Spatial econometric methods in agricultural economics using R
Author(s)
Bibliographic Information
Spatial econometric methods in agricultural economics using R
（A Science Publishers book）
CRC Press, 2022
- : pbk
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Note
Includes bibliographical references and index
Description and Table of Contents
Description
- 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.
Table of Contents
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 -convergence 13. Spatial Panel Regression Models in Agriculture
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