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January 2019

Stop button on board a bus

Real Journey Time, Real City Size, and the disappearing productivity puzzle.

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Featured image © dzphotogallery / Adobe Stock

For a year we’ve been tracking most of the buses and trams in The West Midlands; the UK city region centred on Birmingham. We do it by polling the live departure screens that you see at bus stops, even at stops where they aren’t installed.

So far we’ve recorded 40 million bus departures, a total of 16GB of data. And we’ve written tools to explore it in seconds.
You can try for yourself at You can see how long every bus took to connect any two bus stops anywhere in The West Midlands, and calculate averages over tens of thousands of bus journeys at specific times, to see how bus journey times change over the course of a typical day.

But why?

Agglomeration: Big cities are more productive.
We’ve mostly done this work because of the following graph.

Many economists argue that larger cities are more productive than smaller cities, and become ever more productive as they grow due to something called agglomeration benefits.

There are many other factors that contribute to productivity, but this simple law seems to hold well in economies like The USA, Germany, France, and The Netherlands. For example, Lyon, the second largest city in France, is more productive than Marseille, the third largest city, which is in turn more productive than Lille.

Almost uniquely among large developed countries, this pattern does not hold in the UK. The UK’s large cities see no significant benefit to productivity from size, especially when we exclude the capital.

The result is that our biggest non-capital cities, Manchester and Birmingham, are significantly less productive than almost all similar-sized cities in Europe, and less productive than much smaller cities such as Edinburgh, Oxford, and Bristol.

Public transport and city size.
One notable difference between the UK’s large cities and those in similar countries is how little public transport infrastructure they have.

While France’s second, third, and fourth cities have 8 Metro lines between them (four in Lyon, two each in Marseille and Lille) the UK’s equivalents have none.

Manchester and Lyon have similar-sized tramway systems, with about 100 stations each, but Marseille (3 lines) and Lille (2 lines) have substantially more than Birmingham (1 line) and Leeds (0 lines).

Is it possible that poor public transport in the UK’s large cities makes their effective size smaller, and thus sacrifices the agglomeration benefits we would expect from their population?

Our Real Journey Time data lets us ask this question.

Real journey time, and journey time variability.
There is an important difference between bus public transport and fixed infrastructure public transport: reliability. I have used our Real Journey Time tool to calculate the worst-case (95th percentile) journey time on public transport on two routes into Birmingham. This is the time that a public transport user must leave for their journey to ensure that they are only late for work or a meeting once a month.

The first journey is a bus from the South of the city, Stirchley to Birmingham. This 3.5 mile journey takes about 20 minutes between 6am and 7am, and about 40 minutes between 8am and 9am.

The second journey is a tram from West Bromwich to Birmingham. This 8.5 mile journey takes 30 minutes regardless of when it is taken, as the tram route is almost completely segregated from traffic.

While the tram is substantially quicker at all times than the bus, the reliability of its timing, even during the most congested periods, provides an additional large benefit to users.

We think that people generate the most agglomeration benefits for a city when they travel at peak times, to get to and from work, meetings, and social events. Our tool shows us that at the times when people need to travel in order to generate these benefits, buses are extremely slow. And since buses are by far the largest mode of public transport in Birmingham this is likely to have significantly higher impact on Birmingham than in Lyon where the largest mode of public transport is the metro, which delivers reliable journey times no matter the time of day.

Our hypothesis is that Birmingham’s reliance on buses makes its effective population much smaller than its real population. This reduces its productivity by sacrificing agglomeration benefits. For the past six months, using our Real Journey Time tool, we’ve worked with The Productivity Insights Network to quantify that.

At peak times, Birmingham is a small city.
The technique is quite simple. We pick 30 minutes as the travel time by bus that marks the boundary of the Birmingham agglomeration. This doesn’t include walking at either end of a journey, or waiting time, so this figure may well mean a 50 minute total journey.

We then use our real journey time to examine how far from central Birmingham that allowed journey time would let a person live.

For example, by examining six months of journeys on the buses we calculate that at off-peak times a person 5 miles from Birmingham in West Bromwich is part of the Birmingham agglomeration. At peak times, this is no longer the case and the outer boundary of the Birmingham agglomeration is reduced in size to just 3.5 miles away in Smethwick.

Making use of our data on trams we can also imagine a Birmingham where major bus routes are replaced by trams and enjoy fast and reliable journey durations, even at peak times. This then includes people as far away as Bilston, 9 miles away.

