The 'cluster theory' has become one of the main concepts promoting regional competitiveness, innovation, and growth. As most empirical applications focus on measures of concentration of one industrial branch in order to identify regional clusters, the appropriate analysis of specific vertical relations is developing in this discussion. This paper tries to identify interrelated sectors via national input-output tables with the help of minimal flow analysis (MFA). The regionalization of these national industry templates is carried out with the allocation of branch-specific production values on regional employment. As a result, the paper shows concentrations of vertical clusters in only 27 of 439 German Nomenclature des Units Territoriales Statistiques (NUTS)-3 regions.

This paper explores the impact of industrial clusters on regional growth at the German labour market region level using a regional convergence model. Based on the results of an exploratory study of the geography of German industrial clusters, we are able to differentiate the impact of industrial clustering from a horizontal and a vertical perspective while taking regional convergence into consideration. The results indicate that in addition to an all-German process of convergence, a specific East German one can be identified. The different types of industrial clusters show mixed effects within this framework. While vertically isolated industrial clusters have a negative impact on regional growth in this period, positive growth effects can be identified when industrial clusters show an intra-regional vertical interconnectedness.

If regional development agencies assume the cluster concept to be an adequate framework to promote regional growth and competitiveness, it is necessary to identify industrial clusters in a comprehensive manner. Previous studies used a diversity of methods to identify the predominant concentrations of economic activity in one industrial sector in a region. This paper is based on a multidimensional approach developed by Titze et al. With the help of the combination of concentration measures and input–output methods they were able to identify horizontal and vertical dimensions of industrial clusters. This paper aims to refine this approach by using a superior measure of spatial concentration and by integrating information about spatial interdependence of industrial cluster structures to contribute to a more adequate framework for industrial cluster identification.

Die vergangenen Jahrzehnte waren weltweit durch eine Zunahme der außenwirtschaftlichen Ungleichgewichte gekennzeichnet. Den Leistungsbilanzüberschussländern, insbesondere Deutschland, wird in diesem Zusammenhang zunehmend vorgeworfen, durch zu moderate Lohnsteigerungen wesentlich zum Aufbau der Ungleichgewichte beigetragen zu haben. Vor diesem Hintergrund werden im vorliegenden Beitrag auf Basis einer Paneldatenanalyse die Determinanten der Leistungsbilanzungleichgewichte in der Europäischen Union ermittelt. Die Ergebnisse zeigen, dass die internationale preisliche Wettbewerbsfähigkeit der Länder nur eine von vielen erklärenden Variablen darstellt. Vielmehr gehen die Ungleichgewichte wesentlich auf unterschiedliche Sparneigungen, sowohl der öffentlichen Hand als auch des privaten Sektors, zurück. Folglich wären die an Deutschland gerichteten Forderungen, zum Abbau der Ungleichgewichte die moderate Lohnpolitik zu beenden, allein nicht zielführend. Stattdessen müssen andere Wege gefunden werden, die Binnennachfrage in den Leistungsbilanzüberschussländern zu stärken und die Ausschöpfung bestehender Sparpotenziale in den Leistungsbilanzdefizitländern zu erhöhen.

Folgt man der Überlegung, dass das Clusterkonzept für die regionale Wirtschaftspolitik Ansatzpunkte bildet, um Wirtschaftswachstum sowie Wettbewerbsfähigkeit von Regionen zu fördern, so setzt dies voraus, industrielle Cluster umfassend zu identifizieren. Bisherige Untersuchungen bedienen sich dazu einer methodischen Vielfalt, ausgehend von spezifischen regionalen Fallstudien über Input-Output-Methoden hin zu verschiedenen Konzentrationsmaßen. Der vorliegende Beitrag verwendet ein für die empirische Clusterforschung neues Instrument – die Qualitative Input-Output-Analyse. Ihr wohnt nach Ansicht der Autoren die Möglichkeit inne, in Verbindung mit Konzentrationsmaßen einen Beitrag zur flächendeckenden Identifikation industrieller Cluster zu liefern. Insbesondere erlaubt die vorgestellte Methodik die Zusammenführung des Tatbestandes einer kritischen Masse von Unternehmen mit dem Merkmal der Interaktion dieser über Input-Output-Beziehungen auch auf größeren regionalen Untersuchungsebenen. Wendet man die Methodik auf die deutschen Arbeitsmarktregionen an, so wird ersichtlich, dass 103 von 270 Arbeitsmarktregionen über Ansätze horizontaler Cluster verfügen, weitere 28 Regionen beherbergen vertikale industrielle Cluster. 139 Arbeitsmarktregionen weisen gemäß dem gewählten Untersuchungsdesign weder horizontale noch vertikale Cluster auf.

