Publications

This paper analyzes the firm’s choice between subsidy support and loan support during the COVID-19 crisis and explores the implications of this choice on firms’ employment growth. We compile a novel micro-level dataset of Lithuanian firms’ balance sheet data and government support records during the pandemic period. We use the dataset to provide a set of stylized facts, categorizing the variety of enacted support policies and tracking aid distribution patterns. We show that larger firms were more likely to choose loans over subsidies. This result cannot be fully explained by policy eligibility criteria and the severity of the pandemic shock, suggesting that firm characteristics played a significant role. Finally, we show that the type of support has implications for firms’ outcomes – subsidy-recipient firms experienced higher employment growth compared to loan-recipient firms.

This paper studies the effect of school closure on student outcomes in the Lithuanian context. Using administrative student-level data over 2013–2017 and propensity score matching, we create a balanced sample of control and treatment groups. In contrast to other studies, we focus on students in the final years of high school, possibly eliciting the upper bar of the disruption effect. Also, we follow students after high school graduation, providing evidence on labor market outcomes. We find that the school closure effect depends on the main teaching language. If we match students on a large set of student and school characteristics but the main teaching language, school closings have a lasting negative effect on exam performance and enrolling in higher education. Matching students on the main teaching language significantly reduces the negative school closure effect, suggesting that the disruption effect is considerably smaller and also has limited outcomes after high school if we take the main teaching language into account.

Keywords: School closure, education finance, student outcomes.
JEL Classification: H52, I22, I24.

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

Subprime lending is concentrated among minorities and in minority neighborhoods. However, the literature has little evidence for what led to the rise of subprime lending in minority neighborhoods. We use the endorsement of FICO credit scores in mortgage underwriting by the Government Sponsored Enterprises (GSEs) in 1995 to answer this question. The use of credit scores led to the sorting of prime and subprime lenders across minority and non-minority neighborhoods. In minority neighborhoods prime lenders were substituted by subprime lenders and, as a result, the share of subprime lending in minority neighborhoods increased by 5 percentage points. Prime lenders with a stronger relationship with the GSEs reduced their lending in minority neighborhoods more. The level of securitization by the GSEs in minority neighborhoods also decreased.

Keywords: Mortgages, Subprime lenders, GSEs, Securitization, Minorities

JEL codes: G21, G28, J15, R23.

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

This paper analyzes the macroeconomic consequences of foreign currency losses by banks, corporates and consumers in order to find whether some allocations of losses are better from a macroeconomic perspective than others. To that end, we construct a New Keynesian DSGE model with debt overhang for corporate borrowers, monitoring costs for household mortgage debt and leverage constraints for banks. The Hungarian experience at the end of 2008 and model estimation on Hungarian data motivate these financial frictions. Model simulation shows that making corporate borrowers bear currency risk results in worse macroeconomic outcomes than shifting currency mismatch losses to banks. Foreign currency mortgages to households, however, generate lower output than currency mismatch in the banking sector. The fact that households do not suffer from debt overhang, among other reasons, is driving this result.

Keywords: Currency mismatch, household debt, corporate debt, leveraged banks, small open economy, Bayesian estimation

JEL codes: E44, G21, F41, P2.

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

Using the universe of mortgage applications data and detailed credit performance data, we document that since the early 1990s there was a significant decline in the share of mortgages with co-borrowers. Although the decline was an almost universal phenomenon across different regions of the US, the rate of the decline showed significant spatial heterogeneity and in turn had implications for regional differences in economic activity. We show that the presence of a co-borrower reduces the mortgage default probability by more than 50 percent for both prime and subprime loans and those regions that had a lower co-borrower share prior to the crisis experienced higher mortgage default rates over the period 2007-2010. Higher default rates created spillovers on economic activity during the Great Recession: a lower co-borrower share at the regional level was also related to persistently lower house price growth, refinancing growth and mortgage credit growth. These results imply that the decrease in the share of mortgages with co-borrowers made the US mortgage market more vulnerable to the financial crisis and contributed to the divergence in economic outcomes across different regions.

JEL Codes: G21, G51, R21. 

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

The objective of increased regulation of mortgage origination activities after the Great Recession was to prevent another foreclosure crisis in the future. However, the literature is not conclusive about the actual effect of these policy changes. By using the 2007-09 panel and subsequent waves of the Survey of Consumer Finances (SCF), we predict foreclosure risk based on individual borrower characteristics. We show that the median mortgage foreclosure probability kept decreasing after 2010, but in 2016 it was still higher relative to the year 2007. The median foreclosure probability has remained high among both non-bank borrowers and bank borrowers. The regulatory changes started in 2010, so we also compare predicted foreclosure probabilities to the levels in 2010 and find that, despite the fact that banks were affected by this regulation more than non-banks, predicted foreclosure probabilities for bank mortgages declined slower than for non-bank mortgages. Our findings offer support for a thorough analysis of the regulatory effects because they might have been weaker than expected or worked in an unexpected way.

JEL Codes: C53, G21, G23.

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

This paper explores the spillover effects from increasing personal bankruptcy protection. Innovatively, the paper shows that the spillover effects can be influenced by the bank portfolio choice. Since a low level of personal bankruptcy protection keeps an insolvent individual liable until her debt is repaid in full, lender’s returns on mortgages are less uncertain than returns on other assets ceteris paribus. Risk-averse banks would prefer mortgages over other types of assets such as corporate loans. Corporate lending and thus equilibrium output would fall. In contrary to the popular view that creditor protection smooths credit provision and makes the allocation of resources more efficient, I show that in some cases a low level of personal bankruptcy protection can lead to aggregate consumption losses. Also I show that macroprudential policies (LTV ratios) can successfully complement higher personal bankruptcy protection in ensuring even higher welfare.

JEL Codes: E44, G11, G21, K35, R21.

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