66 resultados para Location of Zeros
em Consorci de Serveis Universitaris de Catalunya (CSUC), Spain
Resumo:
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.
Resumo:
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.
Resumo:
We offer a formulation that locates hubs on a network in a competitiveenvironment; that is, customer capture is sought, which happenswhenever the location of a new hub results in a reduction of thecurrent cost (time, distance) needed by the traffic that goes from thespecified origin to the specified destination.The formulation presented here reduces the number of variables andconstraints as compared to existing covering models. This model issuited for both air passenger and cargo transportation.In this model, each origin-destination flow can go through either oneor two hubs, and each demand point can be assigned to more than a hub,depending on the different destinations of its traffic. Links(``spokes'' have no capacity limit. Computational experience is provided.
Resumo:
We propose a model and solution methods, for locating a fixed number ofmultiple-server, congestible common service centers or congestible publicfacilities. Locations are chosen so to minimize consumers congestion (orqueuing) and travel costs, considering that all the demand must be served.Customers choose the facilities to which they travel in order to receiveservice at minimum travel and congestion cost. As a proxy for thiscriterion, total travel and waiting costs are minimized. The travel costis a general function of the origin and destination of the demand, whilethe congestion cost is a general function of the number of customers inqueue at the facilities.
Resumo:
The results of the application of the geophysical electromagnetic prospection methods in the resolution of the problems of the spatial location of the travertine quaternary formations of the Banyoles depression are presented
Resumo:
The objective of this paper is to explore the relative importance of each of Marshall's agglomeration mechanisms by examining the location of new manufacturing firms in Spain. In particular, we estimate the count of new firms by industry and location as a function of (pre-determined) local employment levels in industries that: 1) use similar workers (labor market pooling); 2) have a customer- supplier relationship (input sharing); and 3) use similar technologies (knowledge spillovers). We examine the variation in the creation of new firms across cities and across municipalities within large cities to shed light on the geographical scope of each of the three agglomeration mechanisms. We find evidence of all three agglomeration mechanisms, although their incidence differs depending on the geographical scale of the analysis.
Resumo:
The objective of this paper is to explore the relative importance of each of Marshall's agglomeration mechanisms by examining the location of new manufacturing firms in Spain. In particular, we estimate the count of new firms by industry and location as a function of (pre-determined) local employment levels in industries that: 1) use similar workers (labor market pooling); 2) have a customer- supplier relationship (input sharing); and 3) use similar technologies (knowledge spillovers). We examine the variation in the creation of new firms across cities and across municipalities within large cities to shed light on the geographical scope of each of the three agglomeration mechanisms. We find evidence of all three agglomeration mechanisms, although their incidence differs depending on the geographical scale of the analysis.
Resumo:
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.
Resumo:
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.
Resumo:
As stated in Aitchison (1986), a proper study of relative variation in a compositional data set should be based on logratios, and dealing with logratios excludes dealing with zeros. Nevertheless, it is clear that zero observations might be present in real data sets, either because the corresponding part is completelyabsent –essential zeros– or because it is below detection limit –rounded zeros. Because the second kind of zeros is usually understood as “a trace too small to measure”, it seems reasonable to replace them by a suitable small value, and this has been the traditional approach. As stated, e.g. by Tauber (1999) and byMartín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000), the principal problem in compositional data analysis is related to rounded zeros. One should be careful to use a replacement strategy that does not seriously distort the general structure of the data. In particular, the covariance structure of the involvedparts –and thus the metric properties– should be preserved, as otherwise further analysis on subpopulations could be misleading. Following this point of view, a non-parametric imputation method isintroduced in Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2000). This method is analyzed in depth by Martín-Fernández, Barceló-Vidal, and Pawlowsky-Glahn (2003) where it is shown that thetheoretical drawbacks of the additive zero replacement method proposed in Aitchison (1986) can be overcome using a new multiplicative approach on the non-zero parts of a composition. The new approachhas reasonable properties from a compositional point of view. In particular, it is “natural” in the sense thatit recovers the “true” composition if replacement values are identical to the missing values, and it is coherent with the basic operations on the simplex. This coherence implies that the covariance structure of subcompositions with no zeros is preserved. As a generalization of the multiplicative replacement, in thesame paper a substitution method for missing values on compositional data sets is introduced
Resumo:
This paper examines competition in a spatial model of two-candidate elections, where one candidate enjoys a quality advantage over the other candidate. The candidates care about winning and also have policy preferences. There is two-dimensional private information. Candidate ideal points as well as their tradeoffs between policy preferences and winning are private information. The distribution of this two-dimensional type is common knowledge. The location of the median voter's ideal point is uncertain, with a distribution that is commonly known by both candidates. Pure strategy equilibria always exist in this model. We characterize the effects of increased uncertainty about the median voter, the effect of candidate policy preferences, and the effects of changes in the distribution of private information. We prove that the distribution of candidate policies approaches the mixed equilibrium of Aragones and Palfrey (2002a), when both candidates' weights on policy preferences go to zero.
Resumo:
When two candidates of different quality compete in a one dimensional policy space, the equilibrium outcomes are asymmetric and do not correspond to the median. There are three main effects. First, the better candidate adopts more centrist policies than the worse candidate. Second, the equilibrium is statistical, in the sense that it predicts a probability distribution of outcomes rather than a single degenerate outcome. Third, the equilibrium varies systematically with the level of uncertainty about the location of the median voter. We test these three predictions using laboratory experiments, and find strong support for all three. We also observe some biases and show that they canbe explained by quantal response equilibrium.
Resumo:
Maybe because of the inconclusive nature of the results on the impact of public capital on output at the regional level, the issue of the possible existence of the regional spillovers from public capital formation has received little attention. The objective of this paper is to provide evidence on the possible existence of such spillovers. We consider the case of Spain and its seventeen regions. Our methodological approach consists in estimating an aggregate VAR model for Spain as well as seventeen region-specific VAR models in which both capital installed in the region and capital installed outside the region are allowed to play a role in enhancing regional output. The estimation results can be summarized as follows. The aggregate effects of public capital formation in Spain are important. They cannot, however, be captured in their entirety by the direct effects in each region from public capital installed in the region itself. When for each region both the capital installed in the region and the capital installed outside the region are considered the total disaggregated effect from the seventeen regional models are very much in line with the aggregate results. Furthermore, the aggregate effect seems to be due in almost equal parts to the direct and spillover effects of public capital formation. Ultimately, this paper establishes the relevance of both capital installed in each region and spillover effects in the understanding of the regional decomposition of the aggregate effects of public capital formation. In doing so it opens the door to some tantalizing and potentially highly charged research issues in terms of the determination of the optimal location of public investment projects.
Resumo:
The aim of this article is to assess the effects of several territorial characteristics, specifically agglomeration economies, on industrial location processes in the Spanish region of Catalonia. Theoretically, the level of agglomeration causes economies which favour the location of new establishments, but an excessive level of agglomeration might cause diseconomies, since congestion effects arise. The empirical evidence on this matter is inconclusive, probably because the models used so far are not suitable enough. We use a more flexible semiparametric specification, which allows us to study the nonlinear relationship between the different types of agglomeration levels and location processes. Our main statistical source is the REIC (Catalan Manufacturing Establishments Register), which has plant-level microdata on location of new industrial establishments. Keywords: agglomeration economies, industrial location, Generalized Additive Models, nonparametric estimation, count data models.