Exploratory and explanatory statistical analysis of spatial data C.P.A. Bartels

Exploratory and explanatory statistical analysis of spatial data by C.P.A. Bartels

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In September 1977 a Regional Science Symposium was held at the Faculty of Economics of the University of Goningen in the Netherlands. The first theme, spatial inequalities and regional development, was chosen because of its central place in regional science.

Exploratory and explanatory statistical analysis of spatial data by C.P.A. Bartels

In September 1977 a Regional Science Symposium was held at the Faculty of Economics of the University of Goningen in the Netherlands. The impetus in organizing this symposium was the recent estab lishmen t at the F acuIty of Economics of a group engaged in teaching and research within the field of regional science. The aim of the symposium was to familiarize university members with regional science and to introduce the new group to both the national and international scene. Two separate topics of potential interest to both researchers and policy-makers were selected. The first theme, spatial inequalities and regional development, was chosen because of its central place in regional science. Authors from several disciplines were asked to approach this theme from a general, policy-oriented point of view. This ensured the spotlighting of the various dimensions of spatial inequality and its implications for regional policy. The results of their efforts have been collected in a volume entitled Spatial Inequalities and Regional Development. The second theme focussed on spatial statistical analysis. This branch of statistics is a relatively new one. It is receiving growing attention from researchers in the field of applied regional science. The conference dealing with this topic concentrated on recent research results related to the use of appropriate statistical and econometric methods for analyzing spatial data. The papers con cerned have been collected in another volume, entitled Exploratory and Explanatory Statistical Analysis of Spatial Data.

1: Introduction.- 1. General Introduction.- 2. Operational Statistical Methods for Analysing Spatial Data.- 2.1. Introduction.- 2.1 The structure of spatial data.- 2.3. Methods based on simple correlations between cross-regional data.- 2.4. Time-series analysis applied to spatial data.- 2.5 Adaptations of time-series analysis to the spatial context.- 2.6. Single equation explanatory models.- 2.7. Simultaneous equation models with spatial data.- 2.8. Some remaining topics.- 2.9. Final remarks.- References.- 2: Exploratory statistical analysis.- 3. The Analysis of Geographical Maps.- 3.1. Introduction.- 3.2. Methods of analysis.- 3.3. Models.- 3.4. Tests for randomness.- 3.5. Examples.- 3.6. Conclusions.- References.- 4 Construction of Interregional Input-Output Tables by Efficient Information Adding.- 4.1. Introduction.- 4.2. Regional and national accounts.- 4.3. Generation of survey-tired transaction tables.- 4.4. Results of the statistical estimations.- 4.5. Results of the minimum information estimations.- 4.6. Some conclusions.- References.- 5. Further Evidence on Alternative Procedures for Testing of Spatial Auto-Correlation among Regression Disturbances.- 5.1. Introduction.- 5.2. Formulation of the statistical decision problem.- 5.3. Moran's test statistic.- 5.4. Moments of the Moran statistic using OLS and LUS estimators.- 5.5. The likelihood ratio test.- 5.6. Simulation study of the Moran and likelihood ratio tests.- 5.7. Results.- 5.8. Conclusions.- References.- 3: Explanatory statistical analysis.- 6. Multivariate Models of Dependent Spatial Data.- 6.1. Introduction.- 6.2. Decomposable covariance structures.- 6.3. Linear models.- 6.4. Principal components.- 6.5. Conclusion.- References.- 7. Bayesian Analysis of the Linear Model with Spatial Dependence.- 7.1. Introduction.- 7.2. The nature of Bayesian inference.- 7.3. Linear regression model with spatially auto-correlated disturbances.- 7.4. An empirical application.- 7.5. Concluding remarks.- References.- 8. Alternative Methods of Estimating Spatial Interaction Models and Their Performance in Short-Term Forecasting.- 8.1. Introduction.- 8.2. Description of data and models.- 8.3. Parameter estimation and model calibration in terms of 1966 and 1971 data.- 8.4. On the accuracy of short-term forecasts made by spatial interaction models.- 8.5. An evaluation of tome alternatives designed to improve model performance.- 8.6. Conclusions.- References.- 9. Two Estimation Methods for Singly Constrained Spatial Distribution Models.- 9.1. Introduction.- 9.2. The calibration of a model.- 9.3. The maximum likelihood method.- 9.4. The least-squares method for the singly constrained model.- 9.5. Numerical results.- 9.6. Conclusions.- References.- 4: The introduction of stochastics in regional control.- 10. Stochastic Control of Regional Economies.- 10.1. Introduction.- 10.2. Mathematical representation of regional systems.- 10.3. Optimal control models of regional systems.- 104 Interaction of optimal control of regional economies with national governments.- 10.5. Problems in applying optimal control to regional systems.- 106. Conclusion.- References.

Exploratory and explanatory statistical analysis of spatial data C.P.A. Bartels

Exploratory and explanatory statistical analysis of spatial data by C.P.A. Bartels

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Exploratory and explanatory statistical analysis of spatial data Summary

Exploratory and explanatory statistical analysis of spatial data by C.P.A. Bartels

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