Publications

This paper discusses a bootstrap-based test, which checks if finite moments exist, and indicates cases of possible misapplication. The analysis indicates that a procedure for finding the smallest power to which observations need to be raised, such as the test rejects a hypothesis that the corresponding moment is finite, works poorly as an estimator of the tail index or moment estimator. This is the case especially for very low- and high-order moments. Several examples of correct usage of the test are also shown. The main result is derived analytically, and a Monte-Carlo experiment is presented.

MSC2010 Codes: 62G10, 65C05.

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

The trade-off between bank competition and financial stability has always been a widely and controversial issue, both among policymakers and academics. This paper empirically re-investigates the relationship between competition and bank risk across a sample of 54 European listed banks over the period 2004-2013. However, in contrast to most extant literature, we consider both individual and systemic dimension of risk. Bank-individual risk is measured by the Z-score and the distance-to-default, while we consider the SRISK as a proxy for bank systemic risk. Using the Lerner index as an inverse measure of competition and after controlling for a variety of bank-specific and macroeconomic factors, our results suggest that competition encourages bank risk-taking and then increases individual bank fragility. This result is in line with the traditional “competition-fragility” view. Our most important findings concern the relationship between competition and systemic risk. Indeed, contrary to our previous results, we find that competition enhances financial stability by decreasing systemic risk. This result can be explained by the fact that weak competition tends to increase the correlation in the risk-taking behavior of banks.

JEL Codes: G21, G28, G32, L51.

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

Since the crisis in the Baltic countries in 2009, the question on the particularities of business models adopted by foreign-owned banks has been often raised. The business models of these banks have changed significantly, but they still remain of major concern. The aim of this paper is to identify what type of business models have been chosen by the Baltic foreign-owned banks, to assess them as well as to provide recommendations on how to address the outlined challenges.
The Literature Review showed that the Business Model Canvas approach can be used for bank business model analysis. However, banking specialness should be taken into account. Empirical research was carried out using a combination of qualitative and quantitative methods for nine Scandinavian banks subsidiaries operating in the Baltics. The main focus of this research was the complex analysis of bank business model components, using the newly created system of key business model indicators. Business model analysis was based only on publicly available information, which is limited and not standardised.
The main characteristics of the business model of Scandinavian banks subsidiaries established in the Baltics are as follows: retail banks operating in one jurisdiction, dependency on the parent bank decisions, aversion to risk, stronger focus on non-interest income and high efficiency due to cost cutting and e-banking, orientation on safety (banks meet prudential requirements with large reserves), and medium profitability with a negative trend for the future. It was determined that if banks keep on doing their business as they are currently, their possibilities of generating acceptable returns will be of major concern. The biggest opportunity for banks in a low interest rate environment is to focus on increasing the volume of interest bearing assets. Financing small and medium-sized enterprises (SMEs), especially in productive sectors and innovative companies, could be the best outcome for banks and Lithuania’s economy. To achieve this goal, banks need to set SMEs financing as a strategic priority, make fundamental changes in their lending policy. The EU and local governments should give financial support for SMEs to strengthen this sector, and that should encourage banks to finance SMEs more actively as well.
The analysis of bank business models is a relatively new approach towards banking industry analysis. This paper is the first attempt of deeper analysis of business models of Scandinavian banks subsidiaries operating in the Baltics. This paper can serve as an eye-opener for Financial Supervisory Authorities and Central Banks, Scandinavian banks when drafting strategies for their subsidiaries and Government representatives who are responsible for the banking system strategy and strengthening SMEs sector.

JEL Codes: G21, M21.

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

This paper presents the analysis of indicators that could signal the build-up of systemic risk in Lithuania during the periods of credit expansion. The resulting set of early warning indicators could be useful in operationalizing countercyclical macroprudential policy measures, especially the countercyclical capital buffer (CCB). It could serve as a starting point in considerations whether there is a need to increase banks’ resilience in the upturn of financial cycle by accumulating additional capital buffers.
Taking into account the short Lithuanian data series which cover only one systemic banking crisis period, the analysis is extensively based on international research, particularly on findings of the European Systemic Risk Board (ESRB) Expert Group which provided analysis for the ESRB Recommendation on guidance on setting countercyclical buffer rates (ESRB 2014/1). Consistent with the existing research, we show that the deviation of the ratio of credit to gross domestic product (GDP) from its long-term trend (credit-to-GDP gap) is a suitable early warning indicator of financial crises in Lithuania. However, gap estimation faces uncertainty as the long-term trend is unobservable. To deal with the uncertainty, the estimation of the long-term trend was augmented with forecasts and most suitable alternative to the so called standardised ‚Basel gap‘ (suggested by the BCBS) is provided. In addition to this, complementary early warning indicators have been selected that could give concise yet comprehensive and robust view of the state of the Lithuanian economy. The performance of selected early warning indicators has also been evaluated for the three Baltic states (Lithuania, Latvia and Estonia).

