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.

Free Mobility and Taste-Homogeneity of Jurisdiction Structures

We consider a population of agents distributed on the unit interval. Agents form jurisdictions in order to provide a public facility and share its costs equally. This creates an incentive to form large entities. Individuals also incur a transportation cost depending on their location and that of the facility which makes small jurisdictions advantageous. We consider a fairly general class of distributions of agents and generalize previous versions of this model by allowing for non-linear transportation costs. We show that, in general, jurisdictions are not necessarily homogeneous. However, they are if facilities are always intraterritory and transportation costs are superadditive. Superadditivity can be weakened to strictly increasing and strictly concave when agents are uniformly distributed. Keywords: Consecutiveness, stratification, local public goods, coalition formation, country formation. JEL Classification: C71 (Cooperative Games), D71 (Social Choice; Clubs; Committees; Associations), H73 (Interjurisdictional Differentials and Their Effects).

(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

Estudi dels impactes ambientals del cicle de vida del compost, de la producció a l'apliacació

La gran majoria d'hivernacles situats en clima mediterrani són de cost relativament baix i de tecnologia senzilla. El cultiu en hivernacle te com a objectiu principal incrementar la producció agrícola per unitat de superfície mitjançant l'aïllament de les condicions del medi. Aquest projecte presenta inventaris detallats i de qualitat del cicle de vida complet del compost amb aplicació en aire lliure i en hivernacle, aportant informació dels impactes ambientals i avaluant la viabilitat agronómica del compost com a fertilitzant quan s’aplica en cultius hortícoles. S’han considerat quatre opcions de cultiu, depenent del tipus de fertilitzant utilitzat (fertilitzans minerals o compost) i de si el cultiu és a l’aire lliure o en hivernacle. Les dades s’han obtingut experimentalment en parceles pilot i en una planta de compostatge industrial, ambdos localitzats prop de Barcelona, en una àrea mediterrànea. Per al cultiu en hivernacle, s’han obtingut produccions de tomàquet superiors a les d’aire lliure en el cas d’aplicar fertilitzants minerals, mentre l’ús de compani són de cost relativament baix i de tecnologia senzilla.

Mechanisms of agglomeration: Evidence from the location of new manufacturing firms in Spain

El objetivo de esta investigación es aportar evidencia sobre las fuentes de las economías de aglomeración para el caso español. De todas las maneras posibles que se han tomado en la literatura para medir las economías de aglomeración, nosotros lo analizamos a partir de las decisiones de localización de las empresas manufactureras. La literatura reciente ha puesto de relieve que el análisis basado en la disyuntiva localización / urbanización (relaciones dentro de un mismo sector) no es suficiente para entender las economías de aglomeración. Sin embargo, las relaciones entre los diferentes sectores sí resultan significativas al examinar por qué las empresas que pertenecen a diferentes sectores se localizan unas al lado de las otras. Con esto en mente, intentamos explicar que relaciones entre diferentes sectores pueden explicar coaglomeración. Para ello, nos centramos en aquellas relaciones entre sectores definidos a partir de los mecanismos de aglomeración de Marshall, es decir, labor market, input sharing y knowledge spillovers. Trabajamos con el labor market pooling en la medida en que los dos sectores utilizan los mismos trabajadores (clasificación de ocupaciones). Con el segundo mecanismo de Marshall, input sharing, introducimos cómo dos sectores tienen una relación de comprador / vendedor. Por último, nos referimos a dos sectores que utilizan las mismas tecnologías en cuanto a los knowledge spillovers. Con el fin de capturar todos los efectos de los mecanismos de aglomeracion en España, en esta investigación trabajamos con dos ámbitos geográficos, los municipios y los mercados de trabajo locales. La literatura existente nunca se ha puesto de acuerdo en cual es el ámbito geográfico en el que mejor trabajan los mecanismos Marshall, por lo que hemos cubierto todas las unidades geográficas potenciales.

On the effect of the geographical scope of agglomeration economies on firm location

This article analyses how agglomeration economies shaped the location decisions of new manufacturing start-ups in Catalan municipalities in 2001-2005. We estimate whether the locations of new firms are spatially autocorrelated and whether this phenomenon is industry-specific. Our aim is to estimate the geographical scope of agglomeration economies on firm entries. The data set comes from a compulsory register of manufacturing establishments (REIC: Catalan Manufacturing Establishments Register). JEL classification: R1, R3 Keywords: firm location; spatial autocorrelation

Location Determinants of New Firms: Does Skill Level of Human Capital Really Matter?

This paper is about the role played by stock of human capital on location decisions of new manufacturing plants. We analyse the effect of several skill levels (from basic school to PhD) on decisions about the location of plants in various industries and, therefore, of different technological levels. We also test whether spatial aggregation level biases the results and determine the most appropriate areas to be considered in analyses of these phenomena. Our main statistical source is the Register of Manufacturing Establishments of Catalonia (REIC), which has plant-level microdata on the locations of new manufacturing plants. Keywords: agglomeration economies, industrial location, human capital, count-data models, spatial econometrics.

