Does spatial clustering help explaining differences in the inequality of income distribution? : evidence from Argentina

Resumen: Este artículo analiza la relación entre la agrupación espacial de la distribución del ingreso y la desigualdad en las provincias de Argentina. El objetivo de este trabajo es usar técnicas espaciales para analizar hasta que punto la agrupación espacial de la distribución del ingreso afecta la desigualdad de la distribución del ingreso en un contexto regional de Argentina. En general, la literatura de desigualdad implícitamente considera a cada región o provincia como una entidad independiente y el potencial para la observación de la interacción a través del espacio a menudo se ha ignorado. Mientras tanto, la autocorrelación espacial ocurre cuando la distribución espacial de la variable de interés exhibe un patrón sistemático. Yo computo tres medidas de autocorrelación espacial global: La I de Moran, c de Geary, y G de Getis y Ord, como grado de CLUSTERING provincial entre 1991 y 2002. La principal conclusión del trabajo es que hay evidencia que provincias con desigualdad relativamente alta (baja) tienden a ser localizadas cerca de otras provincias con alta (baja) desigualdad más a menudo de lo esperado debido al azar. Por ende cada provincia no debería ser vista como una observación independiente, como ha sido supuesto implícitamente en estudios previos sobre la desigualdad de ingresos regional.

Far-field intensity distribution and M-2 factor of hollow Gaussian beams

The far-field intensity distribution of hollow Gaussian beams was investigated based on scalar diffraction theory. An analytical expression of the M-2 factor of the beams was derived on the basis of the second-order moments. Moreover, numerical examples to illustrate our analytical results are given. (c) 2005 Optical Society of America.

Far-field intensity distribution, M-2 factor of beams generated by Gaussian mirror resonator

We investigated M-2 factor and far-field distribution of beams generated by Gaussian mirror resonator. And we found usable analytical expressions of the M2 factor and the far-field distribution intensity with respect to variation of diffraction parameters. Particular attention was paid to the parameters such as mirror spot size and reflectance of the Gaussian mirror. (c) 2006 Elsevier GrnbH. All rights reserved.

A multivariate statistical study with a factor analysis of recent planktonic foraminiferal distribution in the Coromandel Coast of India

A study of planktonic foraminiferal assemblages from 19 stations in the neritic and oceanic regions off the Coromandel Coast, Bay of Bengal has been made using a multivariate statistical method termed as factor analysis. On the basis of abundance, 17 foraminiferal species, species were clustered into 5 groups with row normalisation and varimax rotation for Q-mode factor analysis. The 19 stations were also grouped into 5 groups with only 2 groups statistically significant using column normalisation and varimax rotation for R-mode analysis. This assemblage grouping method is suitable because groups of species/stations can explain the maximum amount of variation in them in relation to prevailing environmental conditions in the area of study.

The Effect of Volume Shape Factor on the Crystal Size Distribution of Fragments due to Attrition

The effect of volume shape factor on crystal size distribution (CSD) is usually ignored to simplify the analysis of population balance equation. In the present work, the CSD of fragments generated from a mechanically stirred crystallizer as the result of attrition mechanism has been reported when the volume shape factor conforms to normal distribution. The physical model of GAHN and MERSMANN which relates the attrition resistance of a crystalline substances to its mechanical properties has been employed. The simulation of fragment size distribution was performed by Monte Carlo (MC) technique. The results are compared with those reported by GAHN and MERSMANN.

Application of factor analysis and geostatistics to identify processes controlling the distribution and bioaccessibility of trace elements in Northern Ireland soils

Geologic and environmental factors acting over varying spatial scales can control
trace element distribution and mobility in soils. In turn, the mobility of an element in soil will affect its oral bioaccessibility. Geostatistics, kriging and principal component analysis (PCA) were used to explore factors and spatial ranges of influence over a suite of 8 element oxides, soil organic carbon (SOC), pH, and the trace elements nickel (Ni), vanadium (V) and zinc (Zn). Bioaccessibility testing was carried out previously using the Unified BARGE Method on a sub-set of 91 soil samples from the Northern Ireland Tellus1 soil archive. Initial spatial mapping of total Ni, V and Zn concentrations shows their distributions are correlated spatially with local geologic formations, and prior correlation analyses showed that statistically significant controls were exerted over trace element bioaccessibility by the 8 oxides, SOC and pH. PCA applied to the geochemistry parameters of the bioaccessibility sample set yielded three principal components accounting for 77% of cumulative variance in the data
set. Geostatistical analysis of oxide, trace element, SOC and pH distributions using 6862 sample locations also identified distinct spatial ranges of influence for these variables, concluded to arise from geologic forming processes, weathering processes, and localised soil chemistry factors. Kriging was used to conduct a spatial PCA of Ni, V and Zn distributions which identified two factors comprising the majority of distribution variance. This was spatially accounted for firstly by basalt rock types, with the second component associated with sandstone and limestone in the region. The results suggest trace element bioaccessibility and distribution is controlled by chemical and geologic processes which occur over variable spatial ranges of influence.

Financialisation, income distribution and aggregate demand in the USA

This paper investigates the effects of financialisation and functional income distribution on aggregate demand in the USA by estimating the effects of the increase in rentier income (dividends and interest payments) and housing and financial wealth on consumption and investment. The redistribution of income in favour of profits suppresses consumption, whereas the increase in the rentier income and wealth has positive effects. A higher rentier income decreases investment. Without the wealth effects, the overall effect of the changes in distribution on aggregate demand would have been negative. Thus a pro-capital income distribution leads to a slightly negative effect on growth, i.e. the USA economy is moderately wage-led.

Revisiting the Relationship between Income Distribution and Economic Growth

La mayoría de los modelos que exploran la relación entre la desigualdad en la distribución del ingreso y el crecimiento económico, postulan la existencia de una correlación negativa entre las dos que es generada a través de diferentes mecanismos. Paralelamente a los modelos teóricos, un número importante de estudios empíricos han tratado de evaluar esta relación. De este esfuerzo ha surgido un consenso amplio que valida la existencia de dicha relación negativa. No obstante, estudios recientes basados en el uso de datos de panel han producido el resultado contrario, documentando la presencia de una relación positiva entre desigualdad y crecimiento. El examen del debate generado a partir de estos resultados, así como el trabajo empírico adelantado en este estudio, indican que las estimaciones obtenidas en diversos trabajos pueden no ser tan robustas como se creía En consecuencia, se sugiere que la realización de estudios de caso por país puede ser una mejor vía para explorar este tema.