A conference was organized by the Alter Property Data Network on November 21st, 2022, hosted by ReFinE/Institut Louis Bachelier. This network gathers economists, data scientists and practitioners from all over the world (from the IMF, World Bank, OECD, European Commission, BIS, central banks, universities…) who share information, data, programs and papers on alternative techniques (web-scraping, mobile data, satellite data, machine learning, text mining…) related to housing and construction in general.
The organizers were, in alphabetical order:
- Alexandre Banquet, OECD
- Kevin Beaubrun-Diant, ReFinE, Institut Louis Bachelier and Paris-Dauphine University
- Daniela Behr, International Finance Corporation (IFC), World Bank Group
- Nina Biljanovska, IMF
- Jean-Charles Bricongne, Banque de France
- Boris Cournède, OECD
- Ludovic Gauvin, Yanport
- Deniz Igan, BIS
- Basile Pfeiffer, Ministère de la transition écologique
- Pierre-Alain Pionnier, OECD
- Volker Ziemann, OECD
The theme of this conference was: To what extent do alternative techniques (web-scraping, satellite data…) help to better understand what happened during the Covid crisis in housing and construction?
After a transversal introductory statement by Yunhui Zhao (IMF), this conference gave insights mainly from two different perspectives, first showing how alternative tools such as web-scraping or satellite data can give additional information on real estate during the Covid-19 and showing the latest developments on methodological tools on housing and construction.
The first part included:
- An OECD paper showing evolutions in housing demand during the pandemics: Rudiger Ahrend, Manuel Bétin, Maria Paula Caldas, Boris Cournède, Marcos Diaz Ramirez, Pierre-Alain Pionnier, Daniel Sanchez-Serra, Paolo Veneri and Volker Ziemann (OECD): Changes in the geography housing demand after the onset of COVID-19: First result for large cities in 13 OECD countries, https://www.oecd-ilibrary.org/economics/changes-in-the-geography-housing-demand-after-the-onset-of-covid-19-first-results-from-large-metropolitan-areas-in-13-oecd-countries_9a99131f-en
- A Banca d’Italia paper analyzing the evolution of housing preferences in the case of Italy: Elisa Guglielminetti & Michele Loberto & Giordano Zevi & Roberta Zizza (Banca d’Italia): Living on my own: the impact of the Covid-19 pandemic on housing preferences; https://www.bancaditalia.it/pubblicazioni/qef/2021-0627/QEF_627_21.pdf
- An article that complements the official statistics on the evolution of the housing market in the UK: Jean-Charles Bricongne (Banque de France), jointly with Baptiste Meunier and Sylvain Pouget: Web-scraping housing prices in real-time: the Covid-19 crisis in the UK (https://www.banque-france.fr/sites/default/files/medias/documents/wp827.pdf )
The second part on methodological tools included the following presentations:
- Alexandre Banquet (OECD): presentation of advances in satellite data for the monitoring of built areas: Dynamic World and new version of GHSL
- Nina Biljanovska (IMF), Chenxu Fu (IMF) & Deniz Igan (BIS), Housing Affordability: A New Panel Dataset
- Emmanuel Flachaire, Gilles Hacheme, Sullivan Hué and Sébastien Laurent (AMSE): GAM(L)A: An econometric models for interpretable Machine Learning, used to forecast housing prices in Boston (USA); https://slaurent.pagesperso-orange.fr/pdf/GAMA.pdf
- Pierre-Alain Pionnier (OECD), jointly with Johannes Schuffels: Estimating regional house price levels; Methodology and results of a pilot project with Spain, https://www.oecd-ilibrary.org/fr/economics/estimating-regional-house-price-levels_b9fec1b2-en