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This paper tests for excessive employment agglomeration among twenty southern California manufacturing industry clusters using two methods claiming to control for the natural and planned geography constraining industrial location generally. We find broad consistency across the alternative tests; although fewer industry clusters test statistically significant for agglomeration or dispersion using the weighted kernel density estimator than when we use the more established weighted case-control approach. Similarly, the observed values for the former statistic test significant over a subset of the spatial scales over which the case-control method tests significant.

PurposeThe purpose of this paper is to explore the threshold effect of firm size on technological innovation using panel data from 2007 to 2012 for listed enterprises in China's manufacturing sector.Design/methodology/approachConsidering the aim of research question is to examine the nonlinear relationship, this paper utilizes the threshold regression proposed by Hansen's (2000).FindingsBased on a threshold regression model using panel data from 2007 to 2012 for listed enterprises in China's manufacturing sector, we find a series of new results. This nonlinear relationship is under the restrictions and impacts of various factors, such as industry characteristics and government subsidies. The results suggest that the threshold regression model well explains the complicated nonlinear relationship and transition process, and it can also shed light on management practice and policy.Originality/valueThere are categorical arguments regarding why firm size is not as effective as before in explaining the monotonic principle of industrial innovation, especially for establishing an effective industrial policy in a particular situation. One of the important reasons is that we have begun to adopt a new perspective from the nonlinear view on the relationship between firm size and industrial innovation. In this study, we have examined the threshold effect of firm size on industrial technological innovation, which is the most representative nonlinear relationship.