By repeating this process for bus route into Birmingham from every direction we create a boundary of the effective size of Birmingham at different times of the day. By summing the population living within each boundary we calculate the real size of Birmingham under three conditions. By bus at peak time, by bus at off-peak time, and in an imaginary future where all buses travelled as quickly and reliably as trams (simulated tram).

At this point you might see why we picked 30 minutes as our travel time. Allowing 30 minutes of travel time using fixed infrastructure such as a tram gives Birmingham a population of about 1.7 million people. Which is very close to its population as defined by the OECD of about 1.9 million.

But at peak time Birmingham’s effective population is just 0.9m, less than half the population that the OECD use.

Birmingham’s effective size might explain most of its productivity gap.
This is where things get very interesting. If we consider that Birmingham has a population of 1.9 million, and we assume that agglomeration benefits should work in the UK to the same extent that they work in France, Birmingham has a 33% productivity shortfall. This underperformance of the UK’s large cities is part of the productivity puzzle that UK economists have been desperately trying to solve.

But once you understand that Birmingham’s real size is much smaller, below 1 million people, the productivity shortfall reduces to just 9% and is no longer significant.

Our hypothesis is that by relying on buses that get caught in congestion at peak times for public transport, Birmingham sacrifices significant size and thus agglomeration benefits to cities like Lyon, which rely on trams and metros. This is based on our calculations that a whole-city tramway system for Birmingham would deliver an effective size roughly equal to the OECD-defined population.

This difference seems to explain a significant proportion of the productivity gap between UK large cities and their European equivalents.

So what should we do?
The good news is that Birmingham’s current plans for transport investment are aimed at increasing its effective size at peak times.

• Using our Real Journey Time tool, TfWM are targeting investment in bus lanes and bus priority measures to improve journey speed and journey reliability on existing bus routes.

• Seven sprint bus routes are being planned, with bus priority measures hopefully delivering journey time reliability similar to a tram.

• Two tram extensions (to Wolverhampton Train station and Edgbaston) are under construction, with two more (to Dudley and Birmingham Airport) under study.

• Station re-openings at places like Moseley and Kings Heath will offer reliable journeys by rail to new areas of the city.

The prize for achieving this is large. If bus journey times became as reliable at peak time as they are off peak the effective population of Birmingham would increase from 0.9m to 1.3m. If we assume that agglomeration benefits in the UK are as significant as in France, this would lead to an increase in GDP/capita of 7%.

What’s next?
We have a reached a good point to share our work, but this is just the beginning.

• We are continuing to improve our codebase to ensure that it can handle up to 200 million stored bus and tram departure times.

• We are looking to incorporate trains into our tool, which will boost Birmingham’s effective size, though not by much.

• We are continuing to work with The Data Science Campus at The Office for National Statistics and Transport for The West Midlands on strengthening our methodology for calculating travel isochrones.

• We have already expanded our service to another UK city and continue to search for more, the sole requirement is an open bus departure API that reports a unique ID for each bus.

• We are working to bring our technique to a French city, probably Lyon or Lille, in order to check that the increased amount of fixed public transport infrastructure does make their effective size larger than Birmingham’s.

How was this work made possible.
The project was delivered by Open Transport North, working with The Open Data Institute Leeds.
This work was inspired by a Birmingham City Council hack event run by Deft 153 held in 2016 at Innovation Birmingham and made possible by the Transport for The West Midlands API, which almost uniquely allows the tracking of individual vehicles.

Development has been funded and supported by Transport for The West Midlands, working with The West Midlands Bus Alliance, including National Express. Funding for the development of a method for estimating the economic impact from increased bus journey times was provided by The Productivity Insights Network (an Economic and Social Research Council investment) with specific guidance provided by Professor Iain Docherty of The University of Glasgow.

Additional support and inspiration has been provided by The Office for National Statistics Open Data Campus, Transport API, The Open Data Institute, and Nesta.

Tom Forth
Head of Data at the Open Data Institute Leeds
This work was undertaken with Daniel Billingsley and Neil McClure

Read about our other funded projects

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Open Innovation, Experimental Entrepreneurship and Productivity

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Featured image © Worawut/ Adobe Stock

Paul Romer, the co-recipient of the 2018 Nobel Memorial Prize in Economic Sciences, argues that economic growth and productivity concerns the nature, formation and commercialisation of ideas. Of course, this a dynamic process, and in recent years significant changes have occurred within economies, industries and places with regard to the generation, sourcing and exploitation of ideas, and the innovations these result in. Such changes are likely to be impacting on productivity and productivity growth at a number of levels. As a means of going someway to addressing these issues, I am currently engaged in a study within which I have interviewed more than 120 individuals – to date – in the field of innovation and entrepreneurship in the UK, Germany, the US, China, and Japan. This includes entrepreneurs, venture capitalists, the operators of incubators, accelerators, co-working spaces, universities, policymakers, as well as representatives of large corporates such as Honeywell, Cisco, Accenture, Bayer, and Snapchat.

