Arbeitspapier

MEDSEA-FIN: An estimated DSGE model with housing and financial frictions for Malta

This paper uses Bayesian techniques and Maltese data over the period 2001-2019 to estimate the parameters of MEDSEA-FIN, one of the Central Bank of Malta's DSGE models. The model captures linkages between the housing sector, banks and the rest of the economy via a borrowing collateral constraint. The paper shows that the data is informative on a subset of the parameters, and documents that the dynamic properties of the estimated model are in line with similar DSGE models estimated for other countries. The results corroborate recent empirical findings for Malta documented in other studies. The model is used to decompose recent macroeconomic data and shows that housing demand shocks were important drivers of house prices and credit. Shocks from the euro area also drove a significant share of macroeconomic fluctuations. The paper also shows that the model survives external validation tests. Although the model remains somewhat stylized along some dimensions, estimation makes it suitable for policy analysis related to housing and credit markets and associated macroprudential policies.

Sprache
Englisch

Erschienen in
Series: CBM Working Papers ; No. WP/05/2022

Klassifikation
Wirtschaft
Bayesian Analysis: General
Multiple or Simultaneous Equation Models: Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
Model Construction and Estimation
Macroeconomics: Consumption; Saving; Wealth
Business Fluctuations; Cycles
Thema
MEDSEA-FIN
Bayesian estimation
house prices
structural shocks

Ereignis
Geistige Schöpfung
(wer)
Gatt, William
Ereignis
Veröffentlichung
(wer)
Central Bank of Malta
(wo)
Valletta
(wann)
2022

Handle
Letzte Aktualisierung
10.03.2025, 11:44 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Gatt, William
  • Central Bank of Malta

Entstanden

  • 2022

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