Latin American Journal of Central Banking最新文献

Large banks and critical financial market infrastructures (FMIs) that are not able to fulfill their payment obligations, for example following a bankruptcy or cyber-attack, can be a source of financial instability and contagion in the financial system. This paper develops a composite risk indicator to evaluate the criticality of participants in a large value payment system network, combining liquidity risk (i.e. size of incoming and outgoing payments) and systemic impact or interconnections between network participants in one approach. It is applied, as a proof of concept, to the TARGET2 payment system that links banks and FMIs in a tight network of interdependencies. We find that the most critical participants in TARGET2 are other payment systems (large value and retail) because of the underlying gross size of their payment flows. Some banks may be critical, but this is mainly due to their interconnectedness with other TARGET2 participants. Central counterparties and central securities depositories are less critical to the payment system. Our findings can be used by (1) financial stability experts to evaluate the impact of a failing critical participant in the financial system, and (2) central banks in their role as payment system operator and overseer. Besides, it feeds into policy discussions on payment system access, oversight, and crisis management.

This paper evaluates the macroeconomic effects of monetary policy for a central bank digital currency rule with traditional monetary policy in an open environment. We build a dynamic stochastic general equilibrium small open model economy with interest-bearing central bank digital currency assets. The redistribution of asset holdings and the change in asset price are the two pathways through which a retail central bank digital currency rule under the traditional monetary policy affects the macroeconomy. Fiat's digital and traditional monetary policies complement one another in lowering macroeconomic fluctuations. As a result, the real exchange rate, current accounts, and consumption are more stable in transmitting foreign shocks. These results occur when price-based or quantitative-based fiat digital monetary policy parallels traditional price-based monetary policy.

We contribute new empirical evidence on monetary policy communication and inflation expectations by firms. First, we construct a new indicator of the perceived tone of monetary policy communication that complements traditional indicators of the effective tone. Both have the expected negative sign and are statistically significant in panel data regressions with firms’ inflation expectations as the dependent variable, suggesting that communication has an important effect over inflation expectations. We also compute readability and perspicuity indicators of the communications. Better readability of monetary policy communication reinforces the effect of the tone. Impact is larger when combined with the indicator of effective tone, suggesting that readability is an important component in monetary policy communication.

The Central Bank uses press releases after board meetings for at least three purposes: first, to justify policy measures based on the economic situation; second, to provide some forward guidance signals to agents; and third, to supply some further (latent) information to the markets. This article involves a reading analysis of press releases based on a machine-learning technique to show, first, the coherence between communications and the changes of the interest rate and, second, the capacity of communications to alter inflation expectations. We find that, following the official mandate of the Central Bank, inflation and inflation expectations as well as economic activity were significant topics in the adoption of policy measures between September 2004 and March 2016, with more emphasis on the former. Our indicators of forward guidance are not significant in the adoption of contemporary policy measures. Finally, with the help of latent semantic analysis, we extract the underlying factors that are then used in structural VAR models to identify and measure the impact of press releases’ shocks on inflation expectations. Our results indicate that Colombia's Central Bank uses communications as a monetary policy tool and that this strategy influences market inflation expectations.

There is no unifying framework for evaluating core inflation measures, so we propose a methodological framework to close this gap. It allows us to construct, evaluate, and rank core inflation measures by applying it to countries and regions with different characteristics, such as Chile, Colombia, Peru, the euro area, and the United States. Our methodology uses highly disaggregated data of consumer price indexes, and hinges on a standard quadratic loss function. We show that the usual indicator that excludes food and energy, which is the most widespread measure of core inflation among central banks, performs poorly across the five countries analyzed, due to substantial bias, low persistence, high volatility, and low forecasting power. Therefore, our recommendation is to revise its use. By optimally selecting the CPI components to be excluded, the properties of core inflation measures can be significantly improved. Finally, we argue that when there is a preference regarding the use of fixed exclusion measures, nothing is lost and much can be gained by optimally selecting the excluded items, instead of sticking with the usual ad hoc criteria of excluding food and energy. Results remain robust to changes in the sample and methodology.

This paper provides several estimates of the GARCH models’ parameters for the S&P500 index, based on returns and CBOE VIX. Using a daily sample collected from 2007 to 2022, we can conclude that adding the VIX information improves the estimates of the long-term volatility. By providing an external validation of the model using an option-based index reported by the Federal Reserve of Minneapolis, we are able to propose a calibrate model to track the tail-risk of this stock index.

We developed a dynamic stochastic general equilibrium (DSGE) model for a small, open economy with a banking sector and endogenous default to assess two macroprudential tools: countercyclical capital buffers (CCB) and dynamic provisions (DP). The model is estimated with data for Uruguay, where dynamic provisioning has existed since the early 2000s. Both tools force banks to build buffers, but DP seem to outperform the CCB in smoothing the cycle. We also find that the source of the shock affecting the financial system matters in assessing the relative performance of both tools. Given a positive external shock, the credit-to-GDP ratio decreases, which should discourage its use as an indicator variable to activate countercyclical regulation.

In this paper, we develop a structural model to estimate the current level of the natural rate for a small open economy, featuring a rich set of shocks to provide economic intuition for its underlying drivers. The model follows the New Keynesian tradition with several frictions and is able to draw implications for a monetary policy stance. In contrast to other DSGE models in the literature, this framework includes two main blocks—one related to the foreign sector and one associated with the local economy, linked by the uncovered interest rate parity condition. With this structure, the natural rate is affected by local and external factors, disaggregated in permanent and transitory shocks. Using Bayesian techniques, the model estimates the natural interest rate for two example cases, Mexico and Canada, considering data from these economies and the United States. Results show that the US economy is relevant to explaining natural rates in both countries. For the Mexican case, the drivers are shocks to the US risk premium and the marginal efficiency of investment, as well as country risk premium variations. For Canada, shocks to the households’ discount factor play an important role.

The adoption of inflation-targeting regimes has led central banks to devote considerable efforts to improve their transparency. Following this trend, several authors have developed tools to measure and compare the levels of transparency of central banks. This paper undertakes this task for the Central Bank of Uruguay by applying two different transparency indexes. The first one was designed in the mid-2000s and has been applied in a sample with a significant number of countries. The second index is based on a new approach that seeks to reflect the best practices of the most advanced inflation-forecast-targeting regimes.

In this paper, we focus on the pass-through of exchange rate fluctuations into prices of final goods and services and examine whether contrasting pass-through rates are associated with regional and/or product-specific characteristics. Using CPI micro-data from 2002 to 2010, we estimate industry-specific rates of pass-through across regions in Mexico. By looking at within-country price responses, we alleviate shortcomings of cross-country studies that assess pass-through determinants. The results indicate that pass-through rates differ across regions and industries: low pass-through regions exhibit nearly one-quarter of the elasticity shown by high pass-through regions after twelve months. This heterogeneity prevails at longer horizons. The findings suggest that full pass-through is rejected for all regions and industries. Most of these differences in transmission rates are explained by regional and product characteristics: demand conditions, economic development, distance to the US border, import intensity, price change dispersion and expenditure share play a clear role in increasing pass-through, whereas market density dampens pass-through rates. The evidence confirms pricing-to-market theories and has implications for the design of monetary and exchange rate policies.