Spatial Econometric Methods in Agricultural Economics Using R
Editat de Paolo Postiglione, Roberto Benedetti, Federica Piersimonien Limba Engleză Paperback – 15 feb 2023
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Livrare economică 15-29 martie
Specificații
ISBN-10: 1032053704
Pagini: 286
Ilustrații: 9 Tables, black and white; 8 Illustrations, color; 35 Illustrations, black and white
Dimensiuni: 156 x 234 x 15 mm
Greutate: 0.53 kg
Ediția:1
Editura: CRC Press
Colecția CRC Press
Locul publicării:Boca Raton, United States
Notă biografică
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 Sapienzä 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.
Cuprins
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
Descriere
- Analyses real data sets from start to conclusion. - Includes an extensive set of examples of the use of R to construct graphs and maps and to model and analyze spatial data. - Provides background information on exploratory and graphical data analysis and on spatial econometrics methods.
- Lists the possible types of spatial data used to analyze and model agriculture economics phenomena (and offers several codes for each example in the R software environment). - Presents the methods of spatial data analysis and of spatial econometric modeling appropriate for each agricultural data type. - Examines how each spatial data type can be used to explore spatial structures and how the spatial effects can be properly added to agricultural economics models.
- Outlines methods for model estimation when data is not available for the whole population but for a sample survey. - Illustrates the simplest and more sophisticated methods both to convert data from one type to another and to integrate different spatial data sources.