Simple diagnostic tests for spatial dependence

Anselin, Luc; Bera, Anil K.; Florax, Raymond J.G.M.; Yoon, Mann J.

doi:10.1016/0166-0462(95)02111-6

Cited by 1,435 publications

(915 citation statements)

References 16 publications

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“…(2) Anselin (1988)'s text fully introduces the maximum-likelihood methodology into this field, along with a new generation of more specific and flexible tests (Anselin et al, 1996, Anselin and Bera 1988, Anselin, 2001, Leung et al, 2003, and Baltagi et al, 2003. (3) Kelejian and Robinson (1993) propose using instrumental variables in connection with spatial models, which leads to a new battery of tests of spatial dependence based, directly or indirectly, on the GMM principle (Anselin and Kelejian, 1997, Kelejian and Prucha, 1999, Conley, 1999, Saavedra, 2003, Kelejian and Prucha, 2004, and Fingleton, 2008 Graaff et al, 2001) and the τ test Pinkse, 1997, Pinkse et al, 2002).…”

Section: Introductionmentioning

confidence: 99%

A non-parametric spatial independence test using symbolic entropy

Hernández

Matilla-García

Mur

et al. 2010

Regional Science and Urban Economics

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RESUMENIn the present paper, we construct a new, simple, consistent and powerful test for spatial independence, called the SG test, by using symbolic dynamics and symbolic entropy as a measure of spatial dependence. We also give a standard asymptotic distribution of an affine transformation of the symbolic entropy under the null hypothesis of independence in the spatial process. The test statistic and its standard limit distribution, with the proposed symbolization, are invariant to any monotonuous transformation of the data.The test applies to discrete or continuous distributions. Given that the test is based on entropy measures, it avoids smoothed nonparametric estimation. We include a Monte Carlo study of our test, together with the well-known Moran's I, the SBDS (de Graaff

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Section: Introductionmentioning

confidence: 99%

A non-parametric spatial independence test using symbolic entropy

Hernández

Matilla-García

Mur

et al. 2010

Regional Science and Urban Economics

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“…El modelo planteado es de una capacidad predictiva alta por lo robusto e insesgados que son sus estimadores, siendo estos no de mínimos cuadrados ordinarios, sino de mayor precisión los de mínimos cuadrados ponderados, haciendo marginal el efecto de la homocedasticidad de las variables asociadas en los productos en análisis, siendo la muestra altamente significativa (Anselin, Bera, Florax, & Yoon, 1996). El indicador de potencial a industrializar arroja una alta significancia estadística sin considerar o excluyendo la variable precio exportable, lo que se sustenta en el postulado de que los precios de bienes exportables no son definidos por factores endógenos sino por factores exógenos y este es el mercado por ejemplo, lo que hace indiferente la postura a industrializarse de alguna manera de forma indistinta si se tiene acuerdo comercial o no (Slocum, McMaster, & Howard, 2009).…”

Section: Discussionunclassified

Análisis del desarrollo de la agroindustria local ecuatoriana y su relación con el potencial territorial. // Analysis of the development of the Ecuadorian local agroindustry and its relation with the territorial potential

Martínez¹,

García²

2018

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Análisis del desarrollo de la agroindustria local ecuatoriana y su relación con el potencial territorialAnalysis of the development of the Ecuadorian local agroindustry and its relation with the territorial potential ResumenEn diversos países el desarrollo de la agroindustria ha permitido el crecimiento de la competitividad. Esto, debido a que amplía la gama de productos disponibles de un país hacia el mundo. Es así como se consigue la penetración de nuevos mercados con productos de calidad que se hayan desarrollado mediante modernos procesos productivos y estrategias óptimas para el cumplimiento de los estándares internacionales. La presente investigación pretende evaluar el efecto de la competitividad agroindustrial, su potencialidad en el desarrollo del territorio ecuatoriano y la demanda internacional. Para ello se consultó diferentes estudios de mercado realizados para determinar cuáles son los clientes potenciales para los nuevos productos que pueden desarrollarse. Así mismo, se realizó un análisis multivariado utilizando datos de panel confrontando la aleatoriedad de los efectos fijos y aleatorios para la toma de decisiones de producción de varios productos a agro-industrializar. Se obtuvo la estimación para la potencialidad de exportación de los productos, potencialidad zonal y potencialidad para industrialización de los productos analizados. Se concluye que el desarrollo agroindustrial, concibe un mayor crecimiento de la competitividad nacional.Palabras Clave: Competitividad; agroindustria; mercados internacionales; datos de panel; estimadores de varianza. AbstractIn several countries the development of agroindustry has allowed the growth of competitiveness. This is because it expands the spectrum of products available from one country to the world. This is how the penetration of new markets with quality products that have been developed through modern production processes and optimal strategies for compliance with international standards is achieved. The present research pretends to evaluate the effect of agroindustrial competitiveness, its potentiality in the development of the Ecuadorian territory and international demand. For this purpose, different market studies were consulted to determine which are the potential customers for the new products that can be developed. Likewise, a multivariate analysis was carried out using panel data comparing the randomness of the fixed and random effects for the production decision making of several agro-industrialized products. The estimation was obtained for the export potential of the products, the zonal potential and potential for industrialization of analyzed products. It is concluded that the agro-industrial development conceives a greater growth of the national competitiveness.

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“…(1) will provide a biased estimation of the parameters in the case of spatial lag dependence, while it provides unbiased and inefficient estimates in the case of spatial error dependence. Therefore, in order to explore the spatial interaction of the geographical distribution of unemployment, we follow loosely the robust specification strategy (see Anselin et al 1996). Generally, one refers to the widest model including all kinds of spatial effects:…”

Section: Models and Data On Unemployment In Italian Provincesmentioning

confidence: 99%

A spatial analysis on Italian unemployment differences

2008

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Using spatial econometric models, this paper focuses attention on the spatial structure of provincial unemployment disparities of Italian provinces for the year 2003. On the basis of findings from the economic literature and of the available socio-economic data, various model specifications including supply-and demandside variables are tested. Further we use ESDA analysis as equivalent to integration analysis on time series; therefore it is applied on each variable, dependent and independent, involved in the statistical model. The suggestions of ESDA lead us to the most adequate statistical model, which estimates indicate that there is a significant degree of neighbouring effect (i.e. positive spatial correlation) among labour markets at the provincial level in Italy; this effect is present notwithstanding we controlled for local characteristics. The unemployment shows a polarized spatial pattern that is strongly connected to labour demand and to a much lesser extent to the share of young population and economic structural composition.

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Simple diagnostic tests for spatial dependence

Cited by 1,435 publications

References 16 publications

A non-parametric spatial independence test using symbolic entropy

A non-parametric spatial independence test using symbolic entropy

Análisis del desarrollo de la agroindustria local ecuatoriana y su relación con el potencial territorial. // Analysis of the development of the Ecuadorian local agroindustry and its relation with the territorial potential

A spatial analysis on Italian unemployment differences

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