Publications

This paper examines the energy efficiency of real estate used as collateral for bank loans in Lithuania, addressing the issue of missing data on building energy performance. We develop econometric models to estimate energy efficiency based on building type and characteristics and link the real estate energy data with loan-level information from the national credit register. Our primary contribution is the development of models to impute missing energy efficiency classifications, offering insights into the quality of real estate-backed bank credit in the context of climate-related risks. Our findings highlight that a significant portion of bank loan portfolios in Lithuania lacks energy efficiency data. We also propose specifications of our models as a potential benchmark for market practices and discuss policy recommendations to address data gaps, enhancing risk assessment and transparency in the financial sector.

Keywords: Climate Change, Energy Efficiency, Asset Pricing, Real Estate Collateral

JEL codes: G21, G32, G28

In 2021, the Bank of Lithuania and the Competition Council published a study assessing the accessibility of financing sources for small and medium-sized businesses (SMEs) in Lithuania in 2018–2019 and the factors limiting it. The study results have revealed that the funding opportunities for SMEs in Lithuania could be limited by various long-term constraints, including the lack of the enterprises’ adequate collateral and a higher risk of some enterprise groups, which has not always received due consideration through state aid measures.

In order to obtain sufficient funding, SMEs are faced with the collateral requirements which are often more difficult to comply with due to the inadequate assets in their possession. One of the measures that allows addressing the problem of inadequate assets of SMEs is loan guarantees. With this measure, the guarantor assumes part of the credit risk, which makes it possible to mitigate the risk for the credit institution and to enable SMEs to obtain adequate funding. However, in the previous study of the Bank of Lithuania and the Competition Council, which analysed SMEs’ access to the funding sources in 2018-2019, the results of the econometric modelling applied did not indicate any significant impact of state guarantees on the size of collateral requested by lenders.

This study is aimed at reviewing in greater detail the international practice of applying state guarantees (Section1) and Lithuania’s experience (Section 2), and at assessing the effectiveness of guarantee instruments in Lithuania, taking into account the groups of enterprises that received a guarantee and the effect of guarantees on the terms of lending (Section 3). In light of the results, lines of action to contribute to the development of these measures are proposed (Section 4).

Keywords: State guarantees, small and medium-sized businesses, access to finance, collateral requirements

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

Available only in Lithuanian

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.