Fw: GeoDa use case from North Macedonia

[Julia Koschinsky]

Question from Aleksandar Kostadinov.

Thanks, Julia

Julia Koschinsky, Ph.D.

Executive Director and Senior Research Associate

Center for Spatial Data Science

University of Chicago

https://spatial.uchicago.edu/

https://puttingscienceintodatascience.org/

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From: spatial...@lists.uchicago.edu <spatial...@lists.uchicago.edu> on behalf of "Aleksandar Kostadinov" <spa...@lists.uchicago.edu>
Sent: Monday, March 18, 2024 7:59 AM
To: spa...@uchicago.edu <spa...@uchicago.edu>
Cc: aleksandar...@yahoo.it <aleksandar...@yahoo.it>
Subject: [spatial] GeoDa use case from North Macedonia

 

Dears,

Hope this message finds you well. I am approaching you for a help regarding my recent analysis in GeoDa. 

Basically, I found significant correlation among  Macedonian diaspora and investments in energy efficient buildings back in North Macedonia.

The method summary:

- Percent of energy efficient buildings per municipality in North Macedonia varies a lot among municipalities (some municipalities have buildings with 6% energy efficient facades, some municipalities have 60% of the buildings with energy efficient facade).  

- Percent of migrant population living abroad per municipality is correlated positively and significantly with the percent of build energy efficient facades.

This tells us that many Macedonian workers send money back to Macedonia for reconstruction of the houses and use of energy efficient constructions. This in turn creates demand for green jobs and green skills in home countries.  

There are also outliers, meaning that those municipalities whose emigrant population is way too high, for example 33% and more are emigrants, do not invest in reconstruction, and possibly will abandon their homes and don't plan to return back to their home country. 

Are there methods to investigate the later statement, what is the cut-off precent of significant emigrant population, and low level of reconstruction? Or maybe some ML models need to be applied? 

I have also other variables collected and according Moran's I, seems that there is a spatial  clustering. I would like to explore these in a meaningful way with the use of GeoDa. 

Thank you very much.

Best regards,

Aleksandar Kostadinov 

IDEI-Skopje

 

 

Aleksandar Kostadinov

Institute for Digitalization, Economy and Innovation

+389 71 530 343

www.idei.org.mk

[pal...@ua.es]

Hi Julia!. Great to hear from you.
Hope everything is OK with you.

Paloma

El 2024-03-21 14:45, Julia Koschinsky escribió:
> Question from Aleksandar Kostadinov.
> Thanks, Julia
>
> Julia Koschinsky, Ph.D.
> Executive Director and Senior Research Associate
> Center for Spatial Data Science
> University of Chicago
> https://spatial.uchicago.edu/
> https://puttingscienceintodatascience.org/
>

> -------------------------

> _Aleksandar Kostadinov_
> _Institute for Digitalization, Economy and Innovation_
> _+389 71 530 343_
> _www.idei.org.mk_
>
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--
Paloma Taltavull de La Paz
Catedrática en Economía Aplicada /Professor in Applied Economics
Departamento de Análisis Económico Aplicado
Universidad de Alicante
e-mail: pal...@ua.es

Journal of European Real Estate Research, Editor in chief
http://www.emeraldinsight.com/journal/jerer

Chair of Real Estate Advisory Group - REM, UNECE
https://www.unece.org/housing/advisory-group.html

Director de la Cátedra de Transformación del Modelo Económico Valenciano
http://catedramodeloeconomico.ua.es

https://rua.ua.es/dspace/handle/10045/53036
https://orcid.org/0000-0002-8924-4380
https://www.researchgate.net/profile/Paloma_Taltavull_de_La_Paz2
https://linkedin.com/in/palomataltavull
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