There are a myriad of issues that have come to light from the work, but perhaps two of the most notable in the context of productivity are the widespread emergence of open innovation practices and what I term ‘experimental entrepreneurship’, both of which are interrelated. First, it is clear that open innovation practices have become prevalent across many industries, especially technology-based sectors. Firms, particularly large corporates, are increasing looking for the latest ideas outside of their corporate boundaries. Alongside traditional joint ventures and collaborations, firms are becoming more and more engaged in a range of new practices from corporate acceleration to open access innovation centres, innovation scouting, innovation competitions and the like. In essence, these mainstay innovation players are moving part of the burden, costs, and to some extent the risk, of innovation to start-up firms, new entrepreneurs, and purely aspirational entrepreneurs, rather than within the safety net of the corporation itself.

These changes are having a potentially profound and complex impact on the relationship between innovation and productivity. For example, the costs, investments, and inputs required to innovate are shifting. In particular, firms are having to invest more and more resources into the networks and relationships that are required to access ideas. Building and maintaining relationships is expensive. There are tangible costs in the form of events – innovation theatre – and the contracting of intermediaries – innovation scouts – as well as huge intangible investment in terms of the time required by firms to generate and sustain the social capital and network capital they need to develop their own innovation ecosystems.

Alongside these inputs, the research undertaken to date indicates that many of the external relationships developed by firms do not result in fruitful outcomes, in terms of innovations that lead to productivity improvements. A lack of compatibility and alignment between internal and external forces, as well as internal resistance, means that many funded ideas and innovations are never implemented. This begins to suggest that despite its undoubted capacity to combine and unleash new ideas, open innovation is not always a practice that leads to efficiency within the innovation process or results in productivity gains.

Partly as a result of open innovation and an unstable macroeconomic climate in recent years, we are witnessing the emergence of a phenomenon that can perhaps be best described as ‘experimental entrepreneurship’. Fundamentally, more and more individuals are experimenting with the idea of becoming entrepreneurs, especially technology entrepreneurs. This goes beyond the usual upturn we see in the numbers of self-employed workers during a crisis, to something that is becoming more embedded and sustained.

Within the technology sectors more individuals across all age groups are taking time to consider if they can develop an idea into a commercially viable innovation and business. The rapid growth, especially in big cities, of co-working spaces and incubators attests to this development. Generally, this can be seen as healthy economic sign, and all cities and regions, large or small, will require this innovation infrastructure if they are to become or remain productive places. It also indicates a role for public policy, and whilst acknowledging the positives of competition, there often appears to be considerable redundancy in terms of the overlap of ideas across experimental entrepreneurs. Many seem to be doing the same thing, all with their own funding streams. For example, within what can be called the ‘App Economy’ there is potentially excessive competition due to low entry costs.

It is noticeable that in areas such as biotechnology and life sciences we do not see anything like the same kind of experimental entrepreneurship. However, there is considerable activity in the area of social innovation among these entrepreneurial groups. Such activity has the potential to have significant positive impacts on productivity, but there appears to be little research that has sought to understand this.

Finally, the current study concludes that the time and external finance many of these experimental entrepreneurs spend is by far from wasted, especially in the long-term. However, the bottom line impact on contemporary productivity is less clear, but perhaps this does not matter to any great degree, and as the urban sociologist and planner Jane Jacobs noted in the 1960s when discussing the economic development of cities, ‘cities are indeed inefficient…the largest and most rapidly growing at any given time are apt to be the least efficient. Cities are economically valuable because they are inefficient’. This appears particularly relevant in the contemporary context and suggests interesting routes for examining the relationship between productivity and efficiency, especially institutional efficiency, with regard to innovation processes.

Robert Huggins
School of Geography and Planning
Cardiff University, UK.
January 2019


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Productivity Policy Review

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Featured image © Julien Eichinger / Adobe Stock

We tend to think about productivity as a long-term issue.  We often review its performance against the long-term trend and we consider underpinning factors that inherently take some time to influence.  How should this translate into policy formulation, and what have been the recent trends in policy?

