Bank of Lithuania
Category
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All results 163
No 96
2021-11-24

The Quadrilemma of a Small Open Circular Economy Through a Prism of the 9R Strategies

  • Abstract

    The Circular Economy (CE) challenges the traditional linear economy model to arrive at a sustainable  economy that minimizes resource use, its negative environmental impact, and dependency on resource imports. We develop a multi-sector dynamic stochastic general equilibrium small open economy model with endogenous adoption of exogenous foreign technology innovations, endogenous environmental quality, and CE elements, comprising recyclable waste as well as recycling and refurbishing sectors. We analyze the model-implied impulse response functions with respect to several economic shocks and conduct a rich scenario-based analysis, for which the scenarios are derived from the 9R strategies. We find important trade-offs to be considered by the economy with respect to circularity, trade, environment, and growth – the four dimensions of the quadrilemma of a small open circular economy. We find that none of the six shocks considered and in none of the eight scenarios analyzed the quadrilemma can be resolved. However, a positive shock to the price of energy or a lower energy share in one of the two intermediate goods sectors provide benefits to three out of four dimensions of the quadrilemma.

    Keywords: Circular economy, Small open economy, Recycling, Refurbishing, Endogenous economic growth, Technology adoption, General equilibrium, Energy.

    JEL codes: E2, F4, O3, O4, Q4, Q5.

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

No 95
2021-11-23

Coworker Networks and the Labor Market Outcomes of Displaced Workers: Evidence from Portugal

  • Abstract

    The use of social contacts in the labor market is widespread. This paper investigates the impact of personal connections on hiring probabilities and re-employment outcomes of displaced workers in Portugal. We rely on rich matched employer-employee data to define personal connections that arise from interactions at the workplace. Our empirical strategy exploits firm closures to select workers who are exogenously forced to search for a new job and leverages variation across displaced workers with direct connections to prospective employers. The hiring analysis indicates that displaced workers with a direct link to a firm through a former coworker are roughly three times more likely to be hired compared to workers displaced from the same closing event who lack such a tie. However, we find that the effect varies according to the type of connection as well as firms’ similarity. Finally, we show that successful displaced workers with a connection in the hiring firm have higher entry-level wages and enjoy greater job security although these advantages disappear over time.

    Keywords: Job Displacement, Coworker Networks, Re-Employment.

    JEL codes: J23, J63, L14.

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

No 94
2021-11-08

Emergence of Subprime Lending in Minority Neighborhoods

  • Abstract

    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.

No 40
2021-10-18

Beyond the Traditional Unemployment Rate during Covid-19 in Lithuania

  • Abstract

    This paper provides empirical evidence on the impact of Covid-19 on unemployment and underemployment in Lithuania. Based on the Labor Force Survey, we document the evolution of the unemployment rate using broader definitions that incorporate the underemployed and marginally attached workers. Our results show that, compared to previous recessions, Covid-19 had a milder impact on the Lithuanian labor market. Moreover, Lithuania fared reasonably well relative to other Eurozone countries. However, the data reveal a substantial increase in marginal workers and underemployment during 2020, with women, young workers and individuals in rural areas being most affected by the pandemic-induced recession.

    Keywords: labor market statistics, labor force, unemployment.

    JEL codes: E24, J21, J64

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

     

     

No 93
2021-10-12

The Effect of the Euro Changeover on Prices: Evidence from Lithuania

  • Abstract

    At the aggregate level, I find that the euro changeover did not lead to a significant change in the overall inflation rate between 2015 and 2019 in Lithuania. When the measures are diversified, however, some inflationary effects emerge in sub-categories. I therefore analyze this heterogeneity at the disaggregated level using a large sample of prices that constitutes the CPI from 2010 to 2018. I show that significant price changes have been confined to the low-weighted components of the HICP. This explains why a spike in the overall price level did not occur at the time of the changeover.

    Keywords: Euro changeover, synthetic difference-in-differences, regression discontinuity in time, price changes.

    JEL codes: E31, F33, L11.

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

No 39
2021-10-11

Becoming a data-centric organisation: a guide to data management initiatives at the Bank of Lithuania

  • Abstract

    Central banks worldwide are grappling with issues relating to data. From how to collect and manage data to aspects of governance, analysis, communication and the proliferation of data – the vast variety of these issues is pushing many to consider root-and-branch reforms. The Bank of Lithuania has been one of the leaders in this regard.

    For several years, the Bank of Lithuania has prioritized the development of innovative solutions for streamlining data collection and reporting. These include smart reporting solutions, such as data collection via API, new technologies enabling a switch from aggregate- to granular-level data, and new possibilities for integrating, reusing, and opening up the existing data.