This study provides new evidence on the impact of the EU Cohesion Policy on income growth in less developed regions. Our panel includes data from all European regions for the years 1989-2020. Using a fuzzy Regression Discontinuity Design, we model treatment dynamics by applying a random effects estimator. Based on digitized historical data, we precisely replicate the policy rule and correctly classify the regions’ eligibility status. Results show that the policy has a moderate positive effect on GDP per capita growth in the targeted regions.

This paper documents substantial fiscal waste in the context of one the world’s largest regional development programs – the EU Cohesion Policy. We study Italy, and find that 20% of funding commitments are never paid out and funneled into unfinished or never-started projects. In our setting, this happens for reasons unrelated to fiscal constraints – municipalities appear to simply leave money on the table. Foregone spending is more prevalent in Southern regions, but there is also stark variation across municipalities within regions. We show that such under-utilization of available funds is strongly associated with limited administrative capacity of local governments.

We study the effects of place-based policies on aggregate productivity using administrative data on projects co-financed by the EU in Italy linked to balance sheet data. We exploit quasi-experimental variation in funding for a large place-based policy stemming from measurement error in regional GDP estimates. Results show that the policy likely decreases productivity. Decompositions reveal that aggregate declines are driven by reallocation of labor to low-productivity firms. Mechanism analysis using firm-level event studies reveals that negative reallocation effects are caused by high-productivity firms taking up the funds and subsequently becoming more liquidity constrained, leading to slowdowns in employment growth.

We study the granular wage and employment effects of a German place-based policy using a research design that leverages conditionally exogenous EU-wide rules governing program parameters at the regional level. The place-based program subsidizes investments to create jobs with a subsidy rate that varies across labor market regions. The analysis uses matched data on the universe of establishments and their employees, establishment-level panel data on program participation, and regional scores that generate spatial discontinuities in program eligibility and generosity. Spatial spillovers of the program linked to changing commuting patterns can be assessed using information on place of work and place of residence, a unique feature of the data. These rich data enable us to study the incidence of the place-based program on different groups of individuals. We find that the program helps establishments create jobs that disproportionately benefit younger and less-educated workers. Funded establishments increase their wages but, unlike employment, wage gains do not persist in the long run. Employment effects estimated at the local area level are slightly larger than establishment- level estimates, suggesting limited economic spillover effects. On the other hand, spatial spillovers are large as over half of the employment increase comes from commuters. Using subsidy rates as an instrumental variable for actual subsidies indicates that it costs approximately EUR 25,000 to create a new job in the economically disadvantaged areas targeted by the program.

The paper presents a modification of the matching and difference-in-differences approach of Heckman et al. (1998) for the staggered treatment adoption design and a Stata tool that implements the approach. This flexible conditional difference-in-differences approach is particularly useful for causal analysis of treatments with varying start dates and varying treatment durations. Introducing more flexibility enables the user to consider individual treatment periods for the treated observations and thus circumventing problems arising in canonical difference-in-differences approaches. The open-source flexpaneldid toolbox for Stata implements the developed approach and allows comprehensive robustness checks and quality tests. The core of the paper gives comprehensive examples to explain the use of the commands and its options on the basis of a publicly accessible data set.