COURSE ID: D-EF34-OL LANGUAGE:

INTRODUCTION TO SPATIAL ANALYSIS USING STATA

Many phenomena in the economics, medical and social fields, such as unemployment, crime rates or infectious diseases, tend to be spatially correlated. Our “Introduction to Spatial Analysis using Stata” course offers researchers a unique opportunity to acquire the necessary toolset to conduct exploratory spatial data analysis.

The course begins by providing an overview of the Stata’s sp suite of commands for spatial analysis and then discusses how to manage different kind of spatial data and how to prepare them for the analysis. The course then turns to cover spatial data visualization, how to define proximity using spatial weights matrices and how to detect spatial autocorrelation. Finally, two sessions introduce the participants to spatial autoregressive models focusing on estimation, testing and model selection. Special emphasis will be given to the computation and interpretation of average direct and indirect marginal effects and to the treatment of special cases such as multiple spatial interactions and more endogenous covariates.

In common with TStat’s course philosophy, each individual session is composed of both a theoretical component (in which the techniques and underlying principles behind them are explained), and an applied segment, during which participants have the opportunity to implement the techniques using real data under the watchful eye of the course tutor. Throughout the course, theoretical sessions are reinforced by case study examples, in which the course tutor discusses and highlights potential pitfalls and the advantages of individual techniques. Particular attention is also given to both the interpretation and presentation of empirical results.

Upon completion of the course, it is expected that participants are able to identify and evaluate which specific spatial econometric methodology is more appropriate to both their dataset and the analysis in hand and subsequently apply the selected estimation techniques to their own data.

Ph.D. Students, researchers and professionals working in public and private institutions interesting in acquire the latest empirical techniques to be able to independently implement spatial data analysis.

Knowledge of basic econometrics tools such as ordinary least-squares, instrumental variables and maximum likelihood estimation of the linear regression model is strongly suggested. Basic knowledge of Stata’s do-file programming is required.  An introductory knowledge of Python, whilst not a perquisite, will facilitate the empirical section dedicated to Python in session 2.

SESSION I

Introduction

Spatial data analysis using Stata: overview of the sp suite
Space, spatial objects and spatial date

Prepare data for the spatial analysis

Spatial data declaration
Data with shapefile: Creating and merging a Stata-format shapefiles
Data without shapefile

 

SESSION II

Visualize spatial data

Geographic coordinate systems
Maps (dot, proportional symbol, diagram, choropleth)
2D spatial point patterns
Change coordinate system using Python
Retrieve data from OpenStreetMap using Python (optional)

 

SESSION III

Measure spatial proximity

The W (eights) matrix
Normalization
Detect spatial autocorrelation

 

SESSION IV

Spatial autoregressive models I

A taxonomy
Quasi Maximum Likelihood estimation
Hypothesis testing and model selection

 

SESSION V

Spatial autoregressive models II

Partial effects: direct, indirect and total effects
Instrumental Variables estimation

Internal instruments
Multiple endogenous covariates

Multiple spatial interactions

Due to the ongoing COVID-19 situation, the 2021 edition of this training course will be offered ONLINE on a part-time basis on the 10th-14th of May 2021 from 10.00 am to 1.30 pm Central European Summer Time (CEST).

Full-Time Students*: € 890.00
Academic: € 1260.00
Commercial: € 1685.00

*To be eligible for student prices, participants must provide proof of their full-time student status for the current academic year.

Fees are subject to VAT (applied at the current Italian rate of 22%). Under current EU fiscal regulations, VAT will not however applied to companies, Institutions or Universities providing a valid tax registration number.

The number of participants is limited to 8. Places, will be allocated on a first come, first serve basis. The course will be officially confirmed, when at least 5 individuals are enrolled.

Course fees cover: teaching materials (handouts, Stata do-files, program templates and datasets to use during the course), a temporary course licence of Stata valid for 30 days from the beginning of the course.

Individuals interested in attending this course, must return their completed registration forms to TStat by the 1st May 2021.


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Many phenomena in the economics, medical and social fields, such as unemployment, crime rates or infectious diseases, tend to be spatially correlated. Our “Introduction to Spatial Analysis using Stata” course offers researchers a unique opportunity to acquire the necessary toolset to conduct exploratory spatial data analysis.

 

Due to the ongoing COVID-19 situation, the 2021 edition of this training course will be offered ONLINE on a part-time basis on the 10th-14th of May.