Jan Kluge (p), Hannes Zens

The common belief of a general positive relationship between economic integration and welfare has been shattered recently. Even though there is clear empirical evidence of an overall welfare gain when borders fall, it seems to become more obvious that remote regions might benefit to a smaller extent. This might especially apply to border regions as they are mostly poorer, insufficiently connected and more sparsely populated than central regions. It is unclear whether they benefit at all from an open border. Also, there is no consensus about the symmetry, i. e. whether border regions in the poorer country benefit more when they move closer to their richer neighbours or vice versa.

In this paper, we investigate the case of European integration in the context of Austria as it provides an interesting laboratory: Austria experienced the fall of the iron curtain that surrounded almost half of the country, leading to more open borders to the east. The western borders virtually vanished when Austria joined the already existing EU in 1993. The eastern expansion in 2004 again focussed on the integration of its eastern neighbours.

We make use of population as well as night-time light data and deploy causal inference techniques in order to investigate the impact of border regime changes on economic parameters of remote regions in Austria and its neighbours. We suppose that the three mentioned historic events have shifted the distribution of economic activity inside Austria. The increased market potential for regions on both sides of the border should have resulted in collective welfare gains. Given classic convergence arguments, however, one would expect the joining regions to benefit to a larger extent.

Bastian Heider (p), Stefan Siedentop

This paper addresses the question on the evolution of metropolitan employment distribution by scrutinizing two relatively large and representative samples of German and US American city regions between 2003 to 2015. In general, US metropolitan areas are far more decentralized and deconcentrated than their German counterparts. While the trajectory of American metropolitan employment dispersal was relatively dynamic with periods of de- and re-concentration, the development trend for German city regions has been remarkably stable. Further, in both countries the tendency of deconcentration and decentralization has been the strongest within the manufacturing sector, while knowledge intensive service industries remained relatively centralized and concentrated. Tendencies for a re-concentration and re-centralization of economic activity were particularly strong in the largest metroplitan areas, in city regions in the north-eastern census region of the US as well as in East Germany. However, within both countries we find a relatively great variety of trajectories, involving the coexistence of reinforced monocentricity, polycentricity, and dispersal. In summary, the overall picture of intra-metropolitan employment distribution seems to be strongly fragmented with diverging trajectories that cannot solely be explained by national or regional patterns.

Petra Staufer-Steinnocher (p), Lukas Hödl, Florian Martin

Emergency medical services (EMS) are crucial parts of modern health care. Given its importance for the modern medical infrastructure, EMS and its service networks represent a well-studied field in operations research. Recent studies pointed out that one of the remaining challenges in EMS is the factor of uncertainty. In cooperation with a local Austrian ambulance service provider (ASP) our objective is to tackle the factor of uncertainty by incorporating the stochastic nature of emergencies. In specific, we i) design and implement a probabilistic demand model for the maximization of stochastic coverage, ii) compare results to a deterministic approach and iii) analyze implications for network capacities and travel times. In doing so, we estimate a probability surface for a one-year operational data provided by the ASP using kernel density function computation. We then specify a probabilistic demand model and design different coverage scenarios, which we compare to prior research using a deterministic approach. Two of the designed coverage scenarios are further subject to a capacitated network and travel time analyses. This research illustrates that a stochastic demand model for maximizing coverage significantly differs from a deterministic approach. Findings offer insights into how the factors of stochastic coverage, number of emergency service stations (ESS), capacities needed, and ambulance travel times are linked.

Augusto Cerqua (p), Guido Pellegrini

This paper studies the impact of the closure of a large plant on the local economy at a time of economic recession. In particular, we examine how the closure of large manufacturing plants in Italy between 2008 and 2013 impact on the local labor market system. We estimate the average treatment effect for the short as well as the medium period by adopting the nonparametric generalization of the difference-in-differences estimator and the generalized synthetic control method. The main dataset comes from the Italian Statistical Register of Active Enterprises archive, which covers the universe of firms and employees of industry and services in Italy. As plant closures are usually accompanied by a bargaining process between the firm and trade unions mediated by the government, we complement our analysis by looking at the official reports of such bargaining processes and by taking such outcomes into account. This is a relevant topic given the large number of employees generally involved in manufacturing plant closures which consequently pushes governments to subsidize or bail out firms on the verge of bankruptcy. However, the literature on this topic is surprisingly scarce and additional compelling empirical analyses are needed to guide policymakers when making such important and costly decisions. Besides, we investigate the heterogeneity of the impact by industry and by geographical area.

Valentina Giannini (p), Donato Iacobucci , Giulio Cainelli

When growing firms often decide to expand by adding new productions in similar o related sectors. This can be done by setting-up new business units (internal growth) or by acquiring existing firms (external growth). In general, the geographical proximity to the headquarter facilitates the communication and the organization between the established firm and the new units; however, the need to specific knowledge and resources of the proximity to the market may result in choosing a different location for the new unit.
Up to now the relation between the location choices and the internal organization of firms has not been fully investigated.
This paper proposes a methodology to define and measure the geography of firms, i.e. the degree of dispersion of their business units, and to investigate the factors influencing such geography.
We expect that the geographical dispersion of productions units depends not only on the strategic choices of firms, such as the degree of diversification, but also from the characteristics of the context in which the leading firm is located.
In the empirical analysis, we associate the business units to the different companies belonging to the same business group. Our sample is composed by a novel dataset of about 16,000 Italian business groups developed by using the BvD Amadeus database containing information on joint stock companies (called head of the group) and their own subsidiaries. The empirical analysis aims to investigate how the structural characteristics of a Local Labour System (LLS) may influence the geographical dispersion of these units. Moreover, we analyse the effects of local productive specialization and diversification on the geography of business groups. We also test this relationship focussing on the role played by the membership to an industrial district and local variety on firm geography.
Our expectation is that the geographical dispersion of firms is influenced by both productive specialization and diversification at local level. This evidence is further confirmed when we consider manufacturing groups. In this case firm geography seems to be affected by the membership to an industrial district and to local variety. This analysis has several policy implications. The most important is related to the role of diversification as driver of some of the strategic choices made by firms. In fact, interventions associated to the so-called Smart Specialization Strategy (S3) can have positive effects not only on the local development patterns but also on the strategic decisions of many firms.