|
on Transition Economics |
| By: | Pierre Monnin (Council on Economic Policies and Centre for Economic Transition Expertise); à dám Banai (Magyar Nemzeti Bank); KristÄ«na BojÄ re (Latvijas Banka); Ján Klacso (National Bank of Slovakia); Reiner Martin (National Bank of Slovakia); János Szakács (Magyar Nemzeti Bank) |
| Abstract: | In this paper, we explore how borrower-based measures (BBMs) can be adjusted to provide additional funding for housing-related energy-efficiency investments without compromising financial stability objectives. We first show that lower energy costs and higher house price values resulting from renovation work allows an easing of borrowing limits while keeping loan risk metrics unchanged. We then focus on three recent easing measures implemented in Slovakia, Hungary, and Latvia and assess their effectiveness using a bank survey. We find that these policy changes did not significantly affect banks’ credit portfolio risk profile and thus financial stability. At the same time, they did not generate a significant increase in loans for energy-efficient investments. We thus suggest combining BBM adjustments with other policy measures to improve energy-efficiency in real estate. |
| JEL: | C8 E44 E50 G21 |
| Date: | 2026–03 |
| URL: | https://d.repec.org/n?u=RePEc:svk:wpaper:1137 |
| By: | Olivier De Jonghe (European Central Bank); Konstantıns Benkovskis (Latvijas Banka); Karolis Bielskis (Bank of Lithuania); Diana Bonfim (Banco de Portugal; Católica Lisbon); Margherita Bottero (Banca d’Italia); Tamás Briglevics (Central Bank of Hungary); Martin Cesnak (Národná banka Slovenska); Mantas Dirma (Bank of Lithuania); Marina Emiris (National Bank of Belgium); Pálma Filep-Mosberger (Central Bank of Hungary); Valentin Jouvanceau (Bank of Lithuania); Nicholas Kaiser (Central Bank of Ireland); Dmitry Khametshin (Banco de España); Tibor Lalinskı (Národná banka Slovenska); Viola M. Grolmusz (Central Bank of Hungary); Laura Moretti (Central Bank of Ireland); Arturs Janis Nikitins (Latvijas Banka); Angelo Nunnari (Banca d’Italia); Maria Rodriguez-Moreno (Banco de España); Elitsa Stefanova (European Central Bank); Lajos Tamás Szabó (Central Bank of Hungary); Karlis Vilerts (Latvijas Banka); Sujiao Emma Zhao (Banco de Portugal) |
| Abstract: | We study heterogeneity in households’ credit across nine European countries (Belgium, Spain, Hungary, Ireland, Italy, Latvia, Lithuania, Portugal, and Slovakia) during 2022-2024 using granular credit register data. We first document substantial between- and withincountry variation in mortgage and consumer lending by borrower age, loan maturity, and interest rate fixation. We then quantify the pass-through of the ECB’s recent tightening cycle to household borrowing costs, and assess its heterogeneous impact across households. Pass-through is nearly complete for mortgages (around 0.9) but considerably weaker for consumer credit (around 0.4). While mortgage pass-through is relatively homogeneous across countries, consumer credit shows pronounced cross-country differences that cannot be explained by borrower or loan characteristics. Younger households face stronger mortgage pass-through but weaker consumer credit pass-through relative to older borrowers, and longer maturities areassociated with stronger pass-through in both credit markets. |
| JEL: | E52 G21 D14 |
| Date: | 2025–11 |
| URL: | https://d.repec.org/n?u=RePEc:svk:wpaper:1131 |
| By: | Lea Gogová (Národná banka Slovenska); Juraj Hledik (Joint Research Centre); Ján Klacso (Národná banka Slovenska) |
| Abstract: | Climate change is expected to lead to more frequent and intense extreme weather events, such as floods and droughts, which in turn increase physical risks. In this paper, we assess the direct exposure of Slovak banks’ corporate loan portfolios to riverine flood risk. We propose several monitoring metrics and estimate exposures at risk due to riverine flood-ing. Our analysis leverages a comprehensive dataset that integrates flood risk maps from the European Commission’s Joint Research Centre, cadastral data on firm properties, credit register data, and firms’ financial statements. While a significant share of firms are located in flood-prone areas, only a subset are likely to face flood levels that exceed critical thresh-olds. Consequently, the direct impact of riverine flooding on corporate credit risk appears to be relatively moderate — with the estimated increase of exposure at default ranging from 2 to 10 basis points of the corporate loan portfolio under standard scenarios, and up to 50–60 basis points in conservative stress cases accounting for asset value declines. Under coun-terfactual scenarios assuming a fivefold increase in the frequency of floods, the estimated increase exceeds 1 percentage point of the loan portfolio. |
| JEL: | G21 Q54 R30 |
| Date: | 2025–10 |
| URL: | https://d.repec.org/n?u=RePEc:svk:wpaper:1130 |
