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How to evaluate sport and culture: the effect of cultural districts (statistical approach)

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What was the programme and what did it aim to do?

This study looks at the effect of cultural districts on employment, income and property prices in US neighbourhoods. Cultural districts are formally designated zones within a city: sometimes simply branded as an ‘arts zone’, sometimes with accompanying tax breaks or incentives for artists to move in. Some districts already have a cluster of cultural amenities and institutions (e.g. museums, arts workshops and studios) as well as complementary amenities (e.g. restaurants, cafes). Here, zoning is designed to maintain organic growth. In a few cases, local policymakers use designation to attract cultural players – such as artists, musicians, galleries or studios – into a neighbourhood with no arts presence. As with most sports and culture projects, the objectives of these projects are not only about delivering local economic benefits. But cities often use cultural districts as part of a place-making strategy, and specifically to ‘revitalise’ the neighbourhood in question, so it is important to understand their economic effects.

What’s the evaluation challenge?

The fact that districts are selected makes evaluation difficult. Districts may be chosen for growth potential or, conversely, because they need regeneration. If cities pick locations where employment is already rising this makes isolating any additional positive cultural district effect difficult. Some of these underlying factors are likely to be unobservable. Alternatively, wider (city or national) conditions may also influence outcomes – e.g. if the urban economy is growing, district outcomes are likely to improve whether or not zoning is in place. It is also not straightforward to identify the spatial scale of impact, or model its intensity across a treatment area – we can imagine property market effects might be biggest in the streets directly around a new museum or arts space, but the same doesn’t necessarily hold for employment or income effects.

What did the evaluation do?

This study implements a ‘difference in difference’ analysis for a number of neighbourhood-level economic outcomes. Specifically, it compares changes in outcome between 1990 and 2000 for neighbourhoods with cultural districts, neighbourhoods immediately adjacent and neighbourhoods in the rest of the county (the latter used as a control group).

The study gathers information on 99 cultural districts across the US, and combines this with city and neighbourhood-level data from the 1980, 1990 and 2000 Census. Neighbourhoods are defined by ‘block groups’, small areas with an average population of about 4,000.

How good was the evaluation?

According to our scoring guide, difference-in-differences receives a maximum of 3 (out of 5) on the Maryland Scientific Methods Scale (Maryland SMS). This is because it does well to control for observable differences (e.g. unemployment levels) between areas with cultural districts and areas without them, but is unable to control for unobservable differences (such as the quality or energy of local arts scenes). To deal with underlying differences between areas, the study also includes a county-level time trend (that captures the fact that counties may exhibit long run differences in growth rates), and a set of 1980 neighbourhood outcomes as controls. Since this study uses a wide range of variables to control for observable differences we score this study 3 on the Scientific Maryland Scale.

What did the evaluation find?

The study finds multiple positive effects of cultural districts: growth in property values is 9.3% higher in district neighbourhoods than the rest of the county; income growth is 5.4% higher and employment growth is 4.4% higher. Poverty declines by 2.3% more in zoned neighbourhoods. While commuting times do not change there is some evidence of more skilled residents moving in, and increased population turnover. Taken together, this implies that residents are likely working outside the neighbourhood (so additional jobs may not go to locals), and there is some displacement of existing residents (likely connected to rising property prices). There is generally little difference in impacts within cultural districts and in adjacent areas.

What can we learn from this?

This analysis raises important questions about who benefits (economically) from cultural districts and similar initiatives. If the hoped for effect of the district is to help local residents into work, it is important to note that the wage and employment effects are positive but pretty small. These benefits may also not accrue to existing residents. In contrast, property owners (whether residents or businesses) experience much larger gains.

Local conditions will vary in UK cities compared to US cities, so some caution is needed in applying these results to Britain. But concerns about displacement of existing residents are likely to generalise. The surest way to test the findings is to replicate the study. Some improvements to the evaluation would be possible if, e.g., cultural district designation is competitively awarded with ‘losers’ used as a control group. Alternatively, one could compare changes in outcomes for active districts against areas where districts were planned but not enacted.

Reference

Noonan, D.S. (2013). How US Cultural Districts Reshape Neighborhoods. Cultural Trends, 22(3-4), 203-212. [Study 327 from our Sports and Culture review]

How to evaluate sport and culture: the effect of cultural districts (statistical approach)