    Recently, we took our data management efforts to an even higher level and embarked on the fast track to becoming a truly data-centric organisation by launching an organisation-wide Data Management Maturity Program (DAMAMA). The program activates far-reaching change across the entire data journey within the organisation: data collection, warehousing, analytics, and data governance.

    This white paper provides an in-depth guide to the recent data management initiatives at the Bank of Lithuania and the range of complex issues that these initiatives help to solve. In addition, this paper presents the ongoing Data Management Maturity Program DAMAMA, transformation areas covered by the program, main objectives and timelines. Lastly, the final section introduces the international context relating to the ongoing efforts of European organisations to harmonise reporting practices across different domains.

    The views expressed are those of the authors and do not necessarily represent those of the Bank of Lithuania.

     

No 26
2021-08-26

Business cycles in the EU: A comprehensive comparison across methods

  • Abstract

    Recently, star variables and the post-crisis nature of cyclical fluctuations have attracted a great deal of interest. In this paper, we investigate different methods of assessing business cycles for the European Union in general and the euro area in particular. First, we conduct a Monte Carlo experiment using a broad spectrum of univariate trend-cycle decomposition methods. The simulation aims to examine the ability of the analyzed methods to find the observed simulated cycle with structural properties similar to actual macroeconomic data. For the simulation, we used the structural model’s parameters calibrated to the euro area’s real GDP and unemployment rate. The simulation outcomes indicate the sufficient composition of the suite of models consisting of popular Hodrick-Prescott, Christiano-Fitzgerald and structural trend-cycle-seasonal filters, then used for the real application. We find that: (i) there is a high level of model uncertainty in comparing the estimates; (ii) growth rate (acceleration) cycles have often the worst performances, but they could be useful as early-warning predictors of turning points in growth and business cycles; and (iii) the best-performing Monte Carlo approaches provide a reasonable combination as the suite of models. When swings last less time and/or are smaller, it is easier to pick a good alternative method to the suite to capture the business cycle for real GDP. Second, we estimate the business cycles for real GDP and unemployment data varying from 1995Q1 to 2020Q4 (GDP) or 2020Q3 (unemployment), ending up with 28 cycles per country. Our analysis also confirms that the business cycles of euro area members are quite synchronized with the aggregate euro area. Some major differences can be found, however, especially in the case of periphery and new member states, with the latter improving in terms of coherency after the global financial crisis. The German cycles are among the cyclical movements least synchronised with the aggregate euro area.

    JEL Codes: C31, E27, E32.

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

No 1
2021-08-17

Feasibility study on the use of the account information service in optimising the provision of electronic money and payment institution data for supervisory services

  • Abstract

    The main objective of this feasibility study is to analyse an opportunity of implementing the optimisation of data management for supervisory purposes by means of the AIS service in observing the compliance of EMI and PI with the requirements for safeguarding client funds.

    As part of the drawing up of the study, the existing supervisory process of safeguarding of client funds which is currently applied by FMSS PMSD was analysed, the AIS service with respect to the AIS provider was described, the survey of the credit institutions and AISPs was conducted, legal and IT feasibilities were assessed and conclusions were provided. 

    Having performed the feasibility study, it was established that:

    the use of the AIS service to receive the supervisory information on client funds held by EMIs and PIs would be one of the possibilities to optimise the supervisory work of FMSS;

    integration of AIS service could be implemented in the short and long term: (a) in the short run, AIS service would ensure the provision of balances of EMI and PI client fund accounts and it could be achieved by means of minimum time limits and financial costs; (b) in the long run, AIS service would help access all information on the account which could be consolidated, processed and applied a cross-cutting analysis to be used for the achievement of the supervisory goals. To implement one of the AIS service integrations referred to herein, the Bank of Lithuania would need to allocate additional financing sources and human resources by involving other FMSS divisions as well;

    If the AIS service, for the purpose of receiving supervisory information, were used in such a way where the EMIs and PIs preserved the option for the Bank of Lithuania to provide relevant information through AISPs and EMIs and PIs were allowed choosing AISPs on their own, the changes in the current legal regulation would not be necessary;

    Consolidated information received from EMIs and PIs through AISPs could be currently stored and held in the existing information acceptance systems of the Bank of Lithuania;

    At the moment, when AIS service is used, FMSS has only limited possibilities to receive information on client funds held with EMIs and PIs on the accounts designed to safeguard client funds as the accounts of safeguarding of client funds in almost all credit institutions are not accessed via PSD2 API interfaces only because they are not classified as the payment accounts;

    Currently, credit institutions are investing and creating premium API interfaces on the market used for the AISPs to receive relevant information for an additional fee. It is estimated that such Premium API interfaces will emerge on the market in the second half of 2021; 

    This feasibility study may be continued having updated and supplemented information and having formed a joint working group from several divisions of FMSS. For this purpose, additional actions are suggested: (a) submit a question to the EBA Q&A and request that it drafts an explanation as to whether the accounts of safeguarding of client funds should be treated as the payment accounts and be accessed via PSD2 API interfaces; (b) monitor the changes undergoing on the market; (c) develop the position of the Bank of Lithuania or interpretation for FMPs based on the response received from the EBA so that they know exactly which accounts should be accessed via PSD2 API interfaces.

