Latin American Journal of Central Banking最新文献

The return of high inflation in Latin America (and worldwide) since 2021 has renewed concerns about the persistence of above-target inflation and a potential de-anchoring of inflation expectations. This paper shows that trend inflation estimation using forward-looking information can offer important insights for the understanding of inflation dynamics and long-term inflation expectations. Our analysis for 5 large LATAM economies (Brazil, Chile, Colombia, Mexico and Peru) reveals that a large part of the high inflation observed over 2021–23 mainly reflects transitory influences, and the stability of long-term survey expectations is broadly in line with persistent inflation trends. The risk of a de-anchoring of expectations in those countries therefore seems to be limited. Our findings provide useful information for both monetary policy and market participants in LATAM countries, as well as for central banks and investors worldwide.

We study for a benchmark small open emerging economy an optimal robust monetary policy à la Hansen and Sargent (2003) considering additive model uncertainty. The robust control approach supposes that economic agents are not able to assign probabilities to a set of all plausible models and rather focuses on the worst possible misspecification from a benchmark model. Our findings are threefold. First, conducting a global robust optimal monetary policy can be limited since the departure from the benchmark model leads to multiple equilibria. Second, when model uncertainty arises only from the IS curve or the UIP condition, the space of unique solutions is expanded. In fact, when the central bank has a preference for robustness on the IS curve only, it should be more aggressive to demand and real exchange rate shocks but more conservative to cost-push shocks. On the other hand, when it has a preference for robustness only for the UIP, the central bank should be more aggressive to demand and cost-push shocks. Third, a sensitivity analysis suggests that conducting a global robust optimal monetary policy with the same misspecification in all equations is limited due to the persistence of inflation, the low exchange-rate pass-through and the need to anchor inflation expectations. Finally, we propose a Bayesian estimation for the Sidaoui and Ramos-Francia’s model over the period 2001–2019.

This paper compiles a novel and unique dataset encompassing 439 individuals who served as board members on 16 different inflation-targeting central banks’ monetary policy committees (MPCs) from 1999 to 2018. We document relevant trends over the past twenty years: (i) An increasing share of women serving on committees, albeit still a minority; (ii) an increase in the share of members with previous private sector experience and (iii) an increase in the average age and experience among members over time. Moreover, we find that: (i) A higher proportion of members with MBAs and Masters’ in economics is related to lower levels of inflation; (ii) a committee with more members with formations not in economics or law tends to be more lenient towards the monetary policy target; (iii) the average MPC age within a range of 55 and 60 years seems to be linked to less volatile inflation; and (iv) more MPC women members correlates with both lower and less volatile inflation.

It is widely accepted that episodes of social unrest, conflict, political tensions and policy uncertainty affect the economy. Nevertheless, the real-time dimension of such relationships is less studied, and it remains unclear how to incorporate them in a forecasting framework. This can be partly explained by a certain divide between the economic and political science contributions in this area, as well as the traditional lack of availability of timely high-frequency indicators measuring such phenomena. The latter constraint, though, is becoming less of a limiting factor through the production of text-based indicators. In this paper we assemble a dataset of such monthly measures of what we call “institutional instability”, for three representative emerging market economies: Brazil, Colombia and Mexico. We then forecast quarterly GDP by adding these new variables to a standard macro-forecasting model using different methods. Our results strongly suggest that capturing institutional instability above a broad set of standard high-frequency indicators is useful when forecasting quarterly GDP. We also analyse relative strengths and weaknesses of the approach.

In late 2021 and early 2022, CEMLA conducted a thorough survey involving 12 central banks to analyze key aspects related to the potential implementation of a Central Bank Digital Currency (CBDC). The findings revealed prevalent issues and objectives regarding digital payments in the region, as well as promising avenues for central bank involvement. However, it highlighted the challenges of creating a universal CBDC framework due to significant disparities among neighboring countries. Nonetheless, the collaborative research approach promises valuable insights for future efforts. To protect participant anonymity, each country’s responses were anonymized with randomly assigned letters.

The survey extensively examined awareness and understanding of CBDCs across diverse stakeholders in Latin American nations, including the general public, corporations, and financial institutions. These insights could shape educational campaigns and communication strategies, enabling policymakers and central banks to effectively share information about CBDCs.

Moreover, this research effort sheds light on public perceptions, expectations, and concerns about CBDCs in Latin America. By exploring various dimensions such as awareness, interest, adoption potential, concerns, preferences, and regulatory considerations, the survey offers a comprehensive understanding of the CBDC landscape in the region. This holistic approach provides valuable insights for policymakers, central banks, and stakeholders to navigate the complexities of CBDC implementation effectively and responsibly.

We analyze the repercussions of different kinds of uncertainty on cash demand, including uncertainty of cashless infrastructures, confidence crises of the financial system, natural disasters, political uncertainties, and inflationary crises. Based on a comprehensive literature survey and complemented by case studies, we derive a classification scheme how cash holdings typically evolved in each of these types of uncertainty over the past 30 years by separating between demand for domestic and international cash as well as between transaction and store of value balances. Hereby, we focus on the stabilizing macroeconomic properties of cash and recommend guidelines for cash supply by central banks and the banking system. Finally, we exemplify our analysis with five case studies from the developing world, namely Venezuela, Zimbabwe, Afghanistan, Iraq, and Libya.

We extend a standard multivariate filter used to estimate the Output Gap (OG) in Chile to account for large economic shocks, such as those observed during the COVID-19 crisis. We propose two methodological extensions. First, we introduce exogenous supply shocks in the dynamics of potential output growth. Second, we add “system” prior distributions on a set of characteristics of the model. We show that these extensions improve several desirable properties of Chile’s OG, such as stability, accuracy, consistency and also reduce the uncertainty surrounding the estimates. Next, we generalize our results by applying our methodology to a panel of countries, showing that the extended filter yields a tighter relationship between inflation developments and the OG, when compared to its standard counterpart.