Empirical studies in industrial location: an assessment of their methods and results

This paper surveys recent evidence on the determinants of (national and/or foreign) industrial location. We find that the basic analytical framework has remained essentially unaltered since the early contributions of the early 1980's while, in contrast, there have been significant advances in the quality of the data and, to a lesser extent, the econometric modelling. We also identify certain determinants (neoclassical and institutional factors) that tend to provide largely consistent results across the reviewed studies. In light of this evidence, we finally suggest future lines of research.

A Model-to-model analysis of the repeated Prisoners' Dilemma: genetic algorithms vs. evolutionary dynamics

We study the properties of the well known Replicator Dynamics when applied to a finitely repeated version of the Prisoners' Dilemma game. We characterize the behavior of such dynamics under strongly simplifying assumptions (i.e. only 3 strategies are available) and show that the basin of attraction of defection shrinks as the number of repetitions increases. After discussing the difficulties involved in trying to relax the 'strongly simplifying assumptions' above, we approach the same model by means of simulations based on genetic algorithms. The resulting simulations describe a behavior of the system very close to the one predicted by the replicator dynamics without imposing any of the assumptions of the analytical model. Our main conclusion is that analytical and computational models are good complements for research in social sciences. Indeed, while on the one hand computational models are extremely useful to extend the scope of the analysis to complex scenar

Multi-scale support vector algorithms for hot spot detection and modelling

The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.

Structure du temps de travail des infirmières de santé publique: effets de l'âge des patients, de la nature des prestations fournies et du lieu du contact. [Structure of work times of public health nurses: effect of the age of patients, nature of care given and location of contact].

In the framework of health services research sponsored by the Swiss National Science Foundation, a research was undertaken of the activity of the large majority of the public health nurses working in the Swiss cantons of Vaud and Fribourg (total population 700,000). During one week, 130 nurses gathered, with a specially devised instrument, data on 4165 patient visits. Studying the duration of the contacts, one has distinguished contact duration per se (DC), duration of the travel time preceding the contact (DD), and total duration in relation with the contact (DTC-addition of the first two). It was noted that the three durations increased significantly with patient age (as regard travel time, this is explained by the higher proportion of home visits in higher age groups, as compared with visits at a health center). Examined according to location of the visit, contact duration per se (without travel) is higher for visits at home and in nursing homes than for those taking place at a health center. Looked at in respect to the care given (technical care, or basic nursing care, or both simultaneously), our data show that the provision of basic nursing care (alone or with technical care) doubles contact duration (from 20 to 42-45'). The analyses according to patient age shows that, at an advanced age (beyond 80 years particularly), there is an important increase of the visits where both types of care are given. However, contact duration per se shows a significant raise with age only for the group "technical care only"; it can be demonstrated that this is due to the fact that older patients require more complex technical acts (e.g., bladder care, as compared with simpler acts such as injection). A model of the relationships between patient age and contact duration is proposed: it is because of the increase in the proportions of home visits, of visits including basic nursing care, and of more complex technical acts that older persons require more of the working time of public health nurses.

Tax differentials and agglomeration economies in intraregional firm location

This paper analyses empirically how differences in local taxes affect the intraregional location of new manufacturing plants. These effects are examined within the random profit maximization framework while accounting for the presence of different types of agglomeration economies (localization/ urbanization/ Jacobs’ economies) at the municipal level. We look at the location decision of more than 10,000 establishments locating between 1996 and 2003 across more than 400 municipalities in Catalonia, a Spanish region. It is necessary to restrict the choice set to the local labor market and, above all, to control for agglomeration economies so as to identify the effects of taxes on the location of new establishments.