    This feasibility study presents the conclusions and recommendations on further actions of the Bank of Lithuania to ensure that both the Bank of Lithuania and FMPs are properly prepared for the application of the AIS service so that data needed for supervision are received, processed and analysed.

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

No 92
2021-07-30

Firm Heterogeneity, Variable Markups, and Multinational Production: A Review from Trade Policy Perspective

  • Abstract

    This paper surveys the main ingredients and results of heterogeneous firms trade policy literature that has been developing since the early 2000s. First, I present the stylized facts regarding firm heterogeneity, firmlevel markups, and multinational production’s global structure. I then survey the trade policy papers that build on the workhorse model of firm heterogeneity. Third, I summarize the recent development of theoretical approaches of modeling the firm-level markups and its trade policy implication. Fourth, I discuss the theoretical frameworks that incorporate multinational production into heterogeneous firms’ framework and their trade policy implication. Finally, I discuss directions for future research and offer suggestions for further readings.

    Keywords: Trade policy, Firm heterogeneity, Variable markups, Multinational production.

    JEL codes: F12, F13, F23, F60.

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

No 91
2021-07-29

The Factor Analytical Approach in Trending Near Unit Root Panels

  • Abstract

    In this study, we re-visit the factor analytical (FA) approach for (near unit root) dynamic panel data models, whose asymptotic distribution has been shown to be normal and well centered at zero without the need for valid instruments or correction for bias. It is therefore very appealing. The question is: Does the appeal of FA, which so far has only been documented for fixed effects panels, extends to panels with incidental trends? This is an important question, because many persistent variables are trending. The answer turns out to be negative. In particular, while consistent, the asymptotic normality of FA breaks down when there is an exact unit root present, which limits its applicability.

    Keywords: Dynamic panel data models, Unit root, Factor analytical method

    JEL codes: C12, C13, C33

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

No 38
2021-07-22

Non price competitiveness of Lithuanian exports

  • Abstract

    Foreign trade accounts for a significant part of Lithuania’s economy and the growth of export volumes is a common occurrence in Lithuania, even with rapidly growing wages. With a growth in Lithuania’s exports, the share of exports is also increasing. This indicates that Lithuanian-origin goods and services are competitive in the international market. The competitiveness of Lithuanian-origin exports may be of two kinds: based on the price and costs and based on other, non-price, factors. This article examines two methods of exports competitiveness calculation. When examining exports competitiveness based on the first method, standard formulation for the export equation, regressions are drawn up where exports growth is a dependent variable, whereas demand and the real effective exchange rates (reflecting the impact of prices and costs) are independent variables. Residual variance (i.e. random value) is seen as non-price factors that influence exports growth. When examining exports competitiveness based on the second method, exports of goods are analysed more closely, broken down into four competitiveness groups. The results indicate that the competitiveness of Lithuanian-origin exports in 2001-2019 was essentially determined by factors other than price or costs. In other words, the labour cost growth experienced by exporters is not a key factor that influences the competitiveness of Lithuanian-origin exports.

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


    Available only in Lithuanian

No 37
2021-05-24

Joint Debt Arrangements in EMU: From NextGenEU to Eurobonds

  • Abstract

    EU’s landmark Next Generation EU programme is an important step forward in both European crisis response and, more generally, EMU deepening, given that the package features elements of both joint debt issuance and fiscal transfers. This paper analyses the programme in comparison to other most prominent joint EMU debt proposals and provides a comparative Scoreboard of the arrangements discussed. It concludes that Next Generation EU falls short of filling in key gaps in the current architecture of the EMU – in particular, the gap laid bare by the lack of a genuine European safe asset. A true “safe haven” instrument – a Eurobond with joint and several guarantees – could move the EMU into a closer alignment with the Optimum Currency Area (OCA) criteria and help compensate for the macroeconomic intra-euro area imbalances. The guarantee structure of the Eurobond, working as an insurance mechanism for Member States’ sovereign debt, would allow for joint debt to significantly strengthen the euro area’s macroeconomic and market stability, the financial sector, or the international role of the Euro. However, issuance of the Eurobond is associated with important moral hazard, political and legal risks, and would most of all require an unprecedented level of trust by Member States.

    The views expressed are those of the authors and do not necessarily represent those of the Bank of Lithuania.

     

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