Spatial models for flood risk assessment

The problem of computing risk measures associated to flood events is extremely important not only from the point of view of civil protection systems but also because of the necessity for the municipalities of insuring against the damages. In this work we propose, in the framework of an integrated strategy, an operating solution which merges in a conditional approach the information usually available in this setup. First we use a Logistic Auto-Logistic (LAM) model for the estimation of the univariate conditional probabilities of flood events. This approach has two fundamental advantages: it allows to incorporate auxiliary information and does not require the target variables to be independent. Then we simulate the joint distribution of floodings by means of the Gibbs Sampler. Finally we propose an algorithm to increase ex post the spatial autocorrelation of the simulated events. The methodology is shown to be effective by means of an application to the estimation of the flood probability of Italian hydrographic regions

A Monte Carlo EM Algorithm for the Estimation of a Logistic Auto-logistic Model with Missing Data

This paper proposes an algorithm for the estimation of the parameters of a Logistic Auto-logistic Model when some values of the target variable are missing at random but the auxiliary information is known for the same areas. First, we derive a Monte Carlo EM algorithm in the setup of maximum pseudo-likelihood estimation; given the analytical intractability of the conditional expectation of the complete pseudo-likelihood function, we implement the E-step by means of Monte Carlo simulation. Second, we give an example using a simulated dataset. Finally, a comparison with the standard non-missing data case shows that the algorithm gives consistent results.Spatial Missing Data, Monte Carlo EM Algorithm, Logistic Auto-logistic Model, Pseudo-Likelihood.

A class of spatial econometric methods in the empirical analysis of clusters of firms in the space

In this paper we aim at identifying stylized facts in order to suggest adequate models of spatial co–agglomeration of industries. We describe a class of spatial statistical methods to be used in the empirical analysis of spatial clusters. Compared to previous contributions using point pattern methods, the main innovation of the present paper is to consider clustering for bivariate (rather than univariate) distributions, which allows uncovering co–agglomeration and repulsion phenomena between the different industrial sectors. Furthermore we present the results of an empirical application of such methods to a set of European Patent Office (EPO) data and we produce a series of empirical evidences referred to the the pair–wise intra–sectoral spatial distribution of patents in Italy in the nineties. In this analysis we are able to identify some distinctive joint patterns of location between patents of different sectors and to propose some possible economic interpretations

R&D, firm size, and product innovation dynamics.

This paper addresses a debated issue in the economics innovation literature, namely the existence of increasing return to R&D expenditures and firm size on innovation output. It further explores how structural characteristics of the firm as well as contextual factors affect the dynamics of product innovation over a relatively long period of time. Taking advantage of an original and unique database comprising innovation data recorded on a monthly base we show that: (i) a negative binomial distribution model is able to predict with great accuracy the probability of having a given number of product announcement sent out in a month; (ii) constant returns to size and R&D expenditure may reasonably characterize the innovation production function of sampled firms; (iii) vertically integrated manufacturers as well as producers operating a larger product portfolio exhibit a higher propensity to introduce new products than their specialized competitors.

Weighting Ripley’s K-function to account for the firm dimension in the analysis of spatial concentration

The spatial concentration of firms has long been a central issue in economics both under the theoretical and the applied point of view due mainly to the important policy implications. A popular approach to its measurement, which does not suffer from the problem of the arbitrariness of the regional boundaries, makes use of micro data and looks at the firms as if they were dimensionless points distributed in the economic space. However in practical circumstances the points (firms) observed in the economic space are far from being dimensionless and are conversely characterized by different dimension in terms of the number of employees, the product, the capital and so on. In the literature, the works that originally introduce such an approach (e.g. Arbia and Espa, 1996; Marcon and Puech, 2003) disregard the aspect of the different firm dimension and ignore the fact that a high degree of spatial concentration may result from both the case of many small points clustering in definite portions of space and from only few large points clustering together (e.g. few large firms). We refer to this phenomena as to clustering of firms and clustering of economic activities. The present paper aims at tackling this problem by adapting the popular Kfunction (Ripley, 1977) to account for the point dimension using the framework of marked point process theory (Penttinen, 2006)Agglomeration, Marked point processes, Spatial clusters, Spatial econometrics

Three-dimensional structure of the flow inside the left ventricle of the human heart

The laboratory models of the human heart left ventricle developed in the last decades gave a valuable contribution to the comprehension of the role of the fluid dynamics in the cardiac function and to support the interpretation of the data obtained in vivo. Nevertheless, some questions are still open and new ones stem from the continuous improvements in the diagnostic imaging techniques. Many of these unresolved issues are related to the three-dimensional structure of the left-ventricular flow during the cardiac cycle. In this paper we investigated in detail this aspect using a laboratory model. The ventricle was simulated by a flexible sack varying its volume in time according to a physiologically shaped law. Velocities measured during several cycles on series of parallel planes, taken from two orthogonal points of view, were combined together in order to reconstruct the phase averaged, three-dimensional velocity field. During the diastole, three main steps are recognized in the evolution of the vortical structures: i) straight propagation in the direction of the long axis of a vortex-ring originated from the mitral orifice; ii) asymmetric development of the vortex-ring on an inclined plane; iii) single vortex formation. The analysis of three-dimensional data gives the experimental evidence of the reorganization of the flow in a single vortex persisting until the end of the diastole. This flow pattern seems to optimize the cardiac function since it directs velocity towards the aortic valve just before the systole and minimizes the fraction of blood residing within the ventricle for more cycles

R&D, Firm Size, and Product Innovation Dynamics.

This paper addresses a debated issue in the economics innovation literature, namely the existence of increasing return to R&D expenditures and sirm size on innovation output. It further explores how structural characteristics of the sirm as well as contextual factors affect the dynamics of product innovation over a relatively long period of time. Taking advantage of an original and unique database comprising innovation data recorded on a monthly base we show that: (i) a negative binomial distribution model is able to predict with great accuracy the probability of having a given number of product announcement sent out in a month; (ii) constant returns to size and R&D expenditure may reasonably characterize the innovation production function of sampled sirms; (iii) vertically integrated manufacturers as well as producers operating a larger product portfolio exhibit a higher propensity to introduce new products than their specialized competitors.