forth with policy ideas, especially those rooted in expressed needs of the people of surrounding communities. And on the other hand, multiple channels to surrounding communities must be opened even wider. The tentative steps toward the ‘anchor institution’ role of universities, and toward encouraging ‘impact’, move in the right direction. Impact in the context of the national REF exercise has too often been interpreted in the context of product invention or of knowledge transfer (from gown to town). Impact activities must also include engagement with communities – dialogues, investments in local initiatives, encouragement of community-building, work with the young.

This ‘opening’ to the communities around universities will expand the space for policy-related discussions that break through current barriers of imagination or customary activities. The time is right for widening circles of possibility. Many of the ongoing debates inside the academy – degrowth versus renewed economic growth, competitiveness through participation in global supply chains versus renationalization of production, post-petroleum individualized transit versus large-scale collective transport, and so on – are unresolvable so long as they remain inside the ‘ivory towers’. And while national efforts to establish national economic strategies around key industries are admirable, there is no substitute for creating local community-university platforms for social-policy, sustainability, and economic-competitiveness experimentation.[5]

This turn to community-linked universities is not a call to restrict debate within the university; to the contrary, a broad array of ideas in every field is needed to push thinking and human possibility forward. It does mean that academics engaging with communities and with local authorities must make themselves aware not just of future-perfect scenarios but of current resource constraints. That said, the more new ideas see the light, the better. What constitutes ‘blue sky’ – that is, impossible – thinking about policy alternatives is not clear in the current environment: as noted, ecological futures are a work in progress, and innovative solutions to educational, healthcare, and housing deficits are still being worked out. Political voices at all levels have to be heard and validated. Diverse community representation is a must – the people have a right and a need to speak. And universities can provide a critical role in making the people’s voices heard.

The post-Covid moment: policy memoranda, position papers, and strategic syntheses

While imagining how the broader university-community relationship can evolve, the needs of the current moment must be kept uppermost in mind. At present, local and combined authorities with uncertain resources at their disposal, faced with imminent budget crises, need advice. There is a need for policy memorandums – which convey objective, evidence-based analysis with action steps that respond directly to the problems identified in the analysis. Position papers that clearly identify the ‘entry point’ of the author(s) are also helpful, as they clarify the author’s underlying assumptions. There is a key role, too, for in-depth reimagining of how economy and society could be organized, which, we would argue, is most valuable when developed and synthesised in a context and region specific way.

An example might help clarify what we mean by ‘context and region specific’. Consider recent efforts in California, aided by the University of California, to design public policies responding to the dangers of wildfire incidence and losses in that state. The ideas that emerged in these efforts were scaled to what the state could mandate: for example, require the clear-cutting of small brush in perimeters around woodland housing, regulate materials used for roofing in woodland/outlying housing, etc. The definition of the problem could of course be scaled ‘up’. For example, two other factors in ‘global warming’ are the drying out of the state through reduced precipitation, cutting the snowpacks in the Sierras; and groundwater depletion throughout the state due to overpopulation. However, taking on these deeper causes would lead to solutions more radical than are feasible or even thinkable for the California policymaker community. Addressing these wider issues would require national scale analysis and policy, informed by regional scale context. At a national scale, a solution would be to ban people from building their wilderness palaces in remote, fire-risk areas just because they didn’t want to be near other people; but that would not be enforceable regionally. Thus, there is always a balancing aspect that invisibly lies behind effective local and regional policy interventions, and those that must be interlinked with policies at national and indeed global scales.

[1] Emails: G.Dymski@leeds.ac.uk; andrew@lubs.leeds.ac.uk.

[2] Nassib Nicholas Taleb, introduced this term into contemporary discourse with The Black Swan: The Impact of the Highly Improbable. New York: Random House, 2007). Chapter 1 defines it as follows: ‘First, it is an outlier, as it lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility. Second, it carries an extreme ‘impact’. Third, in spite of its outlier status, human nature makes us concoct explanations for its occurrence after the fact, making it explainable and predictable. … [that is, a ‘black swan’ event involves] the triplet: rarity, extreme ‘impact’, and retrospective (though not prospective) predictability.’

