Giuseppe Arbia

Giuseppe Arbia
Catholic University of the Sacred Heart | UNICATT · Department of Statistical Science

Ph D Cantab

About

46
Publications
5,624
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1,464
Citations

Publications

Publications (46)
Article
Full-text available
This article proposes a new method for the estimation of the parameters of a simple linear regression model which accounts for the role of co-moments in non-Gaussian distributions being based on the minimization of a quartic loss function. Although the proposed method is very general, we examine its application to finance. In fact, in this field th...
Article
Spatial models have been widely applied in the context of growth regressions with spatial spillovers usually modelled by simultaneous autoregressions (SAR). Although largely used, such a class of models present some logical difficulties connected with the error behaviour, the lack of identifiability of the model parameters and their substantive int...
Article
Full-text available
This paper proposes a bivariate marginal likelihood specification of spatial econometrics models that simplifies the derivation of the log-likelihood and leads to a closed form expression for the estimation of the parameters. With respect to the more traditional specifications of spatial autoregressive models, our method avoids the arbitrariness of...
Article
Why do industrial clusters occur in space? Is it because industries need to stay close together to interact or, conversely, because they concentrate in certain portions of space to exploit favourable conditions like public incentives, proximity to communication networks, to big population concentrations or to reduce transport costs? This is a funda...
Article
Abstract The Spatial Econometrics Association appeared on the scene only five years ago during a time of unprecedented expansion of research activities in the field. This paper tries to summarize the developments that occurred in this first lustrum of life of the Association. The review considers more than 230 papers that appeared in the last five...
Article
The modifiable areal unit problem refers to the modifications of any statistical analysis when changing the scale of observation (e.g. from region to countries) or the aggregation criterion (e.g. different partitions of one country at a given scale). In a previous work (Arbia in Spatial data configuration in the statistical analysis of regional eco...
Article
This paper considers the standard error of the estimate of the mean of a spatially correlated variable in the case where data are obtained by a process of random sampling. Two distinct mean estimation problems are identified: estimating the area mean and estimating the population mean. Methods are described for obtaining standard error estimates in...
Article
Full-text available
Negative spatial autocorrelation refers to a geographic distribution of values, or a map pattern, in which the neighbors of locations with large values have small values, the neighbors of locations with intermediate values have intermediate values, and the neighbors of locations with small values have large values. Little is known about negative sp...
Article
The study of the pollutants needs a better understanding of their extreme behaviours which could potentially cause adverse health effects. When analysing spatial dependence of the pollutant, the dependogram proposed by Arbia and Lafratta is preferred to the traditional correlogram used in the spatial statistics literature because it captures nonlin...
Chapter
The aim of this chapter is to present a class of statistical models to study the location of economic agents and their geographical concentration and explain their spatial interacting behaviour. Traditionally, the problem of the spatial location of economic activities has been approached in three different ways.
Article
A spatial sampling strategy is proposed for monitoring the exceedances of soil pollutants over a given regulatory threshold in a discretized three-dimensional (3-D) portion of space. In each site of the study area, an indicator variable is defined assuming a value of 1 if the threshold is exceeded and 0 otherwise. The spatial distribution of such v...
Article
This paper examines stochastic convergence in real per capita GDP for Italian regions using recent non-stationary panel data methodologies over the period 1951 to 2002. Economies stochastically converge when regional differences across economies are not persistent, and long-run movements in a region's real per capita GDP are driven by technological...
Article
In many instances it is of interest to measure the degree of similarity between neighboring regions. Spatial autocorrelation measures are the most popular means of doing it. However, such measures only capture a global linear relationship between regions, whereas in many circumstances a more general instrument is required. For instance, in economic...
Article
Full-text available
Las aproximaciones estándar utilizadas en la literatura empírica para contrastar la convergencia divergencia económica entre los países y regiones están todas relacionadas con las contribuciones de MankiW-ROmerWeil y Barro-Sala-i-Martin que llevan al celebrado modelo de b convergencia. Tal modelo, sin embargo, presenta fuertes limitaciones. Este pa...
Article
In this paper we start from a continuous time framework derived from the classical predator-prey model in order to analyze the recent dynamics of regional evolution in the EU. The model describes a system of interrelated units obeying a complex functional dynamics that at any moment may encompass divergent forces. After briefly reviewing the modeli...
Article
In this article, the authors use a continuous-time framework to model the potential convergence dynamics in a group of regions. They propose a model based on the classical Lotka-Volterra predator-prey system of two equations—a model originally proposed by Samuelson in 1971 to perform dynamic economic analysis—and extend the model to the case of mor...
Article
Full-text available
