Latin American Journal of Central Banking最新文献

Distributed ledger technologies (DLT) are increasingly considered to enhance payment systems’ and market infrastructures’ functionalities like their accessibility and interoperability. We explore DLT architecture options to enable a new tiered access in the RTGS system of Chile for new payment service providers (PSP). We find that by introducing decentralized apps (DApps) the RTGS system would become more accessible and interoperable by enabling a tiered access to new participants. Our work also suggests that central banks exploring design alternatives for retail Central Bank Digital Currencies (CBDC) could find relevant our approach as a pivot to build a far-reaching PSP network.

COVID-19 has proven to be a unique and complex shock for firms. In this paper we analyze the performance of individual Chilean firms during this episode drawing on administrative datasets. In particular we empirically characterize the international trade adjustment at the firm and product level. Importer firms, specially in the manufacturing sector, have adjusted their import flow through three margins along 2020/21. In 2020 imports declined as some firms either stopped their import activity, or they imported less product varieties (product and country of origin) or by reducing the intensity of imported varieties. In this period importers faced a short-lived increase in imported input costs. In 2021 imports rebound strongly. While exporter firms (excluding mining) kept their export activity as well as their selling price stable. We also explore if foreign factors such as the incidence of COVID-19 and containment measures in partner countries had an impact on Chilean trade during 2020. We find that these foreign factors had an impact on intermediate rather than consumption goods imports.

This paper provides the first steps towards a theoretical and structural modelling framework through which optimal decision making in financial market infrastructures such as payments clearing and settlement systems can be assessed from a market microstructure perspective. In particular, the paper focuses on the application of agent-based computational economics and stochastic games in modelling the bilateral credit limit establishing behaviour of Participants in loss sharing arrangements within financial market infrastructures such as the Canadian Large Value Payments System (LVTS). With specific focus on the LVTS, the paper presents a structural model where the payments system represents a market in which bilateral credit limits are the pricing mechanisms for intraday liquidity provisioning and the credit risk arising from the loss sharing arrangement. The data-driven stochastic game framework further illustrates how payments data, in conjunction with other financial market and credit data, can be used to assess emergent macroscopic outcomes in clearing and settlement systems from the underpinning interactions of autonomous decision making agents. The paper speaks to potential policy issues such as the effectiveness of policy levers such as the System-Wide Percentage, regulatory concerns around procyclicality and free-riding arising from the market microstructure behaviours, and design of the System.

This paper examines the impact of fiscal and monetary policies on carbon dioxide emissions in Trinidad and Tobago, using data from 1970 to 2020. We use a fiscal policy index based on government revenue and expenditure, a monetary policy index based on interest rates and reserve requirement data, and a Non-linear Autoregressive Distributed Lag technique. Our results show that expansionary fiscal policy raises emissions, while contractionary fiscal policy reduces emissions. Intriguingly, expansionary monetary policy increases emissions, while contractionary monetary policy lowers them. These findings hold significance for fiscal and monetary policymakers working on climate change mitigation strategies.

This paper analyzes the contribution of supply, demand, and labor market shocks, to the evolution of regional production and inflation of manufactured goods in Mexico within the context of the pandemic. Under the identification of a Bayesian Structural Vector Autoregressive (SBVAR) model with zero and sign restrictions, it is found that since 2021, external demand shocks increased their contribution relative to local shocks in explaining the growth of manufactured goods production in all regions except the South; meanwhile, external supply shocks increased their positive contribution in explaining inflationary pressures across all regions. On the other hand, from 2022 onwards, labor supply shocks have contributed to the production and inflation of manufactured goods mainly in the Northern and North-Central regions, while wage bargaining shocks have emerged as drivers of inflationary pressures in all regions.

