This project is funded by the European Union under Horizon2020 Research and Innovation Programme Grant Agreement n°824091
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Methods in Action: “Spatial regression models for estimating determinants of regional knowledge creation”

Sep 5 @ 9:00 am - Sep 12 @ 12:00 pm

The “Methods in Action Series” course Spatial regression models for estimating determinants of regional knowledge creation is organized by AIT Austrian Institute of Technology and will take place on online platform on  5 September and 12 September 2022.





Topic and objective

• Dealing with common issues in spatial regression models on research and innovation data at the regional level
• Including Spatial Durbin Models, spatial weight matrices and coefficients interpretation (direct, indirect spillover and total effects)
• Application to an interesting recent research debate, investigating drivers of different modes of regional knowledge creation
• Specific emphasis shifted to the impact of R&D networks on regional knowledge exploration versus knowledge exploitation

Online course including:

• Online lecture on spatial regression models as adequate instruments to estimate drivers of innovation at regional level.
• Group exercises where participants will apply spatial regressions models using example datasets
• Plenary discussion on pros and cons of regression strategies and how to motivate them to the reviewers.




Course programme

Monday 5th of September 2022

9:00-09:15 Introduction to the Course

09:15-10:00 Lecture: Basics of spatial econometrics

10:30-11:30 R tutorial on how to estimate spatial regression models

11:30-12:15 Creation of the groups and task assignment


Interim discussion with groups online upon request on September 7 (instructors stay online)


Monday 12th of September 2022

9:00-10:00 Group presentations

10:00-10:30  Final discussion and assessment of the use of methods



Martina Neuländtner and Thomas Scherngell, AIT Austrian Institute of Technology

Reference paper for the course

Neuländtner, M., & Scherngell, T. (2022). R&D networks and their effects on knowledge exploration versus knowledge exploitation: Evidence from a spatial econometric perspective. Industry and Innovation, 1-32



Target audience:

The course aims at involving participants among the following categories:

•Senior scientists, early career researchers focusing on empirical research
•PhD or master students at the last phase of their training
•Research intermediaries (e.g. research association like Science Europe).



Course prerequisites:

Basic requisite for admission will be:

•Knowledge of basic principles of statistics, as well as of Ordinary Least Squares (OLS) regression
•Solid working knowledge of R-Cran programming

Cost and Fees:

Cost and Fees: No registration fees to be paid by European Participants.

Maximum number of participants: 16.


by email to the organizer including a CV and a short statement of interest.

Deadline for request of participation:

29th August 2022.

Contact person:

Martina Neuländtner,



Sep 5 @ 9:00 am
Sep 12 @ 12:00 pm
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