The collection of accurate and timely information on land use, crops, forest and vegetation are increasingly based on remote sensing spectral measurements produced by satellites. The most recent spacecrafts like the Earth Observing 1 (EO-1) produce a rich source of information being endowed with hyperspectral sensors that can provide up to 200 or m...
Article
Full-text available
In many empirical studies spatial correlations are used to identify the distance above which dependency is negligible, to assist the choice in locating a systematic grid of sample points in ground surveys. However, estimates are undermined by the fact that our inference is based on satellite data that are only an approximation of the ground truth,...
Article
Isotropic processes form an inadequate basis in modelling many spatially distributed data. In particular environmental phenomena often have strong anisotropic spatial variation, especially when the regions monitored are very large. We extend a recently proposed optimal sampling strategy by assuming a spatial anisotropic random field as the basis fo...
Article
Full-text available
In this paper we extend the concept of Value-at-risk (VaR) to bivariate return distributions in order to obtain measures of the market risk of an asset taking into account additional features linked to downside risk exposure. We first present a general definition of risk as the probability of an adverse event over a random distribution and we then...
Article
Full-text available
. Economists have recently devoted an increasing attention to the issue of spatial concentration of economic activities. However, surprisingly enough, most of the empirical work is still based on the computation of very basic statistical measures in which the geographical characteristics of data play no role. By making use of a series of empirical...
Article
Full-text available
In the present article we propose a spatial micro econometric approach for studying the geographical concentration of economic activities. We analyse the incentives to use this approach rather than the traditional one based on regional aggregates. As an example, we present our prototypical theoretic model - to be seen as a continuous space version...
Article
Full-text available
In this paper we extend the concept of Value-at-risk (VaR) to bivariate return distributions in order to obtain measures of the market risk of an asset taking into account additional features linked to downside risk exposure. We first present a general definition of risk as the probability of an adverse event over a random distribution and we then...
Article
Full-text available
The purpose of this paper is to identify error properties arising when source maps that individually contain error are added or when the ratio of one map with respect to another is computed. The research approach to the problem combines mathematical analysis and simulation where source maps and error processes have been constructed with specified p...
Article
Full-text available
Performing data manipulations on maps that possess error as a result of the process of data collection leads to error propagation. The errors that are present in maps are modified by such operations in ways that may undermine the purposeofanalysisand lead to increased uncertainty in thevalidity ofthe conclusions that are drawn. This paper analyses...
Article
In many repeated environmental surveys, data are collected in space without a rigorous statistical design, based only on practical circumstances such as social importance of the site, availability of space, or nearness to main roads. Furthermore, the sample size is usually fixed because of financial constraints. Given these conditions, two issues a...
Article
The aim of this paper is to introduce a class of testable statistical models aimed at modelling archaeological sites locations (ASL) or a continuous space and at producing probability maps of ASL. These models are based on collected statistical and auxiliary information (such as information about the slope or exposure of the land, the topography, t...
Article
This paper analyses the effects of the modifiable areal unit problem (MAUP) on the accuracy of maximum likelihood (ML) classification of categorical multispectral images. By looking at a series of simulated experiments we extend the traditional analysis of the effects of MAUP on the basic statistical measures to cases when an image consists of cate...
Article
Forecasting statistical models are becoming increasingly important in archaeological research. One of the reasons of this popularity is that archaeological sites tend to present themselves in particular environments so that forecasting models can help in identifying areas where the probability is higher based on previously collected statistical inf...
Article
In image processing and geographic information systems, a new map is constructed by carrying out a sequence of operations on a set of source maps. These operations typically include the adding, ratioing, and overlaying (or buffering) of two or more maps. But each source map may contain error. There may be error associated with measuring attribute v...
Article
The paper is divided into three parts. The first part reviews GIS technologies as essential background to the remainder of the paper. The second part of the paper aims to show the impact and potential of employing GIS technologies in survey processing and, in particular, in survey design. We show how, by employing a GIS-assisted computer-intensive...
Chapter
Statistical data in economic modelling are constituted as a role by aggregation of individual characteristics over time (Granger, 1987, 1988; Lütkpohl, 1985), space (Arbia, 1989) and individual decision makers (Granger, 1988). Examples include the Gross National Product as the sum of the Gross Regional Products, the total consumption as the sum of...
Article
In this paper, we consider the problem of estimating the unknown parameters of non-stationary spatial process when only a single replication of the process is available. The approach suggested here to overcome the problem of estimating a number of parameters a lot larger than the number of observations, is based upon the general idea of resampling....

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