[3] These terms are worth unpacking. A ‘fix’ in everyday parlance refers to an informal or temporary solution. This term was adapted by David Harvey (he introduced it initially in his The Limits to Capital. Baltimore: Johns Hopkins University Press, 1982) and was subsequently came into common use in human geography (see, for example, Erica Schoenberger, ‘The Spatial Fix Revisited,’ Antipode 36(3) June 2004: 427-33). Harvey portrays capitalism, using a broad Marxian crisis framework, as beset by several crisis tendencies, among which is over-accumulation (under-consumption) – a condition in which productive capacity outpaces consumption and/or investment outlets. When this happens, continued accumulation requires further an expanded number of consumption/investment hubs. The expansion of business service offices or supermarkets can be seen as examples of spatial fixes. A spatial fix is at once necessary but, at the same time, temporary – the value invested in any location only retains its value if another is found. The notion of a ‘steady state’, in macroeconomic theory, refers to a configuration of demand and supply forces that can be reproduced or smoothly expanded through time.

[4] There is more to be done to retain or earn the public trust – for example, by insuring that all Britons have access to all universities at all levels, regardless of income or racial/minority status. But this is an item readily added to the universities’ agendas, especially in the era of social-policy rethinking spurred by the BLM movement.

[5] This, of course, will have implications for what is valued in academics’ efforts to meet performance expectations of university supervisors, and for any national efforts – should they remain necessary – to evaluate excellence in academic work.

By Soumyadeb Chowdhury¹, Alexander Kharlamov¹, Oscar Rodriguez-Espindola¹, Prasanta Dey¹, Ian Maidment¹, Peter Ball², Carolyn Chew-Graham³, Steven Marwaha⁴, Joemon Jose⁵

¹Aston University, ²University of York, ³Keele University, ⁴University of Birmingham, ⁵University of Glasgow

Primary contact: S.chowdhury5@aston.ac.uk and P.K.Dey@aston.ac.uk

This Photo by Unknown Author is licensed under CC BY-NC-ND

The importance of mental health and wellbeing is becoming widely recognised. Mental health and wellbeing are complex constructs and our understanding of it or its implications on organisational performance is limited. The context of Small and Medium Enterprises is particularly challenging.

In the EU and UK, SMEs are limited to fewer than 250 staff and are usually partitioned into micro firms (1-9 employees); small enterprises (10-49 employees); and medium enterprises (50-249 employees) (OECD, 2005). According to the Department for Business, Energy, and Industrial Strategy October 2019 Statistical Release[1], there were 5.9 million businesses in the UK. Of them, 5.82 million (99%) were micro or small businesses (up to 49 employees); 35,600 medium businesses (50-249 employees) and 7,700 large businesses (250 or more employees). While micro and small companies employed 47.8% of the UK workforce, medium employed 12.6% of the UK workers. In terms of turnover, micro and small companies’ share was 36.8% and medium businesses’ share was 15.4% of the total UK turnover at the start of 2019. Overall, the SME sector in the UK employed 16,630,000 people and generated £2,168,005 million. In terms of industrial composition, Construction had the largest number of SME businesses (17.68%), followed by Professional, Scientific, and Technical Activities (15%), and Wholesale and Retail Trade and Repair (9%). Yet, Wholesale and Retail Trade and Repair brought in the largest turnover (1/3 of SME turnover) and employed most people (14% of all SME employment). (Department for Business, Energy and Industrial Strategy, 2019).

SMEs usually face a large number of challenges, such as lack of stable financing and lack of scalability opportunities leading most SMEs to fail within the first year of existence (e.g., OECD, 2018). After analysing the data from Austria, Czech Republic, Estonia, Germany, Hungary, Italy, Latvia, Poland, Portugal, Slovak Republic, Slovenia, Spain, Sweden, and United Kingdom, a number of OECD studies concluded that “the productivity gap between large firms and smaller SMEs has widened” between 2005 and 2014, with micro firms (1-9 people firms) particularly suffering from decreased productivity in the manufacturing sector (OECD, 2018, p.6). These findings uncover an interesting paradox: even though the rapid development of SMEs is desirable for any economy, their prevalence does not guarantee increased productivity, which is one of the major factors for economic prosperity.  At the same time, recent advances in business and economics literature suggest that productivity can be increased through the improvement of job satisfaction, life satisfaction as well as via increasing the level of wellbeing (e.g., Oswald et al. 2015; Clarke and Mahadi 2017; etc.). Under these circumstances, the link between individual wellbeing, SMEs and productivity becomes very interesting for further research.

