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For cities to better understand their strengths and weaknesses, and what policies might help them to grow, it is crucial that they can compare themselves to the performance of other places. However, making these comparisons can be very difficult, especially at an international level, as cities often struggle to find data that covers comparable urban geographies. Another more basic problem for places is knowing where to look, given the hundreds of cities in the world that could be used as potential benchmarks.
As a result, it is tempting for places to simply replicate well-known examples of “iconic” cities’ policies – such as Barcelona’s economic development strategy, Copenhagen’s green transports approach, Leipzig’s urban regeneration success, and Bilbao and its famous “Guggenheim effect”. However, what works in one place is dependent on specific social and economic conditions, making policy replication potentially ineffective unless you are comparing like-with-like.
Instead, cities need a better insight into which places they are closely related to economically, to understand what they can learn from their similar counterparts. That is why in our new report Competing with the Continent, we created groups of comparable cities across Europe based on their industrial structure. For each UK city we considered the share of jobs in each sector and looked for the continental cities with the statistically closest industrial mix.
Comparing the performance of cities that have a similar industrial structure is particularly useful as it helps us to better understand the reasons for any differences between places that the analysis highlights. Take Manchester, for example – based on the proportion of jobs in each sector of its economy, it is most similar to Hamburg in Germany out of all European cities. But although the economic structure is similar in the two cities, productivity levels are considerably different: the average economic output of each worker in Manchester was £43,500 in 2011, more than 50 per cent less than that of workers in Hamburg (£67,100).
What can explain such a productivity gap between two highly similar economies? Our analysis shows that one major difference between the two cities is the level of education of their resident population. Interestingly both cities have a similar share of high-skilled residents (31 per cent in Manchester and 32 per cent in Hamburg), but Manchester is home to a much higher sharer low-skilled residents than Hamburg: 34 per cent of the former’s residents had less than 5 good GCSEs as their highest education level, while only 15 per cent of Hamburg’s population had an equivalent level of education.
Another difference is the number of patent application in the two cities. In 2011, there were around 24 patents applications per 100,000 inhabitants in Hamburg, but just 5 per 100,000 inhabitants in Manchester.
These comparisons suggest that the reason for the productivity gap between the two places is likely to be the contrasting quality of their economic output: although the overarching industrial structure is the same between the two cities, firms in Hamburg are more innovative overall and have access to a higher-skilled labour pool, making them more productive. For Manchester, this means that the answer to boosting productivity does not necessarily come from changing its industrial mix, but rather from improving the quality of the goods and services it produces. Above all, to upscale their production, firms in Manchester need access to a more skilled and therefore productive labour force than is currently available.
Further investigation is required to fully understand local differences and potential policy implications that this kind of city-by-city comparison can offer. But comparing places based on their industrial structures provides a first step to more relevant city comparisons and better policy prescriptions, instead of places trying to copy ideas from other cities which their economic structure bears no relation to. To find out which of their continental counterparts each UK city is closest to, explore our data tool.
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