Viviana Elizabeth Zárate-Mirón
Regional resilience and cluster strength: The case of the U.S. in the Great Recession
Zárate-Mirón, V. E., & Moreno Serrano, R.
This paper evaluates the role of cluster strength on regional resilience. Previous literature shows that the industrial composition of a region, measured with indicators of its specialization, diversity and related and unrelated variety, is a crucial determinant of resilience. In this article, we aggregate cluster-level data into several indicators of regional cluster strength to proxy different aspects of the cluster portfolio of a region. Specifically, we consider the role of the presence of strong clusters in a regional economy as well as the mix of clusters in which the region has main relevance. On the one hand, we assume that the agglomeration forces arising in regions specialized in certain clusters could mitigate the effect of recessions. However, these strong industrial linkages may increase the difusion of the economic shock from one industry to the rest. To check which of these two forces dominates, we consider the resilience of the U.S. states over the Great Recession period and use a cluster definition that classify traded industries in 51 clusters. Our findings suggest that the presence of a portfolio of strong clusters allows mitigating economic shocks.
Keywords: resilience, cluster strength, traded industries, great recession.
The impact of smart specialization strategies on sub-cluster efficiency: simulation exercise for the case of Mexico
Zárate-Mirón, V. E., & Moreno Serrano, R. (2021)
This paper aims to evaluate whether the integration of smart specialization strategies (S3) into clusters significantly impacts their efficiency for countries that still do not implement this policy. This study tests three effects: whether the kind of policies envisaged through an S3 strategy impacts cluster’s efficiency; whether this impact changes with the technological intensity of the clusters; to determine which S3 is more suitable for sub-clusters at different levels of technological intensity. The Mexican economy is taken as case of study because it has a proper classification of its industries intro Porter’s cluster’s definition but still does not adopt the S3 policy. Through data envelopment analysis (DEA), this study evaluates the cluster’s efficiency increment when variables representing the S3 elements are included. The results show that strategies following the S3 had a significant impact in all clusters, but when clusters were classified by technological intensity, the impact on efficiency is higher in clusters in the medium low-tech group. According to the results in the DEA, it can be concluded that these S3 strategies have the potential to increase the clusters’ productivity significantly. These results make convenient the adoption of the S3 policy by countries that already count with a properly cluster definition.These findings contribute to the lack of studies that analyze the join implementation of S3 on clusters.
Research
Keywords: Productivity, Data envelopment analysis, Clusters, Technical efficiency, Smart specialization strategy
Labor congestion in the automotive cluster:the role of wages
Mendoza-Velazquez, A., Santillana, J. A., Zárate-Mirón, V. E., & Cabanas, M. (2018).
The purpose of this study is to investigate labor congestion in the automotive industry in Mexico. By using the cluster and subcluster definitions by Delgado et al. (2016) and relying on an efficiency and production function perspective, this study estimates a standard production function and measures marginal returns of labor at the regional cluster and subclusters levels. To assess whether wages affect the finding of congestion and productivity, the model also measures the individual impact of wages on both total productivity and marginal returns of labor. Among other results, this paper finds evidence of labor congestion in the automotive cluster in Mexico. This congestion deepens with wages and it is specific to some regions and some subclusters. The methods used are based on panel data techniques but are fundamentally cross-section in nature. The time period available may condition these findings. To the authors’ knowledge, this is the first study reporting congestion in the automotive cluster in Mexico.
Keywords: Productivity, Cluster, Automotive, Competitiveness, Congestion, Negative marginal returns