Finite Sample Properties of Moran's I Test for Spatial Autocorrelation in Probit and Tobit Models - Empirical Evidence

In this paper, we investigate the finite sample properties of Moran’s I test statistic for spatial autocorrelation in limited dependent variable models suggested by Kelejian and Prucha (2001). We analyze the socio- economic determinants of the availability of dialysis equipment in 5,507 Brazilian municipalities in 2009 by means of a probit and tobit specifica- tion. We assess the extent to which evidence of spatial autocorrelation can be remedied by the inclusion of spatial fixed effects. We find spa- tial autocorrelation in both model specifications. For the probit model, a spatial fixed effects approach removes evidence of spatial autocorrelation. However, this is not the case for the tobit specification. We further fill a void in the theoretical literature by investigating the finite sample prop- erties of these test statistics in a series of Monte Carlo simulations, using data sets ranging from 49 to 15,625 observations. We find that the tests are unbiased and have considerable power for even medium-sized sample sizes. Under the null hypothesis of no spatial autocorrelation, their em- pirical distribution cannot be distinguished from the asymptotic normal distribution, empirically confirming the theoretical results of Kelejian and Prucha (2001), although the sample size required to achieve this result is larger in the tobit case than in the probit case.

Advanced Trip Generation/Attraction Models

In this paper, advanced trip generation/attraction models are proposed. A multiple linear regression (MLR) model has been created from zonal data. These models are compared to each other by analyzing their hypothesis and the required adjustments. Additionally, advanced generation/attraction models considering spatial correlation are proposed, and their improvements with reference to previous models not considering spatial correlation are analyzed. A global spatial correlation model that conducts a joint review of every unit in the sample to determine whether the spatial units are randomly distributed or in accordance with a certain pattern is specified. To consider cluster situations in a given area, a local spatial correlation model aimed to measure the spatial autocorrelation to place each observation is defined. The models are applied to the Santander metropolitan area (in Spain) in order to obtain advanced generation/attraction models in that city. For Santander, the models considering spatial dependence among observations have better results than the MLR models.This work was made possible thanks to a grant from the Spanish Ministerio de Economía y Competitividad with additional financing from FEDER funds to the project TRA2012-3765

Exploring variations in childhood stunting in Nigeria using league table, control chart and spatial analysis

Background: Stunting, linear growth retardation is the best measure of child health inequalities as it captures multiple dimensions of children’s health, development and environment where they live. The developmental priorities and socially acceptable health norms and practices in various regions and states within Nigeria remains disaggregated and with this, comes the challenge of being able to ascertain which of the regions and states identifies with either high or low childhood stunting to further investigate the risk factors and make recommendations for action oriented policy decisions. Methods: We used data from the birth histories included in the 2008 Nigeria Demographic and Health Survey (DHS) to estimate childhood stunting. Stunting was defined as height for age below minus two standard deviations from the median height for age of the standard World Health Organization reference population. We plotted control charts of the proportion of childhood stunting for the 37 states (including federal capital, Abuja) in Nigeria. The Local Indicators of Spatial Association (LISA) were used as a measure of the overall clustering and is assessed by a test of a null hypothesis. Results: Childhood stunting is high in Nigeria with an average of about 39%. The percentage of children with stunting ranged from 11.5% in Anambra state to as high as 60% in Kebbi State. Ranking of states with respect to childhood stunting is as follows: Anambra and Lagos states had the least numbers with 11.5% and 16.8% respectively while Yobe, Zamfara, Katsina, Plateau and Kebbi had the highest (with more than 50% of their underfives having stunted growth). Conclusions: Childhood stunting is high in Nigeria and varied significantly across the states. The northern states have a higher proportion than the southern states. There is an urgent need for studies to explore factors that may be responsible for these special cause variations in childhood stunting in Nigeria

Electronic and traditional savings accounts in colombia: A spatial agglomeration model

The purpose of this article is to apply a multivariate spatial statistics technique: cluster analysis or spatial agglomeration, in order to classify departments into groups based on behavior in the number of active, inactive electronic savings accounts and savings traditional active accounts, with database available as of September 2017 in the bank of Colombia. The selection of this type of accounts was due to the fact that the financial product with the highest penetration in the Colombian population in September 2017, continued to be the savings account; 73.5% of the population had this financial product. However, this percentage is far from the target of 84% proposed in the National Development Plan. The findings show that the departments where electronic accounts are most used are Cauca, Bogotá, Meta, Casanare, Arauca, Vichada, Huila, Amazonas, Guainía, Vaupés, Caldas, Chocó, Sucre, La Guajira, César, Norte de Santander, however, the levels of penetration of this type of product are very low yet in the Colombian territory

Relationship between spatial proximity and travel-to-work distance : the effect of the compact city

In this paper, an assessment is made of the relationship between selected aspects of spatial proximity (density, diversity, minimum commuting distance, jobs-housing balance and job accessibility) and reported commuting distances in Flanders (Belgium). Results show that correlations may depend on the considered trip end. For example, a high residential density, a high degree of spatial diversity and a high level of job accessibility are all associated with a short commute by residents, while a high job density is associated with a long commute by employees. A jobs-housing balance close to one is associated with a short commute, both by residents and by employees. In general, it appears that the alleged sustainability benefits of the compact city model are still valid in a context of continuously expanding commuting trip lengths