Giuseppe Espa – författare

Due to the widespread use of surveys in agricultural resources estimation there is a broad and recognizable interest in methods and techniques to collect and process agricultural data. This book brings together the knowledge of academics and experts to increase the dissemination of the latest developments in agricultural statistics. Conducting a census, setting up frames and registers and using administrative data for statistical purposes are covered and issues arising from sample design and estimation, use of remote sensing, management of data quality and dissemination and analysis of survey data are explored. Key features: Brings together high quality research on agricultural statistics from experts in this field.Provides a thorough and much needed overview of developments within agricultural statistics.Contains summaries for each chapter, providing a valuable reference framework for those new to the field.Based upon a selection of key methodological papers presented at the ICAS conference series, updated and expanded to address current issues.Covers traditional statistical methodologies including sampling and weighting.This book provides a much needed guide to conducting surveys of land use and to the latest developments in agricultural statistics. Statisticians interested in agricultural statistics, agricultural statisticians in national statistics offices and statisticians and researchers using survey methodology will benefit from this book.

Spatial Microeconometrics introduces the reader to the basic concepts of spatial statistics, spatial econometrics and the spatial behavior of economic agents at the microeconomic level. Incorporating useful examples and presenting real data and datasets on real firms, the book takes the reader through the key topics in a systematic way. The book outlines the specificities of data that represent a set of interacting individuals with respect to traditional econometrics that treat their locational choices as exogenous and their economic behavior as independent. In particular, the authors address the consequences of neglecting such important sources of information on statistical inference and how to improve the model predictive performances. The book presents the theory, clarifies the concepts and instructs the readers on how to perform their own analyses, describing in detail the codes which are necessary when using the statistical language R. The book is written by leading figures in the field and is completely up to date with the very latest research. It will be invaluable for graduate students and researchers in economic geography, regional science, spatial econometrics, spatial statistics and urban economics.