Publications

The high-paced growth of the Lithuanian mortgage market may cast doubt on either the efficacy of the country’s macroprudential toolkit, or the appropriateness of its current parametrisation in putting a backstop to excessive dynamics. This paper assesses the adequacy of BBM’s in Lithuania by building a novel lifetime expected credit loss framework that is founded on actual loan-level default and household income data. Based on the modelling framework we document seven findings which are relevant for policymakers. We show that the BBM package effectively contains mortgage credit risk and that housing loans are more resilient to stress than in the pre-regulatory era. Our BBM limit calibration exercise reveals that: i) in the low-interest rate environment income-based measures could have been tighter; ii) borrowers taking out secondary mortgages rightly are and should be required to pledge a higher down payment of at least 30%.

Keywords: macroprudential policy, borrower-based measures, LTV, mortgage credit risk, lifetime expected credit loss, probability of default.

JEL Codes: C25, E61, G18, G21, G51.

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

While Euro area interest rates were responding to accommodative monetary policy and decreasing throughout 2015-19, in stark contrast, Lithuania’s bank lending rates increased. Although the rates have slightly dropped around the onset of the pandemic, they are still elevated and well above the EA figures. This paper calls into question, what were the drivers of such interest rate dynamics in Lithuania? By analysing the historical events and practical aspects of loan pricing in Lithuania’s banking industry, we build an empirical model that exploits lending rate variation across banks, time and lending segments, and maps it to different drivers of pricing. We find that the recent changes in lending rates can be attributed to average bank margins, which moved largely in response to changes in market concentration.

Keywords: interest rates, loan pricing, banking, concentration, capital requirements.

JEL Codes: D22, D40, E43, G21, L11.

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

During the Covid-19 pandemic, house prices and mortgage credit are growing at a long-unseen pace. However, it is unclear, whether such growth is warranted by the underlying market and macroeconomic fundamentals. This paper offers a new structural two-market disequilibrium model that can be estimated using full-information methods, and applied to analyse housing and credit dynamics. Dealing with econometric specification uncertainty, we estimate a large ensemble of the two-market disequilibrium model specifications for Lithuanian monthly data. Using the model estimates, we identify the historical drivers of Lithuania’s housing and credit demand and supply, as well as price and market quantity variables. The paper provides a novel approach in the financial stability literature to jointly measure house price overvaluation and mortgage credit flow gaps. We find that by mid-2021 Lithuania was experiencing a heating in housing and mortgage credit markets, with home prices overvalued by around 16% and the volume of mortgage credit flow being 20% above its fundamentals.

JEL Codes: C34, D50, E44, E51, G21.

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

From the bookkeeping perspective, the flipside of bank loan issuance is a simultaneous creation of a deposit in the borrower’s account. By the act of lending banks do not simply intermediate pre-accumulated real resources but rather create new financial resources (money in the form of deposits) and new purchasing power. Being a major driver behind money growth, bank credit directly fuels domestic demand and inflationary pressures and thus needs to be modelled as a monetary phenomenon rather than as a mere reallocation of real resources. To this end, we develop a simple DSGE model and show that the basic DSGE framework, representing an open flexible-price economy with savers and borrowers and a simple bank with an explicit balance sheet, can indeed capture the essence of a bank as a monetary institution. The theoretical model confirms that the financial system is highly elastic in a sense that banks can extend loans at will largely irrespective of pre-accumulated resources and without needing to raise nominal deposit rates or increase financing from abroad. Moreover, in our model, changes in bank credit do have an immediate impact on nominal incomes, domestic demand and real economic activity. Model results are highly relevant from the policy perspective because they explain the fundamental relationship between financial (credit) cycle and the business cycle (e.g. observed income growth can be a consequence of a credit boom) and also suggest that sound domestic banks can stimulate domestic demand and can effectively reduce the developing economy’s reliance on foreign financing. Notably, the model focuses on a small open economy – a member of a monetary union – which thus has no independent monetary policy. We calibrate the model to the Lithuanian data and perform a number of policy-relevant shock experiments.

JEL Codes: E30, E44, E51, G21.

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