A primer for spatial econometrics: with applications in R, STATA and Python

By:

Arbia, Giuseppe

Material type: Text

TextSeries: Palgrave Texts in EconometricsPublication details: Palgrave Macmillan Switzerland 2025Edition: 2ndDescription: xix, 234 pISBN:

9783031571817

Subject(s):

DDC classification:

330.015195 ARB

Summary: This textbook offers a practical and engaging introduction to spatial econometric modelling, detailing the key models, methodologies and tools required to successfully apply a spatial approach. The second edition contains new methodological developments, new references and new software routines in R that have emerged since the first edition published in 2014. It also extends practical applications with the use of the software STATA and of the programming language Python. The first software is used increasingly by many economists, applied econometricians and social scientists while the software Python is becoming the elective choice in many scientific applications. With new statistical appendices in R, STATA and Python, as well as worked examples, learning questions, exercises and technical definitions, this is a significantly expanded second edition that will be a valuable resource for advanced students of econometrics. (https://link.springer.com/book/10.1007/978-3-031-57182-4)

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Holdings
Item type	Current library	Collection	Call number	Copy number	Status	Date due	Barcode
Book	Indian Institute of Management LRC General Stacks	Public Policy & General Management	330.015195 ARB (Browse shelf(Opens below))	1	Available		008774

This textbook offers a practical and engaging introduction to spatial econometric modelling, detailing the key models, methodologies and tools required to successfully apply a spatial approach.

The second edition contains new methodological developments, new references and new software routines in R that have emerged since the first edition published in 2014. It also extends practical applications with the use of the software STATA and of the programming language Python. The first software is used increasingly by many economists, applied econometricians and social scientists while the software Python is becoming the elective choice in many scientific applications. With new statistical appendices in R, STATA and Python, as well as worked examples, learning questions, exercises and technical definitions, this is a significantly expanded second edition that will be a valuable resource for advanced students of econometrics.

(https://link.springer.com/book/10.1007/978-3-031-57182-4)

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