Model based fault diagnosis with application to an automotive engine

Report for the scientific sojourn at the University of Linköping between April to July 2007. Monitoring of the air intake system of an automotive engine is important to meet emission related legislative diagnosis requirements. During the research the problem of fault detection in the air intake system was stated as a constraint satisfaction problem over continuous domains with a big number of variables and constraints. This problem was solved using Interval-based Consistency Techniques. Interval-based consistency techniques are shown to be particularly efficient for checking the consistency of the Analytical Redundancy Relations (ARRs), dealing with uncertain measurements and parameters, and using experimental data. All experiments were performed on a four-cylinder turbo-charged spark-ignited SAAB engine located in the research laboratory at Vehicular System Group - University of Linköping.

Market Familiarity and the Location of South and North MNEs

We use a systematic empirical analysis of the determinants of South-South (SS) and North-South (NS) foreign direct investment (FDI) as a canvas to explore how multinational enterprises’ (MNEs) location decisions are shaped by better acquaintance with a foreign market resulting from bilateral ties, experience of international expansion, and knowledge of how to deal with poor governance. We find that these various aspects of market familiarity, which can interact together, are important to explain and differentiate the location behaviours of South MNEs (S-MNEs) and North MNEs (N-MNEs) in developing countries.

Employment Protection, Flexibility and Firms’ Strategic Location Decisions under Uncertainty

We construct a model in which oligopolistic firms decide between locating in a country where employment protection implies costly output adjustments and in one without employment protection. Using a two-period three-stage game with uncertainty, we demonstrate that location is influenced by both flexibility and strategic concerns. The strategic effects under Cournot work towards domestic anchorage in the country with employment protection while those under Bertrand do not. Strategic agglomeration can occur in the inflexible country under Cournot and even under Bertrand, provided uncertainty and foreign direct investment costs are low.

Anatomy of contaminated aquifers of an industrial site: insights from the stable isotope compositions of waters and dissolved inorganic carbon

The hydrogen and oxygen isotopes of water and the carbon isotope composition of dissolved inorganic carbon (DIC) from different aquifers at an industrial site, highly contaminated by organic pollutants representing residues of the former gas production, have been used as natural tracers to characterize the hydrologic system. On the basis of their stable isotope compositions as well as the seasonal variations, different groups of waters (precipitation, surface waters, groundwaters and mineral waters) as well as seasonably variable processes of mixing between these waters can clearly be distinguished. In addition, reservoir effects and infiltration rates can be estimated. In the northern part of the site an influence of uprising mineral waters within the Quaternary aquifers, presumably along a fault zone, can be recognized. Marginal infiltration from the Neckar River in the cast and surface water infiltration adjacent to a steep hill on the western edge of the site with an infiltration rate of about one month can also be resolved through the seasonal variation. Quaternary aquifers closer to the centre of the site show no seasonal variations, except for one borehole close to a former mill channel and another borehole adjacent to a rain water channel. Distinct carbon isotope compositions and concentrations of DIC for these different groups of waters reflect variable influence of different components of the natural carbon cycle: dissolution of marine carbonates in the mineral waters, biogenic, soil-derived CO2 in ground- and surface waters, as well as additional influence of atmospheric CO2 for the surface waters. Many Quaternary aquifer waters have, however, distinctly lower delta(13)C(DIC) values and higher DIC concentrations compared to those expected for natural waters. Given the location of contaminated groundwaters at this site but also in the industrially well-developed valley outside of this site, the most likely source for the low C-13(DIC) values is a biodegradation of anthropogenic organic substances, in particular the tar oils at the site.

Fast numerical algorithms for the computation of invariant tori in Hamiltonian systems