Source: https://www.businesshealthy.org/mental-ill-health-workplace-impact-business-productivity/

Wellbeing and Productivity in the Business Enterprise Sector: The Curse of SME

In order to understand the link between productivity and wellbeing in the context of SME’s, we formulate the Business-Wellbeing-Productivity framework (Figure 1), which connects business size and organisational structure with wellbeing parameter, which, in turn, is correlated with productivity. Using country-level dataset of the OECD countries, we show that prevalence of SMEs in a country’s business sector is associated with the decrease in productivity of this country through the SMEs’ negative impact on the workforce wellbeing.

Figure 1 Business-Wellbeing-Productivity Framework

The development of SMEs within the business enterprise sector in a given country is related to the overall wellbeing of this country’s workforce and this wellbeing indeed affects country’s productivity. We propose a new Business-Wellbeing-Productivity (BWP) framework, linking business performance to business size through the workforce wellbeing factors and test this framework using data from 38 countries worldwide including Australia, Austria, Belgium, Bulgaria, Canada, Chile, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Japan, Korea, Latvia, Lithuania, Luxembourg, Mexico, Netherlands, New Zealand, Norway, Poland, Portugal, Romania, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, UK, and United States. We find that BWP relations are characterized by “the Curse of SMEs”: large number of SMEs in a country negatively influences this country’s workforce wellbeing determinants, which, in turn, directly (negatively) affect productivity. In other words, the prevalence of SMEs in any given economy negatively impact productivity because it leads to decline in people’s job and life satisfaction.

The initial impact of COVID-19 on SMEs in the UK on Mental Health, Wellbeing and Productivity

This study considers first-order effects of COVID-19 on SMEs in the UK with data collected in April 2020. In a comprehensive survey study (N=192), we measure a range of effects of the pandemic on the way SMEs handle the existing crisis. While under normal circumstances we would expect that wellbeing positively affects productivity in organizations consistent with previous research (e.g., Oswald et al., 2015; Sgroi, 2015) we do not observe the same relationships in times of crisis. We find that SME workers are overwhelmed by the income concerns – i.e., financial instability is a major factor explaining increased anxiety, declined wellbeing and decreasing productivity.

Figure 2 Relative position of income, wellbeing and SME performance under Normal vs Crisis conditions

The second most important predictor of productivity identified is the number of days working from home, which affects productivity negatively, meaning that the more SME workers are required to work from home the worse is the productivity of the business. General wellbeing is predicted by greater emotional stability, low number of jobs and greater income. Job satisfaction is predicted by company’s high innovativeness, higher individual’s conscientiousness and emotional stability, lower working hours and larger frequency of work-related training. Financial wellbeing is predicted by higher conscientiousness, lower anxiety and depression scores (i.e. better mental health), greater income, fewer work from home days, longer employment and greater frequency of trainings per year. Contrary to previous research, we demonstrate that in times of crisis securing basic income needs becomes a greater concern than the overall wellbeing together with the work mode which plays a critical role in ensuring that firms remain productive. Further research is required to understand the complex link between individual wellbeing and SME performance in times of crisis.

Modelling the Impact of COVID-19 on Small and Medium-sized Enterprises in the UK

By June COVID-19 pandemic caused global impact affecting individuals and organisations. The Small and Medium Enterprises (SMEs) have been some of the most affected sectors and beyond observed economic data most of the insight is anecdotal and our previous research during the early stages of the pandemic demonstrate that in times of crisis SME workers were overwhelmed by income concerns which predicted SME performance better than individual wellbeing. We explore the impact of COVID-19 on productivity considering wellbeing, job characteristics, firm characteristics, individual characteristics, leadership and mental health using Structural Equation Modelling on a sample of UK SME employees (N=163). We found that wellbeing strongly impacts productivity.

We consider a wide range of factors (such as organisational responsiveness, leadership, use of ICT and working remotely, government communication, change management within the organisation and resource adaptability) and tried to find the main determinants of successes and failures of SMEs as a result of pandemic. We are particularly interested in the effects of COVID-19 on productivity. Using a survey, conducted with British SMEs, we consider a broad range of factors from individual psychological characteristics to financial circumstances of companies in order to determine the main consequences of coronavirus on SME performance.