| By: | Ales Marsal (National Bank of Slovakia); Patryk Perkowski (Yeshiva University) |
| Abstract: | We examine how generative AI impacts productivity across the task-based framework using a field experiment at the National Bank of Slovakia. In our experiment, we randomly assign generative AI access to central bank employees completing workplace tasks that mirror the theoretical task-based framework. Our results indicate that generative AI access leads to large improvements in both quality and efficiency for the majority of participants. We find a strong complementarity between generative AI and non-routine work, both on average and for most participants. We also find some support for generative AI as both cognitive-biased and specialist-biased, though smaller in magnitude than our tests of routine-biased. While workers in routine jobs experience larger individual performance gains, generative AI is less effective for the routine task content of their work. The mismatch between generative AI’s task- versus worker-level impacts is economically large, and results from a simulation exercise suggest the organization can increase output by 7.3% by changing how workers are assigned to tasks in the presence of generative AI. Additionally, we find differences in how the benefits of generative AI relate to worker skills: low-skill workers benefitmost in terms of quality while high-skill workers benefit in terms of efficiency. Our findings provide empirical support on generative AI and task-level complementarities, with important implications for how generative AI will impact workers, organizations, and labor markets more broadly. |
| JEL: | J24 M15 E58 C93 O33 |
| Date: | 2025–07 |
| URL: | https://d.repec.org/n?u=RePEc:svk:wpaper:1128 |
| By: | Hantsiak, Mykhailo |
| Abstract: | In Ukraine, the debt crisis has intensified, manifested in the growth of public liabilities, an expanding budget deficit, and increasing pressure on public finances. Limited domestic funding sources compel the state to actively borrow on the debt market, exceeding safe limits and heightening insolvency risks. Under these conditions, debt restructuring emerges as a key tool to prevent financial destabilization. Global experience provides insights into effective mechanisms that can be adapted to Ukraine’s realities to restore debt sustainability. The purpose of the study is to outline the key principles for implementing sovereign debt restructuring mechanisms, with a focus on global experience, to develop recommendations for their successful application in Ukraine. The study is based on official statistical data from Ukraine and international financial institutions, scientific publications, analytical reports, and examples of global debt restructuring cases. Methods of analysis and synthesis, comparative and statistical analysis, graphical methods, and the case study approach were employed to identify trends and assess the effectiveness of debt mechanisms. The necessity of restructuring as a key tool for stabilizing public finances has been substantiated. The effectiveness of restructuring mechanisms has been shown to depend on the depth of changes to debt conditions and coordination with creditors. Emphasis has been placed on the role of comprehensive reforms and fiscal consolidation. A comparison of global cases of successful and unsuccessful restructurings has been conducted. The main tools and approaches to their implementation have been systematized. The conclusion has been drawn on the advisability of adapting the best international practices to Ukraine’s conditions. Sovereign debt restructuring is a crucial tool for reducing debt burden and restoring financial stability, but its effectiveness depends on a comprehensive approach, coordination with creditors, and accompanying economic reforms. Global experience highlights the advisability of combining various mechanisms and implementing innovative tools. For Ukraine, the key lies in adapting the best international practices to national conditions and maintaining systematic dialogue with creditors to enhance debt sustainability. |
| Keywords: | restructuring, sovereign debt, financial instruments, government borrowings, debt sustainability, debt security, debt crisis |
| JEL: | E62 F30 F34 G38 H63 |
| Date: | 2025–09–08 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127547 |
| By: | Verheliuk, Yuliia |
