Template-Type: ReDIF-Paper 1.0
Author-Name: Bence Mero 
Author-X-Name-First: Bence
Author-X-Name-Last: Mero
Author-Email: merob@mnb.hu
Author-Workplace-Name: Magyar Nemzeti Bank (Central Bank of Hungary)

Author-Name: Andras Borsos
Author-X-Name-First: Andras
Author-X-Name-Last: Borsos
Author-Email: borsosa@mnb.hu
Author-Workplace-Name: Magyar Nemzeti Bank (Central Bank of Hungary)

Author-Name: Zsuzsanna Hosszu
Author-X-Name-First: Zsuzsanna
Author-X-Name-Last: Hosszu
Author-Email: hosszuzs@mnb.hu
Author-Workplace-Name: Magyar Nemzeti Bank (Central Bank of Hungary)

Author-Name: Zsolt Olah
Author-X-Name-First: Zsolt
Author-X-Name-Last: Olah
Author-Email: olahzs@mnb.hu
Author-Workplace-Name: Magyar Nemzeti Bank (Central Bank of Hungary)

Author-Name: Nikolett Vago
Author-X-Name-First: Nikolett
Author-X-Name-Last: Vago
Author-Email: vagon@mnb.hu
Author-Workplace-Name: Magyar Nemzeti Bank (Central Bank of Hungary)

Title: A High Resolution Agent-based Model of the Hungarian Housing Market.

Abstract: This paper presents a complex, modular, 1:1 scale model of the Hungarian residential housing market. All the 4 million households and their relevant characteristics are represented based on empirical micro-level data coming from the Central Credit Information System, the Pension Payment database and transaction data of property sales collected by the National Tax and Customs Administration and the largest real estate agencies. The model features transactions in the housing and rental markets, a construction sector, buy-to-let investors, housing loans, house price dynamics and a procyclical banking sector regulated by a macroprudential authority. The flats in the model are characterized with detailed attributes regarding their size, state and neighbourhood quality. Households choose the flat with the highest consumer surplus according to standard utility maximization theory. Additionally, we have also implemented demographic trends, including childbearing, marriage and inheritance. This way the model is suitable for analysing various types of macroprudential, fiscal and monetary policies as well as for the assessment of exogenous shock scenarios. Initiating the model simulation from 2018, it managed to reproduce the number of transactions and the observed house price dynamics in most of the regions of Hungary for 2018-2019, while the volume of new housing loans and their distribution regarding income deciles and loan-to-value ratios were also in compliance with the empirical data.

Length: 78 pages
Creation-Date: 2022
File-URL: https://www.mnb.hu/letoltes/mnb-wp-2022-7-final-1.pdf
File-Format: Application/pdf
Number: 2022/6
Classification-JEL: C63, D1, D31, E58, R21, R31
Keywords: agent-based modelling, macroprudential policy, housing market, housing loans
Handle: RePEc:mnb:wpaper:2022/7