In this paper, we develop numerical algorithms that use small requirements of storage and operations for the computation of invariant tori in Hamiltonian systems (exact symplectic maps and Hamiltonian vector fields). The algorithms are based on the parameterization method and follow closely the proof of the KAM theorem given in [LGJV05] and [FLS07]. They essentially consist in solving a functional equation satisfied by the invariant tori by using a Newton method. Using some geometric identities, it is possible to perform a Newton step using little storage and few operations. In this paper we focus on the numerical issues of the algorithms (speed, storage and stability) and we refer to the mentioned papers for the rigorous results. We show how to compute efficiently both maximal invariant tori and whiskered tori, together with the associated invariant stable and unstable manifolds of whiskered tori. Moreover, we present fast algorithms for the iteration of the quasi-periodic cocycles and the computation of the invariant bundles, which is a preliminary step for the computation of invariant whiskered tori. Since quasi-periodic cocycles appear in other contexts, this section may be of independent interest. The numerical methods presented here allow to compute in a unified way primary and secondary invariant KAM tori. Secondary tori are invariant tori which can be contracted to a periodic orbit. We present some preliminary results that ensure that the methods are indeed implementable and fast. We postpone to a future paper optimized implementations and results on the breakdown of invariant tori.

(Optimal) Spatial Aggregation in the Determinants of Industrial Location

Empirical studies on the determinants of industrial location typically use variables measured at the available administrative level (municipalities, counties, etc.). However, this amounts to assuming that the effects these determinants may have on the location process do not extent beyond the geographical limits of the selected site. We address the validity of this assumption by comparing results from standard count data models with those obtained by calculating the geographical scope of the spatially varying explanatory variables using a wide range of distances and alternative spatial autocorrelation measures. Our results reject the usual practice of using administrative records as covariates without making some kind of spatial correction. Keywords: industrial location, count data models, spatial statistics JEL classification: C25, C52, R11, R30

Western Préalpes Médianes Romandes: Timing and structure. A review.

Between the original position and their present day location as klippen, the Prealpes Medianes underwent a complex history of paleotectonics and alpine tectonics. Due to the opening of the Piemont ocean the Brianconnais sedimentation realm of the Prealpes Medianes evolved as a rim basin of the northern passive margin during Jurassic to Eocene times. Different paleotectonic features (normal faults, synsedimentary growth structures, inversion structures) developed and were active above a basal detachment in evaporitic layers. The tectonic movements were a consequence of thermal events in the crust. Isolated from the Iberic continent at the end of the Late Cretaceous, the Brianconnais exotic terrain was incorporated into the accretionary prism of the closing Piemont ocean and the incipient alpine orogeny during the Lutetian-Bartonian. The Prealpes Medianes were detached from their homeland during the Bartonian-Priabonian and were transported onto the foreland. The tectonic style is one of a thin-skinned foreland fold and thrust belt. Fault associated fold development above a main decollement, together with internal deformation, represent the Prealpes Medianes main structural features. The very low-grade metamorphic conditions have their origin in the heat flux induced by tectonic burial by overriding nappes in the accretionary prism. After having been transported on top of the developing Helvetic nappes the Prealpes were emplaced in their present day position in front of the Alpine mountain belt during Oligocene times. Post-emplacement and out of sequence thrusting, possibly younger than Oligocene, is observed and can be related to thrusting in the sedimentary substratum and the basement.

A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification

Defining an efficient training set is one of the most delicate phases for the success of remote sensing image classification routines. The complexity of the problem, the limited temporal and financial resources, as well as the high intraclass variance can make an algorithm fail if it is trained with a suboptimal dataset. Active learning aims at building efficient training sets by iteratively improving the model performance through sampling. A user-defined heuristic ranks the unlabeled pixels according to a function of the uncertainty of their class membership and then the user is asked to provide labels for the most uncertain pixels. This paper reviews and tests the main families of active learning algorithms: committee, large margin, and posterior probability-based. For each of them, the most recent advances in the remote sensing community are discussed and some heuristics are detailed and tested. Several challenging remote sensing scenarios are considered, including very high spatial resolution and hyperspectral image classification. Finally, guidelines for choosing the good architecture are provided for new and/or unexperienced user.