| Abstract: | State-guaranteed debt arises from borrowings by economic entities for the implementation of infrastructure projects under state guarantees, which offers advantages provided there is effective control and minimal corruption risks. However, the imperfection of Ukraine’s practice in managing guaranteed debt leads to an increase in residents’ indebtedness, which transforms into guaranteed debt, while a significant portion of projects remains unimplemented, highlighting the need for improving the monitoring system. To assess the role of state-guaranteed debt within Ukraine’s system of obligations, with an emphasis on the challenges of managing and providing state guarantees. The research is based on a normative analysis of the legislative framework, statistical methods for assessing trends in guaranteed debt, and theoretical methods for generalizing the fundamental principles of managing guaranteed debt and the process of providing state guarantees. State-guaranteed debt constitutes a contingent liability that arises due to the inability of residents to fulfill debt obligations obtained under state guarantees. The absence of a clear methodology for assessing the creditworthiness of economic entities, a specialized management body, and transparent project selection procedures increases corruption risks and threatens debt security. International experience confirms that ineffective management of guaranteed debt leads to a crowding-out effect on investments, hindering economic development. Inadequate control over the use of loans exacerbates the financial burden on the state budget. This necessitates a revision of approaches to providing guarantees to ensure their effectiveness. The shortcomings in the management of guaranteed debt in Ukraine, particularly the lack of transparency and creditworthiness assessment, create fiscal risks. There is a need to improve legislation, project selection procedures, and establish a specialized body to enhance efficiency and strengthen debt security. Further research should focus on developing clear criteria for assessing borrowers’ solvency and creating a specialized body for managing guaranteed debt to reduce corruption risks and increase the effectiveness of state guarantees. |
| Keywords: | state-guaranteed debt, state guarantees, debt security, debt management, investment projects, economic development |
| JEL: | E62 F34 G38 H63 |
| Date: | 2025–08–08 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127545 |
| By: | Francesca de Nicola; Alexandros Ragoussis; Tim Schmidt-Eisenlohr; Trang Thu Tran |
| Abstract: | Letters of credit are a key trade finance instrument that covers more than 10 percent of global trade, with a notably larger role in low-and middle-income economies. Studying detailed trade data from Viet Nam, we document how letter of credit use varies with firm characteristics. We show that the probability of using a letter of credit is systematically lower for younger, smaller, and foreign-owned trading firms. Importers that are less diversified or have less trading experience are more likely to use letters of credit. Firm characteristics have the strongest effects in markets where information is scarce and enforcement is weak. These patterns are consistent with a model in which the ability to screen trading partners and the cost of bank intermediation vary with firm characteristics, and where a firm’s screening ability and country institutions are substitutes. Any policy or intervention that aims at increasing the use of bank-intermediated trade finance will therefore need to take firm heterogeneity into account. |
| Keywords: | international trade, trade finance, letter-of-credit, firms, development |
| JEL: | F14 F34 O16 |
| Date: | 2026 |
| URL: | https://d.repec.org/n?u=RePEc:ces:ceswps:_12524 |
| By: | Bell, Peter |
| Abstract: | This paper presents a statistical analysis of the global database of Volcanogenic Massive Sulphide (VMS) mineral deposits. The paper shows the joint and partial probability distributions for copper equivalent grade and total tonnage based on current metals prices for copper, zinc, lead, and gold. The article develops a new method using the joint distribution to identify the set of quantile values for grade and tonnage that have approximately 50% probability; this set of quantile values represents the median grade-tonnage curve for VMS deposits around the world. The article also shows how to analyze individual projects in comparison with the global database. For example, the size of the Shamlugskoe mine in Armenia is ranked according to the global database. For another example, a model of the exploration project called Mount Sicker is presented and compared to nearby projects that are in the global database. |
| Keywords: | Natural Resources, Mining, Copper, Zinc, Volcanogenic Massive Sulphide, Metals Grade, Deposit Tonnage, Grade-Tonnage Curve, Probability Distribution, Median Path, Statistical Analysis, Simulation, Quantile |
| JEL: | A1 A19 B5 B59 C0 C02 C1 C14 C15 C18 C4 C40 C6 C63 C69 C8 C81 D2 D8 D81 G1 G17 G3 G31 H2 H25 K2 K23 L2 L5 L7 L72 Q3 Q32 Q33 Q5 Y1 |
| Date: | 2026–01–01 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127617 |
| By: | Zachary Bleemer |
