Shulph Ink
Spatial Econometric Methods in Agricultural Economics Using R
Spatial Econometric Methods in Agricultural Economics Using R
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- More about Spatial Econometric Methods in Agricultural Economics Using R
Modern tools like GIS and remote sensing are used to monitor agricultural resources, allowing agricultural economics analysts to combine spatial information from different sources and produce different models. This book aims to support stakeholders in designing spatial surveys for agricultural data and analyzing geographically collected data. It covers topics such as spatial interpolation, point patterns, spatial autocorrelation, survey data analysis, small area estimation, regional data modeling, and spatial econometrics techniques.
Format: Hardback
Length: 280 pages
Publication date: 23 December 2021
Publisher: Taylor & Francis Inc
Modern tools, such as GIS and remote sensing, are increasingly being used in the monitoring of agricultural resources. The advancements in GIS technology have opened up vast opportunities for agricultural economics analysts to work with large and intricate spatial databases, enabling them to combine spatial information from various sources and create diverse models. The availability of these valuable sources of information makes the advanced models suggested in the spatial statistic and econometric literature applicable to agricultural economics.
This book aims to provide valuable support to stakeholders involved in designing spatial surveys for agricultural data and/or analyzing the geographically collected data. It endeavors to describe the primary typology of agricultural data and the most suitable methods for analysis, along with a comprehensive description of the available data sources and their collection methods. Topics such as spatial interpolation, point patterns, spatial autocorrelation, survey data analysis, small area estimation, regional data modeling, and spatial econometrics techniques are covered in depth, alongside issues arising from the integration of multiple data types.
The theory of spatial methods is complemented by real and/or simulated examples implemented through the open-source software R.
Weight: 689g
Dimension: 234 x 156 (mm)
ISBN-13: 9781498766814
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