Spatial Econometric Methods in Agricultural Economics Using R

The methods and techniques presented in this book are focused on spatial data and its use in monitoring agricultural resources, farm management, and regional markets. Spatial econometrics models are introduced for different data types relevant to the statistical units adopted in agricultural economics analyses. The theory and procedures of each model are described in a simple, intuitive way and complemented by examples of real data developed using R software. The combined use of statistical methods, new technologies, and economic theory is treated with particular reference to the peculiarities of spatial data for a proper and efficient analysis of agricultural data sets.

Paolo Postiglione is a professor of Economic Statistics at University of Chieti-Pescara, Italy. He received a Ph.D. in Statistics from the University of Chieti-Pescara in 1998. From 1996 to 2001, he was a statistical executive at Ministry of Transports and Navigation and head of Human Resources. His current research interests focus on spatial statistics and econometrics, regional economic convergence, models for spatial non-stationary data, spatial sampling, and agricultural statistics.

Roberto Benedetti is a professor of Economic Statistics at University of Chieti-Pescara, Italy. He obtained his Ph.D. in Methodological Statistics in 1994 from La Sapienza University of Rome, Italy. From 1989 – 1994, he was employed at Telespazio S.p.A., one of the world’s leading companies in satellite services and telecommunications, working on remotely sensed data. From 1994-2001, he was a research director and head of the Agricultural Statistical Service at the Italian National Statistical Office. Since 2001, he has been employed as a professor of Economic Statistics at the University of Chieti-Pescara. He is currently the chairman of the graduate program in economics and business at the University of Chieti-Pescara. His current research interests focus on agricultural statistics, sample design, small area estimation, and spatial data analysis.

Federica Piersimoni is a senior researcher with the Agricultural Statistics Service at the Italian National Statistical Institute. In 1999, she received a Specialization Degree in Operational Research and Decision Theory from the University of Rome La Sapienza and received a Ph.D. in Statistics from the University of Chieti-Pescara in 2014. Her main research interests concern disclosure control, and sample design.