Publications

This paper introduces the Systemic Risk Modelling System (SRMS), a new macroprudential stress testing model for the Lithuanian banking sector. The SRMS addresses the limitations of traditional static models by incorporating dynamic balance sheet assumptions and capturing second-round effects, providing a more comprehensive assessment of systemic risks. The model’s applications extend beyond stress testing, including macroprudential policy stance assessment, capital-at-risk analysis, and macroprudential policy impact evaluation. The SRMS model enhances the understanding of systemic risks within the Lithuanian banking sector and offers a potential benchmark for other national central banks seeking to strengthen their financial stability frameworks.

Keywords: macroprudential stress testing, macroprudential policy, feedback loop, secondround effects.

JEL codes: E37, E58, G21, G28

Timely monitoring of the housing market developments in Lithuania is one of the key elements in the analysis framework of the macroprudential authority aiming to contribute to financial stability in Lithuania. In this paper, we addressed three important questions related to Lithuanian house prices, namely, whether house prices are under- or over valuated, which explanatory variables have the biggest impact on the growth of house prices and what the future development of the Lithuanian house price index could be. Three separate modelling and forecasting exercises were performed in order to tackle these questions. The first exercise employs the vector error correction modelling (VECM) approach to assess under- or overvaluation of the house prices. We then use an autoregressive distributed lag model (ARDL) to evaluate which explanatory variables have the biggest impact on house price growth. As the last exercise, we develop a suite of models that are used to forecast future development of the house price index. The analysis presented in this paper may be viewed as a further step towards more formalised modelling and forecasting of the Lithuanian house price index.

JEL Codes: C22, C32, C53, E37, R30.

The views expressed are those of the author(s) and do not necessarily represent those of the Bank of Lithuania.