Rosa Bernardini Papalia

University of Bologna | UNIBO · "Paolo Fortunati" Department of Statistical Sciences STAT

The analysis of environmental issues and the pursuit of environmental justice have gained significant attention in modern times. While progress has been made in understanding environmental impacts and establishing the right to access environmental information, the need to examine environmental inequalities persists. This study aimed to propose a me...

Crop quality and productivity are the fundamental strategies of agricultural practice and technology; consequently, one of the priorities in agriculture is to be aware of new and innovative field experiments and production practices. The effectiveness of innovative practices and resources is influenced by a multitude of factors. This study aimed to...

Statistical information for empirical analysis is frequently available at a higher level of aggregation than is desired. The spatial disaggregation of the socioeconomic data is considered complex due to the inherent spatial properties and relationships of the spatial data, namely, spatial dependence and spatial heterogeneity. The spatial dependence...

Info-metrics is a framework for modeling, reasoning, and drawing inferences under conditions of noisy and insufficient information. It is an interdisciplinary framework situated at the intersection of information theory, statistical inference, and decision-making under uncertainty. In a recent book on the Foundations of Info-Metrics, Golan (OUP, 20...

Information-based estimation techniques are becoming more popular in the field of Ecological Inference. Within this branch of estimation techniques, two alternative approaches can be pointed out. The first one is the Generalized Maximum Entropy (GME) approach based on a matrix adjustment problem where the only observable information is given by the...

This paper assesses whether there might be complementarities between different types of innovation activities (product, process and organizational) and how these effects may be linked to the likelihood that a firm will export. Complementarity is addressed through the properties of supermodular functions, and firm heterogeneity by export destination...

Small area estimation techniques are becoming increasingly used in survey applications to provide estimates for local areas of interest. The objective of this article is to develop and apply Information Theoretic (IT)-based formulations to estimate small area business and trade statistics. More specifically, we propose a Generalized Maximum Entropy...

This paper contributes to the explanation of international trade flows with structural gravity models taking heterogeneity and excess zeroes into account. We introduce a more general hypothesis on the structure of trade costs in Helpman et al. (2008) theoretical model that is capable of explaining over-dispersion in trade data. Zero inflated negati...

The focus of this paper is on Spatial Structural Equation Models (S-SEM) also extended to a Panel data framework. More specifically, our ob- jective is to introduce a Generalized Maximum Entropy formulation for the class of spatial structural equations models with the aim of developing a com- posite index. We present an application of the method to...

In this paper we study the potentialities of a multivariate index approach for measuring competitiveness. Our proposal aims at developing a multidimensional economic performance index that could be used to measure and compare competitiveness at different level of aggregation (country, region or sector) with a micro-level foundation. The basic idea...

This article deals with heterogeneity and spatial dependence in economic growth analysis by developing a two-stage strategy that identifies clubs by a mapping analysis and estimates a club convergence model with spatial dependence. Since estimation of this class of convergence models in the presence of regional heterogeneity poses both identificati...

This paper deals with heterogeneity and nonlinearities in the growth process by developing a two-stage strategy to identify and estimate a club convergence model with threshold externalities. Because of identification and collinearity problems, we develop an entropy-based estimation procedure which simultaneously takes account of ill-posed and ill-...

The objective of this paper is to develop a GME formulation for the class of spatial structural equations models (S-SEM). In this respect, two innovatory aspects are introduced: (i) the formalization of the GME estimation approach for structural equations models that account for spatial heterogeneity and spatial dependence; (ii) the extension of th...

In this paper, we study the relationship between the level of development of an economy and returns to different levels of education for the panel of OECD countries over the 1965-2004 period, in a club convergence framework. The connection between growth and human capital measures of primary, secondary and tertiary education in a multiple-club spat...

This paper introduces Information Theoretic – based methods for estimating a target variable in a set of small geographical areas, by exploring spatially heterogeneous relationships at the disaggregate level. Controlling for spatial effects means introducing models whereby the assumption is that values in adjacent geographic locations are linked...

The aim of this paper is to formulate an analytical-informational-theoretical approach which, given the incomplete nature of the available micro-level data, can be used to provide disaggregated values of a given variable. A functional relationship between the variable to be disaggregated and the available variables/indicators at the area level is s...

This paper introduces an Information Theory-based method for modeling economic aggregates and estimating their sub-group (sub-area) decomposition when no individual or sub-group data are available. This method offers a flexible framework for modeling the underlying variation in sub-group indicators, by addressing the spatial dependency problem. A b...

Using the idea of the multidimensional generalization of the Duncans' index, the productivity per worker differentials across groups of firms can be decomposed into different components attributed to differences in: sectoral productivity, investment in human and physical capital, size and other determinants. More specifically, for decomposing group...

Flow data are viewed as cross-classified data, and spatial interaction models are reformulated as log-linear models. According to this view, we introduce a spatial panel data model and we derive a Generalized Maximum Entropy - based estimation formulation. The estimator we propose has the advantage of being consistent with the underlying data gener...

Using the idea of the multidimensional generalization of the Duncans' index (Silber 1992), the productivity per worker differentials across groups of firms can be decomposed into different components attributed to differences in: sectoral productivity, investment in human and physical capital, size and other determinants. More specifically, for dec...