JEL Codes: C40, G01.

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

Exchange rate assessment is becoming increasingly relevant for economic surveillance in the European Union (EU). The persistence of different wage, price and productivity dynamics among the Economic and Monetary Union (EMU) countries or EU members with a fixed exchange regime with the euro, coupled with the impossibility of correcting competitiveness differentials via the adjustment of nominal rates, have resulted in divergent dynamics in Real Effective Exchange Rates. This paper explores the role of economic fundamentals, included in the transfer effect theory, in explaining medium/long-run movements in the Real Effective Exchange Rates in the EU over the period 1994–2012 by using heterogeneous, co-integrated panel frameworks in static and dynamic terms. In addition, the paper provides an analysis of the misalignments of the rate for each member state based on the “equilibrium” measure calculated from the permanent component of the fundamentals (the so-called Behavioural Effective Exchange Rate).
We find that the coefficients of the determinants are extremely different across groups in magnitude and sometimes in sign as well and the transfer theory does not hold for periphery and the Central and Eastern European countries (CEECs). The relative importance of the transfer variable and the Balassa-Samuelson measure are crucial for the asymmetries. The resulting misalignments in EU28 are huge and the patterns diverge significantly across groups. The core countries have been undervalued for almost the whole period, which entails from an important increase in competitiveness for those countries. Instead the periphery has experienced high rates, especially in Portugal. In addition, the behaviour of CEECs is also driven, as expected, by the catching-up process and the criteria to the accession to the EU. The misalignments in this case are still extremely wide and reflect these phenomena.

JEL Codes: F31, C23.

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

The article examines the usefulness of six sector-based confidence indicators in forecasting Lithuanian short-term sectoral economic activity. All six sentiment indicators are examined side-by-side, which allows us to compare their properties, informational content and marginal contribution in forecasting. One of the properties common to all the confidence indices is that the confidence indices’ levels are more related to annual activity changes than to quarterly changes, which motivates us to take into account as well the change in the confidence index level. We find consumer, construction, and economic sentiment indicators to be the most reliable of the six indices, while the manufacturing sentiment index was the least useful in forecasting. We assess the marginal impact of the indicators, employing factor models augmented by additional regressors. Our results also suggest that information on sentiment in one sector is useful in forecasting activity of other sectors as well. The relationship between consumer confidence and private consumption seems to be a somewhat more interesting case than the others, as the level of consumer confidence is statistically significant in regressions when other available economic information is already taken into account. Our interpretation is that the consumer confidence indicator is a proxy of a structural consumption parameter, such as marginal propensity to consume.

JEL Codes: C33, C53.

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

This paper analyses the link between migration and sizes of countries. It explains why larger countries (in terms of population) have lower shares of migrants in their populations. First, the data is analysed; next, a macroeconomic model with international trade and migration, explaining the stylised facts, is developed. The model includes country size, which gives rise to cheaper country-specific goods produced in a large country relative to the goods produced in a smaller country. Higher wages in the small country spur immigration to it.

JEL Codes: F16, F22.

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

The paper presents a short-term Lithuanian inflation forecasting model for predicting monthly inflation of 5 main HICP subgroups. We model inflation employing a set of univariate equations, which are mainly based on firms’ mark-up pricing. We make use of disaggregate HICP data, consisting of 92 price series, which naturally evokes discussion of potential pros and cons of forecasting disaggregate series vs. forecasting an aggregate. Besides exploring potential gains of using disaggregate data, we are also interested in the international commodity prices transmission mechanism, which we implement employing a distributed lag model. To examine the performance of model’s forecasts, we employ a recursive pseudo real-time out-of–sample forecasting exercise, generating inflation forecasts up to 15 months ahead. We find that our suggested set of univariate equations produce more accurate forecasts than the competing factor model, VARX model and various benchmark models for all 5 HICP subgroups.

JEL Codes: C52, C53, E37.