| Abstract: | The Vietnam draft conscripted hundreds of thousands of young Americans into an integrated military. I combine near-random draft lottery variation with administrative voter data to study the long-run racial integration effects of coerced national service. Black and Native American veterans became more likely to marry white spouses, identify as Republicans, and live in more-integrated neighborhoods. Improved economic standing may partly mediate these effects. Effects are larger for Southerners and are precisely null for white veterans. Coerced military service generates substantial but asymmetric cross-racial political convergence and racial integration: Vietnam-era service caused about 20 percent of affected cohorts' interracial marriages. |
| JEL: | H56 J12 J15 R21 |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:nbr:nberwo:34900 |
| By: | Ibrahimov, Oktay |
| Abstract: | In the emerging Artificial Intelligence–native paradigm, where algorithmic systems increasingly function as societal infrastructure, this paper develops the Cultural–Technological Synergy framework—a meso-level diagnostic model explaining how cultural conditions enable or constrain that transformation. The framework rests on four established principles: (1) shared cultural values shape the behaviour of individuals and institutions; (2) new technologies diffuse through social learning and demonstrable benefits; (3) durable systems depend on public legitimacy and consent; and (4) effective cross-institutional coordination is essential to scale pilots into operational infrastructure. Drawing on these principles, the Cultural–Technological Synergy framework elucidates how cultural dynamics influence the capacity, incentives, and legitimacy required for Artificial Intelligence to evolve from experimental applications into essential public infrastructure. While recognizing economic, technological, infrastructural, and governance drivers, the framework adds cultural, societal, and psychological dimensions—operationalized through norms, values, identities, and risk perceptions—to be measured and compared on equal footing. It defines four interacting dimensions—Heritage Adaptability, Cross-Civilizational Competence, Innovation Ethos, and Strategic Determination—that shape the progression from pilots and sectoral deployments to public infrastructure. These dimensions interface directly with the companion frameworks: AI as Public Infrastructure, which theorizes when Artificial Intelligence attains infrastructural status, and the Infrastructure Status Index, which operationalizes that status. In diagnostic use, the Cultural–Technological Synergy framework offers a lens for (i) evaluating cultural readiness, (ii) identifying bottlenecks, and (iii) supporting prioritization through analysis of how cultural factors condition capacity, incentives, and legitimacy in transitions to public infrastructure. Positioned at the meso level, the framework specifies how cultural architectures enable or constrain institutional pathways across successive phases defined by AI as Public Infrastructure and the Infrastructure Status Index. The Azerbaijan case illustrates this logic—explaining ambition formation, legitimacy dynamics, and early coordination gains. |
| Keywords: | Cultural–Technological Synergy (CTS); AI as Public Infrastructure (AIPI); Infrastructure Status Index (ISI); Infrastructural Transition; Transitional Societies; Culture–Institution Interaction |
| JEL: | O33 O35 O38 |
| Date: | 2025–12–15 |
| URL: | https://d.repec.org/n?u=RePEc:pra:mprapa:127612 |
| By: | Fabbri Emanuele (European Commission - JRC); Innocenti Niccolò; Bole Domen; Šćepanović Biljana; Rakčević Balša; Vojinović Ivana; Jabučanin Boris; Latinović Nedeljko; Kojić Jovana; Radulović Valentina; Laušević-odalović Maja; Morić Ilija; Zvizdojević Jelena; Nikolić Ratko; Vujičić Savica; Fabbri Emanuele (European Commission - JRC); Janković Mijanović Ivana |
| Abstract: | The Smart Specialisation Strategy (S3) is a place-based economic agenda that Montenegro, as the first non-EU country to adopt a strategy based on this framework, is now updating for the 2026–2031 period. This new iteration elevates S3 to a national ‘umbrella’ strategy, utilizing comprehensive quantitative and qualitative mapping to identify the country’s economic, scientific, and innovative strengths. The resulting report serves as an analytical foundation for the upcoming Entrepreneurial Discovery Process (EDP), where stakeholders collaborate to finalize Montenegro’s strategic priority domains. The analysis identifies five preliminary priority areas for Montenegro’s 2026–2031 S3 strategy: Construction, Energy and Sustainable Environment, Sustainable Agriculture and Food, Digital Innovation and Transformation, and Innovative and Sustainable Tourism. While sectors like Construction and Energy are highlighted for their roles in infrastructure and green transitions, the ICT and Tourism sectors stand out as high-growth pillars, contributing significantly to GDP and export potential. |
| Date: | 2026–02 |
| URL: | https://d.repec.org/n?u=RePEc:ipt:iptwpa:jrc145542 |