The article aims at providing a suitable measure of total factor productivity (TFP) levels within the conditional convergence framework by introducing unobserved heterogeneity in terms of a "mapping model". Our goal is twofold. First, we develop a generalized maximum entropy estimation procedure to account for ill-posed and ill-conditioned inferenc...

Flow data are viewed as cross-classified data, and spatial interaction models are reformulated as log-linear models. According to this view, we introduce a spatial panel data model and we derive a Generalized Maximum Entropy - based estimation formulation. The estimator we propose has the advantage of being consistent with the underlying data gener...

The objective of this paper is to test for the importance of local agglomeration externalities in determining inward foreign direct investment (FDI) intensity, viewed as a measure of regional attractiveness to FDI. The links between the degree of FDI inflow penetration into Italy and its determinants at the regional level are examined using alterna...

This paper introduces an entropy-based estimation strategy for spatial heterogeneous panel data models where separate processes for each unit are considered. The starting point is a general model specification which account for both temporal and spatial lagged effects in a panel data context by treating individual relationships as a system of seemi...

The need of security for messages transferred between two entities in computer network is a reality. Many algorithms use text key's with variable length of them. This paper propose an algorithm that use like encoding key a part of an image. For an image ...

In this study we examine regional data on per worker GDP, disaggregated at sectoral level, by focusing our interest on the role of differences in the sectoral composition of activities, and in productivity gaps that are uniform across sectors, in explaining the catching-up process, which is realized through physical and human capital as well as tec...

Flow data are viewed as cross-classified data, and spatial interaction models are reformulated as log-linear models. According to this view, we introduce a spatial panel data model and we derive a Generalized Maximum Entropy-based estimation approach. The estimator has the advantage of being consistent with the underlying data generation process an...

This article introduces a maximum entropy-based estimation methodology that can be used both to represent the uncertainty of a partial-incomplete economic data generation process and to consider the direct influence of learning from repeated samples. Then, a composite cross-entropy estimator, incorporating information from a subpopulation based on...

The regional Consumer Price Index (CPI) is an issue of great interest to measure the price movements for a specific local area of interest and can be used: (i) to deflate monetary measures of household living standards, and (ii) to update poverty lines, at a regional level. The issue that consumer price index bias may affect the measurement of the...

In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information and learning from repeated samples. The basis for this method has its roots in information theory and builds on the classical maximum entropy work of Janes (1957). We illustrate the use of this approach, describe how to impose restrictions on the esti...

In this study, an alternative estimation strategy is suggested, which requires the solution of a dynamic programming problem, expressed in term of conditional choice value functions. The problem of defining the Euler equation for the corner solution case is overcome by introducing an additional constraint on the conditional choice value functions,...

In this paper a logarithmic transformation of the standard Tobit model is proposed. The model represents an interesting tool in order to specify alternative form of data heterosckedasticity. The properties of applied estimators are compared by a set of Monte Carlo experiments.

This paper presents and applies a local generalized method of moments (LGMM) estimator for regression functions. The method is an extension of previous results obtained bu P. L. Gozalo and O. Linton [Local nonlinear least squares estimation: Using parametric estimation nonparametrically. Mimeo (1995)]. The LGMM estimation procedure can be applied t...

The aim of this paper is to study the probability to find an opportunity of collaboration among small and medium sized firms by participating in the Europartenariat meeting created to encourage co-operation links. Contacts among firms are relatively few in number and are assumed to be generated by a Poisson process. Empirical results of different P...

A theoretical search model applied to collaboration among firms with a public authority as an intermediate is the primary issue of this paper. Specifically, we consider the Europartenariat event since it represents a good opportunity to study a problem of interaction between the decision to search a collaboration and the exchange of information inv...

L'obiettivo di questo lavoro è la ricerca di un modello delle esportazioni italiane dei prodotti trasformati del grano duro, in particolare pasta e semola. La specificazione del modello qui utilizzato è quella proposta da Goldstein e Khan (1978). Più specificatamente si intende stimare un modello di error correction sulla base di una generalizzazio...

This paper proposes a maximum entropy (ME) - based method for modeling economic aggregates and estimating their sub- group (sub-area) decomposition when no individual or sub- group data are available. This method also offers a tractable framework for modeling the underlying variation in sub-group indicators. A basic ecological inference problem whi...

This paper assess the existence of club convergence across OECD over the period 1965-2004 by developing a two stage strategy, which employs information on clustering schemes -identified by a mapping analysis -and estimates a multiple equation dynamic panel model with non linearities and spatial dependence. Because of identification and collinearity...

Using the idea of the multidimensional generalization of the Duncans’ index (Silber 1992), the productivity per worker differential across groups of firms can be decomposed into different components attributed to differences in: sectoral productivity, investment in human and physical capital, employment and other determinants. More specifically, fo...

In this study we illustrate a Maximum Entropy (ME) methodology for modeling incomplete information and learning from repeated samples. The basis for this method has its roots in information theory and builds on the classical maximum entropy work of Janes (1957). We illustrate the use of this approach, describe how to impose restrictions on the esti...