Evaluating the influence of spatial uncertainty in locality points for species distributional modeling

1. Species distribution modelling is used increasingly in both applied and theoretical research to predict how species are distributed and to understand attributes of species' environmental requirements. In species distribution modelling, various statistical methods are used that combine species occurrence data with environmental spatial data layers to predict the suitability of any site for that species. While the number of data sharing initiatives involving species' occurrences in the scientific community has increased dramatically over the past few years, various data quality and methodological concerns related to using these data for species distribution modelling have not been addressed adequately. 2. We evaluated how uncertainty in georeferences and associated locational error in occurrences influence species distribution modelling using two treatments: (1) a control treatment where models were calibrated with original, accurate data and (2) an error treatment where data were first degraded spatially to simulate locational error. To incorporate error into the coordinates, we moved each coordinate with a random number drawn from the normal distribution with a mean of zero and a standard deviation of 5 km. We evaluated the influence of error on the performance of 10 commonly used distributional modelling techniques applied to 40 species in four distinct geographical regions. 3. Locational error in occurrences reduced model performance in three of these regions; relatively accurate predictions of species distributions were possible for most species, even with degraded occurrences. Two species distribution modelling techniques, boosted regression trees and maximum entropy, were the best performing models in the face of locational errors. The results obtained with boosted regression trees were only slightly degraded by errors in location, and the results obtained with the maximum entropy approach were not affected by such errors. 4. Synthesis and applications. To use the vast array of occurrence data that exists currently for research and management relating to the geographical ranges of species, modellers need to know the influence of locational error on model quality and whether some modelling techniques are particularly robust to error. We show that certain modelling techniques are particularly robust to a moderate level of locational error and that useful predictions of species distributions can be made even when occurrence data include some error.

Dukes B colorectal cancer: distinct genetic categories and clinical outcome based on proximal or distal tumor location.

PURPOSE: The aim of this study was to determine whether tumor location proximal or distal to the splenic flexure is associated with distinct molecular patterns and can predict clinical outcome in a homogeneous group of patients with Dukes B (T3-T4, N0, M0) colorectal cancer. It has been hypothesized that proximal and distal colorectal cancer may arise through different pathogenetic mechanisms. Although p53 and Ki-ras gene mutations occur frequently in distal tumors, another form of genomic instability associated with defective DNA mismatch repair has been predominantly identified in the proximal colon. To date, however, the clinical usefulness of these molecular characteristics remains unproven. METHODS: A total of 126 patients with a lymph node-negative sporadic colon or rectum adenocarcinoma were prospectively assessed with the endpoint of death by cancer. No patient received either radiotherapy or chemotherapy. p53 protein was studied by immunohistochemistry using DO-7 monoclonal antibody, and p53 and Ki-ras gene mutations were detected by single strand conformation polymorphism assay. RESULTS: During a mean follow-up of 67 months, the overall five-year survival was 70 percent. Nuclear p53 staining was found in 57 tumors (47 percent), and was more frequent in distal than in proximal tumors (55 vs. 21 percent; chi-squared test, P < 0.001). For the whole group, p53 protein expression correlated with poor survival in univariate and multivariate analysis (log-rank test, P = 0.01; hazard ratio = 2.16; 95 percent confidence interval = 1.12-4.11, P = 0.02). Distal colon tumors and rectal tumors exhibited similar molecular patterns and showed no difference in clinical outcome. In comparison with distal colorectal cancer, proximal tumors were found to be statistically significantly different on the following factors: mucinous content (P = 0.008), degree of histologic differentiation (P = 0.012), p53 protein expression, and gene mutation (P = 0.001 and 0.01 respectively). Finally, patients with proximal tumors had a marginally better survival than those with distal colon or rectal cancers (log-rank test, P = 0.045). CONCLUSION: In this series of Dukes B colorectal cancers, p53 protein expression was an independent factor for survival, which also correlated with tumor location. Eighty-six percent of p53-positive tumors were located in the distal colon and rectum. Distal colon and rectum tumors had similar molecular and clinical characteristics. In contrast, proximal neoplasms seem to represent a distinct entity, with specific histopathologic characteristics, molecular patterns, and clinical outcome. Location of the neoplasm in reference to the splenic flexure should be considered before group stratification in future trials of adjuvant chemotherapy in patients with Dukes B tumors.