Colombia is particularly affected by the El Niño Southern Oscillation (ENSO) weather fluctuations. In this context, this study explores how adverse weather events linked to ENSO affect inflation expectations in Colombia and how to incorporate these second-round effects into a small open economy New Keynesian model. Using BVARx models, we find evidence that inflation expectations – obtained from surveys and break-even inflation measures – are influenced by weather-related supply shocks. Building on this stylized fact, we modify one of the core forecasting models of the Banco de la República to incorporate the mechanisms through which weather-related shocks could affect marginal costs and inflation expectations. We conclude that ENSO shocks play a significant role in influencing both inflation and the dynamics of inflation expectations, a fact that should be considered by policymakers.

This paper documents the recent changes in the structure and estimation procedures of the SAMBA model, providing a complete description of the decision problems that each economic agent faces, the first order conditions that solve those problems, and the new techniques employed to estimate the model. This updated version of the model incorporates new features, such as involuntary unemployment, imported goods in the consumption bundle and a new identified vector auto-regressive process for the rest of the world. Reflecting these changes, the set of observables was expanded to include, for instance, participation rates in the labor market and an exogenous measure of output gap. In face of increased complexity and the large number of observables, the model was estimated using Sequential Monte Carlo (SMC) methods, allowing for a smaller sensitivity to the choice of priors.

This paper examines the effects of job loss on workers. Using detailed administrative data from Costa Rica, we use a clustering algorithm to group workers into types based on their employment stability and job search efficiency. Our results show that job displacement leads to persistent earning losses for workers, particularly during economic downturns such as the COVID-19 pandemic. Displaced workers during the pandemic are moving to more productive and higher-paying firms, especially those types with initially higher earnings potentials and stable employment histories. Nonetheless, these workers are also shifting to lower-paying occupations. The findings suggest that changes in job characteristics rather than employer characteristics should be considered to explain earning losses and labor reallocation in the aftermath of the pandemic.

The Central Banks use diffusion indexes ($DIs$) to synthesize information from proprietary surveys that complement official statistics generating real-time proxies of the economically relevant variables. According to the evidence, the $DIs$ closely follow the economic cycle reflected in those official statistics. In this paper, we calculate diffusion indexes to summarize relevant qualitative information on the economic situation of the firms participating in the Survey of Business Economic Perspectives collected by the Argentinean Central Bank [Banco Central de la República Argentina (BCRA)] and we evaluate their ability to track economic activity in real-time. The indexes are analyzed for the 2017–2022 period, a particularly volatile business cycle for Argentina and (given the impact of Covid-19) for the global economy. Using the qualitative data from the firms we calculate (i) the marginal diffusion index ($MDI$) proposed by the Federal Reserve Bank of Chicago (FRB-Chicago) and based on the balance of answers corrected by the averaged participant response and, (ii) the marginal fixed diffusion index ($MFDI$), a real-time variation of the latter. To contrast and validate the indexes’ ability to summarize relevant information we introduce an econometric procedure aimed at assessing their relationships with official economic activity indicators. The results indicate that the $DIs$ calculated with the qualitative BCRA’s Survey information closely track and even anticipate the behavior of other official activity indicators both for the entire sample of firms and for the industrial sector.

In this paper, we analyse the appropriate capital adequacy ratio for banks from a socio-economic perspective. More equity capital in banks can contribute to financial stability by reducing the risk of costly banking crises, but lending may become more expensive if banks are required finance their assets with more equity. When assessing optimal capital adequacy ratios, the economic costs of more expensive credit must therefore be weighed against the benefits of fewer and less costly banking crises. Importantly, we compute optimal capital adequacy ratios for Norway which allows us to take into account recent changes in bank capital regulation. The results indicate that banks should have a Common Equity Tier 1 (CET1) ratio of between 12 and 19 percent. The current CET1 ratio of around 18 percent in our sample is in line with this. Our estimates are consistent with results from international studies, but estimates vary considerably with changes in uncertain assumptions. However, banks’ capital needs during the Nordic banking crisis in the beginning of the 1990s show that such estimates are not unreasonable.