Local weighting or the necessity of flexibility

The local estimation algorithms are well-known techniques in the current spatial econometric literature. The Geographically Weighted Regressions are very popular to estimate, locally, static models, whereas the SALE or the Zoom approaches are useful solutions in the case of dynamic models. These techniques are well founded from a methodological point of view and present interesting properties. However, Farber and Paez (2008) detect some inconsistencies in the behavior of some of these algorithms that claim for a further analysis. The point that we want to study in this paper refers to the role of the bandwith. This measure defines how many neighbors will be used in the estimation of the local parameters corresponding to each observation. The cross-validation is the most popular criteria to fix the bandwith, although there are several other criteria in the literature. We think that there is a basic problem with this approach. The objective of these algorithms is to relax the restriction of homogeneity of the parameters of the model allowing for local peculiarities; however the definition of local neighborhood is the same. It does not matter if the observation corresponds to an isolated and poorly communicated region or it belongs to a central and highly connected point. According to our view, this is a very restrictive decision that should be avoided. Specifically, we discuss the procedure of specifying the sequence of local weighting matrices that will be used in the analysis. Our purpose is to achieve that these matrices also reflect the local surrounding of each observation. We examine two different strategies in order to construct the local weighting matrices. The first is a parametric approach which involves the J test, as presented by Kelejian (2008), and the second is a nonparametric approach that uses the guidance of the symbolic entropy measures. The first part of the paper presents the overall problem, including a review of the literature; we discuss the solutions in the second part and the third part consists of a Monte Carlo simulation.

Comparison of Thematic Maps Using Symbolic Entropy

Comparison of thematic maps is an important task in a number of disciplines. Map comparison has traditionally been conducted using cell-by-cell agreement indicators, such as the Kappa measure. More recently, other methods have been proposed that take into account not only spatially coincident cells in two maps, but also their surroundings or the spatial structure of their differences. The objective of this paper is to propose a framework for map comparison that considers 1) the patterns of spatial association in two maps, in other words, the map elements in their surroundings; 2) the equivalence of those patterns; and 3) the independence of patterns between maps. Two new statistics for the spatial analysis of qualitative data are introduced. These statistics are based on the symbolic entropy of the maps, and function as measures of map compositional equivalence and independence. As well, all inferential elements to conduct hypothesis testing are developed. The framework is illustrated using real and synthetic maps. Key word: Thematic maps, map comparison, qualitative variables, spatial association, symbolic entropy, hypothesis tests

Local weighting or the necessity of flexibility

The local estimation algorithms are well-known techniques in the current spatial econometric literature. The Geographically Weighted Regressions are very popular to estimate, locally, static models, whereas the SALE or the Zoom approaches are useful solutions in the case of dynamic models. These techniques are well founded from a methodological point of view and present interesting properties. However, Farber and Paez (2008) detect some inconsistencies in the behavior of some of these algorithms that claim for a further analysis. The point that we want to study in this paper refers to the role of the bandwith. This measure defines how many neighbors will be used in the estimation of the local parameters corresponding to each observation. The cross-validation is the most popular criteria to fix the bandwith, although there are several other criteria in the literature. We think that there is a basic problem with this approach. The objective of these algorithms is to relax the restriction of homogeneity of the parameters of the model allowing for local peculiarities; however the definition of local neighborhood is the same. It does not matter if the observation corresponds to an isolated and poorly communicated region or it belongs to a central and highly connected point. According to our view, this is a very restrictive decision that should be avoided. Specifically, we discuss the procedure of specifying the sequence of local weighting matrices that will be used in the analysis. Our purpose is to achieve that these matrices also reflect the local surrounding of each observation. We examine two different strategies in order to construct the local weighting matrices. The first is a parametric approach which involves the J test, as presented by Kelejian (2008), and the second is a nonparametric approach that uses the guidance of the symbolic entropy measures. The first part of the paper presents the overall problem, including a review of the literature; we discuss the solutions in the second part and the third part consists of a Monte Carlo simulation

Development of a new framework to guide, assess, and evaluate student reflections in a university sustainability course

Many institutions of higher education increasingly place a focus on various forms of experiential education. While much work has been done in this and related areas, the resources currently available are not sufficient to effectively guide, assess, and evaluate student learning. Personal reflections can be used as a tool to assess student learning through experience. However, guiding students through the process, assessing their work, and providing an evaluation presents challenges for educators. A new framework, a robust rubric, and a guide that students and evaluators can use to support experiential learning through reflection are provided. The framework and resources are based on a grounded investigation of student reflections, which were compared to various evaluation models from the literature. The resources discussed in this paper have already been used in practice for over four years and with over 1,000 students. The purpose of this paper is to describe the journey leading to the development of this framework, to provide a description of the rubric and guide, and to share the lessons learned. This framework and accompanying materials will hopefully be a useful resource for instructors and students wishing to support reflection and experiential learning

Regional dimensions of infant mortality rate in Brazil, 1980-2000

Development can be understood from many perspectives. Among those, the one proposed by Amartya Sen states that a development policy should aim at expanding the freedom of individuals, and this goal can be achieved by the expansion of capabilities. With this conceptual framework in mind, health, more specifically infant mortality, is chosen as a measure of development and as the object of study. The Government should guarantee the provision of health services, as they consist in meritory goods. Mosley and Chen (1984) propose a theoretical framework to study infant mortality based on the proximal determinants, in which the socioeconomic factors affect the result observed indirectly. In Brazil there has been a substantial reduction of the average levels of infant mortality rates in the last decades. However, there is still a significant regional inequality. Econometric models for 1980, 1991 and 2000 are estimated including a spatial filter in order to account for the spatial dependency observed in the data. The study concludes that health infrastructure lost its explanative power for the differences in infant mortality rate among the localities. On the other hand, socioeconomic variables have become more relevant and significant. It means that future public policies must try to improve the access of the families to public facilities, reduce poverty and inequality and improve educational levels. Therefore, the family-based prevention against health problems should be stimulated, helping to avoid premature death

Inducing Non-Orthogonal and Non-Linear Decision Boundaries in Decision Trees via Interactive Basis Functions

© 2019. This document is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This document is the submitted version of a published work that appeared in final form in Expert Systems with ApplicationsWe use a local projection approach to analyze the effect of economic recessions on income inequality in a comprehensive sample of 43 countries from 1960 to 2016. Although we consider both business-cycle and growth-cycle recessions, we fail to find evidence of significant positive impacts of economic downturns on income distribution, once controls are added to the model. However, we do find important differences across countries, which mainly depend on the degree of economic development

Transportation infrastructure impacts on firm location: the effect of a new metro line in the suburbs of Madrid

Firm location patterns emerge as a consequence of multiple factors, including firm considerations, labor force availability, market opportunities, and transportation costs. Many of these factors are influenced by changes in accessibility wrought by new transportation infrastructure. In this paper we use spatial statistical techniques and a micro-level data base to evaluate the effects of Madrid?s metro line 12 (known as Metrosur) expansion on business location patterns. The case study is the municipality of Alcorcon, which is served by the new metro line since 2003. Specifically, we explore the location patterns by different industry sectors, to evaluate if the new metro line has encouraged the emergence of a ?Metrosur spatial economy?. Our results indicate that the pattern of economic activity location is related to urban accessibility and that agglomeration, through economies of scale, also plays an important role. The results presented in this paper provide evidence useful to inform efficient transportation, urban, and regional economic planning