To complement the evidence reviews on different thematic areas of interest to the Productivity Insights Network, we have conducted a review of policy changes in relation to productivity.  The review focused on policies and the policy narrative over the period from 1997 to present, and as well as looking at specific policy areas relating to business support, innovation, skills and regional/local economic development.

The review found that the policy focus on productivity has waxed and waned, with three periods identified:

• The policy narrative was explicit in the 2000s with the five drivers framework (investment, innovation, skills, enterprise and competition) used as a device for policy formulation and review, both nationally and regionally.

• There was a hiatus in productivity as an overarching policy objective from around 2010 until 2015. This reflected the focus on other issues, notably dealing with public finances.

• An explicit productivity framework re-emerged from 2015 culminating in the recent Industrial Strategy, which established the five foundations framework (ideas, people, infrastructure, business environment and places). This has strong alignment to the aforementioned five drivers.

These periods align with significant changes in the political and economic landscape, notably changes in government and the immediate aftermath of the financial crisis of 2008-09.  The review also found that there has been constant churn in the policy and institutional landscape, both between different administrations and throughout successive governments’ times in office.  In many cases it was the nomenclature that changed with rebranding or repackaging of existing programmes or policies.  Other changes marked a shift in targeting or focus to reflect the issue of the day.  There were three aspects where policy developments have been longstanding and have crossed government administrations:

• The gradual shift towards a new form of industrial policy-making and ultimately Industrial Strategy, which began in 2009 and has continued to the present.

• The increased emphasis on a demand-led skills agenda, highlighted initially in the Leitch Review of 2006.

• The changing nature of innovation policy, with more consideration of societal challenges and the use of demand-pull, as well as supply-push, policies, identified in the TSB’s (now Innovate UK) first strategy in 2008.

Churn in policy has been commented on by others (e.g. see Norris and Adam, 2017), including its relationship with short-term policy cycles, and ministerial changes whereby ministers want to make their own mark.  Resolving the productivity puzzle is a long-term challenge, and such policy churn may in and of itself be damaging to these endeavours.  Greater stability would result in more certainty and allow institutions to mature and develop.

The role of regional/local institutions has similarly changed over the period, especially in England.  Some issues are persistent challenges, though political, economic and technological contexts have evolved.  Regional institutions and devolved administrations were critical in the 2000s and were specifically tasked with improving drivers of productivity.  The current context places greater importance on the local scale through various structures and initiatives including Local Enterprise Partnerships, combined authorities, Local Industrial Strategies and City Deals.  Arrangements and tools have altered, though those adopted previously may provide lessons and insights to inform current developments.

National policy and strategic documentation is important in framing local responses, because it informs how local strategy is developed, structured and delivered.  This is important for productivity, because of the importance of breaking down silos and integrating different issues.  In terms of these institutional and policy-framing issues, we highlight three sets of points:

• Regional Economic Strategies (RESs) were 5-10 year strategies and their priorities had to align with Public Service Agreement targets and the five drivers of productivity. Whilst the strategic development matured over time, this requirement for alignment may have driven a focus on silos.  Prior to the abolition of the regional development agencies, there was the intent to develop Integrated Regional Strategies so that economic priorities were integrated with spatial planning.  In developing and delivering Local Industrial Strategies are there lessons from the RESs, in particular so that they are integrated and can genuinely focus on long-term issues?  And how can funding, and alignment with statutory obligations and planning help?

• How can the local-regional-national interface in delivering the Industrial Strategy work most effectively? There remain debates about the appropriate geographical level for intervention, and our policy review identified how different aspects of policy had been variously regionalised, localised and/or centralised.  Other spatial configurations exist, such as pan-regional working on issues like research and innovation, access to finance, and transport.  This raises issues around the joining-up of policies and programmes to make the most of synergies and avoid duplication.

• Regional Development Agencies were quasi-autonomous institutions, and so they were independent and could consider longer-term priorities that were outside of political cycles. However, it also left them open to criticism as they lacked democratic accountability.  How can LEPs, and local and combined authorities strike the right balance between these factors?

These sets of points highlight three important principles for strategic development, which need to be set nationally and locally.  These are having a long-term outlook, integrating key factors that influence productivity, and having appropriate institutional arrangements.  These three principles are clearly interconnected.  Our policy review suggests that this combination of principles has been lacking in the last 20 years.

Jonathan Cook, Dan Hardy and Imogen Sprackling