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Zeno Adams

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University of St.Gallen
University of St.Gallen

Course location

University of St.Gallen

Home university

University of St.Gallen
Adams
Zeno Adams is Assistant Professor of Finance at the University of St.Gallen. He teaches various courses in real estate markets and spatial econometrics. His classes focus on data analysis and applied econometrics using the free and powerful language R. His research is focused on the spatial interaction and spatial networks between real estate markets, firms, and population flows. His research has been published in various academic journals such as Journal of Financial and Quantitative Analysis, Journal of Banking and Finance, and Real Estate Economics.

Courses taught by this instructor

Course

Description

Instructor

Level

B = Basic
M = Intermediate
A = Advanced

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Course

Description

Instructor

Level

B = Basic
M = Intermediate
A = Advanced

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Next course

Regression Analysis for Spatial Data

This course focuses on the visualization and modeling of spatial data. Examples are taken from different research areas such as political science, empirical international trade, criminology, and real estate. It offers a detailed explanation of individual estimation methods and their implementation in R. In this course, students will learn ‑ How to generate a variety of different maps that visualize the location of spatial units ‑ How maximum likelihood estimation works and how to set up and optimize a likelihood function in R ‑ How to deal with computational problems that are frequently accounted when working with spatial data ‑ How to increase computation speed using concentrated maximum likelihood and the matrix exponential spatial specification model ‑ How to estimate a spatial regression model both, with cross‑sectional and with time‑series data ‑ How to properly interpret the output from a spatial regression model and how to investigate policy interventions. ‑ A basic background on spatial interaction models, heterogeneous coefficient SAR models, and spatio‑temporal models
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A

Regression Analysis for Spatial Data

This course focuses on the visualization and modeling of spatial data. Examples are taken from different research areas such as political science, empirical international trade, criminology, and real estate. It offers a detailed explanation of individual estimation methods and their implementation in R. In this course, students will learn ‑ How to generate a variety of different maps that visualize the location of spatial units ‑ How maximum likelihood estimation works and how to set up and optimize a likelihood function in R ‑ How to deal with computational problems that are frequently accounted when working with spatial data ‑ How to increase computation speed using concentrated maximum likelihood and the matrix exponential spatial specification model ‑ How to estimate a spatial regression model both, with cross‑sectional and with time‑series data ‑ How to properly interpret the output from a spatial regression model and how to investigate policy interventions. ‑ A basic background on spatial interaction models, heterogeneous coefficient SAR models, and spatio‑temporal models
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