Paolo Postiglione

Spatial Econometric Methods in Agricultural Economics Using R (eBook, PDF)

• Format: PDF

Produktbeschreibung

The book describes methods and techniques of spatial data and its use in monitoring agricultural resources, farms management and regional markets. Spatial econometrics models for different data types relevant to statistical units adopted in typical agricultural economics analyses, are introduced.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 286
• Erscheinungstermin: 22. Dezember 2021
• Englisch
• ISBN-13: 9781498766838
• Artikelnr.: 62878509

Autorenporträt

Paolo Postiglione is Professor in Economic Statistics at University of Chieti-Pescara (Italy). He received a Ph.D. in Statistics from the University of Chieti-Pescara in 1998. His research interests mainly concern regional quantitative analysis, spatial statistics and econometrics, spatial concentration, regional economic convergence, agricultural statistics, and spatial sampling.

Roberto Benedetti is Professor in Economic Statistics at University of Chieti-Pescara (Italy). He obtained a Ph.D. in Methodological Statistics in 1994 from "La Sapienza" University of Rome (Italy). His current research interests focus on agricultural statistics, sample design, small area estimation, and spatial data analysis.

Federica Piersimoni is Senior Researcher at Processes Design and Frames Service in the Methodological Department of the Italian National Statistical Institute, since 1996. Her main research interests concern disclosure control and sample design.

Inhaltsangabe

1. Basic Concepts 2. Spatial Sampling Designs 3. Including Spatial
Information in Estimation from Complex Survey Data 4. Yield Prediction in
Agriculture: A Comparison Between Regression Kriging and Random Forest 5.
Land Cover/Use Analysis and Modelling 6. Statistical Systems in Agriculture
7. Exploring Spatial Point Patterns in Agriculture 8. Spatial Analysis of
Farm Data 9. Spatial Econometric Modelling of Farm Data 10. Areal
Interpolation Methods: The Bayesian Interpolation Method 11. Small Area
Estimation of Agricultural Data 12. Cross-sectional Spatial Regression
Models for Measuring Agricultural ß-convergence 13. Spatial Panel
Regression Models in Agriculture