Spatial Autocorrelation: A Primer

Dubin, Robin A.

doi:10.1006/jhec.1998.0236

Cited by 242 publications

(139 citation statements)

References 10 publications

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“…Both databases are maintained by the Student Association of Tel-Aviv University. 3 Tel-Aviv University students have free access to the databases, whereas non-students can obtain it for a fee. Anyone may post an apartment in the appropriate database for a fee.…”

Section: Datamentioning

confidence: 99%

Rule-Based and Case-Based Reasoning in Housing Prices

Gayer

Gilboa

Lieberman

2007

The B.E. Journal of Theoretical Economics

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People reason about real-estate prices both in terms of general rules and in terms of analogies to similar cases. We propose to empirically test which mode of reasoning fits the data better. To this end, we develop the statistical techniques required for the estimation of the casebased model. It is hypothesized that case-based reasoning will have relatively more explanatory power in databases of rental apartments, whereas rule-based reasoning will have a relative advantage in sales data. We motivate this hypothesis on theoretical grounds, and find empirical support for it by comparing the two statistical techniques (rule-based and case-based) on two databases (rentals and sales).

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Section: Datamentioning

confidence: 99%

Rule-Based and Case-Based Reasoning in Housing Prices

Gayer

Gilboa

Lieberman

2007

The B.E. Journal of Theoretical Economics

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“…Wherever location matters and influences the behavior of another entity, spatial autocorrelation is likely to be present (Dubin, 1998). Autocorrelation means that a variable is related to itself.…”

Section: Theory: Definition Of Spatial Autocorrelationmentioning

confidence: 99%

Spatial Dependency in Employment Growth in NC Counties

Scott¹

2018

Preprint

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A. IntroductionEconomic impact analysis has a significant role in policy making for the governments. It can increase/decrease the economic opportunities for the residents of each area. Many researchers have been studying the effect of employment growth in different regions on increasing/decreasing of employment opportunities in other regions in close proximity.In this project, I will study whether employment growth in one county can affect activities in adjacent counties within the state of North Carolina. In other words, I want to explore whether growing counties are close to each other or not by using spatial autocorrelation techniques.The unit of analysis of this research is counties in NC. I use percentage change in employment of each county between 2010 and 2015 data, collected from BEA website to test my hypothesis. B. Purpose of the study To find whether there is any spatial autocorrelation between different counties in NC in terms of economic activity and provide this information to decision makers for their regional analyses  Economic Impact Assessment to assess how activities in adjacent counties within the state impact conditions and processes inside of North Carolina  Whether growing counties are close to each other  Estimates of county-based, project-specific employment spillovers to/from one county

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“…For instance, when an econometric model is specified, there might be omitted variables that are spatially correlated (Kalenkoski & Lacombe, 2008), which is what happens in many studies of real estate markets (Dubin, 1998). Moreover, interactions and externalities between observations and regions may also exist.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, interactions and externalities between observations and regions may also exist. These features create spatial dependency and/or spatial heterogeneity (Anselin, 1988;Dubin, 1998), and a hierarchical-spatial approach can be applied in order to overcome some of these drawbacks. Empirical applications of this method are yet not numerous in economics in general or in real estate market analyses in particular.…”

Section: Introductionmentioning

confidence: 99%

Housing market analysis using a hierarchical–spatial approach: the case of Belo Horizonte, Minas Gerais, Brazil

Aguiar¹,

Simões²,

Golgher³

2014

Regional Studies, Regional Science

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The paper analyzes the determinants of apartments' prices in Belo Horizonte, MG, Brazil, with the use of hierarchical models, spatial models and a hierarchical-spatial approach. Besides the apartments' characteristics, such as area, age and building standard, prices were determined by local urban amenities. The hierarchical models indicated that local variables, such as urban violence, infrastructure and services, explained over 75% of prices' remaining variability. The spatial models analyzed if, after controlling for price variability with the explanatory variables in the second level of the hierarchical models, spatial correlations still existed in price determination. The positive and significant spatial coefficient in spatial autoregressive models (SAR) indicated spatial dependency. The hierarchical-spatial approach showed that over 70% of apartment prices' remaining variability could be explained by local variables and that the lagged urban services variable explained another 12% of this variability.

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Spatial Autocorrelation: A Primer

Cited by 242 publications

References 10 publications

Rule-Based and Case-Based Reasoning in Housing Prices

Rule-Based and Case-Based Reasoning in Housing Prices

Spatial Dependency in Employment Growth in NC Counties

Housing market analysis using a hierarchical–spatial approach: the case of Belo Horizonte, Minas Gerais, Brazil

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