Our main finding is that individual wellbeing of the SME employees directly influences productivity. SMEs, where staff reports higher life and job satisfaction levels achieve better productivity outcomes. Mental health issues as well as Organisational flexibility has a negative impact on productivity. Wellbeing is positively dependent on financial wellbeing, general wellbeing job satisfaction, and leadership quality. Work strain has a strong negative impact on wellbeing.  Even though previous literature showed that (i) human mental health may be affected by COVID-19 anti-spread measures (e.g., Galea et al., 2020) as well as (ii) demonstrated the positive effect of improvement in individual wellbeing on productivity in experimental setting (e.g., Oswald et al., 2015) and in the context of a developing economy under “business as usual” (e.g., Clarke and Mahadi, 2017), this research extends existing literature by establishing a strong link between wellbeing and productivity during crisis and in the context of SMEs, which has not been done before.

[1] See https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/852919/Business_Population_Estimates_for_the_UK_and_regions_-_2019_Statistical_Release.pdf for more detail.

Clarke, N. and Mahadi, N., 2017. Mutual recognition respect between leaders and followers: Its relationship to follower job performance and well-being. Journal of business ethics, 141(1), pp.163-178.

Galea, S., Merchant, R.M. and Lurie, N., 2020. The mental health consequences of COVID-19 and physical distancing: The need for prevention and early intervention. JAMA internal medicine, 180(6), pp.817-818.

Oreg, S., 2003. Resistance to change: Developing an individual differences measure. Journal of applied psychology, 88(4), p.680.

Oswald, A. J., Proto, E., & Sgroi, D. (2015). Happiness and productivity. Journal of Labor Economics, 33(4), 789-822.

Featured Image: Photo by NASA on Unsplash

by Hadi Arbabi. Department of Civil & Structural Engineering, The University of Sheffield

Our current understanding of and approaches to devising and selecting infrastructural and ultimately land-use interventions for better urban economic performance are often of limited capacity in providing long-term ‘place-based’ blueprints. Best framed by Sir David Higgins, the former Chair of HS2 Limited, what we need is an overall national transport strategy for and against which individual interventions can be constructed and appraised.¹ In our Productivity Insights Network project, we attempted to quantifying a sense of productivity premium that may be locked in and associated with the spatial organization and connectivity of small-area neighborhoods and their demographic profiles within cities.

Cities as geographic networks

Emerging studies on patterns of urban scaling across systems of cities have sought to formalize and explain long-observed size-related agglomerations in and across different countries by developing explicit and implicit geographically embedded network models of cities’ inhabitants and mobility infrastructure.² These works make explicit the assumption within the agglomeration-related work that average-aggregated urban economic output is a function of the number of human interactions fostered and facilitated by cities. Within these spatially explicit frameworks, long-term blueprints of infrastructure can then be thought of in terms of spatial layouts of the cities’ inhabitants that increase or maximize the number of interactions between individuals across the city and hence its economic output. Particularly, if given a certain labor and skills profile, the relative number of interactions between a city as is it exists in space and how it could potentially be (re)arranged provides a gage for the magnitude of potential productivity premium related to the city’s spatial organization.

What we have seen so far

In the rest of this post, I briefly summarize our main observations based on our optimization of inter-neighborhood distances in Sheffield to maximize its inhabitants’ interactions. I should mention in advance that our findings are mostly intuitive in themselves and might appear trivial. What is of importance, however, is that they are independently reaffirmed by our approach which can be seen to be more general in its assumptions especially avoiding strong ones regarding individual behavior.

1. Denser cities perform better especially if long-range connectivity is more difficult.

This one is too obvious. It is easy to see that a trivial solution to optimizing inter-neighborhood distances, for maximizing individual interactions for a geographically embedded social network on a flat plane, is to stack individuals vertically to maximize density and interactions!

We have estimated Sheffield’s potential productivity premiums as the number of inhabitants’ interactions, under a varying influence of distance on interactions, relative to those of the city’s existing geography. When we assume a mobility infrastructure that assists in formation of long-range interactions already exists, there is virtually no difference in productivity of an optimized layout and only about a 12% advantage for an extremely densified layout. However, as long-range interaction formation becomes more difficult, ie, we assume a more realistic provision of mobility anywhere outside London, rearrangements of the city’s neighborhood layout can unlock a 15% increase in output with extreme densification signaling a near sevenfold increase in output.