Industrial Location and Space: New Insights

This paper tries to resolve some of the main shortcomings in the empirical literature of location decisions for new plants, i.e. spatial effects and overdispersion. Spatial effects are omnipresent, being a source of overdispersion in the data as well as a factor shaping the functional relationship between the variables that explain a firm’s location decisions. Using Count Data models, empirical researchers have dealt with overdispersion and excess zeros by developments of the Poisson regression model. This study aims to take this a step further, by adopting Bayesian methods and models in order to tackle the excess of zeros, spatial and non-spatial overdispersion and spatial dependence simultaneously. Data for Catalonia is used and location determinants are analysed to that end. The results show that spatial effects are determinant. Additionally, overdispersion is descomposed into an unstructured iid effect and a spatially structured effect. Keywords: Bayesian Analysis, Spatial Models, Firm Location. JEL Classification: C11, C21, R30.

Growth in a Cross-Section of Cities: Location, Increasing Returns or Random Growth?

This article analyzes empirically the main existing theories on income and population city growth: increasing returns to scale, locational fundamentals and random growth. To do this we implement a threshold nonlinearity test that extends standard linear growth regression models to a dataset on urban, climatological and macroeconomic variables on 1,175 U.S. cities. Our analysis reveals the existence of increasing returns when per-capita income levels are beyond $19; 264. Despite this, income growth is mostly explained by social and locational fundamentals. Population growth also exhibits two distinct equilibria determined by a threshold value of 116,300 inhabitants beyond which city population grows at a higher rate. Income and population growth do not go hand in hand, implying an optimal level of population beyond which income growth stagnates or deteriorates

What underlies localization and urbanization economies? Evidence from the location of new firms

The objective of this paper is to analyze why firms in some industries locate in specialized economic environments (localization economies) while those in other industries prefer large city locations (urbanization economies). To this end, we examine the location decisions of new manufacturing firms in Spain at the city level and for narrowly defined industries (three-digit level). First, we estimate firm location models to obtain estimates that reflect the importance of localization and urbanization economies in each industry. In a second step, we regress these estimates on industry characteristics that are related to the potential importance of three agglomeration theories, namely, labor market pooling, input sharing and knowledge spillovers. Localization effects are low and urbanization effects are high in knowledge-intensive industries, suggesting that firms (partly) locate in large cities to reap the benefits of inter-industry knowledge spillovers. We also find that localization effects are high in industries that employ workers whose skills are more industry-specific, suggesting that industries (partly) locate in specialized economic environments to share a common pool of specialized workers.

Application for fault location in electrical power distribution systems

Fault location has been studied deeply for transmission lines due to its importance in power systems. Nowadays the problem of fault location on distribution systems is receiving special attention mainly because of the power quality regulations. In this context, this paper presents an application software developed in Matlabtrade that automatically calculates the location of a fault in a distribution power system, starting from voltages and currents measured at the line terminal and the model of the distribution power system data. The application is based on a N-ary tree structure, which is suitable to be used in this application due to the highly branched and the non- homogeneity nature of the distribution systems, and has been developed for single-phase, two-phase, two-phase-to-ground, and three-phase faults. The implemented application is tested by using fault data in a real electrical distribution power system

Two methods for voltage sag source location

This paper presents and compares two approaches to estimate the origin (upstream or downstream) of voltage sag registered in distribution substations. The first approach is based on the application of a single rule dealing with features extracted from the impedances during the fault whereas the second method exploit the variability of waveforms from an statistical point of view. Both approaches have been tested with voltage sags registered in distribution substations and advantages, drawbacks and comparative results are presented

Estimation of zero-sequence impedance of undergrounds cables for single-phase fault location in distribution systems with electric arc

This paper focus on the problem of locating single-phase faults in mixed distribution electric systems, with overhead lines and underground cables, using voltage and current measurements at the sending-end and sequence model of the network. Since calculating series impedance for underground cables is not as simple as in the case of overhead lines, the paper proposes a methodology to obtain an estimation of zero-sequence impedance of underground cables starting from previous single-faults occurred in the system, in which an electric arc occurred at the fault location. For this reason, the signal is previously pretreated to eliminate its peaks voltage and the analysis can be done working with a signal as close as a sinus wave as possible

A hybrid method for sag source location in power network

The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

Decision Support Methods for Global Optomization

Immobile location-allocation (LA) problems is a type of LA problem that consists in determining the service each facility should offer in order to optimize some criterion (like the global demand), given the positions of the facilities and the customers. Due to the complexity of the problem, i.e. it is a combinatorial problem (where is the number of possible services and the number of facilities) with a non-convex search space with several sub-optimums, traditional methods cannot be applied directly to optimize this problem. Thus we proposed the use of clustering analysis to convert the initial problem into several smaller sub-problems. By this way, we presented and analyzed the suitability of some clustering methods to partition the commented LA problem. Then we explored the use of some metaheuristic techniques such as genetic algorithms, simulated annealing or cuckoo search in order to solve the sub-problems after the clustering analysis