Marcel Ribeiro

Central banks operating under inflation targeting often adopt gradual disinflationary policies. This paper studies the trade-offs between “Cold Turkey” (CT) and gradual disinflations using a New Keynesian model with imperfect credibility regarding the inflation target. In the baseline calibration, agents slowly learn about the target in both policies, which dampens inflation expectations decline. As a result, inflation is closer to the target under the gradual policy, allowing a relatively looser monetary policy and lower disinflation costs. CT is preferred when credibility is sufficiently high to promote a strong response of inflation expectations, as agents learn faster the immediate target decline. 

What are the macroeconomic implications of informational frictions in a quantitative business cycle model? We develop a general solution method that allows enriching a standard medium-scale DSGE model with dispersed information. We estimate the model, incorporating comprehensive macroeconomic and expectation data, and revisit crucial questions about business cycles. Expectation data identifies strong informational frictions, which dampen general equilibrium effects and change the relative importance of various shocks in driving business cycles. We find that informational frictions complement standard inertial frictions rather than being alternatives. The former is crucial for generating sluggishness in inflation, whereas the latter is important for inertia in real macroeconomic aggregates.

A standard assumption in imperfect and common information models is that information is complete, allowing agents to know all current endogenous variables. In contrast, strategic uncertainty prevents the inference of aggregate variables in models with heterogeneous information. This paper studies the limiting case of a model with exogenous heterogeneous information, where private signals become arbitrarily imprecise and strategic uncertainty is vanishing small. In this limit, agents form expectations and make optimal decisions homogeneously, without relying on information from aggregate variables. This restriction alters equilibrium conditions and the learning process about shocks, leading to a markedly different equilibrium.

The assumption of complete information introduces an unintended consequence: because agents are certain about each other's actions, they can infer aggregate variables and use them to learn about unobserved shocks. The limiting case removes this implicit consequence without introducing the additional complexity of higher-order expectations.

This limiting case can be implemented using standard solution methods with partial information, provided that aggregate variables are excluded from agents' information sets. These findings underscore the importance of transparency in agents' information set choices.

Esse artigo agrupa os setores da economia brasileira durante a pandemia de COVID-19 em setores afetados diretamente e indiretamente. Com base em modelo RBC calibrado com dois setores, compara-se as funções resposta ao impulso dos choques setoriais de demanda, produtividade e desutilidade do trabalho com a trajetória dos dados setoriais de produção, emprego e salários pós-COVID. Os resultados sugerem que o choque setorial na produtividade é o que melhor se captura a dinâmica dos dados. Adicionalmente, verifica-se que a inclusão de capital no modelo, relaxa as condições para a ocorrência de um choque de oferta keynesiano. 

This article presents a simple macroeconomic model where government spending affects aggregate demand directly and indirectly, through an expectational channel. Prices are fully flexible and the model is static, so intertemporal issues play no role. There are three important elements in the model: (i) fixed adjustment costs for investment, which create an inaction zone; (ii) noisy idiosyncratic information about the aggregate economy; and (iii) imperfect substitution among private goods and goods provided by the government. An increase in government spending raises demand for private goods and may prevent a coordination failure. The optimal level of government expenditure is high when the desired level of investment is low, which we interpret as a time of low economic activity. 

Informality is a major issue in Latin America and the Caribbean (LAC). The literature estimating its size has been primarily limited to worldwide models applied to the region. This paper proposes a Multiple Indicators Multiple Causes (MIMIC) model using a dataset composed of 41 countries in LAC. The model introduces income inequality and total factor productivity in addition to traditional variables. The results indicate that income inequality is a key determinant of IE, both in terms of statistical significance and measurement. When compared to a model using data from 188 countries, some causal variables have an impact ten times higher on the level of informality, highlighting the importance of tailored data set selection when modeling IE with MIMIC. 

This article explores new tools for the ex-ante analysis of PTAs using large scale CGE models. The traditional impact analysis based on tariff cuts and gross trade performance is then extended to incorporate new features of the ongoing globalization process, such as non-tariff barriers (NTBs) and the so-called trade in value-added. Several methodological as well as conceptual issues are then readdressed, including the proper use of estimated ad-valorem equivalents of NTBs as inputs in perfect competition CGE models as well as the very concept of a “preferential trade partner” in a world where nearly 65% of global exports correspond to trade in intermediates. The article concentrates its impact analysis on the Brazilian economy – providing an overview of its trade policy over the last decades- and the likely consequences of a hypothetical PTA involving Mercosur and China.  

This article proposes an alternative methodology for estimating the impacts of TBT/SPS measures on international trade, based on the recent literature of gravity models. A Heckman selection model is applied to the case of Brazilian exports, where the second stage equation is theoretically grounded on the Melitz model of heterogeneous firms. This equation highlights the role played by zero trade flows as well as firm heterogeneity, two factors usually omitted in standard specifications. Based on a simple Cournot model, a preliminary effort is made in order to elucidate the main microeconomic channels through which TBT/SPS measures may affect trade flows.