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

In the recent debate about the channels for growth there are two different aspects to take into account: the importance of the exports in services and the sophistication of the exports themselves. We analyze in this paper the situation of exports in Lithuania, highlighting the modern/high-tech sectors with a special focus on services.
We found that the percentage of high-tech merchandise exports on the total exports increased in general the last decade, from less than 4% of total merchandise exports to more than 10%.The exports in modern services are instead the only one which experienced a positive growth rate in the worst period of the crisis (2009). Looking at the foreign demand for services, especially for modern services, this changed a lot in the last decade. The main partner for modern services now is Germany, while for total service exports the first destination is Russia, as it is for total goods. For total goods other countries not in the EU mattered more in 2004 than nowadays. Non-EU countries are becoming crucial for exports in modern services.
In addition, we provide a simple econometric setup in which we study the impact on the different type of real exports of the Real Effective Exchange Rate (REER, deflated in several ways) and the trade-weighted (weighted for trade in services and in goods) foreign demand based on real GDP data or Gross Value Added. The exports of modern services seem to be not explained by the competitiveness or demand factor. In our setups the main determinant is the exports in the previous period. The outcome for modern services is quite robust across the specifications and with different REERs. The exceptions concern the setup with GDP foreign demand estimated by OLS, in which also the foreign demand seems to play a role for exports in modern services. For exports in total services and traditional services instead, foreign demand matter in more cases and using different REERs especially with a more general measure of foreign demand based on real GDP.
The REER for goods and services exports matters more if deflated by CPI both in case of GDP and Gross Value Added-based foreign demand, and mostly in the short-run.

JEL Codes: F14, F43, C22.

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

In this paper, we analyze how borrower characteristics influence the choice between the short-term fixed-rate mortgage (STFRM) and the long-term fixed-rate mortgage (LTFRM) types in an emerging market. We use the national Survey of Households with Housing Loans conducted by the Bank of Lithuania between 2009 and 2012. This paper is the first to empirically test the findings of Campbell and Cocco in an emerging market. Following the model of Campbell and Cocco (2003), our analysis focuses on the interaction of demand and supply. We focus on the contract outcome; we do not specify who initiated such outcome – the household or the mortgage provider. We supplement the findings of previous literature by testing the model among financially constrained households in a different economic and institutional setting; that is, in Lithuania.
We define financial constraints of a household in multiple ways: high mortgage payment-toincome ratio, low residual income, high loan-to-value ratio, absence of savings, existence of other obligations, a single breadwinner in the household, and the existence of dependants in the household. Estimates based on these measures indicate that constrained households are more likely to choose a safer, but more expensive, long-term interest rate mortgage. Our results are in line with Campbell and Cocco’s (2003) suggestion that, when borrowing constraints are binding, financially constrained households should choose a long-term interest rate mortgage. Our results contradict the empirical evidence of Coulibaly and Li (2009), of Damen and Buyst (2013), of Ehrmann and Ziegelmeyer (2013), and of Hullgren and Söderberg (2013) that financially constrained households prefer short-term interest rate mortgages. We argue that the difference arises because of institutional features.
Our study adds to existing literature by showing that, in the world where borrowing constraints are binding, financially constrained households have the safer mortgage type that reduces consumption shock and liquidity risks. 

This paper presents a simple condition for optimal asymmetric labour (capital) taxation/subsidization in a two-sector model with logarithmic utilities and Cobb-Douglas production functions, linked to demographic factors: fertility rate and longevity. The paper shows that depending on parameter values, it may be optimal to tax or subsidize labour in the sectors. If it is optimal to tax the investment-goods sector, a Pareto-improving tax reform is possible. Larger output elasticities of capital in the sectors reduce the possibilities of a Pareto-improving reform, while population ageing in terms of higher longevity enhances the possibilities of welfare improvement for all generations. Fertility rates do not affect optimal taxation.

JEL Codes: E62, H21, J10.

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

The paper provides estimates for the New Keynesian Phillips curve (NKPC) in Lithuania. The paper considers the baseline and hybrid NKPC, the latter accounting for inflation inertia, under the closed and open economy frameworks. The estimates highlight the importance of expected and lagged inflation in the inflation formation process. The role of real marginal cost is found to be limited in shaping the dynamics of inflation. The study yields estimates for the underlying characteristics of pricing behaviour in Lithuania. The estimates show that the price duration stands at around 2.2–2.8 quarters, while the fraction of firms that adjust prices in a backward looking way amounts to around one third.

JEL Codes: D40, E30.

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