2. Homogenous deployment of mixed-used planning across the city is beneficial.

For most cities, the neighborhoods with the largest number of inter-neighborhood interactions comprise the city center and often exist within the city’s ring road. City centers, therefore, house a high-density mix of residential use, commercial activities, and crucially employment. This combined effect of their density and mixed use transforms them to the foci of both inter- and intra-neighborhood interactions. Meanwhile, the further away one gets from the city center, the more the prominence of suburban commuter-belt residential use and fewer the opportunities for local interactions.

Delving into the inter-neighborhood distances after optimization shows that increasing the number of interactions in the city requires a change in the land use. In essence, city-center type activities need to be more easily accessible city-wide. As such, the long-term optimal spatial layout of cities can be seen as one more resembling a chess board pattern of residential/commercial use that both maximizes overall city-wide interactions and facilitates walkability.³

Choropleth showing indicative mean percentage change of inter-neighborhood distance for each neighborhood. Color scheme from green to blue corresponds to an average decrease of distances to an average increase in distances after optimization; and as such, whether the neighborhood as a whole needs to become more central to facilitate more interactions.

3. Rearrangement of neighborhoods unlocks the highest potential in relatively lower-income lower-education neighborhoods

Mean increase in neighborhoods’ interactions correlates systematically with their population-weighted levels of education. While, the magnitude of these effects may be due to the particularly segregated organization of neighborhoods in Sheffield, the core reasoning remains the same as that underlying the need for mixed-use planning. Lower-income lower-education neighborhoods are inherently more likely to be vulnerable to effects of low long-range accessibility while simultaneously less likely to feature adequate employment opportunities. The break-up of core city-center type functionality to be more evenly distributed across the city cultivates more interactions in these neighborhoods.

Mean percentage increase in neighborhood interactions against population weighted neighborhood average education levels. It is worth mentioning that the top 10% of the largest increases in interaction count because of our optimization of the layout involve neighborhood pairs with one area of low average income.

Connectivity beyond physical mobility

As a final note, we should perhaps mention that interpretations of urban scaling models of cities need not be constrained to purely physical aspects of mobility. Our approach has been motivated by and particularly focused on the physical aspect of the spatial organization of cities and the provision of mobility within them and we have, simplistically, quantified interactions and the possibility of their existence over distances in a city. With particular reference to the ongoing COVID-19 pandemic, the prevalence of home-working has forced a dramatic drop in physical intra-city mobility.⁴ However, for those sectors that have remained economically active despite lockdown measures, the underlying individual interactions involved in creating cities’ output have not completely vanished. Portions of these interactions are now simply forced to be made remotely. The spatial patterns of interaction that we have identified, ostensibly based on road distances between neighborhoods, can, therefore, be interpreted as priorities for provision of alternative and/or digital connectivity infrastructure.

1 – Economic Affairs Committee. The Economics of High Speed 2, House of Lords Economic Affairs Committee 1st Report of Session 2014‒15. https://publications.parliament.uk/pa/ld201415/ldselect/ldeconaf/134/134.pdf (2015).

2 – Bettencourt, L. M. A. The Origins of Scaling in Cities. Science 340, 1438–1441 (2013).

3- Hamiduddin, I. Journey to Work Travel Outcomes from ‘City of Short Distances’ Compact City Planning in Tübingen, Germany. Planning Practice & Research 33, 372–391 (2018).

4 – Google. United Kingdom COVID-19 Community Mobility Report. https://www.gstatic.com/covid19/mobility/2020-06-27_GB_Mobility_Report_en-GB.pdf (2020).

Featured Image: Photo by Danielle MacInnes on Unsplash

By Dr Paula Turner, Co-Founder, The Centre for Tendering

info@centrefortendering.com       www.centrefortendering.com

How well do Local Enterprise Partnerships (LEPs) provide a strong value proposition in their business support ecosystem to prepare small firms for a tendering capability learning journey? A productive economy in part depends on SMEs developing a capability to tender for public sector contracts and the enterprise ecosystems that support that capability. In the Covid-19 context, enabling small firms to permeate public sector procurement markets – and ensuring that procurement is used to fulfil economic and social goals so we can “build back better” – is an even higher priority.

