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As recovery from the Great Recession continues, economic development scholars and practitioners are again focused on the pace and the sustainability of recovery, as well as on efforts to minimise the severity of future downturns. This paper contributes to the literature by exploring the relationship between industry diversity and economic resilience over time. Using fixed effects models with data from the Bureau of Labour Statistics and the Census Bureau, the paper examines the influence of industrial diversity and concentration on unemployment rate stability in Ohio counties between 1977 and 2011. Results indicate that while more concentrated counties had lower unemployment rates when times were good, counties with more diverse industry structures fared better during times of national or local employment shocks. The paper also finds that there is a relationship between concentration in particular industries and the ability to withstand a shock changes over the 35 years examined, thus highlighting the need to take care when interpreting findings over shorter periods and the need to consider the particular industry of dependence. While local policymakers have little ability to affect industrial concentration in the short run, the paper recommends that highly concentrated counties adopt policies that may help buffer their economies to effects of negative shocks. [ABSTRACT FROM AUTHOR]

'Borrowed size' is an emerging policy concept in several European countries, presenting theoretical potential to explain contemporary urban dynamics unaddressed through conventional urban growth theories that emphasise the role of agglomeration economies. In its original conceptualisation by Alonso, the concept describes and explains the situation that especially smaller cities that are located in a larger 'megapolitan complex' do perform better because they have access to agglomeration benefits of larger neighbouring cities. This paper scrutinises the concept of borrowed size, thereby focusing on its conceptualisation and reviewing its empirical justification thus far. Our empirical analyses show that the concept must be stretched in terms of scale and scope to enhance its policy value. Borrowed size occurs when a city possesses urban functions and/or performance levels normally associated with larger cities. This is enabled through interactions in networks of cities across multiple spatial scales. These networks serve as a substitute for the benefits of agglomeration. Theoretically, the borrowed size concept demands a recasting of the geographical foundations of agglomeration theory. [ABSTRACT FROM AUTHOR]

Access to a large labour pool (labour pooling) leads to local economic concentrations through agglomeration economies. However, these concentrations may be self-limiting by reducing labour availability through competition over high-skill workers. This paper examines whether labour pooling and labour availability of workers with different incomes account for local job growth in the Atlanta metropolitan area between 2000 and 2006. Workers’ income is employed to account for the human capital of workers, including education and skills. It is found that the availability of high-income workers is the only positive significant factor for job growth and the spatial size of the effect is larger than the traffic analysis zone (neighbourhood scale). In contrast, no labour pooling indicators show a positive association with job growth. The finding casts doubt on labour pooling effects at the intraregional level and suggests avenues for further research on local-area agglomeration economies. [ABSTRACT FROM PUBLISHER]

This paper considers the work of the European Cluster Observatory (ECO) in light of current debates around the notion of clusters. Examining the definitions employed by the ECO, questions are posed about how effective policy can be when using highly restrictive means of analysis. Further, the work contends that, far from this being purely an analytical problem, there also exists a fundamental semantic issue regarding the term ‘economic cluster’. [ABSTRACT FROM PUBLISHER]