The UK Government’s SME Action Plan[i] sets out a modern, ambitious strategy that includes an ambition to spend £1 in every £3 of public sector procurement on smaller businesses by 2022. Achieving the Government’s laudable objectives will demand both a reform of procurement practices to streamline the capabilities demanded by tendering and investment to build the capability to tender in small firms.

An enterprise ecosystem needs to know how to support small firms to strategically commit (or not) to tendering, build the capability needed to be tender-ready and continuously develop tendering capability through tendering experience. This ecosystem will not only supply information via learning opportunities but enhance social capital: an entrepreneur’s ability to get resource – in this case information and sensemaking about tendering – out of networks. The support will, therefore, draw them into a relationship with procurers, expert business support providers and peers and encourage information sharing, reflection and mutual sensemaking. In other words, if an ecosystem is a multi-lateral arrangement of actors and organisations that creates a value proposition[ii] then it requires a coordinated infrastructure to ensure that £1 of £3 of public sector procurement can be spent on small firms that have capacity to tender.

Outside of the retail sector, business founding is usually focused on delivering goods and services to customers, rather than being ready to sell. Selling via tendering can be particularly alien to small firm leaders because most have product or service specific expertise and lack any experience of tendering. For many, their previous employment may have provided face-to-face customer negotiation skills but not ability to strategically situate a business in a tendering environment, decipher tender invitations and write a technical and competitive document.

Small firm learning tends to be problem-situated and small businesses tend to be focused on the short-term problem of survival. Typically, they are not likely to spontaneously develop capability to tender prior to an individual tender invitation. There is an argument, then, for aligning learning to the process of responding to a specific tender invitation. Yet, the Centre for Tendering’s Capability Model for Tendering depicts top-performing capabilities that suggest being successful at tendering demands some pre-existing capability as well as the ability to learn fast about efficient and competitive means of selecting tender invitations, writing tenders and reviewing outcomes. When a small firm approaches tendering without any awareness of its demands, and very low tendering capability, they are likely to waste resources on failure or an aborted attempt to tender, particularly when they have failed to ‘triage’ the opportunity to realise that they are trying to tender for a contract they cannot win or do not want.

For some firms, public sector tendering is not the right strategic choice and learning to avoid this market is sensible. Of more concern are discouraged tenderers, with the potential to thrive through public sector contracting but low optimism or access to support to build capability. And, repeat failures that make multiple unsuccessful attempts to tender but do not learn from these or make a strategic choice to properly invest in building capability or to avoid this market.

There is a puzzle here: how to motivate and support small firms to strategically invest in developing a core set of capabilities so they become tender-ready as well as supporting them to use experience to hone and adapt tendering capability so they build and sustain their competitive edge.

Join The Centre for Tendering free webinar on Tuesday 30^th June 1-2pm https://us02web.zoom.us/webinar/register/8815918639780/WN_hu_4r4zuRka3ruOw-9A0Cw to learn how regional enterprise ecosystems can comprehensively support small firms: Enhancing Business Support for SME Tendering: A Dashboard of Priorities for Regions.

Finally, small firms are open to innovation at a time of crisis and we know they often turn to their customers or suppliers to find collaborators for innovation[iii]. It would be unproductive for procurement to become a ‘flat process’ of administration rather than collaborative means of developing economies and communities. To achieve this, LEPS must commission enterprise ecosystem actors that can invest in developing small firm capability to tender and procurement must become more open to input from small businesses.

[i]  Department of Business, Enterprise and Industrial Strategy (2019), SME action plan, Crown Copyright, https://www.gov.uk/government/publications/beis-small-and-medium-enterprises-sme-action-plan

[ii] Adner, R. (2017) ‘Ecosystem as structure: An actionable construct for strategy’, Journal of Management, 43, (1), pp.39-58

[iii] Roper, S. (2020) ‘R&D and innovation after Covid-19: What can we expect? A review of trends after the financial crisis’, Published: 7 May 2020, https://www.enterpriseresearch.ac.uk/people/stephen-roper-3/

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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?

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

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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.

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.

[1] https://www.centreforcities.org/blog/what-does-the-covid-19-crisis-mean-for-the-economies-of-british-cities-and-large-towns/

[2] https://www.ft.com/content/4b2c47fc-c195-4109-9432-87cbc9e0ace5

[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 – http://www.camecon.com/wp-content/uploads/2020/06/2020-04-16_COVID-19_Local-slide-pack.pptx

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

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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).